SNP calling, genotype calling, and sample allele frequency estimation from New-Generation Sequencing data

BATCAVE: calling somatic mutations with a tumor- and site-specific prior

Detecting somatic mutations withins tumors is key to understanding treatment resistance, patient prognosis and tumor evolution. Mutations at low allelic frequency, those present in only a small portion of tumor cells, are particularly difficult to detect. Many algorithms have been developed to detect such mutations, but none models a key aspect of tumor biology. Namely, every tumor has its own profile of mutation types that it tends to generate. We present BATCAVE (Bayesian Analysis Tools for Context-Aware Variant Evaluation), an algorithm that first learns the individual tumor mutational profile and mutation rate then uses them in a prior for evaluating potential mutations. We also present an R implementation of the algorithm, built on the popular caller MuTect. Using simulations, we show that adding the BATCAVE algorithm to MuTect improves variant detection. It also improves the calibration of posterior probabilities, enabling more principled tradeoff between precision and recall. We also show that BATCAVE performs well on real data. Our implementation is computationally inexpensive and straightforward to incorporate into existing MuTect pipelines. More broadly, the algorithm can be added to other variant callers, and it can be extended to include additional biological features that affect mutation generation.

Contemporary Demographic Reconstruction Methods Are Robust to Genome Assembly Quality: A Case Study in Tasmanian Devils

Reconstructing species’ demographic histories is a central focus of molecular ecology and evolution. Recently, an expanding suite of methods leveraging either the sequentially Markovian coalescent (SMC) or the site-frequency spectrum has been developed to reconstruct population size histories from genomic sequence data. However, few studies have investigated the robustness of these methods to genome assemblies of varying quality. In this study, we first present an improved genome assembly for the Tasmanian devil using the Chicago library method. Compared with the original reference genome, our new assembly reduces the number of scaffolds (from 35,975 to 10,010) and increases the scaffold N90 (from 0.101 to 2.164 Mb). Second, we assess the performance of four contemporary genomic methods for inferring population size history (PSMC, MSMC, SMC++, Stairway Plot), using the two devil genome assemblies as well as simulated, artificially fragmented genomes that approximate the hypothesized demographic history of Tasmanian devils. We demonstrate that each method is robust to assembly quality, producing similar estimates of Ne when simulated genomes were fragmented into up to 5,000 scaffolds. Overall, methods reliant on the SMC are most reliable between ∼300 generations before present (gbp) and 100 kgbp, whereas methods exclusively reliant on the site-frequency spectrum are most reliable between the present and 30 gbp. Our results suggest that when used in concert, genomic methods for reconstructing species’ effective population size histories 1) can be applied to nonmodel organisms without highly contiguous reference genomes, and 2) are capable of detecting independently documented effects of historical geological events.

On the Extent of Linkage Disequilibrium in the Genome of Farm Animals

Given the importance of linkage disequilibrium (LD) in gene mapping and evolutionary inferences, I characterize in this review the pattern of LD and discuss the influence of human intervention during domestication, breed establishment, and subsequent genetic improvement on shaping the genome of livestock species. To this end, I summarize data on the profile of LD based on array genotypes vs. sequencing data in cattle and chicken, two major livestock species, and compare to the human case. This comparison provides insights into the real dimension of the pairwise allelic correlation and haplo-block structuring. The dependency of LD on allelic frequency is pictured and a recently introduced metric for moderating it is outlined. In the context of the contact farm animals had with human, the impact of genetic forces including admixture, mutation, recombination rate, selection, and effective population size on LD is discussed. The review further highlights the interplay of LD with runs of homozygosity and concludes with the operational implications of the widely used association and selection mapping studies in relation to LD.

Landscape drivers of genomic diversity and divergence in woodland Eucalyptus

Spatial genetic patterns are influenced by numerous factors, and they can vary even among coexisting, closely related species due to differences in dispersal and selection. Eucalyptus (L'Héritier 1789; the "eucalypts") are foundation tree species that provide essential habitat and modulate ecosystem services throughout Australia. Here we present a study of landscape genomic variation in two woodland eucalypt species, using whole-genome sequencing of 388 individuals of Eucalyptus albens and Eucalyptus sideroxylon. We found exceptionally high genetic diversity (π ≈ 0.05) and low genome-wide, interspecific differentiation (FST  = 0.15) and intraspecific differentiation between localities (FST  ≈ 0.01-0.02). We found no support for strong, discrete population structure, but found substantial support for isolation by geographic distance (IBD) in both species. Using generalized dissimilarity modelling, we identified additional isolation by environment (IBE). Eucalyptus albens showed moderate IBD, and environmental variables have a small but significant amount of additional predictive power (i.e. IBE). Eucalyptus sideroxylon showed much stronger IBD and moderate IBE. These results highlight the vast adaptive potential of these species and set the stage for testing evolutionary hypotheses of interspecific adaptive differentiation across environments.

Allele frequency-free inference of close familial relationships from genotypes or low-depth sequencing data

Knowledge of how individuals are related is important in many areas of research, and numerous methods for inferring pairwise relatedness from genetic data have been developed. However, the majority of these methods were not developed for situations where data are limited. Specifically, most methods rely on the availability of population allele frequencies, the relative genomic position of variants and accurate genotype data. But in studies of non‐model organisms or ancient samples, such data are not always available. Motivated by this, we present a new method for pairwise relatedness inference, which requires neither allele frequency information nor information on genomic position. Furthermore, it can be applied not only to accurate genotype data but also to low‐depth sequencing data from which genotypes cannot be accurately called. We evaluate it using data from a range of human populations and show that it can be used to infer close familial relationships with a similar accuracy as a widely used method that relies on population allele frequencies. Additionally, we show that our method is robust to SNP ascertainment and applicable to low‐depth sequencing data generated using different strategies, including resequencing and RADseq, which is important for application to a diverse range of populations and species.

