Validation of Pooled Whole-Genome Re-Sequencing in Arabidopsis lyrata

Genomic implications of the repeated shift to self-fertilization across a species' geographic distribution

The ability to self-fertilize often varies among closely related hermaphroditic plant species, though, variation can also exist within species. In the North American Arabidopsis lyrata, the shift from self-incompatibility (SI) to selfing established in multiple regions independently, mostly since recent postglacial range expansion. This has made the species an ideal model for the investigation of the genomic basis of the breakdown of SI and its population genetic consequences. By comparing nearby selfing and outcrossing populations across the entire species' geographic distribution, we investigated variation at the self-incompatibility (S-)locus and across the genome. Furthermore, a diallel crossing experiment on one mixed-mating population was performed to gain insight into the inheritance of mating system variation. We confirmed that the breakdown of SI had evolved in several S-locus backgrounds. The diallel suggested the involvement of biparental contributions with dominance relations. Though, the population-level genome-wide association study did not single out clear-cut candidate genes but several regions with one near the S-locus. On the implication side, selfing as compared to outcrossing populations had less than half of the genomic diversity, while the number and length of runs of homozygosity (ROHs) scaled with the degree of inbreeding. Selfing populations with a history of long expansion had the longest ROHs. The results highlight that mating system shift to selfing, its genetic underpinning and the likely negative genomic consequences for evolutionary potential can be strongly interlinked with past range dynamics.

Identification of Functional Variants Between Tong Sheep and Hu Sheep by Whole-Genome Sequencing Pools of Individuals

Tong sheep, known for their superior meat quality and disease resilience, face breeding challenges due to low prolificacy, unlike Hu sheep, which exhibit higher fertility and growth rates. This study identified over 700,000 genetic variants between these breeds through pooled whole-genome sequencing. Functional analysis reveals key differences in pathways related to fat metabolism, insulin signaling, and cell cycle regulation. Notable findings include unique microRNA variants (miR-1185-3p in Tong sheep and miR-487-5p in Hu sheep), with the miR-487-5p mutation potentially regulating KITLG, a fertility-related gene. These results suggest that non-coding RNA mutations contribute to phenotypic differences and provide a genomic foundation for molecular-assisted selection to improve Tong sheep breeding programs.

Identification of a Unique Genomic Region in Sweet Chestnut (Castanea sativa Mill.) That Controls Resistance to Asian Chestnut Gall Wasp Dryocosmus kuriphilus Yasumatsu

The Asian chestnut gall wasp (ACGW) (Hymenoptera Dryocosmus kuriphilus Yasumatsu) is a severe pest of sweet chestnut (Castanea sativa Mill.) with a strong impact on growth and nut production. A comparative field trial in Central Italy, including provenances from Spain, Italy, and Greece, was screened for ACGW infestation over consecutive years. The Greek provenance Hortiatis expressed a high proportion of immune plants and was used to perform a genome-wide association study based on DNA pool sequencing (Pool-GWAS) by comparing two DNA pools from 25 susceptible and 25 resistant plants. DNA pools were sequenced with 50X coverage depth. Sequence reads were aligned to a C. mollissima reference genome and the pools were compared to identify SNPs associated with resistance. Twenty-one significant SNPs were identified and highlighted a small genomic region on pseudochromosome 3 (Chr 3), containing 12 candidate genes of three gene families: Cytochrome P450, UDP-glycosyltransferase, and Rac-like GTP-binding protein. Functional analyses revealed a putative metabolic gene cluster related to saccharide biosynthesis in the genomic regions associated with resistance that could be involved in the production of a toxic metabolite against parasites. The comparison with previous genetic studies confirmed the involvement of Chr 3 in the control of resistance to ACGW.

ngsJulia: population genetic analysis of next-generation DNA sequencing data with Julia language

A sound analysis of DNA sequencing data is important to extract meaningful information and infer quantities of interest. Sequencing and mapping errors coupled with low and variable coverage hamper the identification of genotypes and variants and the estimation of population genetic parameters. Methods and implementations to estimate population genetic parameters from sequencing data available nowadays either are suitable for the analysis of genomes from model organisms only, require moderate sequencing coverage, or are not easily adaptable to specific applications. To address these issues, we introduce ngsJulia, a collection of templates and functions in Julia language to process short-read sequencing data for population genetic analysis. We further describe two implementations, ngsPool and ngsPloidy, for the analysis of pooled sequencing data and polyploid genomes, respectively. Through simulations, we illustrate the performance of estimating various population genetic parameters using these implementations, using both established and novel statistical methods. These results inform on optimal experimental design and demonstrate the applicability of methods in ngsJulia to estimate parameters of interest even from low coverage sequencing data. ngsJulia provide users with a flexible and efficient framework for ad hoc analysis of sequencing data.ngsJulia is available from: https://github.com/mfumagalli/ngsJulia.

