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Distinct structural transitions of chromatin topological domains coordinate hormone-induced gene regulation

10.1101/003293

François Le Dily;Davide Baù;Andy Pohl;Guillermo P. Vicent;Daniel Soronellas;Giancarlo Castellano;François Serra;Roni H. G. Wright;Cecilia J. Ballare;Guillaume Filion;Marc A. Marti-Renom;Miguel Beato;

The human genome is segmented into Topologically Associating Domains (TADs), but the role of this conserved organization during transient changes in gene expression is not known. Here we described the distribution of Progestin-induced chromatin modifications and changes in transcriptional activity over TADs in T47D breast cancer cells. Using ChIP-Seq, Hi-C and 3D modelling techniques, we found that the borders of the [~]2,000 TADs in these cells are largely maintained after hormone treatment but that some TADs operate as discrete regulatory units in which the majority of the genes are either transcriptionally activated or repressed upon hormone stimulus. The epigenetic signatures of the TADs are coordinately modified by hormone in correlation with the transcriptional changes. Hormone-induced changes in gene activity and chromatin remodeling are accompanied by differential structural changes for activated and repressed TADs. In response to hormone activated TADs exhibit higher density of internal contacts, while repressed TADs show less intra-TAD contacts. Integrative 3D modelling revealed that TADs structurally expanded if activated and compacted when repressed, and that this is accompanied by differential changes in their global accessibility. We thus propose that TADs function as \"regulons\" to enable spatially proximal genes to be coordinately transcribed in response to hormones.

2014-03-13

Genetic influences on translation in yeast

10.1101/003319

Frank W. Albert;Dale Muzzey;Jonathan S. Weissman;Leonid Kruglyak;

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.\n\nAuthor summaryIndividuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic - it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called \"ribosome profiling\" to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.

2014-03-16

Genetic influences on translation in yeast

10.1101/003319

Frank W. Albert;Dale Muzzey;Jonathan S. Weissman;Leonid Kruglyak;

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.\n\nAuthor summaryIndividuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic - it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called \"ribosome profiling\" to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.

2014-07-17

Genetic influences on translation in yeast

10.1101/003319

Frank W. Albert;Dale Muzzey;Jonathan S. Weissman;Leonid Kruglyak;

Heritable differences in gene expression between individuals are an important source of phenotypic variation. The question of how closely the effects of genetic variation on protein levels mirror those on mRNA levels remains open. Here, we addressed this question by using ribosome profiling to examine how genetic differences between two strains of the yeast S. cerevisiae affect translation. Strain differences in translation were observed for hundreds of genes. Allele specific measurements in the diploid hybrid between the two strains revealed roughly half as many cis-acting effects on translation as were observed for mRNA levels. In both the parents and the hybrid, most effects on translation were of small magnitude, such that the direction of an mRNA difference was typically reflected in a concordant footprint difference. The relative importance of cis and trans acting variation on footprint levels was similar to that for mRNA levels. There was a tendency for translation to cause larger footprint differences than expected given the respective mRNA differences. This is in contrast to translational differences between yeast species that have been reported to more often oppose than reinforce mRNA differences. Finally, we catalogued instances of premature translation termination in the two yeast strains and also found several instances where erroneous reference gene annotations lead to apparent nonsense mutations that in fact reside outside of the translated gene body. Overall, genetic influences on translation subtly modulate gene expression differences, and translation does not create strong discrepancies between genetic influences on mRNA and protein levels.\n\nAuthor summaryIndividuals in a species differ from each other in many ways. For many traits, a fraction of this variation is genetic - it is caused by DNA sequence variants in the genome of each individual. Some of these variants influence traits by altering how much certain genes are expressed, i.e. how many mRNA and protein molecules are made in different individuals. Surprisingly, earlier work has found that the effects of genetic variants on mRNA and protein levels for the same genes appear to be very different. Many variants appeared to influence only mRNA (but not protein) levels, and vice versa. In this paper, we studied this question by using a technique called \"ribosome profiling\" to measure translation (the cellular process of reading mRNA molecules and synthesizing protein molecules) in two yeast strains. We found that the genetic differences between these two strains influence translation for hundreds of genes. Because most of these effects were small in magnitude, they explain at most a small fraction of the discrepancies between the effects of genetic variants on mRNA and protein levels.

2014-09-02

Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems

10.1101/003335

Melissa K Takahashi;James Chappell;Clarmyra A Hayes;Zachary Z Sun;Vipul Singhal;Kevin J Spring;Shaima Al-Khabouri;Christopher P Fall;Vincent Noireaux;Richard M Murray;Julius B Lucks;

RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on timescales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold response tuning. Finally we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

2014-03-17

Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems

10.1101/003335

Melissa K Takahashi;James Chappell;Clarmyra A Hayes;Zachary Z Sun;Vipul Singhal;Kevin J Spring;Shaima Al-Khabouri;Christopher P Fall;Vincent Noireaux;Richard M Murray;Julius B Lucks;

RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on timescales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold response tuning. Finally we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

2014-03-18

Measuring error rates in genomic perturbation screens: gold standards for human functional genomics

10.1101/003327

Traver Hart;Kevin R Brown;Fabrice Sircoulomb;Robert Rottapel;Jason Moffat;

Technological advancement has opened the door to systematic genetics in mammalian cells. Genome-scale loss-of-function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by offtarget effects of perturbation reagents and poorly quantified error rates in large-scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold-standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi, and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.

2014-03-17

Analysis of stop-gain and frameshift variants in human innate immunity genes

10.1101/003376

Antonio Rausell;Pejman Mohammadi;Paul J McLaren;Ioannis Xenarios;Jacques Fellay;Amalio Telenti;

Loss-of-function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies. Recent resequencing projects report that stop-gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter-individual variability in innate immune response. Current computational approaches evaluating loss-of-function in genes carrying these variants rely on gene-level characteristics such as evolutionary conservation and functional redundancy across the genome. However, innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated. To create a ranking of severity that would be applicable to the innate immunity genes we first evaluated 17764 stop-gain and 13915 frameshift variants from the NHLBI Exome Sequencing Project and 1000 Genomes Project. Sequence-based features such as loss of functional domains, isoform-specific truncation and non-sense mediated decay were found to correlate with variant allele frequency and validated with gene expression data. We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against OMIM disease stop-gains and frameshifts. The classification scheme was applied in the assessment of 335 stop-gains and 236 frameshifts affecting 227 interferon-stimulated genes. The sequence-based score ranks variants in innate immunity genes according to their potential to cause disease, and complements existing gene-based pathogenicity scores.

2014-03-17

Horizontal Transfers and Gene Losses in the phospholipid pathway of Bartonella reveal clues about early ecological niches

10.1101/003350

Qiyun Zhu;Michael Kosoy;Kevin J Olival;Katharina Dittmar;

Bartonellae are mammalian pathogens vectored by blood-feeding arthropods. Although of increasing medical importance, little is known about their ecological past, and host associations are underexplored. Previous studies suggest an influence of horizontal gene transfers in ecological niche colonization by acquisition of host pathogenicity genes. We here expand these analyses to metabolic pathways of 28 Bartonella genomes, and experimentally explore the distribution of bartonellae in 21 species of blood-feeding arthropods. Across genomes, repeated gene losses and horizontal gains in the phospholipid pathway were found. The evolutionary timing of these patterns suggests functional consequences likely leading to an early intracellular lifestyle for stem bartonellae. Comparative phylogenomic analyses discover three independent lineage-specific reacquisitions of a core metabolic gene - NAD(P)H-dependent glycerol-3-phosphate dehydrogenase (gpsA) - from Gammaproteobacteria and Epsilonproteobacteria. Transferred genes are significantly closely related to invertebrate Arsenophonus-, and Serratia-like endosymbionts, and mammalian Helicobacter-like pathogens, supporting a cellular association with arthropods and mammals at the base of extant bartonellae. Our studies suggest that the horizontal re-aquisitions had a key impact on bartonellae lineage specific ecological and functional evolution.

2014-03-17

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

10.1101/003400

Luke Stoeckel;Kathleen A. Garrison;Satrajit S Ghosh;Paul Wighton;Colleen A. Hanlon;Jodi M. Gilman;Stephanie Greer;Nicholas B. Turk-Browne;Megan T. deBettencourt;Dustin Scheinost;Cameron Craddock;Todd Thompson;Vanessa Calderon;Clemens C. Bauer;Mark George;Hans C. Breiter;Susan Whitfield-Gabrieli;John D. Gabrieli;Stephen M. LaConte;Laurence M. Hirshberg;Judson A. Brewer;Michelle Hampson;Andre Van Der Kouwe;Sean Mackey;Anne E Evins;

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

2014-03-18

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

10.1101/003400

Luke Stoeckel;Kathleen A. Garrison;Satrajit S Ghosh;Paul Wighton;Colleen A. Hanlon;Jodi M. Gilman;Stephanie Greer;Nicholas B. Turk-Browne;Megan T. deBettencourt;Dustin Scheinost;Cameron Craddock;Todd Thompson;Vanessa Calderon;Clemens C. Bauer;Mark George;Hans C. Breiter;Susan Whitfield-Gabrieli;John D. Gabrieli;Stephen M. LaConte;Laurence M. Hirshberg;Judson A. Brewer;Michelle Hampson;Andre Van Der Kouwe;Sean Mackey;Anne E Evins;

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

2014-03-19

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

10.1101/003400

Luke Stoeckel;Kathleen A. Garrison;Satrajit S Ghosh;Paul Wighton;Colleen A. Hanlon;Jodi M. Gilman;Stephanie Greer;Nicholas B. Turk-Browne;Megan T. deBettencourt;Dustin Scheinost;Cameron Craddock;Todd Thompson;Vanessa Calderon;Clemens C. Bauer;Mark George;Hans C. Breiter;Susan Whitfield-Gabrieli;John D. Gabrieli;Stephen M. LaConte;Laurence M. Hirshberg;Judson A. Brewer;Michelle Hampson;Andre Van Der Kouwe;Sean Mackey;Anne E Evins;

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

2014-03-20

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

10.1101/003400

Luke Stoeckel;Kathleen A. Garrison;Satrajit S Ghosh;Paul Wighton;Colleen A. Hanlon;Jodi M. Gilman;Stephanie Greer;Nicholas B. Turk-Browne;Megan T. deBettencourt;Dustin Scheinost;Cameron Craddock;Todd Thompson;Vanessa Calderon;Clemens C. Bauer;Mark George;Hans C. Breiter;Susan Whitfield-Gabrieli;John D. Gabrieli;Stephen M. LaConte;Laurence M. Hirshberg;Judson A. Brewer;Michelle Hampson;Andre Van Der Kouwe;Sean Mackey;Anne E Evins;

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

2014-03-21

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

10.1101/003400

Luke Stoeckel;Kathleen A. Garrison;Satrajit S Ghosh;Paul Wighton;Colleen A. Hanlon;Jodi M. Gilman;Stephanie Greer;Nicholas B. Turk-Browne;Megan T. deBettencourt;Dustin Scheinost;Cameron Craddock;Todd Thompson;Vanessa Calderon;Clemens C. Bauer;Mark George;Hans C. Breiter;Susan Whitfield-Gabrieli;John D. Gabrieli;Stephen M. LaConte;Laurence M. Hirshberg;Judson A. Brewer;Michelle Hampson;Andre Van Der Kouwe;Sean Mackey;Anne E Evins;

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

2014-04-24

Optimizing Real Time fMRI Neurofeedback for Therapeutic Discovery and Development

10.1101/003400

Luke Stoeckel;Kathleen A. Garrison;Satrajit S Ghosh;Paul Wighton;Colleen A. Hanlon;Jodi M. Gilman;Stephanie Greer;Nicholas B. Turk-Browne;Megan T. deBettencourt;Dustin Scheinost;Cameron Craddock;Todd Thompson;Vanessa Calderon;Clemens C. Bauer;Mark George;Hans C. Breiter;Susan Whitfield-Gabrieli;John D. Gabrieli;Stephen M. LaConte;Laurence M. Hirshberg;Judson A. Brewer;Michelle Hampson;Andre Van Der Kouwe;Sean Mackey;Anne E Evins;

While reducing the burden of brain disorders remains a top priority of organizations like the World Health Organization and National Institutes of Health (BRAIN, 2013), the development of novel, safe and effective treatments for brain disorders has been slow. In this paper, we describe the state of the science for an emerging technology, real time functional magnetic resonance imaging (rtfMRI) neurofeedback, in clinical neurotherapeutics. We review the scientific potential of rtfMRI and outline research strategies to optimize the development and application of rtfMRI neurofeedback as a next generation therapeutic tool. We propose that rtfMRI can be used to address a broad range of clinical problems by improving our understanding of brain-behavior relationships in order to develop more specific and effective interventions for individuals with brain disorders. We focus on the use of rtfMRI neurofeedback as a clinical neurotherapeutic tool to drive plasticity in brain function, cognition, and behavior. Our overall goal is for rtfMRI to advance personalized assessment and intervention approaches to enhance resilience and reduce morbidity by correcting maladaptive patterns of brain function in those with brain disorders.

2014-06-20

Hydrogen peroxide thermochemical oscillator as driver for primordial RNA replication

10.1101/003368

Rowena Ball;John Brindley;

This paper presents and tests a previously unrecognised mechanism for driving a replicating molecular system on the prebiotic earth. It is proposed that cell-free RNA replication in the primordial soup may have been driven by self-sustained oscillatory thermochemical reactions. To test this hypothesis a well-characterised hydrogen peroxide oscillator was chosen as the driver and complementary RNA strands with known association and melting kinetics were used as the substrate. An open flow system model for the self-consistent, coupled evolution of the temperature and concentrations in a simple autocatalytic scheme is solved numerically, and it is shown that thermochemical cycling drives replication of the RNA strands. For the (justifiably realistic) values of parameters chosen for the simulated example system, the mean amount of replicant produced at steady state is 6.56 times the input amount, given a constant supply of substrate species. The spontaneous onset of sustained thermochemical oscillations via slowly drifting parameters is demonstrated, and a scheme is given for prebiotic production of complementary RNA strands on rock surfaces.

