Visualizing spatial population structure with estimated effective migration surfaces

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Visualizing spatial population structure with estimated effective migration surfaces
Desislava Petkova, John Novembre, Matthew Stephens
doi: http://dx.doi.org/10.1101/011809

Genetic data often exhibit patterns that are broadly consistent with “isolation by distance” – a phenomenon where genetic similarity tends to decay with geographic distance. In a heterogeneous habitat, decay may occur more quickly in some regions than others: for example, barriers to gene flow can accelerate the genetic differentiation between groups located close in space. We use the concept of “effective migration” to model the relationship between genetics and geography: in this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to quantify and visualize variation in effective migration across the habitat, which can be used to identify potential barriers to gene flow, from geographically indexed large-scale genetic data. Our approach uses a population genetic model to relate underlying migration rates to expected pairwise genetic dissimilarities, and estimates migration rates by matching these expectations to the observed dissimilarities. We illustrate the potential and limitations of our method using simulations and data from elephant, human, and Arabidopsis thaliana populations. The resulting visualizations highlight important features of the spatial population structure that are difficult to discern using existing methods for summarizing genetic variation such as principal components analysis.

Reveel: large-scale population genotyping using low-coverage sequencing data

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Reveel: large-scale population genotyping using low-coverage sequencing data
Lin Huang, Bo Wang, Ruitang Chen, Sivan Bercovici, Serafim Batzoglou
doi: http://dx.doi.org/10.1101/011882

Population low-coverage whole-genome sequencing is rapidly emerging as a prominent approach for discovering genomic variation and genotyping a cohort. This approach combines substantially lower cost than full-coverage sequencing with whole-genome discovery of low-allele-frequency variants, to an extent that is not possible with array genotyping or exome sequencing. However, a challenging computational problem arises when attempting to discover variants and genotype the entire cohort. Variant discovery and genotyping are relatively straightforward on a single individual that has been sequenced at high coverage, because the inference decomposes into the independent genotyping of each genomic position for which a sufficient number of confidently mapped reads are available. However, in cases where low-coverage population data are given, the joint inference requires leveraging the complex linkage disequilibrium patterns in the cohort to compensate for sparse and missing data in each individual. The potentially massive computation time for such inference, as well as the missing data that confound low-frequency allele discovery, need to be overcome for this approach to become practical. Here, we present Reveel, a novel method for single nucleotide variant calling and genotyping of large cohorts that have been sequenced at low coverage. Reveel introduces a novel technique for leveraging linkage disequilibrium that deviates from previous Markov-based models. We evaluate Reveel???s performance through extensive simulations as well as real data from the 1000 Genomes Project, and show that it achieves higher accuracy in low-frequency allele discovery and substantially lower computation cost than previous state-of-the-art methods.

Bet-hedging, seasons and the evolution of behavioral diversity in Drosophila

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Bet-hedging, seasons and the evolution of behavioral diversity in Drosophila
Jamey Kain, Sarah Zhang, Mason Klein, Aravinthan Samuel, Benjamin de Bivort
doi: http://dx.doi.org/10.1101/012021

Organisms use various strategies to cope with fluctuating environmental conditions. In diversified bet-hedging, a single genotype exhibits phenotypic heterogeneity with the expectation that some individuals will survive transient selective pressures. To date, empirical evidence for bet-hedging is scarce. Here, we observe that individual Drosophila melanogaster flies exhibit striking variation in light- and temperature-preference behaviors. With a modeling approach that combines real world weather and climate data to simulate temperature preference-dependent survival and reproduction, we find that a bet-hedging strategy may underlie the observed inter-individual behavioral diversity. Specifically, bet-hedging outcompetes strategies in which individual thermal preferences are heritable. Animals employing bet-hedging refrain from adapting to the coolness of spring with increased warm-seeking that inevitably becomes counterproductive in the hot summer. This strategy is particularly valuable when mean seasonal temperatures are typical, or when there is considerable fluctuation in temperature within the season. The model predicts, and we experimentally verify, that the behaviors of individual flies are not heritable. Finally, we model the effects of historical weather data, climate change, and geographic seasonal variation on the optimal strategies underlying behavioral variation between individuals, characterizing the regimes in which bet-hedging is advantageous.

