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Generation of Aggregates of Mouse ES Cells that Show Symmetry Breaking, Polarisation and Emergent Collective Behaviour in vitro.

10.1101/005215

Peter Baillie-Johnson;Susanne C van den Brink;Tina Balayo;David A Turner;Alfonso Martinez Arias;

Dissociated mouse embryonic stem (ES) cells were cultured to form aggregates in small volumes of basal medium in U-bottomed, non tissue-culture-treated 96-well plates and subsequently maintained in suspension culture. After growth for 48 hours, the aggregates are competent to respond to ubiquitous experimental signals which result in their symmetry-breaking and generation of defined polarised structures by 96 hours. It is envisaged that this system can be applied both to the study of early developmental events and more broadly to the processes of self-organisation and cellular decision-making. It may also provide a suitable niche for the generation of cell types present in the embryo but unobtainable from conventional adherent culture.

2014-05-15

Generation of Aggregates of Mouse ES Cells that Show Symmetry Breaking, Polarisation and Emergent Collective Behaviour in vitro.

10.1101/005215

Peter Baillie-Johnson;Susanne C van den Brink;Tina Balayo;David A Turner;Alfonso Martinez Arias;

Dissociated mouse embryonic stem (ES) cells were cultured to form aggregates in small volumes of basal medium in U-bottomed, non tissue-culture-treated 96-well plates and subsequently maintained in suspension culture. After growth for 48 hours, the aggregates are competent to respond to ubiquitous experimental signals which result in their symmetry-breaking and generation of defined polarised structures by 96 hours. It is envisaged that this system can be applied both to the study of early developmental events and more broadly to the processes of self-organisation and cellular decision-making. It may also provide a suitable niche for the generation of cell types present in the embryo but unobtainable from conventional adherent culture.

2014-05-19

Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory

10.1101/005140

Mehdi Keramati;Boris Gutkin;

Efficient regulation of internal homeostasis and defending it against perturbations requires complex behavioral strategies. However, the computational principles mediating brains homeostatic regulation of reward and associative learning remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behavior is modulated by the internal state of the animal. The theory proves that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further give a formal basis for temporal discounting of reward. It also explains how animals learn to act predictively to preclude prospective homeostatic challenges, and attributes a normative computational role to the modulation of midbrain dopaminergic activity by hypothalamic signals.

2014-05-14

Collecting reward to defend homeostasis: A homeostatic reinforcement learning theory

10.1101/005140

Mehdi Keramati;Boris Gutkin;

Efficient regulation of internal homeostasis and defending it against perturbations requires complex behavioral strategies. However, the computational principles mediating brains homeostatic regulation of reward and associative learning remain undefined. Here we use a definition of primary rewards, as outcomes fulfilling physiological needs, to build a normative theory showing how learning motivated behavior is modulated by the internal state of the animal. The theory proves that seeking rewards is equivalent to the fundamental objective of physiological stability, defining the notion of physiological rationality of behavior. We further give a formal basis for temporal discounting of reward. It also explains how animals learn to act predictively to preclude prospective homeostatic challenges, and attributes a normative computational role to the modulation of midbrain dopaminergic activity by hypothalamic signals.

2014-06-05

Locus architecture affects mRNA expression levels in Drosophila embryos

10.1101/005173

Tara Lydiard-Martin;Meghan Bragdon;Kelly B Eckenrode;Zeba Wunderlich;Angela H DePace;

Structural variation in the genome is common due to insertions, deletions, duplications and rearrangements. However, little is known about the ways structural variants impact gene expression. Developmental genes are controlled by multiple regulatory sequence elements scattered over thousands of bases; developmental loci are therefore a good model to test the functional impact of structural variation on gene expression. Here, we measured the effect of rearranging two developmental enhancers from the even-skipped (eve) locus in Drosophila melanogaster blastoderm embryos. We systematically varied orientation, order, and spacing of the enhancers in transgenic reporter constructs and measured expression quantitatively at single cell resolution in whole embryos to detect changes in both level and position of expression. We found that the position of expression was robust to changes in locus organization, but levels of expression were highly sensitive to the spacing between enhancers and order relative to the promoter. Our data demonstrate that changes in locus architecture can dramatically impact levels of gene expression. To quantitatively predict gene expression from sequence, we must therefore consider how information is integrated both within enhancers and across gene loci.

2014-05-14

SraTailor: GUI software for visualizing high-throughput sequence read archives

10.1101/005231

Shinya Oki;Kazumitsu Maehara;Yasuyuki Ohkawa;Chikara Meno;

Raw high-throughput sequence data are deposited in public databases as SRAs (Sequence Read Archives) and are publically available to every researcher. However, in order to graphically visualize the sequence data of interest, the corresponding SRAs must be downloaded and converted into BigWig format through complicated command-line processing. This task requires users to possess skill with script languages and sequence data processing, a requirement that prevents a wide range of biologists from exploiting SRAs. To address these challenges, we developed SraTailor, a GUI (Graphical User Interface) software package that automatically converts an SRA into a BigWig-formatted file. Simplicity of use is one of the most notable features of SraTailor: entering an accession number of an SRA and clicking the mouse are the only steps required in order to obtain BigWig-formatted files and to graphically visualize the extents of reads at given loci. SraTailor is also able to make peak calls and files of other formats, and the software also accepts various command-line-like options. Therefore, this software makes SRAs fully exploitable by a wide range of biologists. SraTailor is freely available at http://www.dev.med.kyushu-u.ac.jp/sra_tailor/.

2014-05-16

Strategic Social Learning and the Population Dynamics of Human Behavior: The Game of Go

10.1101/005223

Bret A Beheim;Calvin Thigpen;Richard McElreath;

Human culture is widely believed to undergo evolution, via mechanisms rooted in the nature of human cognition. A number of theories predict the kinds of human learning strategies, as well as the population dynamics that result from their action. There is little work, however, that quantitatively examines the evidence for these strategies and resulting cultural evolution within human populations. One of the obstacles is the lack of individual-level data with which to link transmission events to larger cultural dynamics. Here, we address this problem with a rich quantitative database from the East Asian board game known as Go. We draw from a large archive of Go games spanning the last six decades of professional play, and find evidence that the evolutionary dynamics of particular cultural variants are driven by a mix of individual and social learning processes. Particular players vary dramatically in their sensitivity to population knowledge, which also varies by age and nationality. The dynamic patterns of opening Go moves are consistent with an ancient, ongoing arms race within the game itself.

2014-05-16

Strategic Social Learning and the Population Dynamics of Human Behavior: The Game of Go

10.1101/005223

Bret A Beheim;Calvin Thigpen;Richard McElreath;

Human culture is widely believed to undergo evolution, via mechanisms rooted in the nature of human cognition. A number of theories predict the kinds of human learning strategies, as well as the population dynamics that result from their action. There is little work, however, that quantitatively examines the evidence for these strategies and resulting cultural evolution within human populations. One of the obstacles is the lack of individual-level data with which to link transmission events to larger cultural dynamics. Here, we address this problem with a rich quantitative database from the East Asian board game known as Go. We draw from a large archive of Go games spanning the last six decades of professional play, and find evidence that the evolutionary dynamics of particular cultural variants are driven by a mix of individual and social learning processes. Particular players vary dramatically in their sensitivity to population knowledge, which also varies by age and nationality. The dynamic patterns of opening Go moves are consistent with an ancient, ongoing arms race within the game itself.

2014-05-19

A putative antiviral role of plant cytidine deaminases

10.1101/005256

Susana Martín;José M. Cuevas;Ana Grande-Pérez;Santiago F. Elena;

A mechanism of innate antiviral immunity operating against viruses infecting mammalian cells has been described during the last decade. Host cytidine deaminases (e.g., APOBEC3 proteins) edit viral genomes giving raise to hypermutated nonfunctional viruses; consequently, viral fitness is reduced through lethal mutagenesis. By contrast, sub-lethal hypermutagenesis may contribute to virus evolvability by increasing population diversity. To prevent genome editing, some viruses have evolved proteins that mediate APOBEC3 degradation. The model plant Arabidopsis thaliana encodes for nine cytidine deaminases (AtCDAs), raising the question of whether deamination is an antiviral mechanism in plants as well. Here we tested the effects of AtCDAs expression on the pararetrovirus Cauliflower mosaic virus (CaMV). We show that A. thaliana AtCDA1 gene product exerts a mutagenic activity, which indeed generates a negative correlation between the level of AtCDA1 expression and CaMV accumulation in the plant, suggesting that deamination may also work as an antiviral mechanism in plants.

2014-05-16

Automation and Evaluation of the SOWH Test with SOWHAT

10.1101/005264

Samuel H. Church;Joseph F. Ryan;Casey W. Dunn;

The Swofford-Olsen-Waddell-Hillis (SOWH) test is a method to evaluate incongruent phylogenetic topologies. It is used, for example, when an investigator wishes to know if the maximum likelihood tree recovered in their analysis is significantly different than an alternative phylogenetic hypothesis. The SOWH test compares the observed difference in likelihood between the topologies to a null distribution of differences in likelihood generated by parametric resampling. The SOWH test is a well-established and important phylogenetic method, but it can be difficult to implement and its sensitivity to various factors is not well understood. We wrote SOWHAT, a program that automates the SOWH test. In test analyses, we find that variation in parameter estimation as well as the use of a more complex model of parameter estimation have little impact on results, but that results can be inconsistent when an insufficient number of replicates are used to estimate the null distribution. We provide methods of analyzing the sampling as well as a simple stopping criteria for sufficient bootstrap replicates, which increase the overall reliability of the approach. Applications of the SOWH test should include explicit evaluations of sampling adequacy. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.

2014-05-19

Automation and Evaluation of the SOWH Test with SOWHAT

10.1101/005264

Samuel H. Church;Joseph F. Ryan;Casey W. Dunn;

The Swofford-Olsen-Waddell-Hillis (SOWH) test is a method to evaluate incongruent phylogenetic topologies. It is used, for example, when an investigator wishes to know if the maximum likelihood tree recovered in their analysis is significantly different than an alternative phylogenetic hypothesis. The SOWH test compares the observed difference in likelihood between the topologies to a null distribution of differences in likelihood generated by parametric resampling. The SOWH test is a well-established and important phylogenetic method, but it can be difficult to implement and its sensitivity to various factors is not well understood. We wrote SOWHAT, a program that automates the SOWH test. In test analyses, we find that variation in parameter estimation as well as the use of a more complex model of parameter estimation have little impact on results, but that results can be inconsistent when an insufficient number of replicates are used to estimate the null distribution. We provide methods of analyzing the sampling as well as a simple stopping criteria for sufficient bootstrap replicates, which increase the overall reliability of the approach. Applications of the SOWH test should include explicit evaluations of sampling adequacy. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.

2015-05-07

Automation and Evaluation of the SOWH Test with SOWHAT

10.1101/005264

Samuel H. Church;Joseph F. Ryan;Casey W. Dunn;

The Swofford-Olsen-Waddell-Hillis (SOWH) test is a method to evaluate incongruent phylogenetic topologies. It is used, for example, when an investigator wishes to know if the maximum likelihood tree recovered in their analysis is significantly different than an alternative phylogenetic hypothesis. The SOWH test compares the observed difference in likelihood between the topologies to a null distribution of differences in likelihood generated by parametric resampling. The SOWH test is a well-established and important phylogenetic method, but it can be difficult to implement and its sensitivity to various factors is not well understood. We wrote SOWHAT, a program that automates the SOWH test. In test analyses, we find that variation in parameter estimation as well as the use of a more complex model of parameter estimation have little impact on results, but that results can be inconsistent when an insufficient number of replicates are used to estimate the null distribution. We provide methods of analyzing the sampling as well as a simple stopping criteria for sufficient bootstrap replicates, which increase the overall reliability of the approach. Applications of the SOWH test should include explicit evaluations of sampling adequacy. SOWHAT is available for download from https://github.com/josephryan/SOWHAT.

2015-06-15

Adaptation to a novel predator in Drosophila melanogaster: How well are we able to predict evolutionary responses?

10.1101/005322

Michael DeNieu;William Pitchers;Ian Dworkin;

Evolutionary theory is sufficiently well developed to allow for short-term prediction of evolutionary trajectories. In addition to the presence of heritable variation, prediction requires knowledge of the form of natural selection on relevant traits. While many studies estimate the form of natural selection, few examine the degree to which traits evolve in the predicted direction. In this study we examine the form of natural selection imposed by mantid predation on wing size and shape in the fruitfly, Drosophila melanogaster. We then evolve populations of D. melanogaster under predation pressure, and examine the extent to which wing size and shape have responded in the predicted direction. We demonstrate that wing form partially evolves along the predicted vector from selection, more so than for control lineages. Furthermore, we re-examined phenotypic selection after [~]30 generations of experimental evolution. We observed that the magnitude of selection on wing size and shape was diminished in populations evolving with mantid predators, while the direction of the selection vector differed from that of the ancestral population for shape. We discuss these findings in the context of the predictability of evolutionary responses, and the need for fully multivariate approaches.

