Population-genetic inference from pooled-sequencing data

Meiotic drive against chromosome fusions in butterfly hybrids

Species frequently differ in the number and structure of chromosomes they harbor, but individuals that are heterozygous for chromosomal rearrangements may suffer from reduced fitness. Chromosomal rearrangements like fissions and fusions can hence serve as a mechanism for speciation between incipient lineages, but their evolution poses a paradox. How can rearrangements get fixed between populations if heterozygotes have reduced fitness? One solution is that this process predominantly occurs in small and isolated populations, where genetic drift can override natural selection. However, fixation is also more likely if a novel rearrangement is favored by a transmission bias, such as meiotic drive. Here, we investigate chromosomal transmission distortion in hybrids between two wood white (Leptidea sinapis) butterfly populations with extensive karyotype differences. Using data from two different crossing experiments, we uncover that there is a transmission bias favoring the ancestral chromosomal state for derived fusions, a result that shows that chromosome fusions actually can fix in populations despite being counteracted by meiotic drive. This means that meiotic drive not only can promote runaway chromosome number evolution and speciation, but also that it can be a conservative force acting against karyotypic change and the evolution of reproductive isolation. Based on our results, we suggest a mechanistic model for why chromosome fusion mutations may be opposed by meiotic drive and discuss factors contributing to karyotype evolution in Lepidoptera.

Estimating microhaplotype allele frequencies from low-coverage or pooled sequencing data

BACKGROUND

Microhaplotypes have the potential to be more cost-effective than SNPs for applications that require genetic panels of highly variable loci. However, development of microhaplotype panels is hindered by a lack of methods for estimating microhaplotype allele frequency from low-coverage whole genome sequencing or pooled sequencing (pool-seq) data.

RESULTS

We developed new methods for estimating microhaplotype allele frequency from low-coverage whole genome sequence and pool-seq data. We validated these methods using datasets from three non-model organisms. These methods allowed estimation of allele frequency and expected heterozygosity at depths routinely achieved from pooled sequencing.

CONCLUSIONS

These new methods will allow microhaplotype panels to be designed using low-coverage WGS and pool-seq data to discover and evaluate candidate loci. The python script implementing the two methods and documentation are available at https://www.github.com/delomast/mhFromLowDepSeq .

FREQ-Seq2: a method for precise high-throughput combinatorial quantification of allele frequencies

The accurate determination of allele frequencies is crucially important across a wide range of problems in genetics, such as developing population genetic models, making inferences from genome-wide association studies, determining genetic risk for diseases, as well as other scientific and medical applications. Furthermore, understanding how allele frequencies change over time in populations is central to ascertaining their evolutionary dynamics. We present a precise, efficient, and economical method (FREQ-Seq2) for quantifying the relative frequencies of different alleles at loci of interest in mixed population samples. Through the creative use of paired barcode sequences, we exponentially increased the throughput of the original FREQ-Seq method from 48 to 2,304 samples. FREQ-Seq2 can be targeted to specific genomic regions of interest, which are amplified using universal barcoded adapters to generate Illumina sequencing libraries. Our enhanced method, available as a kit along with open-source software for analyzing sequenced libraries, enables the detection and removal of errors that are undetectable in the original FREQ-Seq method as well as other conventional methods for allele frequency quantification. Finally, we validated the performance of our sequencing-based approach with a highly multiplexed set of control samples as well as a competitive evolution experiment in Escherichia coli and compare the latter to estimates derived from manual colony counting. Our analyses demonstrate that FREQ-Seq2 is flexible, inexpensive, and produces large amounts of data with low error, low noise, and desirable statistical properties. In summary, FREQ-Seq2 is a powerful method for quantifying allele frequency that provides a versatile approach for profiling mixed populations.

