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Noradrenergic plasticity of olfactory sensory neuron inputs to the main olfactory bulb

10.1101/002550

Dennis Eckmeier;Stephen David Shea;

Sensory responses are modulated throughout the nervous system by internal factors including attention, experience, and brain state. This is partly due to fluctuations in neuromodulatory input from regions such as the noradrenergic locus coeruleus (LC) in the brainstem. LC activity changes with arousal and modulates sensory processing, cognition and memory. The main olfactory bulb (MOB) is richly targeted by LC fibers and noradrenaline profoundly influences MOB circuitry and odor-guided behavior. Noradrenaline-dependent plasticity affects the output of the MOB. However, it is unclear whether noradrenergic plasticity includes modulation in the glomerular layer, the site of input to the MOB. Noradrenergic terminals are found in the glomerular layer, but noradrenaline receptor activation does not seem to acutely modulate olfactory sensory neuron terminals in vitro. We investigated whether noradrenaline induces plasticity at the glomerulus. We used wide-field optical imaging to measure changes in odor responses following electrical stimulation of locus coeruleus in anesthetized mice. Surprisingly, the odor-evoked intrinsic optical signals at the glomerulus were persistently weakened after LC activation. Calcium imaging selectively from olfactory sensory neurons confirmed that this effect was due to a uniform gain suppression of presynaptic input, and did not require exposure to a stimulus during the LC activation. Finally, noradrenaline antagonists prevented glomerular suppression. We conclude that noradrenaline release from LC has persistent effects on odor processing already at the first synapse of the main olfactory system. This mechanism could contribute to arousal-dependent memories.

2014-02-09

Noradrenergic plasticity of olfactory sensory neuron inputs to the main olfactory bulb

10.1101/002550

Dennis Eckmeier;Stephen David Shea;

Sensory responses are modulated throughout the nervous system by internal factors including attention, experience, and brain state. This is partly due to fluctuations in neuromodulatory input from regions such as the noradrenergic locus coeruleus (LC) in the brainstem. LC activity changes with arousal and modulates sensory processing, cognition and memory. The main olfactory bulb (MOB) is richly targeted by LC fibers and noradrenaline profoundly influences MOB circuitry and odor-guided behavior. Noradrenaline-dependent plasticity affects the output of the MOB. However, it is unclear whether noradrenergic plasticity includes modulation in the glomerular layer, the site of input to the MOB. Noradrenergic terminals are found in the glomerular layer, but noradrenaline receptor activation does not seem to acutely modulate olfactory sensory neuron terminals in vitro. We investigated whether noradrenaline induces plasticity at the glomerulus. We used wide-field optical imaging to measure changes in odor responses following electrical stimulation of locus coeruleus in anesthetized mice. Surprisingly, the odor-evoked intrinsic optical signals at the glomerulus were persistently weakened after LC activation. Calcium imaging selectively from olfactory sensory neurons confirmed that this effect was due to a uniform gain suppression of presynaptic input, and did not require exposure to a stimulus during the LC activation. Finally, noradrenaline antagonists prevented glomerular suppression. We conclude that noradrenaline release from LC has persistent effects on odor processing already at the first synapse of the main olfactory system. This mechanism could contribute to arousal-dependent memories.

2014-08-12

Sashimi plots: Quantitative visualization of alternative isoform expression from RNA-seq data

10.1101/002576

Yarden Katz;Eric T Wang;Jacob Stilterra;Schraga Schwartz;Bang Wong;Helga Thorvaldsdóttir;James T Robinson;Jill P Mesirov;Edoardo M Airoldi;Christopher B Burge;

To the Editor: To the Editor: Software documentation and... References Analysis of RNA sequencing (RNA-Seq) data revealed that the vast majority of human genes express multiple mRNA isoforms, produced by alternative pre-mRNA splicing and other mechanisms, and that most alternative isoforms vary in expression between human tissues (Pan et al., 2008; Wang et al., 2008). As RNA-Seq datasets grow in size, it remains challenging to visualize isoform expression across multiple samples. We present Sashimi plots, a quantitative multi-sample visualization of RNA-Seq reads aligned to gene annotations, which enables quantitative comparison of isoform usage across samples or experimental conditions. Given an input annotation and spliced alignments of reads from a sample, a region of interest is visualized in a Sashimi plot as follows: (i) alignments in ...

2014-02-11

Social, spatial and temporal segregation in an ant society

10.1101/002519

Lauren E Quevillon;Ephraim M Hanks;Shweta Bansal;David P Hughes;

Introduction Introduction Results Discussion Methods References Sociality can be risky. A chief cost of social living is increased transmission of infectious diseases, due to higher population densities combined with greater contact between susceptible and infected individuals (1,2,3,4). This greater encounter rate has led to a growing interest in the role of social contact structure in infectious disease transmission (5,6,7,8,9,10,11) To capture the dynamics of disease spread within dense groups, epidemiological models are shifting from the principle of mass action, in which infected and susceptible individuals are assumed to mix randoml ...

2014-02-11

Estimating the evolution of human life history traits in age-structured populations

10.1101/002584

Ryan Baldini;

I propose a method that estimates the selection response of all vital rates in an age-structured population. I assume that vital rates are determined by the additive genetic contributions of many loci. The method uses all relatedness information in the sample to inform its estimates of genetic parameters, via an MCMC Bayesian framework. One can use the results to estimate the selection response of any life history trait that is a function of the vital rates, including the age at first reproduction, total lifetime fertility, survival to adulthood, and others. This method closely ties the empirical analysis of life history evolution to dynamically complete models of natural selection, and therefore enjoys some theoretical advantages over other methods. I demonstrate the method on a simulated model of evolution with two age classes. Finally I discuss how the method can be extended to more complicated cases.

2014-02-11

Estimating the evolution of human life history traits in age-structured populations

10.1101/002584

Ryan Baldini;

I propose a method that estimates the selection response of all vital rates in an age-structured population. I assume that vital rates are determined by the additive genetic contributions of many loci. The method uses all relatedness information in the sample to inform its estimates of genetic parameters, via an MCMC Bayesian framework. One can use the results to estimate the selection response of any life history trait that is a function of the vital rates, including the age at first reproduction, total lifetime fertility, survival to adulthood, and others. This method closely ties the empirical analysis of life history evolution to dynamically complete models of natural selection, and therefore enjoys some theoretical advantages over other methods. I demonstrate the method on a simulated model of evolution with two age classes. Finally I discuss how the method can be extended to more complicated cases.

2014-02-19

Evidence for widespread positive and negative selection in coding and conserved noncoding regions of Capsella grandiflora

10.1101/002428

Robert J Williamson;Emily B Josephs;Adrian E Platts;Khaled M Hazzouri;Annabelle Haudry;Mathieu Blanchette;Stephen I Wright;

The extent that both positive and negative selection vary across different portions of plant genomes remains poorly understood. Here, we sequence whole genomes of 13 Capsella grandiflora individuals and quantify the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we show that selection is strong in coding regions, but weak in most noncoding regions, with the exception of 5’ and 3’ untranslated regions (UTRs). However, estimates of selection in noncoding regions conserved across the Brassicaceae family show strong signals of selection. Additionally, we see reductions in neutral diversity around functional substitutions in both coding and conserved noncoding regions, indicating recent selective sweeps at these sites. Finally, using expression data from leaf tissue we show that genes that are more highly expressed experience stronger negative selection but comparable levels of positive selection to lowly expressed genes. Overall, we observe widespread positive and negative selection in coding and regulatory regions, but our results also suggest that both positive and negative selection in plant noncoding sequence are considerably rarer than in animal genomes.

2014-02-10

Evidence for widespread positive and negative selection in coding and conserved noncoding regions of Capsella grandiflora

10.1101/002428

Robert J Williamson;Emily B Josephs;Adrian E Platts;Khaled M Hazzouri;Annabelle Haudry;Mathieu Blanchette;Stephen I Wright;

The extent that both positive and negative selection vary across different portions of plant genomes remains poorly understood. Here, we sequence whole genomes of 13 Capsella grandiflora individuals and quantify the amount of selection across the genome. Using an estimate of the distribution of fitness effects, we show that selection is strong in coding regions, but weak in most noncoding regions, with the exception of 5’ and 3’ untranslated regions (UTRs). However, estimates of selection in noncoding regions conserved across the Brassicaceae family show strong signals of selection. Additionally, we see reductions in neutral diversity around functional substitutions in both coding and conserved noncoding regions, indicating recent selective sweeps at these sites. Finally, using expression data from leaf tissue we show that genes that are more highly expressed experience stronger negative selection but comparable levels of positive selection to lowly expressed genes. Overall, we observe widespread positive and negative selection in coding and regulatory regions, but our results also suggest that both positive and negative selection in plant noncoding sequence are considerably rarer than in animal genomes.

2014-06-09

Spectacle: Faster and more accurate chromatin state annotation using spectral learning

10.1101/002725

Jimin Song;Kevin C Chen;

Recently, a wealth of epigenomic data has been generated by biochemical assays and next-generation sequencing (NGS) technologies. In particular, histone modification data generated by the ENCODE project and other large-scale projects show specific patterns associated with regulatory elements in the human genome. It is important to build a unified statistical model to decipher the patterns of multiple histone modifications in a cell type to annotate chromatin states such as transcription start sites, enhancers and transcribed regions rather than to map histone modifications individually to regulatory elements.\n\nSeveral genome-wide statistical models have been developed based on hidden Markov models (HMMs). These methods typically use the Expectation-Maximization (EM) algorithm to estimate the parameters of the model. Here we used spectral learning, a state-of-the-art parameter estimation algorithm in machine learning. We found that spectral learning plus a few (up to five) iterations of local optimization of the likelihood outper-forms the standard EM algorithm. We also evaluated our software implementation called Spectacle on independent biological datasets and found that Spectacle annotated experimentally defined functional elements such as enhancers significantly better than a previous state-of-the-art method.\n\nSpectacle can be downloaded from https://github.com/jiminsong/Spectacle.

2014-02-14

Spectacle: Faster and more accurate chromatin state annotation using spectral learning

10.1101/002725

Jimin Song;Kevin C Chen;

Recently, a wealth of epigenomic data has been generated by biochemical assays and next-generation sequencing (NGS) technologies. In particular, histone modification data generated by the ENCODE project and other large-scale projects show specific patterns associated with regulatory elements in the human genome. It is important to build a unified statistical model to decipher the patterns of multiple histone modifications in a cell type to annotate chromatin states such as transcription start sites, enhancers and transcribed regions rather than to map histone modifications individually to regulatory elements.\n\nSeveral genome-wide statistical models have been developed based on hidden Markov models (HMMs). These methods typically use the Expectation-Maximization (EM) algorithm to estimate the parameters of the model. Here we used spectral learning, a state-of-the-art parameter estimation algorithm in machine learning. We found that spectral learning plus a few (up to five) iterations of local optimization of the likelihood outper-forms the standard EM algorithm. We also evaluated our software implementation called Spectacle on independent biological datasets and found that Spectacle annotated experimentally defined functional elements such as enhancers significantly better than a previous state-of-the-art method.\n\nSpectacle can be downloaded from https://github.com/jiminsong/Spectacle.

2014-03-09

A reassessment of consensus clustering for class discovery

10.1101/002642

Yasin Şenbabaoğlu;George Michailidis;Jun Z Li;

Consensus clustering (CC) is an unsupervised class discovery method widely used to study sample heterogeneity in high-dimensional datasets. It calculates \"consensus rate\" between any two samples as how frequently they are grouped together in repeated clustering runs under a certain degree of random perturbation. The pairwise consensus rates form a between-sample similarity matrix, which has been used (1) as a visual proof that clusters exist, (2) for comparing stability among clusters, and (3) for estimating the optimal number (K) of clusters. However, the sensitivity and specificity of CC have not been systemically studied. To assess its performance, we investigated the most common implementations of CC; and compared CC with other popular methods that also focus on cluster stability and estimation of K. We evaluated these methods using simulated datasets with either known structure or known absence of structure. Our results showed that (1) CC was able to divide randomly generated unimodal data into pre-specified numbers of clusters, and was able to show apparent stability of these chance partitions of known cluster-less data; (2) for data with known structure, the proportion of ambiguously clustered (PAC) pairs infers the known number of clusters more reliably than several commonly used K estimating methods; and (3) validation of the optimal K by choosing the most discriminant genes from the discovery cohort and applying them in an independent cohort often exaggerates the confidence in K due to inherent gene-gene correlations among the selected genes. While these results do not yet prove that any of the published studies using CC has generated false positive findings, they show that datasets with subtle or no structure are fully capable of producing strong evidence of consensus clustering. We therefore recommend caution is using CC in class discovery and validation.