Genome-wide patterns of genetic diversity, population structure and demographic history in mānuka (Leptospermum scoparium) growing on indigenous Māori land

Leptospermum scoparium J. R. Forst et G. Forst, known as mānuka by Māori, the indigenous people of Aotearoa (New Zealand), is a culturally and economically significant shrub species, native to New Zealand and Australia. Chemical, morphological and phylogenetic studies have indicated geographical variation of mānuka across its range in New Zealand, and genetic differentiation between New Zealand and Australia. We used pooled whole genome re-sequencing of 76 L. scoparium and outgroup populations from New Zealand and Australia to compile a dataset totalling ~2.5 million SNPs. We explored the genetic structure and relatedness of L. scoparium across New Zealand, and between populations in New Zealand and Australia, as well as the complex demographic history of this species. Our population genomic investigation suggests there are five geographically distinct mānuka gene pools within New Zealand, with evidence of gene flow occurring between these pools. Demographic modelling suggests three of these gene pools have undergone expansion events, whilst the evolutionary histories of the remaining two have been subjected to contractions. Furthermore, mānuka populations in New Zealand are genetically distinct from populations in Australia, with coalescent modelling suggesting these two clades diverged ~9-12 million years ago. We discuss the evolutionary history of this species and the benefits of using pool-seq for such studies. Our research will support the management and conservation of mānuka by landowners, particularly Māori, and the development of a provenance story for the branding of mānuka based products.

Haploid, diploid, and pooled exome capture recapitulate features of biology and paralogy in two non-model tree species

Despite their suitability for studying evolution, many conifer species have large and repetitive giga‐genomes (16–31 Gbp) that create hurdles to producing high coverage SNP data sets that capture diversity from across the entirety of the genome. Due in part to multiple ancient whole genome duplication events, gene family expansion and subsequent evolution within Pinaceae, false diversity from the misalignment of paralog copies creates further challenges in accurately and reproducibly inferring evolutionary history from sequence data. Here, we leverage the cost‐saving benefits of pool‐seq and exome‐capture to discover SNPs in two conifer species, Douglas‐fir (Pseudotsuga menziesii var. menziesii (Mirb.) Franco, Pinaceae) and jack pine (Pinus banksiana Lamb., Pinaceae). We show, using minimal baseline filtering, that allele frequencies estimated from pooled individuals show a strong, positive correlation with those estimated by sequencing the same population as individuals (r > .948), on par with such comparisons made in model organisms. Further, we highlight the utility of haploid megagametophyte tissue for identifying sites that are probably due to misaligned paralogs. Together with additional minor filtering, we show that it is possible to remove many of the loci with large frequency estimate discrepancies between individual and pooled sequencing approaches, improving the correlation further (r > .973). Our work addresses bioinformatic challenges in non‐model organisms with large and complex genomes, highlights the use of megagametophyte tissue for the identification of paralogous artefacts, and suggests the combination of pool‐seq and exome capture to be robust for further evolutionary hypothesis testing in these systems.

Optimizing sampling design and sequencing strategy for the genomic analysis of quantitative traits in natural populations

Mapping the genes underlying ecologically relevant traits in natural populations is fundamental to develop a molecular understanding of species adaptation. Current sequencing technologies enable the characterization of a species' genetic diversity across the landscape or even over its whole range. The relevant capture of the genetic diversity across the landscape is critical for a successful genetic mapping of traits and there are no clear guidelines on how to achieve an optimal sampling and which sequencing strategy to implement. Here we determine, through simulation, the sampling scheme that maximizes the power to map the genetic basis of a complex trait in an outbreeding species across an idealized landscape and draw genomic predictions for the trait, comparing individual and pool sequencing strategies. Our results show that quantitative trait locus detection power and prediction accuracy are higher when more populations over the landscape are sampled and this is more cost-effectively done with pool sequencing than with individual sequencing. Additionally, we recommend sampling populations from areas of high genetic diversity. As progress in sequencing enables the integration of trait-based functional ecology into landscape genomics studies, these findings will guide study designs allowing direct measures of genetic effects in natural populations across the environment.