Genomic selection pressure discovery using site-frequency spectrum and reduced local variability statistics in Pakistani Dera-Din-Panah goat

BACKGROUND

Population geneticists have long sought to comprehend various selection traces accumulated in the goat genome due to natural or human driven artificial selection through breeding practices, which led the wild animals to domestication, so understanding evolutionary process may helpful to utilize the full genetic potential of goat genome.

METHODS AND RESULTS

As a step forward to pinpoint the selection signals in Pakistani Dera-Din-Panah (DDP) goat, whole-genome pooled sequencing (n = 12) was performed, and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signature statistics were applied using four site-frequency spectrum (SFS) methods (Tajima's D ([Formula: see text]), Fay and Wu's H ([Formula: see text]), Zeng's E ([Formula: see text]), [Formula: see text]) and one reduced local variability approach named pooled heterozygosity ([Formula: see text]). The under-selection regions were annotated with significant threshold values of [Formula: see text]≥4.7, [Formula: see text]≥6, [Formula: see text]≥2.5, Pool-HMM ≥ 12, and [Formula: see text]≥5 that resulted in accumulative 364 candidate gene hits. The highest genomic selection signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, and 27 and harbor ADAMTS6, CWC27, RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3, FH, MFHAS1, KLKB1, RRM1, KMO, SPEF2, F11, KIT, KMO, ERI1, ATP8B4, and RHOG genes. Next, the validation of our captured genomic hits was also performed by more than one applied statistics which harbor meat production, immunity, and reproduction associated genes to strengthen our hypothesis of under-selection traits in this Pakistani goat breed. Furthermore, common candidate genes captured by more than one statistical method were subjected to gene ontology and KEGG pathway analysis to get insights of particular biological processes associated with this goat breed.

CONCLUSION

Current perception of genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other economically important traits of medium to large body size, milk, and fiber production by updating the genomic insight driven breeding strategies to boost the livestock and agriculture-based economy of the country.

Geographic Variation in Genomic Signals of Admixture Between Two Closely Related European Sepsid Fly Species

The extent of interspecific gene flow and its consequences for the initiation, maintenance, and breakdown of species barriers in natural systems remain poorly understood. Interspecific gene flow by hybridization may weaken adaptive divergence, but can be overcome by selection against hybrids, which may ultimately promote reinforcement. An informative step towards understanding the role of gene flow during speciation is to describe patterns of past gene flow among extant species. We investigate signals of admixture between allopatric and sympatric populations of the two closely related European dung fly species Sepsis cynipsea and S. neocynipsea (Diptera: Sepsidae). Based on microsatellite genotypes, we first inferred a baseline demographic history using Approximate Bayesian Computation. We then used genomic data from pooled DNA of natural and laboratory populations to test for past interspecific gene flow based on allelic configurations discordant with the inferred population tree (ABBA-BABA test with D-statistic). Comparing the detected signals of gene flow with the contemporary geographic relationship among interspecific pairs of populations (sympatric vs. allopatric), we made two contrasting observations. At one site in the French Cevennes, we detected an excess of past interspecific gene flow, while at two sites in Switzerland we observed lower signals of past microsatellite genotypes gene flow among populations in sympatry compared to allopatric populations. These results suggest that the species boundaries between these two species depend on the past and/or present eco-geographic context in Europe, which indicates that there is no uniform link between contemporary geographic proximity and past interspecific gene flow in natural populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11692-023-09612-5.

A macroecological perspective on genetic diversity in the human gut microbiome

While the human gut microbiome has been intensely studied, we have yet to obtain a sufficient understanding of the genetic diversity that it harbors. Research efforts have demonstrated that a considerable fraction of within-host genetic variation in the human gut is driven by the ecological dynamics of co-occurring strains belonging to the same species, suggesting that an ecological lens may provide insight into empirical patterns of genetic diversity. Indeed, an ecological model of self-limiting growth and environmental noise known as the Stochastic Logistic Model (SLM) was recently shown to successfully predict the temporal dynamics of strains within a single human host. However, its ability to predict patterns of genetic diversity across human hosts has yet to be tested. In this manuscript I determine whether the predictions of the SLM explain patterns of genetic diversity across unrelated human hosts for 22 common microbial species. Specifically, the stationary distribution of the SLM explains the distribution of allele frequencies across hosts and predicts the fraction of hosts harboring a given allele (i.e., prevalence) for a considerable fraction of sites. The accuracy of the SLM was correlated with independent estimates of strain structure, suggesting that patterns of genetic diversity in the gut microbiome follow statistically similar forms across human hosts due to the existence of strain-level ecology.

