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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2014

The emergence of network structure, complementarity and convergence from basic ecological and genetic processes

Plant-animal mutualistic networks are highly diverse and structured. This has been explained by coevolution through niche based processes. However, this explanation is only warranted if neutral processes (e.g. limited dispersal, genetic and ecological drift) cannot explain these patterns. Here we present a spatially explicit model based on explicit genetics and quantitative traits to study the connection between genome evolution, speciation and plant-animal network demography. We consider simple processes for the speciation dynamics of plant-animal mutualisms: ecological (dispersal, demography) and genetic processes (mutation, recombination, drift) and morphological constraints (matching of quantitative trait) for species interactions, particularly mating. We find the evolution of trait convergence and complementarity and topological features observed in real plant-animal mutualistic webs (i.e. nestedness and centrality). Furthermore, the morphological constraint for plant reproduction generates higher centrality among plant individuals (and species) than in animals, consistent with observations. We argue that simple processes are able to reproduce some well known ecological and evolutionary patterns of plant-animal mutualistic webs.

Evolutionary Biology↗

bioRxiv2014

Quantitative Genetics and Modularity in cranial and mandibular morphology of Calomys expulsus

Patterns of genetic covariance between characters (represented by the covariance matrix G) play an important role in morphological evolution, since they interact with the evolutionary forces acting over populations. They are also expected to influence the patterns expressed in their phenotypic counterparts (P), because of limits imposed by multiple developmental and functional restrictions on the genotype/phenotype map. We have investigated genetic covariances in the skull and mandible of the vesper mouse (Calomys expulsus) in order to estimate the degree of similarity between genetic and phenotypic covariances and its potential roots on developmental and functional factors shaping those integration patterns. We use a classic adhoc analysis of morphological integration based on current state of art of developmental/functional factors during mammalian ontogeny and also applied a novel methodology that makes use of simulated evolutionary responses. We have obtained P and G that are strongly similar, for both skull and mandible; their similarity is achieved through the spatial and temporal organization of developmental and functional interactions, which are consistently recognized as hypothesis of trait associations in both matrices.

Evolutionary Biology↗

bioRxiv2014

Expansion load: recessive mutations and the role of standing genetic variation

Expanding populations incur a mutation burden - the so-called expansion load. Previous studies of expansion load have focused on co-dominant mutations. An important consequence of this assumption is that expansion load stems exclusively from the accumulation of new mutations occurring in individuals living at the wave front. Using individual-based simulations we study here the dynamics of standing genetic variation at the front of expansions, and its consequences on mean fitness if mutations are recessive. We find that deleterious genetic diversity is quickly lost at the front of the expansion, but the loss of deleterious mutations at some loci is compensated by an increase of their frequencies at other loci. The frequency of deleterious homozygotes therefore increases along the expansion axis whereas the average number of deleterious mutations per individual remains nearly constant across the species range. This reveals two important differences to co-dominant models: (i) mean fitness at the front of the expansion drops much faster if mutations are recessive, and (ii) mutation load can increase during the expansion even if the total number of deleterious mutations per individual remains constant. We use our model to make predictions about the shape of the site frequency spectrum at the front of range expansion, and about correlations between heterozygosity and fitness in different parts of the species range. Importantly, these predictions provide opportunities to empirically validate our theoretical results. We discuss our findings in the light of recent results on the distribution of deleterious genetic variation across human populations, and link them to empirical results on the correlation of heterozygosity and fitness found in many natural range expansions.

Evolutionary Biology↗

bioRxiv2014

An annotated consensus genetic map for Pinus taeda L. and extent of linkage disequilibrium in three genotype-phenotype discovery populations

A consensus genetic map for Pinus taeda (loblolly pine) was constructed by merging three previously published maps with a map from a pseudo-backcross between P. taeda and P. elliottii (slash pine). The consensus map positioned 4981 markers via genotyping of 1251 individuals from four pedigrees. It is the densest linkage map for a conifer to date. Average marker spacing was 0.48 centiMorgans and total map length was 2372 centiMorgans. Functional predictions for 4762 markers for expressed sequence tags were improved by alignment to full-length P. taeda transcripts. Alignments to the P. taeda genome mapped 4225 scaffold sequences onto linkage groups. The consensus genetic map was used to compare the extent of genome-wide linkage disequilibrium in an association population of distantly related P. taeda individuals (ADEPT2), a multiple-family pedigree used for genomic selection studies (CCLONES), and a full-sib quantitative trait locus mapping population (BC1). Weak linkage disequilibrium was observed in CCLONES and ADEPT2. Average squared correlations, R2, between genotypes at SNPs less than one centiMorgan apart was less than 0.05 in both populations and R2 did not decay substantially with genetic distance. By contrast, strong and extended linkage disequilibrium was observed among BC1 full-sibs where average R2 decayed from 0.8 to less than 0.1 over 53 centiMorgans. The consensus map and analysis of linkage disequilibrium establish a foundation for comparative association and quantitative trait locus mapping between genotype-phenotype discovery populations.