2014-03-17

Metabolic free energy and deterministic-but-for-error biological codes: a ‘Data Rate Theorem’ aging model

10.1101/003384

Rodrick Wallace;

The living state is cognitive at every scale and level of organization. Since it is possible to associate a broad class of cognitive processes with dual information sources, many pathologies can be addressed using statistical models based on the Shannon Coding, the Shannon-McMillan Source Coding, the Rate Distortion, and the Data Rate Theorems, as these impose powerful necessary condition constraints on information generation and exchange, and on system control. Deterministic-but-for-error biological codes do not directly invoke cognition, although they may be essential subcomponents within larger cognitive processes. A formal argument, however, places such codes within a similar framework, with metabolic free energy serving as a control signal stabilizing biochemical code-and-translator dynamics in the presence of noise. Demand beyond available energy supply then expresses itself in punctuated destabilization of the coding channel, affecting a spectrum of essential biological functions. Aging, normal or prematurely driven by psychosocial or environmental stressors, must eventually interfere with the routine operation of such mechanisms, triggering chronic diseases associated with senescence. Amyloid fibril formation, intrinsically disordered protein logic gates, and cell surface glycan/lectin kelp bed logic gates are reviewed from this perspective. The results, however, generalize beyond coding systems having easily recognizable symmetry modes.

2014-03-17

Metabolic free energy and biological codes: a ‘Data Rate Theorem’ aging model

10.1101/003384

Rodrick Wallace;

The living state is cognitive at every scale and level of organization. Since it is possible to associate a broad class of cognitive processes with dual information sources, many pathologies can be addressed using statistical models based on the Shannon Coding, the Shannon-McMillan Source Coding, the Rate Distortion, and the Data Rate Theorems, as these impose powerful necessary condition constraints on information generation and exchange, and on system control. Deterministic-but-for-error biological codes do not directly invoke cognition, although they may be essential subcomponents within larger cognitive processes. A formal argument, however, places such codes within a similar framework, with metabolic free energy serving as a control signal stabilizing biochemical code-and-translator dynamics in the presence of noise. Demand beyond available energy supply then expresses itself in punctuated destabilization of the coding channel, affecting a spectrum of essential biological functions. Aging, normal or prematurely driven by psychosocial or environmental stressors, must eventually interfere with the routine operation of such mechanisms, triggering chronic diseases associated with senescence. Amyloid fibril formation, intrinsically disordered protein logic gates, and cell surface glycan/lectin kelp bed logic gates are reviewed from this perspective. The results, however, generalize beyond coding systems having easily recognizable symmetry modes.

2014-03-30

Metabolic free energy and biological codes: a ‘Data Rate Theorem’ aging model

10.1101/003384

Rodrick Wallace;

The living state is cognitive at every scale and level of organization. Since it is possible to associate a broad class of cognitive processes with dual information sources, many pathologies can be addressed using statistical models based on the Shannon Coding, the Shannon-McMillan Source Coding, the Rate Distortion, and the Data Rate Theorems, as these impose powerful necessary condition constraints on information generation and exchange, and on system control. Deterministic-but-for-error biological codes do not directly invoke cognition, although they may be essential subcomponents within larger cognitive processes. A formal argument, however, places such codes within a similar framework, with metabolic free energy serving as a control signal stabilizing biochemical code-and-translator dynamics in the presence of noise. Demand beyond available energy supply then expresses itself in punctuated destabilization of the coding channel, affecting a spectrum of essential biological functions. Aging, normal or prematurely driven by psychosocial or environmental stressors, must eventually interfere with the routine operation of such mechanisms, triggering chronic diseases associated with senescence. Amyloid fibril formation, intrinsically disordered protein logic gates, and cell surface glycan/lectin kelp bed logic gates are reviewed from this perspective. The results, however, generalize beyond coding systems having easily recognizable symmetry modes.

2014-04-23

Mpl expression on megakaryocytes and platelets is dispensable for thrombopoiesis but essential to prevent myeloproliferation

10.1101/003459

Ashley P Ng;Maria Kauppi;Donald Metcalf;Craig D Hyland;Emma C Josefsson;Marion Lebois;Jian-Guo Zhang;Ladina Di Rago;Tracey Baldwin;Douglas J Hilton;Warren S Alexander;

Thrombopoietin (TPO) acting via its receptor Mpl is the major cytokine regulator of platelet number. To precisely define the role of specific hematopoietic cells in TPO dependent hematopoiesis, we generated mice that express the Mpl receptor normally on stem/progenitor cells but lack expression on megakaryocytes and platelets (MplPF4cre/PF4cre). MplPF4cre/PF4cre mice displayed profound megakaryocytosis and thrombocytosis with a remarkable expansion of megakaryocyte-committed and multipotential progenitor cells, the latter displaying biological responses and a gene expression signature indicative of chronic TPO over-stimulation as the underlying causative mechanism, despite a normal circulating TPO level. Thus, TPO signaling in megakaryocytes is dispensable for platelet production; its key role in control of platelet number is via generation and stimulation of the bipotential megakaryocyte precursors. Nevertheless, Mpl expression on megakaryocytes and platelets is essential to prevent megakaryocytosis and myeloproliferation by restricting the amount of TPO available to stimulate the production of megakaryocytes from the progenitor cell pool.\n\nSignificance statementBlood platelets, the small circulating cells that co-ordinate hemostasis, are produced by specialized bone marrow cells called megakaryocytes. The cytokine thrombopoietin (TPO) is a key regulator of platelet production acting via its specific cell receptor, Mpl. Via genetic modification of the Mpl allele in mice, we precisely define the bone marrow cells that express Mpl and, by genetically removing Mpl from megakaryocytes and platelets, we show TPO signaling via Mpl is not required in megakaryocytes for their expansion, maturation or platelet production. Rather, Mpl expression on megakaryocytes is essential for regulating TPO availability in the bone marrow microenvironment to prevent myeloproliferation, a model we suggest is important for human disease.

2014-03-19

The Role of Migration in the Evolution of Phenotypic Switching

10.1101/003442

Oana Carja;Robert E Furrow;Marc W Feldman;

Stochastic switching is an example of phenotypic bet-hedging, where an individual can switch between different phenotypic states in a fluctuating environment. Although the evolution of stochastic switching has been studied when the environment varies temporally, there has been little theoretical work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here we use a population genetic model to explore the interaction of temporal and spatial variation in the evolutionary dynamics of phenotypic switching. We find that spatial variation in selection is important; when selection pressures are similar across space, migration can decrease the rate of switching, but when selection pressures differ spatially, increasing migration between demes can facilitate the evolution of higher rates of switching. These results may help explain the diverse array of non-genetic contributions to phenotypic variability and phenotypic inheritance observed in both wild and experimental populations.

2014-03-19

Epigenetic Modifications are Associated with Inter-species Gene Expression Variation in Primates

10.1101/003467

Xiang Zhou;Carolyn Cain;Marsha Myrthil;Noah Lewellen;Katelyn Michelini;Emily Davenport;Matthew Stephens;Jonathan Pritchard;Yoav Gilad;

Changes in gene regulation level have long been thought to play an important role in evolution and speciation, especially in primates. Over the past decade, comparative genomic studies have revealed extensive inter-species differences in gene expression levels yet we know much less about the extent to which regulatory mechanisms differ between species. To begin addressing this gap, we performed a comparative epigenetic study in primate lymphoblastoid cell lines (LCLs), to query the contribution of RNA polymerase II (Pol II) and four histone modifications (H3K4me1, H3K4me3, H3K27ac, and H3K27me3) to inter-species variation in gene expression levels. We found that inter-species differences in mark enrichment near transcription start sites are significantly more often associated with inter-species differences in the corresponding gene expression level than expected by chance alone. Interestingly, we also found that first-order interactions among the histone marks and Pol II do not markedly contribute to the degree of association between the marks and inter-species variation in gene expression levels, suggesting that the marginal effects of the five marks dominate this contribution.

2014-03-19

Divide and Conquer approach for Genome Classification based on subclass characterization

10.1101/003475

Siddanagouda Somanagouda Patil;Narasimha Murty Musti;Ulavappa Basvanneppa Angadi;

Classification of large grass genome sequences has major challenges in functional genomes. The presence of motifs in grass genome chains can make the prediction of the functional behavior of grass genome possible. The correlation between grass genome properties and their motifs is not always obvious, since more than one motif may exist within a genome chain. Due to the complexity of this association most pattern classification algorithms are either vain or time consuming. Attempted to a reduction of high dimensional data that utilizes DAC technique is presented. Data are disjoining into equal multiple sets while preserving the original data distribution in each set. Then, multiple modules are created by using the data sets as independent training sets and classified into respective modules. Finally, the modules are combined to produce the final classification rules, containing all the previously extracted information. The methodology is tested using various grass genome data sets. Results indicate that the time efficiency of our algorithm is improved compared to other known data mining algorithms.

2014-03-20

Towards a new history and geography of human genes informed by ancient DNA

10.1101/003517

Joseph Pickrell;David Reich;

Genetic information contains a record of the history of our species, and technological advances have transformed our ability to access this record. Many studies have used genome-wide data from populations today to learn about the peopling of the globe and subsequent adaptation to local conditions. Implicit in this research is the assumption that the geographic locations of people today are informative about the geographic locations of their ancestors in the distant past. However, it is now clear that long-range migration, admixture and population replacement have been the rule rather than the exception in human history. In light of this, we argue that it is time to critically re-evaluate current views of the peopling of the globe and the importance of natural selection in determining the geographic distribution of phenotypes. We specifically highlight the transformative potential of ancient DNA. By accessing the genetic make-up of populations living at archaeologically-known times and places, ancient DNA makes it possible to directly track migrations and responses to natural selection.

2014-03-21

Response to a population bottleneck can be used to infer recessive selection

10.1101/003491

Daniel J Balick;Ron Do;David Reich;Shamil R Sunyaev;

Here we present the first genome wide statistical test for recessive selection. This test uses explicitly non-equilibrium demographic differences between populations to infer the mode of selection. By analyzing the transient response to a population bottleneck and subsequent re-expansion, we qualitatively distinguish between alleles under additive and recessive selection. We analyze the response of the average number of deleterious mutations per haploid individual and describe time dependence of this quantity. We introduce a statistic, BR, to compare the number of mutations in different populations and detail its functional dependence on the strength of selection and the intensity of the population bottleneck. This test can be used to detect the predominant mode of selection on the genome wide or regional level, as well as among a sufficiently large set of medically or functionally relevant alleles.

2014-03-21

Identification of five patterns of nucleosome positioning that globally describe transcription factor function

10.1101/003483

Kazumitsu Maehara;Yasuyuki Ohkawa;

Following the binding of transcription factors (TF) to specific regions, chromatin remodeling including alterations in nucleosome positioning (NP) occurs. These changes in NP cause selective gene expression to determine cell function. However whether specific NP patterns upon TF binding determine the transcriptional regulation such as gene activation or suppression is unclear. Here we identified five patterns of NP around TF binding sites (TFBSs) using fixed MNase-Seq analysis. The most frequently observed NP pattern described the transcription state. The five patterns explained approximately 80% of the whole NP pattern on the genome in mouse C2C12 cells. We further performed ChIP-Seq using the input obtained from the fixed MNase-Seq. The result showed that a single trial of ChIP-Seq could visualize the NP patterns around the TFBS and predict the function of the transcriptional regulation at the same time. These findings indicate that NP can directly predict the function of TFs.

2014-03-21

Towards a molecular systems model of coronary artery disease

10.1101/003525

Gad Abraham;Oneil G Bhalala;Paul IW de Bakker;Samuli Ripatti;Michael Inouye;

Coronary artery disease (CAD) is a complex disease driven by myriad interactions of genetics and environmental factors. Traditionally, studies have analyzed only one disease factor at a time, providing useful but limited understanding of the underlying etiology. Recent advances in cost-effective and high-throughput technologies, such as single nucleotide polymorphism (SNP) genotyping, exome/genome sequencing, gene expression microarrays and metabolomics assays have enabled the collection of millions of data points in many thousands of individuals. In order to make sense of such omics data, effective analytical methods are needed. We review and highlight some of the main results in this area, focusing on integrative approaches that consider multiple modalities simultaneously. Such analyses have the potential to uncover the genetic basis of CAD, produce genomic risk scores (GRS) for disease prediction, disentangle the complex interactions underlying disease, and predict response to treatment.

2014-03-23

An optimized CRISPR/Cas toolbox for efficient germline and somatic genome engineering in Drosophila

10.1101/003541

Fillip Port;Hui-Min Chen;Tzumin Lee;Simon L Bullock;

The type II CRISPR/Cas system has recently emerged as a powerful method to manipulate the genomes of various organisms. Here, we report a novel toolbox for high efficiency genome engineering of Drosophila melanogaster consisting of transgenic Cas9 lines and versatile guide RNA (gRNA) expression plasmids. Systematic evaluation reveals Cas9 lines with ubiquitous or germline restricted patterns of activity. We also demonstrate differential activity of the same gRNA expressed from different U6 snRNA promoters, with the previously untested U6:3 promoter giving the most potent effect. Choosing an appropriate combination of Cas9 and gRNA allows targeting of essential and non-essential genes with transmission rates ranging from 25% - 100%. We also provide evidence that our optimized CRISPR/Cas tools can be used for offset nicking-based mutagenesis and, in combination with oligonucleotide donors, to precisely edit the genome by homologous recombination with efficiencies that do not require the use of visible markers. Lastly, we demonstrate a novel application of CRISPR/Cas-mediated technology in revealing loss-of-function phenotypes in somatic cells following efficient biallelic targeting by Cas9 expressed in a ubiquitous or tissue-restricted manner. In summary, our CRISPR/Cas tools will facilitate the rapid evaluation of mutant phenotypes of specific genes and the precise modification of the genome with single nucleotide precision. Our results also pave the way for high throughput genetic screening with CRISPR/Cas.

2014-03-24

An optimized CRISPR/Cas toolbox for efficient germline and somatic genome engineering in Drosophila

10.1101/003541

Fillip Port;Hui-Min Chen;Tzumin Lee;Simon L Bullock;

The type II CRISPR/Cas system has recently emerged as a powerful method to manipulate the genomes of various organisms. Here, we report a novel toolbox for high efficiency genome engineering of Drosophila melanogaster consisting of transgenic Cas9 lines and versatile guide RNA (gRNA) expression plasmids. Systematic evaluation reveals Cas9 lines with ubiquitous or germline restricted patterns of activity. We also demonstrate differential activity of the same gRNA expressed from different U6 snRNA promoters, with the previously untested U6:3 promoter giving the most potent effect. Choosing an appropriate combination of Cas9 and gRNA allows targeting of essential and non-essential genes with transmission rates ranging from 25% - 100%. We also provide evidence that our optimized CRISPR/Cas tools can be used for offset nicking-based mutagenesis and, in combination with oligonucleotide donors, to precisely edit the genome by homologous recombination with efficiencies that do not require the use of visible markers. Lastly, we demonstrate a novel application of CRISPR/Cas-mediated technology in revealing loss-of-function phenotypes in somatic cells following efficient biallelic targeting by Cas9 expressed in a ubiquitous or tissue-restricted manner. In summary, our CRISPR/Cas tools will facilitate the rapid evaluation of mutant phenotypes of specific genes and the precise modification of the genome with single nucleotide precision. Our results also pave the way for high throughput genetic screening with CRISPR/Cas.