Benchmarking the performance of Pool-seq SNP callers using simulated and real sequencing data

Population genomics is a fast-developing discipline with promising applications in a growing number of life sciences fields. Advances in sequencing technologies and bioinformatics tools allow population genomics to exploit genome-wide information to identify the molecular variants underlying traits of interest and the evolutionary forces that modulate these variants through space and time. However, the cost of genomic analyses of multiple populations is still too high to address them through individual genome sequencing. Pooling individuals for sequencing can be a more effective strategy in Single Nucleotide Polymorphism (SNP) detection and allele frequency estimation because of a higher total coverage. However, compared to individual sequencing, SNP calling from pools has the additional difficulty of distinguishing rare variants from sequencing errors, which is often avoided by establishing a minimum threshold allele frequency for the analysis. Finding an optimal balance between minimizing information loss and reducing sequencing costs is essential to ensure the success of population genomics studies. Here, we have benchmarked the performance of SNP callers for Pool-seq data, based on different approaches, under different conditions, and using computer simulations and real data. We found that SNP callers performance varied for allele frequencies up to 0.35. We also found that SNP callers based on Bayesian (SNAPE-pooled) or maximum likelihood (MAPGD) approaches outperform the two heuristic callers tested (VarScan and PoolSNP), in terms of the balance between sensitivity and FDR both in simulated and sequencing data. Our results will help inform the selection of the most appropriate SNP caller not only for large-scale population studies but also in cases where the Pool-seq strategy is the only option, such as in metagenomic or polyploid studies.

Growth genes are implicated in the evolutionary divergence of sympatric piscivorous and insectivorous rainbow trout (Oncorhynchus mykiss)

Background

Identifying ecologically significant phenotypic traits and the genomic mechanisms that underly them are crucial steps in understanding traits associated with population divergence. We used genome-wide data to identify genomic regions associated with key traits that distinguish two ecomorphs of rainbow trout (Oncorhynchus mykiss)—insectivores and piscivores—that coexist for the non-breeding portion of the year in Kootenay Lake, southeastern British Columbia. “Gerrards” are large-bodied, rapidly growing piscivores with high metabolic rates that spawn north of Kootenay Lake in the Lardeau River, in contrast to the insectivorous populations that are on average smaller in body size, with lower growth and metabolic rates, mainly forage on aquatic insects, and spawn in tributaries immediately surrounding Kootenay Lake. We used pool-seq data representing ~ 60% of the genome and 80 fish per population to assess the level of genomic divergence between ecomorphs and to identify and interrogate loci that may play functional or selective roles in their divergence.

Results

Genomic divergence was high between sympatric insectivores and piscivores (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST = 0.188), and in fact higher than between insectivorous populations from Kootenay Lake and the Blackwater River (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST = 0.159) that are > 500 km apart. A window-based \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST analysis did not reveal “islands” of genomic differentiation; however, the window with highest \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$F_{\text{ST}}$$\end{document}FST estimate did include a gene associated with insulin secretion. Although we explored the use of the “Local score” approach to identify genomic outlier regions, this method was ultimately not used because simulations revealed a high false discovery rate (~ 20%). Gene ontology (GO) analysis identified several growth processes as enriched in genes occurring in the ~ 200 most divergent genomic windows, indicating many loci of small effect involved in growth and growth-related metabolic processes are associated with the divergence of these ecomorphs.

Conclusion

Our results reveal a high degree of genomic differentiation between piscivorous and insectivorous populations and indicate that the large body piscivorous phenotype is likely not due to one or a few loci of large effect. Rather, the piscivore phenotype may be controlled by several loci of small effect, thus highlighting the power of whole-genome resequencing in identifying genomic regions underlying population-level phenotypic divergences.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12862-021-01795-9.

Drivers of linkage disequilibrium across a species' geographic range

While linkage disequilibrium (LD) is an important parameter in genetics and evolutionary biology, the drivers of LD remain elusive. Using whole-genome sequences from across a species’ range, we assessed the impact of demographic history and mating system on LD. Both range expansion and a shift from outcrossing to selfing in North American Arabidopsis lyrata were associated with increased average genome-wide LD. Our results indicate that range expansion increases short-distance LD at the farthest range edges by about the same amount as a shift to selfing. However, the extent over which LD in genic regions unfolds was shorter for range expansion compared to selfing. Linkage among putatively neutral variants and between neutral and deleterious variants increased to a similar degree with range expansion, providing support that genome-wide LD was positively associated with mutational load. As a consequence, LD combined with mutational load may decelerate range expansions and set range limits. Finally, a small number of genes were identified as LD outliers, suggesting that they experience selection by either of the two demographic processes. These included genes involved in flowering and photoperiod for range expansion, and the self-incompatibility locus for mating system.

Nearby genomic variants are often co-inherited because of limited recombination. The extent of non-random association of alleles at different loci is called linkage disequilibrium (LD) and is commonly used in genomic analyses, for example to detect regions under selection or to determine effective population size. Here we reversed testing and addressed how demographic history may affect LD within a species. Using genomic data from more than a thousand individuals of North American Arabidopsis lyrata from across the entire species’ range, we quantified the effect of postglacial range expansion and a shift in mating system from outcrossing to selfing on LD. We show that both factors lead to increased LD, and that the maximal effect of range expansion is comparable with a shift in mating system to selfing. Heightened LD involves deleterious mutations, and therefore, LD can also serve as an indicator of mutation accumulation. Furthermore, we provide evidence that some genes experienced stronger increases in LD possibly due to selection associated with the two demographic changes. Our results provide a novel and broad view on the evolutionary factors shaping LD that may also apply to the very many species that underwent postglacial range expansion.