Genomics↗

bioRxiv2015

Genetic variability under the seedbank coalescent

We analyse patterns of genetic variability of populations in the presence of a large seed bank with the help of a new coalescent structure called the seed bank coalescent. This ancestral process appears naturally as scaling limit of the genealogy of large populations that sustain seed banks, if the seed bank size and individual dormancy times are of the same order as the active population. Mutations appear as Poisson processes on the active lineages, and potentially at reduced rate also on the dormant lineages. The presence of dormant lineages leads to qualitatively altered times to the most recent common ancestor and non-classical patterns of genetic diversity. To illustrate this we provide a Wright-Fisher model with seed bank component and mutation, motivated from recent models of microbial dormancy, whose genealogy can be described by the seed bank coalescent. Based on our coalescent model, we derive recursions for the expectation and variance of the time to most recent common ancestor, number of segregating sites, pairwise differences, and singletons. Estimates (obtained by simulations) of the distributions of commonly employed distance statistics, in the presence and absence of a seed bank, are compared. The effect of a seed bank on the expected site-frequency spectrum is also investigated using simulations. Our results indicate that the presence of a large seed bank considerably alters the distribution of some distance statistics, as well as the site-frequency spectrum. Thus, one should be able to detect the presence of a large seed bank in genetic data.

Evolutionary Biology↗

bioRxiv2015

Generating effective models and parameters for RNA genetic circuits

RNA genetic circuitry is emerging as a powerful tool to control gene expression. However, little work has been done to create a theoretical foundation for RNA circuit design. A prerequisite to this is a quantitative modeling framework that accurately describes the dynamics of RNA circuits. In this work, we develop an ordinary differential equation model of transcriptional RNA genetic circuitry, using an RNA cascade as a test case. We show that parameter sensitivity analysis can be used to design a set of four simple experiments that can be performed in parallel using rapid cell-free transcription-translation (TX-TL) reactions to determine the thirteen parameters of the model. The resulting model accurately recapitulates the dynamic behavior of the cascade, and can be easily extended to predict the function of new cascade variants that utilize new elements with limited additional characterization experiments. Interestingly, we show that inconsistencies between model predictions and experiments led to the model-guided discovery of a previously unknown maturation step required for RNA regulator function. We also determine circuit parameters in two different batches of TX-TL, and show that batch-to-batch variation can be attributed to differences in parameters that are directly related to the concentrations of core gene expression machinery. We anticipate the RNA circuit models developed here will inform the creation of computer aided genetic circuit design tools that can incorporate the growing number of RNA regulators, and that the parameterization method will find use in determining functional parameters of a broad array of natural and synthetic regulatory systems.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC=\"FIGDIR/small/018358_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (17K):\norg.highwire.dtl.DTLVardef@1eace4dorg.highwire.dtl.DTLVardef@8e2757org.highwire.dtl.DTLVardef@b8f454org.highwire.dtl.DTLVardef@b0cfc9_HPS_FORMAT_FIGEXP M_FIG C_FIG

