Yogesh Paudel

Regions of Homozygosity in the Porcine Genome: Consequence of Demography and the Recombination Landscape

Inbreeding has long been recognized as a primary cause of fitness reduction in both wild and domesticated populations. Consanguineous matings cause inheritance of haplotypes that are identical by descent (IBD) and result in homozygous stretches along the genome of the offspring. Size and position of regions of homozygosity (ROHs) are expected to correlate with genomic features such as GC content and recombination rate, but also direction of selection. Thus, ROHs should be non-randomly distributed across the genome. Therefore, demographic history may not fully predict the effects of inbreeding. The porcine genome has a relatively heterogeneous distribution of recombination rate, making Sus scrofa an excellent model to study the influence of both recombination landscape and demography on genomic variation. This study utilizes next-generation sequencing data for the analysis of genomic ROH patterns, using a comparative sliding window approach. We present an in-depth study of genomic variation based on three different parameters: nucleotide diversity outside ROHs, the number of ROHs in the genome, and the average ROH size. We identified an abundance of ROHs in all genomes of multiple pigs from commercial breeds and wild populations from Eurasia. Size and number of ROHs are in agreement with known demography of the populations, with population bottlenecks highly increasing ROH occurrence. Nucleotide diversity outside ROHs is high in populations derived from a large ancient population, regardless of current population size. In addition, we show an unequal genomic ROH distribution, with strong correlations of ROH size and abundance with recombination rate and GC content. Global gene content does not correlate with ROH frequency, but some ROH hotspots do contain positive selected genes in commercial lines and wild populations. This study highlights the importance of the influence of demography and recombination on homozygosity in the genome to understand the effects of inbreeding.

Genome sequencing reveals fine scale diversification and reticulation history during speciation in Sus

BackgroundElucidating the process of speciation requires an in-depth understanding of the evolutionary history of the species in question. Studies that rely upon a limited number of genetic loci do not always reveal actual evolutionary history, and often confuse inferences related to phylogeny and speciation. Whole-genome data, however, can overcome this issue by providing a nearly unbiased window into the patterns and processes of speciation. In order to reveal the complexity of the speciation process, we sequenced and analyzed the genomes of 10 wild pigs, representing morphologically or geographically well-defined species and subspecies of the genus Sus from insular and mainland Southeast Asia, and one African common warthog.ResultsOur data highlight the importance of past cyclical climatic fluctuations in facilitating the dispersal and isolation of populations, thus leading to the diversification of suids in one of the most species-rich regions of the world. Moreover, admixture analyses revealed extensive, intra- and inter-specific gene-flow that explains previous conflicting results obtained from a limited number of loci. We show that these multiple episodes of gene-flow resulted from both natural and human-mediated dispersal.ConclusionsOur results demonstrate the importance of past climatic fluctuations and human mediated translocations in driving and complicating the process of speciation in island Southeast Asia. This case study demonstrates that genomics is a powerful tool to decipher the evolutionary history of a genus, and reveals the complexity of the process of speciation.

Evolutionary dynamics of copy number variation in pig genomes in the context of adaptation and domestication.

BackgroundCopy number variable regions (CNVRs) can result in drastic phenotypic differences and may therefore be subject to selection during domestication. Studying copy number variation in relation to domestication is highly relevant in pigs because of their very rich natural and domestication history that resulted in many different phenotypes. To investigate the evolutionary dynamic of CNVRs, we applied read depth method on next generation sequence data from 16 individuals, comprising wild boars and domestic pigs from Europe and Asia.ResultsWe identified 3,118 CNVRs with an average size of 13 kilobases comprising a total of 39.2 megabases of the pig genome and 545 overlapping genes. Functional analyses revealed that CNVRs are enriched with genes related to sensory perception, neurological process and response to stimulus, suggesting their contribution to adaptation in the wild and behavioral changes during domestication. Variations of copy number (CN) of antimicrobial related genes suggest an ongoing process of evolution of these genes to combat food-borne pathogens. Likewise, some genes related to the omnivorous lifestyle of pigs, like genes involved in detoxification, were observed to be CN variable. A small portion of CNVRs was unique to domestic pigs and may have been selected during domestication. The majority of CNVRs, however, is shared between wild and domesticated individuals, indicating that domestication had minor effect on the overall diversity of CNVRs. Also, the excess of CNVRs in non-genic regions implies that a major part of these variations is likely to be (nearly) neutral. Comparison between different populations showed that larger populations have more CNVRs, highlighting that CNVRs are, like other genetic variation such as SNPs and microsatellites, reflecting demographic history rather than phenotypic diversity.ConclusionCNVRs in pigs are enriched for genes related to sensory perception, neurological process, and response to stimulus. The majority of CNVRs ascertained in domestic pigs are also variable in wild boars, suggesting that the domestication of the pig did not result in a change in CNVRs in domesticated pigs. The majority of variable regions were found to reflect demographic patterns rather than phenotypic.