2014-05-19

Phylogenetic confidence intervals for the optimal trait value

10.1101/005314

Krzysztof Bartoszek;Serik Sagitov;

We consider a stochastic evolutionary model for a phenotype developing amongst n related species with unknown phylogeny. The unknown tree is modelled by a Yule process conditioned on n contemporary nodes. The trait value is assumed to evolve along lineages as an Ornstein-Uhlenbeck process. As a result, the trait values of the n species form a sample with dependent observations. We establish three limit theorems for the sample mean corresponding to three domains for the adaptation rate. In the case of fast adaptation, we show that for large n the normalized sample mean is approximately normally distributed. Using these limit theorems, we develop novel confidence interval formulae for the optimal trait value.

2014-05-19

Phylogenetic confidence intervals for the optimal trait value

10.1101/005314

Krzysztof Bartoszek;Serik Sagitov;

We consider a stochastic evolutionary model for a phenotype developing amongst n related species with unknown phylogeny. The unknown tree is modelled by a Yule process conditioned on n contemporary nodes. The trait value is assumed to evolve along lineages as an Ornstein-Uhlenbeck process. As a result, the trait values of the n species form a sample with dependent observations. We establish three limit theorems for the sample mean corresponding to three domains for the adaptation rate. In the case of fast adaptation, we show that for large n the normalized sample mean is approximately normally distributed. Using these limit theorems, we develop novel confidence interval formulae for the optimal trait value.

2014-11-10

Ultra fast tissue staining with chemical tags

10.1101/005298

Johannes Kohl;Julian Ng;Sebastian Cachero;Michael-John Dolan;Ben Sutcliffe;Daniel Krüger;Shahar Frechter;Gregory SXE Jefferis;

Genetically encoded fluorescent proteins and immunostainings are widely used to detect cellular or sub-cellular structures in thick biological samples. However, each approach suffers from limitations, including low signal and limited spectral flexibility or slow speed, poor penetration and high background, respectively. Here we overcome these limitations by using transgenically expressed chemical tags for rapid, even and low-background labeling of thick biological tissues. We construct a platform of widely applicable transgenic Drosophila reporter lines, demonstrating that chemical labeling can accelerate staining of whole-mount fly brains by a factor of 100x. Together, this tag-based approach drastically improves the speed and specificity of labeling genetically marked cells in intact and/or thick biological samples.

2014-05-19

Differences in sensitivity to EGFR inhibitors could be explained by described biochemical differences between oncogenic Ras mutants

10.1101/005397

Edward C Stites;

Emerging data suggest different activating Ras mutants may have different biological behaviors. The most striking example may be in colon cancer, where activating KRAS mutations generally indicate a lack of benefit to treatment with EGFR inhibitors, although the activating KRAS G13D mutation appears to be an exception. As KRAS G13D generally shares the same biochemical defects as the other oncogenic KRAS mutants, a mechanism for differential sensitivity is not apparent. Here, a previously developed mathematical model of Ras mutant signaling is used to investigate this problem. The purpose of the analysis is to determine whether differential response is consistent with known mechanisms of Ras signaling, and to determine if any known features of Ras mutants provide an explanation for differential sensitivity. Computational analysis of the mathematical model finds that differential response to upstream inhibition between cancers with different Ras mutants is indeed consistent with known mechanisms of Ras biology. Moreover, model analysis demonstrates that the subtle biochemical differences between G13D and G12D (and G12V) mutants are sufficient to enable differential response to upstream inhibition. Simulations suggest that wild-type Ras within the G13D mutant context is more effectively inhibited by upstream inhibitors than when it is in the G12D or G12V contexts. This difference is a consequence of an elevated Km for the G13D mutant. The identification of a single parameter that influences sensitivity is significant in that it suggests an approach to evaluate other, less common, Ras mutations for their anticipated response to upstream inhibition.

2014-05-21

Sperm should evolve to make female meiosis fair.

10.1101/005363

Yaniv Brandvain;Graham Coop;

Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.

2014-05-21

Sperm should evolve to make female meiosis fair.

10.1101/005363

Yaniv Brandvain;Graham Coop;

Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.

2014-05-22

Sperm should evolve to make female meiosis fair.

10.1101/005363

Yaniv Brandvain;Graham Coop;

Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.

2014-07-28

Sperm should evolve to make female meiosis fair.

10.1101/005363

Yaniv Brandvain;Graham Coop;

Genomic conflicts arise when an allele gains an evolutionary advantage at a cost to organismal fitness. Oogenesis is inherently susceptible to such conflicts because alleles compete for inclusion into the egg. Alleles that distort meiosis in their favor (i.e. meiotic drivers) often decrease organismal fitness, and therefore indirectly favor the evolution of mechanisms to suppress meiotic drive. In this light, many facets of oogenesis and gametogenesis have been interpreted as mechanisms of protection against genomic outlaws. That females of many animal species do not complete meiosis until after fertilization, appears to run counter to this interpretation, because this delay provides an opportunity for sperm-acting alleles to meddle with the outcome of female meiosis and help like alleles drive in heterozygous females. Contrary to this perceived danger, the population genetic theory presented herein suggests that, in fact, sperm nearly always evolve to increase the fairness of female meiosis in the face of genomic conflicts. These results are consistent with the apparent sperm dependence of the best characterized female meiotic drivers in animals. Rather than providing an opportunity for sperm collaboration in female meiotic drive, the fertilization requirement indirectly protects females from meiotic drivers by providing sperm an opportunity to suppress drive.

2014-12-26

IVT-seq reveals extreme bias in RNA-sequencing

10.1101/005371

Nicholas F Lahens;Ibrahim Halil Kavakli;Ray Zhang;Katharina Hayer;Michael B Black;Hannah Dueck;Angel Pizarro;Junhyong Kim;Rafael A Irizarry;Russell S Thomas;Gregory R Grant;John B Hogenesch;

BackgroundRNA sequencing (RNA-seq) is a powerful technique for identifying and quantifying transcription and splicing events, both known and novel. However, given its recent development and the proliferation of library construction methods, understanding the bias it introduces is incomplete but critical to realizing its value.\n\nResultsHere we present a method, in vitro transcription sequencing (IVT-seq), for identifying and assessing the technical biases in RNA-seq library generation and sequencing at scale. We created a pool of > 1000 in vitro transcribed (IVT) RNAs from a full-length human cDNA library and sequenced them with poly-A and total RNA-seq, the most common protocols. Because each cDNA is full length and we show IVT is incredibly processive, each base in each transcript should be equivalently represented. However, with common RNA-seq applications and platforms, we find [~]50% of transcripts have > 2-fold and [~]10% have > 10-fold differences in within-transcript sequence coverage. Strikingly, we also find > 6% of transcripts have regions of high, unpredictable sequencing coverage, where the same transcript varies dramatically in coverage between samples, confounding accurate determination of their expression. To get at causal factors, we used a combination of experimental and computational approaches to show that rRNA depletion is responsible for the most significant variability in coverage and that several sequence determinants also strongly influence representation.\n\nConclusionsIn sum, these results show the utility of IVT-seq in promoting better understanding of bias introduced by RNA-seq and suggest caution in its interpretation. Furthermore, we find that rRNA-depletion is responsible for substantial, unappreciated biases in coverage. Perhaps most importantly, these coverage biases introduced during library preparation suggest exon level expression analysis may be inadvisable.

2014-05-21

Inference of phenotype-defining functional modules of protein families for microbial plant biomass degraders

10.1101/005355

Sebastian Gil Anthony Konietzny;Phillip Byron Pope;Aaron Weimann;Alice Carolyn McHardy;

BackgroundEfficient industrial processes for converting plant lignocellulosic materials into biofuels are a key challenge in global efforts to use alternative energy sources to fossil fuels. Novel cellulolytic enzymes have been discovered from microbial genomes and metagenomes of microbial communities. However, the identification of relevant genes without known homologs, and elucidation of the lignocellulolytic pathways and protein complexes for different microorganisms remain a challenge.\n\nResultsWe describe a new computational method for the targeted discovery of functional modules of plant biomass-degrading protein families based on their co-occurrence patterns across genomes and metagenome datasets, and the strength of association of these modules with the genomes of known degraders. From more than 6.4 million family annotations for 2884 microbial genomes and 332 taxonomic bins from 18 metagenomes, we identified five functional modules that are distinctive for plant biomass degraders, which we call plant biomass degradation modules (PDMs). These modules incorporated protein families involved in the degradation of cellulose, hemicelluloses and pectins, structural components of the cellulosome and additional families with potential functions in plant biomass degradation. The PDMs could be linked to 81 gene clusters in genomes of known lignocellulose degraders, including previously described clusters of lignocellulolytic genes. On average, 70% of the families of each PDM mapped to gene clusters in known degraders, which served as an additional confirmation of their functional relationships. The presence of a PDM in a genome or taxonomic metagenome bin allowed us to predict an organisms ability for plant biomass degradation accurately. For 15 draft genomes of a cow rumen metagenome, we validated by cross-linking with confirmed cellulolytic enzymes that the PDMs identified plant biomass degraders within a complex microbial community.\n\nConclusionsFunctional modules of protein families that realize different aspects of plant cell wall degradation can be inferred from co-occurrence patterns across (meta)genomes with a probabilistic topic model. The PDMs represent a new resource of protein families and candidate genes implicated in microbial plant biomass degradation. They can be used to predict the ability to degrade plant biomass for a genome or taxonomic bin. The method would also be suitable for characterizing other microbial phenotypes.

2014-05-21

The distribution of deleterious genetic variation in human populations

10.1101/005330

Kirk E Lohmueller;

Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, numbers of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load may not differ across populations, and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.

2014-05-21

Inferring human population size and separation history from multiple genome sequences

10.1101/005348

Stephan Schiffels;Richard Durbin;

The availability of complete human genome sequences from populations across the world has given rise to new population genetic inference methods that explicitly model their ancestral relationship under recombination and mutation. So far, application of these methods to evolutionary history more recent than 20-30 thousand years ago and to population separations has been limited. Here we present a new method that overcomes these shortcomings. The Multiple Sequentially Markovian Coalescent (MSMC) analyses the observed pattern of mutations in multiple individuals, focusing on the first coalescence between any two individuals. Results from applying MSMC to genome sequences from nine populations across the world suggest that the genetic separation of non-African ancestors from African Yoruban ancestors started long before 50,000 years ago, and give information about human population history as recently as 2,000 years ago, including the bottleneck in the peopling of the Americas, and separations within Africa, East Asia and Europe.

2014-05-21

Inferring human population size and separation history from multiple genome sequences

10.1101/005348

Stephan Schiffels;Richard Durbin;

The availability of complete human genome sequences from populations across the world has given rise to new population genetic inference methods that explicitly model their ancestral relationship under recombination and mutation. So far, application of these methods to evolutionary history more recent than 20-30 thousand years ago and to population separations has been limited. Here we present a new method that overcomes these shortcomings. The Multiple Sequentially Markovian Coalescent (MSMC) analyses the observed pattern of mutations in multiple individuals, focusing on the first coalescence between any two individuals. Results from applying MSMC to genome sequences from nine populations across the world suggest that the genetic separation of non-African ancestors from African Yoruban ancestors started long before 50,000 years ago, and give information about human population history as recently as 2,000 years ago, including the bottleneck in the peopling of the Americas, and separations within Africa, East Asia and Europe.

2014-05-23

LIMIX: genetic analysis of multiple traits

10.1101/003905

Christoph Lippert;Francesco Paolo Casale;Barbara Rakitsch;Oliver Stegle;

Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to flexibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix.

2014-05-21

LIMIX: genetic analysis of multiple traits

10.1101/003905

Christoph Lippert;Francesco Paolo Casale;Barbara Rakitsch;Oliver Stegle;

Multi-trait mixed models have emerged as a promising approach for joint analyses of multiple traits. In principle, the mixed model framework is remarkably general. However, current methods implement only a very specific range of tasks to optimize the necessary computations. Here, we present a multi-trait modeling framework that is versatile and fast: LIMIX enables to flexibly adapt mixed models for a broad range of applications with different observed and hidden covariates, and variable study designs. To highlight the novel modeling aspects of LIMIX we performed three vastly different genetic studies: joint GWAS of correlated blood lipid phenotypes, joint analysis of the expression levels of the multiple transcript-isoforms of a gene, and pathway-based modeling of molecular traits across environments. In these applications we show that LIMIX increases GWAS power and phenotype prediction accuracy, in particular when integrating stepwise multi-locus regression into multi-trait models, and when analyzing large numbers of traits. An open source implementation of LIMIX is freely available at: https://github.com/PMBio/limix.

