Correcting estimators of theta and Tajima's D for ascertainment biases caused by the single-nucleotide polymorphism discovery process

Molecular marker development and genetic diversity exploration in Medicago polymorpha

Medicago polymorpha L. (bur clover), an invasive plant species of the genus Medicago, has been traditionally used in China as an edible vegetable crop because of its high nutritive value. However, few molecular markers for M. polymorpha have been identified. Using the recently published high-quality reference genome of M. polymorpha, we performed a specific-locus amplified fragment sequencing (SLAF-seq) analysis of 10 M. polymorpha accessions to identify molecular markers and explore genetic diversity. A total of 52,237 high-quality single nucleotide polymorphisms (SNPs) were developed. These SNPs were mostly distributed on pseudochromosome 3, least distributed on pseudochromosome 7, and relatively evenly distributed on five other pseudochromosomes of M. polymorpha. Phenotypic analysis showed that there was a great difference in phenotypic traits among different M. polymorpha accessions. Moreover, clustering all M. polymorpha accessions based on their phenotypic traits revealed three groups. Both phylogenetic analysis and principal component analysis (PCA) of all M. polymorpha accessions based on SNP markers consistently indicated that all M. polymorpha accessions could be divided into three distinct groups (I, II, and III). Subsequent genetic diversity analysis for the 10 M. polymorpha accessions validated the effectiveness of the M. polymorpha germplasm molecular markers in China. Additionally, SSR mining analysis was also performed to identify polymorphic SSR motifs, which could provide valuable candidate markers for the further breeding of M. polymorpha. Since M. polymorpha genetics have not been actively studied, the molecular markers generated from our research will be useful for further research on M. polymorpha resource utilization and marker-assisted breeding.

High fraction of silent recombination in a finite-population two-locus neutral birth-death-mutation model

A precise estimate of allele and haplotype polymorphism is of great interest in theoretical population genetics, but also has practical applications, such as bone marrow registries management. Allele polymorphism is driven mainly by point mutations, while haplotype polymorphism is also affected by recombination. Current estimates treat recombination as mutations in an infinite site model. We here show that even in the simple case of two loci in a haploid individual, for a finite population, most recombination events produce existing haplotypes, and as such are silent. Silent recombination considerably reduces the total number of haplotypes expected from the infinite site model for populations that are not much larger than one over the mutation rate. Moreover, in contrast with mutations, the number of haplotypes does not grow linearly with the population size. We hence propose a more accurate estimate of the total number of haplotypes that takes into account silent recombination. We study large-scale human leukocyte antigen (HLA) haplotype frequencies from human populations to show that the current estimated recombination rate in the HLA region is underestimated.

Divergent and linked selection shape patterns of genomic differentiation between European and North American Atlantic salmon (Salmo salar)

As populations diverge many processes can shape genomic patterns of differentiation. Regions of high differentiation can arise due to divergent selection acting on selected loci, genetic hitchhiking of nearby loci, or through repeated selection against deleterious alleles (linked background selection); this divergence may then be further elevated in regions of reduced recombination. Atlantic salmon (Salmo salar) from Europe and North America diverged >600,000 years ago and despite some evidence of secondary contact, the majority of genetic data indicate substantial divergence between lineages. This deep divergence with potential gene flow provides an opportunity to investigate the role of different mechanisms that shape the genomic landscape during early speciation. Here, using 184,295 single nucleotide polymorphisms (SNPs) and 80 populations, we investigate the genomic landscape of differentiation across the Atlantic Ocean with a focus on highly differentiated regions and the processes shaping them. We found evidence of high (mean F_ST  = 0.26) and heterogeneous genomic differentiation between continents. Genomic regions associated with high trans-Atlantic differentiation ranged in size from single loci (SNPs) within important genes to large regions (1-3 Mbp) on four chromosomes (Ssa06, Ssa13, Ssa16 and Ssa19). These regions showed signatures consistent with selection, including high linkage disequilibrium, despite no significant reduction in recombination. Genes and functional enrichment of processes associated with differentiated regions may highlight continental differences in ocean navigation and parasite resistance. Our results provide insight into potential mechanisms underlying differences between continents, and evidence of near-fixed and potentially adaptive trans-Atlantic differences concurrent with a background of high genome-wide differentiation supports subspecies designation in Atlantic salmon.