Genomic analysis reveals selection for Asian genes in European pigs following human-mediated introgression

The independent domestication of local wild boar populations in Asia and Europe about 10,000 years ago led to distinct European and Asian pig breeds, each with very different phenotypic characteristics. During the Industrial Revolution, Chinese breeds were imported to Europe to improve commercial traits in European breeds. Here we demonstrate the presence of introgressed Asian haplotypes in European domestic pigs and selection signatures on some loci in these regions, using whole genome sequence data. The introgression signatures are widespread and the Asian haplotypes are rarely fixed. The Asian introgressed haplotypes are associated with regions harbouring genes involved in meat quality, development and fertility. We identify Asian-derived non-synonymous mutations in the AHR gene that associate with increased litter size in multiple European commercial lines. These findings demonstrate that increased fertility was an important breeding goal for early nineteenth century pig farmers, and that Asian variants of genes related to this trait were preferentially selected during the development of modern European pig breeds.

Dissecting structural and nucleotide genome-wide variation in inbred Iberian pigs

BackgroundIn contrast to international pig breeds, the Iberian breed has not been admixed with Asian germplasm. This makes it an important model to study both domestication and relevance of Asian genes in the pig. Besides, Iberian pigs exhibit high meat quality as well as appetite and propensity to obesity. Here we provide a genome wide analysis of nucleotide and structural diversity in a reduced representation library from a pool (n=9 sows) and shotgun genomic sequence from a single sow of the highly inbred Guadyerbas strain. In the pool, we applied newly developed tools to account for the peculiarities of these data.ResultsA total of 254,106 SNPs in the pool (79.6 Mb covered) and 643,783 in the Guadyerbas sow (1.47 Gb covered) were called. The nucleotide diversity (1.31x10-3 per bp in autosomes) is very similar to that reported in wild boar. A much lower than expected diversity in the X chromosome was confirmed (1.79x10-4 per bp in the individual and 5.83x10-4 per bp in the pool). A strong (0.70) correlation between recombination and variability was observed, but not with gene density or GC content. Multicopy regions affected about 4% of annotated pig genes in their entirety, and 2% of the genes partially. Genes within the lowest variability windows comprised interferon genes and, in chromosome X, genes involved in behavior like HTR2C or MCEP2. A modified Hudson-Kreitman-Aguadé test for pools also indicated an accelerated evolution in genes involved in behavior, as well as in spermatogenesis and in lipid metabolism.ConclusionsThis work illustrates the strength of current sequencing technologies to picture a comprehensive landscape of variability in livestock species, and to pinpoint regions containing genes potentially under selection. Among those genes, we report genes involved in behavior, including feeding behavior, and lipid metabolism. The pig X chromosome is an outlier in terms of nucleotide diversity, which suggests selective constraints. Our data further confirm the importance of structural variation in the species, including Iberian pigs, and allowed us to identify new paralogs for known gene families.