2014-03-26

Preparation of next-generation DNA sequencing libraries from ultra-low amounts of input DNA: Application to single-molecule, real-time (SMRT) sequencing on the Pacific Biosciences RS II.

10.1101/003566

Castle Raley;David Munroe;Kristie Jones;Yu-Chih Tsai;Yan Guo;Bao Tran;Sujatha Gowda;Jennifer L. Troyer;Daniel R. Soppet;Claudia Stewart;Robert Stephens;Jack Chen;TF Skelly;Cheryl Heiner;Jonas Korlach;Dwight Nissley;

We have developed and validated an amplification-free method for generating DNA sequencing libraries from very low amounts of input DNA (500 picograms - 20 nanograms) for singlemolecule sequencing on the Pacific Biosciences (PacBio) RS II sequencer. The common challenge of high input requirements for single-molecule sequencing is overcome by using a carrier DNA in conjunction with optimized sequencing preparation conditions and re-use of the MagBead-bound complex. Here we describe how this method can be used to produce sequencing yields comparable to those generated from standard input amounts, but by using 1000-fold less starting material.

2014-03-25

Rice BiP3 regulates immunity mediated by the PRRs XA3 and XA21 but not immunity mediated by the NB-LRR protein, Pi5

10.1101/003533

Chang-Jin Park;Min-Young Song;Chi-Yeol Kim;Jong-Seong Jeon;Pamela C. Ronald;

Plant innate immunity is mediated by pattern recognition receptors (PRRs) and intracellular NB-LRR (nucleotide-binding domain and leucine-rich repeat) proteins. Overexpression of the endoplasmic reticulum (ER) chaperone, luminal-binding protein 3 (BiP3) compromises resistance to Xanthomonas oryzae pv. oryzae (Xoo) mediated by the rice PRR XA21 (Park et al., PLoS ONE 5(2): e9262). Here we show that BiP3 overexpression also compromises resistance mediated by rice XA3, a PRR that provides broad-spectrum resistance to Xoo. In contrast, BiP3 overexpression has no effect on resistance mediated by rice Pi5, an NB-LRR protein that confers resistance to the fungal pathogen Magnaporthe oryzae (M. oryzae). Our results suggest that rice BiP3 regulates membrane-resident PRR-mediated immunity.

2014-03-26

How many digits in a mean are worth reporting?

10.1101/003558

R.S. Clymo;

Most bioscientists need to report mean values, yet many have little idea of how many digits are significant, and at what point further digits are mere random junk. Thus a recent report that the mean of 17 values was 3.863 with a standard error of the mean (SEM) of 2.162 revealed only that none of the seven authors understood the limitations of their work. The simple rule derived here by experiment for restricting a mean value to its significant digits (sig-digs) is this: the last sig-dig in the mean value is at the same decimal decade as the first sig-dig (the first non-zero) in the SEM. An extended rule for the mean, and a different rule for the SEM itself are also derived. For the example above the reported values should be a mean of 4 with SEM 2.2. Routine application of these simple rules will often show that a result is not as compelling as one had hoped.

2014-03-25

A Comparison of Peak Callers Used for DNase-seq Data

10.1101/003608

Hashem Koohy;Thomas Down;Mikhail Spivakov;Tim Hubbard;

Genome-wide profiling of open chromatin regions using DNase I and high-throughput sequencing (DNase-seq) is an increasingly popular approach for finding and studying regulatory elements. A variety of algorithms have been developed to identify regions of open chromatin from raw sequence-tag data, which has motivated us to assess and compare their performance.\n\nIn this study, four published, publicly available peak calling algorithms used for DNase-seq data analysis (F-seq, Hotspot, MACS and ZINBA) are assessed at a range of signal thresholds on two published DNase-seq datasets for three cell types. The results were benchmarked against an independent dataset of regulatory regions derived from ENCODE in vivo transcription factor binding data for each particular cell type. The level of overlap between peak regions reported by each algorithm and this ENCODE-derived reference set was used to assess sensitivity and specificity of the algorithms.\n\nOur study suggests that F-seq has a slightly higher sensitivity than the next best algorithms. Hotspot and the ChIP-seq oriented method, MACS, both perform competitively when used with their default parameters. However the generic peak finder ZINBA appears to be less sensitive than the other three.\n\nWe also assess accuracy of each algorithm over a range of signal thresholds. In particular, we show that the accuracy of F-Seq can be considerably improved by using a threshold setting that is different from the default value.

2014-03-27

A Comparison of Peak Callers Used for DNase-seq Data

10.1101/003608

Hashem Koohy;Thomas Down;Mikhail Spivakov;Tim Hubbard;

Genome-wide profiling of open chromatin regions using DNase I and high-throughput sequencing (DNase-seq) is an increasingly popular approach for finding and studying regulatory elements. A variety of algorithms have been developed to identify regions of open chromatin from raw sequence-tag data, which has motivated us to assess and compare their performance.\n\nIn this study, four published, publicly available peak calling algorithms used for DNase-seq data analysis (F-seq, Hotspot, MACS and ZINBA) are assessed at a range of signal thresholds on two published DNase-seq datasets for three cell types. The results were benchmarked against an independent dataset of regulatory regions derived from ENCODE in vivo transcription factor binding data for each particular cell type. The level of overlap between peak regions reported by each algorithm and this ENCODE-derived reference set was used to assess sensitivity and specificity of the algorithms.\n\nOur study suggests that F-seq has a slightly higher sensitivity than the next best algorithms. Hotspot and the ChIP-seq oriented method, MACS, both perform competitively when used with their default parameters. However the generic peak finder ZINBA appears to be less sensitive than the other three.\n\nWe also assess accuracy of each algorithm over a range of signal thresholds. In particular, we show that the accuracy of F-Seq can be considerably improved by using a threshold setting that is different from the default value.

2014-04-14

The HVCN1 channel conducts protons into the phagocytic vacuole of neutrophils to produce a physiologically alkaline pH

10.1101/003616

Adam P Levine;Michael R Duchen;Anthony W Segal;

Activation of the NADPH oxidase (NOX2) of the phagocytic vacuole of neutrophils is essential for innate immunity. Sustained activity of the oxidase requires that charge movements across the membrane are balanced. A role for the proton channel, HVCN1, has been proposed but not proven. Using the ratiometric pH indicator SNARF, introduced into the cytosol and separately into the vacuole coupled to Candida, we used confocal microscopy to measure changes in pH in these two compartments in human and mouse neutrophils. Shortly after phagocytosis by human cells, the vacuolar pH rose to ~9, at which it was maintained for ~20 minutes, while the cytosol showed a small acidification of ~0.25 pH unit. Alkalinisation has important consequences for the microbicidal and digestive functions of vacuolar enzymes. In HVCN1 knock out mouse neutrophils, the phagocytosis induced respiratory burst was halved to ~3 fmols per Candida, the vacuolar pH rose to >11 and the cytosol acidified excessively to pH ~6.75. These changes were prevented by the protonophore CCCP. The rate of extrusion of protons into the extracellular medium following phagocytosis was not significantly different from wild type neutrophils suggesting that cytoplasmic acidification resulted from the loss of the proton sink into the vacuole. HVCN1 phagocytic vacuoles showed considerable swelling, and this was blocked by CCCP and decreased by valinomycin. Stoichiometric considerations indicated that the HVCN1 channel compensates 90-95% of the oxidase-induced charge in normal cells, and in its absence, charge is carried by ions other than protons, including K+.

2014-03-27

3D mapping of disease in ant societies reveals a strategy of a specialized parasite

10.1101/003574

Raquel G Loreto;Simon L Elliot;Mayara LR Freitas;Thairine M Pereira;David P Hughes;

Despite the widely held position that the social insects have evolved effective ways to limit infectious disease spread, many pathogens and parasites do attack insect societies. Maintaining a disease-free nest environment is an important evolutionary feature, but since workers have to leave the nest to forage they are routinely exposed to disease. Here we show that despite effective social immunity, in which workers act collectively to reduce disease inside the nest, 100% of studied ant colonies of Camponotus rufipes in a Brazilian Rainforest were infected by the specialized fungal parasite Ophiocordyceps unilateralis s.l. Not only is disease present for all colonies but long-term dynamics over 20 months revealed disease is a permanent feature. Using 3D maps, we showed the parasite optimizes its transmission by controlling workers behavior to die on the doorstep of the colony, where susceptible foragers are predictable in time and space. Therefore, despite social immunity, specialized diseases of ants have evolved effective strategies to exploit insect societies.

2014-03-27

The Scramble Conversion Tool

10.1101/003640

James K Bonfield;

MotivationThe reference CRAM file format implementation is in Java. We present \"Scramble\": a new C implementation of SAM, BAM and CRAM file I/O.\n\nResultsThe C API for CRAM is 1.5-1.7x slower than BAM at decoding, but 1.8-2.6x faster at encoding. We see file size savings of 40-50%.\n\nAvailabilitySource code is available from http://sourceforge.net/projects/staden/files/io_lib/

2014-03-28

Flexible analysis of transcriptome assemblies with Ballgown

10.1101/003665

Alyssa C Frazee;Geo Pertea;Andrew E Jaffe;Ben Langmead;Steven L Salzberg;Jeffrey T Leek;

Introduction Introduction Negative control experiment Positive control experiment Confirmation of statistical... Analysis of RNA-seq experiments... Analysis of quantitative... Expression quantitative trait... Computational Efficiency Summary References A key advantage of RNA sequencing (RNA-seq) over hybridization-based technologies such as microarrays is that RNA-seq makes it possible to reconstruct complete gene structures, including multiple splice variants, from raw RNA-seq reads without relying on previously-established annotations [20, 32, 9]. But with this added flexibility, there are increased computational demands on upstream processing tasks such as alignment and ass ...

2014-03-30

Flexible analysis of transcriptome assemblies with Ballgown

10.1101/003665

Alyssa C Frazee;Geo Pertea;Andrew E Jaffe;Ben Langmead;Steven L Salzberg;Jeffrey T Leek;

Introduction Introduction Negative control experiment Positive control experiment Confirmation of statistical... Analysis of RNA-seq experiments... Analysis of quantitative... Expression quantitative trait... Computational Efficiency Summary References A key advantage of RNA sequencing (RNA-seq) over hybridization-based technologies such as microarrays is that RNA-seq makes it possible to reconstruct complete gene structures, including multiple splice variants, from raw RNA-seq reads without relying on previously-established annotations [20, 32, 9]. But with this added flexibility, there are increased computational demands on upstream processing tasks such as alignment and ass ...

2014-09-05

Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology

10.1101/003657

Daniel McGlinn;Xiao Xiao;Justin Kitzes;Ethan P White;

AimThe Maximum Entropy Theory of Ecology (METE) is a unified theory of biodiversity that attempts to simultaneously predict patterns of species abundance, size, and spatial structure. The spatial predictions of this theory have repeatedly performed well at predicting diversity patterns across scales. However, the theoretical development and evaluation of METE has focused on predicting patterns that ignore inter-site spatial correlations. As a result the theory has not been evaluated using one of the core components of spatial structure. We develop and test a semi-recursive version of METEs spatially explicit predictions for the distance decay relationship of community similarity and compare METEs performance to the classic random placement model of completely random species distributions. This provides a better understanding and stronger test of METEs spatial community predictions.\n\nLocationNew world tropical and temperate plant communities.\n\nMethodsWe analytically derived and simulated METEs spatially explicit expectations for the Sorensen index of community similarity. We then compared the distance decay of community similarity of 16 mapped plant communities to METE and the random placement model.\n\nResultsThe version of METE we examined was successful at capturing the general functional form of empirical distance decay relationships, a negative power function relationship between community similarity and distance. However, the semi-recursive approach consistently over-predicted the degree and rate of species turnover and yielded worse predictions than the random placement model.\n\nMain conclusionsOur results suggest that while METEs current spatial models accurately predict the spatial scaling of species occupancy, and therefore core ecological patterns like the species-area relationship, its semi-recursive form does not accurately characterize spatially-explicit patterns of correlation. More generally, this suggests that tests of spatial theories based only on the species-area relationship may appear to support the underlying theory despite significant deviations in important aspects of spatial structure.

2014-03-30

Exploring the spatially explicit predictions of the Maximum Entropy Theory of Ecology

10.1101/003657

Daniel McGlinn;Xiao Xiao;Justin Kitzes;Ethan P White;

AimThe Maximum Entropy Theory of Ecology (METE) is a unified theory of biodiversity that attempts to simultaneously predict patterns of species abundance, size, and spatial structure. The spatial predictions of this theory have repeatedly performed well at predicting diversity patterns across scales. However, the theoretical development and evaluation of METE has focused on predicting patterns that ignore inter-site spatial correlations. As a result the theory has not been evaluated using one of the core components of spatial structure. We develop and test a semi-recursive version of METEs spatially explicit predictions for the distance decay relationship of community similarity and compare METEs performance to the classic random placement model of completely random species distributions. This provides a better understanding and stronger test of METEs spatial community predictions.\n\nLocationNew world tropical and temperate plant communities.\n\nMethodsWe analytically derived and simulated METEs spatially explicit expectations for the Sorensen index of community similarity. We then compared the distance decay of community similarity of 16 mapped plant communities to METE and the random placement model.\n\nResultsThe version of METE we examined was successful at capturing the general functional form of empirical distance decay relationships, a negative power function relationship between community similarity and distance. However, the semi-recursive approach consistently over-predicted the degree and rate of species turnover and yielded worse predictions than the random placement model.\n\nMain conclusionsOur results suggest that while METEs current spatial models accurately predict the spatial scaling of species occupancy, and therefore core ecological patterns like the species-area relationship, its semi-recursive form does not accurately characterize spatially-explicit patterns of correlation. More generally, this suggests that tests of spatial theories based only on the species-area relationship may appear to support the underlying theory despite significant deviations in important aspects of spatial structure.