Convergent Adaptation to Quantitative Host Resistance in a Major Plant Pathogen

Plant pathogens can adapt to quantitative resistance, eroding its effectiveness. The aim of this work was to reveal the genomic basis of adaptation to such a resistance in populations of the fungus Pseudocercospora fijiensis, a major devastating pathogen of banana, by studying convergent adaptation on different cultivars. Samples from P. fijiensis populations showing a local adaptation pattern on new banana hybrids with quantitative resistance were compared, based on a genome scan approach, with samples from traditional and more susceptible cultivars in Cuba and the Dominican Republic. Whole-genome sequencing of pools of P. fijiensis isolates (pool-seq) sampled from three locations per country was conducted according to a paired population design. The findings of different combined analyses highly supported the existence of convergent adaptation on the study cultivars between locations within but not between countries. Five to six genomic regions involved in this adaptation were detected in each country. An annotation analysis and available biological data supported the hypothesis that some genes within the detected genomic regions may play a role in quantitative pathogenicity, including gene regulation. The results suggested that the genetic basis of fungal adaptation to quantitative plant resistance is at least oligogenic, while highlighting the existence of specific host-pathogen interactions for this kind of resistance.IMPORTANCE Understanding the genetic basis of pathogen adaptation to quantitative resistance in plants has a key role to play in establishing durable strategies for resistance deployment. In this context, a population genomic approach was developed for a major plant pathogen (the fungus Pseudocercospora fijiensis causing black leaf streak disease of banana) whereby samples from new resistant banana hybrids were compared with samples from more susceptible conventional cultivars in two countries. A total of 11 genomic regions for which there was strong evidence of selection by quantitative resistance were detected. An annotation analysis and available biological data supported the hypothesis that some of the genes within these regions may play a role in quantitative pathogenicity. These results suggested a polygenic basis of quantitative pathogenicity in this fungal pathogen and complex molecular plant-pathogen interactions in quantitative disease development involving several genes on both sides.

Population Genomics on the Fly: Recent Advances in Drosophila

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field.

Demographic Processes Linked to Genetic Diversity and Positive Selection across a Species' Range

Demography determines the strength of genetic drift, which generally reduces genetic variation and the efficacy of selection. Here, we disentangled the importance of demographic processes at a local scale (census size and mating system) and at a species-range scale (old split between population clusters, recolonization after the last glaciation cycle, and admixture) in determining within-population genomic diversity and genomic signatures of positive selection. Analyses were based on re-sequence data from 52 populations of North American Arabidopsis lyrata collected across its entire distribution. The mating system and range dynamics since the last glaciation cycle explained around 60% of the variation in genomic diversity among populations and 52% of the variation in the signature of positive selection. Diversity was lowest in selfing compared with outcrossing populations and in areas further away from glacial refugia. In parallel, reduced positive selection was found in selfing populations and in populations with a longer route of postglacial range expansion. The signature of positive selection was also reduced in populations without admixture. We conclude that recent range expansion can have a profound influence on diversity in coding and non-coding DNA, similar in magnitude to the shift toward selfing. Distribution limits may in fact be caused by reduced effective population size and compromised positive selection in recently colonized parts of the range.

Genomics versus mtDNA for resolving stock structure in the silky shark (Carcharhinus falciformis)

Conservation genetic approaches for elasmobranchs have focused on regions of the mitochondrial genome or a handful of nuclear microsatellites. High-throughput sequencing offers a powerful alternative for examining population structure using many loci distributed across the nuclear and mitochondrial genomes. These single nucleotide polymorphisms are expected to provide finer scale and more accurate population level data; however, there have been few genomic studies applied to elasmobranch species. The desire to apply next-generation sequencing approaches is often tempered by the costs, which can be offset by pooling specimens prior to sequencing (pool-seq). In this study, we assess the utility of pool-seq by applying this method to the same individual silky sharks, Carcharhinus falciformis, previously surveyed with the mtDNA control region in the Atlantic and Indian Oceans. Pool-seq methods were able to recover the entire mitochondrial genome as well as thousands of nuclear markers. This volume of sequence data enabled the detection of population structure between regions of the Atlantic Ocean populations, undetected in the previous study (inter-Atlantic mitochondrial SNPs FST values comparison ranging from 0.029 to 0.135 and nuclear SNPs from 0.015 to 0.025). Our results reinforce the conclusion that sampling the mitochondrial control region alone may fail to detect fine-scale population structure, and additional sampling across the genome may increase resolution for some species. Additionally, this study shows that the costs of analyzing 4,988 loci using pool-seq methods are equivalent to the standard Sanger-sequenced markers and become less expensive when large numbers of individuals (>300) are analyzed.