Untangling the hybrid nature of modern pig genomes: a mosaic derived from biogeographically distinct and highly divergent Sus scrofa populations

The merging of populations after an extended period of isolation and divergence is a common phenomenon, in natural settings as well as due to human interference. Individuals with such hybrid origins contain genomes that essentially form a mosaic of different histories and demographies. Pigs are an excellent model species to study hybridization because European and Asian wild boars diverged ~1.2 Mya, and pigs were domesticated independently in Europe and Asia. During the Industrial Revolution in England, pigs were imported from China to improve the local pigs. This study utilizes the latest genomics tools to identify the origin of haplotypes in European domesticated pigs that are descendant from Asian and European populations. Our results reveal fine‐scale haplotype structure representing different ancient demographic events, as well as a mosaic composition of those distinct histories due to recently introgressed haplotypes in the pig genome. As a consequence, nucleotide diversity in the genome of European domesticated pigs is higher when at least one haplotype of Asian origin is present, and haplotype length correlates negatively with recombination frequency and nucleotide diversity. Another consequence is that the inference of past effective population size is influenced by the background of the haplotypes in an individual, but we demonstrate that by careful sorting based on the origin of haplotypes, both distinct demographic histories can be reconstructed. Future detailed mapping of the genomic distribution of variation will enable a targeted approach to increase genetic diversity of captive and wild populations, thus facilitating conservation efforts in the near future.

Copy number variation in the speciation of pigs: a possible prominent role for olfactory receptors

BackgroundUnraveling the genetic mechanisms associated with reduced gene flow between genetically differentiated populations is key to understand speciation. Different types of structural variations (SVs) have been found as a source of genetic diversity in a wide range of species. Previous studies provided detailed knowledge on the potential evolutionary role of SVs, especially copy number variations (CNVs), between well diverged species of e.g. primates. However, our understanding of their significance during ongoing speciation processes is limited due to the lack of CNV data from closely related species. The genus Sus (pig and its close relatives) which started to diverge ~4 Mya presents an excellent model for studying the role of CNVs during ongoing speciation.ResultsIn this study, we identified 1408 CNV regions (CNVRs) across the genus Sus. These CNVRs encompass 624 genes and were found to evolve ~2.5 times faster than single nucleotide polymorphisms (SNPs). The majority of these copy number variable genes are olfactory receptors (ORs) known to play a prominent role in food foraging and mate recognition in Sus. Phylogenetic analyses, including novel Bayesian analysis, based on CNVRs that overlap ORs retain the well-accepted topology of the genus Sus whereas CNVRs overlapping genes other than ORs show evidence for random drift and/or admixture.ConclusionWe hypothesize that inter-specific variation in copy number of ORs provided the means for rapid adaptation to different environments during the diversification of the genus Sus in the Pliocene. Furthermore, these regions might have acted as barriers preventing massive gene flow between these species during the multiple hybridization events that took place later in the Pleistocene suggesting a possible prominent role of ORs in the ongoing Sus speciation.

Hybrid origin of European commercial pigs examined by an in-depth haplotype analysis on chromosome 1

Although all farm animals have an original source of domestication, a large variety of modern breeds exist that are phenotypically highly distinct from the ancestral wild population. This phenomenon can be the result of artificial selection or gene flow from other sources into the domesticated population. The Eurasian wild boar (Sus scrofa) has been domesticated at least twice in two geographically distinct regions during the Neolithic revolution when hunting shifted to farming. Prior to the establishment of the commercial European pig breeds we know today, some 200 years ago Chinese pigs were imported into Europe to improve local European pigs. Commercial European domesticated pigs are genetically more diverse than European wild boars, although historically the latter represents the source population for domestication. In this study we examine the cause of the higher diversity within the genomes of European commercial pigs compared to their wild ancestors by testing two different hypotheses. In the first hypothesis we consider that European commercial pigs are a mix of different European wild populations as a result of movement throughout Europe, hereby acquiring haplotypes from all over the European continent. As an alternative hypothesis, we examine whether the introgression of Asian haplotypes into European breeds during the Industrial Revolution caused the observed increase in diversity. By using re-sequence data for chromosome 1 of 136 pigs and wild boars, we show that an Asian introgression of about 20% into the genome of European commercial pigs explains the majority of the increase in genetic diversity. These findings confirm that the Asian hybridization, that was used to improve production traits of local breeds, left its signature in the genome of the commercial pigs we know today.