2014-09-02

Numerous new mitogenomic sequences and multiple new environmental DNA markers for invasive bighead and silver carp (Hypophthalmichthys nobilis and H. molitrix) populations in North America

10.1101/003624

Richard F. Lance;Heather L. Farrington;Christine E. Edwards;Xin Guan;Matthew R. Carr;Kelly Baerwaldt;

Invasive Asian bighead and silver carp (Hypophthalmichthys nobilis and H. molitrix) pose a substantial threat to North American waterways. Recently, environmental DNA (eDNA), the use of species-specific genetic assays to detect the DNA of a particular species in a water sample, has gained recognition as a tool for tracking the invasion front of these species toward the Great Lakes. The goal of this study was to develop new species-specific conventional PCR (cPCR) and quantitative (qPCR) markers for detection of these species in North American waterways. We first generated complete mitochondrial genome sequences from 33 bighead and 29 silver carp individuals collected throughout their introduced range. These sequences were aligned with other common and closely related species to identify potential eDNA markers. We then field-tested these genetic markers for species-specificity and sensitivity in environmental samples. Newly developed markers performed well in field trials, had low false positive rates and had comparable sensitivity compared to current markers. The new markers developed in this study greatly expand the number of species-specific genetic markers available to track the invasion front of bighead and silver carp, and can be used to improve the resolution of these assays. Additionally, the use of the qPCR markers developed in this study may reduce sample processing time and cost of eDNA monitoring for these species.

2014-03-30

Geometry shapes evolution of early multicellularity

10.1101/003673

Eric Libby;Will Ratcliff;Mike Travisano;Ben Kerr;

Organisms have increased in complexity through a series of major evolutionary transitions, in which formerly autonomous entities become parts of a novel higher-level entity. One intriguing feature of the higher-level entity after some major transitions is a division of reproductive labor among its lower-level units. Although it can have clear benefits once established, it is unknown how such reproductive division of labor originates. We consider a recent evolution experiment on the yeast Saccharomyces cerevisiae as a unique platform to address the issue of reproductive differentiation during an evolutionary transition in individuality. In the experiment, independent yeast lineages evolved a multicellular \"snowflake-like\" cluster form in response to gravity selection. Shortly after the evolution of clusters, the yeast evolved higher rates of cell death. While cell death enables clusters to split apart and form new groups, it also reduces their performance in the face of gravity selection. To understand the selective value of increased cell death, we create a mathematical model of the cellular arrangement within snowflake yeast clusters. The model reveals that the mechanism of cell death and the geometry of the snowflake interact in complex, evolutionarily important ways. We find that the organization of snowflake yeast imposes powerful limitations on the available space for new cell growth. By dying more frequently, cells in clusters avoid encountering space limitations, and, paradoxically, reach higher numbers. In addition, selection for particular group sizes can explain the increased rate of apoptosis both in terms of total cell number and total numbers of collectives. Thus, by considering the geometry of a primitive multicellular organism we can gain insight into the initial emergence of reproductive division of labor during an evolutionary transition in individuality.

2014-03-30

An evolutionary resolution of manipulation conflict

10.1101/003707

Mauricio González-Forero;

Individuals can manipulate the behavior of social partners. However, manipulation may conflict with the fitness interests of the manipulated individuals. Manipulated individuals can then be favored to resist manipulation, possibly reducing or eliminating the manipulated behavior in the long run. I use a mathematical model to show that conflicts where manipulation and resistance coevolve can disappear as a result of the coevolutionary process. I find that while manipulated individuals are selected to resist, they can simultaneously be favored to express the manipulated behavior at higher efficiency (i.e., providing increasing fitness effects to recipients of the manipulated behavior). Efficiency can increase to a point at which selection for resistance disappears. This process yields an efficient social behavior that is induced by social partners, and over which the inducing and induced individuals are no longer in conflict. A necessary factor is costly inefficiency. I develop the model to address the evolution of advanced eusociality via maternal manipulation (AEMM). The model predicts AEMM to be particularly likely in taxa with ancestrally imperfect resistance to maternal manipulation. Costly inefficiency occurs if the cost of delayed dispersal is larger than the benefit of exploiting the maternal patch. I discuss broader implications of the process.

2014-03-31

An evolutionary resolution of manipulation conflict

10.1101/003707

Mauricio González-Forero;

Individuals can manipulate the behavior of social partners. However, manipulation may conflict with the fitness interests of the manipulated individuals. Manipulated individuals can then be favored to resist manipulation, possibly reducing or eliminating the manipulated behavior in the long run. I use a mathematical model to show that conflicts where manipulation and resistance coevolve can disappear as a result of the coevolutionary process. I find that while manipulated individuals are selected to resist, they can simultaneously be favored to express the manipulated behavior at higher efficiency (i.e., providing increasing fitness effects to recipients of the manipulated behavior). Efficiency can increase to a point at which selection for resistance disappears. This process yields an efficient social behavior that is induced by social partners, and over which the inducing and induced individuals are no longer in conflict. A necessary factor is costly inefficiency. I develop the model to address the evolution of advanced eusociality via maternal manipulation (AEMM). The model predicts AEMM to be particularly likely in taxa with ancestrally imperfect resistance to maternal manipulation. Costly inefficiency occurs if the cost of delayed dispersal is larger than the benefit of exploiting the maternal patch. I discuss broader implications of the process.

2014-04-14

New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

10.1101/003764

Michael C Schatz;Lyza G Maron;Joshua C Stein;Alejandro Hernandez Wences;James Gurtowski;Eric Biggers;Hayan Lee;Melissa Kramer;Eric Antonio;Elena Ghiban;Mark H Wright;Jer-ming Chia;Doreen Ware;Susan R McCouch;William Richard McCombie;

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the \"pan-genome\" of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

2014-04-02

HGTector: An automated method facilitating genome-wide discovery of putative horizontal gene transfers

10.1101/003731

Qiyun Zhu;Michael Kosoy;Katharina Dittmar;

A new computational method of rapid, exhaustive and genome-wide detection of HGT was developed, featuring the systematic analysis of BLAST hit distribution patterns in the context of a priori defined hierarchical evolutionary categories. Genes that fall beyond a series of statistically determined thresholds are identified as not adhering to the typical vertical history of the organisms in question, but instead having a putative horizontal origin. Tests on simulated genomic data suggest that this approach effectively targets atypically distributed genes that are highly likely to be HGT-derived, and exhibits robust performance compared to conventional BLAST-based approaches. This method was further tested on real genomic datasets, including Rickettsia genomes, and was compared to previous studies. Results show consistency with currently employed categories of HGT prediction methods. In-depth analysis of both simulated and real genomic data suggests that the method is notably insensitive to stochastic events such as gene loss, rate variation and database error, which are common challenges to the current methodology. An automated pipeline was created to implement this approach and was made publicly available at: https://github.com/DittmarLab/HGTector. The program is versatile, easily deployed, has low requirements for computational resources, and is an effective tool for initial or standalone large-scale discovery of candidate HGT-derived genes.

2014-04-02

Comparison of the theoretical and real-world evolutionary potential of a genetic circuit.

10.1101/003772

Manuel Razo-Mejia;James Boedicker;Daniel Jones;Alexander de Luna;Justin Block Kinney;Rob Phillips;

With the development of next-generation sequencing technologies, many large scale experimental efforts aim to map genotypic variability among individuals. This natural variability in populations fuels many fundamental biological processes, ranging from evolutionary adaptation and speciation to the spread of genetic diseases and drug resistance. An interesting and important component of this variability is present within the regulatory regions of genes. As these regions evolve, accumulated mutations lead to modulation of gene expression, which may have consequences for the phenotype. A simple model system where the link between genetic variability, gene regulation and function can be studied in detail is missing. In this article we develop a model to explore how the sequence of the wild-type lac promoter dictates the fold change in gene expression. The model combines single-base pair resolution maps of transcription factor and RNA polymerase binding energies with a comprehensive thermodynamic model of gene regulation. The model was validated by predicting and then measuring the variability of lac operon regulation in a collection of natural isolates. We then implement the model to analyze the sensitivity of the promoter sequence to the regulatory output, and predict the potential for regulation to evolve due to point mutations in the promoter region.

2014-04-02

Multilocus Species Trees Show the Recent Adaptive Radiation of the Mimetic Heliconius Butterflies

10.1101/003749

Krzysztof M Kozak;Niklas Wahlberg;Andrew Neild;Kanchon K Dasmahapatra;James Mallet;Chris D Jiggins;

Mullerian mimicry among Neotropical Heliconiini butterflies is an excellent example of natural selection, and is associated with the diversification of a large continental-scale radiation. Some of the processes driving the evolution of mimicry rings are likely to generate incongruent phylogenetic signals across the assemblage, and thus pose a challenge for systematics. We use a dataset of 22 mitochondrial and nuclear markers from 92% of species in the tribe to re-examine the phylogeny of Heliconiini with both supermatrix and multi-species coalescent approaches, characterise the patterns of conflicting signal and compare the performance of various methodological approaches to reflect the heterogeneity across the data. Despite the large extent of reticulate signal and strong conflict between markers, nearly identical topologies are consistently recovered by most of the analyses, although the supermatrix approach fails to reflect the underlying variation in the history of individual loci. The first comprehensive, time-calibrated phylogeny of this group is used to test the hypotheses of a diversification rate increase driven by the dramatic environmental changes in the Amazonia over the past 23 million years, or changes caused by diversity-dependent effects on the rate of diversification. We find that the tribe Heliconiini had doubled its rate of speciation around 11 Ma and that the presently most speciose genus Heliconius started diversifying rapidly at 10 Ma, likely in response to the recent drastic changes in topography of the region. Our study provides comprehensive evidence for a rapid adaptive radiation among an important insect radiation in the most biodiverse region of the planet.

2014-04-02

READemption - A tool for the computational analysis of deep-sequencing-based transcriptome data

10.1101/003723

Konrad Ulrich Förstner;Jörg Vogel;Cynthia Mira Sharma;

SummaryRNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. In order to draw biological conclusions based on RNA-Seq data, several steps some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes, RNA immunoprecipitated with proteins, not only from bacteria, but also from eukaryotes and archaea.\n\nAvailability and ImplementationREADemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).\n\[email protected]; [email protected]

2014-04-03

READemption - A tool for the computational analysis of deep-sequencing-based transcriptome data

10.1101/003723

Konrad Ulrich Förstner;Jörg Vogel;Cynthia Mira Sharma;

SummaryRNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. In order to draw biological conclusions based on RNA-Seq data, several steps some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes, RNA immunoprecipitated with proteins, not only from bacteria, but also from eukaryotes and archaea.\n\nAvailability and ImplementationREADemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).\n\[email protected]; [email protected]

2014-04-15

READemption - A tool for the computational analysis of deep-sequencing-based transcriptome data

10.1101/003723

Konrad Ulrich Förstner;Jörg Vogel;Cynthia Mira Sharma;

SummaryRNA-Seq has become a potent and widely used method to qualitatively and quantitatively study transcriptomes. In order to draw biological conclusions based on RNA-Seq data, several steps some of which are computationally intensive, have to be taken. Our READemption pipeline takes care of these individual tasks and integrates them into an easy-to-use tool with a command line interface. To leverage the full power of modern computers, most subcommands of READemption offer parallel data processing. While READemption was mainly developed for the analysis of bacterial primary transcriptomes, we have successfully applied it to analyze RNA-Seq reads from other sample types, including whole transcriptomes, RNA immunoprecipitated with proteins, not only from bacteria, but also from eukaryotes and archaea.\n\nAvailability and ImplementationREADemption is implemented in Python and is published under the ISC open source license. The tool and documentation is hosted at http://pythonhosted.org/READemption (DOI:10.6084/m9.figshare.977849).\n\[email protected]; [email protected]

2014-05-19

Protected polymorphisms and evolutionary stability of patch-selection strategies in stochastic environments

10.1101/003780

Steve Evans;Alexandru Hening;Sebastian Schreiber;

We consider consider a population living in a patchy environment that varies stochastically in space and time. The population is composed of two morphs (that is, individuals of the same species with different genotypes). In terms of survival and reproductive success, the associated phenotypes differ only in their habitat selection strategies. We compute invasion rates corresponding to the rates at which the abundance of an initially rare morph increases in the presence of the other morph established at equilibrium. If both morphs have positive invasion rates when rare, then there is an equilibrium distribution such that the two morphs coexist; that is, there is a protected polymorphism for habitat selection. Alternatively, if one morph has a negative invasion rate when rare, then it is asymptotically displaced by the other morph under all initial conditions where both morphs are present. We refine the characterization of an evolutionary stable strategy for habitat selection from [Schreiber, 2012] in a mathematically rigorous manner. We provide a necessary and sufficient condition for the existence of an ESS that uses all patches and determine when using a single patch is an ESS. We also provide an explicit formula for the ESS when there are two habitat types. We show that adding environmental stochasticity results in an ESS that, when compared to the ESS for the corresponding model without stochasticity, spends less time in patches with larger carrying capacities and possibly makes use of sink patches, thereby practicing a spatial form of bet hedging.

2014-04-03

Protected polymorphisms and evolutionary stability of patch-selection strategies in stochastic environments

10.1101/003780

Steve Evans;Alexandru Hening;Sebastian Schreiber;

We consider consider a population living in a patchy environment that varies stochastically in space and time. The population is composed of two morphs (that is, individuals of the same species with different genotypes). In terms of survival and reproductive success, the associated phenotypes differ only in their habitat selection strategies. We compute invasion rates corresponding to the rates at which the abundance of an initially rare morph increases in the presence of the other morph established at equilibrium. If both morphs have positive invasion rates when rare, then there is an equilibrium distribution such that the two morphs coexist; that is, there is a protected polymorphism for habitat selection. Alternatively, if one morph has a negative invasion rate when rare, then it is asymptotically displaced by the other morph under all initial conditions where both morphs are present. We refine the characterization of an evolutionary stable strategy for habitat selection from [Schreiber, 2012] in a mathematically rigorous manner. We provide a necessary and sufficient condition for the existence of an ESS that uses all patches and determine when using a single patch is an ESS. We also provide an explicit formula for the ESS when there are two habitat types. We show that adding environmental stochasticity results in an ESS that, when compared to the ESS for the corresponding model without stochasticity, spends less time in patches with larger carrying capacities and possibly makes use of sink patches, thereby practicing a spatial form of bet hedging.

2014-09-02

An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs

10.1101/003848

Jesse D Bloom;

Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg et al, 2014) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence.

2014-04-03

An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs

10.1101/003848

Jesse D Bloom;

Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg et al, 2014) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence.