A genetic analysis of a Spanish population with early onset Parkinson's disease

Introduction

Both recessive and dominant genetic forms of Parkinson’s disease have been described. The aim of this study was to assess the contribution of several genes to the pathophysiology of early onset Parkinson’s disease in a cohort from central Spain.

Methods/patients

We analyzed a cohort of 117 unrelated patients with early onset Parkinson’s disease using a pipeline, based on a combination of a next-generation sequencing panel of 17 genes previously related with Parkinson’s disease and other Parkinsonisms and CNV screening.

Results

Twenty-six patients (22.22%) carried likely pathogenic variants in PARK2, LRRK2, PINK1, or GBA. The gene most frequently mutated was PARK2, and p.Asn52Metfs*29 was the most common variation in this gene. Pathogenic variants were not observed in genes SNCA, FBXO7, PARK7, HTRA2, DNAJC6, PLA2G6, and UCHL1. Co-occurrence of pathogenic variants involving two genes was observed in ATP13A2 and PARK2 genes, as well as LRRK2 and GIGYF2 genes.

Conclusions

Our results contribute to the understanding of the genetic architecture associated with early onset Parkinson’s disease, showing both PARK2 and LRRK2 play an important role in Spanish Parkinson’s disease patients. Rare variants in ATP13A2 and GIGYF2 may contribute to PD risk. However, a large proportion of genetic components remains unknown. This study might contribute to genetic diagnosis and counseling for families with early onset Parkinson’s disease.

Shared genetic susceptibilities for irritable bowel syndrome and depressive disorder in Chinese patients uncovered by pooled whole-exome sequencing

Irritable bowel syndrome (IBS) is the most prevalent functional gastrointestinal disorder presenting a high comorbidity with depressive disorder (DD). Many studies have confirmed that these two disease share the similar pathophysiological process, but evidence of the genetic risks is limited. This study aimed to analyze the genetic susceptibilities for IBS and DD in Chinese patients. Pooled whole-exome sequencing (pooled-WES) was performed to identify the candidate variants in the group of diarrhea predominant IBS (IBS-D) patients, DD patients, and healthy controls (HC). Then, targeted sequencing was used to validate the candidate variants in three additional cohorts of IBS-D, DD, and HC. Four variants associated with both IBS-D and DD were identified through pooled-WES, and three of them were validated in targeted sequencing. SYT8 rs3741231 G allele and SSPO rs12536873 TT genotype were associated with both IBS-D and DD. The genes of these variants are important in neurogenesis and neurotransmission. In addition, we found COL6A1 rs13051496, a unique risk variation for IBS-D. It increased the IBS-D risk and had a positive correlation with the scores of abdominal bloating and dissatisfaction of bowel habits. Through the results of this study, it provides a genetic basis for the high comorbidity of IBS-D and DD.

Postglacial ecotype formation under outcrossing and self-fertilization in Arabidopsis lyrata

The formation of ecotypes has been invoked as an important driver of postglacial biodiversity, because many species colonized heterogeneous habitats and experienced divergent selection. Ecotype formation has been predominantly studied in outcrossing taxa, while far less attention has been paid to the implications of mating system shifts. Here, we addressed whether substrate-related ecotypes exist in selfing and outcrossing populations of Arabidopsis lyrata subsp. lyrata and whether the genomic footprint differs between mating systems. The North American subspecies colonized both rocky and sandy habitats during postglacial range expansion and shifted the mating system from predominantly outcrossing to predominantly selfing in a number of regions. We performed an association study on pooled whole-genome sequence data of 20 selfing or outcrossing populations, which suggested genes involved in adaptation to substrate. Motivated by enriched gene ontology terms, we compared root growth between plants from the two substrates in a common environment and found that plants originating from sand grew roots faster and produced more side roots, independent of mating system. Furthermore, single nucleotide polymorphisms associated with substrate-related ecotypes were more clustered among selfing populations. Our study provides evidence for substrate-related ecotypes in A. lyrata and divergence in the genomic footprint between mating systems. The latter is the likely result of selfing populations having experienced divergent selection on larger genomic regions due to higher genome-wide linkage disequilibrium.