Evolution of Tibetan wild boars

To the Editor: The analysis presented by Li et al.1 in their report of the genome sequence of the Tibetan wild boar provides interesting insights into the genetic architecture of high altitude adaptation in this species. However, despite the large volume of novel data, we found shortcomings in several parts of the study, suggesting that some specific findings presented by Li et al. result from over-interpretation. In addition, several of their conclusions contradict those reported in previous analyses2–5. More specifically, the authors infer that Tibetan wild boars and Duroc breeds (S. scrofa Ssc10.2 reference genome) diverged during the Miocene, ~6.8 million years ago (Mya). This estimated date is nearly 10 times more ancient than the recently reported split between Asian and European wild boar (2-0.8Mya) 2,4. In addition, previous studies2,3 estimated the divergence time between S. scrofa and other Sus species from Island Southeast Asia (outgroups in Figure 2b/e in ref 1) to be 5.3-1.3 Mya. Li et al.1 do not describe the details of the molecular clock analysis, other than stating that PAML (MCMCTREE)6 was used with three molecular clock based calibrations (as opposed to fossil calibrations), and they neither specified which nodes were calibrated nor did they include the uncertainties of these calibrations in their age priors. Moreover, we believe that the tree used for the molecular clock analysis is too sparsely sampled to be informative for the Duroc-Tibetan split time. Indeed, different mutation rates are expected for the deep internal branches, separating mammalian orders, compared to the short branches separating the two sub-species of S. scrofa2,4,7. Hence, estimating a subspecific split using rates estimated from the divergence of mammalian orders is nearly certain to bias the estimate leading to an incorrect conclusion. We therefore believe that this analysis is likely to be influenced both by prior age misspecification and biased taxon sampling, resulting in a gross overestimation of the divergence time. Furthermore, the authors do not take into account the suid paleontological literature that provides specific contradictory examples to their conclusions (Figure 1a) and would have provided useful calibrations (see Additional File 6 in ref 2). To illustrate our concerns we constructed a phylogenetic tree using data from a Tibetan wild boar1 together with seven other Sus samples (Figure 1a) that were used in two previous studies2,4 and the study of Li et al.1 (Supplementary Note). We further annotated the tree with well known fossils, and our own time estimates2,3,8 (Figure 1a). Our results demonstrate that Tibetan wild boar clusters together with Chinese wild boar (also suggested by the Li et. al. ancestry and phylogenetic analyses). Based on our molecular clock analyses2,3, we conclude that Tibetan and European wild boars are not different species, but instead are closely related sub-species that diverged during the Pleistocene. In addition, we show that the evolutionary time scale proposed by Li et al.1 for the genus Sus implies a significantly older speciation timeframe contradicting the fossil record (Figure 1a). Furthermore, according to our branch length estimates (Supplementary Methods), a divergence time for European and Asian wild boars of 6.8 Mya1 (confidence interval 12.9-2.4), would imply that African and Eurasian Suinae diverged roughly 26 Mya (confidence interval 50-13 Mya), an estimate that bears no correspondence with the fossil time-frame for Suinae8. The erroneous time inference presented by Li et al. contributed to their generally implausible results. Figure 1 Evolutionary history of Sus species Another point of concern is the results of their demographic analysis9, pictured in Figure 2e in Li et al.1 which highlights the low coverage of the dataset and the shortcomings of a next-generation-sequence (NGS) based genome assembly. The authors present the demographic history as inferred both from boars re-sequenced and aligned to their assembly (green and pink lines in Figure 2e in ref 1) as well as previously sequenced boar genomes and aligned to the high quality draft reference genome4 (Ssc10.2, blue and black lines Figure 2e in ref 1). Surprisingly, the results for Chinese wild boar aligned to Ssc10.2 and to the de novo assembly significantly disagree (e.g. South China with Southwest China in Figure 2e in ref 1.). This lack of correspondence is worrying since these individuals have similar ancestry and are very closely related (see Figure 2b in ref 1; Figure 1a). The authors do not address this discrepancy but instead draw the conclusion, “to our knowledge this is the first study supporting the refuge theory on the basis of demographic history revealed by genome-wide analysis”. We believe that this result does not reflect a realistic population size for wild boar in Tibet during the Pleistocene, but instead illustrates the lack of resolution of de novo assembled genomes for demographic estimations in combination with underestimation of true heterozygosity due to low coverage re-sequencing data (5x coverage for individuals re-sequenced in this study versus 10x coverage for previously published re-sequenced individuals). To support our claims, we re-analyzed Li et al.’s data by aligning short-read sequences from a single Tibetan wild boar that was used for de novo assembly (over 10x coverage; Supplementary Methods) to the Ssc10.2 reference genome and conducted a similar PSMC analysis to the one carried out by Li et al.1 Our results demonstrate that Tibetan and South Chinese wild boar have similar demographic histories (Figure 1b). In particular, we show that Tibetan wild boar underwent population size fluctuations during the Pleistocene, contrary to the conclusions of Li et al. This analysis shows that the claim that Tibetan wild boar experienced no demographic fluctuations due to the presence of refugia in Tibet is incorrect. In the light of the Assemblathon 2.010 we believe that it is important not to over-interpret data from NGS short-read de novo assemblies, especially when comparing these to an assembly built from Sanger reads combined with a high-resolution linkage map. Here we show that the over-confidence of the authors in their de novo assembly and divergence time estimates misled their interpretation of the evolutionary history of Tibetan wild boars. Furthermore, we believe that some results presented in the study by Li. et. al.1, in particular large scale gene family expansion and/or contraction since the European-Tibetan wild-boar split are dubious. The interpretation of these results, as being the result of a genuine biological signal rather than assembly artifact, may have been misled by the gross over-estimation of evolutionary time frame of S. scrofa. We suggest that the experimental design of studies describing re-sequencing of closely related species or sub-species needs to be different from the analysis conducted on newly sequenced genomes. For example, a more relevant analysis would have been to compare the “wild Sus species” and Warthog to the genome of the Tibetan wild boar rather than comparing within S. scrofa evolutionary changes with evolutionary processes that occurred at the scale of mammalian evolution. With the power of multiple complete genomes comes the responsibility to interpret them in light of both the potential pitfalls of NGS and the published genomic and paleontological evidence.