Synthetic Biology↗

bioRxiv2015

Detection and interpretation of shared genetic influences on 40 human traits

We performed a genome-wide scan for genetic variants that influence multiple human phenotypes by comparing large genome-wide association studies (GWAS) of 40 traits or diseases, including anthropometric traits (e.g. nose size and male pattern baldness), immune traits (e.g. susceptibility to childhood ear infections and Crohns disease), metabolic phenotypes (e.g. type 2 diabetes and lipid levels), and psychiatric diseases (e.g. schizophrenia and Parkinsons disease). First, we identified 307 loci (at a false discovery rate of 10%) that influence multiple traits (excluding \"trivial\" phenotype pairs like type 2 diabetes and fasting glucose). Several loci influence a large number of phenotypes; for example, variants near the blood group gene ABO influence eleven of these traits, including risk of childhood ear infections (rs635634: log-odds ratio = 0.06, P = 1.4 x 10-8) and allergies (log-odds ratio = 0.05, P = 2.5 x 10-8), among others. Similarly, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of these traits, including risk of schizophrenia (rs13107325: log-odds ratio = 0.15, P = 2 x 10-12) and Parkinsons disease (log-odds ratio = -0.15, P = 1.6 x 10-7), among others. Second, we used these loci to identify traits that share multiple genetic causes in common. For example, genetic variants that delay age of menarche in women also, on average, delay age of voice drop in men, decrease body mass index (BMI), increase adult height, and decrease risk of male pattern baldness. Finally, we identified four pairs of traits that show evidence of a causal relationship. For example, we show evidence that increased BMI causally increases triglyceride levels, and that increased liability to hypothyroidism causally decreases adult height.

Genomics↗

bioRxiv2015

How obstacles perturb population fronts and alter their genetic structure

As populations spread into new territory, environmental heterogeneities can shape the population front and genetic composition. We study here the effect of one important building block of inhomogeneous environments, compact obstacles. With a combination of experiments, theory, and simulation, we show how isolated obstacles both create long-lived distortions of the front shape and amplify the effect of genetic drift. A system of bacteriophage T7 spreading on a spatially heterogeneous Escherichia coli lawn serves as an experimental model system to study population expansions. Using an inkjet printer, we create well-defined replicates of the lawn and quantitatively study the population expansion manifested in plaque growth. The transient perturbations of the plaque boundary found in the experiments are well described by a model in which the front moves with constant speed. Independent of the precise details of the expansion, we show that obstacles create a kink in the front that persists over large distances and is insensitive to the details of the obstacle's shape. The small deviations between experimental findings and the predictions of the constant speed model can be understood with a more general reaction-diffusion model, which reduces to the constant speed model when the obstacle size is large compared to the front width. Using this framework, we demonstrate that frontier alleles that just graze the side of an isolated obstacle increase in abundance, a phenomenon we call 'geometry-enhanced genetic drift', complementary to the founder effect associated with spatial bottlenecks. Bacterial range expansions around nutrient-poor barriers and stochastic simulations confirm this prediction, the latter highlight as well the effect of the obstacle on the genealogy of individuals at the front. We argue that related ideas and experimental techniques are applicable to a wide variety of more complex environments, leading to a better understanding of how environmental heterogeneities affect population range expansions.

Evolutionary Biology↗

bioRxiv2015

Genetic loci with parent of origin effects cause hybrid seed lethality between Mimulus species

The classic finding in both flowering plants and mammals that hybrid lethality often depends on parent of origin effects suggests that divergence in the underlying loci might be an important source of hybrid incompatibilities between species. In flowering plants, there is now good evidence from diverse taxa that seed lethality arising from interploidy crosses is often caused by endosperm defects associated with deregulated imprinted genes. A similar seed lethality phenotype occurs in many crosses between closely related diploid species, but the genetic basis of this form of early-acting F1 postzygotic reproductive isolation is largely unknown. Here, we show that F1 hybrid seed lethality is an exceptionally strong isolating barrier between two closely related Mimulus species, M. guttatus and M. tilingii, with reciprocal crosses producing less than 1% viable seeds. Using a powerful crossing design and high-resolution genetic mapping, we identify both maternally- and paternally-derived loci that contribute to hybrid seed incompatibility. Strikingly, these two sets of loci are largely non-overlapping, providing strong evidence that genes with parent of origin effects are the primary driver of F1 hybrid seed lethality between M. guttatus and M. tilingii. We find a highly polygenic basis for both parental components of hybrid seed lethality suggesting that multiple incompatibility loci have accumulated to cause strong postzygotic isolation between these closely related species. Our genetic mapping experiment also reveals hybrid transmission ratio distortion and chromosomal differentiation, two additional correlates of functional and genomic divergence between species.

Evolutionary Biology↗

bioRxiv2015

EvolQG - An R package for evolutionary quantitative genetics

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable. Given this mathematical representation of available variation, the EvolQG package provides functions for calculation of relevant evolutionary statistics, estimation of sampling error, corrections for this error, matrix comparison via correlations and distances, and functions for testing evolutionary hypotheses on taxa diversification.