2014-05-22

Profiling direct mRNA-microRNA interactions using synthetic biotinylated microRNA-duplexes

10.1101/005439

Shivangi Wani;Nicole Cloonan;

MicroRNAs (miRNAs) are predominantly negative regulators of gene expression that act through the RNA-induced Silencing Complex (RISC) to suppress the translation of protein coding mRNAs. Despite intense study of these regulatory molecules, the specific molecular functions of most miRNAs remain unknown, largely due to the challenge of accurately identifying miRNA targets. Reporter gene assays can determine direct interactions, but are laborious and do not scale to genome-wide screens. Genomic scale methods such as HITS-CLIP do not preserve the direct interactions, and rely on computationally derived predictions of interactions that are plagued by high false positive rates. Here we describe a protocol for the isolation of direct targets of a mature miRNA, using synthetic biotinylated miRNA duplexes. This approach allows sensitive and specific detection of miRNA-mRNA interactions, isolating high quality mRNA suitable for analysis by microarray or RNAseq.

2014-05-22

A genome-wide analysis of Cas9 binding specificity using ChIP-seq and targeted sequence capture

10.1101/005413

Henriette O'Geen;Isabelle M. Henry;Mital S. Bhakta;Joshua F. Meckler;David J. Segal;

Clustered regularly interspaced short palindromic repeat (CRISPR) RNA-guided nucleases have gathered considerable excitement as a tool for genome engineering. However, questions remain about the specificity of their target site recognition. Most previous studies have examined predicted off-target binding sites that differ from the perfect target site by one to four mismatches, which represent only a subset of genomic regions. Here, we use ChIP-seq to examine genome-wide CRISPR binding specificity at gRNA-specific and gRNA-independent sites. For two guide RNAs targeting the murine Snurf gene promoter, we observed very high binding specificity at the intended target site while off-target binding was observed at 2- to 6-fold lower intensities. We also identified significant gRNA-independent off-target binding. Interestingly, we found that these regions are highly enriched in the PAM site, a sequence required for target site recognition by CRISPR. To determine the relationship between Cas9 binding and endonuclease activity, we used targeted sequence capture as a high-throughput approach to survey a large number of the potential off-target sites identified by ChIP-seq or computational prediction. A high frequency of indels was observed at both target sites and one off-target site, while no cleavage activity could be detected at other ChIP-bound regions. Our data is consistent with recent finding that most interactions between the CRISPR nuclease complex and genomic PAM sites are transient and do not lead to DNA cleavage. The interactions are stabilized by gRNAs with good matches to the target sequence adjacent to the PAM site, resulting in target cleavage activity.

2014-05-22

Powerful tests for multi-marker association analysis using ensemble learning

10.1101/005405

Badri Padhukasahasram;Chandan K Reddy;L. Keoki Williams;

Multi-marker approaches are currently gaining a lot of interest in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene and pathway based association tests are increasingly being viewed as useful complements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants. A major drawback of single-marker based methods is that they do not consider pairwise and higher-order interactions between genetic variants. Here, we describe novel tests for multi-marker association analyses that are based on phenotype predictions obtained from machine learning algorithms. Instead of utilizing only a linear or logistic regression model, we propose the use of ensembles of diverse machine learning algorithms for constructing such association tests. As the true mathematical relationship between a phenotype and any group of genetic and clinical variables is unknown in advance and may be complex, such a strategy gives us a general and flexible framework to approximate this relationship across different sets of SNPs. We show how phenotype prediction obtained from ensemble learning algorithms can be used for constructing tests for the joint association of multiple variants. We first apply our method to simulated datasets to demonstrate its power and correctness. Then, we apply our method to previously studied asthma-related genes in two independent asthma cohorts to conduct association tests.

2014-05-23

Powerful tests for multi-marker association analysis using ensemble learning

10.1101/005405

Badri Padhukasahasram;Chandan K Reddy;L. Keoki Williams;

Multi-marker approaches are currently gaining a lot of interest in genome wide association studies and can enhance power to detect new associations under certain conditions. Gene and pathway based association tests are increasingly being viewed as useful complements to the more widely used single marker association analysis which have successfully uncovered numerous disease variants. A major drawback of single-marker based methods is that they do not consider pairwise and higher-order interactions between genetic variants. Here, we describe novel tests for multi-marker association analyses that are based on phenotype predictions obtained from machine learning algorithms. Instead of utilizing only a linear or logistic regression model, we propose the use of ensembles of diverse machine learning algorithms for constructing such association tests. As the true mathematical relationship between a phenotype and any group of genetic and clinical variables is unknown in advance and may be complex, such a strategy gives us a general and flexible framework to approximate this relationship across different sets of SNPs. We show how phenotype prediction obtained from ensemble learning algorithms can be used for constructing tests for the joint association of multiple variants. We first apply our method to simulated datasets to demonstrate its power and correctness. Then, we apply our method to previously studied asthma-related genes in two independent asthma cohorts to conduct association tests.

2014-06-13

Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture

10.1101/005470

Homayun Mehrabani;Neil Ray;Kyle Tse;Dennis Evangelista;

Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g. Antarctic anchor ice), or in environments with moisture and cold air (e.g. plants, intertidal) begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We screened biological and artifical samples for ice formation and accretion in submerged conditions using previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. It appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri) slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli). The geometric dimensions of the features have only a small ([~]6%) effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and coatings, and their interaction with surface pattern.

2014-05-24

Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture

10.1101/005470

Homayun Mehrabani;Neil Ray;Kyle Tse;Dennis Evangelista;

Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g. Antarctic anchor ice), or in environments with moisture and cold air (e.g. plants, intertidal) begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We screened biological and artifical samples for ice formation and accretion in submerged conditions using previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. It appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri) slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli). The geometric dimensions of the features have only a small ([~]6%) effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and coatings, and their interaction with surface pattern.

2014-06-26

The methylome of the human frontal cortex across development

10.1101/005504

Andrew E Jaffe;Yuan Gao;Ran Tao;Thomas M Hyde;Daniel R Weinberger;Joel E Kleinman;

DNA methylation (DNAm) plays an important role in epigenetic regulation of gene expression, orchestrating tissue differentiation and development during all stages of mammalian life. This epigenetic control is especially important in the human brain, with extremely dynamic gene expression during fetal and infant life, and becomes progressively more stable at later periods of development. We characterized the epigenetic state of the developing and aging human frontal cortex in post-mortem tissue from 351 individuals across the lifespan using the Illumina 450k DNA methylation microarray. The largest changes in the methylome occur at birth at varying spatial resolutions - we identify 359,087 differentially methylated loci, which form 23,732 significant differentially methylated regions (DMRs). There were also 298 regions of long-range changes in DNAm, termed \"blocks\", associated with birth that strongly overlap previously published colon cancer \"blocks\". We then identify 55,439 DMRs associated with development and aging, of which 61.9% significantly associate with nearby gene expression levels. Lastly, we find enrichment of genomic loci of risk for schizophrenia and several other common diseases among these developmental DMRs. These data, integrated with existing genetic and transcriptomic data, create a rich genomic resource across brain development.

2014-05-26

The methylome of the human frontal cortex across development

10.1101/005504

Andrew E Jaffe;Yuan Gao;Ran Tao;Thomas M Hyde;Daniel R Weinberger;Joel E Kleinman;

DNA methylation (DNAm) plays an important role in epigenetic regulation of gene expression, orchestrating tissue differentiation and development during all stages of mammalian life. This epigenetic control is especially important in the human brain, with extremely dynamic gene expression during fetal and infant life, and becomes progressively more stable at later periods of development. We characterized the epigenetic state of the developing and aging human frontal cortex in post-mortem tissue from 351 individuals across the lifespan using the Illumina 450k DNA methylation microarray. The largest changes in the methylome occur at birth at varying spatial resolutions - we identify 359,087 differentially methylated loci, which form 23,732 significant differentially methylated regions (DMRs). There were also 298 regions of long-range changes in DNAm, termed \"blocks\", associated with birth that strongly overlap previously published colon cancer \"blocks\". We then identify 55,439 DMRs associated with development and aging, of which 61.9% significantly associate with nearby gene expression levels. Lastly, we find enrichment of genomic loci of risk for schizophrenia and several other common diseases among these developmental DMRs. These data, integrated with existing genetic and transcriptomic data, create a rich genomic resource across brain development.

2014-05-27

Alternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis

10.1101/005546

Matteo Carrara;Josephine Lum;Francesca Cordero;Marco Beccuti;Michael Poidinger;Susanna Donatelli;Raffaele A Calogero;Francesca Zolezzi;

BackgroundRNAseq provides remarkable power in the area of biomarkers discovery and disease stratification. The main technical steps affecting the results of RNAseq experiments are Library Sample Preparation (LSP) and Bioinformatics Analysis (BA). At the best of our knowledge, a comparative evaluation of the combined effect of LSP and BA was never considered and it might represent a valuable knowledge to optimize alternative splicing detection, which is a challenging task due to moderate fold change differences to be detected within a complex isoforms background.\n\nResultsDifferent LSPs (TruSeq unstranded/stranded, ScriptSeq, NuGEN) allow the detection of a large common set of isoforms. However, each LSP also detects a smaller set of isoforms, which are characterized both by lower coverage and lower FPKM than that observed for the common ones among LSPs. This characteristic is particularly critical in case of low input RNA NuGEN v2 LSP.\n\nThe effect on statistical detection of alternative splicing considering low input LSP (NuGEN v2) with respect to high input LSP (TruSeq) on statistical detection of alternative splicing was studied using a benchmark dataset, in which both synthetic reads and reads generated from high (TruSeq) and low input (NuGEN) LSPs were spiked-in. Statistical detection of alternative splicing (AltDE) was done using prototypes of BA for isoform-reconstruction (Cuffdiff) and exon-level analysis (DEXSeq). Exon-level analysis performs slightly better than isoform-reconstruction approach although at most only 50% of the spiked-in transcripts are detected. Both isoform-reconstruction and exon-level analysis performances improve by rising the number of input reads.\n\nConclusionData, derived from NuGEN v2, are not the ideal input for AltDE, specifically when exon-level approach is used. It is notable that ribosomal depletion, with respect to polyA+ selection, reduces the amount of coding mappable reads resulting detrimental in the case of AltDE. Furthermore, we observed that both isoform-reconstruction and exon-level analysis performances are strongly dependent on the number of input reads.

2014-05-26

Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences

10.1101/005462

Vincenza Colonna;Qasim Ayub;Yuan Chen;Luca Pagani;Pierre Luisi;Marc Pybus;Erik Garrison;Yali Xue;Chris Tyler-Smith;

BackgroundPopulation differentiation has proved to be effective for identifying loci under geographically-localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes.\n\nResultsWe demonstrate that while sites of low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively.\n\nConclusionsWe have identified known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.

2014-05-23

Human genomic regions with exceptionally high or low levels of population differentiation identified from 911 whole-genome sequences

10.1101/005462

Vincenza Colonna;Qasim Ayub;Yuan Chen;Luca Pagani;Pierre Luisi;Marc Pybus;Erik Garrison;Yali Xue;Chris Tyler-Smith;

BackgroundPopulation differentiation has proved to be effective for identifying loci under geographically-localized positive selection, and has the potential to identify loci subject to balancing selection. We have previously investigated the pattern of genetic differentiation among human populations at 36.8 million genomic variants to identify sites in the genome showing high frequency differences. Here, we extend this dataset to include additional variants, survey sites with low levels of differentiation, and evaluate the extent to which highly differentiated sites are likely to result from selective or other processes.\n\nResultsWe demonstrate that while sites of low differentiation represent sampling effects rather than balancing selection, sites showing extremely high population differentiation are enriched for positive selection events and that one half may be the result of classic selective sweeps. Among these, we rediscover known examples, where we actually identify the established functional SNP, and discover novel examples including the genes ABCA12, CALD1 and ZNF804, which we speculate may be linked to adaptations in skin, calcium metabolism and defense, respectively.\n\nConclusionsWe have identified known and many novel candidate regions for geographically restricted positive selection, and suggest several directions for further research.

2014-05-27

Differential stoichiometry among core ribosomal proteins

10.1101/005553

Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;

Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.

2014-05-26

Differential stoichiometry among core ribosomal proteins

10.1101/005553

Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;

Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.

2015-01-28

Differential stoichiometry among core ribosomal proteins

10.1101/005553

Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;

Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.

2015-07-20

Differential stoichiometry among core ribosomal proteins

10.1101/005553

Nikolai Slavov;Stefan Semrau;Edoardo Airoldi;Bogdan Budnik;Alexander van Oudenaarden;

Understanding the regulation and structure of ribosomes is essential to understanding protein synthesis and its dysregulation in disease. While ribosomes are believed to have a fixed stoichiometry among their core ribosomal proteins (RPs), some experiments suggest a more variable composition. Testing such variability requires direct and precise quantification of RPs. We used mass-spectrometry to directly quantify RPs across monosomes and polysomes of mouse embryonic stem cells (ESC) and budding yeast. Our data show that the stoichiometry among core RPs in wild-type yeast cells and ESC depends both on the growth conditions and on the number of ribosomes bound per mRNA. Furthermore, we find that the fitness of cells with a deleted RP-gene is inversely proportional to the enrichment of the corresponding RP in polysomes. Together, our findings support the existence of ribosomes with distinct protein composition and physiological function.