Estimating linkage disequilibrium and selection from allele frequency trajectories

Genetic sequences collected over time provide an exciting opportunity to study natural selection. In such studies, it is important to account for linkage disequilibrium to accurately measure selection and to distinguish between selection and other effects that can cause changes in allele frequencies, such as genetic hitchhiking or clonal interference. However, most high-throughput sequencing methods cannot directly measure linkage due to short-read lengths. Here we develop a simple method to estimate linkage disequilibrium from time-series allele frequencies. This reconstructed linkage information can then be combined with other inference methods to infer the fitness effects of individual mutations. Simulations show that our approach reliably outperforms inference that ignores linkage disequilibrium and, with sufficient sampling, performs similarly to inference using the true linkage information. We also introduce two regularization methods derived from random matrix theory that help to preserve its performance under limited sampling effects. Overall, our method enables the use of linkage-aware inference methods even for data sets where only allele frequency time series are available.

Viral variant-resolved wastewater surveillance of SARS-CoV-2 at national scale

SARS-CoV-2 surveillance by wastewater-based epidemiology is poised to provide a complementary approach to sequencing individual cases. However, robust quantification of variants and de novo detection of emerging variants remains challenging for existing strategies. We deep sequenced 3,413 wastewater samples representing 94 municipal catchments, covering >59% of the population of Austria, from December 2020 to February 2022. Our system of variant quantification in sewage pipeline designed for robustness (termed VaQuERo) enabled us to deduce the spatiotemporal abundance of predefined variants from complex wastewater samples. These results were validated against epidemiological records of >311,000 individual cases. Furthermore, we describe elevated viral genetic diversity during the Delta variant period, provide a framework to predict emerging variants and measure the reproductive advantage of variants of concern by calculating variant-specific reproduction numbers from wastewater. Together, this study demonstrates the power of national-scale WBE to support public health and promises particular value for countries without extensive individual monitoring.

Genomic signatures of selection associated with benzimidazole drug treatments in Haemonchus contortus field populations

Genome-wide methods offer a powerful approach to detect signatures of drug selection. However, limited availability of suitable reference genomes and the difficulty of obtaining field populations with well-defined, distinct drug treatment histories mean there is little information on the signatures of selection in parasitic nematodes and on how best to detect them. This study addresses these knowledge gaps by using field populations of Haemonchus contortus with well-defined benzimidazole treatment histories, leveraging a recently completed chromosomal-scale reference genome assembly. We generated a panel of 49,393 genomic markers to genotype 20 individual adult worms from each of four H. contortus populations: two from closed sheep flocks with an approximate 20 year history of frequent benzimidazole treatment, and two populations with a history of little or no treatment. Sampling occurred in the same geographical region to limit genetic differentiation and maximise the detection sensitivity. A clear signature of selection was detected on chromosome I, centred on the isotype-1 β-tubulin gene. Two additional, but weaker, signatures of selection were detected; one near the middle of chromosome I spanning 3.75 Mbp and 259 annotated genes, and one on chromosome II spanning a region of 3.3 Mbp and 206 annotated genes, including the isotype-2 β-tubulin locus. We also assessed how sensitivity was impacted by sequencing depth, worm number, and pooled versus individual worm sequence data. This study provides the first known direct genome-wide evidence for any parasitic nematode, that the isotype-1 β-tubulin gene is quantitatively the single most important benzimidazole resistance locus. It also identified two additional genomic regions that likely contain benzimidazole resistance loci of secondary importance. This study provides an experimental framework to maximise the power of genome-wide approaches to detect signatures of selection driven by anthelmintic drug treatments in field populations of parasitic nematodes.