Evolutionary Biology↗

bioRxiv2015

Genetic structure of island and mainland populations of a Neotropical bumble bee species

Biodiversity loss is a global problem and island species/populations are particularly vulnerable to such loss. Low genetic diversity is one of the factors that can lead a population to extinction. Loss of bee populations is of particular concern because of the knock-on consequences for the pollination guilds that the lost bees once serviced. Here we evaluate the genetic structure of the bumble bee Bombus morio populations on the mainland of South East Brazil and on nearby islands. We analyzed a total of 659 individuals from 24 populations by sequencing two mitochondrial genes (COI and Cytb) and using 14 microsatellite loci. Levels of diversity were high in most of populations and were similar on islands and the mainland. Furthermore, genetic diversity was not significantly correlated with island area, although it was lower in populations from distant islands. Our data suggest that long-term isolation on islands is not affecting the population viability of this species. This may be attributed to the high dispersal ability of B. morio, its capacity to suvive in urban environments, and the characteristics of the studied islands.

Evolutionary Biology↗

bioRxiv2015

Molecular stripping in the NFκB/IκB/DNA genetic regulatory network

Genetic switches based on the NF{kappa}B/I{kappa}B/DNA system are master regulators of an array of cellular responses. Recent kinetic experiments have shown that I{kappa}B can actively remove NF{kappa}B bound to its genetic sites via a process called \"molecular stripping\". This allows the NF{kappa}B/I{kappa}B/DNA switch to function under kinetic control rather than the thermodynamic control contemplated in the traditional models of gene switches. Using molecular dynamics simulations of coarse grained predictive energy landscape models for the constituent proteins by themselves and interacting with the DNA we explore the functional motions of the transcription factor NF{kappa}B and its various binary and ternary complexes with DNA and the inhibitor I{kappa}B. These studies show that the function of the NF{kappa}B/I{kappa}B/DNA genetic switch is realized via an allosteric mechanism. Molecular stripping occurs through the activation of a domain twist mode by the binding of I{kappa}B which occurs through conformational selection. Free energy calculations for DNA binding show that the binding of I{kappa}B not only results in a significant decrease of the affinity of the transcription factor for the DNA but also kinetically speeds DNA release. Projections of the free energy onto various reaction coordinates reveal the structural details of the stripping pathways.

Biophysics↗

bioRxiv2015

Deep learning for population genetic inference

Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce here a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. In contrast to Approximate Bayesian Computation, another likelihood-free approach widely used in population genetics and other fields, deep learning does not require a distance function on summary statistics or a rejection step, and it is robust to the addition of uninformative statistics. To demonstrate that deep learning can be effectively employed to estimate population genetic parameters and learn informative features of data, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme, likely due in part to the unaccounted impact of selection.

Evolutionary Biology↗

bioRxiv2015

DBSIM: A Platform of Simulation Resources for Genetic Epidemiology Studies

Computer simulations are routinely conducted to evaluate new statistical methods, to compare the properties among different methods, and to mimic the real data in genetic epidemiology studies. Conducting simulation studies can become a complicated task as several challenges can occur, such as the selection of an appropriate simulation tool and the specification of parameters in the simulation model. Although abundant simulated data have been generated for human genetic research, currently there is no public database designed specifically as a repository for these simulated data. With the lack of such database, for similar studies, similar simulations may have been repeated, which resulted in redundant works. We created an online platform, DBSIM, for simulation data sharing and discussion of simulation techniques for human genetic studies. DBSIM has a database containing simulation scripts, simulated data, and documentations from published manuscripts, as well as a discussion forum, which provides a platform for discussion of the simulated data and exchanging simulation ideas. DBSIM will be useful in three aspects. Moreover, summary statistics such as the simulation tools that are most commonly used and datasets that are most frequently downloaded are provided. The statistics will be very informative for researchers to choose an appropriate simulation tool or select a common dataset for method comparisons. DBSIM can be accessed at http://dbsim.nhri.org.tw.