Accurate Allele Frequencies from Ultra-low Coverage Pool-Seq Samples in Evolve-and-Resequence Experiments

Evolve-and-resequence (E+R) experiments leverage next-generation sequencing technology to track the allele frequency dynamics of populations as they evolve. While previous work has shown that adaptive alleles can be detected by comparing frequency trajectories from many replicate populations, this power comes at the expense of high-coverage (>100x) sequencing of many pooled samples, which can be cost-prohibitive. Here, we show that accurate estimates of allele frequencies can be achieved with very shallow sequencing depths (<5x) via inference of known founder haplotypes in small genomic windows. This technique can be used to efficiently estimate frequencies for any number of bi-allelic SNPs in populations of any model organism founded with sequenced homozygous strains. Using both experimentally-pooled and simulated samples of Drosophila melanogaster, we show that haplotype inference can improve allele frequency accuracy by orders of magnitude for up to 50 generations of recombination, and is robust to moderate levels of missing data, as well as different selection regimes. Finally, we show that a simple linear model generated from these simulations can predict the accuracy of haplotype-derived allele frequencies in other model organisms and experimental designs. To make these results broadly accessible for use in E+R experiments, we introduce HAF-pipe, an open-source software tool for calculating haplotype-derived allele frequencies from raw sequencing data. Ultimately, by reducing sequencing costs without sacrificing accuracy, our method facilitates E+R designs with higher replication and resolution, and thereby, increased power to detect adaptive alleles.

Parallel Speciation of Wild Rice Associated with Habitat Shifts

The occurrence of parallel speciation strongly implies the action of natural selection. However, it is unclear how general a phenomena parallel speciation is since it was only shown in a small number of animal species. In particular, the adaptive process and mechanisms underlying the process of parallel speciation remain elusive. Here, we used an integrative approach incorporating population genomics, common garden, and crossing experiments to investigate parallel speciation of the wild rice species Oryza nivara from O. rufipogon. We demonstrated that O. nivara originated multiple times from different O. rufipogon populations and revealed that different O. nivara populations have evolved similar phenotypes under divergent selection, a reflection of recurrent local adaptation of ancient O. rufipogon populations to dry habitats. Almost completed premating isolation was detected between O. nivara and O. rufipogon in the absence of any postmating barriers between and within these species. These results suggest that flowering time is a “magic” trait that contributes to both local adaptation and reproductive isolation in the origin of wild rice species. Our study thus demonstrates a convincing case of parallel ecological speciation as a consequence of adaptation to new environments.

Genomic variation predicts adaptive evolutionary responses better than population bottleneck history

The relationship between population size, inbreeding, loss of genetic variation and evolutionary potential of fitness traits is still unresolved, and large-scale empirical studies testing theoretical expectations are surprisingly scarce. Here we present a highly replicated experimental evolution setup with 120 lines of Drosophila melanogaster having experienced inbreeding caused by low population size for a variable number of generations. Genetic variation in inbred lines and in outbred control lines was assessed by genotyping-by-sequencing (GBS) of pooled samples consisting of 15 males per line. All lines were reared on a novel stressful medium for 10 generations during which body mass, productivity, and extinctions were scored in each generation. In addition, we investigated egg-to-adult viability in the benign and the stressful environments before and after rearing at the stressful conditions for 10 generations. We found strong positive correlations between levels of genetic variation and evolutionary response in all investigated traits, and showed that genomic variation was more informative in predicting evolutionary responses than population history reflected by expected inbreeding levels. We also found that lines with lower genetic diversity were at greater risk of extinction. For viability, the results suggested a trade-off in the costs of adapting to the stressful environments when tested in a benign environment. This work presents convincing support for long-standing evolutionary theory, and it provides novel insights into the association between genetic variation and evolutionary capacity in a gradient of diversity rather than dichotomous inbred/outbred groups.

Comparing Pool-seq, Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost-effective sequencing approaches, namely Pool-seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping-by-sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool-seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool-seq data showed F ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F ST estimates, indicating that individual-based approaches provided more congruent results than Pool-seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost-effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.

Family quarrels in seeds and rapid adaptive evolution in Arabidopsis

Evolutionary conflict can drive rapid adaptive evolution, sometimes called an arms race, because each party needs to respond continually to the adaptations of the other. Evidence for such arms races can sometimes be seen in morphology, in behavior, or in the genes underlying sexual interactions of host-pathogen interactions, but is rarely predicted a priori. Kin selection theory predicts that conflicts of interest should usually be reduced but not eliminated among genetic relatives, but there is little evidence as to whether conflict within families can drive rapid adaptation. Here we test multiple predictions about how conflict over the amount of resources an offspring receives from its parent would drive rapid molecular evolution in seed tissues of the flowering plant Arabidopsis As predicted, there is more adaptive evolution in genes expressed in Arabidopsis seeds than in other specialized organs, more in endosperms and maternal tissues than in embryos, and more in the specific subtissues involved in nutrient transfer. In the absence of credible alternative hypotheses, these results suggest that kin selection and conflict are important in plants, that the conflict includes not just the mother and offspring but also the triploid endosperm, and that, despite the conflict-reducing role of kinship, family members can engage in slow but steady tortoise-like arms races.