>msCentipede: Modeling heterogeneity across genomic sites improves accuracy in the inference of transcription factor binding

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msCentipede: Modeling heterogeneity across genomic sites improves accuracy in the inference of transcription factor binding
Anil Raj, Heejung Shim, Yoav Gilad, Jonathan K Pritchard, Matthew Stephens
doi: http://dx.doi.org/10.1101/012013

Motivation: Understanding global gene regulation depends critically on accurate annotation of regulatory elements that are functional in a given cell type. CENTIPEDE, a powerful, probabilistic framework for identifying transcription factor binding sites from tissue-specific DNase I cleavage patterns and genomic sequence content, leverages the hypersensitivity of factor-bound chromatin and the information in the DNase I spatial cleavage profile characteristic of each DNA binding protein to accurately infer functional factor binding sites. However, the model for the spatial profile in this framework underestimates the substantial variation in the DNase I cleavage profiles across factor-bound genomic locations and across replicate measurements of chromatin accessibility. Results: In this work, we adapt a multi-scale modeling framework for inhomogeneous Poisson processes to better model the underlying variation in DNase I cleavage patterns across genomic locations bound by a transcription factor. In addition to modeling variation, we also model spatial structure in the heterogeneity in DNase I cleavage patterns for each factor. Using DNase-seq measurements assayed in a lymphoblastoid cell line, we demonstrate the improved performance of this model for several transcription factors by comparing against the Chip-Seq peaks for those factors. Finally, we propose an extension to this framework that allows for a more flexible background model and evaluate the additional gain in accuracy achieved when the background model parameters are estimated using DNase-seq data from naked DNA. The proposed model can also be applied to paired-end ATAC-seq and DNase-seq data in a straightforward manner. Availability: msCentipede, a Python implementation of an algorithm to infer transcription factor binding using this model, is made available at https://github.com/rajanil/msCentipede

Demographic inference using genetic data from a single individual: separating population size variation

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Demographic inference using genetic data from a single individual: separating population size variation from population structure
Olivier Mazet, Willy Rodríguez, Lounès Chikhi
doi: http://dx.doi.org/10.1101/011866

The rapid development of sequencing technologies represents new opportunities for population genetics research. It is expected that genomic data will increase our ability to reconstruct the history of populations. While this increase in genetic information will likely help biologists and anthropologists to reconstruct the demographic history of populations, it also represents new challenges. Recent work has shown that structured populations generate signals of population size change. As a consequence it is often difficult to determine whether demographic events such as expansions or contractions (bottlenecks) inferred from genetic data are real or due to the fact that populations are structured in nature. Given that few inferential methods allow us to account for that structure, and that genomic data will necessarily increase the precision of parameter estimates, it is important to develop new approaches. In the present study we analyse two demographic models. The first is a model of instantaneous population size change whereas the second is the classical symmetric island model. We (i) re-derive the distribution of coalescence times under the two models for a sample of size two, (ii) use a maximum likelihood approach to estimate the parameters of these models (iii) validate this estimation procedure under a wide array of parameter combinations, (iv) implement and validate a model choice procedure by using a Kolmogorov-Smirnov test. Altogether we show that it is possible to estimate parameters under several models and perform efficient model choice using genetic data from a single diploid individual.

Recent Y chromosome divergence despite ancient origin of dioecy in poplars (Populus)

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Recent Y chromosome divergence despite ancient origin of dioecy in poplars (Populus)
Armando Geraldes, Charles A Hefer, Arnaud Capron, Natalia Kolosova, Felix Martinez-Nuñez, Raju Y Soolanayakanahally, Brian Stanton, Robert D Guy, Shawn D Mansfield, Carl J Douglas, Quentin C B Cronk
doi: http://dx.doi.org/10.1101/011817
Abstract

All species of the genus Populus (poplar, aspen) are dioecious, suggesting an ancient origin of this trait. Theory suggests that non-recombining sex-linked regions should quickly spread, eventually becoming heteromorphic chromosomes. In contrast, we show using whole genome scans that the sex-associated region in P. trichocarpa is small and much younger than the age of the genus. This indicates that sex-determination is highly labile in poplar, consistent with recent evidence of “turnover” of sex determination regions in animals. We performed whole genome resequencing of 52 Populus trichocarpa (black cottonwood) and 34 P. balsamifera (balsam poplar) individuals of known sex. Genome-wide association studies (GWAS) in these unstructured populations identified 650 SNPs significantly associated with sex. We estimate the size of the sex-linked region to be ∼100 Kbp. All significant SNPs were in strong linkage disequilibrium despite the fact that they were mapped to six different chromosomes (plus 3 unmapped scaffolds) in version 2.2 of the reference genome. We show that this is likely due to genome misassembly. The segregation pattern of sex associated SNPs revealed this to be an XY sex determining system. Estimated divergence times of X and Y haplotype sequences (6-7 MYA) are much more recent than the divergence of P. trichocarpa (poplar) and P. tremuloides (aspen). Consistent with this, in P. tremuloides we found no XY haplotype divergence within the P. trichocarpa sex-determining region. These two species therefore have a different genomic architecture of sex, suggestive of at least one turnover event in the recent past.