2015-09-19

Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

10.1101/005587

Ramon Diaz-Uriarte;

Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.

2014-05-27

Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

10.1101/005587

Ramon Diaz-Uriarte;

Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.

2014-06-03

Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

10.1101/005587

Ramon Diaz-Uriarte;

Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.

2014-06-12

Inferring restrictions in the temporal order of mutations during tumor progression: effects of passengers, evolutionary models, and sampling

10.1101/005587

Ramon Diaz-Uriarte;

Cancer progression is caused by the sequential accumulation of mutations, but not all orders of accumulation of mutations are equally likely. When the fixation of some mutations depends on the presence of previous ones, identifying restrictions in the order of accumulation of mutations can lead to the discovery of therapeutic targets and diagnostic markers. Using simulated data sets, I conducted a comprehensive comparison of the performance of all available methods to identify these restrictions from cross-sectional data. In contrast to previous work, I embedded restrictions within evolutionary models of tumor progression that included passengers (mutations not responsible for the development of cancer, known to be very common). This allowed me to asses the effects of having to filter out passengers, of sampling schemes, and of deviations from order restrictions. Poor choices of method, filtering, and sampling lead to large errors in all performance metrics. Having to filter passengers lead to decreased performance, especially because true restrictions were missed. Overall, the best method for identifying order restrictions were Oncogenetic Trees, a fast and easy to use method that, although unable to recover dependencies of mutations on more than one mutation, showed good performance in most scenarios, superior to Conjunctive Bayesian Networks and Progression Networks. Single cell sampling provided no advantage, but sampling in the final stages of the disease vs. sampling at different stages had severe effects. Evolutionary model and deviations from order restrictions had major, and sometimes counterintuitive, interactions with other factors that affected performance. This paper provides practical recommendations for using these methods with experimental data. Moreover, it shows that it is both possible and necessary to embed assumptions about order restrictions and the nature of driver status within evolutionary models of cancer progression to evaluate the performance of inferential approaches.

2014-06-22

Dynamics of a combined medea-underdominant population transformation system

10.1101/005512

Chaitanya Gokhale;Richard Guy Reeves;Floyd A Reed;

BackgroundTransgenic constructs intended to be stably established at high frequencies in wild populations have been demonstrated to \"drive\" from low frequencies in experimental insect populations. Linking such population transformation constructs to genes which render them unable to transmit pathogens could eventually be used to stop the spread of vector-borne diseases like malaria and dengue.\n\nResultsGenerally, population transformation constructs with only a single transgenic drive mechanism have been envisioned. Using a theoretical modelling approach we describe the predicted properties of a construct combining autosomal Medea and underdominant population transformation systems. We show that when combined they can exhibit synergistic properties which in broad circumstances surpass those of the single systems.\n\nConclusionWith combined systems, intentional population transformation and its reversal can be achieved readily. Combined constructs also enhance the capacity to geographically restrict transgenic constructs to targeted populations. It is anticipated that these properties are likely to be of particular value in attracting regulatory approval and public acceptance of this novel technology.

2014-05-27

Dynamics of a combined medea-underdominant population transformation system

10.1101/005512

Chaitanya Gokhale;Richard Guy Reeves;Floyd A Reed;

BackgroundTransgenic constructs intended to be stably established at high frequencies in wild populations have been demonstrated to \"drive\" from low frequencies in experimental insect populations. Linking such population transformation constructs to genes which render them unable to transmit pathogens could eventually be used to stop the spread of vector-borne diseases like malaria and dengue.\n\nResultsGenerally, population transformation constructs with only a single transgenic drive mechanism have been envisioned. Using a theoretical modelling approach we describe the predicted properties of a construct combining autosomal Medea and underdominant population transformation systems. We show that when combined they can exhibit synergistic properties which in broad circumstances surpass those of the single systems.\n\nConclusionWith combined systems, intentional population transformation and its reversal can be achieved readily. Combined constructs also enhance the capacity to geographically restrict transgenic constructs to targeted populations. It is anticipated that these properties are likely to be of particular value in attracting regulatory approval and public acceptance of this novel technology.

2014-05-28

Reconstructing Austronesian population history in Island Southeast Asia

10.1101/005603

Mark Lipson;Po-Ru Loh;Nick Patterson;Priya Moorjani;Ying-Chin Ko;Mark Stoneking;Bonnie Berger;David Reich;

Austronesian languages are spread across half the globe, from Easter Island to Madagascar. Evidence from linguistics and archaeology indicates that the \"Austronesian expansion,\" which began 4-5 thousand years ago, likely had roots in Taiwan, but the ancestry of present-day Austronesian-speaking populations remains controversial. Here, focusing primarily on Island Southeast Asia, we analyze genome-wide data from 56 populations using new methods for tracing ancestral gene flow. We show that all sampled Austronesian groups harbor ancestry that is more closely related to aboriginal Taiwanese than to any present-day mainland population. Surprisingly, western Island Southeast Asian populations have also inherited ancestry from a source nested within the variation of present-day populations speaking Austro-Asiatic languages, which have historically been nearly exclusive to the mainland. Thus, either there was once a substantial Austro-Asiatic presence in Island Southeast Asia, or Austronesian speakers migrated to and through the mainland, admixing there before continuing to western Indonesia.

2014-05-27

Novel Natural Product Discovery from Marine Sponges and their Obligate Symbiotic Organisms

10.1101/005454

Regina Monaco;Rena Quinlan;

Discovery of novel natural products is an accepted method for the elucidation of pharmacologically active molecules and drug leads. Best known sources for such discovery have been terrestrial plants and microbes, accounting for about 85% of the approved natural products in pharmaceutical use (1), and about 60% of approved pharmaceuticals and new drug applications annually (2). Discovery in the marine environment has lagged due to the difficulty of exploration in this ecological niche. Exploration began in earnest in the 1950s, after technological advances such as scuba diving allowed collection of marine organisms, primarily at a depth to about 15m.\n\nNatural products from filter feeding marine invertebrates and in particular, sponges, have proven to be a rich source of structurally unique pharmacologically active compounds, with over 16,000 molecules isolated thus far (3, 1) and a continuing pace of discovery at hundreds of novel bioactive molecules per year. All classes of pharmaceuticals have been represented in this discovery process, including antiprotazoals, pesticides, TGF-beta inhibitors, cationic channel blockers, anticancer, cytotoxic, antiviral, anti-inflammatory and antibacterial compounds. Important biosynthetic pathways found in sponges which give rise to these compounds include the terpenoid (4), fatty acid, polyketoid, quinone reductase, alkaloid, isoprenoid (5), and non-ribosomal protein synthase pathways.

2014-05-24

Hip and knee kinematics display complex and time-varying sagittal kinematics during repetitive stepping: Implications for design of a functional fatigue model of the knee extensors and flexors

10.1101/005538

Corey Scholes;Michael McDonald;Anthony Parker;

The validity of fatigue protocols involving multi-joint movements, such as stepping, has yet to be clearly defined. Although surface electromyography can monitor the fatigue state of individual muscles, the effects of joint angle and velocity variation on signal parameters are well established. Therefore, the aims of this study were to i) describe sagittal hip and knee kinematics during repetitive stepping ii) identify periods of high inter-trial variability and iii) determine within-test reliability of hip and knee kinematic profiles. A group of healthy men (N = 15) ascended and descended from a knee-high platform wearing a weighted vest (10%BW) for 50 consecutive trials. The hip and knee underwent rapid flexion and extension during step ascent and descent. Variability of hip and knee velocity peaked between 20-40% of the ascent phase and 80-100% of the descent. Significant (p<0.05) reductions in joint range of motion and peak velocity during step ascent were observed, while peak flexion velocity increased during descent. Healthy individuals use complex hip and knee motion to negotiate a knee-high step with kinematic patterns varying across multiple repetitions. These findings have important implications for future studies intending to use repetitive stepping as a fatigue model for the knee extensors and flexors.

2014-05-26

Different profile of transcriptome between wheat Yunong 201 and its high-yield mutant Yunong 3114

10.1101/005496

Feng Chen;Zhongdong Dong;Ning Zhang;Xiangfen Zhang;Dangqun Cui;

Wheat is one of the most important crops in the world. With the exponentially increasing population and the need for ever increased food and feed production, an increased yield of wheat grain (as well as rice, maize and other grains) will be critical. Modern technologies are utilized to assist breeding programs. Such as the transcriptome sequencing, which greatly improves our genetic understanding, provides a platform for functional genomics research on crops. Herein, to get an overview of transcriptome characteristics of Yunong 3114, which is screened from the EMS mutagenized population of, a high quality Chinese winter noodle wheat, due to its different plant architecture as well as larger kernel size and higher grain weight, a high-throughput RNA sequencing based on next generation sequencing technology (Illumina) were performed. These unigenes were annotated by Blastx alignment against the NCBI non-redundant (nr), Clusters of orthologous groups (COG), gene orthology (GO), and the Kyoto Encyclopedia of Genesand Genomes (KEGG) databases. The 90.96% of the unigenes matched with protein in the NCBI nr database. Functional analysis identified that changes in several GO categories, including recognition of pollen, apoptotic process, defense response, receptor activity, protein kinase activity, DNA integration and so forth, played crucial roles in the high-yield characteristics of the mutant. Real-time PCR analysis revealed that the recognition of pollen related gene GsSRK is significantly up-regulated in Yunong 3114. In addition, alternative splicing (AS) analysis results indicated that mutation influence AS ratio, especially the retained introns, including the pollen related genes. Furthermore, the digital gene expression spectrum (DGE) profiling data provides comprehensive information at the transcriptional level that facilitates our understanding of the molecular mechanisms of various physiological aspects including development and high-yield of wheat. Together, these studies substantially increase our knowledge of potential genes and pathways for the genetic improvement of wheat and provide new insights into the yield and breeding strategies.

2014-05-27

A comparative study of techniques for differential expression analysis on RNA-Seq data

10.1101/005611

Zong Hong Zhang;Dhanisha J. Jhaveri;Vikki M. Marshall;Denis C. Bauer;Janette Edson;Ramesh K. Narayanan;Gregory J. Robinson;Andreas E. Lundberg;Perry F. Bartlett;Naomi R. Wray;Qiongyi Zhao;

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes (DEGs) between treatment groups based on RNA-Seq data. However, there is a lack of consensus on how to approach an optimal study design and choice of suitable software for the analysis. In this comparative study we evaluate the performance of three of the most frequently used software tools: Cufflinks-Cuffdiff2, DESeq and edgeR. A number of important parameters of RNA-Seq technology were taken into consideration, including the number of replicates, sequencing depth, and balanced vs. unbalanced sequencing depth within and between groups. We benchmarked results relative to sets of DEGs identified through either quantitative RT-PCR or microarray. We observed that edgeR performs slightly better than DESeq and Cuffdiff2 in terms of the ability to uncover true positives. Overall, DESeq or taking the intersection of DEGs from two or more tools is recommended if the number of false positives is a major concern in the study. In other circumstances, edgeR is slightly preferable for differential expression analysis at the expense of potentially introducing more false positives.

2014-05-28

Lighter: fast and memory-efficient error correction without counting

10.1101/005579

Li Song;Liliana Florea;Ben Langmead;

Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.

2014-05-27

Lighter: fast and memory-efficient error correction without counting

10.1101/005579

Li Song;Liliana Florea;Ben Langmead;

Lighter is a fast, memory-efficient tool for correcting sequencing errors. Lighter avoids counting k-mers. Instead, it uses a pair of Bloom filters, one holding a sample of the input k-mers and the other holding k-mers likely to be correct. As long as the sampling fraction is adjusted in inverse proportion to the depth of sequencing, Bloom filter size can be held constant while maintaining near-constant accuracy. Lighter is parallelized, uses no secondary storage, and is both faster and more memory-efficient than competing approaches while achieving comparable accuracy.

2014-08-07

Artificially inducing close apposition of endoplasmic reticulum and mitochondria induces mitochondrial fragmentation.

10.1101/005645

Victoria J Miller;David J Stephens;

Cycles of mitochondrial fission and fission are essential for normal cell physiology. Defects in the machinery controlling these processes lead to neurodegenerative disease. While we are beginning to understand the machinery that drives fission, our knowledge of the spatial and temporal control of this event is lacking. Here we use a rapamycin-inducible heterodimerization system comprising both ER and mitochondrial transmembrane components to bring the ER membrane into close physical proximity with mitochondria. We show that this artificial apposition of membranes is sufficient to cause rapid mitochondrial fragmentation. Resulting mitochondrial fragments are shown to be distinct entities using fluorescence recovery after photobleaching. We also show that these fragments retain a mitochondrial membrane potential. In contrast, inducible tethering of the peripheral ER exit site protein TFG does not cause mitochondrial fragmentation suggesting that very close apposition of the two membranes is required.