SV-AUTOPILOT: optimized, automated construction of structural variation discovery and benchmarking pipelines

BackgroundMany tools exist to predict structural variants (SVs), utilizing a variety of algorithms. However, they have largely been developed and tested on human germline or somatic (e.g. cancer) variation. It seems appropriate to exploit this wealth of technology available for humans also for other species. Objectives of this work included:a)Creating an automated, standardized pipeline for SV prediction.b)Identifying the best tool(s) for SV prediction through benchmarking.c)Providing a statistically sound method for merging SV calls.ResultsThe SV-AUTOPILOT meta-tool platform is an automated pipeline for standardization of SV prediction and SV tool development in paired-end next-generation sequencing (NGS) analysis. SV-AUTOPILOT comes in the form of a virtual machine, which includes all datasets, tools and algorithms presented here. The virtual machine easily allows one to add, replace and update genomes, SV callers and post-processing routines and therefore provides an easy, out-of-the-box environment for complex SV discovery tasks. SV-AUTOPILOT was used to make a direct comparison between 7 popular SV tools on the Arabidopsis thaliana genome using the Landsberg (Ler) ecotype as a standardized dataset. Recall and precision measurements suggest that Pindel and Clever were the most adaptable to this dataset across all size ranges while Delly performed well for SVs larger than 250 nucleotides. A novel, statistically-sound merging process, which can control the false discovery rate, reduced the false positive rate on the Arabidopsis benchmark dataset used here by >60%.ConclusionSV-AUTOPILOT provides a meta-tool platform for future SV tool development and the benchmarking of tools on other genomes using a standardized pipeline. It optimizes detection of SVs in non-human genomes using statistically robust merging. The benchmarking in this study has demonstrated the power of 7 different SV tools for analyzing different size classes and types of structural variants. The optional merge feature enriches the call set and reduces false positives providing added benefit to researchers planning to validate SVs. SV-AUTOPILOT is a powerful, new meta-tool for biologists as well as SV tool developers.