Spider web DNA: a new spin on noninvasive genetics of predator and prey

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Spider web DNA: a new spin on noninvasive genetics of predator and prey

Charles Cong Yang Xu, Ivy J Yen, Dean Bowman, Cameron R. Turner
doi: http://dx.doi.org/10.1101/011775

Noninvasive genetic approaches enable biomonitoring without the need to directly observe or disturb target organisms. Environmental DNA (eDNA) methods have recently extended this approach by assaying genetic material within bulk environmental samples without a priori knowledge about the presence of target biological material. This paper describes a novel and promising source of noninvasive spider DNA and insect eDNA from spider webs. Using black widow spiders (Latrodectus spp.) fed with house crickets (Acheta domesticus), we successfully extracted and amplified mitochondrial DNA sequences of both spider and prey from spider web. Detectability of spider DNA did not differ between assays with amplicon sizes from 135 to 497 base pairs. Spider DNA and prey eDNA remained detectable at least 88 days after living organisms were no longer present on the web. Spider web DNA may be an important tool in conservation research, pest management, biogeography studies, and biodiversity assessments.

Genetic landscape of populations along the Silk Road: admixture and migration patterns

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Genetic landscape of populations along the Silk Road: admixture and migration patterns

Massimo Mezzavilla, Diego Vozzi, Nicola Pirastu, Giorgia Girotto, Pio D’Adamo, Paolo Gasparini, Vincenza Colonna
doi: http://dx.doi.org/10.1101/011759

Background The ancient Silk Road has been a trading route between Europe and Central Asia from the 2nd century BCE to the 15th century CE. While most populations on this route have been characterized, the genetic background of others remains poorly understood, and little is known about past migration patterns. The scientific expedition “Marco Polo” has recently collected genetic and phenotypic data in six regions (Georgia, Armenia, Azerbaijan, Uzbekistan, Kazakhstan, Tajikistan) along the Silk Road to study the genetics of a number of phenotypes. Results We characterized the genetic structure of these populations within a worldwide context. We observed a West-East subdivision albeit the existence of a genetic component shared within Central Asia and nearby populations from Europe and Near East. We observed a contribution of up to 50% from Europe and Asia to most of the populations that have been analyzed. The contribution from Asia dates back to ~25 generations and is limited to the Eastern Silk Road. Time and direction of this contribution are consistent with the Mongolian expansion era. Conclusions We clarified the genetic structure of six populations from Central Asia and suggested a complex pattern of gene flow among them. We provided a map of migration events in time and space and we quantified exchanges among populations. Altogether these novel findings will support the future studies aimed at understanding the genetics of the phenotypes that have been collected during the Marco Polo campaign, they will provide insights into the history of these populations, and they will be useful to reconstruct the developments and events that have shaped modern Eurasians genomes.

Dynamic epistasis for different alleles of the same gene

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Dynamic epistasis for different alleles of the same gene

Lin Xu, Brandon Barker, Zhenglong Gu
(Submitted on 24 Nov 2014)

Epistasis refers to the phenomenon in which phenotypic consequences caused by mutation of one gene depend on one or more mutations at another gene. Epistasis is critical for understanding many genetic and evolutionary processes, including pathway organization, evolution of sexual reproduction, mutational load, ploidy, genomic complexity, speciation, and the origin of life. Nevertheless, current understandings for the genome-wide distribution of epistasis are mostly inferred from interactions among one mutant type per gene, whereas how epistatic interaction partners change dynamically for different mutant alleles of the same gene is largely unknown. Here we address this issue by combining predictions from flux balance analysis and data from a recently published high-throughput experiment. Our results show that different alleles can epistatically interact with very different gene sets. Furthermore, between two random mutant alleles of the same gene, the chance for the allele with more severe mutational consequence to develop a higher percentage of negative epistasis than the other allele is 50-70% in eukaryotic organisms, but only 20-30% in bacteria and archaea. We developed a population genetics model that predicts that the observed distribution for the sign of epistasis can speed up the process of purging deleterious mutations in eukaryotic organisms. Our results indicate that epistasis among genes can be dynamically rewired at the genome level, and call on future efforts to revisit theories that can integrate epistatic dynamics among genes in biological systems.

Tissue-specific evolution of protein coding genes in human and mouse

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Tissue-specific evolution of protein coding genes in human and mouse

Nadezda Kryuchkova, Marc Robinson-Rechavi
doi: http://dx.doi.org/10.1101/011692

Protein-coding genes evolve at different rates, and the influence of different parameters, from gene size to expression level, has been extensively studied. While in yeast gene expression level is the major causal factor of gene evolutionary rate, the situation is more complex in animals. Here we investigate these relations further, especially taking in account gene expression in different organs as well as indirect correlations between parameters. We used RNA-seq data from two large datasets, covering 22 mouse tissues and 27 human tissues. Over all tissues, evolutionary rate only correlates weakly with levels and breadth of expression. The strongest explanatory factors of strong purifying selection are GC content, expression in many developmental stages, and expression in brain tissues. While the main component of evolutionary rate is purifying selection, we also find tissue-specific patterns for sites under neutral evolution and for positive selection. We observe fast evolution of genes expressed in testis, but also in other tissues, notably liver, which are explained by weak purifying selection rather than by positive selection.