2014-02-14

A reassessment of consensus clustering for class discovery

10.1101/002642

Yasin Şenbabaoğlu;George Michailidis;Jun Z Li;

Consensus clustering (CC) is an unsupervised class discovery method widely used to study sample heterogeneity in high-dimensional datasets. It calculates \"consensus rate\" between any two samples as how frequently they are grouped together in repeated clustering runs under a certain degree of random perturbation. The pairwise consensus rates form a between-sample similarity matrix, which has been used (1) as a visual proof that clusters exist, (2) for comparing stability among clusters, and (3) for estimating the optimal number (K) of clusters. However, the sensitivity and specificity of CC have not been systemically studied. To assess its performance, we investigated the most common implementations of CC; and compared CC with other popular methods that also focus on cluster stability and estimation of K. We evaluated these methods using simulated datasets with either known structure or known absence of structure. Our results showed that (1) CC was able to divide randomly generated unimodal data into pre-specified numbers of clusters, and was able to show apparent stability of these chance partitions of known cluster-less data; (2) for data with known structure, the proportion of ambiguously clustered (PAC) pairs infers the known number of clusters more reliably than several commonly used K estimating methods; and (3) validation of the optimal K by choosing the most discriminant genes from the discovery cohort and applying them in an independent cohort often exaggerates the confidence in K due to inherent gene-gene correlations among the selected genes. While these results do not yet prove that any of the published studies using CC has generated false positive findings, they show that datasets with subtle or no structure are fully capable of producing strong evidence of consensus clustering. We therefore recommend caution is using CC in class discovery and validation.

2014-02-15

A reassessment of consensus clustering for class discovery

10.1101/002642

Yasin Şenbabaoğlu;George Michailidis;Jun Z Li;

Consensus clustering (CC) is an unsupervised class discovery method widely used to study sample heterogeneity in high-dimensional datasets. It calculates \"consensus rate\" between any two samples as how frequently they are grouped together in repeated clustering runs under a certain degree of random perturbation. The pairwise consensus rates form a between-sample similarity matrix, which has been used (1) as a visual proof that clusters exist, (2) for comparing stability among clusters, and (3) for estimating the optimal number (K) of clusters. However, the sensitivity and specificity of CC have not been systemically studied. To assess its performance, we investigated the most common implementations of CC; and compared CC with other popular methods that also focus on cluster stability and estimation of K. We evaluated these methods using simulated datasets with either known structure or known absence of structure. Our results showed that (1) CC was able to divide randomly generated unimodal data into pre-specified numbers of clusters, and was able to show apparent stability of these chance partitions of known cluster-less data; (2) for data with known structure, the proportion of ambiguously clustered (PAC) pairs infers the known number of clusters more reliably than several commonly used K estimating methods; and (3) validation of the optimal K by choosing the most discriminant genes from the discovery cohort and applying them in an independent cohort often exaggerates the confidence in K due to inherent gene-gene correlations among the selected genes. While these results do not yet prove that any of the published studies using CC has generated false positive findings, they show that datasets with subtle or no structure are fully capable of producing strong evidence of consensus clustering. We therefore recommend caution is using CC in class discovery and validation.

2014-03-11

Non-specificity of Pitstop 2 in clathrin-mediated endocytosis

10.1101/002675

Anna K Willox;Yasmina M.E. Sahraoui;Stephen J Royle;

Small molecule inhibitors of clathrin-mediated endocytosis are highly desired for the dissection of membrane trafficking pathways in the lab and for potential use as anti-infectives in the clinic. One inhibition strategy is to prevent clathrin from contacting adaptor proteins so that clathrin-mediated endocytosis cannot occur. \"Pitstop\" compounds have been developed which block only one of the four functional interaction sites on the N-terminal domain of clathrin heavy chain. Despite this limitation, Pitstop 2 causes profound inhibition of clathrin-mediated endocytosis. In this study, we probed for non-specific activity of Pitstop 2 by examining its action in cells expressing clathrin heavy chain harbouring mutations in the N-terminal domain interaction sites. We conclude that the inhibition observed with this compound is due to non-specificity, i.e. it causes inhibition away from its proposed mode of action. We recommend that these compounds be used with caution in cells and that they should not be used to conclude anything of the function of clathrins N-terminal domain.

2014-02-13

Non-specificity of Pitstop 2 in clathrin-mediated endocytosis

10.1101/002675

Anna K Willox;Yasmina M.E. Sahraoui;Stephen J Royle;

Small molecule inhibitors of clathrin-mediated endocytosis are highly desired for the dissection of membrane trafficking pathways in the lab and for potential use as anti-infectives in the clinic. One inhibition strategy is to prevent clathrin from contacting adaptor proteins so that clathrin-mediated endocytosis cannot occur. \"Pitstop\" compounds have been developed which block only one of the four functional interaction sites on the N-terminal domain of clathrin heavy chain. Despite this limitation, Pitstop 2 causes profound inhibition of clathrin-mediated endocytosis. In this study, we probed for non-specific activity of Pitstop 2 by examining its action in cells expressing clathrin heavy chain harbouring mutations in the N-terminal domain interaction sites. We conclude that the inhibition observed with this compound is due to non-specificity, i.e. it causes inhibition away from its proposed mode of action. We recommend that these compounds be used with caution in cells and that they should not be used to conclude anything of the function of clathrins N-terminal domain.

2014-04-15

Production of systemically circulating Hedgehog by the intestine couples nutrition to growth and development

10.1101/002626

Jonathan Rodenfels;Oksana Lavrynenko;Sophie Ayciriex;Julio L Sampaio;Maria Carvalho;Andrej Shevchenko;Suzanne Eaton;

In Drosophila larvae, growth and developmental timing are regulated by nutrition in a tightly coordinated fashion. The networks that couple these processes are far from understood. Here, we show that the intestine responds to nutrient availability by regulating production of a circulating lipoprotein associated form of the signaling protein Hedgehog (Hh). Levels of circulating Hh tune the rates of growth and developmental timing in a coordinated fashion. Circulating Hh signals to the fat body to control larval growth. It regulates developmental timing by controlling ecdysteroid production in the prothoracic gland. Circulating Hh is especially important during starvation, when it is also required for mobilization of fat body triacylglycerol (TAG) stores. Thus, we demonstrate that Hh, previously known only for its local morphogenetic functions, also acts as a lipoprotein-associated endocrine hormone, coordinating the response of multiple tissues to nutrient availability.

2014-02-14

Production of systemically circulating Hedgehog by the intestine couples nutrition to growth and development

10.1101/002626

Jonathan Rodenfels;Oksana Lavrynenko;Sophie Ayciriex;Julio L Sampaio;Maria Carvalho;Andrej Shevchenko;Suzanne Eaton;

In Drosophila larvae, growth and developmental timing are regulated by nutrition in a tightly coordinated fashion. The networks that couple these processes are far from understood. Here, we show that the intestine responds to nutrient availability by regulating production of a circulating lipoprotein associated form of the signaling protein Hedgehog (Hh). Levels of circulating Hh tune the rates of growth and developmental timing in a coordinated fashion. Circulating Hh signals to the fat body to control larval growth. It regulates developmental timing by controlling ecdysteroid production in the prothoracic gland. Circulating Hh is especially important during starvation, when it is also required for mobilization of fat body triacylglycerol (TAG) stores. Thus, we demonstrate that Hh, previously known only for its local morphogenetic functions, also acts as a lipoprotein-associated endocrine hormone, coordinating the response of multiple tissues to nutrient availability.

2014-07-29

Production of systemically circulating Hedgehog by the intestine couples nutrition to growth and development

10.1101/002626

Jonathan Rodenfels;Oksana Lavrynenko;Sophie Ayciriex;Julio L Sampaio;Maria Carvalho;Andrej Shevchenko;Suzanne Eaton;

In Drosophila larvae, growth and developmental timing are regulated by nutrition in a tightly coordinated fashion. The networks that couple these processes are far from understood. Here, we show that the intestine responds to nutrient availability by regulating production of a circulating lipoprotein associated form of the signaling protein Hedgehog (Hh). Levels of circulating Hh tune the rates of growth and developmental timing in a coordinated fashion. Circulating Hh signals to the fat body to control larval growth. It regulates developmental timing by controlling ecdysteroid production in the prothoracic gland. Circulating Hh is especially important during starvation, when it is also required for mobilization of fat body triacylglycerol (TAG) stores. Thus, we demonstrate that Hh, previously known only for its local morphogenetic functions, also acts as a lipoprotein-associated endocrine hormone, coordinating the response of multiple tissues to nutrient availability.

2014-11-03

mangal - making ecological network analysis simple

10.1101/002634

Timothée E Poisot;Benjamin Baiser;Jennifer A Dunne;Sonia Kéfi;Francois Massol;Nicolas Mouquet;Tamara N Romanuk;Daniel B Stouffer;Spencer A Wood;Dominique Gravel;

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package (rmangal) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

2014-02-12

mangal - making ecological network analysis simple

10.1101/002634

Timothée E Poisot;Benjamin Baiser;Jennifer A Dunne;Sonia Kéfi;Francois Massol;Nicolas Mouquet;Tamara N Romanuk;Daniel B Stouffer;Spencer A Wood;Dominique Gravel;

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package (rmangal) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

2014-09-30

mangal - making ecological network analysis simple

10.1101/002634

Timothée E Poisot;Benjamin Baiser;Jennifer A Dunne;Sonia Kéfi;Francois Massol;Nicolas Mouquet;Tamara N Romanuk;Daniel B Stouffer;Spencer A Wood;Dominique Gravel;

The study of ecological networks is severely limited by (i) the difficulty to access data, (ii) the lack of a standardized way to link meta-data with interactions, and (iii) the disparity of formats in which ecological networks themselves are represented. To overcome these limitations, we conceived a data specification for ecological networks. We implemented a database respecting this standard, and released a R package (rmangal) allowing users to programmatically access, curate, and deposit data on ecological interactions. In this article, we show how these tools, in conjunctions with other frameworks for the programmatic manipulation of open ecological data, streamlines the analysis process, and improves eplicability and reproducibility of ecological networks studies.

2015-02-24

Evolutionary rates for multivariate traits: the role of selection and genetic variation

10.1101/002683

William Pitchers;Jason B. Wolf;Tom Tregenza;John Hunt;Ian Dworkin;

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders equation [Formula], which predicts evolutionary change for a suite of phenotypic traits [Formula] as a product of directional selection acting on them ({beta}) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and {beta} to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are in part due to genetic architecture. We find evidence some evidence that sexually selected traits exhibit faster rates of evolution compared to life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

2014-02-14

Evolutionary rates for multivariate traits: the role of selection and genetic variation

10.1101/002683

William Pitchers;Jason B. Wolf;Tom Tregenza;John Hunt;Ian Dworkin;

A fundamental question in evolutionary biology is the relative importance of selection and genetic architecture in determining evolutionary rates. Adaptive evolution can be described by the multivariate breeders equation [Formula], which predicts evolutionary change for a suite of phenotypic traits [Formula] as a product of directional selection acting on them ({beta}) and the genetic variance-covariance matrix for those traits (G). Despite being empirically challenging to estimate, there are enough published estimates of G and {beta} to allow for synthesis of general patterns across species. We use published estimates to test the hypotheses that there are systematic differences in the rate of evolution among trait types, and that these differences are in part due to genetic architecture. We find evidence some evidence that sexually selected traits exhibit faster rates of evolution compared to life-history or morphological traits. This difference does not appear to be related to stronger selection on sexually selected traits. Using numerous proposed approaches to quantifying the shape, size and structure of G we examine how these parameters relate to one another, and how they vary among taxonomic and trait groupings. Despite considerable variation, they do not explain the observed differences in evolutionary rates.

2014-05-05

Differential gene expression and alternative splicing in insect immune specificity

10.1101/002709

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

2014-02-14

Differential gene expression and alternative splicing in insect immune specificity

10.1101/002709

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

2014-02-15

Differential gene expression and alternative splicing in insect immune specificity

10.1101/002709

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

2014-03-12

Differential gene expression and alternative splicing in insect immune specificity

10.1101/002709

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

2014-04-30

Differential gene expression and alternative splicing in insect immune specificity

10.1101/002709

Carolyn Riddell;Juan David Lobaton Garces;Sally Adams;Seth M Barribeau;David Twell;Eamonn Mallon;

Ecological studies routinely show genotype-genotype interactions between insects and their parasites. The mechanisms behind these interactions are not clearly understood. Using the bumblebee Bombus terrestris / trypanosome Crithidia bombi model system, we have carried out a transcriptome-wide analysis of gene expression and alternative splicing in bees during C. bombi infection. We have performed four analyses, 1) comparing gene expression in infected and non-infected bees 24 hours after infection by Crithidia bombi, 2) comparing expression at 24 and 48 hours after C.bombi infection, 3) searching for differential gene expression associated with the host-parasite genotype-genotype interaction at 24 hours after infection and 4) searching for alternative splicing associated with the host-parasite genotype-genotype interaction at 24 hours post infection. We found a large number of genes differentially regulated related to numerous canonical immune pathways. These genes include receptors, signaling pathways and effectors. We discovered a possible interaction between the peritrophic membrane and the insect immune system in defense against Crithidia. Most interestingly we found differential expression and alternative splicing of Dscam related transcripts and a novel immunoglobulin related gene Twitchin depends on the genotype-genotype interactions of the given bumblebee colony and Crithidia strain.