Identification of a candidate sex determination gene in Culaea inconstans suggests convergent recruitment of an Amh duplicate in two lineages of stickleback

Sex chromosomes vary greatly in their age and levels of differentiation across the tree of life. This variation is largely due to the rates of sex chromosome turnover in different lineages; however, we still lack an explanation for why sex chromosomes are so conserved in some lineages (e.g. mammals, birds) but so labile in others (e.g. teleosts, amphibians). To identify general mechanisms driving transitions in sex determination systems or forces which favour their conservation, we first require empirical data on sex chromosome systems from multiple lineages. Stickleback fishes are a valuable model lineage for the study of sex chromosome evolution due to variation in sex chromosome systems between closely-related species. Here, we identify the sex chromosome and a strong candidate for the master sex determination gene in the brook stickleback, Culaea inconstans. Using whole-genome sequencing of wild-caught samples and a lab cross, we identify AmhY, a male specific duplication of the gene Amh, as the candidate master sex determination gene. AmhY resides on Chromosome 20 in C. inconstans and is likely a recent duplication, as both AmhY and the sex-linked region of Chromosome 20 show little sequence divergence. Importantly, this duplicate AmhY represents the second independent duplication and recruitment of Amh as the sex determination gene in stickleback and the eighth example known across teleosts. We discuss this convergence in the context of sex chromosome turnovers and the role that the Amh/AmhrII pathway, which is crucial for sex determination, may play in the evolution of sex chromosomes in teleosts.

A pan-genome data structure induced by pooled sequencing facilitates variant mining in heterogeneous germplasm

Valuable genetic variation lies unused in gene banks due to the difficulty of exploiting heterogeneous germplasm accessions. Advances in molecular breeding, including transgenics and genome editing, present the opportunity to exploit hidden sequence variation directly. Here we describe the pan-genome data structure induced by whole-genome sequencing of pooled individuals from wild populations of Patellifolia spp., a source of disease resistance genes for the related crop species sugar beet (Beta vulgaris). We represent the pan-genome as a map of reads from pooled sequencing of a heterogeneous population sample to a reference genome, plus a BLAST data base of the mapped reads. We show that this basic data structure can be queried by reference genome position or homology to identify sequence variants present in the wild relative, at genes of agronomic interest in the crop, a process known as allele or variant mining. Further we demonstrate the possibility of cataloging variants in all Patellifolia genomic regions that have corresponding single copy orthologous regions in sugar beet. The data structure, termed a "pooled read archive," can be produced, altered, and queried using standard tools to facilitate discovery of agronomically-important sequence variation.

Supplementary information

The online version contains supplementary material available at 10.1007/s11032-022-01308-6.

Detecting Genetic Variation of Colonizing Streptococcus agalactiae Genomes in Humans: A Precision Protocol

Deciphering the genotypic diversity of within-individual pathogens and verifying the evolutionary model can help elucidate resistant genotypes, virulent subpopulations, and the mechanism of opportunistic pathogenicity. However, observed polymorphic mutations (PMs) are rare and difficult to be detected in the “dominant-lineage” model of bacterial infection due to the low frequency. The four pooled group B Streptococcus (GBS) samples were collected from the genital tracts of healthy pregnant women, and the pooled samples and the isogenic controls were genomically sequenced. Using the PMcalling program, we detected the PMs in samples and compared the results between two technical duplicates, GBS-M001T and GBS-M001C. Tested with simulated datasets, the PMcalling program showed high sensitivity especially in low-frequency PMs and reasonable specificity. The genomic sequence data from pooled samples of GBS colonizing carrier pregnant women were analyzed, and few high-frequency PMs and some low-frequency PMs were discovered, indicating a dominant-lineage evolution model. The PMs mainly were nonsynonymous and enriched in quorum sensing, glycolysis/gluconeogenesis, ATP-binding cassette (ABC) transporters, etc., suggesting antimicrobial or environmental selective pressure. The re-analysis of the published Burkholderia dolosa data showed a diverse-community model, and only a few low-frequency PMs were shared between different individuals. Genes of general control non-repressible 5-related N-acetyltransferases family, major facilitator superfamily (MFS) transporter, and ABC transporter were positive selection candidates. Our findings indicate an unreported nature of the dominant-lineage model of GBS colonization in healthy women, and a formerly not observed mutation pool in a colonized microbial community, possibly maintained by selection pressure.