Host plant-related genomic differentiation in the European cherry fruit fly, Rhagoletis cerasi

Elucidating the mechanisms and conditions facilitating the formation of biodiversity are central topics in evolutionary biology. A growing number of studies imply that divergent ecological selection may often play a critical role in speciation by counteracting the homogenising effects of gene flow. Several examples involve phytophagous insects, where divergent selection pressures associated with host plant shifts may generate reproductive isolation, promoting speciation. Here, we use ddRADseq to assess the population structure and to test for host‐related genomic differentiation in the European cherry fruit fly, Rhagoletis cerasi (L., 1758) (Diptera: Tephritidae). This tephritid is distributed throughout Europe and western Asia, and has adapted to two different genera of host plants, Prunus spp. (cherries) and Lonicera spp. (honeysuckle). Our data imply that geographic distance and geomorphic barriers serve as the primary factors shaping genetic population structure across the species range. Locally, however, flies genetically cluster according to host plant, with consistent allele frequency differences displayed by a subset of loci between Prunus and Lonicera flies across four sites surveyed in Germany and Norway. These 17 loci display significantly higher F_ST values between host plants than others. They also showed high levels of linkage disequilibrium within and between Prunus and Lonicera flies, supporting host‐related selection and reduced gene flow. Our findings support the existence of sympatric host races in R. cerasi embedded within broader patterns of geographic variation in the fly, similar to the related apple maggot, Rhagoletis pomonella, in North America.

GPU empowered pipelines for calculating genome-wide kinship matrices with ultra-high dimensional genetic variants and facilitating 1D and 2D GWAS

Genome-wide association study (GWAS) is a powerful approach that has revolutionized the field of quantitative genetics. Two-dimensional GWAS that accounts for epistatic genetic effects needs to consider the effects of marker pairs, thus quadratic genetic variants, compared to one-dimensional GWAS that accounts for individual genetic variants. Calculating genome-wide kinship matrices in GWAS that account for relationships among individuals represented by ultra-high dimensional genetic variants is computationally challenging. Fortunately, kinship matrix calculation involves pure matrix operations and the algorithms can be parallelized, particular on graphics processing unit (GPU)-empowered high-performance computing (HPC) architectures. We have devised a new method and two pipelines: KMC1D and KMC2D for kinship matrix calculation with high-dimensional genetic variants, respectively, facilitating 1D and 2D GWAS analyses. We first divide the ultra-high-dimensional markers and marker pairs into successive blocks. We then calculate the kinship matrix for each block and merge together the block-wise kinship matrices to form the genome-wide kinship matrix. All the matrix operations have been parallelized using GPU kernels on our NVIDIA GPU-accelerated server platform. The performance analyses show that the calculation speed of KMC1D and KMC2D can be accelerated by 100–400 times over the conventional CPU-based computing.

Impact of demography on linked selection in two outcrossing Brassicaceae species

Genetic diversity is shaped by mutation, genetic drift, gene flow, recombination, and selection. The dynamics and interactions of these forces shape genetic diversity across different parts of the genome, between populations and species. Here, we have studied the effects of linked selection on nucleotide diversity in outcrossing populations of two Brassicaceae species, Arabidopsis lyrata and Capsella grandiflora, with contrasting demographic history. In agreement with previous estimates, we found evidence for a modest population size expansion thousands of generations ago, as well as efficient purifying selection in C. grandiflora. In contrast, the A. lyrata population exhibited evidence for very recent strong population size decline and weaker efficacy of purifying selection. Using multiple regression analyses with recombination rate and other genomic covariates as explanatory variables, we can explain 47% of the variance in neutral diversity in the C. grandiflora population, while in the A. lyrata population, only 11% of the variance was explained by the model. Recombination rate had a significant positive effect on neutral diversity in both species, suggesting that selection at linked sites has an effect on patterns of neutral variation. In line with this finding, we also found reduced neutral diversity in the vicinity of genes in the C. grandiflora population. However, in A. lyrata no such reduction in diversity was evident, a finding that is consistent with expectations of the impact of a recent bottleneck on patterns of neutral diversity near genes. This study thus empirically demonstrates how differences in demographic history modulate the impact of selection at linked sites in natural populations.

Testing for Hardy-Weinberg equilibrium in structured populations using genotype or low-depth next generation sequencing data

Testing for deviations from Hardy-Weinberg equilibrium (HWE) is a common practice for quality control in genetic studies. Variable sites violating HWE may be identified as technical errors in the sequencing or genotyping process, or they may be of particular evolutionary interest. Large-scale genetic studies based on next-generation sequencing (NGS) methods have become more prevalent as cost is decreasing but these methods are still associated with statistical uncertainty. The large-scale studies usually consist of samples from diverse ancestries that make the existence of some degree of population structure almost inevitable. Precautions are therefore needed when analysing these data set, as population structure causes deviations from HWE. Here we propose a method that takes population structure into account in the testing for HWE, such that other factors causing deviations from HWE can be detected. We show the effectiveness of PCAngsd in low-depth NGS data, as well as in genotype data, for both simulated and real data set, where the use of genotype likelihoods enables us to model the uncertainty.

Phenotypic sexual dimorphism is associated with genomic signatures of resolved sexual conflict

Intralocus sexual conflict, where an allele benefits one sex at the expense of the other, has an important role in shaping genetic diversity of populations through balancing selection. However, the potential for mating systems to exert balancing selection through sexual conflict on the genome remains unclear. Furthermore, the nature and potential for resolution of sexual conflict across the genome has been hotly debated. To address this, we analysed de novo transcriptomes from six avian species, chosen to reflect the full range of sexual dimorphism and mating systems. Our analyses combine expression and population genomic statistics across reproductive and somatic tissue, with measures of sperm competition and promiscuity. Our results reveal that balancing selection is weakest in the gonad, consistent with the resolution of sexual conflict and evolutionary theory that phenotypic sex differences are associated with lower levels of ongoing conflict. We also demonstrate a clear link between variation in sexual conflict and levels of genetic variation across phylogenetic space in a comparative framework. Our observations suggest that this conflict is short-lived, and is resolved via the decoupling of male and female gene expression patterns, with important implications for the role of sexual selection in adaptive potential and role of dimorphism in facilitating sex-specific fitness optima.