2014-06-30

Cell specific eQTL analysis without sorting cells

10.1101/002600

Harm-Jan Westra;Danny Arends;Tõnu Esko;Marjolein J. Peters;Claudia Schurmann;Katharina Schramm;Johannes Kettunen;Hanieh Yaghootkar;Benjamin Fairfax;Anand Kumar Andiappan;Yang Li;Jingyuan Fu;Juha Karjalainen;Mathieu Platteel;Marijn Visschedijk;Rinse Weersma;Silva Kasela;Lili Milani;Liina Tserel;Pärt Peterson;Eva Reinmaa;Albert Hofman;André G. Uitterlinden;Fernando Rivadeneira;Georg Homuth;Astrid Petersmann;Roberto Lorbeer;Holger Prokisch;Thomas Meitinger;Christian Herder;Michael Roden;Harald Grallert;Samuli Ripatti;Markus Perola;Adrew R. Wood;David Melzer;Luigi Ferrucci;Andrew B. Singleton;Dena

Expression quantitative trait locus (eQTL) mapping on tissue, organ or whole organism data can detect associations that are generic across cell types. We describe a new method to focus upon specific cell types without first needing to sort cells. We applied the method to whole blood data from 5,683 samples and demonstrate that SNPs associated with Crohn's disease preferentially affect gene expression within neutrophils.

2014-02-12

The immunologic V-gene repertoire in mammals

10.1101/002667

David N Olivieri;Bernardo von Haeften;Christian Sánchez-Espinel;Francisco Gambón-Deza;

From recent whole genome shotgun data of 48 mammalian species, we have used our software VgenExtractor to obtain the functional V-gene sequence repertoire in order to conduct comparative phylogenetic studies. These studies reveal a large variation in the number of V-genes across mammalian species, ranging from a mere 36 V-genes in dolphins to nearly 600 V-genes in rats. Monotremes and marsupials are the only mammals possessing an additional locus, the TRMV, apart from the seven common loci found in mammals. Also, we show evidence for the loss of the light chain loci, specifically the V{kappa} chain in one microbat, and the V{lambda} chain in one rodent species. Finally, we suggest different features related to the evolution of immunoglobulin and T cell receptor loci, where frequent sequence duplications are seen in the former, while preserved and undiversified lineages are observed in the latter. All the V-gene sequences described in this study are available in the public database repository vgenerepertoire.org.

2014-02-13

Genomic V-gene repertoire in reptiles

10.1101/002618

David N Olivieri;Bernardo von Haeften;Christian Sánchez-Espinel;Jose Faro;Francisco Gambón-Deza;

Reptiles and mammals diverged over 300 million years ago, creating two parallel evolutionary lineages amongst terrestrial vertebrates. In reptiles, two main evolutionary lines emerged, one gave rise to Squamata, while the other gave rise to Testudines, Crocodylia and birds. In this study, we determined the genomic variable (V)-gene repertoire in reptiles corresponding to the three main immunoglobulin (Ig) loci and the four main T-cell receptor (TCR) loci. We show that squamata lack the TCR{gamma} /{delta} genes and snakes lack the V{kappa} genes. In representative species of testudines and crocodiles, the seven major Ig and TCR loci are maintained. As in mammals, genes of the Ig loci can be grouped into well-defined clans through a multi-species phylogenetic analysis. We show that the reptile VH and V{lambda} genes are distributed amongst the established mammalian clans, while their V{kappa} genes are found within a single clan, nearly exclusive from the mammalian sequences. The reptile and mammal V-genes of the TRA locus cluster into six common evolutionary clans. In contrast, the reptile V-genes from the TRB locus cluster into three clans, which have few mammalian members. In this locus, the V-gene sequences from mammals appear to have undergone different evolutionary diversification processes that occurred outside these shared reptile clans.

2014-02-12

Neuroanatomical diversity of corpus callosum and brain volume in the Autism Brain Imaging Data Exchange (Abide) project

10.1101/002691

Aline Lefebvre;Anita Beggiato;Thomas Bourgeron;Roberto Toro;

The corpus callosum - the main pathway for long-distance inter-hemispheric integration in the human brain - has been frequently reported to be smaller among autistic patients compared with non-autistic controls. We conducted a meta-analysis of the literature which suggested a statistically significant difference. However, the studies included were heavily underpowered: on average only 20% power to detect differences of 0.3 standard deviations, which makes it difficult to establish the reality of such a difference. We therefore studied the size of the corpus callosum among 694 subjects (328 patients, 366 controls) from the Abide cohort. Despite having achieved 99% power to detect statistically significant differences of 0.3 standard deviations, we did not observe any. To better understand the neuroanatomical diversity of the corpus callosum, and the possible reasons for the previous findings, we analysed the relationship between its size, the size of the brain, intracranial volume and intelligence scores. The corpus callosum appeared to scale non-linearly with brain size, with large brains having a proportionally smaller corpus callosum. Additionally, intelligence scores correlated with brain volume among controls but the correlation was significantly weaker among patients. We used simulations to determine to which extent these two effects could lead to artefactual differences in corpus callosum size within populations. We observed that, were there a difference in brain volume between cases and controls, normalising corpus callosum size by brain volume would not eliminate the brain volume effect, but adding brain volume as a covariate in a linear model would. Finally, we observed that because of the weaker correlation of intelligence scores and brain volume among patients, matching populations by intelligence scores could result in a bias towards including more patients with large brain volumes, inducing an artificial difference. Overall, our results highlight the necessity for open data sharing efforts such as Abide to provide a more solid ground for the discovery of neuroimaging biomarkers, within the context of the wide human neuroanatomical diversity.

2014-02-14

Neuroanatomical diversity of corpus callosum and brain volume in the Autism Brain Imaging Data Exchange (Abide) project

10.1101/002691

Aline Lefebvre;Anita Beggiato;Thomas Bourgeron;Roberto Toro;

The corpus callosum - the main pathway for long-distance inter-hemispheric integration in the human brain - has been frequently reported to be smaller among autistic patients compared with non-autistic controls. We conducted a meta-analysis of the literature which suggested a statistically significant difference. However, the studies included were heavily underpowered: on average only 20% power to detect differences of 0.3 standard deviations, which makes it difficult to establish the reality of such a difference. We therefore studied the size of the corpus callosum among 694 subjects (328 patients, 366 controls) from the Abide cohort. Despite having achieved 99% power to detect statistically significant differences of 0.3 standard deviations, we did not observe any. To better understand the neuroanatomical diversity of the corpus callosum, and the possible reasons for the previous findings, we analysed the relationship between its size, the size of the brain, intracranial volume and intelligence scores. The corpus callosum appeared to scale non-linearly with brain size, with large brains having a proportionally smaller corpus callosum. Additionally, intelligence scores correlated with brain volume among controls but the correlation was significantly weaker among patients. We used simulations to determine to which extent these two effects could lead to artefactual differences in corpus callosum size within populations. We observed that, were there a difference in brain volume between cases and controls, normalising corpus callosum size by brain volume would not eliminate the brain volume effect, but adding brain volume as a covariate in a linear model would. Finally, we observed that because of the weaker correlation of intelligence scores and brain volume among patients, matching populations by intelligence scores could result in a bias towards including more patients with large brain volumes, inducing an artificial difference. Overall, our results highlight the necessity for open data sharing efforts such as Abide to provide a more solid ground for the discovery of neuroimaging biomarkers, within the context of the wide human neuroanatomical diversity.

2014-02-15

Synthesis and patterning of tunable multiscale materials with engineered cells

10.1101/002659

Allen Y Chen;Urartu O.S. Seker;Michelle Y Lu;Robert J Citorik;Timothy Lu;

A major challenge in materials science is to create self-assembling, functional, and environmentally responsive materials which can be patterned across multiple length scales. Natural biological systems, such as biofilms, shells, and skeletal tissues, implement dynamic regulatory programs to assemble complex multiscale materials comprised of living and non-living components1-9. Such systems can provide inspiration for the design of heterogeneous functional systems which integrate biotic and abiotic materials via hierarchical self-assembly. Here, we present a synthetic-biology platform for synthesizing and patterning self-assembled functional amyloid materials across multiple length scales with bacterial biofilms. We engineered Escherichia coli curli amyloid production under the tight control of synthetic regulatory circuits and interfaced amyloids with inorganic materials to create a biofilm-based electrical switch whose conductance can be selectively toggled by specific environmental signals. Furthermore, we externally tuned synthetic biofilms to build nanoscale amyloid biomaterials with different structure and composition through the controlled expression of their constituent subunits with artificial gene circuits. By using synthetic cell-cell communication, our engineered biofilms can also autonomously manufacture dynamic materials whose structure and composition change with time. In addition, we show that by combining subunit-level protein engineering, controlled genetic expression of self-assembling subunit proteins, and macroscale spatial gradients, synthetic biofilms can pattern protein biomaterials across multiple length scales. This work lays a foundation for synthesizing, patterning, and controlling composite materials with engineered biological systems. We envision that this approach can be expanded to other cellular and biomaterials contexts for the construction of self-organizing, environmentally responsive, and tunable multiscale composite materials with heterogeneous functionalities.

2014-02-14

Synthesis and patterning of tunable multiscale materials with engineered cells

10.1101/002659

Allen Y Chen;Urartu O.S. Seker;Michelle Y Lu;Robert J Citorik;Timothy Lu;

A major challenge in materials science is to create self-assembling, functional, and environmentally responsive materials which can be patterned across multiple length scales. Natural biological systems, such as biofilms, shells, and skeletal tissues, implement dynamic regulatory programs to assemble complex multiscale materials comprised of living and non-living components1-9. Such systems can provide inspiration for the design of heterogeneous functional systems which integrate biotic and abiotic materials via hierarchical self-assembly. Here, we present a synthetic-biology platform for synthesizing and patterning self-assembled functional amyloid materials across multiple length scales with bacterial biofilms. We engineered Escherichia coli curli amyloid production under the tight control of synthetic regulatory circuits and interfaced amyloids with inorganic materials to create a biofilm-based electrical switch whose conductance can be selectively toggled by specific environmental signals. Furthermore, we externally tuned synthetic biofilms to build nanoscale amyloid biomaterials with different structure and composition through the controlled expression of their constituent subunits with artificial gene circuits. By using synthetic cell-cell communication, our engineered biofilms can also autonomously manufacture dynamic materials whose structure and composition change with time. In addition, we show that by combining subunit-level protein engineering, controlled genetic expression of self-assembling subunit proteins, and macroscale spatial gradients, synthetic biofilms can pattern protein biomaterials across multiple length scales. This work lays a foundation for synthesizing, patterning, and controlling composite materials with engineered biological systems. We envision that this approach can be expanded to other cellular and biomaterials contexts for the construction of self-organizing, environmentally responsive, and tunable multiscale composite materials with heterogeneous functionalities.

2014-03-27

Immune stimulation reduces sleep and memory ability in Drosophila melanogaster

10.1101/002717

Eamonn Mallon;Akram Alghamdi;Robert Holdbrook;Ezio Rosato;

Psychoneuroimmunology studies the increasing number of connections between neurobiology and immunology. We establish Drosophila melanogaster as a tractable model in this field by demonstrating the effects of the immune response on two fundamental behaviours: sleep and memory ability.\n\nWe used the Geneswitch system to upregulate peptidoglycan receptor protein (PGRP) expression, thereby stimulating the immune system in the absence of infection. Geneswitch was activated by feeding the steroid RU486, to the flies. Importantly, by stimulating the immune system of adult flies in the absence of infection we have avoided the added complications of developmental and disease effects that have confounded other studies. We used an aversive classical conditioning paradigm to quantify memory and measures of activity to infer sleep.\n\nImmune stimulated flies exhibited reduced levels of sleep, which could not be explained by a generalised increase in waking activity. The effects on sleep were more pronounced for day compared to night sleep. Immune stimulated flies also showed a reduction in memory abilities.\n\nThese are important results as they establish Drosophila as a model for immune-neural interactions and provide a possible role for sleep in the interplay between the immune response and memory.