A Large Panel of Drosophila simulans Reveals an Abundance of Common Variants

The rapidly expanding availability of large NGS data sets provides an opportunity to investigate population genetics at an unprecedented scale. Drosophila simulans is the sister species of the model organism Drosophila melanogaster, and is often presumed to share similar demographic history. However, previous population genetic and ecological work suggests very different signatures of selection and demography. Here, we sequence a new panel of 170 inbred genotypes of a North American population of D. simulans, a valuable complement to the DGRP and other D. melanogaster panels. We find some unexpected signatures of demography, in the form of excess intermediate frequency polymorphisms. Simulations suggest that this is possibly due to a recent population contraction and selection. We examine the outliers in the D. simulans genome determined by a haplotype test to attempt to parse the contribution of demography and selection to the patterns observed in this population. Untangling the relative contribution of demography and selection to genomic patterns of variation is challenging, however, it is clear that although D. melanogaster was thought to share demographic history with D. simulans different forces are at work in shaping genomic variation in this population of D. simulans.

Population genomics of the eastern cottonwood (Populus deltoides)

Despite its economic importance as a bioenergy crop and key role in riparian ecosystems, little is known about genetic diversity and adaptation of the eastern cottonwood (Populus deltoides). Here, we report the first population genomics study for this species, conducted on a sample of 425 unrelated individuals collected in 13 states of the southeastern United States. The trees were genotyped by targeted resequencing of 18,153 genes and 23,835 intergenic regions, followed by the identification of single nucleotide polymorphisms (SNPs). This natural P. deltoides population showed low levels of subpopulation differentiation (F_ST = 0.022–0.106), high genetic diversity (θ_W = 0.00100, π = 0.00170), a large effective population size (N_e ≈ 32,900), and low to moderate levels of linkage disequilibrium. Additionally, genomewide scans for selection (Tajima's D), subpopulation differentiation (X^TX), and environmental association analyses with eleven climate variables carried out with two different methods (LFMM and BAYENV2) identified genes putatively involved in local adaptation. Interestingly, many of these genes were also identified as adaptation candidates in another poplar species, Populus trichocarpa, indicating possible convergent evolution. This study constitutes the first assessment of genetic diversity and local adaptation in P. deltoides throughout the southern part of its range, information we expect to be of use to guide management and breeding strategies for this species in future, especially in the face of climate change.

Environmental versus geographical effects on genomic variation in wild soybean (Glycine soja) across its native range in northeast Asia

A fundamental goal in evolutionary biology is to understand how various evolutionary factors interact to affect the population structure of diverse species, especially those of ecological and/or agricultural importance such as wild soybean (Glycine soja). G. soja, from which domesticated soybeans (Glycine max) were derived, is widely distributed throughout diverse habitats in East Asia (Russia, Japan, Korea, and China). Here, we utilize over 39,000 single nucleotide polymorphisms genotyped in 99 ecotypes of wild soybean sampled across their native geographic range in northeast Asia, to understand population structure and the relative contribution of environment versus geography to population differentiation in this species. A STRUCTURE analysis identified four genetic groups that largely corresponded to the geographic regions of central China, northern China, Korea, and Japan, with high levels of admixture between genetic groups. A canonical correlation and redundancy analysis showed that environmental factors contributed 23.6% to population differentiation, much more than that for geographic factors (6.6%). Precipitation variables largely explained divergence of the groups along longitudinal axes, whereas temperature variables contributed more to latitudinal divergence. This study provides a foundation for further understanding of the genetic basis of climatic adaptation in this ecologically and agriculturally important species.