Consequences of breed formation on patterns of genomic diversity and differentiation: the case of highly diverse peripheral Iberian cattle

BACKGROUND

Iberian primitive breeds exhibit a remarkable phenotypic diversity over a very limited geographical space. While genomic data are accumulating for most commercial cattle, it is still lacking for these primitive breeds. Whole genome data is key to understand the consequences of historic breed formation and the putative role of earlier admixture events in the observed diversity patterns.

RESULTS

We sequenced 48 genomes belonging to eight Iberian native breeds and found that the individual breeds are genetically very distinct with FST values ranging from 4 to 16% and have levels of nucleotide diversity similar or larger than those of their European counterparts, namely Jersey and Holstein. All eight breeds display significant gene flow or admixture from African taurine cattle and include mtDNA and Y-chromosome haplotypes from multiple origins. Furthermore, we detected a very low differentiation of chromosome X relative to autosomes within all analyzed taurine breeds, potentially reflecting male-biased gene flow.

CONCLUSIONS

Our results show that an overall complex history of admixture resulted in unexpectedly high levels of genomic diversity for breeds with seemingly limited geographic ranges that are distantly located from the main domestication center for taurine cattle in the Near East. This is likely to result from a combination of trading traditions and breeding practices in Mediterranean countries. We also found that the levels of differentiation of autosomes vs sex chromosomes across all studied taurine and indicine breeds are likely to have been affected by widespread breeding practices associated with male-biased gene flow.

Environmental drivers and genomic architecture of trait differentiation in fire-adapted Banksia attenuata ecotypes

Trait divergence between populations is considered an adaptive response to different environments, but to what extent this response is accompanied by genetic differentiation is less clear since it may be phenotypic plasticity. In this study, we analyzed phenotypic variation between two Banksia attenuata growth forms, lignotuberous (shrub) and epicormic resprouting (tree), in fire-prone environments to identify the environmental factors that have driven this phenotypic divergence. We linked genotype with phenotype and traced candidate genes using differential gene expression analysis. Fire intervals determined the phenotypic divergence between growth forms in B. attenuata. A genome-wide association study identified 69 single nucleotide polymorphisms, putatively associated with growth form, whereas no growth form- or phenotype-specific genotypes were identified. Genomic differentiation between the two growth forms was low (F_st  = 0.024). Differential gene expression analysis identified 37 genes/transcripts that were differentially expressed in the two growth forms. A small heat-shock protein gene, associated with lignotuber presence, was differentially expressed in the two forms. We conclude that different fire regimes induce phenotypic polymorphism in B. attenuata, whereas phenotypic trait divergence involves the differential expression of a small fraction of genes that interact strongly with the disturbance regime. Thus, phenotypic plasticity among resprouters is the general strategy for surviving varying fire regimes.

Signatures of Selection on Standing Genetic Variation Underlie Athletic and Navigational Performance in Racing Pigeons

Racing pigeons have been selectively bred to find their way home quickly over what are often extremely long distances. This breed is of substantial commercial value and is also an excellent avian model to gain empirical insights into the evolution of traits associated with flying performance and spatial orientation. Here, we investigate the molecular basis of the superior athletic and navigational capabilities of racing pigeons using whole-genome and RNA sequencing data. We inferred multiple signatures of positive selection distributed across the genome of racing pigeons. The strongest signature overlapped the CASK gene, a gene implicated in the formation of neuromuscular junctions. However, no diagnostic alleles were found between racing pigeons and other breeds, and only a small proportion of highly differentiated variants were exclusively detected in racing pigeons. We can thus conclude that very few individual genetic changes, if any, are either strictly necessary or sufficient for superior athletics and navigation. Gene expression analysis between racing and nonracing breeds revealed modest differences in muscle (213) and brain (29). These transcripts, however, showed only slightly elevated levels of genetic differentiation between the two groups, suggesting that most differential expression is not causative but likely a consequence of alterations in regulatory networks. Our results show that the unique suite of traits that enable fast flight, long endurance, and accurate navigation in racing pigeons, do not result from few loci acting as master switches but likely from a polygenic architecture that leveraged standing genetic variation available at the onset of the breed formation.

Out of Southern East Asia of the Brown Rat Revealed by Large-Scale Genome Sequencing

The geographic origin and migration of the brown rat (Rattus norvegicus) remain subjects of considerable debate. In this study, we sequenced whole genomes of 110 wild brown rats with a diverse world-wide representation. We reveal that brown rats migrated out of southern East Asia, rather than northern Asia as formerly suggested, into the Middle East and then to Europe and Africa, thousands of years ago. Comparison of genomes from different geographical populations reveals that many genes involved in the immune system experienced positive selection in the wild brown rat.

A high-throughput SNP discovery strategy for RNA-seq data

Background

Single nucleotide polymorphisms (SNP) have been applied as important molecular markers in genetics and breeding studies. The rapid advance of next generation sequencing (NGS) provides a high-throughput means of SNP discovery. However, SNP development is limited by the availability of reliable SNP discovery methods. Especially, the optimum assembler and SNP caller for accurate SNP prediction from next generation sequencing data are not known.

Results

Herein we performed SNP prediction based on RNA-seq data of peach and mandarin peel tissue under a comprehensive comparison of two paired-end read lengths (125 bp and 150 bp), five assemblers (Trinity, IDBA, oases, SOAPdenovo, Trans-abyss) and two SNP callers (GATK and GBS). The predicted SNPs were compared with the authentic SNPs identified via PCR amplification followed by gene cloning and sequencing procedures. A total of 40 and 240 authentic SNPs were presented in five anthocyanin biosynthesis related genes in peach and in nine carotenogenic genes in mandarin. Putative SNPs predicted from the same RNA-seq data with different strategies led to quite divergent results. The rate of false positive SNPs was significantly lower when the paired-end read length was 150 bp compared with 125 bp. Trinity was superior to the other four assemblers and GATK was substantially superior to GBS due to a low rate of missing authentic SNPs. The combination of assembler Trinity, SNP caller GATK, and the paired-end read length 150 bp had the best performance in SNP discovery with 100% accuracy both in peach and in mandarin cases. This strategy was applied to the characterization of SNPs in peach and mandarin transcriptomes.