2014-06-11

Unravelling the diversity behind Ophiocordyceps unilateralis complex: Three new species of Zombie-Ant fungus from Brazilian Amazon

10.1101/003806

João Araújo;Harry C Evans;David M Geiser;William P Mackay;David P Hughes;

In tropical forests, one of the most common relationships between parasites and insects is that between the fungus Ophiocordyceps (Ophiocordycipitaceae, Hypocreales, Ascomycota) and ants, especially within the tribe Camponotini. These fungi have the ability to penetrate the exoskeleton of the ant and to manipulate the behavior of the host, making it leave the nest and ascend understorey shrubs, to die biting onto the vegetation: hence, the term zombie-ant fungi to describe this behavioral changes on the host. It is posited that this behavioral change aids spore dispersal and thus increases the chances of infection. Despite their undoubted importance for ecosystem functioning, these fungal pathogens are still poorly documented, especially regarding their diversity, ecology and evolutionary relationships. Here, we describe three new and host-specific species of the genus Ophiocordyceps on Camponotus ants from the central Amazonian region of Brazil which can readily be separated using classic taxonomic criteria, in particular ascospore morphology. In addition, we also employed molecular techniques to show for the first time the phylogenetic relationships between these taxa and closely related species within the Ophiocordyceps unilateralis complex, as well as with other members of the family Ophiocordycipitaceae.

2014-04-03

Unravelling the diversity behind Ophiocordyceps unilateralis complex: Three new species of Zombie-Ant fungus from Brazilian Amazon

10.1101/003806

João Araújo;Harry C Evans;David M Geiser;William P Mackay;David P Hughes;

In tropical forests, one of the most common relationships between parasites and insects is that between the fungus Ophiocordyceps (Ophiocordycipitaceae, Hypocreales, Ascomycota) and ants, especially within the tribe Camponotini. These fungi have the ability to penetrate the exoskeleton of the ant and to manipulate the behavior of the host, making it leave the nest and ascend understorey shrubs, to die biting onto the vegetation: hence, the term zombie-ant fungi to describe this behavioral changes on the host. It is posited that this behavioral change aids spore dispersal and thus increases the chances of infection. Despite their undoubted importance for ecosystem functioning, these fungal pathogens are still poorly documented, especially regarding their diversity, ecology and evolutionary relationships. Here, we describe three new and host-specific species of the genus Ophiocordyceps on Camponotus ants from the central Amazonian region of Brazil which can readily be separated using classic taxonomic criteria, in particular ascospore morphology. In addition, we also employed molecular techniques to show for the first time the phylogenetic relationships between these taxa and closely related species within the Ophiocordyceps unilateralis complex, as well as with other members of the family Ophiocordycipitaceae.

2014-06-03

Unravelling the diversity behind Ophiocordyceps unilateralis complex: Three new species of Zombie-Ant fungus from Brazilian Amazon

10.1101/003806

João Araújo;Harry C Evans;David M Geiser;William P Mackay;David P Hughes;

In tropical forests, one of the most common relationships between parasites and insects is that between the fungus Ophiocordyceps (Ophiocordycipitaceae, Hypocreales, Ascomycota) and ants, especially within the tribe Camponotini. These fungi have the ability to penetrate the exoskeleton of the ant and to manipulate the behavior of the host, making it leave the nest and ascend understorey shrubs, to die biting onto the vegetation: hence, the term zombie-ant fungi to describe this behavioral changes on the host. It is posited that this behavioral change aids spore dispersal and thus increases the chances of infection. Despite their undoubted importance for ecosystem functioning, these fungal pathogens are still poorly documented, especially regarding their diversity, ecology and evolutionary relationships. Here, we describe three new and host-specific species of the genus Ophiocordyceps on Camponotus ants from the central Amazonian region of Brazil which can readily be separated using classic taxonomic criteria, in particular ascospore morphology. In addition, we also employed molecular techniques to show for the first time the phylogenetic relationships between these taxa and closely related species within the Ophiocordyceps unilateralis complex, as well as with other members of the family Ophiocordycipitaceae.

2014-09-29

MicroRNAs Regulate the Wnt/Ca2+ Signaling Pathway to Promote the Secretion of Insulin in Pancreatic Nestin-Positive Progenitor Cells

10.1101/003913

Chunyu Bai;Xiangchen Li;Yuhua Gao;Taofeng Lu;Kunfu Wang;Qian Li;Hui Xiong;Jia Chen;Ping Zhang;Wenjie Wang;Tingting Sun;Zhiqiang Shan;Bo Sun;Pei Pei;Changqing Liu;Weijun Guan;Yuehui Ma;

MicroRNAs (miRNAs) are small noncoding RNAs that bind to the 3'-UTR of mRNAs and function mainly in post-transcriptional regulation. MiRNAs have been implicated to play roles in organ development, including that of the pancreas. Many miRNAs, such as miR-375, miR-124, miR-7, miR-21 and miR-221, have been shown to regulate insulin production as well as insulin secretion. However, it is not known whether miRNAs can regulate insulin secretion via the control of intracellular Ca2+ in pancreatic beta cells. In this research, expression profiles of miRNAs and mRNAs were investigated using RNA-sequencing and microarray analysis in chicken pancreatic nestin-positive progenitor cells and differentiated pancreatic beta cells. A number of miRNAs were up-regulated after differentiation of progenitors into beta cells, which regulate cell signaling pathways to control cell function. miR-223 and miR146a were shown to promote insulin secretion from pancreatic beta cells by regulating the concentration of intracellular Ca2+ via the down-regulation of their target genes.

2014-04-04

Diversity of entomopathogens Fungi: Which groups conquered the insect body?

10.1101/003756

João P.M. Araújo;David P Hughes;

The entomopathogenic Fungi comprise a wide range of ecologically diverse species. This group of parasites can be found distributed among all fungal phyla and as well as among the ecologically similar but phylogenetically distinct Oomycetes or water molds, that belong to a different kingdom (Stramenopila). As a group, the entomopathogenic fungi and water molds parasitize a wide range of insect hosts from aquatic larvae in streams to adult insects of high canopy tropical forests. Their hosts are spread among 18 orders of insects, in all developmental stages such as: eggs, larvae, pupae, nymphs and adults exhibiting completely different ecologies. Such assortment of niches has resulted in these parasites evolving a considerable morphological diversity, resulting in enormous biodiversity, much of which remains unknown. Here we gather together a huge amount of records of these entomopathogens to comparing and describe both their morphologies and ecological traits. These findings highlight a wide range of adaptations that evolved following the evolutionary transition to infecting the most diverse and widespread animals on Earth, the insects.

2014-04-04

Diversity of entomopathogens Fungi: Which groups conquered the insect body?

10.1101/003756

João P.M. Araújo;David P Hughes;

The entomopathogenic Fungi comprise a wide range of ecologically diverse species. This group of parasites can be found distributed among all fungal phyla and as well as among the ecologically similar but phylogenetically distinct Oomycetes or water molds, that belong to a different kingdom (Stramenopila). As a group, the entomopathogenic fungi and water molds parasitize a wide range of insect hosts from aquatic larvae in streams to adult insects of high canopy tropical forests. Their hosts are spread among 18 orders of insects, in all developmental stages such as: eggs, larvae, pupae, nymphs and adults exhibiting completely different ecologies. Such assortment of niches has resulted in these parasites evolving a considerable morphological diversity, resulting in enormous biodiversity, much of which remains unknown. Here we gather together a huge amount of records of these entomopathogens to comparing and describe both their morphologies and ecological traits. These findings highlight a wide range of adaptations that evolved following the evolutionary transition to infecting the most diverse and widespread animals on Earth, the insects.

2014-04-14

Intermediate Migration Yields Optimal Adaptation in Structured, Asexual Populations

10.1101/003897

Arthur Covert III;Claus O Wilke;

Most evolving populations are subdivided into multiple subpopulations connected to each other by varying levels of gene flow. However, how population structure and gene flow (i.e., migration) affect adaptive evolution is not well understood. Here, we studied the impact of migration on asexually reproducing evolving computer programs (digital organisms). We found that digital organisms evolve the highest fitness values at intermediate migration rates, and we tested three hypotheses that could potentially explain this observation: (i) migration promotes passage through fitness valleys, (ii) migration increases genetic variation, and (iii) migration reduces clonal interference through a process called leapfrogging. We found that migration had no appreciable effect on the number of fitness valleys crossed and that genetic variation declined monotonously with increasing migration rates, instead of peaking at the optimal migration rate. However, the number of leapfrogging events, in which a superior beneficial mutation emerges on a genetic background that predates the previously best genotype in the population, did peak at the optimal migration rate. We thus conclude that in structured, asexual populations intermediate migration rates allow for optimal exploration of multiple, distinct fitness peaks, and thus yield the highest long-term adaptive success.

2014-04-04

SplitMEM: Graphical pan-genome analysis with suffix skips

10.1101/003954

Shoshana Marcus;Hayan Lee;Michael Schatz;

Motivation: With the rise of improved sequencing technologies, genomics is expanding from a single reference per species paradigm into a more comprehensive pan-genome approach with multiple individuals represented and analyzed together. One of the most sophisticated data structures for representing an entire population of genomes is a compressed de Bruijn graph. The graph structure can robustly represent simple SNPs to complex structural variations far beyond what can be done from linear sequences alone. As such there is a strong need to develop algorithms that can efficiently construct and analyze these graphs. Results: In this paper we explore the deep topological relationships between the suffix tree and the compressed de Bruijn graph. We introduce a novel O(n log n) time and space algorithm called splitMEM, that directly constructs the compressed de Bruijn graph for a pan-genome of total length n. To achieve this time complexity, we augment the suffix tree with suffix skips, a new construct that allows us to traverse several suffix links in constant time, and use them to efficiently decompose maximal exact matches (MEMs) into the graph nodes. We demonstrate the utility of splitMEM by analyzing the pan- genomes of 9 strains of Bacillus anthracis and 9 strains of Escherichia coli to reveal the properties of their core genomes. Availability: The source code and documentation are available open- source at http://splitmem.sourceforge.net

2014-04-06

Evolutionary Multiplayer Games

10.1101/003939

Chaitanya S Gokhale;Arne Traulsen;

Evolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g. increase less than linear with the number of cooperators. Such multiplayer games can be introduced in all the fields where evolutionary game theory is already well established. However, the inclusion of non-linearities can help to advance the analysis of systems which are known to be complex, e.g. in the case of non-Mendelian inheritance. We review the diachronic theory and applications of multiplayer evolutionary games and present the current state of the field. Our aim is a summary of the theoretical results from well-mixed populations in infinite as well as finite populations. We also discuss examples from three fields where the theory has been successfully applied, ecology, social sciences and population genetics. In closing, we probe certain future directions which can be explored using the complexity of multiplayer games while preserving the promise of simplicity of evolutionary games.

2014-04-07

Evolutionary Multiplayer Games

10.1101/003939

Chaitanya S Gokhale;Arne Traulsen;

Evolutionary game theory has become one of the most diverse and far reaching theories in biology. Applications of this theory range from cell dynamics to social evolution. However, many applications make it clear that inherent non-linearities of natural systems need to be taken into account. One way of introducing such non-linearities into evolutionary games is by the inclusion of multiple players. An example is of social dilemmas, where group benefits could e.g. increase less than linear with the number of cooperators. Such multiplayer games can be introduced in all the fields where evolutionary game theory is already well established. However, the inclusion of non-linearities can help to advance the analysis of systems which are known to be complex, e.g. in the case of non-Mendelian inheritance. We review the diachronic theory and applications of multiplayer evolutionary games and present the current state of the field. Our aim is a summary of the theoretical results from well-mixed populations in infinite as well as finite populations. We also discuss examples from three fields where the theory has been successfully applied, ecology, social sciences and population genetics. In closing, we probe certain future directions which can be explored using the complexity of multiplayer games while preserving the promise of simplicity of evolutionary games.

2014-04-15

KmerStream: Streaming algorithms for k-mer abundance estimation

10.1101/003962

Páll Melsted;Bjarni V. Halldórsson;

Motivation: Several applications in bioinformatics, such as genome assemblers and error corrections methods, rely on counting and keeping track of k-mers (substrings of length k). Histograms of k-mer frequencies can give valuable insight into the underlying distribution and indicate the error rate and genome size sampled in the sequencing experiment.\n\nResults: We present KmerStream, a streaming algorithm for computing statistics for high throughput sequencing data based on the frequency of k-mers. The algorithm runs in time linear in the size of the input and the space requirement are logarithmic in the size of the input. This very low space requirement allows us to deal with much larger datasets than previously presented algorithms. We derive a simple model that allows us to estimate the error rate of the sequencing experiment, as well as the genome size, using only the aggregate statistics reported by KmerStream and validate the accuracy on sequences from a PhiX control.\n\nAs an application we show how KmerStream can be used to compute the error rate of a DNA sequencing experiment. We run KmerStream on a set of 2656 whole genome sequenced individuals and compare the error rate to quality values reported by the sequencing equipment. We discover that while the quality values alone are largely reliable as a predictor of error rate, there is considerable variability in the error rates between sequencing runs, even when accounting for reported quality values.\n\nAvailability: The tool KmerStream is written in C++ and is released under a GPL license. It is freely available at https://github.com/pmelsted/KmerStream\n\nContact: [email protected]

2014-04-07

Brachyury cooperates with Wnt/β-Catenin signalling to elicit Primitive Streak like behaviour in differentiating mouse ES cells.

10.1101/003871

David Andrew Turner;Pau Rué;Jonathan P Mackenzie;Eleanor Davies;Alfonso Martinez Arias;

The formation of the Primitive Streak is the first visible sign of gastrulation, the process by which the three germ layers are formed from a single epithelium during early development. Embryonic Stem Cells (ESCs) provide a good system to understand the molecular and cellular events associated with these processes. Previous work, both in embryos and in culture, has shown how converging signals from both Nodal/TGF{beta}R and Wnt/{beta}-Catenin signalling pathways specify cells to adopt a Primitive Streak like fate and direct them to undertake an epithelial to mesenchymal transition (EMT). However, many of these approaches have relied on genetic analyses without taking into account the temporal progression of events within single cells. In addition, it is still unclear as to what extent events in the embryo are able to be reproduced in culture. Here, we combine flow-cytometry and a quantitative live single-cell imaging approach to demonstrate how the controlled differentiation of mouse ESCs (mESCs) towards a Primitive Streak fate in culture results in cells displaying many of the characteristics observed during early mouse development including transient Brachyury expression, EMT and increased motility. We also find that the EMT initiates the process, and this is both fuelled and terminated by the action of Bra, whose expression is dependent on the EMT and {beta}-Catenin activity. As a consequence of our analysis, we propose that a major output of Brachyury expression is in controlling the velocity of the cells that are transiting out of the Primitive Streak.

2014-04-07

Brachyury cooperates with Wnt/β-Catenin signalling to elicit Primitive Streak like behaviour in differentiating mouse ES cells.