2014-02-14

Immune stimulation reduces sleep and memory ability in Drosophila melanogaster

10.1101/002717

Eamonn Mallon;Akram Alghamdi;Robert Holdbrook;Ezio Rosato;

Psychoneuroimmunology studies the increasing number of connections between neurobiology and immunology. We establish Drosophila melanogaster as a tractable model in this field by demonstrating the effects of the immune response on two fundamental behaviours: sleep and memory ability.\n\nWe used the Geneswitch system to upregulate peptidoglycan receptor protein (PGRP) expression, thereby stimulating the immune system in the absence of infection. Geneswitch was activated by feeding the steroid RU486, to the flies. Importantly, by stimulating the immune system of adult flies in the absence of infection we have avoided the added complications of developmental and disease effects that have confounded other studies. We used an aversive classical conditioning paradigm to quantify memory and measures of activity to infer sleep.\n\nImmune stimulated flies exhibited reduced levels of sleep, which could not be explained by a generalised increase in waking activity. The effects on sleep were more pronounced for day compared to night sleep. Immune stimulated flies also showed a reduction in memory abilities.\n\nThese are important results as they establish Drosophila as a model for immune-neural interactions and provide a possible role for sleep in the interplay between the immune response and memory.

2014-03-12

Large-scale non-targeted metabolomic profiling in three human population-based studies

10.1101/002782

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

2014-02-17

Large-scale non-targeted metabolomic profiling in three human population-based studies

10.1101/002782

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

2014-02-19

Large-scale non-targeted metabolomic profiling in three human population-based studies

10.1101/002782

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

2015-05-28

Large-scale non-targeted metabolomic profiling in three human population-based studies

10.1101/002782

Andrea Ganna;Tove Fall;Samira Salihovic;Woojoo Lee;Corey D Broeckling;Jitender Kumar;Sara Hägg;Markus Stenemo;Patrik K.E. Magnusson;Jessica Prenni;Lars Lind;Yudi Pawitan;Erik Ingelsson;

Metabolomic profiling is an emerging technique in life sciences. Human studies using these techniques have been performed in a small number of individuals or have been targeted at a restricted number of metabolites. In this article, we propose a data analysis workflow to perform non-targeted metabolomic profiling in large human population-based studies using ultra performance liquid chromatography-mass spectrometry (UPLC-MS). We describe challenges and propose solutions for quality control, statistical analysis and annotation of metabolic features. Using the data analysis workflow, we detected more than 8,000 metabolic features in serum samples from 2,489 fasting individuals. As an illustrative example, we performed a non-targeted metabolome-wide association analysis of high-sensitive C-reactive protein (hsCRP) and detected 407 metabolic features corresponding to 90 unique metabolites that could be replicated in an external population. Our results reveal unexpected biological associations, such as metabolites identified as monoacylphosphorylcholines (LysoPC) being negatively associated with hsCRP. R code and fragmentation spectra for all metabolites are made publically available. In conclusion, the results presented here illustrate the viability and potential of non-targeted metabolomic profiling in large population-based studies.

2015-11-12

A Novel Approach for Multi-Domain and Multi-Gene Family Identification Provides Insights into Evolutionary Dynamics of Disease Resistance Genes in Core Eudicot Plants

10.1101/002766

Johannes A. Hofberger;Beifei Zhou;Haibao Tang;Jonathan DG Jones;M. Eric Schranz;

Recent advances in DNA sequencing techniques resulted in more than forty sequenced plant genomes representing a diverse set of taxa of agricultural, energy, medicinal and ecological importance. However, gene family curation is often only inferred from DNA sequence homology and lacks insights into evolutionary processes contributing to gene family dynamics. In a comparative genomics framework, we integrated multiple lines of evidence provided by gene synteny, sequence homology and protein-based Hidden Markov Modelling to extract homologous super-clusters composed of multi-domain resistance (R)-proteins of the NB-LRR type (for NUCLEOTIDE BINDING/LEUCINE-RICH REPEATS), that are involved in plant innate immunity. To assess the diversity of R-proteins within and between species, we screened twelve eudicot plant genomes including six major crops and found a total of 2,363 NB-LRR genes. Our curated R-proteins set shows a 50% average for tandem duplicates and a 22% fraction of gene copies retained from ancient polyploidy events (ohnologs). We provide evidence for strong positive selection acting on all identified genes and show significant differences in molecular evolution rates (Ka/Ks-ratio) among tandem- (mean = 1.59), ohnolog (mean = 1.36) and singleton (mean = 1.22) R-gene duplicates. To foster the process of gene-edited plant breeding, we report species-specific presence/absence of all 140 NB-LRR genes present in the model plant Arabidopsis and describe four distinct clusters of NB-LRR \"gatekeeper\" loci sharing syntelogs across all analyzed genomes. In summary, we designed and implemented an easy-to-follow computational framework for super-gene family identification, and provide the most curated set of NB-LRR genes whose genetic versatility among twelve lineages can underpin crop improvement.

2014-02-17

Fluorescent sensors for activity and regulation of the nitrate transceptor CHL1/NRT1.1 and oligopeptide transporters

10.1101/002741

Cheng Hsun Ho;Wolf B. Frommer;

To monitor nitrate and peptide transport activity in vivo, we converted the dual-affinity nitrate transceptor CHL1/NRT1.1/NPF6.3 and four related oligopeptide transporters PTR1, 2, 4 and 5 into fluorescence activity sensors (NiTrac1, PepTrac). Substrate addition to yeast expressing transporter fusions with yellow fluorescent protein and mCerulean triggered substrate-dependent donor quenching or resonance energy transfer. Fluorescence changes were nitrate/peptide-specific, respectively. Like CHL1, NiTrac1 had biphasic kinetics. Mutation of T101A eliminated high-affinity transport and blocked the fluorescence response to low nitrate. NiTrac was used for characterizing side chains considered important for substrate interaction, proton coupling, and regulation. We observed a striking correlation between transport activity and sensor output. Coexpression of NiTrac with known calcineurin-like proteins (CBL1, 9; CIPK23) and candidates identified in an interactome screen (CBL1, KT2, WNKinase 8) blocked NiTrac1 responses, demonstrating the suitability for in vivo analysis of activity and regulation. The new technology is applicable in plant and medical research.

2014-02-18

ESCRT-0 is not required for ectopic Notch activation and tumor suppression in Drosophila

10.1101/002790

Emiliana Tognon;Nadine Wollscheid;Katia Cortese;Carlo Tacchetti;thomas vaccari;

Multivesicular endosome (MVE) sorting depends on proteins of the Endosomal Sorting Complex Required for Transport (ESCRT) family. These are organized in four complexes (ESCRT-0, -I, -II, -III) that act in a sequential fashion to deliver ubiquitylated cargoes into the internal luminal vesicles (ILVs) of the MVE. Drosophila genes encoding ESCRT-I, -II, -III components function in sorting signaling receptors, including Notch and the JAK/STAT signaling receptor Domeless. Loss of ESCRT-I, -II, -III in Drosophila epithelia causes altered signaling and cell polarity, suggesting that ESCRTs genes are tumor suppressors. However, the nature of the tumor suppressive function of ESCRTs, and whether tumor suppression is linked to receptor sorting is unclear. Unexpectedly, a null mutant in Hrs, encoding one of components of the ESCRT-0 complex, which acts upstream of ESCRT-I, -II, -III in MVE sorting is dispensable for tumor suppression. Here, we report that two Drosophila epithelia lacking activity of Stam, the other known components of the ESCRT-0 complex, or of both Hrs and Stam fail to degrade signaling receptors. However, mutant tissue surprisingly maintains normal apico-basal polarity and proliferation control and does not display ectopic Notch signaling activation, unlike cells that lack ESCRT-I, -II, -III activity. Overall, our in vivo data indicate that the ESCRT-0 complex plays no crucial role in regulation of tumor suppression, and suggest re-evaluation of the relationship of signaling modulation in endosomes and tumorigenesis.

2014-02-18

Migration and interaction in a contact zone: mtDNA variation among Bantu-speakers in southern Africa

10.1101/002808

Chiara Barbieri;Mário Vicente;Sandra Oliveira;Koen Bostoen;Jorge Rocha;Mark Stoneking;Brigitte Pakendorf;

Bantu speech communities expanded over large parts of sub-Saharan Africa within the last 4000-5000 years, reaching different parts of southern Africa 1200-2000 years ago. The Bantu languages subdivide in several major branches, with languages belonging to the Eastern and Western Bantu branches spreading over large parts of Central, Eastern, and Southern Africa. There is still debate whether this linguistic divide is correlated with a genetic distinction between Eastern and Western Bantu speakers. During their expansion, Bantu speakers would have come into contact with diverse local populations, such as the Khoisan hunter-gatherers and pastoralists of southern Africa, with whom they may have intermarried. In this study, we analyze complete mtDNA genome sequences from over 900 Bantu-speaking individuals from Angola, Zambia, Namibia, and Botswana to investigate the demographic processes at play during the last stages of the Bantu expansion. Our results show that most of these Bantu-speaking populations are genetically very homogenous, with no genetic division between speakers of Eastern and Western Bantu languages. Most of the mtDNA diversity in our dataset is due to different degrees of admixture with autochthonous populations. Only the pastoralist Himba and Herero stand out due to high frequencies of particular L3f and L3d lineages; the latter are also found in the neighboring Damara, who speak a Khoisan language and were foragers and small-stock herders. In contrast, the close cultural and linguistic relatives of the Herero and Himba, the Kuvale, are genetically similar to other Bantu-speakers. Nevertheless, as demonstrated by resampling tests, the genetic divergence of Herero, Himba, and Kuvale is compatible with a common shared ancestry with high levels of drift and differential female admixture with local pre-Bantu populations.

2014-02-18

Widespread signals of convergent adaptation to high altitude in Asia and America

10.1101/002816

Matthieu Foll;Oscar E. Gaggiotti;Josephine T. Daub;Alexandra Vatsiou;Laurent Excoffier;

Living at high-altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can be also due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

2014-02-19

Widespread signals of convergent adaptation to high altitude in Asia and America

10.1101/002816

Matthieu Foll;Oscar E. Gaggiotti;Josephine T. Daub;Alexandra Vatsiou;Laurent Excoffier;

Living at high-altitude is one of the most difficult challenges that humans had to cope with during their evolution. Whereas several genomic studies have revealed some of the genetic bases of adaptations in Tibetan, Andean and Ethiopian populations, relatively little evidence of convergent evolution to altitude in different continents has accumulated. This lack of evidence can be due to truly different evolutionary responses, but it can be also due to the low power of former studies that have mainly focused on populations from a single geographical region or performed separate analyses on multiple pairs of populations to avoid problems linked to shared histories between some populations. We introduce here a hierarchical Bayesian method to detect local adaptation that can deal with complex demographic histories. Our method can identify selection occurring at different scales, as well as convergent adaptation in different regions. We apply our approach to the analysis of a large SNP dataset from low- and high-altitude human populations from America and Asia. The simultaneous analysis of these two geographic areas allows us to identify several candidate genome regions for altitudinal selection, and we show that convergent evolution among continents has been quite common. In addition to identifying several genes and biological processes involved in high altitude adaptation, we identify two specific biological pathways that could have evolved in both continents to counter toxic effects induced by hypoxia.

2014-09-26

A GWAS platform built on iPlant cyber-infrastructure

10.1101/002881

Liya Wang;Doreen Ware;Carol Lushbough;Nirav Merchant;Lincoln Stein;

We demonstrated a flexible Genome-Wide Association Study (GWAS) platform built upon the iPlant Collaborative Cyber-infrastructure. The platform supports big data management, sharing, and large scale study of both genotype and phenotype data on clusters. End users can add their own analysis tools, and create customized analysis workflows through the graphical user interfaces in both iPlant Discovery Environment and BioExtract server.

2014-02-20

HTSeq - A Python framework to work with high-throughput sequencing data

10.1101/002824

Simon Anders;Paul Theodor Pyl;Wolfgang Huber;

MotivationA large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed.\n\nResultsWe present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.\n\nAvailabilityHTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index https://pypi.python.org/pypi/HTSeq.\n\[email protected]

2014-02-20

HTSeq - A Python framework to work with high-throughput sequencing data

10.1101/002824

Simon Anders;Paul Theodor Pyl;Wolfgang Huber;

MotivationA large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed.\n\nResultsWe present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes.\n\nAvailabilityHTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index https://pypi.python.org/pypi/HTSeq.\n\[email protected]

2014-08-19

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

10.1101/002832

Michael I Love;Wolfgang Huber;Simon Anders;

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

2014-02-19

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

10.1101/002832

Michael I Love;Wolfgang Huber;Simon Anders;

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

2014-05-27

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

10.1101/002832

Michael I Love;Wolfgang Huber;Simon Anders;

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html.

2014-11-17

An experimentally determined evolutionary model dramatically improves phylogenetic fit

10.1101/002899

Jesse D Bloom;

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

2014-02-20

An experimentally determined evolutionary model dramatically improves phylogenetic fit

10.1101/002899

Jesse D Bloom;

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

2014-03-02

An experimentally determined evolutionary model dramatically improves phylogenetic fit

10.1101/002899

Jesse D Bloom;

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

2014-03-05

An experimentally determined evolutionary model dramatically improves phylogenetic fit

10.1101/002899

Jesse D Bloom;

All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.