Conclusions

Through comparison of authentic SNPs obtained by PCR cloning strategy and putative SNPs predicted from different combinations of five assemblers, two SNP callers, and two paired-end read lengths, we provided a reliable and efficient strategy, Trinity-GATK with 150 bp paired-end read length, for SNP discovery from RNA-seq data. This strategy discovered SNP at 100% accuracy in peach and mandarin cases and might be applicable to a wide range of plants and other organisms.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5533-4) contains supplementary material, which is available to authorized users.

Unexpected population fragmentation in an endangered seabird: the case of the Peruvian diving-petrel

In less than one century, the once-abundant Peruvian diving petrel has become the first endangered seabird of the Humboldt Current System (HCS). This small endemic petrel of the South American Pacific coast is now an important indicator of ongoing habitat loss and of the success of local conservation policies in the HCS - an ecoregion designated as a priority for the conservation of global biodiversity. Yet so far, poorly understood life history traits such as philopatry or dispersal ability may strongly influence the species' response to ecosystem changes, but also our capacity to assess and interpret this response. To address this question, we explore the range-wide population structure of the Peruvian diving petrel, and show that this small seabird exhibits extreme philopatric behavior at the island level. Mitochondrial DNA sequences and genome-wide SNP data reveal significant isolation and low migration at very short distances, and provide strong evidence for questioning the alleged recovery in the Peruvian and Chilean populations of this species. Importantly, the full demographic independence between colonies makes local population rescue through migration unlikely. As a consequence, the Peruvian diving petrel appears to be particularly vulnerable to ongoing anthropogenic pressure. By excluding immigration as a major factor of demographic recovery, our results highlight the unambiguously positive impact of local conservation measures on breeding populations; yet at the same time they also cast doubt on alleged range-wide positive population trends. Overall, the protection of independent breeding colonies, and not only of the species as a whole, remains a major element in the conservation strategy for endemic seabirds. Finally, we underline the importance of considering the philopatric behavior and demographic independence of breeding populations, even at very fine spatial scales, in spatial planning for marine coastal areas.

Cost-effective assembly of the African wild dog (Lycaon pictus) genome using linked reads

Background

A high-quality reference genome assembly is a valuable tool for the study of non-model organisms. Genomic techniques can provide important insights about past population sizes and local adaptation and can aid in the development of breeding management plans. This information is important for fields such as conservation genetics, where endangered species require critical and immediate attention. However, funding for genomic-based methods can be sparse for conservation projects, as costs for general species management can consume budgets.

Findings

Here, we report the generation of high-quality reference genomes for the African wild dog (Lycaon pictus) at a low cost (<$3000), thereby facilitating future studies of this endangered canid. We generated assemblies for three individuals using the linked-read 10x Genomics Chromium system. The most continuous assembly had a scaffold and contig N50 of 21 Mb and 83 Kb, respectively, and completely reconstructed 95% of a set of conserved mammalian genes. Additionally, we estimate the heterozygosity and demographic history of African wild dogs, revealing that although they have historically low effective population sizes, heterozygosity remains high.

Conclusions

We show that 10x Genomics Chromium data can be used to effectively generate high-quality genomes from Illumina short-read data of intermediate coverage (∼25x–50x). Interestingly, the wild dog shows higher heterozygosity than other species of conservation concern, possibly due to its behavioral ecology. The availability of reference genomes for non-model organisms will facilitate better genetic monitoring of threatened species such as the African wild dog and help conservationists to better understand the ecology and adaptability of those species in a changing environment.

The genetic legacy of 50 years of desert bighorn sheep translocations

Conservation biologists have increasingly used translocations to mitigate population declines and restore locally extirpated populations. Genetic data can guide the selection of source populations for translocations and help evaluate restoration success. Bighorn sheep (Ovis canadensis) are a managed big game species that suffered widespread population extirpations across western North America throughout the early 1900s. Subsequent translocation programs have successfully re-established many formally extirpated bighorn herds, but most of these programs pre-date genetically informed management practices. The state of Nevada presents a particularly well-documented case of decline followed by restoration of extirpated herds. Desert bighorn sheep (O. c. nelsoni) populations declined to less than 3,000 individuals restricted to remnant herds in the Mojave Desert and a few locations in the Great Basin Desert. Beginning in 1968, the Nevada Department of Wildlife translocated ~2,000 individuals from remnant populations to restore previously extirpated areas, possibly establishing herds with mixed ancestries. Here, we examined genetic diversity and structure among remnant herds and the genetic consequences of translocation from these herds using a genotyping-by-sequencing approach to genotype 17,095 loci in 303 desert bighorn sheep. We found a signal of population genetic structure among remnant Mojave Desert populations, even across geographically proximate mountain ranges. Further, we found evidence of a genetically distinct, potential relict herd from a previously hypothesized Great Basin lineage of desert bighorn sheep. The genetic structure of source herds was clearly reflected in translocated populations. In most cases, herds retained genetic evidence of multiple translocation events and subsequent admixture when founded from multiple remnant source herds. Our results add to a growing literature on how population genomic data can be used to guide and monitor restoration programs.

Genomic Selection in Aquaculture: Application, Limitations and Opportunities With Special Reference to Marine Shrimp and Pearl Oysters

Within aquaculture industries, selection based on genomic information (genomic selection) has the profound potential to change genetic improvement programs and production systems. Genomic selection exploits the use of realized genomic relationships among individuals and information from genome-wide markers in close linkage disequilibrium with genes of biological and economic importance. We discuss the technical advances, practical requirements, and commercial applications that have made genomic selection feasible in a range of aquaculture industries, with a particular focus on molluscs (pearl oysters, Pinctada maxima) and marine shrimp (Litopenaeus vannamei and Penaeus monodon). The use of low-cost genome sequencing has enabled cost-effective genotyping on a large scale and is of particular value for species without a reference genome or access to commercial genotyping arrays. We highlight the pitfalls and offer the solutions to the genotyping by sequencing approach and the building of appropriate genetic resources to undertake genomic selection from first-hand experience. We describe the potential to capture large-scale commercial phenotypes based on image analysis and artificial intelligence through machine learning, as inputs for calculation of genomic breeding values. The application of genomic selection over traditional aquatic breeding programs offers significant advantages through being able to accurately predict complex polygenic traits including disease resistance; increasing rates of genetic gain; minimizing inbreeding; and negating potential limiting effects of genotype by environment interactions. Further practical advantages of genomic selection through the use of large-scale communal mating and rearing systems are highlighted, as well as presenting rate-limiting steps that impact on attaining maximum benefits from adopting genomic selection. Genomic selection is now at the tipping point where commercial applications can be readily adopted and offer significant short- and long-term solutions to sustainable and profitable aquaculture industries.