Environmental versus geographical effects on genomic variation in wild soybean (Glycine soja) across its native range in northeast Asia

A fundamental goal in evolutionary biology is to understand how various evolutionary factors interact to affect the population structure of diverse species, especially those of ecological and/or agricultural importance such as wild soybean (Glycine soja). G. soja, from which domesticated soybeans (Glycine max) were derived, is widely distributed throughout diverse habitats in East Asia (Russia, Japan, Korea, and China). Here, we utilize over 39,000 single nucleotide polymorphisms genotyped in 99 ecotypes of wild soybean sampled across their native geographic range in northeast Asia, to understand population structure and the relative contribution of environment versus geography to population differentiation in this species. A STRUCTURE analysis identified four genetic groups that largely corresponded to the geographic regions of central China, northern China, Korea, and Japan, with high levels of admixture between genetic groups. A canonical correlation and redundancy analysis showed that environmental factors contributed 23.6% to population differentiation, much more than that for geographic factors (6.6%). Precipitation variables largely explained divergence of the groups along longitudinal axes, whereas temperature variables contributed more to latitudinal divergence. This study provides a foundation for further understanding of the genetic basis of climatic adaptation in this ecologically and agriculturally important species.

Inferring positive selection in humans from genomic data

Adaptation can be described as an evolutionary process that leads to an adjustment of the phenotypes of a population to their environment. In the classical view, new mutations can introduce novel phenotypic features into a population that leave footprints in the genome after fixation, such as selective sweeps. Alternatively, existing genetic variants may become beneficial after an environmental change and increase in frequency. Although they may not reach fixation, they may cause a shift of the optimum of a phenotypic trait controlled by multiple loci. With the availability of polymorphism data from various organisms, including humans and chimpanzees, it has become possible to detect molecular evidence of adaptation and to estimate the strength and target of positive selection. In this review, we discuss the two competing models of adaptation and suitable approaches for detecting the footprints of positive selection on the molecular level.

A bioinformatics workflow for detecting signatures of selection in genomic data

The detection of "signatures of selection" is now possible on a genome-wide scale in many plant and animal species, and can be performed in a population-specific manner due to the wealth of per-population genome-wide genotype data that is available. With genomic regions that exhibit evidence of having been under selection shown to also be enriched for genes associated with biologically important traits, detection of evidence of selective pressure is emerging as an additional approach for identifying novel gene-trait associations. While high-density genotype data is now relatively easy to obtain, for many researchers it is not immediately obvious how to go about identifying signatures of selection in these data sets. Here we describe a basic workflow, constructed from open source tools, for detecting and examining evidence of selection in genomic data. Code to install and implement the pipeline components, and instructions to run a basic analysis using the workflow described here, can be downloaded from our public GitHub repository: http://www.github.com/smilefreak/selectionTools/

Detecting natural selection in genomic data

The past fifty years have seen the development and application of numerous statistical methods to identify genomic regions that appear to be shaped by natural selection. These methods have been used to investigate the macro- and microevolution of a broad range of organisms, including humans. Here, we provide a comprehensive outline of these methods, explaining their conceptual motivations and statistical interpretations. We highlight areas of recent and future development in evolutionary genomics methods and discuss ongoing challenges for researchers employing such tests. In particular, we emphasize the importance of functional follow-up studies to characterize putative selected alleles and the use of selection scans as hypothesis-generating tools for investigating evolutionary histories.

Calculation of Tajima's D and other neutrality test statistics from low depth next-generation sequencing data

BACKGROUND

A number of different statistics are used for detecting natural selection using DNA sequencing data, including statistics that are summaries of the frequency spectrum, such as Tajima's D. These statistics are now often being applied in the analysis of Next Generation Sequencing (NGS) data. However, estimates of frequency spectra from NGS data are strongly affected by low sequencing coverage; the inherent technology dependent variation in sequencing depth causes systematic differences in the value of the statistic among genomic regions.

RESULTS

We have developed an approach that accommodates the uncertainty of the data when calculating site frequency based neutrality test statistics. A salient feature of this approach is that it implicitly solves the problems of varying sequencing depth, missing data and avoids the need to infer variable sites for the analysis and thereby avoids ascertainment problems introduced by a SNP discovery process.

CONCLUSION

Using an empirical Bayes approach for fast computations, we show that this method produces results for low-coverage NGS data comparable to those achieved when the genotypes are known without uncertainty. We also validate the method in an analysis of data from the 1000 genomes project. The method is implemented in a fast framework which enables researchers to perform these neutrality tests on a genome-wide scale.