2014-04-27

Mapping the structure of drosophilid behavior

10.1101/002873

Gordon J Berman;Daniel M Choi;William Bialek;Joshua W Shaevitz;

Most animals possess the ability to actuate a vast diversity of movements, ostensibly constrained only by morphology and physics. In practice, however, a frequent assumption in behavioral science is that most of an animals activities can be described in terms of a small set of stereotyped motifs. Here we introduce a method for mapping the behavioral space of organisms, relying only upon the underlying structure of postural movement data to organize and classify behaviors. We find that six different drosophilid species each perform a mix of non-stereotyped actions and over one hundred hierarchically-organized, stereotyped behaviors. Moreover, we use this approach to compare these species behavioral spaces, systematically identifying subtle behavioral differences between closely-related species.

2014-02-20

No evidence that natural selection has been less effective at removing deleterious mutations in Europeans than in West Africans

10.1101/002865

Ron Do;Daniel Balick;Heng Li;Ivan Adzhubei`;Shamil Sunyaev;David Reich;

Non-African populations have experienced major bottlenecks in the time since their split from West Africans, which has led to the hypothesis that natural selection to remove weakly deleterious mutations may have been less effective in non-Africans. To directly test this hypothesis, we measure the per-genome accumulation of deleterious mutations across diverse humans. We fail to detect any significant differences, but find that archaic Denisovans accumulated non-synonymous mutations at a higher rate than modern humans, consistent with the longer separation time of modern and archaic humans. We also revisit the empirical patterns that have been interpreted as evidence for less effective removal of deleterious mutations in non-Africans than in West Africans, and show they are not driven by differences in selection after population separation, but by neutral evolution.

2014-02-20

Functional normalization of 450k methylation array data improves replication in large cancer studies

10.1101/002956

Jean-Philippe Fortin;Aurelie Labbe;Mathieu Lemire;Brent W. Zanke;Thomas J. Hudson;Elana J. Fertig;Celia M.T. Greenwood;Kasper D. Hansen;

We propose an extension to quantile normalization which removes unwanted technical variation using control probes. We adapt our algorithm, functional normalization, to the Illumina 450k methylation array and address the open problem of normalizing methylation data with global epigenetic changes, such as human cancers. Using datasets from The Cancer Genome Atlas and a large case-control study, we show that our algorithm outperforms all existing normalization methods with respect to replication of results between experiments, and yields robust results even in the presence of batch effects. Functional normalization can be applied to any microarray platform, provided suitable control probes are available.

2014-02-23

LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies

10.1101/002931

Brendan Bulik-Sullivan;Po-Ru Loh;Hilary Finucane;Stephan Ripke;Jian Yang;Schizophrenia Working Group Psychiatric Genomics Consortium;Nick Patterson;Mark J Daly;Alkes L Price;Benjamin M Neale;

Both polygenicity1,2 (i.e. many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification3, can yield inflated distributions of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from bias and true signal from polygenicity. We have developed an approach that quantifies the contributions of each by examining the relationship between test statistics and linkage disequilibrium (LD). We term this approach LD Score regression. LD Score regression provides an upper bound on the contribution of confounding bias to the observed inflation in test statistics and can be used to estimate a more powerful correction factor than genomic control4-14. We find strong evidence that polygenicity accounts for the majority of test statistic inflation in many GWAS of large sample size.

2014-02-21

Spatial Information in Large-Scale Neural Recordings

10.1101/002923

Thaddeus R Cybulski;Joshua I Glaser;Adam H Marblestone;Bradley M Zamft;Edward S Boyden;George M Church;Konrad P Kording;

A central issue in neural recording is that of distinguishing the activities of many neurons. Here, we develop a framework, based on Fisher information, to quantify how separable a neurons activity is from the activities of nearby neurons. We (1) apply this framework to model information flow and spatial distinguishability for several electrical and optical neural recording methods, (2) provide analytic expressions for information content, and (3) demonstrate potential applications of the approach. This method generalizes to many recording devices that resolve objects in space and thus may be useful in the design of next-generation scalable neural recording systems.

2014-02-21

Population diversification in a yeast metabolic program promotes anticipation of environmental shifts

10.1101/002907

Ophelia S Venturelli;Ignacio Zuleta;Richard M Murray;Hana El-Samad;

Delineating the strategies by which cells contend with combinatorial changing environments is crucial for understanding cellular regulatory organization. When presented with two carbon sources, microorganisms first consume the carbon substrate that supports the highest growth rate (e.g. glucose) and then switch to the secondary carbon source (e.g. galactose), a paradigm known as the Monod model. Sequential sugar utilization has been attributed to transcriptional repression of the secondary metabolic pathway, followed by activation of this pathway upon depletion of the preferred carbon source. In this work, we challenge this notion. Although Saccharomyces cerevisiae cells consume glucose before galactose, we demonstrate that the galactose regulatory pathway is activated in a fraction of the cell population hours before glucose is fully consumed. This early activation reduces the time required for the population to transition between the two metabolic programs and provides a fitness advantage that might be crucial in competitive environments. Importantly, these findings define a new paradigm for the response of microbial populations to combinatorial carbon sources.

2014-02-21

Efficient synergistic single-cell genome assembly

10.1101/002972

Narjes S. Movahedi;Zeinab Taghavi;Mallory Embree;Harish Nagarajan;Karsten Zengler;Hamidreza Chitsaz;

As the vast majority of all microbes are unculturable, single-cell sequencing has become a significant method to gain insight into microbial physiology. Single-cell sequencing methods, currently powered by multiple displacement genome amplification (MDA), have passed important milestones such as finishing and closing the genome of a prokaryote. However, the quality and reliability of genome assemblies from single cells are still unsatisfactory due to uneven coverage depth and the absence of scattered chunks of the genome in the final collection of reads caused by MDA bias. In this work, our new algorithm Hybrid De novo Assembler (HyDA) demonstrates the power of co-assembly of multiple single-cell genomic data sets through significant improvement of the assembly quality in terms of predicted functional elements and length statistics. Co-assemblies contain significantly more base pairs and protein coding genes, cover more subsystems, and consist of longer contigs compared to individual assemblies by the same algorithm as well as state-of-the-art single-cell assemblers SPAdes and IDBA-UD. Hybrid De novo Assembler (HyDA) is also able to avoid chimeric assemblies by detecting and separating shared and exclusive pieces of sequence for input data sets. By replacing one deep single-cell sequencing experiment with a few single-cell sequencing experiments of lower depth, the co-assembly method can hedge against the risk of failure and loss of the sample, without significantly increasing sequencing cost. Application of the single-cell coassembler HyDA to the study of three uncultured members of an alkane-degrading methanogenic community validated the usefulness of the co-assembly concept.

2014-02-24

T-lex2: genotyping, frequency estimation and re-annotation of transposable elements using single or pooled next-generation sequencing data

10.1101/002964

Anna-Sophie Fiston-Lavier;Maite G. Barrón;Dmitri A. Petrov;Josefa González;

Transposable elements (TEs) are the most active, diverse and ancient component in a broad range of genomes. As such, a complete understanding of genome function and evolution cannot be achieved without a thorough understanding of TE impact and biology. However, in-depth analyses of TEs still represent a challenge due to the repetitive nature of these genomic entities. In this work, we present a broadly applicable and flexible tool: T-lex2. T-lex2 is the only available software that allows routine,automatic, and accurate genotyping of individual TE insertions and estimation of their population frequencies both using individual strain and pooled next-generation sequencing (NGS) data. Furthermore, T-lex2 also assesses the quality of the calls allowing the identification of miss-annotated TEs and providing the necessary information to re-annotate them. Although we tested the fidelity of T-lex2 using the high quality Drosophila melanogaster genome, the flexible and customizable design of T-lex2 allows running it in any genome and for any type of TE insertion. Overall, T-lex2 represents a significant improvement in our ability to analyze the contribution of TEs to genome function and evolution as well as learning about the biology of TEs. T-lex2 is freely available online at http://petrov.stanford.edu/cgi-bin/Tlex.html.

2014-02-24

T-lex2: genotyping, frequency estimation and re-annotation of transposable elements using single or pooled next-generation sequencing data

10.1101/002964

Anna-Sophie Fiston-Lavier;Maite G. Barrón;Dmitri A. Petrov;Josefa González;

Transposable elements (TEs) are the most active, diverse and ancient component in a broad range of genomes. As such, a complete understanding of genome function and evolution cannot be achieved without a thorough understanding of TE impact and biology. However, in-depth analyses of TEs still represent a challenge due to the repetitive nature of these genomic entities. In this work, we present a broadly applicable and flexible tool: T-lex2. T-lex2 is the only available software that allows routine,automatic, and accurate genotyping of individual TE insertions and estimation of their population frequencies both using individual strain and pooled next-generation sequencing (NGS) data. Furthermore, T-lex2 also assesses the quality of the calls allowing the identification of miss-annotated TEs and providing the necessary information to re-annotate them. Although we tested the fidelity of T-lex2 using the high quality Drosophila melanogaster genome, the flexible and customizable design of T-lex2 allows running it in any genome and for any type of TE insertion. Overall, T-lex2 represents a significant improvement in our ability to analyze the contribution of TEs to genome function and evolution as well as learning about the biology of TEs. T-lex2 is freely available online at http://petrov.stanford.edu/cgi-bin/Tlex.html.

2014-09-16

Genetic drift suppresses bacterial conjugation in spatially structured populations

10.1101/002980

Peter D. Freese;Kirill S. Korolev;Jose I Jimenez;Irene A. Chen;

Conjugation is the primary mechanism of horizontal gene transfer that spreads antibiotic resistance among bacteria. Although conjugation normally occurs in surface-associated growth (e.g., biofilms), it has been traditionally studied in well-mixed liquid cultures lacking spatial structure, which is known to affect many evolutionary and ecological processes. Here we visualize spatial patterns of gene transfer mediated by F plasmid conjugation in a colony of Escherichia coli growing on solid agar, and we develop a quantitative understanding by spatial extension of traditional mass-action models. We found that spatial structure suppresses conjugation in surface-associated growth because strong genetic drift leads to spatial isolation of donor and recipient cells, restricting conjugation to rare boundaries between donor and recipient strains. These results suggest that ecological strategies, such as enforcement of spatial structure and enhancement of genetic drift, could complement molecular strategies in slowing the spread of antibiotic resistance genes.

2014-02-24

Extensive translation of small ORFs revealed by polysomal ribo-Seq

10.1101/002998

Julie L Aspden;Ying Chen Eyre-Walker;Rose J. Phillips;Michele Brocard;Unum Amin;Juan Couso;

Thousands of small Open Reading Frames (smORFs) encoding small peptides of fewer than 100 amino acids exist in our genomes. Examples of functional smORFs have been characterised in a few species but the actual number of translated smORFs, and their molecular, functional and evolutionary features are not known. Here we present a genome-wide assessment of smORF translation by ribosomal profiling of polysomal fractions. This polysomal ribo-Seq suggests that smORFs are translated at the same level and in the same relative numbers (80%) as normal proteins. The smORF peptides appear widely conserved, show activity in cells, and display a putative amino acid signature. These findings reinforce the idea that smORFs are an abundant and fundamental genome component, displaying features usually attributed to canonical proteins, including high translation levels, biological function, amino acid sequence specificity and cross-species conservation.

2014-02-24

A tug-of-war between driver and passenger mutations in cancer and other adaptive processes

10.1101/003053

Christopher Dennis McFarland;Leonid A Mirny;Kirill S Korolev;

Cancer progression is an example of a rapid adaptive process where evolving new traits is essential for survival and requires a high mutation rate. Precancerous cells acquire a few key mutations that drive rapid population growth and carcinogenesis. Cancer genomics demonstrates that these few driver mutations occur alongside thousands of random passenger mutations--a natural consequence of cancers elevated mutation rate. Some passengers can be deleterious to cancer cells, yet have been largely ignored in cancer research. In population genetics, however, the accumulation of mildly deleterious mutations has been shown to cause population meltdown. Here we develop a stochastic population model where beneficial drivers engage in a tug-of-war with frequent mildly deleterious passengers. These passengers present a barrier to cancer progression that is described by a critical population size, below which most lesions fail to progress, and a critical mutation rate, above which cancers meltdown. We find support for the model in cancer age-incidence and cancer genomics data that also allow us to estimate the fitness advantage of drivers and fitness costs of passengers. We identify two regimes of adaptive evolutionary dynamics and use these regimes to rationalize successes and failures of different treatment strategies. We find that a tumors load of deleterious passengers can explain previously paradoxical treatment outcomes and suggest that it could potentially serve as a biomarker of response to mutagenic therapies. The collective deleterious effect of passengers is currently an unexploited therapeutic target. We discuss how their effects might be exacerbated by both current and future therapies.