Accumulation of Mutational Load at the Edges of a Species Range

Why species have geographically restricted distributions is an unresolved question in ecology and evolutionary biology. Here, we test a new explanation that mutation accumulation due to small population size or a history of range expansion can contribute to restricting distributions by reducing population growth rate at the edge. We examined genomic diversity and mutational load across the entire geographic range of the North American plant Arabidopsis lyrata, including old, isolated populations predominantly at the southern edge and regions of postglacial range expansion at the northern and southern edges. Genomic diversity in intergenic regions declined toward distribution edges and signatures of mutational load in exon regions increased. Genomic signatures of mutational load were highly linked to phenotypically expressed load, measured as reduced performance of individual plants and lower estimated rate of population growth. The geographic pattern of load and the connection between load and population growth demonstrate that mutation accumulation reduces fitness at the edge and helps restrict species' distributions.

Experimental drought reduces genetic diversity in the grassland foundation species Bouteloua eriopoda

Understanding the resistance and resilience of foundation plant species to climate change is a critical issue because the loss of these species would fundamentally reshape communities and ecosystem processes. High levels of population genetic diversity may buffer foundation species against climate disruptions, but the strong selective pressures associated with climatic shifts may also rapidly reduce such diversity. We characterized genetic diversity and its responsiveness to experimental drought in the foundation plant, black grama grass (Bouteloua eriopoda), which dominates many western North American grasslands and shrublands. Previous studies suggested that in arid ecosystems, black grama reproduces largely asexually via stolons, and thus is likely to have low genetic variability, which might limit its potential to respond to climate disruptions. Using genotyping-by-sequencing, we demonstrated unexpectedly high genetic variability among black grama plants in a 1 ha site within the Sevilleta National Wildlife Refuge in central New Mexico, suggesting some level of sexual reproduction. Three years of experimental, growing season drought reduced black grama survival and biomass (the latter by 96%), with clear genetic differentiation (higher F_ST) between plants succumbing to drought and those remaining alive. Reduced genetic variability in the surviving plants in drought plots indicated that the experimental drought had forced black grama populations through selection bottlenecks. These results suggest that foundation grass species, such as black grama, may experience rapid evolutionary change if future climates include more severe droughts.

Temporal changes in genetic diversity and forage yield of perennial ryegrass in monoculture and in combination with red clover in swards

Agricultural grasslands are often cultivated as mixtures of grasses and legumes, and an extensive body of literature is available regarding interspecific interactions, and how these relate to yield and agronomic performance. However, knowledge of the impact of intraspecific diversity on grassland functioning is scarce. We investigated these effects during a 4-year field trial established with perennial ryegrass (Lolium perenne) and red clover (Trifolium pratense). We simulated different levels of intraspecific functional diversity by sowing single cultivars or by combining cultivars with contrasting growth habits, in monospecific or bispecific settings (i.e. perennial ryegrass whether or not in combination with red clover). Replicate field plots were established for seven seed compositions. We determined yield parameters and monitored differences in genetic diversity in the ryegrass component among seed compositions, and temporal changes in the genetic composition and genetic diversity at the within plot level. The composition of cultivars of both species affected the yield and species abundance. In general, the presence of clover had a positive effect on the yield. The cultivar composition of the ryegrass component had a significant effect on the yield, both in monoculture, and in combination with clover. For the genetic analyses, we validated empirically that genotyping-by-sequencing of pooled samples (pool-GBS) is a suitable method for accurate measurement of population allele frequencies, and obtained a dataset of 22,324 SNPs with complete data. We present a method to investigate the temporal dynamics of cultivars in seed mixtures grown under field conditions, and show how cultivar abundances vary during subsequent years. We screened the SNP panel for outlier loci, putatively under selection during the cultivation period, but none were detected.

Genomewide signatures of selection in Epichloë reveal candidate genes for host specialization

Host specialization is a key process in ecological divergence and speciation of plant-associated fungi. The underlying determinants of host specialization are generally poorly understood, especially in endophytes, which constitute one of the most abundant components of the plant microbiome. We addressed the genetic basis of host specialization in two sympatric subspecies of grass-endophytic fungi from the Epichloë typhina complex: subsp. typhina and clarkii. The life cycle of these fungi entails unrestricted dispersal of gametes and sexual reproduction before infection of a new host, implying that the host imposes a selective barrier on viability of the progeny. We aimed to detect genes under divergent selection between subspecies, experiencing restricted gene flow due to adaptation to different hosts. Using pooled whole-genome sequencing data, we combined F_ST and D_XY population statistics in genome scans and detected 57 outlier genes showing strong differentiation between the two subspecies. Genomewide analyses of nucleotide diversity (π), Tajima's D and dN/dS ratios indicated that these genes have evolved under positive selection. Genes encoding secreted proteins were enriched among the genes showing evidence of positive selection, suggesting that molecular plant-fungus interactions are strong drivers of endophyte divergence. We focused on five genes encoding secreted proteins, which were further sequenced in 28 additional isolates collected across Europe to assess genetic variation in a larger sample size. Signature of positive selection in these isolates and putative identification of pathogenic function supports our findings that these genes represent strong candidates for host specialization determinants in Epichloë endophytes. Our results highlight the role of secreted proteins as key determinants of host specialization.