2014-05-28

Cis-regulatory elements and human evolution

10.1101/005652

Adam Siepel;Leonardo Arbiza;

Modification of gene regulation has long been considered an important force in human evolution, particularly through changes to cis-regulatory elements (CREs) that function in transcriptional regulation. For decades, however, the study of cis-regulatory evolution was severely limited by the available data. New data sets describing the locations of CREs and genetic variation within and between species have now made it possible to study CRE evolution much more directly on a genome-wide scale. Here, we review recent research on the evolution of CREs in humans based on large-scale genomic data sets. We consider inferences based on primate divergence,human polymorphism, and combinations of divergence and polymorphism. We then consider "new frontiers" in this field stemming from recent research on transcriptional regulation.

2014-05-28

Quantifying the effects of anagenetic and cladogenetic evolution

10.1101/005561

Krzysztof Bartoszek;

An ongoing debate in evolutionary biology is whether phenotypic change occurs predominantly around the time of speciation or whether it instead accumulates gradually over time. In this work I propose a general framework incorporating both types of change, quantify the effects of speciational change via the correlation between species and attribute the proportion of change to each type. I discuss results of parameter estimation of Hominoid body size in this light. I derive mathematical formulae related to this problem, the probability generating functions of the number of speciation events along a randomly drawn lineage and from the most recent common ancestor of two randomly chosen tip species for a conditioned Yule tree. Additionally I obtain in closed form the variance of the distance from the root to the most recent common ancestor of two randomly chosen tip species.

2014-05-28

Quantifying the effects of anagenetic and cladogenetic evolution

10.1101/005561

Krzysztof Bartoszek;

An ongoing debate in evolutionary biology is whether phenotypic change occurs predominantly around the time of speciation or whether it instead accumulates gradually over time. In this work I propose a general framework incorporating both types of change, quantify the effects of speciational change via the correlation between species and attribute the proportion of change to each type. I discuss results of parameter estimation of Hominoid body size in this light. I derive mathematical formulae related to this problem, the probability generating functions of the number of speciation events along a randomly drawn lineage and from the most recent common ancestor of two randomly chosen tip species for a conditioned Yule tree. Additionally I obtain in closed form the variance of the distance from the root to the most recent common ancestor of two randomly chosen tip species.

2014-11-10

Extensive Regulation of Metabolism and Growth during the Cell Division Cycle

10.1101/005629

Nikolai Slavov;David Botstein;Amy Caudy;

Yeast cells grown in culture can spontaneously synchronize their respiration, metabolism, gene expression and cell division. Such metabolic oscillations in synchronized cultures reflect single-cell oscillations, but the relationship between the oscillations in single cells and synchronized cultures is poorly understood. To understand this relationship and the coordination between metabolism and cell division, we collected and analyzed DNA-content, gene-expression and physiological data, at hundreds of time-points, from cultures metabolically-synchronized at different growth rates, carbon sources and biomass densities. The data enabled us to extend and generalize our mechanistic model, based on ensemble average over phases (EAP), connecting the population-average gene-expression of asynchronous cultures to the gene-expression dynamics in the single-cells comprising the cultures. The extended model explains the carbon-source specific growth-rate responses of hundreds of genes. Our physiological data demonstrate that the frequency of metabolic cycling in synchronized cultures increases with the biomass density, suggesting that this cycling is an emergent behavior, resulting from the entraining of the single-cell metabolic cycle by a quorum-sensing mechanism, and thus underscoring the difference between metabolic cycling in single cells and in synchronized cultures. Measurements of constant levels of residual glucose across metabolically synchronized cultures indicate that storage carbohydrates are required to fuel not only the G1/S transition of the division cycle but also the metabolic cycle. Despite the large variation in profiled conditions and in the scale of their dynamics, most genes preserve invariant dynamics of coordination with each other and with the rate of oxygen consumption. Similarly, the G1/S transition always occurs at the beginning, middle or end of the high oxygen consumption phases, analogous to observations in human and drosophila cells. These results highlight evolutionary conserved coordination among metabolism, cell growth and division.

2014-05-28

Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia

10.1101/005637

Simone Ecker;Vera Pancaldi;Daniel Rico;Alfonso Valencia;

BackgroundChronic Lymphocytic Leukemia (CLL) presents two subtypes which have drastically different clinical outcomes. So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.\n\nResultsWe propose to use gene expression variability across patients to investigate differences between the two CLL subtypes. We find that the most aggressive type of this disease shows higher variability of gene expression across patients and we elaborate on this observation to produce a method that classifies patients into clinical subtypes. Finally, we find that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication, probably related to faster progression of this disease subtype.\n\nConclusionsThere are strong relations between disease subtype and gene expression variability linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

2014-05-29

Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia

10.1101/005637

Simone Ecker;Vera Pancaldi;Daniel Rico;Alfonso Valencia;

BackgroundChronic Lymphocytic Leukemia (CLL) presents two subtypes which have drastically different clinical outcomes. So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.\n\nResultsWe propose to use gene expression variability across patients to investigate differences between the two CLL subtypes. We find that the most aggressive type of this disease shows higher variability of gene expression across patients and we elaborate on this observation to produce a method that classifies patients into clinical subtypes. Finally, we find that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication, probably related to faster progression of this disease subtype.\n\nConclusionsThere are strong relations between disease subtype and gene expression variability linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

2014-07-09

Higher gene expression variability in the more aggressive subtype of chronic lymphocytic leukemia

10.1101/005637

Simone Ecker;Vera Pancaldi;Daniel Rico;Alfonso Valencia;

BackgroundChronic Lymphocytic Leukemia (CLL) presents two subtypes which have drastically different clinical outcomes. So far, these two subtypes are not associated to clear differences in gene expression profiles. Interestingly, recent results have highlighted important roles for heterogeneity, both at the genetic and at the epigenetic level in CLL progression.\n\nResultsWe propose to use gene expression variability across patients to investigate differences between the two CLL subtypes. We find that the most aggressive type of this disease shows higher variability of gene expression across patients and we elaborate on this observation to produce a method that classifies patients into clinical subtypes. Finally, we find that, overall, genes that show higher variability in the aggressive subtype are related to cell cycle, development and inter-cellular communication, probably related to faster progression of this disease subtype.\n\nConclusionsThere are strong relations between disease subtype and gene expression variability linking significantly increased expression variability to phenotypes such as aggressiveness and resistance to therapy in CLL.

2014-09-03

Cancer-associated recurrent mutations in RNase III domains of DICER1

10.1101/005686

Bülent Arman Aksoy;Anders Jacobsen;Robert J Fieldhouse;William Lee;Emek Demir;Giovanni Ciriello;Nikolaus Schultz;Debora S Marks;Chris Sander;

Mutations in the RNase IIIb domain of DICER1 are known to disrupt processing of 5p-strand pre-miRNAs and these mutations have previously been associated with cancer. Using data from the Cancer Genome Atlas project, we show that these mutations are recurrent across four cancer types and that a previously uncharacterized recurrent mutation in the adjacent RNase IIIa domain also disrupts 5p-strand miRNA processing. Analysis of the downstream effects of the resulting imbalance 5p/3p shows a statistically significant effect on the expression of mRNAs targeted by major conserved miRNA families. In summary, these mutations in DICER1 lead to an imbalance in miRNA strands, which has an effect on mRNA transcript levels that appear to contribute to the oncogenesis.

2014-05-29

Cancer-associated recurrent mutations in RNase III domains of DICER1

10.1101/005686

Bülent Arman Aksoy;Anders Jacobsen;Robert J Fieldhouse;William Lee;Emek Demir;Giovanni Ciriello;Nikolaus Schultz;Debora S Marks;Chris Sander;

Mutations in the RNase IIIb domain of DICER1 are known to disrupt processing of 5p-strand pre-miRNAs and these mutations have previously been associated with cancer. Using data from the Cancer Genome Atlas project, we show that these mutations are recurrent across four cancer types and that a previously uncharacterized recurrent mutation in the adjacent RNase IIIa domain also disrupts 5p-strand miRNA processing. Analysis of the downstream effects of the resulting imbalance 5p/3p shows a statistically significant effect on the expression of mRNAs targeted by major conserved miRNA families. In summary, these mutations in DICER1 lead to an imbalance in miRNA strands, which has an effect on mRNA transcript levels that appear to contribute to the oncogenesis.

2014-09-12

Practopoiesis: Or how life fosters a mind

10.1101/005660

Danko Nikolic;

The mind is a biological phenomenon. Thus, biological principles of organization should also be the principles underlying mental operations. Practopoiesis states that the key for achieving intelligence through adaptation is an arrangement in which mechanisms laying a lower level of organization, by their operations and interaction with the environment, enable creation of mechanisms lying at a higher level of organization. When such an organizational advance of a system occurs, it is called a traverse. A case of traverse is when plasticity mechanisms (at a lower level of organization), by their operations, create a neural network anatomy (at a higher level of organization). Another case is the actual production of behavior by that network, whereby the mechanisms of neuronal activity operate to create motor actions. Practopoietic theory explains why the adaptability of a system increases with each increase in the number of traverses. With a larger number of traverses, a system can be relatively small and yet, produce a higher degree of adaptive/intelligent behavior than a system with a lower number of traverses. The present analyses indicate that the two well-known traverses--neural plasticity and neural activity--are not sufficient to explain human mental capabilities. At least one additional traverse is needed, which is named anapoiesis for its contribution in reconstructing knowledge e.g., from long-term memory into working memory. The conclusions bear implications for brain theory, the mind-body explanatory gap, and developments of artificial intelligence technologies.

2014-05-29

Practopoiesis: Or how life fosters a mind

10.1101/005660

Danko Nikolic;

The mind is a biological phenomenon. Thus, biological principles of organization should also be the principles underlying mental operations. Practopoiesis states that the key for achieving intelligence through adaptation is an arrangement in which mechanisms laying a lower level of organization, by their operations and interaction with the environment, enable creation of mechanisms lying at a higher level of organization. When such an organizational advance of a system occurs, it is called a traverse. A case of traverse is when plasticity mechanisms (at a lower level of organization), by their operations, create a neural network anatomy (at a higher level of organization). Another case is the actual production of behavior by that network, whereby the mechanisms of neuronal activity operate to create motor actions. Practopoietic theory explains why the adaptability of a system increases with each increase in the number of traverses. With a larger number of traverses, a system can be relatively small and yet, produce a higher degree of adaptive/intelligent behavior than a system with a lower number of traverses. The present analyses indicate that the two well-known traverses--neural plasticity and neural activity--are not sufficient to explain human mental capabilities. At least one additional traverse is needed, which is named anapoiesis for its contribution in reconstructing knowledge e.g., from long-term memory into working memory. The conclusions bear implications for brain theory, the mind-body explanatory gap, and developments of artificial intelligence technologies.

2015-01-27

The genetic basis of energy conservation in the sulfate-reducing bacterium Desulfovibrio alaskensis G20

10.1101/005694

Morgan Price;Jayashree Ray;Kelly M Wetmore;Jennifer V. Kuehl;Stefan Bauer;Adam M Deutschbauer;Adam P Arkin;

Sulfate-reducing bacteria play major roles in the global carbon and sulfur cycles, but it remains unclear how reducing sulfate yields energy. To determine the genetic basis of energy conservation, we measured the fitness of thousands of pooled mutants of Desulfovibrio alaskensis G20 during growth in 12 different combinations of electron donors and acceptors. We show that ion pumping by the ferredoxin:NADH oxidoreductase Rnf is required whenever substrate-level phosphorylation is not possible. The uncharacterized complex Hdr/flox-1 (Dde_1207:13) is sometimes important alongside Rnf and may perform an electron bifurcation to generate more reduced ferredoxin from NADH to allow further ion pumping. Similarly, during the oxidation of malate or fumarate, the electron-bifurcating transhydrogenase NfnAB-2 (Dde_1250:1) is important and may generate reduced ferredoxin to allow additional ion pumping by Rnf. During formate oxidation, the periplasmic [NiFeSe] hydrogenase HysAB is required, which suggests that hydrogen forms in the periplasm, diffuses to the cytoplasm, and is used to reduce ferredoxin, thus providing a substrate for Rnf. During hydrogen utilization, the transmembrane electron transport complex Tmc is important and may move electrons from the periplasm into the cytoplasmic sulfite reduction pathway. Finally, mutants of many other putative electron carriers have no clear phenotype, which suggests that they are not important under our growth conditions.