10.1101/003871

David Andrew Turner;Pau Rué;Jonathan P Mackenzie;Eleanor Davies;Alfonso Martinez Arias;

The formation of the Primitive Streak is the first visible sign of gastrulation, the process by which the three germ layers are formed from a single epithelium during early development. Embryonic Stem Cells (ESCs) provide a good system to understand the molecular and cellular events associated with these processes. Previous work, both in embryos and in culture, has shown how converging signals from both Nodal/TGF{beta}R and Wnt/{beta}-Catenin signalling pathways specify cells to adopt a Primitive Streak like fate and direct them to undertake an epithelial to mesenchymal transition (EMT). However, many of these approaches have relied on genetic analyses without taking into account the temporal progression of events within single cells. In addition, it is still unclear as to what extent events in the embryo are able to be reproduced in culture. Here, we combine flow-cytometry and a quantitative live single-cell imaging approach to demonstrate how the controlled differentiation of mouse ESCs (mESCs) towards a Primitive Streak fate in culture results in cells displaying many of the characteristics observed during early mouse development including transient Brachyury expression, EMT and increased motility. We also find that the EMT initiates the process, and this is both fuelled and terminated by the action of Bra, whose expression is dependent on the EMT and {beta}-Catenin activity. As a consequence of our analysis, we propose that a major output of Brachyury expression is in controlling the velocity of the cells that are transiting out of the Primitive Streak.

2014-08-26

Brachyury cooperates with Wnt/β-Catenin signalling to elicit Primitive Streak like behaviour in differentiating mouse ES cells.

10.1101/003871

David Andrew Turner;Pau Rué;Jonathan P Mackenzie;Eleanor Davies;Alfonso Martinez Arias;

The formation of the Primitive Streak is the first visible sign of gastrulation, the process by which the three germ layers are formed from a single epithelium during early development. Embryonic Stem Cells (ESCs) provide a good system to understand the molecular and cellular events associated with these processes. Previous work, both in embryos and in culture, has shown how converging signals from both Nodal/TGF{beta}R and Wnt/{beta}-Catenin signalling pathways specify cells to adopt a Primitive Streak like fate and direct them to undertake an epithelial to mesenchymal transition (EMT). However, many of these approaches have relied on genetic analyses without taking into account the temporal progression of events within single cells. In addition, it is still unclear as to what extent events in the embryo are able to be reproduced in culture. Here, we combine flow-cytometry and a quantitative live single-cell imaging approach to demonstrate how the controlled differentiation of mouse ESCs (mESCs) towards a Primitive Streak fate in culture results in cells displaying many of the characteristics observed during early mouse development including transient Brachyury expression, EMT and increased motility. We also find that the EMT initiates the process, and this is both fuelled and terminated by the action of Bra, whose expression is dependent on the EMT and {beta}-Catenin activity. As a consequence of our analysis, we propose that a major output of Brachyury expression is in controlling the velocity of the cells that are transiting out of the Primitive Streak.

2014-08-27

Model adequacy and the macroevolution of angiosperm functional traits

10.1101/004002

Matthew Pennell;Richard G FitzJohn;William K Cornwell;Luke J Harmon;

Making meaningful inferences from phylogenetic comparative data requires a meaningful model of trait evolution. It is thus important to determine whether the model is appropriate for the data and the question being addressed. One way to assess this is to ask whether the model provides a good statistical explanation for the variation in the data. To date, researchers have focused primarily on the explanatory power of a model relative to alternative models. Methods have been developed to assess the adequacy, or absolute explanatory power, of phylogenetic trait models but these have been restricted to specific models or questions. Here we present a general statistical framework for assessing the adequacy of phylogenetic trait models. We use our approach to evaluate the statistical performance of commonly used trait models on 337 comparative datasets covering three key Angiosperm functional traits. In general, the models we tested often provided poor statistical explanations for the evolution of these traits. This was true for many different groups and at many different scales. Whether such statistical inadequacy will qualitatively alter inferences draw from comparative datasets will depend on the context. Regardless, assessing model adequacy can provide interesting biological insights -- how and why a model fails to describe variation in a dataset gives us clues about what evolutionary processes may have driven trait evolution across time.

2014-04-07

Model adequacy and the macroevolution of angiosperm functional traits

10.1101/004002

Matthew Pennell;Richard G FitzJohn;William K Cornwell;Luke J Harmon;

Making meaningful inferences from phylogenetic comparative data requires a meaningful model of trait evolution. It is thus important to determine whether the model is appropriate for the data and the question being addressed. One way to assess this is to ask whether the model provides a good statistical explanation for the variation in the data. To date, researchers have focused primarily on the explanatory power of a model relative to alternative models. Methods have been developed to assess the adequacy, or absolute explanatory power, of phylogenetic trait models but these have been restricted to specific models or questions. Here we present a general statistical framework for assessing the adequacy of phylogenetic trait models. We use our approach to evaluate the statistical performance of commonly used trait models on 337 comparative datasets covering three key Angiosperm functional traits. In general, the models we tested often provided poor statistical explanations for the evolution of these traits. This was true for many different groups and at many different scales. Whether such statistical inadequacy will qualitatively alter inferences draw from comparative datasets will depend on the context. Regardless, assessing model adequacy can provide interesting biological insights -- how and why a model fails to describe variation in a dataset gives us clues about what evolutionary processes may have driven trait evolution across time.

2014-10-31

Sharing of Very Short IBD Segments between Humans, Neandertals, and Denisovans

10.1101/003988

Gundula Povysil;Sepp Hochreiter;

We analyze the sharing of very short identity by descent (IBD) segments between humans, Neandertals, and Denisovans to gain new insights into their demographic history. Short IBD segments convey information about events far back in time because the shorter IBD segments are, the older they are assumed to be. The identification of short IBD segments becomes possible through next generation sequencing (NGS), which offers high variant density and reports variants of all frequencies. However, only recently HapFABIA has been proposed as the first method for detecting very short IBD segments in NGS data. HapFABIA utilizes rare variants to identify IBD segments with a low false discovery rate.\n\nWe applied HapFABIA to the 1000 Genomes Project whole genome sequencing data to identify IBD segments that are shared within and between populations. Many IBD segments have to be old since they are shared with Neandertals or Denisovans, which explains their shorter lengths compared to segments that are not shared with these ancient genomes. The Denisova genome most prominently matches IBD segments that are shared by Asians. Many of these segments were found exclusively in Asians and they are longer than segments shared between other continental populations and the Denisova genome. Therefore, we could confirm an introgression from Deniosvans into ancestors of Asians after their migration out of Africa. While Neandertal-matching IBD segments are most often shared by Asians, Europeans share a considerably higher percentage of IBD segments with Neandertals compared to other populations, too. Again, many of these Neandertal-matching IBD segments are found exclusively in Asians, whereas Neandertal-matching IBD segments that are shared by Europeans are often found in other populations, too. Neandertal-matching IBD segments that are shared by Asians or Europeans are longer than those observed in Africans. These IBD segments hint at a gene flow from Neandertals into ancestors of Asians and Europeans after they left Africa. Interestingly, many Neandertal-and/or Denisova-matching IBD segments are predominantly observed in Africans -- some of them even exclusively. IBD segments shared between Africans and Neandertals or Denisovans are strikingly short, therefore we assume that they are very old. Consequently, we conclude that DNA regions from ancestors of humans, Neandertals, and Denisovans have survived in Africans. As expected, IBD segments on chromosome X are on average longer than IBD segments on the autosomes. Neandertal-matching IBD segments on chromosome X confirm gene flow from Neandertals into ancestors of Asians and Europeans outside Africa that was already found on the autosomes. Interestingly, there is hardly any signal of Denisova introgression on the X chromosome.

2014-04-07

Sharing of Very Short IBD Segments between Humans, Neandertals, and Denisovans

10.1101/003988

Gundula Povysil;Sepp Hochreiter;

We analyze the sharing of very short identity by descent (IBD) segments between humans, Neandertals, and Denisovans to gain new insights into their demographic history. Short IBD segments convey information about events far back in time because the shorter IBD segments are, the older they are assumed to be. The identification of short IBD segments becomes possible through next generation sequencing (NGS), which offers high variant density and reports variants of all frequencies. However, only recently HapFABIA has been proposed as the first method for detecting very short IBD segments in NGS data. HapFABIA utilizes rare variants to identify IBD segments with a low false discovery rate.\n\nWe applied HapFABIA to the 1000 Genomes Project whole genome sequencing data to identify IBD segments that are shared within and between populations. Many IBD segments have to be old since they are shared with Neandertals or Denisovans, which explains their shorter lengths compared to segments that are not shared with these ancient genomes. The Denisova genome most prominently matches IBD segments that are shared by Asians. Many of these segments were found exclusively in Asians and they are longer than segments shared between other continental populations and the Denisova genome. Therefore, we could confirm an introgression from Deniosvans into ancestors of Asians after their migration out of Africa. While Neandertal-matching IBD segments are most often shared by Asians, Europeans share a considerably higher percentage of IBD segments with Neandertals compared to other populations, too. Again, many of these Neandertal-matching IBD segments are found exclusively in Asians, whereas Neandertal-matching IBD segments that are shared by Europeans are often found in other populations, too. Neandertal-matching IBD segments that are shared by Asians or Europeans are longer than those observed in Africans. These IBD segments hint at a gene flow from Neandertals into ancestors of Asians and Europeans after they left Africa. Interestingly, many Neandertal-and/or Denisova-matching IBD segments are predominantly observed in Africans -- some of them even exclusively. IBD segments shared between Africans and Neandertals or Denisovans are strikingly short, therefore we assume that they are very old. Consequently, we conclude that DNA regions from ancestors of humans, Neandertals, and Denisovans have survived in Africans. As expected, IBD segments on chromosome X are on average longer than IBD segments on the autosomes. Neandertal-matching IBD segments on chromosome X confirm gene flow from Neandertals into ancestors of Asians and Europeans outside Africa that was already found on the autosomes. Interestingly, there is hardly any signal of Denisova introgression on the X chromosome.

2014-07-15

Application of the radial distribution function for quantitative analysis of neuropil microstructure in stratum radiatum of CA1 region in hippocampus.

10.1101/003863

Yuriy Mishchenko;

Various structures in the brain contain many important clues to the brain?s development and function. Among these, the microscopic organization of neural tissue is of particular interest since such organization has direct potential to affect the formation of local synaptic connectivity between axons and dendrites, serving as an important factor affecting the brain?s development. While the organization of the brain at large and intermediate scales had been well studied, the organization of neural tissue at micrometer scales remains largely unknown. In particular, at present it is not known what specific structures exist in neuropil at micrometer scales, what effect such structures have on formation of synaptic connectivity, and what processes shape the micrometer-scale organization of neuropil. In this work, we present an analysis of recent electron microscopy reconstructions of blocks of neuropil tissue from rat s. radiatum of hippocampal CA1 to provide insights into these questions. We propose a new statistical method for systematically analyzing the small-scale organization of neuropil based on an adaptation of the approach of radial distribution functions from statistical physics. Our results show that the micrometer-scale organization of hippocampal CA1 neuropil can be viewed as a disordered arrangement of axonal and dendritic processes without significant small-scale positional coordinations. We observe several deviations from this picture in the distributions of glia and dendritic spines. Finally, we study the relationship between local synaptic connectivity and the small-scale organization of neuropil.

2014-04-07

Application of the radial distribution function for quantitative analysis of neuropil microstructure in stratum radiatum of CA1 region in hippocampus.

10.1101/003863

Yuriy Mishchenko;

Various structures in the brain contain many important clues to the brain?s development and function. Among these, the microscopic organization of neural tissue is of particular interest since such organization has direct potential to affect the formation of local synaptic connectivity between axons and dendrites, serving as an important factor affecting the brain?s development. While the organization of the brain at large and intermediate scales had been well studied, the organization of neural tissue at micrometer scales remains largely unknown. In particular, at present it is not known what specific structures exist in neuropil at micrometer scales, what effect such structures have on formation of synaptic connectivity, and what processes shape the micrometer-scale organization of neuropil. In this work, we present an analysis of recent electron microscopy reconstructions of blocks of neuropil tissue from rat s. radiatum of hippocampal CA1 to provide insights into these questions. We propose a new statistical method for systematically analyzing the small-scale organization of neuropil based on an adaptation of the approach of radial distribution functions from statistical physics. Our results show that the micrometer-scale organization of hippocampal CA1 neuropil can be viewed as a disordered arrangement of axonal and dendritic processes without significant small-scale positional coordinations. We observe several deviations from this picture in the distributions of glia and dendritic spines. Finally, we study the relationship between local synaptic connectivity and the small-scale organization of neuropil.

2014-04-08

Application of the radial distribution function for quantitative analysis of neuropil microstructure in stratum radiatum of CA1 region in hippocampus.

10.1101/003863

Yuriy Mishchenko;

Various structures in the brain contain many important clues to the brain?s development and function. Among these, the microscopic organization of neural tissue is of particular interest since such organization has direct potential to affect the formation of local synaptic connectivity between axons and dendrites, serving as an important factor affecting the brain?s development. While the organization of the brain at large and intermediate scales had been well studied, the organization of neural tissue at micrometer scales remains largely unknown. In particular, at present it is not known what specific structures exist in neuropil at micrometer scales, what effect such structures have on formation of synaptic connectivity, and what processes shape the micrometer-scale organization of neuropil. In this work, we present an analysis of recent electron microscopy reconstructions of blocks of neuropil tissue from rat s. radiatum of hippocampal CA1 to provide insights into these questions. We propose a new statistical method for systematically analyzing the small-scale organization of neuropil based on an adaptation of the approach of radial distribution functions from statistical physics. Our results show that the micrometer-scale organization of hippocampal CA1 neuropil can be viewed as a disordered arrangement of axonal and dendritic processes without significant small-scale positional coordinations. We observe several deviations from this picture in the distributions of glia and dendritic spines. Finally, we study the relationship between local synaptic connectivity and the small-scale organization of neuropil.