Genetic diversity analysis of elite European maize (Zea mays L.) inbred lines using AFLP, SSR, and SNP markers reveals ascertainment bias for a subset of SNPs

Recent advances in high-throughput sequencing technologies have triggered a shift toward single-nucleotide polymorphism (SNP) markers. A systematic bias can be introduced if SNPs are ascertained in a small panel of genotypes and then used for characterizing a larger population (ascertainment bias). With the objective of evaluating a potential ascertainment bias of the Illumina MaizeSNP50 array with respect to elite European maize dent and flint inbred lines, we compared the genetic diversity among these materials based on 731 amplified fragment length polymorphisms (AFLPs), 186 simple sequence repeats (SSRs), 41,434 SNPs of the MaizeSNP50 array (SNP-A), and two subsets of it, i.e., 30,068 Panzea (SNP-P) and 11,366 Syngenta markers (SNP-S). We evaluated the bias effects on major allele frequency, allele number, gene diversity, modified Roger's distance (MRD), and on molecular variance (AMOVA). We revealed ascertainment bias in SNP-A, compared to AFLPs and SSRs. It affected especially European flint lines analyzed with markers (SNP-S) specifically developed to maximize differences among North American dent germplasm. The bias affected all genetic parameters, but did not substantially alter the relative distances between inbred lines within groups. For these reasons, we conclude that the SNP markers of the MaizeSNP50 array can be employed for breeding purposes in the investigated material. However, attention should be paid in case of comparisons between genotypes belonging to different heterotic groups. In this case, it is advisable to prefer a marker subset with potentially low ascertainment bias, like in our case the SNP-P marker set.

Evolution and functional impact of rare coding variation from deep sequencing of human exomes

As a first step toward understanding how rare variants contribute to risk for complex diseases, we sequenced 15,585 human protein-coding genes to an average median depth of 111× in 2440 individuals of European (n = 1351) and African (n = 1088) ancestry. We identified over 500,000 single-nucleotide variants (SNVs), the majority of which were rare (86% with a minor allele frequency less than 0.5%), previously unknown (82%), and population-specific (82%). On average, 2.3% of the 13,595 SNVs each person carried were predicted to affect protein function of ~313 genes per genome, and ~95.7% of SNVs predicted to be functionally important were rare. This excess of rare functional variants is due to the combined effects of explosive, recent accelerated population growth and weak purifying selection. Furthermore, we show that large sample sizes will be required to associate rare variants with complex traits.

Population biology of fungal plant pathogens

Studies of the population genetics of fungal and oomycetous phytopathogens are essential to clarifying the disease epidemiology and devising management strategies. Factors commonly associated with higher organisms such as migration, natural selection, or recombination, are critical for the building of a clearer picture of the pathogen in the landscape. In this chapter, we focus on a limited number of experimental and analytical methods that are commonly applied in population genetics. At first, we present different types of qualitative and quantitative traits that could be identified morphologically (phenotype). Subsequently, we describe several molecular methods based on dominant and codominant markers, and we provide our assessment of the advantages and shortfalls of these methods. Third, we discuss various analytical methods, which include phylogenies, summary statistics as well as coalescent-based methods, and we elaborate on the benefits associated with each approach. Last, we develop a case study in which we investigate the population structure of the fungal phytopathogen Verticillium dahliae in coastal California, and assess the hypotheses of transcontinental gene flow and recombination in a fungus that is described as asexual.

Rare variant density across the genome and across populations

Next-generation sequencing allows for a new focus on rare variant density for conducting analyses of association to disease and for narrowing down the genomic regions that show evidence of functionality. In this study we use the 1000 Genomes Project pilot data as distributed by Genetic Analysis Workshop 17 to compare rare variant densities across seven populations. We made the comparisons using regressions of rare variants on total variant counts per gene for each population and Tajima's D values calculated for each gene in each population, using data on 3,205 genes. We found that the populations clustered by continent for both the regression slopes and Tajima's D values, with the African populations (Yoruba and Luhya) showing the highest density of rare variants, followed by the Asian populations (Han and Denver Chinese followed by the Japanese) and the European populations (CEPH [European-descent] and Tuscan) with the lowest densities. These significant differences in rare variant densities across populations seem to translate to measures of the rare variant density more commonly used in rare variant association analyses, suggesting the need to adjust for ancestry in such analyses. The selection signal was high for AHNAK, HLA-A, RANBP2, and RGPD4, among others. RANBP2 and RGPD4 showed a marked difference in rare variant density and potential selection between the Luhya and the other populations. This may suggest that differences between populations should be considered when delimiting genomic regions according to functionality and that these differences can create potential for disease heterogeneity.