2014-05-31

Phylogenetic Identification and Functional Characterization of Orthologs and Paralogs across Human, Mouse, Fly, and Worm

10.1101/005736

Yi-Chieh Wu;Mukul S Bansal;Matthew D Rasmussen;Javier Herrero;Manolis Kellis;

Model organisms can serve the biological and medical community by enabling the study of conserved gene families and pathways in experimentally-tractable systems. Their use, however, hinges on the ability to reliably identify evolutionary orthologs and paralogs with high accuracy, which can be a great challenge at both small and large evolutionary distances. Here, we present a phylogenomics-based approach for the identification of orthologous and paralogous genes in human, mouse, fly, and worm, which forms the foundation of the comparative analyses of the modENCODE and mouse ENCODE projects. We study a median of 16,101 genes across 2 mammalian genomes (human, mouse), 12 Drosophila genomes, 5 Caenorhabditis genomes, and an outgroup yeast genome, and demonstrate that accurate inference of evolutionary relationships and events across these species must account for frequent gene-tree topology errors due to both incomplete lineage sorting and insufficient phylogenetic signal. Furthermore, we show that integration of two separate phylogenomic pipelines yields increased accuracy, suggesting that their sources of error are independent, and finally, we leverage the resulting annotation of homologous genes to study the functional impact of gene duplication and loss in the context of rich gene expression and functional genomic datasets of the modENCODE, mouse ENCODE, and human ENCODE projects.

2014-05-31

Boymaw, Overexpressed in Brains with Major Psychiatric Disorders, May Encode a Small Protein to Inhibit Mitochondrial Function and Protein Translation

10.1101/005728

Baohu Ji;Minjung Kim;Kerin Higa;Xianjin Zhou;

The t(1,11) chromosome translocation co-segregates with major psychiatric disorders in a large Scottish family. The translocation disrupts the DISC1 and Boymaw (DISC1FP1) genes on chromosomes 1 and 11, respectively. After translocation, two fusion genes are generated. Our recent studies found that the DISC1-Boymaw fusion protein is localized in mitochondria and inhibits oxidoreductase activity, rRNA expression, and protein translation. Mice carrying the DISC1-Boymaw fusion genes display intermediate behavioral phenotypes related to major psychiatric disorders. Here, we report that the Boymaw gene encodes a small protein predominantly localized in mitochondria. The Boymaw protein inhibits oxidoreductase activity, rRNA expression, and protein translation in the same way as the DISC1-Boymaw fusion protein. Interestingly, Boymaw expression is up-regulated by different stressors at RNA and/or protein translational levels. In addition, we found that Boymaw RNA expression is significantly increased in the postmortem brains of patients with major psychiatric disorders. Our studies therefore suggest that the Boymaw gene is a potential susceptibility gene for major psychiatric disorders in both the Scottish t(1,11) family and the general population of patients.

2014-05-31

Inhibition of protein translation by the DISC1-Boymaw fusion gene from a Scottish family with major psychiatric disorders

10.1101/005710

Baohu Ji;Kerin Higa;Minjung Kim;Lynn Zhou;Jared Young;Mark Geyer;Xianjin Zhou;

The t(1; 11) translocation appears to be the causal genetic lesion with 70% penetrance for schizophrenia, major depression, and other psychiatric disorders in a Scottish family. Molecular studies identified the disruption of the DISC1 (disrupted-in-schizophrenia 1) gene by chromosome translocation at chromosome 1q42. Our previous studies, however, revealed that the translocation also disrupted another gene, Boymaw (also termed DISC1FP1), on chromosome 11. After translocation, two fusion genes (the DISC1-Boymaw (DB7) and the Boymaw-DISC1 (BD13)) are generated between the DISC1 and Boymaw genes. In the present study, we report that expression of the DB7 fusion gene inhibits both intracellular NADH oxidoreductase activities and protein translation. We generated humanized DISC1-Boymaw mice with gene targeting to examine the in vivo functions of the fusion genes. Consistent with the in vitro studies on the DB7 fusion gene, protein translation activity is decreased in the hippocampus and in cultured primary neurons from the brains of the humanized mice. Expression of Gad67, Nmdar1, and Psd95 proteins are also reduced. The humanized mice display prolonged and increased responses to the NMDA receptor antagonist, ketamine, on various mouse genetic backgrounds. Abnormal information processing of acoustic startle and depressive-like behaviors are also observed. In addition, the humanized mice display abnormal erythropoiesis, which was reported to associate with depression in humans. Expression of the DB7 fusion gene may reduce protein translation to impair brain functions and thereby contribute to the pathogenesis of major psychiatric disorders.

2014-05-31

High-throughput functional annotation of influenza A virus genome at single-nucleotide resolution

10.1101/005702

Nicholas C. Wu;Arthur P. Young;Laith Q. Al-Mawsawi;C. Anders Olson;Jun Feng;Hangfei Qi;Shu-Hwa Chen;I-Hsuan Lu;Chung-Yen Lin;Robert G. Chin;Harding H. Luan;Nguyen Nguyen;Stanley F. Nelson;Xinmin Li;Ting-Ting Wu;Ren Sun;

A novel genome-wide genetics platform is presented in this study, which permits functional interrogation of all point mutations across a viral genome in parallel. Here we generated the first fitness profile of individual point mutations across the influenza virus genome. Critical residues on the viral genome were systematically identified, which provided a collection of subdomain data informative for structure-function studies and for effective rational drug and vaccine design. Our data was consistent with known, well-characterized structural features. In addition, we have achieved a validation rate of 68% for severely attenuated mutations and 94% for neutral mutations. The approach described in this study is applicable to other viral or microbial genomes where a means of genetic manipulation is available.

2014-05-31

A field test for frequency-dependent selection on mimetic colour patterns in Heliconius butterflies

10.1101/005249

Patricio Alejandro Salazar Carrión;Martin Stevens;Robert T. Jones;Imogen Ogilvie;Chris Jiggins;

Mullerian mimicry, the similarity among unpalatable species, is thought to evolve by frequency-dependent selection. Accordingly, phenotypes that become established in an area are positively selected because predators have learnt to avoid these forms, while introduced phenotypes are eliminated because predators have not yet learnt to associate these other forms with unprofitability. We tested this prediction in two areas where different colour morphs of the mimetic species Heliconius erato and H. melpomene have become established, as well as in the hybrid zone between these morphs. In each area we tested for selection on three colour patterns: the two parental and the most common hybrid. We recorded bird predation on butterfly models with paper wings, matching the appearance of each morph to bird vision, and plasticine bodies. We did not detect differences in survival between colour morphs, but all morphs were more highly attacked in the hybrid zone. This finding is consistent with recent evidence from controlled experiments with captive birds, which suggest that the effectiveness of warning signals decreases when a large signal diversity is available to predators. This is likely to occur in the hybrid zone where over twenty hybrid phenotypes coexist.

2014-06-02

Bacillus Calmette-Guerin infection in NADPH oxidase deficiency: defective mycobacterial sequestration and granuloma formation

10.1101/005835

Christine Deffert;Michela G. Schäppi;Jean-Claude Pache;Julien Cachat;Dominique Vesin;Ruth Bisig;Xiaojuan Ma Mulone;Tiina Kelkka;Rikard Holmdahl;Irene Garcia;Maria L. Olleros;Karl-Heinz Krause;

Patients with chronic granulomatous disease (CGD) lack generation of reactive oxygen species (ROS) through the phagocyte NADPH oxidase NOX2. CGD is an immune deficiency that leads to frequent infections with certain pathogens; this is well documented for S. aureus and A. fumigatus, but less clear for mycobacteria. We therefore performed an extensive literature search which yielded 297 cases of CGD patients with mycobacterial infections; M.bovis BCG was most commonly recovered (74%). The relationship between NOX2 deficiency and BCG infection however has never been studied in a mouse model. We therefore investigated BCG infection in three different mouse models of CGD: Ncf1 mutants in two different genetic backgrounds and NOX2 knock-out mice. In addition we investigated a macrophage-specific rescue (transgenic expression of Ncf1 under the control of the CD68 promoter). Wild type mice did not develop severe disease upon BCG injection. In contrast, all three types of CGD mice were highly susceptible to BCG, as witnessed by a severe weight loss, development of hemorrhagic pneumonia, and a high mortality ([~] 50%). Rescue of NOX2 activity in macrophages restored BCG resistance, similar as seen in wild-type mice. Granulomas from mycobacteria-infected wild type mice generated ROS, while granulomas from CGD mice did not. Bacterial load in CGD mice was only moderately increased, suggesting that it was not crucial for the observed phenotype. CGD mice responded with massively enhanced cytokine release (TNF-, IFN-{gamma}, IL-17 and IL-12) to BCG infection, which might account for severity of the disease. Finally, in wild-type mice, macrophages formed clusters and restricted mycobacteria to granulomas, while macrophages and mycobacteria were diffusely distributed in lung tissue from CGD mice. Our results demonstrate that lack of the NADPH oxidase leads to a markedly increased severity of BCG infection through mechanisms including increased cytokine production and impaired granuloma formation.

2014-06-03

How the tortoise beats the hare: Slow and steady adaptation in structured populations suggests a rugged fitness landscape in bacteria

10.1101/005793

Joshua R. Nahum;Peter Godfrey-Smith;Brittany N. Harding;Joseph H. Marcus;Jared Carlson-Stevermer;Benjamin Kerr;

AbstractIn the context of Wrights adaptive landscape, genetic epistasis can yield a multipeaked or \"rugged\" topography. In an unstructured population, a lineage with selective access to multiple peaks is expected to rapidly fix on one, which may not be the highest peak. Contrarily, beneficial mutations in a population with spatially restricted migration take longer to fix, allowing distant parts of the population to explore the landscape semi-independently. Such a population can simultaneous discover multiple peaks and the genotype at the highest discovered peak is expected to fix eventually. Thus, structured populations sacrifice initial speed of adaptation for breadth of search. As in the Tortoise-Hare fable, the structured population (Tortoise) starts relatively slow, but eventually surpasses the unstructured population (Hare) in average fitness. In contrast, on single-peak landscapes (e.g., systems lacking epistasis), all uphill paths converge. Given such \"smooth\" topography, breadth of search is devalued, and a structured population only lags behind an unstructured population in average fitness (ultimately converging). Thus, the Tortoise-Hare pattern is an indicator of ruggedness. After verifying these predictions in simulated populations where ruggedness is manipulable, we then explore average fitness in metapopulations of Escherichia coli. Consistent with a rugged landscape topography, we find a Tortoise-Hare pattern. Further, we find that structured populations accumulate more mutations, suggesting that distant peaks are higher. This approach can be used to unveil landscape topography in other systems, and we discuss its application for antibiotic resistance, engineering problems, and elements of Wrights Shifting Balance Process.\n\nSignificance StatementAdaptive landscapes are a way of describing how mutations interact with each other to produce fitness. If an adaptive landscape is rugged, organisms achieve higher fitness with more difficulty because the mutations to reach high fitness genotypes may not be always beneficial. By evolving populations of Escherichia coli with different degrees of spatial structure, we identified a Tortoise-Hare pattern, where structured populations were initially slower, but overtook less structured populations in mean fitness. These results, combined with genetic sequencing and computational simulation, indicate this bacterial adaptive landscape is rugged. Our findings address one of the most enduring questions in evolutionary biology, in addition to, providing insight into how evolution may influence medicine and engineering.

2014-06-03

Natural variation in teosinte at the domestication locus teosinte branched1 (tb1)

10.1101/005819

Laura Vann;Thomas Kono;Tanja Pyha ̈j ̈arvi;Matthew B Hufford;Jeffrey Ross-Ibarra;

Premise of the studyThe teosinte branched1 (tb1) gene is a major QTL controlling branching differences between maize and its wild progenitor, teosinte. The insertion of a transposable element (Hopscotch) upstream of tb1 is known to enhance the genes expression, causing reduced tillering in maize. Observations of the maize tb1 allele in teosinte and estimates of an insertion age of the Hopscotch that predates domestication led us to investigate its prevalence and potential role in teosinte.\n\nMethodsPrevalence of the Hopscotch element was assessed across an Americas-wide sample of 837 maize and teosinte individuals using a co-dominant PCR assay. Population genetic summaries were calculated for a subset of individuals from four teosinte populations in central Mexico. Phenotypic data were also collected using seed from a single teosinte population where Hopscotch was found segregating at high frequency.\n\nKey resultsGenotyping results indicate the Hopscotch element is found in a number of teosinte populations and linkage disequilibrium near tb1 does not support recent introgression from maize. Population genetic signatures are consistent with selection on this locus revealing a potential ecological role for Hopscotch in teosinte, but a greenhouse experiment does not detect a strong association between tb1 and tillering in teosinte.\n\nConclusionsOur findings suggest the role of Hopscotch differs between maize and teosinte. Future work should assess tb1 expression levels in teosinte with and without the Hopscotch and more comprehensively phenotype teosinte to assess the ecological significance of the Hopscotch insertion and, more broadly, the tb1 locus in teosinte.