Selection of genome-wide SNPs for pooled allelotyping assays useful for population monitoring

Parasitic worms are serious pests of humans, livestock and crops worldwide. Multiple management strategies are employed in order to reduce their impact, and some of these may affect their genome and population allelic frequency distribution. The evolution of chemical resistance, ecological changes, and pest dispersal have allowed an increasing number of pests to become difficult to control with current management methods. Their lifestyle limits the use of ecological and individual-based management of populations. There is a need to develop rapid, affordable, and simple diagnostics to assess the efficacy of management strategies and delay the evolution of resistance to these strategies. This study presents a multi-locus, equal-representation, whole genome pooled SNPs selection approach as a monitoring tool for the ovine nematode parasite Haemonchus contortus. The SNP selection method used two reference genomes of different quality, then validated these SNPs against a high-quality recent genome assembly. From over 11 million high-quality SNPs identified, 334 SNPs were selected, of which 262 were species-specific, yielded similar allele frequencies when assessed as multiple individuals or as pools of individuals, and suitable to distinguish mixed nematode isolate pools from single isolate pools. As a proof-of-concept, 21 Australian H. contortus populations with various phenotypes and genotypes were screened. This analysis confirmed the overall low-level of genetic differentiation between populations collected from the field, but clearly identifying highly inbred populations, and populations showing genetic signatures associated with chemical resistance. The analysis showed that 66% of the SNPs were necessary for stability in assessing population genetic patterns, and SNP pairs did not show linkage according to allelic frequencies across the 21 populations. This method demonstrates that ongoing monitoring of parasite allelic frequencies and genetic changes can be achieved as a management assessment tool to identify drug-treatment failure, population incursions, and inbreeding signatures due to selection. The SNP selection method could also be applied to other parasite species.

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.

Select and Sequence of a Segregating Sugar Beet Population Provides Genomic Perspective of Host Resistance to Seedling Rhizoctonia solani Infection

Understanding the genetic basis of polygenic traits is a major challenge in agricultural species, especially in non-model systems. Select and sequence (SnS) experiments carried out within existing breeding programs provide a means to simultaneously identify the genomic background of a trait while improving the mean phenotype for a population. Using pooled whole genome sequencing (WGS) of selected and unselected bulks derived from a synthetic outcrossing sugar beet population EL57 (PI 663212), which segregates for seedling rhizoctonia resistance, we identified a putative genomic background involved in conditioning a resistance phenotype. Population genomic parameters were estimated to measure fixation (He), genome divergence (F ST ), and allele frequency changes between bulks (DeltaAF). We report on the genome wide patterns of variation resulting from selection and highlight specific genomic features associated with resistance. Expected heterozygosity (He) showed an increased level of fixation in the resistant bulk, indicating a greater selection pressure was applied. In total, 1,311 biallelic loci were detected as significant FST outliers (p < 0.01) in comparisons between the resistant and susceptible bulks. These loci were detected in 206 regions along the chromosomes and contained 275 genes. We estimated changes in allele frequency between bulks resulting from selection for resistance by leveraging the allele frequencies of an unselected bulk. DeltaAF was a more stringent test of selection and recovered 186 significant loci, representing 32 genes, all of which were also detected using FST. Estimates of population genetic parameters and statistical significance were visualized with respect to the EL10.2 physical map and produced a candidate gene list that was enriched for function in cell wall metabolism and plant disease resistance, including pathogen perception, signal transduction, and pathogen response. Specific variation associated with these genes was also reported and represents genetic markers for validation and prediction of resistance to Rhizoctonia. Select and sequence experiments offer a means to characterize the genetic base of sugar beet, inform selection within breeding programs, and prioritize candidate variation for functional studies.