Perspectives on human population structure at the cusp of the sequencing era

Human groups show structured levels of genetic similarity as a consequence of factors such as geographical subdivision and genetic drift. Surveying this structure gives us a scientific perspective on human origins, sheds light on evolutionary processes that shape both human adaptation and disease, and is integral to effectively carrying out the mission of global medical genetics and personalized medicine. Surveys of population structure have been ongoing for decades, but in the past three years, single-nucleotide-polymorphism (SNP) array technology has provided unprecedented detail on human population structure at global and regional scales. These studies have confirmed well-known relationships between distantly related populations and uncovered previously unresolvable relationships among closely related human groups. SNPs represent the first dense genome-wide markers, and as such, their analysis has raised many challenges and insights relevant to the study of population genetics with whole-genome sequences. Here we draw on the lessons from these studies to anticipate the directions that will be most fruitful to pursue during the emerging whole-genome sequencing era.

Deciphering the genetic basis of animal domestication

Genomic technologies for livestock and companion animal species have revolutionized the study of animal domestication, allowing an increasingly detailed description of the genetic changes accompanying domestication and breed development. This review describes important recent results derived from the application of population and quantitative genetic approaches to the study of genetic changes in the major domesticated species. These include findings of regions of the genome that show between-breed differentiation, evidence of selective sweeps within individual genomes and signatures of demographic events. Particular attention is focused on the study of the genetics of behavioural traits and the implications for domestication. Despite the operation of severe bottlenecks, high levels of inbreeding and intensive selection during the history of domestication, most domestic animal species are genetically diverse. Possible explanations for this phenomenon are discussed. The major insights from the surveyed studies are highlighted and directions for future study are suggested.

Evaluating SNP ascertainment bias and its impact on population assignment in Atlantic cod, Gadus morhua

The increasing use of single nucleotide polymorphisms (SNPs) in studies of nonmodel organisms accentuates the need to evaluate the influence of ascertainment bias on accurate ecological or evolutionary inference. Using a panel of 1641 expressed sequence tag-derived SNPs developed for northwest Atlantic cod (Gadus morhua), we examined the influence of ascertainment bias and its potential impact on assignment of individuals to populations ranging widely in origin. We hypothesized that reductions in assignment success would be associated with lower diversity in geographical regions outside the location of ascertainment. Individuals were genotyped from 13 locations spanning much of the contemporary range of Atlantic cod. Diversity, measured as average sample heterozygosity and number of polymorphic loci, declined (c. 30%) from the western (H(e) = 0.36) to eastern (H(e) = 0.25) Atlantic, consistent with a signal of ascertainment bias. Assignment success was examined separately for pools of loci representing differing degrees of reductions in diversity. SNPs displaying the largest declines in diversity produced the most accurate assignment in the ascertainment region (c. 83%) and the lowest levels of correct assignment outside the ascertainment region (c. 31%). Interestingly, several isolated locations showed no effect of assignment bias and consistently displayed 100% correct assignment. Contrary to expectations, estimates of accurate assignment range-wide using all loci displayed remarkable similarity despite reductions in diversity. Our results support the use of large SNP panels in assignment studies of high geneflow marine species. However, our evidence of significant reductions in assignment success using some pools of loci suggests that ascertainment bias may influence assignment results and should be evaluated in large-scale assignment studies.

Sequencing and analysis of an Irish human genome

Background

Recent studies generating complete human sequences from Asian, African and European subgroups have revealed population-specific variation and disease susceptibility loci. Here, choosing a DNA sample from a population of interest due to its relative geographical isolation and genetic impact on further populations, we extend the above studies through the generation of 11-fold coverage of the first Irish human genome sequence.

Results

Using sequence data from a branch of the European ancestral tree as yet unsequenced, we identify variants that may be specific to this population. Through comparisons with HapMap and previous genetic association studies, we identified novel disease-associated variants, including a novel nonsense variant putatively associated with inflammatory bowel disease. We describe a novel method for improving SNP calling accuracy at low genome coverage using haplotype information. This analysis has implications for future re-sequencing studies and validates the imputation of Irish haplotypes using data from the current Human Genome Diversity Cell Line Panel (HGDP-CEPH). Finally, we identify gene duplication events as constituting significant targets of recent positive selection in the human lineage.