2014-10-29

Estimating Phylogeny from microRNA Data: A Critical Appraisal

10.1101/003921

Robert Thomson;David Plachetzki;Luke Mahler;Brian Moore;

Recent progress in resolving the tree of life continues to expose relationships that resist resolution, which drives the search for novel sources of information to solve these difficult phylogenetic problems. A recent example, the presence and absence of microRNA families, has been vigorously promoted as an ideal source of phylogenetic data and has been applied to several perennial phylogenetic problems. The utility of such data for phylogenetic inference hinges critically both on developing stochastic models that provide a reasonable description of the process that give rise to these data, and also on the careful validation of those models in real inference scenarios. Remarkably, however, the statistical behavior and phylogenetic utility of microRNA data have not yet been rigorously characterized. Here we explore the behavior and performance of microRNA presence/absence data under a variety of evolutionary models and reexamine datasets from several previous studies. We find that highly heterogeneous rates of microRNA gain and loss, pervasive secondary loss, and sampling error collectively render microRNA-based inference of phylogeny difficult. Moreover, our reanalyses fundamentally alter the conclusions for four of the five studies that we reexamined. Our results indicate that the capacity of miRNA data to resolve the tree of life has been overstated, and we urge caution in their application and interpretation.

2014-04-08

Estimating Phylogeny from microRNA Data: A Critical Appraisal

10.1101/003921

Robert Thomson;David Plachetzki;Luke Mahler;Brian Moore;

Recent progress in resolving the tree of life continues to expose relationships that resist resolution, which drives the search for novel sources of information to solve these difficult phylogenetic problems. A recent example, the presence and absence of microRNA families, has been vigorously promoted as an ideal source of phylogenetic data and has been applied to several perennial phylogenetic problems. The utility of such data for phylogenetic inference hinges critically both on developing stochastic models that provide a reasonable description of the process that give rise to these data, and also on the careful validation of those models in real inference scenarios. Remarkably, however, the statistical behavior and phylogenetic utility of microRNA data have not yet been rigorously characterized. Here we explore the behavior and performance of microRNA presence/absence data under a variety of evolutionary models and reexamine datasets from several previous studies. We find that highly heterogeneous rates of microRNA gain and loss, pervasive secondary loss, and sampling error collectively render microRNA-based inference of phylogeny difficult. Moreover, our reanalyses fundamentally alter the conclusions for four of the five studies that we reexamined. Our results indicate that the capacity of miRNA data to resolve the tree of life has been overstated, and we urge caution in their application and interpretation.

2014-07-29

A signature of power law network dynamics

10.1101/004028

Ashish Bhan;Animesh Ray;

Can one hear the sound of a growing network? We address the problem of recognizing the topology of evolving biological or social networks. Starting from percolation theory, we analytically prove a linear inverse relationship between two simple graph parameters--the logarithm of the average cluster size and logarithm of the ratio of the edges of the graph to the theoretically maximum number of edges for that graph--that holds for all growing power law graphs. The result establishes a novel property of evolving power-law networks in the asymptotic limit of network size. Numerical simulations as well as fitting to real-world citation co-authorship networks demonstrate that the result holds for networks of finite sizes, and provides a convenient measure of the extent to which an evolving family of networks belongs to the same power-law class.

2014-04-09

Building realistic assemblages with a Joint Species Distribution Model

10.1101/003947

David J. Harris;

O_LISpecies distribution models (SDMs) can be used to predict how individual species--and whole assemblages of species--will respond to a changing environment. Until now, these models have either assumed (1) that species occurrence probabilities are uncorrelated, or (2) that species respond linearly to preselected environmental variables. These two assumptions currently prevent ecologists from modeling assemblages with realistic co-occurrence and species richness properties.\nC_LIO_LIThis paper introduces a stochastic feedforward neural network, called mistnet, which makes neither assumption. Thus, unlike most SDMs, mistnet can account for non-independent co-occurrence patterns driven by unobserved environmental heterogeneity. And unlike recently proposed Joint SDMs, mistnet can also learn nonlinear functions relating species occurrence probabilities to environmental predictors.\nC_LIO_LIMistnet makes more accurate predictions about the North American bird communities found along Breeding Bird Survey transects than several alternative methods tested. In particular, typical assemblages held out of sample for validation were nearly 50,000 times more likely under the mistnet model than under independent combinations of single-species models.\nC_LIO_LIApart from improved accuracy, mistnet shows two other important benefits for ecological research and management. First: by analyzing co-occurrence data, mistnet can identify unmeasured--and perhaps unanticipated--environmental variables that drive species turnover. For example, mistnet identified a strong grassland/forest gradient, even though only temperature and precipitation were given as model inputs. Second: mistnet is able to take advantage of incomplete data sets to guide its predictions towards more realistic assemblages. For example, mistnet automatically adjusts its expectations to include more forest-associated species in response to a stray observation of a forest-dwelling warbler.\nC_LI

2014-04-09

Bias and measurement error in comparative analyses: a case study with the Ornstein Uhlenbeck model

10.1101/004036

Gavin Huw Thomas;Natalie Cooper;Chris Venditti;Andrew Meade;Robert P Freckleton;

Phylogenetic comparative methods are increasingly used to give new insight into variation, causes and consequences of trait variation among species. The foundation of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the parameters of these models have been hypothesised to be biased and only asymptotically behave in a statistically predictable way as datasets become large. This does not seem to be widely appreciated. We show that a commonly used model in evolutionary biology (the Ornstein-Uhlenbeck model) is biased over a wide range of conditions. Many studies fitting this model use datasets that are small and prone to substantial biases. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model.

2014-04-09

Bias and measurement error in comparative analyses: a case study with the Ornstein Uhlenbeck model

10.1101/004036

Gavin Huw Thomas;Natalie Cooper;Chris Venditti;Andrew Meade;Robert P Freckleton;

Phylogenetic comparative methods are increasingly used to give new insight into variation, causes and consequences of trait variation among species. The foundation of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the parameters of these models have been hypothesised to be biased and only asymptotically behave in a statistically predictable way as datasets become large. This does not seem to be widely appreciated. We show that a commonly used model in evolutionary biology (the Ornstein-Uhlenbeck model) is biased over a wide range of conditions. Many studies fitting this model use datasets that are small and prone to substantial biases. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model.

2015-04-15

MixMir: microRNA motif discovery from gene expression data using mixed linear models

10.1101/004010

LIYANG Diao;Antoine Marcais;Scott Norton;Kevin C. Chen;

microRNAs (miRNAs) are a class of [~]22nt non-coding RNAs that potentially regulate over 60% of human protein-coding genes. miRNA activity is highly specific, differing between cell types, developmental stages and environmental conditions, so the identification of active miRNAs in a given sample is of great interest. Here we present a novel computational approach for analyzing both mRNA sequence and gene expression data, called MixMir. Our method corrects for 3' UTR background sequence similarity between transcripts, which is known to correlate with mRNA transcript abundance. We demonstrate that after accounting for kmer sequence similarities in 3 UTRs, a statistical linear model based on motif presence/absence can effectively discover active miRNAs in a sample. MixMir utilizes fast software implementations for solving mixed linear models which are widely-used in genome-wide association studies (GWAS). Essentially we use 3 UTR sequence similarity in place of population cryptic relatedness in the GWAS problem. Compared to similar methods such as miReduce, Sylamer and cWords, we found that MixMir performed better at discovering true miRNA motifs in three mouse Dicer knockout experiments from different tissues, two of which were collected by our group. We confirmed these results on protein and mRNA expression data obtained from miRNA transfection experiments in human cell lines. MixMir can be freely downloaded from https://github.com/ldiao/MixMir.

2014-04-09

MixMir: microRNA motif discovery from gene expression data using mixed linear models

10.1101/004010

LIYANG Diao;Antoine Marcais;Scott Norton;Kevin C. Chen;

microRNAs (miRNAs) are a class of [~]22nt non-coding RNAs that potentially regulate over 60% of human protein-coding genes. miRNA activity is highly specific, differing between cell types, developmental stages and environmental conditions, so the identification of active miRNAs in a given sample is of great interest. Here we present a novel computational approach for analyzing both mRNA sequence and gene expression data, called MixMir. Our method corrects for 3' UTR background sequence similarity between transcripts, which is known to correlate with mRNA transcript abundance. We demonstrate that after accounting for kmer sequence similarities in 3 UTRs, a statistical linear model based on motif presence/absence can effectively discover active miRNAs in a sample. MixMir utilizes fast software implementations for solving mixed linear models which are widely-used in genome-wide association studies (GWAS). Essentially we use 3 UTR sequence similarity in place of population cryptic relatedness in the GWAS problem. Compared to similar methods such as miReduce, Sylamer and cWords, we found that MixMir performed better at discovering true miRNA motifs in three mouse Dicer knockout experiments from different tissues, two of which were collected by our group. We confirmed these results on protein and mRNA expression data obtained from miRNA transfection experiments in human cell lines. MixMir can be freely downloaded from https://github.com/ldiao/MixMir.

2014-04-10

MixMir: microRNA motif discovery from gene expression data using mixed linear models

10.1101/004010

LIYANG Diao;Antoine Marcais;Scott Norton;Kevin C. Chen;

microRNAs (miRNAs) are a class of [~]22nt non-coding RNAs that potentially regulate over 60% of human protein-coding genes. miRNA activity is highly specific, differing between cell types, developmental stages and environmental conditions, so the identification of active miRNAs in a given sample is of great interest. Here we present a novel computational approach for analyzing both mRNA sequence and gene expression data, called MixMir. Our method corrects for 3' UTR background sequence similarity between transcripts, which is known to correlate with mRNA transcript abundance. We demonstrate that after accounting for kmer sequence similarities in 3 UTRs, a statistical linear model based on motif presence/absence can effectively discover active miRNAs in a sample. MixMir utilizes fast software implementations for solving mixed linear models which are widely-used in genome-wide association studies (GWAS). Essentially we use 3 UTR sequence similarity in place of population cryptic relatedness in the GWAS problem. Compared to similar methods such as miReduce, Sylamer and cWords, we found that MixMir performed better at discovering true miRNA motifs in three mouse Dicer knockout experiments from different tissues, two of which were collected by our group. We confirmed these results on protein and mRNA expression data obtained from miRNA transfection experiments in human cell lines. MixMir can be freely downloaded from https://github.com/ldiao/MixMir.

2014-06-12

Whole Genome Bisulfite Sequencing of Cell Free DNA and its Cellular Contributors Uncovers Placenta Hypomethylated Domains

10.1101/004101

Taylor Jensen;Sung K Kim;Zhanyang Zhu;Christine Chin;Claudia Gebhard;Tim Lu;Cosmin Deciu;Dirk van den Boom;Mathias Ehrich;

BackgroundCirculating cell free fetal DNA has enabled non-invasive prenatal fetal aneuploidy testing without direct discrimination of the genetically distinct maternal and fetal DNA. Current testing may be improved by specifically enriching the sample material for fetal DNA. DNA methylation may allow for such a separation of DNA and thus support additional clinical opportunities; however, this depends on knowledge of the methylomes of ccf DNA and its cellular contributors.\n\nResultsWhole genome bisulfite sequencing was performed on a set of unmatched samples including ccf DNA from 8 non-pregnant (NP) and 7 pregnant female donors and genomic DNA from 7 maternal buffy coat and 5 placenta samples. We found CpG cytosines within longer fragments were more likely to be methylated, linking DNA methylation and fragment size in ccf DNA. Comparison of the methylomes of placenta and NP ccf DNA revealed many of the 51,259 identified differentially methylated regions (DMRs) were located in domains exhibiting consistent placenta hypomethylation across millions of consecutive bases, regions we termed placenta hypomethylated domains (PHDs). We found PHDs were consistently located within regions exhibiting low CpG and gene density. DMRs identified when comparing placenta to NP ccf DNA were recapitulated in pregnant ccf DNA, confirming the ability to detect differential methylation in ccf DNA mixtures.\n\nConclusionsWe generated methylome maps for four sample types at single base resolution, identified a link between DNA methylation and fragment length in ccf DNA, identified DMRs between sample groups, and uncovered the presence of megabase-size placenta hypomethylated domains. Furthermore, we anticipate these results to provide a foundation to which future studies using discriminatory DNA methylation may be compared.

2014-04-11

Natural CMT2 variation is associated with genome-wide methylation changes and temperature seasonality

10.1101/004119

Xia Shen;Jennifer De Jonge;Simon Forsberg;Mats Pettersson;Zheya Sheng;Lars Hennig;Örjan Carlborg;

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.\n\nAUTHOR SUMMARYA central problem when studying adaptation to a new environment is the interplay between genetic variation and phenotypic plasticity. Arabidopsis thaliana has colonized a wide range of habitats across the world and it is therefore an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we study two collections of A. thaliana accessions from across Eurasia to identify loci associated with differences in climates at the sampling sites. A new genome-wide association analysis method was developed to detect adaptive loci where the alleles tolerate different climate ranges. Sixteen novel such loci were found including a strong association between Chromomethylase 2 (CMT2) and temperature seasonality. The reference allele dominated in areas with less seasonal variability in temperature, and the alternative allele existed in both stable and variable regions. Our results thus link natural variation in CMT2 and epigenetic changes to temperature adaptation. We showed experimentally that plants with a defective CMT2 gene tolerate heat-stress better than plants with a functional gene. Together this strongly suggests a role for genetic regulation of epigenetic modifications in natural adaptation to temperature and illustrates the importance of re-analyses of existing data using new analytical methods to obtain deeper insights into the underlying biology from available data.

2014-04-10

Natural CMT2 variation is associated with genome-wide methylation changes and temperature seasonality

10.1101/004119

Xia Shen;Jennifer De Jonge;Simon Forsberg;Mats Pettersson;Zheya Sheng;Lars Hennig;Örjan Carlborg;

As Arabidopsis thaliana has colonized a wide range of habitats across the world it is an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we used public data from two collections of A. thaliana accessions to associate genetic variability at individual loci with differences in climates at the sampling sites. We use a novel method to screen the genome for plastic alleles that tolerate a broader climate range than the major allele. This approach reduces confounding with population structure and increases power compared to standard genome-wide association methods. Sixteen novel loci were found, including an association between Chromomethylase 2 (CMT2) and temperature seasonality where the genome-wide CHH methylation was different for the group of accessions carrying the plastic allele. Cmt2 mutants were shown to be more tolerant to heat-stress, suggesting genetic regulation of epigenetic modifications as a likely mechanism underlying natural adaptation to variable temperatures, potentially through differential allelic plasticity to temperature-stress.\n\nAUTHOR SUMMARYA central problem when studying adaptation to a new environment is the interplay between genetic variation and phenotypic plasticity. Arabidopsis thaliana has colonized a wide range of habitats across the world and it is therefore an attractive model for studying the genetic mechanisms underlying environmental adaptation. Here, we study two collections of A. thaliana accessions from across Eurasia to identify loci associated with differences in climates at the sampling sites. A new genome-wide association analysis method was developed to detect adaptive loci where the alleles tolerate different climate ranges. Sixteen novel such loci were found including a strong association between Chromomethylase 2 (CMT2) and temperature seasonality. The reference allele dominated in areas with less seasonal variability in temperature, and the alternative allele existed in both stable and variable regions. Our results thus link natural variation in CMT2 and epigenetic changes to temperature adaptation. We showed experimentally that plants with a defective CMT2 gene tolerate heat-stress better than plants with a functional gene. Together this strongly suggests a role for genetic regulation of epigenetic modifications in natural adaptation to temperature and illustrates the importance of re-analyses of existing data using new analytical methods to obtain deeper insights into the underlying biology from available data.