Modeling mutant/wild-type interactions to ascertain pathogenicity of PROKR2 missense variants in patients with isolated GnRH deficiency

A major challenge in human genetics is the validation of pathogenicity of heterozygous missense variants. This problem is well-illustrated by PROKR2 variants associated with Isolated GnRH Deficiency (IGD). Homozygous, loss of function variants in PROKR2 was initially implicated in autosomal recessive IGD; however, most IGD-associated PROKR2 variants are heterozygous. Moreover, while IGD patient cohorts are enriched for PROKR2 missense variants similar rare variants are also found in normal individuals. To elucidate the pathogenic mechanisms distinguishing IGD-associated PROKR2 variants from rare variants in controls, we assessed 59 variants using three approaches: (i) in silico prediction, (ii) traditional in vitro functional assays across three signaling pathways with mutant-alone transfections, and (iii) modified in vitro assays with mutant and wild-type expression constructs co-transfected to model in vivo heterozygosity. We found that neither in silico analyses nor traditional in vitro assessments of mutants transfected alone could distinguish IGD variants from control variants. However, in vitro co-transfections revealed that 15/34 IGD variants caused loss-of-function (LoF), including 3 novel dominant-negatives, while only 4/25 control variants caused LoF. Surprisingly, 19 IGD-associated variants were benign or exhibited LoF that could be rescued by WT co-transfection. Overall, variants that were LoF in ≥ 2 signaling assays under co-transfection conditions were more likely to be disease-associated than benign or 'rescuable' variants. Our findings suggest that in vitro modeling of WT/Mutant interactions increases the resolution for identifying causal variants, uncovers novel dominant negative mutations, and provides new insights into the pathogenic mechanisms underlying heterozygous PROKR2 variants.

Historical Genomes Reveal the Genomic Consequences of Recent Population Decline in Eastern Gorillas

Many endangered species have experienced severe population declines within the last centuries [1, 2]. However, despite concerns about negative fitness effects resulting from increased genetic drift and inbreeding, there is a lack of empirical data on genomic changes in conjunction with such declines [3-7]. Here, we use whole genomes recovered from century-old historical museum specimens to quantify the genomic consequences of small population size in the critically endangered Grauer's and endangered mountain gorillas. We find a reduction of genetic diversity and increase in inbreeding and genetic load in the Grauer's gorilla, which experienced severe population declines in recent decades. In contrast, the small but relatively stable mountain gorilla population has experienced little genomic change during the last century. These results suggest that species histories as well as the rate of demographic change may influence how population declines affect genome diversity.

Ancient nuclear genomes enable repatriation of Indigenous human remains

After European colonization, the ancestral remains of Indigenous people were often collected for scientific research or display in museum collections. For many decades, Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return. However, many of these remains have no recorded provenance, making their repatriation very difficult or impossible. To determine whether DNA-based methods could resolve this important problem, we sequenced 10 nuclear genomes and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1540 years before the present) of known provenance and compared them to 100 high-coverage contemporary Aboriginal Australian genomes, also of known provenance. We report substantial ancient population structure showing strong genetic affinities between ancient and contemporary Aboriginal Australian individuals from the same geographic location. Our findings demonstrate the feasibility of successfully identifying the origins of unprovenanced ancestral remains using genomic methods.

Using Genomic Data to Infer Historic Population Dynamics of Nonmodel Organisms

Genome sequence data are now being routinely obtained from many nonmodel organisms. These data contain a wealth of information about the demographic history of the populations from which they originate. Many sophisticated statistical inference procedures have been developed to infer the demographic history of populations from this type of genomic data. In this review, we discuss the different statistical methods available for inference of demography, providing an overview of the underlying theory and logic behind each approach. We also discuss the types of data required and the pros and cons of each method. We then discuss how these methods have been applied to a variety of nonmodel organisms. We conclude by presenting some recommendations for researchers looking to use genomic data to infer demographic history.

Conserved Noncoding Elements Influence the Transposable Element Landscape in Drosophila

Highly conserved noncoding elements (CNEs) constitute a significant proportion of the genomes of multicellular eukaryotes. The function of most CNEs remains elusive, but growing evidence indicates they are under some form of purifying selection. Noncoding regions in many species also harbor large numbers of transposable element (TE) insertions, which are typically lineage specific and depleted in exons because of their deleterious effects on gene function or expression. However, it is currently unknown whether the landscape of TE insertions in noncoding regions is random or influenced by purifying selection on CNEs. Here, we combine comparative and population genomic data in Drosophila melanogaster to show that the abundance of TE insertions in intronic and intergenic CNEs is reduced relative to random expectation, supporting the idea that selective constraints on CNEs eliminate a proportion of TE insertions in noncoding regions. However, we find no evidence for differences in the allele frequency spectra for polymorphic TE insertions in CNEs versus those in unconstrained spacer regions, suggesting that the distribution of fitness effects acting on observable TE insertions is similar across different functional compartments in noncoding DNA. Our results provide evidence that selective constraints on CNEs contribute to shaping the landscape of TE insertion in eukaryotic genomes, and provide further evidence that CNEs are indeed functionally constrained and not simply mutational cold spots.