Conclusions

Our findings show that there remains utility in generating whole genome sequences to illustrate both general principles and reveal specific instances of human biology. With increasing access to low cost sequencing we would predict that even armed with the resources of a small research group a number of similar initiatives geared towards answering specific biological questions will emerge.

Even small SNP clusters are non-randomly distributed: is this evidence of mutational non-independence?

Single nucleotide polymorphisms (SNPs) are distributed highly non-randomly in the human genome through a variety of processes from ascertainment biases (i.e. the preferential development of SNPs around interesting genes) to the action of mutation hotspots and natural selection. However, with more systematic SNP development, one might expect an increasing proportion of SNPs to be distributed more or less randomly. Here, I test this null hypothesis using stochastic simulations and compare this output with that of an alternative hypothesis that mutations are more likely to occur near existing SNPs, a possibility suggested both by molecular studies of meiotic mismatch repair in yeast and by data showing that SNPs cluster around heterozygous deletions. A purely Poisson process generates SNP clusters that differ from equivalent data from human chromosome 1 in both the frequency of different-sized clusters and the SNP density within each cluster, even for small clusters of just four or five SNPs, while clusters on the X chromosome differ from those on the autosomes. In contrast, modest levels of mutational non-independence generate a reasonable fit to the real data for both cluster frequency and density, and also exhibit the evolutionary transience noted for 'mutation hotspots'. Mutational non-independence therefore provides an interesting new hypothesis that appears capable of explaining the distribution of SNPs in the human genome.

Diversity and evolution of 11 innate immune genes in Bos taurus taurus and Bos taurus indicus cattle

The Toll-like receptor (TLR) and peptidoglycan recognition protein 1 (PGLYRP1) genes play key roles in the innate immune systems of mammals. While the TLRs recognize a variety of invading pathogens and induce innate immune responses, PGLYRP1 is directly microbicidal. We used custom allele-specific assays to genotype and validate 220 diallelic variants, including 54 nonsynonymous SNPs in 11 bovine innate immune genes (TLR1-TLR10, PGLYRP1) for 37 cattle breeds. Bayesian haplotype reconstructions and median joining networks revealed haplotype sharing between Bos taurus taurus and Bos taurus indicus breeds at every locus, and we were unable to differentiate between the specialized B. t. taurus beef and dairy breeds, despite an average polymorphism density of one locus per 219 bp. Ninety-nine tagSNPs and one tag insertion-deletion polymorphism were sufficient to predict 100% of the variation at all 11 innate immune loci in both subspecies and their hybrids, whereas 58 tagSNPs captured 100% of the variation at 172 loci in B. t. taurus. PolyPhen and SIFT analyses of nonsynonymous SNPs encoding amino acid replacements indicated that the majority of these substitutions were benign, but up to 31% were expected to potentially impact protein function. Several diversity-based tests provided support for strong purifying selection acting on TLR10 in B. t. taurus cattle. These results will broadly impact efforts related to bovine translational genomics.

Widespread genomic signatures of natural selection in hominid evolution

Selection acting on genomic functional elements can be detected by its indirect effects on population diversity at linked neutral sites. To illuminate the selective forces that shaped hominid evolution, we analyzed the genomic distributions of human polymorphisms and sequence differences among five primate species relative to the locations of conserved sequence features. Neutral sequence diversity in human and ancestral hominid populations is substantially reduced near such features, resulting in a surprisingly large genome average diversity reduction due to selection of 19-26% on the autosomes and 12-40% on the X chromosome. The overall trends are broadly consistent with "background selection" or hitchhiking in ancestral populations acting to remove deleterious variants. Average selection is much stronger on exonic (both protein-coding and untranslated) conserved features than non-exonic features. Long term selection, rather than complex speciation scenarios, explains the large intragenomic variation in human/chimpanzee divergence. Our analyses reveal a dominant role for selection in shaping genomic diversity and divergence patterns, clarify hominid evolution, and provide a baseline for investigating specific selective events.