2014-10-03

Neural lineage induction reveals multi-scale dynamics of 3D chromatin organization

10.1101/004168

Aleksandra Pekowska;Bernd Klaus;Felix Alexander Klein;Simon Anders;Malgorzata Oles;Lars Michael Steinmetz;Paul Bertone;Wolfgang Huber;

Regulation of gene expression underlies cell identity. Chromatin structure and gene activity are linked at multiple levels, via positioning of genomic loci to transcriptionally permissive or repressive environments and by connecting cis-regulatory elements such as promoters and enhancers. However, the genome-wide dynamics of these processes during cell differentiation has not been characterized. Using tethered chromatin conformation capture (TCC) sequencing we determined global three-dimensional chromatin structures in mouse embryonic stem (ES) and neural stem (NS) cell derivatives. We found that changes in the propensity of genomic regions to form inter-chromosomal contacts are pervasive in neural induction and are associated with the regulation of gene expression. Moreover, we found a pronounced contribution of euchromatic domains to the intra-chromosomal interaction network of pluripotent cells, indicating the existence of an ES cell-specific mode of chromatin organization. Mapping of promoter-enhancer interactions in pluripotent and differentiated cells revealed that spatial proximity without enhancer element activity is a common architectural feature in cells undergoing early developmental changes. Activity-independent formation of higher-order contacts between cis-regulatory elements, predominant at complex loci, may thus provide an additional layer of transcriptional control.

2014-04-11

Direct Reciprocity Under Uncertainty Does Not Explain One-shot Cooperation, but Demonstrates the Benefits of a Norm Psychology

10.1101/004135

Matthew Zefferman;

Humans in many societies cooperate in economic experiments at much higher levels than would be expected if their goal was maximizing economic returns, even when their interactions are anonymous and one-shot. This is a puzzle because paying a cost to benefit another in one-shot interactions gives no direct or indirect benefits to the cooperator. This paper explores the logic of two competing evolutionary hypotheses to explain this behavior. The \"norm psychology\" hypothesis holds that a player's choice of strategy reflects socially-learned cultural norms. Its premise is that over the course of human evolutionary history, cultural norms varied considerably across human societies and through a process of gene-culture co-evolution, humans evolved mechanisms to learn and adopt the norms that are successful in their particular society. The \"mismatch\" hypothesis holds that pro-social preferences evolved genetically in our hunter-gatherer past where one-shot anonymous interactions were rare and these preferences are misapplied in modern laboratory settings. I compare these hypotheses by adopting a well-known model of the mismatch hypothesis and show that selection for one-shot cooperation in the model is an artifact of agents being constrained to only two strategies: Tit-for-Tat and Always Defect. Allowing for repentant and forgiving strategies reverses selection away from one-shot cooperation under all environmental parameters. Direct reciprocity does not necessarily lead to cooperation, but instead generates many different normative equilibria depending on a groups idiosyncratic evolutionary history. Therefore, an agent whose behavior is evoked solely from non-cultural environmental cues will be disadvantaged relative to an agent who learns the locally successful norms. Cooperation in one-shot laboratory experiments is thus more easily explained as the result of a psychology evolved for learning social norms than as a genetic mismatch.

2014-04-11

Average oxidation state of carbon in proteins

10.1101/004127

Jeffrey M. Dick;

The degree of oxidation of carbon atoms in organic molecules depends on the covalent structure. In proteins, the average oxidation state of carbon (ZC) can be calculated as an elemental ratio from the chemical formula. To investigate oxidation-reduction (redox) patterns, groups of proteins from different subcellular locations and phylogenetic divisions were selected for comparison. Extracellular proteins of yeast have a relatively high oxidation state of carbon, corresponding with oxidizing conditions outside of the cell. However, an inverse relationship between ZC and redox potential occurs between the endoplasmic reticulum and cytoplasm; this trend is interpreted as resulting from overall coupling of protein turnover to the formation of a lower glutathione redox potential in the cytoplasm. In Rubisco homologues, lower ZC tends to occur in organisms with higher optimal growth temperature, and there are broad changes in ZC in whole-genome protein compositions in microbes from different environments. Energetic costs calculated from thermodynamic models suggest that thermophilic organisms exhibit molecular adaptation to not only high temperature but also the reducing nature of many hydrothermal fluids. A view of protein metabolism that depends on the chemical conditions of cells and environments raises new questions linking biochemical processes to changes on evolutionary timescales.

2014-04-14

Flexible methods for estimating genetic distances from nucleotide data

10.1101/004184

Simon Joly;David J Bryant;Peter J Lockhart;

O_LIWith the increasing use of massively parallel sequencing approaches in evolutionary biology, the need for fast and accurate methods suitable to investigate genetic structure and evolutionary history are more important than ever. We propose new distance measures for estimating genetic distances between individuals when allelic variation, gene dosage and recombination could compromise standard approaches.\nC_LIO_LIWe present four distance measures based on single nucleotide polymorphisms (SNP) and evaluate them against previously published measures using coalescent-based simulations. Simulations were used to test (i) whether the measures give unbiased and accurate distance estimates, (ii) if they can accurately identify the genomic mixture of hybrid individuals and (iii) if they give precise (low variance) estimates.\nC_LIO_LIThe results showed that the SNP-based GENPOFAD distance we propose appears to work well in the widest circumstances. It was the most accurate method for estimating genetic distances and is also relatively good at estimating the genomic mixture of hybrid individuals.\nC_LIO_LIOur simulations provide benchmarks to compare the performance of different distance measures in specific situations.\nC_LI

2014-04-14

Flexible methods for estimating genetic distances from nucleotide data

10.1101/004184

Simon Joly;David J Bryant;Peter J Lockhart;

O_LIWith the increasing use of massively parallel sequencing approaches in evolutionary biology, the need for fast and accurate methods suitable to investigate genetic structure and evolutionary history are more important than ever. We propose new distance measures for estimating genetic distances between individuals when allelic variation, gene dosage and recombination could compromise standard approaches.\nC_LIO_LIWe present four distance measures based on single nucleotide polymorphisms (SNP) and evaluate them against previously published measures using coalescent-based simulations. Simulations were used to test (i) whether the measures give unbiased and accurate distance estimates, (ii) if they can accurately identify the genomic mixture of hybrid individuals and (iii) if they give precise (low variance) estimates.\nC_LIO_LIThe results showed that the SNP-based GENPOFAD distance we propose appears to work well in the widest circumstances. It was the most accurate method for estimating genetic distances and is also relatively good at estimating the genomic mixture of hybrid individuals.\nC_LIO_LIOur simulations provide benchmarks to compare the performance of different distance measures in specific situations.\nC_LI

2014-11-28

A novel paradigm for auditory discrimination training with social reinforcement in songbirds

10.1101/004176

Kirill Tokarev;Ofer Tchernichovski;

Zebra finches are a highly social, gregarious, species and eagerly engage in vocal communication. We have developed a training apparatus that allows training zebra finches to discriminate socially reinforced and aversive vocal stimuli. In our experiments, juvenile male zebra finches were trained to discriminate a song that was followed by a brief air puff (aversive) and a song that allowed them to stay in visual contact with another bird, audience (social song). During training, the birds learned quickly to avoid air puffs by escaping the aversive song within 2 sec. They escaped significantly more aversive songs than socially reinforced ones, and this effect grew stronger with the number of training sessions. Therefore, we propose this training procedure as an effective method to teach zebra finches to discriminate between different auditory stimuli, which may also be used as a broader paradigm for addressing social reinforcement learning. The apparatus can be built from commercially available parts, and we are sharing the controlling software on our website.

2014-04-14

Bridging the Genotype and the Phenotype: Towards An Epigenetic Landscape Approach to Evolutionary Systems Biology

10.1101/004218

Jose Davila-Velderrain;Elena R Alvarez-Buylla;

Understanding the mapping of genotypes into phenotypes is a central challenge of current biological research. Such mapping, conceptually represents a developmental mechanism through which phenotypic variation can be generated. Given the nongenetic character of developmental dynamics, phenotypic variation to a great extent has been neglected in the study of evolution. What is the relevance of considering this generative process in the study of evolution? How can we study its evolutionary consequences? Despite an historical systematic bias towards linear causation schemes in biology; in the post-genomic era, a systems-view to biology based on nonlinear (network) thinking is increasingly being adopted. Within this view, evolutionary dynamics can be studied using simple dynamical models of gene regulatory networks (GRNs). Through the study of GRN dynamics, genotypes and phenotypes can be unambiguously defined. The orchestrating role of GRNs constitutes an operational non-linear genotype-phenotype map. Further extension of these GRN models in order to explore and characterize an associated Epigenetic Landscape enables the study of the evolutionary consequences of both genetic and non-genetic sources of phenotypic variation within the same coherent theoretical framework. The merging of conceptually clear theories, computational/mathematical tools, and molecular/genomic data into coherent frameworks could be the basis for a transformation of biological research from mainly a descriptive exercise into a truly mechanistic, explanatory endeavor.

2014-04-14

Epigenetic Landscape Models: The Post-Genomic Era

10.1101/004192

Jose Davila-Velderrain;Juan Carlos Martinez-Garcia;Elena R Alvarez-Buylla;

Complex networks of regulatory interactions orchestrate developmental processes in multicellular organisms. Such a complex internal structure intrinsically constrains cellular behavior allowing only a reduced set of attainable and observable cellular states or cell types. Thus, a multicellular system undergoes cell fate decisions in a robust manner in the course of its normal development. The epigenetic landscape (EL) model originally proposed by C.H. Waddington was an early attempt to integrate these processes in a universal conceptual model of development. Since then, a wealth of experimental data has accumulated, the general mechanisms of gene regulation have been uncovered, and the placement of specific molecular components within modular gene regulatory networks (GRN) has become a common practice. This has motivated the development of mathematical and computational models inspired by the EL aiming to integrate molecular data and gain a better understanding of development, and hopefully predict cell differentiation and reprogramming events. Both deterministic and stochastic dynamical models have been used to described cell state transitions. In this review, we describe recent EL models, emphasising that the construction of an explicit landscape from a GRN is not the only way to implement theoretical models consistent with the conceptual basis of the EL. Moreover, models based on the EL have been shown to be useful in the study of morphogenic processes and not just cell differentiation. Here we describe the distinct approaches, comparing their strengths and weaknesses and the kind of biological questions that they have been able to address. We also point to challenges ahead.

2014-04-14

Epigenetic Landscape Models: The Post-Genomic Era

10.1101/004192

Jose Davila-Velderrain;Juan Carlos Martinez-Garcia;Elena R Alvarez-Buylla;

Complex networks of regulatory interactions orchestrate developmental processes in multicellular organisms. Such a complex internal structure intrinsically constrains cellular behavior allowing only a reduced set of attainable and observable cellular states or cell types. Thus, a multicellular system undergoes cell fate decisions in a robust manner in the course of its normal development. The epigenetic landscape (EL) model originally proposed by C.H. Waddington was an early attempt to integrate these processes in a universal conceptual model of development. Since then, a wealth of experimental data has accumulated, the general mechanisms of gene regulation have been uncovered, and the placement of specific molecular components within modular gene regulatory networks (GRN) has become a common practice. This has motivated the development of mathematical and computational models inspired by the EL aiming to integrate molecular data and gain a better understanding of development, and hopefully predict cell differentiation and reprogramming events. Both deterministic and stochastic dynamical models have been used to described cell state transitions. In this review, we describe recent EL models, emphasising that the construction of an explicit landscape from a GRN is not the only way to implement theoretical models consistent with the conceptual basis of the EL. Moreover, models based on the EL have been shown to be useful in the study of morphogenic processes and not just cell differentiation. Here we describe the distinct approaches, comparing their strengths and weaknesses and the kind of biological questions that they have been able to address. We also point to challenges ahead.

2015-02-28

Building a better frog trap: The benefits of mal-adaptive habitat choice for metapopulations with different life history strategies

10.1101/004226

Rosemary Hartman;Noam Ross;

By spatially distributing offspring among several habitat patches in varying environments, an organism can \"hedge its bets\" to protect against bad conditions in any single patch. This strategy can maintain populations even when some or even all locations are, on average, population sinks. However, species may not have evolved this bet-hedging mechanism, especially when sink environments are anthropogenic \"traps\" - locations where traditional habitat cues have been altered. Using a model based on the life history of the Cascades frog (Rana cascadae), we examine the conditions that maximize growth in an environment with ecological traps created by the introduction of predators. In a temporally stochastic environment, maximum growth rates occur when some juveniles disperse to the trap. We then examine how different life histories and predation regimes affect the ability of an organism gain an advantage by bet-hedging, and find that bet-hedging can be less useful when the ecological trap drives adult, rather than juvenile, mortality.

2014-04-15

Genetic Influences on Brain Gene Expression in Rats Selected for Tameness and Aggression

10.1101/004234

Henrike Heyne;Susann Lautenschlaeger;Ronald Nelson;François Besnier;Maxime Rotival;Alexander Cagan;Rimma Kozhemyakina;Irina Plyusnina;Lyudmila Trut;Orjan Carlborg;Enrico Petretto;Leonid Kruglyak;Svante Pääbo;Torsten Schoeneberg;Frank Albert;

Inter-individual differences in many behaviors are partly due to genetic differences, but the identification of the genes and variants that influence behavior remains challenging. Here, we studied an F2 intercross of two outbred lines of rats selected for tame and aggressive behavior towards humans for more than 64 generations. By using a mapping approach that is able to identify genetic loci segregating within the lines, we identified four times more loci influencing tameness and aggression than by an approach that assumes fixation of causative alleles, suggesting that many causative loci were not driven to fixation by the selection. We used RNA sequencing in 150 F2 animals to identify hundreds of loci that influence brain gene expression. Several of these loci colocalize with tameness loci and may reflect the same genetic variants. Through analyses of correlations between allele effects on behavior and gene expression, differential expression between the tame and aggressive rat selection lines, and correlations between gene expression and tameness in F2 animals, we identify the genes Gltscr2, Lgi4, Zfp40 and Slc17a7 as candidate contributors to the strikingly different behavior of the tame and aggressive animals.

2014-04-17