2014-02-26

Neanderthals had our de novo genes.

10.1101/003004

John Stewart Taylor;

Gene duplication provides a profusion of raw material for evolutionary innovation (Lynch and Conery, 2000). While most duplicates rapidly become unrecognizable some, e.g., those that are immediately useful or those that after a period of relaxed selection gain unique roles, are retained and thereby expand a genomes protein-coding repertoire. Ohno (1970) famously remarked that without gene duplication, the creation of metazoans, vertebrates, and mammals from unicellular organisms would have been impossible. Such big leaps in evolution, he argued, required the creation of new gene loci with previously nonexistent functions (Taylor and Raes, 2004). Recently, another source of new genes has been recognized: Though rare, it seems clear that new genes can emerge from formerly non-coding DNA, the de novo protein coding genes (Zhao et al., 2014, and references therein).\n\nIn 2009 Knowles ...

2014-02-25

Genetic drift opposes mutualism during spatial population expansion

10.1101/003012

Melanie JI Mueller;Beverly I Neugeboren;David R Nelson;Andrew W Murray;

Mutualistic interactions benefit both partners, promoting coexistence and genetic diversity. Spatial structure can promote cooperation, but spatial expansions may also make it hard for mutualistic partners to stay together, since genetic drift at the expansion front creates regions of low genetic and species diversity. To explore the antagonism between mutualism and genetic drift, we grew cross-feeding strains of the budding yeast S. cerevisiae on agar surfaces as a model for mutualists undergoing spatial expansions. By supplying varying amounts of the exchanged nutrients, we tuned strength and symmetry of the mutualistic interaction. Strong mutualism suppresses genetic demixing during spatial expansions and thereby maintains diversity, but weak or asymmetric mutualism is overwhelmed by genetic drift even when mutualism is still beneficial, slowing growth and reducing diversity. Theoretical modeling using experimentally measured parameters predicts the size of demixed regions and how strong mutualism must be to survive a spatial expansion.

2014-02-25

Chromatin Loops as Allosteric Modulators of Enhancer-Promoter Interactions

10.1101/003087

Boryana Doyle;Geoffrey Fudenberg;Maxim Imakaev;Leonid Mirny;

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.\n\nAuthor SummaryIn eukaryotes, enhancers directly contact promoters over large genomic distances to regulate gene expression. Characterizing the principles underlying these long-range enhancer-promoter contacts is crucial for a full understanding of gene expression. Recent experimental mapping of chromosomal interactions by the Hi-C method shows an intricate network of local looping interactions surrounding enhancers and promoters. We model a region of chromatin fiber as a long polymer and study how the formation of loops between certain regulatory elements can insulate or facilitate enhancer-promoter interactions. We find 2-5 fold insulation or facilitation, depending on the location of looping elements relative to an enhancer-promoter pair. These effects originate from the polymer nature of chromatin, without requiring additional mechanisms beyond the formation of a chromatin loop. Our findings suggest that loop-mediated gene regulation by elements in the vicinity of an enhancer-promoter pair can be understood as an allosteric effect. This highlights the complex effects that local chromatin organization can have on gene regulation.

2014-02-26

Chromatin Loops as Allosteric Modulators of Enhancer-Promoter Interactions

10.1101/003087

Boryana Doyle;Geoffrey Fudenberg;Maxim Imakaev;Leonid Mirny;

The classic model of eukaryotic gene expression requires direct spatial contact between a distal enhancer and a proximal promoter. Recent Chromosome Conformation Capture (3C) studies show that enhancers and promoters are embedded in a complex network of looping interactions. Here we use a polymer model of chromatin fiber to investigate whether, and to what extent, looping interactions between elements in the vicinity of an enhancer-promoter pair can influence their contact frequency. Our equilibrium polymer simulations show that a chromatin loop, formed by elements flanking either an enhancer or a promoter, suppresses enhancer-promoter interactions, working as an insulator. A loop formed by elements located in the region between an enhancer and a promoter, on the contrary, facilitates their interactions. We find that different mechanisms underlie insulation and facilitation; insulation occurs due to steric exclusion by the loop, and is a global effect, while facilitation occurs due to an effective shortening of the enhancer-promoter genomic distance, and is a local effect. Consistently, we find that these effects manifest quite differently for in silico 3C and microscopy. Our results show that looping interactions that do not directly involve an enhancer-promoter pair can nevertheless significantly modulate their interactions. This phenomenon is analogous to allosteric regulation in proteins, where a conformational change triggered by binding of a regulatory molecule to one site affects the state of another site.\n\nAuthor SummaryIn eukaryotes, enhancers directly contact promoters over large genomic distances to regulate gene expression. Characterizing the principles underlying these long-range enhancer-promoter contacts is crucial for a full understanding of gene expression. Recent experimental mapping of chromosomal interactions by the Hi-C method shows an intricate network of local looping interactions surrounding enhancers and promoters. We model a region of chromatin fiber as a long polymer and study how the formation of loops between certain regulatory elements can insulate or facilitate enhancer-promoter interactions. We find 2-5 fold insulation or facilitation, depending on the location of looping elements relative to an enhancer-promoter pair. These effects originate from the polymer nature of chromatin, without requiring additional mechanisms beyond the formation of a chromatin loop. Our findings suggest that loop-mediated gene regulation by elements in the vicinity of an enhancer-promoter pair can be understood as an allosteric effect. This highlights the complex effects that local chromatin organization can have on gene regulation.

2014-11-24

On a solution of the biodiversity paradox and a competitive coexistence principle

10.1101/003095

Lev V. Kalmykov;Vyacheslav L. Kalmykov;

The biodiversity paradox is the central problem in theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. This contradiction is the key subject of the long-standing and continuing biodiversity debates. The paradox impedes our insights into biodiversity conservation. Previously we proved that due to a soliton-like behaviour of population waves complete competitors can indefinitely coexist in one closed homogeneous habitat on one and the same limiting resource under constant conditions of environment, without any trade-offs and cooperations. As this fact violates the known formulations of the competitive exclusion principle we have reformulated the principle. Here we explain why this reformulation of the principle results in a solution of the biodiversity paradox. In addition, we generalize the competitive exclusion principle. Reasoning by contradiction, we formulate a generalized principle of competitive coexistence. These principles expand theoretical basis for biodiversity conservation and sustainable development.

2014-02-27

DNA methylation modulates transcription factor occupancy chiefly at sites of high intrinsic cell-type variability

10.1101/003061

Matthew Maurano;Hao Wang;Sam John;Anthony Shafer;Theresa Canfield;Kristen Lee;John A Stamatoyannopoulos;

The nuclear genome of every cell harbors millions of unoccupied transcription factor (TF) recognition sequences that harbor methylated cytosines. Although DNA methylation is commonly invoked as a repressive mechanism, the extent to which it actively silences specific TF occupancy sites is unknown. To define the role of DNA methylation in modulating TF binding, we quantified the effect of DNA methyltransferase abrogation on the occupancy patterns of a ubiquitous TF capable of autonomous binding to its target sites in chromatin (CTCF). Here we show that the vast majority of unoccupied, methylated CTCF recognition sequences remain unbound upon depletion of DNA methylation. Rather, methylation-regulated binding is restricted to a small fraction of elements that exhibit high intrinsic variability in CTCF occupancy across cell types. Our results suggest that DNA methylation is not a major groundskeeper of genomic transcription factor occupancy landscapes, but rather a specialized mechanism for stabilizing epigenetically labile sites.

2014-02-27

Genomic Repeat Element Analyzer for Mammals (GREAM)

10.1101/003111

Darshan S Chandrashekar;Poulami Dey;Kshitish K Acharya;

Background: Understanding the mechanism behind the transcriptional regulation of genes is still a challenge. Recent findings indicate that the genomic repeat elements (such as LINES, SINES and LTRs) could play an important role in the transcription control. Hence, it is important to further explore the role of genomic repeat elements in the gene expression regulation, and perhaps in other molecular processes. Although many computational tools exists for repeat element analysis, almost all of them simply identify and/or classifying the genomic repeat elements within query sequence(s); none of them facilitate identification of repeat elements that are likely to have a functional significance, particularly in the context of transcriptional regulation.\n\nResult: We developed the Genomic Repeat Element Analyzer for Mammals (GREAM) to allow gene-centric analysis of genomic repeat elements in 17 mammalian species, and validated it by comparing with some of the existing experimental data. The output provides a categorized list of the specific type of transposons, retro-transposons and other genome-wide repeat elements that are statistically over-represented across specific neighborhood regions of query genes. The position and frequency of these elements, within the specified regions, are displayed as well. The tool also offers queries for position-specific distribution of repeat elements within chromosomes. In addition, GREAM facilitates the analysis of repeat element distribution across the neighborhood of orthologous genes.\n\nConclusion: GREAM allows researchers to short-list the potentially important repeat elements, from the genomic neighborhood of genes, for further experimental analysis. GREAM is free and available for all at http://resource.ibab.ac.in/GREAM/

2014-02-28

A novel inference of the fundamental biodiversity number for multiple immigration-limited communities

10.1101/003137

Champak Beeravolu Reddy;François Munoz;Pierre Couteron;

Neutral community theory postulates a fundamental quantity, {theta}, which reflects the species diversity on a regional scale. While the recent genealogical formulation of community dynamics has considerably enhanced quantitative neutral ecology, its inferential aspects have remained computationally prohibitive. Here, we make use of a generalized version of the original two-level hierarchical framework in order to define a novel estimator for{theta} ;, which proves to be computationally efficient and robust when tested on a wide range of simulated neutral communities. Estimating{theta} ; from field data is also illustrated using two tropical forest datasets consisting of spatially separated permanent field plots. Preliminary results also reveal that our inferred regional diversity parameter based on community dynamics may be linked to widely used ordination techniques in ecology. This paper essentially paves the way for future work dealing with the parameter inference of neutral communities with respect to their spatial scale and structure.

2014-02-28

High Bacterial Load Predicts Poor Outcomes in Patients with Idiopathic Pulmonary Fibrosis

10.1101/003145

Philip Molyneaux;Michael Cox;Saffron Willis-Owen;Kirsty Russell;Patrick Mallia;Anne-Marie Russell;Sebastian Johnston;Athol Wells;William Cookson;Toby Maher;Miriam Moffatt;

BackgroundRepetitive alveolar damage and aberrant repair may be important in the development of the fatal condition Idiopathic Pulmonary Fibrosis (IPF). The role played by microorganisms in this cycle is unknown.\n\nMethodsWe consecutively enrolled patients diagnosed with IPF according to international criteria together with healthy smokers, non-smokers and subjects with moderate Chronic Obstructive Pulmonary Disease (COPD) as controls. Subjects underwent bronchoalveolar lavage (BAL) from which genomic DNA was isolated. The V3-V5 region of the bacterial 16S rRNA gene was amplified, allowing quantification of bacterial load and identification of communities by 16S rRNA qPCR and pyrosequencing.\n\nResultsOur 65 IPF patients had 3.9x109 copies of the 16S rRNA gene per ml of BAL, two-fold more than the 1.8x109 copies in 44 sex- and smoking-matched controls (P<0.0001). Baseline BAL bacterial burden predicted Forced Vital Capacity (FVC) decline (P=0.02). Patients in the highest tertile of bacterial burden were at a higher risk of mortality compared to subjects in the lowest tertile (hazard ratio 4.59 (95% CI, 1.05-20); P=0.04).\n\nSequencing yielded 912,883 high quality reads from all subjects. Operational Taxonomic Units (OTUs) representing Haemophilus, Streptococcus, Neisseria and Veillonella were 1.5 to 3.5 fold more abundant in cases than controls (P<0.05). Regression analyses indicated that these specific OTUs as well as bacterial burden associated independently with IPF.\n\nConclusionsIPF is characterised by an increased bacterial burden in BAL that predicts decline in lung function and death. Clinical trials of antimicrobial therapy may determine if microbial burden is causal or not in IPF progression.

2014-02-28

A Genetic Screen Identifies Two Novel Rice Cysteine-rich Receptor-like Kinases That Are Required for the Rice NH1-mediated Immune Response

10.1101/003129

Mawsheng Chern;Rebecca Bart;Wei Bai;Deling Ruan;Wing Hoi Sze-To;Canlas Patrick;Rashmi Jain;Xuewei Chen;Pamela Ronald;

Over-expression of rice NH1 (NH1ox), the ortholog of Arabidopsis NPR1, confers immunity to bacterial and fungal pathogens and induces the appearance of necrotic lesions due to activation of defense genes at the pre-flowering stage. This lesion-mimic phenotype can be enhanced by the application of benzothiadiazole (BTH). To identify genes regulating these responses, we screened a fast neutron-irradiated NH1ox rice population. We identified one mutant, called sn11 (suppressor of NH1-mediated lesion-mimic 1), which is impaired both in BTH-induced necrotic lesion formation and in the immune response. Using a comparative genome hybridization approach employing rice whole genome tiling array, we identified 11 genes associated with the sn11 phenotype. Transgenic analysis revealed that RNA interference of two of the genes, encoding previously uncharacterized cysteine-rich receptor-like kinases (CRK6 and CRK10), re-created the sn11 phenotype. Elevated expression of CRK10 using an inducible expression system resulted in enhanced immunity. Quantitative PCR revealed that BTH treatment and elevated levels of rice NH1 and its paralog NH3 induced expression of CRK10 and CRK6 RNA. These results indicate that CRK6 and CRK10 are required for the BTH-activated immune response mediated by NH1.