2014-06-03

Natural variation in teosinte at the domestication locus teosinte branched1 (tb1)

10.1101/005819

Laura Vann;Thomas Kono;Tanja Pyha ̈j ̈arvi;Matthew B Hufford;Jeffrey Ross-Ibarra;

Premise of the studyThe teosinte branched1 (tb1) gene is a major QTL controlling branching differences between maize and its wild progenitor, teosinte. The insertion of a transposable element (Hopscotch) upstream of tb1 is known to enhance the genes expression, causing reduced tillering in maize. Observations of the maize tb1 allele in teosinte and estimates of an insertion age of the Hopscotch that predates domestication led us to investigate its prevalence and potential role in teosinte.\n\nMethodsPrevalence of the Hopscotch element was assessed across an Americas-wide sample of 837 maize and teosinte individuals using a co-dominant PCR assay. Population genetic summaries were calculated for a subset of individuals from four teosinte populations in central Mexico. Phenotypic data were also collected using seed from a single teosinte population where Hopscotch was found segregating at high frequency.\n\nKey resultsGenotyping results indicate the Hopscotch element is found in a number of teosinte populations and linkage disequilibrium near tb1 does not support recent introgression from maize. Population genetic signatures are consistent with selection on this locus revealing a potential ecological role for Hopscotch in teosinte, but a greenhouse experiment does not detect a strong association between tb1 and tillering in teosinte.\n\nConclusionsOur findings suggest the role of Hopscotch differs between maize and teosinte. Future work should assess tb1 expression levels in teosinte with and without the Hopscotch and more comprehensively phenotype teosinte to assess the ecological significance of the Hopscotch insertion and, more broadly, the tb1 locus in teosinte.

2014-09-11

Genomic, transcriptomic and phenomic variation reveals the complex adaptation of modern maize breeding

10.1101/005751

Haijun Liu;Xiaqing Wang;Marilyn Warburton;Weiwei Wen;Minliang Jin;Min Deng;Jie Liu;Hao Tong;Qingchun Pan;Xiaohong Yang;Jianbing Yan;

The temperate-tropical division of early maize germplasm to different agricultural environments was arguably the greatest adaptation process associated with the success and near ubiquitous importance of global maize production. Deciphering this history is challenging, but new insight has been gained from the genomic, transcriptomic and phenotypic variation collected from 368 diverse temperate and tropical maize inbred lines in this study. This is the first attempt to systematically explore the mechanisms of the adaptation process. Our results indicated that divergence between tropical and temperate lines seem occur 3,400-6,700 years ago. A number of genomic selection signals and transcriptomic variants including differentially expressed individual genes and rewired co-expression networks of genes were identified. These candidate signals were found to be functionally related to stress response and most were associated with directionally selected traits, which may have been an advantage under widely varying environmental conditions faced by maize as it was migrated away from its domestication center. Its also clear in our study that such stress adaptation could involve evolution of protein-coding sequences as well as transcriptome-level regulatory changes. This latter process may be a more flexible and dynamic way for maize to adapt to environmental changes over this dramatically short evolutionary time frame.

2014-06-03

Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits

10.1101/005892

Darren Kessner;John Novembre;

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTLs) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides produces qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTLs under selection impacts the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50-100%) can be explained by detected QTLs in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.

2014-06-04

Complete plastid genome assembly of invasive plant, Centaurea diffusa

10.1101/005900

Kathryn G Turner;Christopher J Grassa;

New genomic tools are needed to elucidate the evolution of invasive, non-model organisms. Here we present the completed plastome assembly for the problematic invasive weed, Centaurea diffusa. This new tool represents a significant contribution to future studies of the ecological genomics of invasive plants, particularly this weedy genus, and studies of the Asteraceae in general.

2014-06-04

Complete plastid genome assembly of invasive plant, Centaurea diffusa

10.1101/005900

Kathryn G Turner;Christopher J Grassa;

New genomic tools are needed to elucidate the evolution of invasive, non-model organisms. Here we present the completed plastome assembly for the problematic invasive weed, Centaurea diffusa. This new tool represents a significant contribution to future studies of the ecological genomics of invasive plants, particularly this weedy genus, and studies of the Asteraceae in general.

2014-06-11

Simultaneous estimation of transcript abundances and transcript specific fragment distributions of RNA-Seq data with the Mix2 model

10.1101/005918

Andreas Tuerk;Gregor Wiktorin;

Quantification of RNA transcripts with RNA-Seq is inaccurate due to positional fragmentation bias, which is not represented appropriately by current statistical models of RNA-Seq data. Another, less investigated, source of error is the inaccuracy of transcript start and end annotations.\n\nThis article introduces the Mix2 (rd. \"mixquare\") model, which uses a mixture of probability distributions to model the transcript specific positional fragment bias. The parameters of the Mix2 model can be efficiently trained with the EM algorithm and are tied between similar transcripts. Transcript specific shift and scale parameters allow the Mix2 model to automatically correct inaccurate transcript start and end annotations. Experiments are conducted on synthetic data covering 7 genes of different complexity, 4 types of fragment bias and correct as well as incorrect transcript start and end annotations. Abundance estimates obtained by Cufflinks 2.2.0, PennSeq and the Mix2 model show superior performance of the Mix2 model in the vast majority of test conditions.\n\nThe Mix2 software is available at http://www.lexogen.com/fileadmin/uploads/bioinfo/mix2model.tgz, subject to the enclosed license.\n\nAdditional experimental data are available in the supplement.

2014-06-04

Untangling cross-frequency coupling in neuroscience

10.1101/005926

Juhan Aru;Jaan Aru;Viola Priesemann;Michael Wibral;Luiz Lana;Gordon Pipa;Wolf Singer;Raul Vicente;

Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis.\n\nHighlightsFundamental caveats and confounds in the methodology of assessing CFC are discussed.\n\nSignificant CFC can be observed without any underlying physiological coupling.\n\nNon-stationarity of a time-series leads to spectral correlations interpreted as CFC.\n\nWe offer practical recommendations, which can relieve some of the current confounds.\n\nFurther theoretical and experimental work is needed to ground the CFC analysis.

2014-06-04

Untangling cross-frequency coupling in neuroscience

10.1101/005926

Juhan Aru;Jaan Aru;Viola Priesemann;Michael Wibral;Luiz Lana;Gordon Pipa;Wolf Singer;Raul Vicente;

Cross-frequency coupling (CFC) has been proposed to coordinate neural dynamics across spatial and temporal scales. Despite its potential relevance for understanding healthy and pathological brain function, the standard CFC analysis and physiological interpretation come with fundamental problems. For example, apparent CFC can appear because of spectral correlations due to common non-stationarities that may arise in the total absence of interactions between neural frequency components. To provide a road map towards an improved mechanistic understanding of CFC, we organize the available and potential novel statistical/modeling approaches according to their biophysical interpretability. While we do not provide solutions for all the problems described, we provide a list of practical recommendations to avoid common errors and to enhance the interpretability of CFC analysis.\n\nHighlightsFundamental caveats and confounds in the methodology of assessing CFC are discussed.\n\nSignificant CFC can be observed without any underlying physiological coupling.\n\nNon-stationarity of a time-series leads to spectral correlations interpreted as CFC.\n\nWe offer practical recommendations, which can relieve some of the current confounds.\n\nFurther theoretical and experimental work is needed to ground the CFC analysis.

2014-08-25

Osmunda pulchella sp. nov. from the Jurassic of Sweden&amp;#151;reconciling molecular and fossil evidence in the phylogeny of Osmundaceae

10.1101/005777

Benjamin Bomfleur;Guido W Grimm;Stephen McLoughlin;

The systematic classification of Osmundaceae has long remained controversial. Recent molecular data indicate that Osmunda is paraphyletic, and needs to be separated into Osmundastrum and Osmunda s. str. Here we describe an exquisitely preserved Jurassic Osmunda rhizome (O. pulchella sp. nov.) that combines diagnostic features of Osmundastrum and Osmunda, calling molecular evidence for paraphyly into question. We assembled a new morphological matrix based on rhizome anatomy, and used network analyses to establish phylogenetic relationships between fossil and extant members of modern Osmundaceae. We re-analysed the original molecular data to evaluate root-placement support. Finally, we integrated morphological and molecular data-sets using the evolutionary placement algorithm. Osmunda pulchella and five additional, newly identified Jurassic Osmunda species show anatomical character suites intermediate between Osmundastrum and Osmunda. Molecular evidence for paraphyly is ambiguous: a previously unrecognized signal from spacer sequences favours an alternative root placement that would resolve Osmunda s.l. as monophyletic. Our evolutionary placement analysis identifies fossil species as ancestral members of modern genera and subgenera. Altogether, the seemingly conflicting evidence from morphological, anatomical, molecular, and palaeontological data can be elegantly reconciled under the assumption that Osmunda is indeed monophyletic; the recently proposed root-placement in Osmundaceae--based solely on molecular data--likely results from un- or misinformative out-group signals.

2014-06-04

A Tandem Cell for Nanopore-based DNA Sequencing with Exonuclease

10.1101/005934

G Sampath;

A tandem cell is proposed for DNA sequencing in which an exonuclease enzyme cleaves bases (mononucleotides) from a strand of DNA for identification inside a nanopore. It has two nanopores and three compartments with the structure [cis1, upstream nanopore (UNP), trans1 = cis2, downstream nanopore (DNP), trans2]. The exonuclease is attached to the exit side of UNP in trans1/cis2. A cleaved base cannot regress into cis1 because of the remaining DNA strand in UNP. A profiled electric field over DNP with positive and negative components slows down base translocation through DNP. The proposed structure is modeled with a Fokker-Planck equation and a piecewise solution presented. Results from the model indicate that with probability approaching 1 bases enter DNP in their natural order, are detected without any loss, and do not regress into DNP after progressing into trans2. Sequencing efficiency with a tandem cell would then be determined solely by the level of discrimination among the base types inside DNP.

2014-06-04

A Tandem Cell for Nanopore-based DNA Sequencing with Exonuclease

10.1101/005934

G Sampath;

A tandem cell is proposed for DNA sequencing in which an exonuclease enzyme cleaves bases (mononucleotides) from a strand of DNA for identification inside a nanopore. It has two nanopores and three compartments with the structure [cis1, upstream nanopore (UNP), trans1 = cis2, downstream nanopore (DNP), trans2]. The exonuclease is attached to the exit side of UNP in trans1/cis2. A cleaved base cannot regress into cis1 because of the remaining DNA strand in UNP. A profiled electric field over DNP with positive and negative components slows down base translocation through DNP. The proposed structure is modeled with a Fokker-Planck equation and a piecewise solution presented. Results from the model indicate that with probability approaching 1 bases enter DNP in their natural order, are detected without any loss, and do not regress into DNP after progressing into trans2. Sequencing efficiency with a tandem cell would then be determined solely by the level of discrimination among the base types inside DNP.

2014-08-08

iRAP - an integrated RNA-seq Analysis Pipeline

10.1101/005991

Nuno A. Fonseca;Robert Petryszak;John Marioni;Alvis Brazma;

RNA-sequencing (RNA-Seq) has become the technology of choice for whole-transcriptome profiling. However, processing the millions of sequence reads generated requires considerable bioinformatics skills and computational resources. At each step of the processing pipeline many tools are available, each with specific advantages and disadvantages. While using a specific combination of tools might be desirable, integrating the different tools can be time consuming, often due to specificities in the formats of input/output files required by the different programs. Here we present iRAP, an integrated RNA-seq analysis pipeline that allows the user to select and apply their preferred combination of existing tools for mapping reads, quantifying expression, testing for differential expression. iRAP also includes multiple tools for gene set enrichment analysis and generates web browsable reports of the results obtained in the different stages of the pipeline. Depending upon the application, iRAP can be used to quantify expression at the gene, exon or transcript level. iRAP is aimed at a broad group of users with basic bioinformatics training and requires little experience with the command line. Despite this, it also provides more advanced users with the ability to customise the options used by their chosen tools.

2014-06-06

Spatial epidemiology of networked metapopulation: An overview

10.1101/003889

Lin WANG;Xiang Li;

An emerging disease is one infectious epidemic caused by a newly transmissible pathogen, which has either appeared for the first time or already existed in human populations, having the capacity to increase rapidly in incidence as well as geographic range. Adapting to human immune system, emerging diseases may trigger large-scale pandemic spreading, such as the transnational spreading of SARS, the global outbreak of A(H1N1), and the recent potential invasion of avian influenza A(H7N9). To study the dynamics mediating the transmission of emerging diseases, spatial epidemiology of networked metapopulation provides a valuable modeling framework, which takes spatially distributed factors into consideration. This review elaborates the latest progresses on the spatial metapopulation dynamics, discusses empirical and theoretical findings that verify the validity of networked metapopulations, and the application in evaluating the effectiveness of disease intervention strategies as well.

2014-06-04

Origin and evolution of the self-organizing cytoskeleton in the network of eukaryotic organelles

10.1101/005868

Gáspár Jékely;

The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity, and in many aspects prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here I compare the dynamic properties of the prokaryotic and eukaryotic cytoskeleton, and discuss how these relate to function and the evolution of organellar networks. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing active gel, the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming.