The Genetic Basis of Adaptation following Plastic Changes in Coloration in a Novel Environment

Phenotypic plasticity has been hypothesized to precede and facilitate adaptation to novel environments [1-8], but examples of plasticity preceding adaptation in wild populations are rare (but see [9, 10]). We studied a population of side-blotched lizards, Uta stansburiana, living on a lava flow that formed 22,500 years ago [11] to understand the origin of their novel melanic phenotype that makes them cryptic on the black lava. We found that lizards living on and off of the lava flow exhibited phenotypic plasticity in coloration but also appeared to have heritable differences in pigmentation. We sequenced the exomes of 104 individuals and identified two known regulators of melanin production, PREP and PRKAR1A, which had markedly increased levels of divergence between lizards living on and off the lava flow. The derived variants in PREP and PRKAR1A were only found in the lava population and were associated with increased pigmentation levels in an experimental cohort of hatchling lizards. Simulations suggest that the derived variants in the PREP and PRKAR1A genes arose recently and were under strong positive selection in the lava population. Overall, our results suggest that ancestral plasticity for coloration facilitated initial survival in the lava environment and was followed by genetic changes that modified the phenotype in the direction of the induced plastic response, possibly through de novo mutations. These observations provide a detailed example supporting the hypothesis that plasticity aids in the initial colonization of a novel habitat, with natural selection subsequently refining the phenotype with genetic adaptations to the new environment. VIDEO ABSTRACT.

The genomic basis of environmental adaptation in house mice

House mice (Mus musculus) arrived in the Americas only recently in association with European colonization (~400-600 generations), but have spread rapidly and show evidence of local adaptation. Here, we take advantage of this genetic model system to investigate the genomic basis of environmental adaptation in house mice. First, we documented clinal patterns of phenotypic variation in 50 wild-caught mice from a latitudinal transect in Eastern North America. Next, we found that progeny of mice from different latitudes, raised in a common laboratory environment, displayed differences in a number of complex traits related to fitness. Consistent with Bergmann's rule, mice from higher latitudes were larger and fatter than mice from lower latitudes. They also built bigger nests and differed in aspects of blood chemistry related to metabolism. Then, combining exomic, genomic, and transcriptomic data, we identified specific candidate genes underlying adaptive variation. In particular, we defined a short list of genes with cis-eQTL that were identified as candidates in exomic and genomic analyses, all of which have known ties to phenotypes that vary among the studied populations. Thus, wild mice and the newly developed strains represent a valuable resource for future study of the links between genetic variation, phenotypic variation, and climate.

Inferring Population Structure and Admixture Proportions in Low-Depth NGS Data

We here present two methods for inferring population structure and admixture proportions in low-depth next-generation sequencing (NGS) data. Inference of population structure is essential in both population genetics and association studies, and is often performed using principal component analysis (PCA) or clustering-based approaches. NGS methods provide large amounts of genetic data but are associated with statistical uncertainty, especially for low-depth sequencing data. Models can account for this uncertainty by working directly on genotype likelihoods of the unobserved genotypes. We propose a method for inferring population structure through PCA in an iterative heuristic approach of estimating individual allele frequencies, where we demonstrate improved accuracy in samples with low and variable sequencing depth for both simulated and real datasets. We also use the estimated individual allele frequencies in a fast non-negative matrix factorization method to estimate admixture proportions. Both methods have been implemented in the PCAngsd framework available at http://www.popgen.dk/software/.

The divergence history of European blue mussel species reconstructed from Approximate Bayesian Computation: the effects of sequencing techniques and sampling strategies

Genome-scale diversity data are increasingly available in a variety of biological systems, and can be used to reconstruct the past evolutionary history of species divergence. However, extracting the full demographic information from these data is not trivial, and requires inferential methods that account for the diversity of coalescent histories throughout the genome. Here, we evaluate the potential and limitations of one such approach. We reexamine a well-known system of mussel sister species, using the joint site frequency spectrum (jSFS) of synonymous mutations computed either from exome capture or RNA-seq, in an Approximate Bayesian Computation (ABC) framework. We first assess the best sampling strategy (number of: individuals, loci, and bins in the jSFS), and show that model selection is robust to variation in the number of individuals and loci. In contrast, different binning choices when summarizing the jSFS, strongly affect the results: including classes of low and high frequency shared polymorphisms can more effectively reveal recent migration events. We then take advantage of the flexibility of ABC to compare more realistic models of speciation, including variation in migration rates through time (i.e., periodic connectivity) and across genes (i.e., genome-wide heterogeneity in migration rates). We show that these models were consistently selected as the most probable, suggesting that mussels have experienced a complex history of gene flow during divergence and that the species boundary is semi-permeable. Our work provides a comprehensive evaluation of ABC demographic inference in mussels based on the coding jSFS, and supplies guidelines for employing different sequencing techniques and sampling strategies. We emphasize, perhaps surprisingly, that inferences are less limited by the volume of data, than by the way in which they are analyzed.

In vivo gene correction with targeted sequence substitution through microhomology-mediated end joining

Genome editing technology using programmable nucleases has rapidly evolved in recent years. The primary mechanism to achieve precise integration of a transgene is mainly based on homology-directed repair (HDR). However, an HDR-based genome-editing approach is less efficient than non-homologous end-joining (NHEJ). Recently, a microhomology-mediated end-joining (MMEJ)-based transgene integration approach was developed, showing feasibility both in vitro and in vivo. We expanded this method to achieve targeted sequence substitution (TSS) of mutated sequences with normal sequences using double-guide RNAs (gRNAs), and a donor template flanking the microhomologies and target sequence of the gRNAs in vitro and in vivo. Our method could realize more efficient sequence substitution than the HDR-based method in vitro using a reporter cell line, and led to the survival of a hereditary tyrosinemia mouse model in vivo. The proposed MMEJ-based TSS approach could provide a novel therapeutic strategy, in addition to HDR, to achieve gene correction from a mutated sequence to a normal sequence.