2014-02-28

Effect of alternating red and blue light irradiation generated by light emitting diodes on the growth of leaf lettuce

10.1101/003103

Akihiro Shimokawa;Yuki Tonooka;Misato Matsumoto;Hironori Ara;Hiroshi Suzuki;Naoki Yamauchi;Masayoshi Shigyo;

Because global climate change has made agricultural supply unstable, plant factories are expected to be a safe and stable means of food production. As the light source of a plant factory or controlled greenhouse, the light emitting diode (LED) is expected to solve cost problems and promote plant growth efficiently. In this study, we examined the light condition created by using monochromatic red and blue LEDs, to provide both simultaneous and alternating irradiation to leaf lettuce. The result was that simultaneous red and blue irradiation promoted plant growth more effectively than monochromatic and fluorescent light irradiation. Moreover, alternating red and blue light accelerated plant growth significantly even when the total light intensity per day was the same as with simultaneous irradiation. The fresh weight in altering irradiation was almost two times higher than with fluorescent light and about 1.6 times higher than with simultaneous irradiation. The growth-promoting effect of alternating irradiation of red and blue light was observed in different cultivars. From the results of experiments, we offer a novel plant growth method named \"Shigyo Method\", the core concept of which is the alternating irradiation of red and blue light.

2014-02-28

Complementation of a temperature sensitive Escherichia coli rpoD mutation using Lactobacillus sigma factors

10.1101/003152

James Winkler;Katy Kao;

Housekeeping sigma factors in the{sigma} 70 family, as components of the RNA polymerase holoenzyme, are responsible for regulating transcription of genes related to vegetative growth. While these factors are well understood in model organisms such as Escherichia coli and Bacillus subtilis, little experimental work has focused on the sigma factors in members of the Lactobacillus genus such as Lactobacillus brevis and Lactobacillus plantarum. This study evaluates the ability of putative{sigma} 70 proteins from L. brevis ([Formula]) and L. plantarum ([Formula]) to complement a temperature sensitive mutation in the E. coli 285c{sigma} 70 protein. This report is the first to show that these heterologous sigma factors were capable of restoring the viability of E. coli 285c for growth at 40-43.5 {degrees}C, indicating the [Formula] and [Formula] are capable of initiating transcription in a complex with the E. coli 285c RNA polymerase. These heterologous sigma factors may therefore be useful for improving biochemical knowledge of the sigma factor family or for use in the expression of hetereologous genomic libraries.

2014-03-02

DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent

10.1101/003178

Graham Jones;Bengt Oxelman;

MotivationThe multispecies coalescent model provides a formal framework for the assignment of individual organisms to species, where the species are modeled as the branches of the species tree. None of the available approaches so far have simultaneously co-estimated all the relevant parameters in the model, without restricting the parameter space by requiring a guide tree and/or prior assignment of individuals to clusters or species.\n\nResultsWe present DISSECT, which explores the full space of possible clusterings of individuals and species tree topologies in a Bayesian framework. It uses an approximation to avoid the need for reversible-jump MCMC, in the form of a prior that is a modification of the birth-death prior for the species tree. It incorporates a spike near zero in the density for node heights. The model has two extra parameters: one controls the degree of approximation, and the second controls the prior distribution on the numbers of species. It is implemented as part of BEAST and requires only a few changes from a standard *BEAST analysis. The method is evaluated on simulated data and demonstrated on an empirical data set. The method is shown to be insensitive to the degree of approximation, but quite sensitive to the second parameter, suggesting that large numbers of sequences are needed to draw firm conclusions.\n\nAvailabilityhttp://code.google.com/p/beast-mcmc/, http://www.indriid.com/dissectinbeast.html\n\[email protected], www.indriid.com\n\nSupplementary informationSupplementary material is available.

2014-03-03

DISSECT: an assignment-free Bayesian discovery method for species delimitation under the multispecies coalescent

10.1101/003178

Graham Jones;Bengt Oxelman;

MotivationThe multispecies coalescent model provides a formal framework for the assignment of individual organisms to species, where the species are modeled as the branches of the species tree. None of the available approaches so far have simultaneously co-estimated all the relevant parameters in the model, without restricting the parameter space by requiring a guide tree and/or prior assignment of individuals to clusters or species.\n\nResultsWe present DISSECT, which explores the full space of possible clusterings of individuals and species tree topologies in a Bayesian framework. It uses an approximation to avoid the need for reversible-jump MCMC, in the form of a prior that is a modification of the birth-death prior for the species tree. It incorporates a spike near zero in the density for node heights. The model has two extra parameters: one controls the degree of approximation, and the second controls the prior distribution on the numbers of species. It is implemented as part of BEAST and requires only a few changes from a standard *BEAST analysis. The method is evaluated on simulated data and demonstrated on an empirical data set. The method is shown to be insensitive to the degree of approximation, but quite sensitive to the second parameter, suggesting that large numbers of sequences are needed to draw firm conclusions.\n\nAvailabilityhttp://code.google.com/p/beast-mcmc/, http://www.indriid.com/dissectinbeast.html\n\[email protected], www.indriid.com\n\nSupplementary informationSupplementary material is available.

2014-12-11

Conditions for the validity of SNP-based heritability estimation

10.1101/003160

James J Lee;Carson C Chow;

The heritability of a trait (h2) is the proportion of its population variance caused by genetic differences, and estimates of this parameter are important for interpreting the results of genome-wide association studies (GWAS). In recent years, researchers have adopted a novel method for estimating a lower bound on heritability directly from GWAS data that uses realized genetic similarities between nominally unrelated individuals. The quantity estimated by this method is purported to be the contribution to heritability that could in principle be recovered from association studies employing the given panel of SNPs [Formula] Thus far the validity of this approach has mostly been tested empirically. Here, we provide a mathematical explication and show that the method should remain a robust means of obtaining [Formula] under circumstances wider than those under which it has so far been derived.

2014-03-03

Conditions for the validity of SNP-based heritability estimation

10.1101/003160

James J Lee;Carson C Chow;

The heritability of a trait (h2) is the proportion of its population variance caused by genetic differences, and estimates of this parameter are important for interpreting the results of genome-wide association studies (GWAS). In recent years, researchers have adopted a novel method for estimating a lower bound on heritability directly from GWAS data that uses realized genetic similarities between nominally unrelated individuals. The quantity estimated by this method is purported to be the contribution to heritability that could in principle be recovered from association studies employing the given panel of SNPs [Formula] Thus far the validity of this approach has mostly been tested empirically. Here, we provide a mathematical explication and show that the method should remain a robust means of obtaining [Formula] under circumstances wider than those under which it has so far been derived.

2014-03-04

Does ‘information control the living state’?

10.1101/003186

Rodrick Wallace;

We generalize the recently-uncovered Data Rate Theorem in the context of cognitive systems having a dual information source, including those of the living state that is particularly characterized by cognition at every scale and level of organization. The unification of information theory and control theory via the Data Rate Theorem is not additive, but synergistic, generating new statistical tools that greatly constrain the possible dynamics of that state. Thus, in addition to providing novel conceptual approaches, this emerging body of theory permits construction of models that, like those of regression analysis, can provide benchmarks against which to compare experimental or observational data.

2014-03-04

Detecting translational regulation by change point analysis of ribosome profiling datasets

10.1101/003210

Anze Zupanic;Catherine Meplan;Sushma N Grellscheid;John C Mathers;Tom BL Kirkwood;John E Hesketh;Daryl P Shanley;

Ribo-Seq maps the location of translating ribosomes on mature mRNA transcripts. While ribosome density is constant along the length of the mRNA coding region, it can be altered by translational regulatory events. In this study, we developed a method to detect translational regulation of individual mRNAs from their ribosome profiles, utilizing changes in ribosome density. We used mathematical modelling to show that changes in ribosome density should occur along the mRNA at the point of regulation. We analyzed a Ribo-Seq dataset obtained for mouse embryonic stem cells and showed that normalization by corresponding RNA-Seq can be used to improve the Ribo-Seq quality by removing bias introduced by deep-sequencing and alignment artefacts. After normalization, we applied a change point algorithm to detect changes in ribosome density present in individual mRNA ribosome profiles. Additional sequence and gene isoform information obtained from the UCSC Genome Browser allowed us to further categorize the detected changes into different mechanisms of regulation. In particular, we detected several mRNAs with known post-transcriptional regulation, e.g. premature termination for selenoprotein mRNAs and translational control of Atf4, but also several more mRNAs with hitherto unknown translational regulation. Additionally, our approach proved useful for identification of new gene isoforms.

2014-03-05

Meteorological conditions influence short-term survival and dispersal in a reinforced long-lived bird population.

10.1101/003228

Loïc A Hardouin;Alexandre Robert;Marie Nevoux;Olivier Gimenez;Frederic Lacroix;Yves Hingrat;

O_LIA high immediate mortality rate of released animals is an important cause of translocation failure (\"release cost\"). Post-release dispersal (i.e. the movements from the release site to the first breeding site) has recently been identified as another source of local translocation failure. In spite of their potential effects on conservation program outcomes, little is known about the quantitative effects of these two sources of translocation failure and their interactions with environmental factors and management designs.\nC_LIO_LIBased on long-term monitoring data of captive-bred North African houbara bustards (hereafter, houbaras) over large spatial scales, we investigated the relative effects of release (e.g., release group size, period of release), individual (e.g., sex and body condition) and meteorological (e.g., temperature and rainfall) conditions on post-release survival (N = 957 houbaras) and dispersal (N = 436 houbaras).\nC_LIO_LIWe found that (i) rainfall and ambient air temperature had respectively a negative and a positive effect on houbara post-release dispersal distance, (ii) in interaction with the release period, harsh meteorological conditions had negative impact on the survival of houbaras, (iii) density dependent processes influenced the pattern of departure from the release site and (iv) post-release dispersal distance was male-biased, as natal dispersal of wild birds (although the dispersal patterns and movements may be influenced by different processes in captive-bred and in wild birds).\nC_LIO_LISynthesis and applications. Overall, our results demonstrate that post-release dispersal and mortality costs in translocated species may be mediated by meteorological factors, which in turn can be buffered by the release method. As the consequences of translocation programs on population dynamics depend primarily upon release costs and colonisation process, we suggest that their potential interactions with meteorological conditions be carefully addressed in future programs.\nC_LI

2014-03-05

Phylogenetic tree shapes resolve disease transmission patterns

10.1101/003194

Jennifer Gardy;Caroline Colijn;

Whole genome sequencing is becoming popular as a tool for understanding outbreaks of communicable diseases, with phylogenetic trees being used to identify individual transmission events or to characterize outbreak-level overall transmission dynamics. Existing methods to infer transmission dynamics from sequence data rely on well-characterised infectious periods, epidemiological and clinical meta-data which may not always be available, and typically require computationally intensive analysis focussing on the branch lengths in phylogenetic trees. We sought to determine whether the topological structures of phylogenetic trees contain signatures of the overall transmission patterns underyling an outbreak. Here we use simulated outbreaks to train and then test computational classifiers. We test the method on data from two real-world outbreaks. We find that different transmission patterns result in quantitatively different phylogenetic tree shapes. We describe five topological features that summarize a phylogenys structure and find that computational classifiers based on these are capable of predicting an outbreaks transmission dynamics. The method is robust to variations in the transmission parameters and network types, and recapitulates known epidemiology of previously characterized real-world outbreaks. We conclude that there are simple structural properties of phylogenetic trees which, when combined, can distinguish communicable disease outbreaks with a super-spreader, homogeneous transmission, and chains of transmission. This is possible using genome data alone, and can be done during an outbreak. We discuss the implications for management of outbreaks.