2014-06-04

Copy number networks to guide combinatorial therapy for cancer and other disorders

10.1101/005942

Andy Lin;Desmond James Smith;

The dwindling drug pipeline is driving increased interest in the use of genome datasets to inform drug treatment. In particular, networks based on transcript data and protein-protein interactions have been used to design therapies that employ drug combinations. But there has been less focus on employing human genetic interaction networks constructed from copy number alterations (CNAs). These networks can be charted with sensitivity and precision by seeking gene pairs that tend to be amplified and/or deleted in tandem, even when they are located at a distance on the genome. Our experience with radiation hybrid (RH) panels, a library of cell clones that have been used for genetic mapping, have shown this tool can pinpoint statistically significant patterns of co-inherited gene pairs. In fact, we were able to identify gene pairs specifically associated with the mechanism of cell survival at single gene resolution. The strategy of seeking correlated CNAs can also be used to map survival networks for cancer. Although the cancer networks have lower resolution, the RH network can be leveraged to provide single gene specificity in the tumor networks. In a survival network for glioblastoma possessing single gene resolution, we found that the epidermal growth factor receptor (EGFR) oncogene interacted with 46 genes. Of these genes, ten (22%) happened to be targets for existing drugs. Here, we briefly review the previous use of molecular networks to design novel therapies. We then highlight the potential of using correlated CNAs to guide combinatorial drug treatment in common medical conditions. We focus on therapeutic opportunities in cancer, but also offer examples from autoimmune disorders and atherosclerosis.

2014-06-05

Copy number networks to guide combinatorial therapy for cancer and other disorders

10.1101/005942

Andy Lin;Desmond James Smith;

The dwindling drug pipeline is driving increased interest in the use of genome datasets to inform drug treatment. In particular, networks based on transcript data and protein-protein interactions have been used to design therapies that employ drug combinations. But there has been less focus on employing human genetic interaction networks constructed from copy number alterations (CNAs). These networks can be charted with sensitivity and precision by seeking gene pairs that tend to be amplified and/or deleted in tandem, even when they are located at a distance on the genome. Our experience with radiation hybrid (RH) panels, a library of cell clones that have been used for genetic mapping, have shown this tool can pinpoint statistically significant patterns of co-inherited gene pairs. In fact, we were able to identify gene pairs specifically associated with the mechanism of cell survival at single gene resolution. The strategy of seeking correlated CNAs can also be used to map survival networks for cancer. Although the cancer networks have lower resolution, the RH network can be leveraged to provide single gene specificity in the tumor networks. In a survival network for glioblastoma possessing single gene resolution, we found that the epidermal growth factor receptor (EGFR) oncogene interacted with 46 genes. Of these genes, ten (22%) happened to be targets for existing drugs. Here, we briefly review the previous use of molecular networks to design novel therapies. We then highlight the potential of using correlated CNAs to guide combinatorial drug treatment in common medical conditions. We focus on therapeutic opportunities in cancer, but also offer examples from autoimmune disorders and atherosclerosis.

2014-06-24

Restriction and recruitment - gene duplication and the origin and evolution of snake venom toxins

10.1101/006023

Adam D Hargreaves;Martin T Swain;Matthew J Hegarty;Darren W Logan;John F Mulley;

Snake venom has been hypothesised to have originated and diversified via a process that involves duplication of genes encoding body proteins with subsequent recruitment of the copy to the venom gland, where natural selection acts to develop or increase toxicity. However, gene duplication is known to be a rare event in vertebrate genomes and the recruitment of duplicated genes to a novel expression domain (neofunctionalisation) is an even rarer process that requires the evolution of novel combinations of transcription factor binding sites in upstream regulatory regions. Therefore, whilst this hypothesis concerning the evolution of snake venom is therefore very unlikely and should be regarded with caution, it is nonetheless often assumed to be established fact, hindering research into the true origins of snake venom toxins. To critically evaluate this hypothesis we have generated transcriptomic data for body tissues and salivary and venom glands from five species of venomous and non-venomous reptiles. Our comparative transcriptomic analysis of these data reveals that snake venom does not evolve via the hypothesised process of duplication and recruitment of genes encoding body proteins. Indeed, our results show that many proposed venom toxins are in fact expressed in a wide variety of body tissues, including the salivary gland of non-venomous reptiles and that these genes have therefore been restricted to the venom gland following duplication, not recruited. Thus snake venom evolves via the duplication and subfunctionalisation of genes encoding existing salivary proteins. These results highlight the danger of the elegant and intuitive ?just-so story? in evolutionary biology.

2014-06-06

Restriction and recruitment - gene duplication and the origin and evolution of snake venom toxins

10.1101/006023

Adam D Hargreaves;Martin T Swain;Matthew J Hegarty;Darren W Logan;John F Mulley;

Snake venom has been hypothesised to have originated and diversified via a process that involves duplication of genes encoding body proteins with subsequent recruitment of the copy to the venom gland, where natural selection acts to develop or increase toxicity. However, gene duplication is known to be a rare event in vertebrate genomes and the recruitment of duplicated genes to a novel expression domain (neofunctionalisation) is an even rarer process that requires the evolution of novel combinations of transcription factor binding sites in upstream regulatory regions. Therefore, whilst this hypothesis concerning the evolution of snake venom is therefore very unlikely and should be regarded with caution, it is nonetheless often assumed to be established fact, hindering research into the true origins of snake venom toxins. To critically evaluate this hypothesis we have generated transcriptomic data for body tissues and salivary and venom glands from five species of venomous and non-venomous reptiles. Our comparative transcriptomic analysis of these data reveals that snake venom does not evolve via the hypothesised process of duplication and recruitment of genes encoding body proteins. Indeed, our results show that many proposed venom toxins are in fact expressed in a wide variety of body tissues, including the salivary gland of non-venomous reptiles and that these genes have therefore been restricted to the venom gland following duplication, not recruited. Thus snake venom evolves via the duplication and subfunctionalisation of genes encoding existing salivary proteins. These results highlight the danger of the elegant and intuitive ?just-so story? in evolutionary biology.

2014-08-25

Gene co-expression modules underlying polymorphic and monomorphic zooids in the colonial hydrozoan, Hydractinia symbiolongicarpus

10.1101/006072

David C Plachetzki;M. Sabrina Pankey;Brian R Johnson;Eric J Ronne;Artyom Kopp;Richard K Grosberg;

Advances in sequencing technology have forced a quantitative revolution in Evolutionary Biology. One important feature of this renaissance is that comprehensive genomic resources can be obtained quickly for almost any taxon, thus speeding the development of new model organisms. Here we analyze 20 RNA-seq libraries from morphologically, sexually, and genetically distinct polyp types from the gonochoristic colonial hydrozoan, Hydractinia symbiolongicarpus (Cnidaria). Analyses of these data using Weighted Gene Co-expression Networks highlights deeply conserved genetic elements of animal spermatogenesis and demonstrate the utility of these methods in identifying modules of genes that correlate with different zooid types across various statistical contrasts. RNAseq data and analytical scripts described here are deposited in publicly available databases.

2014-06-07

Recombination impacts damaging and disease mutation accumulation in human populations

10.1101/006064

Julie Hussin;Alan Hodgkinson;Youssef Idaghdour;Jean-Christophe Grenier;Jean-Philippe Goulet;Elias Gbeha;Elodie Hip-Ki;Philip Awadalla;

Many decades of theory have demonstrated that in non-recombining systems, slightly deleterious mutations accumulate non-reversibly1, potentially driving the extinction of many asexual species. Non-recombining chromosomes in sexual organisms are thought to have degenerated in a similar fashion2, however it is not clear the extent to which these processes operate along recombining chromosomes with highly variable rates of crossing over. Using high coverage sequencing data from over 1400 individuals in The 1000 Genomes and CARTaGENE projects, we show that recombination rate modulates the genomic distribution of putatively deleterious variants across the entire human genome. We find that exons in regions of low recombination are significantly enriched for deleterious and disease variants, a signature that varies in strength across worldwide human populations with different demographic histories. As low recombining regions are enriched for highly conserved genes with essential cellular functions, and show an excess of mutations with demonstrated effect on health, this phenomenon likely affects disease susceptibility in humans.

2014-06-08

Recombination impacts damaging and disease mutation accumulation in human populations

10.1101/006064

Julie Hussin;Alan Hodgkinson;Youssef Idaghdour;Jean-Christophe Grenier;Jean-Philippe Goulet;Elias Gbeha;Elodie Hip-Ki;Philip Awadalla;

Many decades of theory have demonstrated that in non-recombining systems, slightly deleterious mutations accumulate non-reversibly1, potentially driving the extinction of many asexual species. Non-recombining chromosomes in sexual organisms are thought to have degenerated in a similar fashion2, however it is not clear the extent to which these processes operate along recombining chromosomes with highly variable rates of crossing over. Using high coverage sequencing data from over 1400 individuals in The 1000 Genomes and CARTaGENE projects, we show that recombination rate modulates the genomic distribution of putatively deleterious variants across the entire human genome. We find that exons in regions of low recombination are significantly enriched for deleterious and disease variants, a signature that varies in strength across worldwide human populations with different demographic histories. As low recombining regions are enriched for highly conserved genes with essential cellular functions, and show an excess of mutations with demonstrated effect on health, this phenomenon likely affects disease susceptibility in humans.

2014-09-10

Testing the Toxicofera: comparative reptile transcriptomics casts doubt on the single, early evolution of the reptile venom system

10.1101/006031

Adam D Hargreaves;Martin T Swain;Darren W Logan;John F Mulley;

Background The identification of apparently conserved gene complements in the venom and salivary glands of a diverse set of reptiles led to the development of the Toxicofera hypothesis the idea that there was a single, early evolution of the venom system in reptiles. However, this hypothesis is based largely on relatively small scale EST-based studies of only venom or salivary glands and toxic effects have been assigned to only some of these putative Toxcoferan toxins in some species. We set out to investigate the distribution of these putative venom toxin transcripts in order to investigate to what extent conservation of gene complements may reflect a bias in previous sampling efforts. Results We have carried out the first large-scale test of the Toxicofera hypothesis and found it lacking in a number of regards. Our quantitative transcriptomic analyses of venom and salivary glands and other body tissues in five species of reptile, together with the use of available RNA-Seq datasets for additional species shows that the majority of genes used to support the establishment and expansion of the Toxicofera are in fact expressed in multiple body tissues and most likely represent general maintenance or housekeeping genes. The apparent conservation of gene complements across the Toxicofera therefore reflects an artefact of incomplete tissue sampling. In other cases, the identification of a non-toxic paralog of a gene encoding a true venom toxin has led to confusion about the phylogenetic distribution of that venom component. Conclusions Venom has evolved multiple times in reptiles. In addition, the misunderstanding regarding what constitutes a toxic venom component, together with the misidentification of genes and the classification of identical or near-identical sequences as distinct genes has led to an overestimation of the complexity of reptile venoms in general, and snake venom in particular, with implications for our understanding of (and development of treatments to counter) the molecules responsible for the physiological consequences of snakebite.

2014-06-06

Rapid transcriptional response to physiological neuronal activity in vivo revealed by transcriptome sequencing

10.1101/005876

Yarden Katz;Tarciso Velho;Vincent Butty;Christopher B. Burge;Carlos Lois;

Neuronal activity serves as a gateway between external stimulus from environment and the brain, often inducing gene expression changes. Alternative splicing (AS) is a widespread mechanism of increasing the number of transcripts produced from a single gene and has been shown to alter properties of neuronal genes, such as ion channels (Xie and Black 2001) and neurotransmitter receptors (Mu et al. 2003). Patterns of neural tissue-specific AS have been identified, often regulated by neuron-specific splicing factors that are essential for survival (Jensen et al. 2000; Li et al. 2007), demonstrating the importance of AS in neurons. In vitro studies of neuronal activity found AS changes in response to neuronal activity in addition to transcriptional ones, raising the question of whether such changes are recapitulated in vivo on behaviorally relevant timescales. We developed a paradigm for studying physiological neuronal activity through controlled stimulation of the olfactory bulb, and performed RNA-Seq transcriptome analysis of olfactory bulbs from odor-deprived and stimulated mice. We found that physiological stimulation induces large, rapid and reproducible changes in transcription in vivo, and that the activation of a core set of activity-regulated factors is recapitulated in an in vitro model of neuronal stimulation. However, physiological activity did not induce global changes in post-transcriptional mRNA processing, such as AS or alternative cleavage and polyadenylation. In contrast, analysis of RNA-Seq from in vitro stimulation models showed rapid activity-dependent changes in both transcription and mRNA processing. Our results provide the first genome-wide look at neuronal activity-dependent mRNA processing and suggest that rapid changes in AS might not be the dominant form of transcriptome alterations that take place during olfactory rodent behavior.

2014-06-07