Whole-genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.

Identifying consistent allele frequency differences in studies of stratified populations

With increasing application of pooled‐sequencing approaches to population genomics robust methods are needed to accurately quantify allele frequency differences between populations. Identifying consistent differences across stratified populations can allow us to detect genomic regions under selection and that differ between populations with different histories or attributes. Current popular statistical tests are easily implemented in widely available software tools which make them simple for researchers to apply. However, there are potential problems with the way such tests are used, which means that underlying assumptions about the data are frequently violated.

These problems are highlighted by simulation of simple but realistic population genetic models of neutral evolution and the performance of different tests are assessed. We present alternative tests (including Generalised Linear Models [GLMs] with quasibinomial error structure) with attractive properties for the analysis of allele frequency differences and re‐analyse a published dataset.

The simulations show that common statistical tests for consistent allele frequency differences perform poorly, with high false positive rates. Applying tests that do not confound heterogeneity and main effects significantly improves inference. Variation in sequencing coverage likely produces many false positives and re‐scaling allele frequencies to counts out of a common value or an effective sample size reduces this effect.

Many researchers are interested in identifying allele frequencies that vary consistently across replicates to identify loci underlying phenotypic responses to selection or natural variation in phenotypes. Popular methods that have been suggested for this task perform poorly in simulations. Overall, quasibinomial GLMs perform better and also have the attractive feature of allowing correction for multiple testing by standard procedures and are easily extended to other designs.

Identifying Genetic Signatures of Natural Selection Using Pooled Population Sequencing in Picea abies

The joint inference of selection and past demography remain a costly and demanding task. We used next generation sequencing of two pools of 48 Norway spruce mother trees, one corresponding to the Fennoscandian domain, and the other to the Alpine domain, to assess nucleotide polymorphism at 88 nuclear genes. These genes are candidate genes for phenological traits, and most belong to the photoperiod pathway. Estimates of population genetic summary statistics from the pooled data are similar to previous estimates, suggesting that pooled sequencing is reliable. The nonsynonymous SNPs tended to have both lower frequency differences and lower F_ST values between the two domains than silent ones. These results suggest the presence of purifying selection. The divergence between the two domains based on synonymous changes was around 5 million yr, a time similar to a recent phylogenetic estimate of 6 million yr, but much larger than earlier estimates based on isozymes. Two approaches, one of them novel and that considers both F_ST and difference in allele frequencies between the two domains, were used to identify SNPs potentially under diversifying selection. SNPs from around 20 genes were detected, including genes previously identified as main target for selection, such as PaPRR3 and PaGI.

Pooled Enrichment Sequencing Identifies Diversity and Evolutionary Pressures at NLR Resistance Genes within a Wild Tomato Population

Nod-like receptors (NLRs) are nucleotide-binding domain and leucine-rich repeats containing proteins that are important in plant resistance signaling. Many of the known pathogen resistance (R) genes in plants are NLRs and they can recognize pathogen molecules directly or indirectly. As such, divergence and copy number variants at these genes are found to be high between species. Within populations, positive and balancing selection are to be expected if plants coevolve with their pathogens. In order to understand the complexity of R-gene coevolution in wild nonmodel species, it is necessary to identify the full range of NLRs and infer their evolutionary history. Here we investigate and reveal polymorphism occurring at 220 NLR genes within one population of the partially selfing wild tomato species Solanum pennellii. We use a combination of enrichment sequencing and pooling ten individuals, to specifically sequence NLR genes in a resource and cost-effective manner. We focus on the effects which different mapping and single nucleotide polymorphism calling software and settings have on calling polymorphisms in customized pooled samples. Our results are accurately verified using Sanger sequencing of polymorphic gene fragments. Our results indicate that some NLRs, namely 13 out of 220, have maintained polymorphism within our S. pennellii population. These genes show a wide range of πN/πS ratios and differing site frequency spectra. We compare our observed rate of heterozygosity with expectations for this selfing and bottlenecked population. We conclude that our method enables us to pinpoint NLR genes which have experienced natural selection in their habitat.