Experimental evidence for rapid genomic adaptation to a new niche in an adaptive radiation

A substantial part of biodiversity is thought to have arisen from adaptive radiations in which one lineage rapidly diversified into multiple lineages adapted to many different niches. However, selection and drift reduce genetic variation during adaptation to new niches and may thus prevent or slow down further niche shifts. We tested whether rapid adaptation is still possible from a highly derived ecotype in the adaptive radiation of threespine stickleback on the Haida Gwaii archipelago, Western Canada. In a 19-years selection experiment, we let giant stickleback from a large blackwater lake evolve in a small clearwater pond without vertebrate predators. 56 whole genomes from the experiment and 26 natural populations revealed that adaptive genomic change was rapid in many small genomic regions and encompassed 75% of the adaptive genomic change between 12,000 years old ecotypes. Adaptive genomic change was as fast as phenotypic change in defence and trophic morphology and both were largely parallel between the short-term selection experiment and long-term natural adaptive radiation. Our results show that functionally relevant standing genetic variation can persist in derived adaptive radiation members, allowing adaptive radiations to unfold very rapidly.

Association mapping from sequencing reads using k-mers

Genome wide association studies (GWAS) rely on microarrays, or more recently mapping of sequencing reads, to genotype individuals. The reliance on prior sequencing of a reference genome limits the scope of association studies, and also precludes mapping associations outside of the reference. We present an alignment free method for association studies of categorical phenotypes based on counting [Formula: see text]-mers in whole-genome sequencing reads, testing for associations directly between [Formula: see text]-mers and the trait of interest, and local assembly of the statistically significant [Formula: see text]-mers to identify sequence differences. An analysis of the 1000 genomes data show that sequences identified by our method largely agree with results obtained using the standard approach. However, unlike standard GWAS, our method identifies associations with structural variations and sites not present in the reference genome. We also demonstrate that population stratification can be inferred from [Formula: see text]-mers. Finally, application to an E.coli dataset on ampicillin resistance validates the approach.

Recognition of the polycistronic nature of human genes is critical to understanding the genotype-phenotype relationship

Technological advances promise unprecedented opportunities for whole exome sequencing and proteomic analyses of populations. Currently, data from genome and exome sequencing or proteomic studies are searched against reference genome annotations. This provides the foundation for research and clinical screening for genetic causes of pathologies. However, current genome annotations substantially underestimate the proteomic information encoded within a gene. Numerous studies have now demonstrated the expression and function of alternative (mainly small, sometimes overlapping) ORFs within mature gene transcripts. This has important consequences for the correlation of phenotypes and genotypes. Most alternative ORFs are not yet annotated because of a lack of evidence, and this absence from databases precludes their detection by standard proteomic methods, such as mass spectrometry. Here, we demonstrate how current approaches tend to overlook alternative ORFs, hindering the discovery of new genetic drivers and fundamental research. We discuss available tools and techniques to improve identification of proteins from alternative ORFs and finally suggest a novel annotation system to permit a more complete representation of the transcriptomic and proteomic information contained within a gene. Given the crucial challenge of distinguishing functional ORFs from random ones, the suggested pipeline emphasizes both experimental data and conservation signatures. The addition of alternative ORFs in databases will render identification less serendipitous and advance the pace of research and genomic knowledge. This review highlights the urgent medical and research need to incorporate alternative ORFs in current genome annotations and thus permit their inclusion in hypotheses and models, which relate phenotypes and genotypes.

Detecting Polygenic Adaptation in Admixture Graphs

An open question in human evolution is the importance of polygenic adaptation: adaptive changes in the mean of a multifactorial trait due to shifts in allele frequencies across many loci. In recent years, several methods have been developed to detect polygenic adaptation using loci identified in genome-wide association studies (GWAS). Though powerful, these methods suffer from limited interpretability: they can detect which sets of populations have evidence for polygenic adaptation, but are unable to reveal where in the history of multiple populations these processes occurred. To address this, we created a method to detect polygenic adaptation in an admixture graph, which is a representation of the historical divergences and admixture events relating different populations through time. We developed a Markov chain Monte Carlo (MCMC) algorithm to infer branch-specific parameters reflecting the strength of selection in each branch of a graph. Additionally, we developed a set of summary statistics that are fast to compute and can indicate which branches are most likely to have experienced polygenic adaptation. We show via simulations that this method-which we call PolyGraph-has good power to detect polygenic adaptation, and applied it to human population genomic data from around the world. We also provide evidence that variants associated with several traits, including height, educational attainment, and self-reported unibrow, have been influenced by polygenic adaptation in different populations during human evolution.

Evolutionary Patterns and Processes: Lessons from Ancient DNA

Ever since its emergence in 1984, the field of ancient DNA has struggled to overcome the challenges related to the decay of DNA molecules in the fossil record. With the recent development of high-throughput DNA sequencing technologies and molecular techniques tailored to ultra-damaged templates, it has now come of age, merging together approaches in phylogenomics, population genomics, epigenomics, and metagenomics. Leveraging on complete temporal sample series, ancient DNA provides direct access to the most important dimension in evolution—time, allowing a wealth of fundamental evolutionary processes to be addressed at unprecedented resolution. This review taps into the most recent findings in ancient DNA research to present analyses of ancient genomic and metagenomic data.

Male-biased gene expression resolves sexual conflict through the evolution of sex-specific genetic architecture

Many genes are subject to contradictory selection pressures in males and females, and balancing selection resulting from sexual conflict has the potential to substantially increase standing genetic diversity in populations and thereby act as an important force in adaptation. However, the underlying causes of sexual conflict, and the potential for resolution, remains hotly debated. Using transcriptome‐resequencing data from male and female guppies, we use a novel approach, combining patterns of genetic diversity and intersexual divergence in allele frequency, to distinguish the different scenarios that give rise to sexual conflict, and how this conflict may be resolved through regulatory evolution. We show that reproductive fitness is the main source of sexual conflict, and this is resolved via the evolution of male‐biased expression. Furthermore, resolution of sexual conflict produces significant differences in genetic architecture between males and females, which in turn lead to specific alleles influencing sex‐specific viability. Together, our findings suggest an important role for sexual conflict in shaping broad patterns of genome diversity, and show that regulatory evolution is a rapid and efficient route to the resolution of conflict.