Bioinformatics↗

bioRxiv2015

Rising out of the ashes: additive genetic variation for susceptibility to Hymenoscyphus fraxineus in Fraxinus excelsior

Ash dieback due to Hymenoscyphus fraxineus is threatening the Fraxinus excelsior species in most of its natural range in Europe and it is becoming obvious that other species in the Fraxinus genus are susceptible to the disease. The fungal pathogen apparently originates from Asia where it may act as an endophyte of local species like F. mandshurica. Previous studies reported significant levels of genetic variability for susceptibility in F. excelsior either in field or inoculation experiments. The present study was based on a field experiment planted in 1995, fifteen years before onset of the disease. Crown and collar status were monitored on 788 trees from 23 open-pollinated progenies originating from 3 French provenances. Susceptibility was modelled using a Bayesian approach where spatio-temporal effects were explicitly taken into account, thus providing accurate narrow-sense heritability estimates (h2). While moderate narrow-sense heritability estimates for Crown Dieback (CD, h2 = 0.42 in this study) have already been reported in the literature, this study is first to show that Collar Lesions are also heritable (h2 = 0.49 for prevalence and h2 = 0.42 for severity) and that there is significant genetic correlation between the severities of both traits (rspearman=0.40). Unexpectedly, their spatio-temporal dynamics followed almost opposite patterns. While no significant Provenance effect were detected for any trait, significant Family effects were found for both CD and CL. Moreover, the analysis strategy implemented here allowed to compute Individual Breeding Values (IBV) and to show that there is more genetic variability within families than between families. In agreement with previous reports, early flushing correlates with better crown status. Consequences of these results in terms of management and breeding are discussed.

Pathology↗

bioRxiv2015

The Genetic Equidistance Phenomenon at the Proteomic Level

The field of molecular evolution started with the alignment of a few protein sequences in the early 1960s. Among the first results found, the genetic equidistance result has turned out to be the most unexpected. It directly inspired the ad hoc universal molecular clock hypothesis that in turn inspired the neutral theory. Unfortunately, however, what is only a maximum distance phenomenon was mistakenly transformed into a mutation rate phenomenon and became known as such. Previous work studied a small set of selected proteins. We have performed proteome wide studies of 7 different sets of proteomes involving a total of 15 species. All 7 sets showed that within each set of 3 species the least complex species is approximately equidistant in average proteome wide identity to the two more complex ones. Thus, the genetic equidis-tance result is a universal phenomenon of maximum distance. There is a reality of constant albeit stepwise or discontinuous increase in complexity during evolution, the rate of which is what the original molecular clock hypothesis is really about. These results provide additional lines of evidence for the recently proposed maximum genetic diversity (MGD) hypothesis.\n\nAvailability and implementationThe source code repository is publicly available at https://github.com/Sephiroth1st/EquidistanceScript\n\nContacthuangshi@sklmg.edu.cn\n\nSupplementary informationSupplementary data are available online.

Evolutionary Biology↗

bioRxiv2015

BioJS-HGV Viewer: Genetic Variation Visualizer

MotivationStudying the pattern of genetic variants is a primary step in deciphering the basis of biological diversity, identifying key driver variants that affect disease states and evolution of a species. Catalogs of genetic variants contain vast numbers of variants and are growing at an exponential rate, but lack an interactive exploratory interface.\n\nResultsWe present BioJS-HGV Viewer, a BioJS component to represent and visualize genetic variants pooled from different sources. The tool displays sequences and variants at different levels of detail, facilitating representation of variant sites and annotations in a user friendly and interactive manner.\n\nAvailabilitySource code for BioJS-HGV Viewer is available at: https://github.com/saketkc/biojs-genetic-variation-viewer\n\nA demo is available at: http://saketkc.github.io/biojs-genetic-variation-viewer\n\nContact: martin@ebi.ac.uk

Bioinformatics↗

bioRxiv2015

Rapid evolution of the inter-sexual genetic correlation for fitness in Drosophila melanogaster

Sexual antagonism (SA) arises when male and female phenotypes are under opposing selection, yet genetically correlated. Until resolved, antagonism limits evolution towards optimal sex-specific phenotypes. Despite its importance for sex-specific adaptation and existing theory, the dynamics of SA resolution are not well understood empirically. Here, we present data from Drosophila melanogaster, compatible with a resolution of SA. We compared two independent replicates of the LHM population in which SA had previously been described. Both had been maintained under identical, controlled conditions, and separated for <250 generations. Although heritabilities of male and female fitness were similar, the inter-sexual genetic correlation differed significantly, being negative in one replicate (indicating SA) but close to zero in the other. Using population sequencing, we show that phenotypic differences were associated with population divergence in allele frequencies at non-random loci across the genome. Large frequency changes were more prevalent in the population without SA and were enriched at loci mapping to genes previously shown to have a sexually antagonistic relationships between expression and fitness. Our data suggest that rapid evolution towards SA resolution has occurred in one of the populations and open avenues towards studying the genetics of SA and its resolution.

Evolutionary Biology↗