2014-03-05

Phylogenetic tree shapes resolve disease transmission patterns

10.1101/003194

Jennifer Gardy;Caroline Colijn;

Whole genome sequencing is becoming popular as a tool for understanding outbreaks of communicable diseases, with phylogenetic trees being used to identify individual transmission events or to characterize outbreak-level overall transmission dynamics. Existing methods to infer transmission dynamics from sequence data rely on well-characterised infectious periods, epidemiological and clinical meta-data which may not always be available, and typically require computationally intensive analysis focussing on the branch lengths in phylogenetic trees. We sought to determine whether the topological structures of phylogenetic trees contain signatures of the overall transmission patterns underyling an outbreak. Here we use simulated outbreaks to train and then test computational classifiers. We test the method on data from two real-world outbreaks. We find that different transmission patterns result in quantitatively different phylogenetic tree shapes. We describe five topological features that summarize a phylogenys structure and find that computational classifiers based on these are capable of predicting an outbreaks transmission dynamics. The method is robust to variations in the transmission parameters and network types, and recapitulates known epidemiology of previously characterized real-world outbreaks. We conclude that there are simple structural properties of phylogenetic trees which, when combined, can distinguish communicable disease outbreaks with a super-spreader, homogeneous transmission, and chains of transmission. This is possible using genome data alone, and can be done during an outbreak. We discuss the implications for management of outbreaks.

2014-05-28

TCF7L2 is a master regulator of insulin production and processing

10.1101/003202

Yuedan Zhou;Soo-Young Park;Jing Su;Kathleen Bailey;Emilia Ottosson-Laakso;Liliya Shcerbina;Nikolay Oskolkov;Enming Zhang;Thomas Thevenin;Jo?o Fadista;Hedvig Bennet;Petter Vikman;Nils Wierup;Malin Fex;Johan Rung;Claes Wollheim;Marcelo Nobrega;Erik Renstr?m;Leif Groop;Ola Hansson;

Although variants in the T-cell factor 7-like 2 gene (TCF7L2) confer the strongest risk of type 2 diabetes (T2D) by presumed effects on islet function, the underlying mechanisms are not well understood. We have identified TCF7L2-target genes and described the regulatory network downstream of TCF7L2 responsible for its effect on insulin secretion in rodents and human pancreatic islets. ISL1 is a direct target of TCF7L2 and regulates proinsulin production and processing via MAFA, PDX1, NKX6.1, PCSK1 and PCSK2 and possibly clearance of proinsulin via SLC30A8. Taken together, these results demonstrate that not only synthesis of proinsulin is regulated by TCF7L2, but also processing and possibly clearance of proinsulin and insulin in a genotype dependent manner. These multiple targets in key pathways may explain why TCF7L2 has emerged as the gene showing the strongest association with T2D.

2014-03-05

Characterization of directed differentiation by high-throughput single-cell RNA-Seq

10.1101/003236

Magali Soumillon;Davide Cacchiarelli;Stefan Semrau;Alexander van Oudenaarden;Tarjei S Mikkelsen;

Directed differentiation of cells in vitro is a powerful approach for dissection of developmental pathways, disease modeling and regenerative medicine, but analysis of such systems is complicated by heterogeneous and asynchronous cellular responses to differentiation-inducing stimuli. To enable deep characterization of heterogeneous cell populations, we developed an efficient digital gene expression profiling protocol that enables surveying of mRNA in thousands of single cells at a time. We then applied this protocol to profile 12,832 cells collected at multiple time points during directed adipogenic differentiation of human adipose-derived stem/stromal cells in vitro. The resulting data reveal the major axes of cell-to-cell variation within and between time points, and an inverse relationship between inflammatory gene expression and lipid accumulation across cells from a single donor.

2014-03-05

An Analysis of Cochlear Implant Distortion from a User’s Perspective

10.1101/003244

Barry David Jacobson;

We describe our first-hand experience with a cochlear implant (CI), being both a recent recipient and a hearing researcher. We note the promising loudness, but very unpleasant distortion, which makes understanding speech difficult in many environments, including in noise, on the phone or through the radio. We also discuss the extreme unpleasantness of music, which makes recognizing familiar melodies very difficult. We investigate the causes of the above problems through mathematical analysis and computer simulations of sound mixtures, and find that surprisingly, the culprit appears to be non-biological in origin, but primarily due to the envelope-based signal processing algorithms currently used. This distortion is generated before the signal even enters the cochlea. Hence, the long-held belief that inter-electrode interference or current spreading is the cause, appears incorrect. We explain that envelope processing may have been originally instituted based on an inaccurate understanding of the role of place coding vs. temporal coding, or alternatively, because of an incorrect analogy to radio modulation theory. On the basis of our analysis, we suggest immediate concrete steps, some possibly in firmware alone, that may lead to a much improved experience.

2014-03-06

An Analysis of Cochlear Implant Distortion from a User's Perspective

10.1101/003244

Barry David Jacobson;

We describe our first-hand experience with a cochlear implant (CI), being both a recent recipient and a hearing researcher. We note the promising loudness, but very unpleasant distortion, which makes understanding speech difficult in many environments, including in noise, on the phone or through the radio. We also discuss the extreme unpleasantness of music, which makes recognizing familiar melodies very difficult. We investigate the causes of the above problems through mathematical analysis and computer simulations of sound mixtures, and find that surprisingly, the culprit appears to be non-biological in origin, but primarily due to the envelope-based signal processing algorithms currently used. This distortion is generated before the signal even enters the cochlea. Hence, the long-held belief that inter-electrode interference or current spreading is the cause, appears incorrect. We explain that envelope processing may have been originally instituted based on an inaccurate understanding of the role of place coding vs. temporal coding, or alternatively, because of an incorrect analogy to radio modulation theory. On the basis of our analysis, we suggest immediate concrete steps, some possibly in firmware alone, that may lead to a much improved experience.

2014-03-09

An Analysis of Cochlear Implant Distortion from a User’s Perspective

10.1101/003244

Barry David Jacobson;

We describe our first-hand experience with a cochlear implant (CI), being both a recent recipient and a hearing researcher. We note the promising loudness, but very unpleasant distortion, which makes understanding speech difficult in many environments, including in noise, on the phone or through the radio. We also discuss the extreme unpleasantness of music, which makes recognizing familiar melodies very difficult. We investigate the causes of the above problems through mathematical analysis and computer simulations of sound mixtures, and find that surprisingly, the culprit appears to be non-biological in origin, but primarily due to the envelope-based signal processing algorithms currently used. This distortion is generated before the signal even enters the cochlea. Hence, the long-held belief that inter-electrode interference or current spreading is the cause, appears incorrect. We explain that envelope processing may have been originally instituted based on an inaccurate understanding of the role of place coding vs. temporal coding, or alternatively, because of an incorrect analogy to radio modulation theory. On the basis of our analysis, we suggest immediate concrete steps, some possibly in firmware alone, that may lead to a much improved experience.

2014-03-11

Filament formation by metabolic enzymes is a specific adaptation to an advanced state of cellular starvation

10.1101/003277

Ivana Petrovska;Elisabeth Nüske;Matthias C Munder;Gayathrie Kulasegaran;Liliana Malinovska;Sonja Kroschwald;Doris Richter;Karim Fahmy;Kimberley Gibson;Jean-Marc Verbavatz;Simon Alberti;

One of the key questions in biology is how the metabolism of a cell responds to changes in the environment. In budding yeast, starvation causes a drop in intracellular pH, but the functional role of this pH change is not well understood. Here, we show that the enzyme glutamine synthetase (Gln1) forms filaments at low pH and that filament formation leads to enzyme inactivation. Filament formation by Gln1 is a highly cooperative process, strongly dependent on macromolecular crowding, and involves back-to-back stacking of cylindrical homo-decamers into filaments that associate laterally to form higher order fibrils. Other metabolic enzymes also assemble into filaments at low pH. Hence, we propose that filament formation is a general mechanism to inactivate and store key metabolic enzymes during a state of advanced cellular starvation. These findings have broad implications for understanding the interplay between nutritional stress, the metabolism and the physical organization of a cell.

2014-03-07

Filament formation by metabolic enzymes is a specific adaptation to an advanced state of cellular starvation

10.1101/003277

Ivana Petrovska;Elisabeth Nüske;Matthias C Munder;Gayathrie Kulasegaran;Liliana Malinovska;Sonja Kroschwald;Doris Richter;Karim Fahmy;Kimberley Gibson;Jean-Marc Verbavatz;Simon Alberti;

One of the key questions in biology is how the metabolism of a cell responds to changes in the environment. In budding yeast, starvation causes a drop in intracellular pH, but the functional role of this pH change is not well understood. Here, we show that the enzyme glutamine synthetase (Gln1) forms filaments at low pH and that filament formation leads to enzyme inactivation. Filament formation by Gln1 is a highly cooperative process, strongly dependent on macromolecular crowding, and involves back-to-back stacking of cylindrical homo-decamers into filaments that associate laterally to form higher order fibrils. Other metabolic enzymes also assemble into filaments at low pH. Hence, we propose that filament formation is a general mechanism to inactivate and store key metabolic enzymes during a state of advanced cellular starvation. These findings have broad implications for understanding the interplay between nutritional stress, the metabolism and the physical organization of a cell.

2014-04-11

Alignathon: A competitive assessment of whole genome alignment methods.

10.1101/003285

Dent Earl;Ngan K Nguyen;Glenn Hickey;Robert S. Harris;Stephen Fitzgerald;Kathryn Beal;Igor Seledtsov;Vladimir Molodtsov;Brian Raney;Hiram Clawson;Jaebum Kim;Carsten Kemena;Jia-Ming Chang;Ionas Erb;Alexander Poliakov;Minmei Hou;Javier Herrero;Victor Solovyev;Aaron E. Darling;Jian Ma;Cedric Notredame;Michael Brudno;Inna Dubchak;David Haussler;Benedict Paten;

BackgroundMultiple sequence alignments (MSAs) are a prerequisite for a wide variety of evolutionary analyses. Published assessments and benchmark datasets for protein and, to a lesser extent, global nucleotide MSAs are available, but less effort has been made to establish benchmarks in the more general problem of whole genome alignment (WGA).\n\nResultsUsing the same model as the successful Assemblathon competitions, we organized a competitive evaluation in which teams submitted their alignments, and assessments were performed collectively after all the submissions were received. Three datasets were used: two of simulated primate and mammalian phylogenies, and one of 20 real fly genomes. In total 35 submissions were assessed, submitted by ten teams using 12 different alignment pipelines.\n\nConclusionsWe found agreement between independent simulation-based and statistical assessments, indicating that there are substantial accuracy differences between contemporary alignment tools. We saw considerable difference in the alignment quality of differently annotated regions, and found few tools aligned the duplications analysed. We found many tools worked well at shorter evolutionary distances, but fewer performed competitively at longer distances. We provide all datasets, submissions and assessment programs for further study, and provide, as a resource for future benchmarking, a convenient repository of code and data for reproducing the simulation assessments.

2014-03-10

Early warning signs in social-ecological networks

10.1101/003269

Samir Suweis;Paolo D'Odorico;

A number of social-ecological systems exhibit complex behaviour associated with nonlinearities, bifurcations, and interaction with stochastic drivers. These systems are often prone to abrupt and unexpected instabilities and state shifts that emerge as a discontinuous response to gradual changes in environmental drivers. Predicting such behaviours is crucial to the prevention of or preparation for unwanted regime shifts. Recent research in ecology has investigated early warning signs that anticipate the divergence of univariate ecosystem dynamics from a stable attractor. To date, leading indicators of instability in systems with multiple interacting components have remained poorly investigated. This is a major limitation in the understanding of the dynamics of complex social-ecological networks. Here, we develop a theoretical framework to demonstrate that rising variance - measured, for example, by the maximum element of the covariance matrix of the network - is an effective leading indicator of network instability. We show that its reliability and robustness depend more on the sign of the interactions within the network than the network structure or noise intensity. Mutualistic, scale free and small world networks are less stable than their antagonistic or random counterparts but their instability is more reliably predicted by this leading indicator. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social-ecological networks.

2014-03-12

Early warning signs in social-ecological networks

10.1101/003269

Samir Suweis;Paolo D'Odorico;

A number of social-ecological systems exhibit complex behaviour associated with nonlinearities, bifurcations, and interaction with stochastic drivers. These systems are often prone to abrupt and unexpected instabilities and state shifts that emerge as a discontinuous response to gradual changes in environmental drivers. Predicting such behaviours is crucial to the prevention of or preparation for unwanted regime shifts. Recent research in ecology has investigated early warning signs that anticipate the divergence of univariate ecosystem dynamics from a stable attractor. To date, leading indicators of instability in systems with multiple interacting components have remained poorly investigated. This is a major limitation in the understanding of the dynamics of complex social-ecological networks. Here, we develop a theoretical framework to demonstrate that rising variance - measured, for example, by the maximum element of the covariance matrix of the network - is an effective leading indicator of network instability. We show that its reliability and robustness depend more on the sign of the interactions within the network than the network structure or noise intensity. Mutualistic, scale free and small world networks are less stable than their antagonistic or random counterparts but their instability is more reliably predicted by this leading indicator. These results provide new advances in multidimensional early warning analysis and offer a framework to evaluate the resilience of social-ecological networks.

2014-06-16