Ancient polymorphisms and divergence hitchhiking contribute to genomic islands of divergence within a poplar species complex

One of the outstanding questions in understanding how new species form is how reproductive isolation arises. In particular, the relative roles of gene flow and natural selection in creating two separate species remains open for debate. Here we show within the four continuously speciating lineages of a poplar that local genomic differentiation of populations is not associated with either rate of recent gene flow or time of species divergence. By contrast, we found that these genomic islands of divergence most likely came about by selective processes—sorting of ancient genetic polymorphisms and the incidental hitchhiking of linked variations. These findings substantially enhance our understanding of genomic changes in speciation.

How genome divergence eventually leads to speciation is a topic of prime evolutionary interest. Genomic islands of elevated divergence are frequently reported between diverging lineages, and their size is expected to increase with time and gene flow under the speciation-with-gene-flow model. However, such islands can also result from divergent sorting of ancient polymorphisms, recent ecological selection regardless of gene flow, and/or recurrent background selection and selective sweeps in low-recombination regions. It is challenging to disentangle these nonexclusive alternatives, but here we attempt to do this in an analysis of what drove genomic divergence between four lineages comprising a species complex of desert poplar trees. Within this complex we found that two morphologically delimited species, Populus euphratica and Populus pruinosa, were paraphyletic while the four lineages exhibited contrasting levels of gene flow and divergence times, providing a good system for testing hypotheses on the origin of divergence islands. We show that the size and number of genomic islands that distinguish lineages are not associated with either rate of recent gene flow or time of divergence. Instead, they are most likely derived from divergent sorting of ancient polymorphisms and divergence hitchhiking. We found that highly diverged genes under lineage-specific selection and putatively involved in ecological and morphological divergence occur both within and outside these islands. Our results highlight the need to incorporate demography, absolute divergence measurement, and gene flow rate to explain the formation of genomic islands and to identify potential genomic regions involved in speciation.

Genomics clarifies taxonomic boundaries in a difficult species complex

Efforts to taxonomically delineate species are often confounded with conflicting information and subjective interpretation. Advances in genomic methods have resulted in a new approach to taxonomic identification that stands to greatly reduce much of this conflict. This approach is ideal for species complexes, where divergence times are recent (evolutionarily) and lineages less well defined. The California Roach/Hitch fish species complex is an excellent example, experiencing a convoluted geologic history, diverse habitats, conflicting species designations and potential admixture between species. Here we use this fish complex to illustrate how genomics can be used to better clarify and assign taxonomic categories. We performed restriction-site associated DNA (RAD) sequencing on 255 Roach and Hitch samples collected throughout California to discover and genotype thousands of single nucleotide polymorphism (SNPs). Data were then used in hierarchical principal component, admixture, and FST analyses to provide results that consistently resolved a number of ambiguities and provided novel insights across a range of taxonomic levels. At the highest level, our results show that the CA Roach/Hitch complex should be considered five species split into two genera (4 + 1) as opposed to two species from distinct genera (1 +1). Subsequent levels revealed multiple subspecies and distinct population segments within identified species. At the lowest level, our results indicate Roach from a large coastal river are not native but instead introduced from a nearby river. Overall, this study provides a clear demonstration of the power of genomic methods for informing taxonomy and serves as a model for future studies wishing to decipher difficult species questions. By allowing for systematic identification across multiple scales, taxonomic structure can then be tied to historical and contemporary ecological, geographic or anthropogenic factors.

Fantastic Beasts and How To Sequence Them: Ecological Genomics for Obscure Model Organisms

The application of genomic approaches to 'obscure model organisms' (OMOs), meaning species with no prior genomic resources, enables increasingly sophisticated studies of the genomic basis of evolution, acclimatization, and adaptation in real ecological contexts. I consider here ecological questions that can be addressed using OMOs, and indicate optimal sequencing and data-handling solutions for each case. With this I hope to promote the diversity of OMO-based projects that would capitalize on the peculiarities of the natural history of OMOs and could feasibly be completed within the scope of a single PhD thesis.

Genome-Wide Analysis of Colonization History and Concomitant Selection in Arabidopsis lyrata

The high climatic variability in the past hundred thousand years has affected the demographic and adaptive processes in many species, especially in boreal and temperate regions undergoing glacial cycles. This has also influenced the patterns of genome-wide nucleotide variation, but the details of these effects are largely unknown. Here we study the patterns of genome-wide variation to infer colonization history and patterns of selection of the perennial herb species Arabidopsis lyrata, in locally adapted populations from different parts of its distribution range (Germany, UK, Norway, Sweden, and USA) representing different environmental conditions. Using site frequency spectra based demographic modeling, we found strong reduction in the effective population size of the species in general within the past 100,000 years, with more pronounced effects in the colonizing populations. We further found that the northwestern European A. lyrata populations (UK and Scandinavian) are more closely related to each other than with the Central European populations, and coalescent based population split modeling suggests that western European and Scandinavian populations became isolated relatively recently after the glacial retreat. We also highlighted loci showing evidence for local selection associated with the Scandinavian colonization. The results presented here give new insights into postglacial Scandinavian colonization history and its genome-wide effects.

Assessing the Relationship of Ancient and Modern Populations

Sequencing DNA from deceased individuals can inform whether the individuals that currently live in a location are descended from individuals that.....

Genetic material sequenced from ancient samples is revolutionizing our understanding of the recent evolutionary past. However, ancient DNA is often degraded, resulting in low coverage, error-prone sequencing. Several solutions exist to this problem, ranging from simple approach, such as selecting a read at random for each site, to more complicated approaches involving genotype likelihoods. In this work, we present a novel method for assessing the relationship of an ancient sample with a modern population, while accounting for sequencing error and postmortem damage by analyzing raw reads from multiple ancient individuals simultaneously. We show that, when analyzing SNP data, it is better to sequence more ancient samples to low coverage: two samples sequenced to 0.5× coverage provide better resolution than a single sample sequenced to 2× coverage. We also examined the power to detect whether an ancient sample is directly ancestral to a modern population, finding that, with even a few high coverage individuals, even ancient samples that are very slightly diverged from the modern population can be detected with ease. When we applied our approach to European samples, we found that no ancient samples represent direct ancestors of modern Europeans. We also found that, as shown previously, the most ancient Europeans appear to have had the smallest effective population sizes, indicating a role for agriculture in modern population growth.