Slow Recovery from Inbreeding Depression Generated by the Complex Genetic Architecture of Segregating Deleterious Mutations

The deleterious effects of inbreeding have been of extreme importance to evolutionary biology, but it has been difficult to characterize the complex interactions between genetic constraints and selection that lead to fitness loss and recovery after inbreeding. Haploid organisms and selfing organisms like the nematode Caenorhabditis elegans are capable of rapid recovery from the fixation of novel deleterious mutation; however, the potential for recovery and genomic consequences of inbreeding in diploid, outcrossing organisms are not well understood. We sought to answer two questions: 1) Can a diploid, outcrossing population recover from inbreeding via standing genetic variation and new mutation? and 2) How does allelic diversity change during recovery? We inbred C. remanei, an outcrossing relative of C. elegans, through brother-sister mating for 30 generations followed by recovery at large population size. Inbreeding reduced fitness but, surprisingly, recovery from inbreeding at large populations sizes generated only very moderate fitness recovery after 300 generations. We found that 65% of ancestral single nucleotide polymorphisms (SNPs) were fixed in the inbred population, far fewer than the theoretical expectation of ∼99%. Under recovery, 36 SNPs across 30 genes involved in alimentary, muscular, nervous, and reproductive systems changed reproducibly across replicates, indicating that strong selection for fitness recovery does exist. Our results indicate that recovery from inbreeding depression via standing genetic variation and mutation is likely to be constrained by the large number of segregating deleterious variants present in natural populations, limiting the capacity for recovery of small populations.

Drosophila Evolution over Space and Time (DEST): A New Population Genomics Resource

Drosophila melanogaster is a leading model in population genetics and genomics, and a growing number of whole-genome data sets from natural populations of this species have been published over the last years. A major challenge is the integration of disparate data sets, often generated using different sequencing technologies and bioinformatic pipelines, which hampers our ability to address questions about the evolution of this species. Here we address these issues by developing a bioinformatics pipeline that maps pooled sequencing (Pool-Seq) reads from D. melanogaster to a hologenome consisting of fly and symbiont genomes and estimates allele frequencies using either a heuristic (PoolSNP) or a probabilistic variant caller (SNAPE-pooled). We use this pipeline to generate the largest data repository of genomic data available for D. melanogaster to date, encompassing 271 previously published and unpublished population samples from over 100 locations in >20 countries on four continents. Several of these locations have been sampled at different seasons across multiple years. This data set, which we call Drosophila Evolution over Space and Time (DEST), is coupled with sampling and environmental metadata. A web-based genome browser and web portal provide easy access to the SNP data set. We further provide guidelines on how to use Pool-Seq data for model-based demographic inference. Our aim is to provide this scalable platform as a community resource which can be easily extended via future efforts for an even more extensive cosmopolitan data set. Our resource will enable population geneticists to analyze spatiotemporal genetic patterns and evolutionary dynamics of D. melanogaster populations in unprecedented detail.

The Limits to Estimating Population-Genetic Parameters with Temporal Data

The ability to obtain genome-wide sequences of very large numbers of individuals from natural populations raises questions about optimal sampling designs and the limits to extracting information on key population-genetic parameters from temporal-survey data. Methods are introduced for evaluating whether observed temporal fluctuations in allele frequencies are consistent with the hypothesis of random genetic drift, and expressions for the expected sampling variances for the relevant statistics are given in terms of sample sizes and numbers. Estimation methods and aspects of statistical reliability are also presented for the mean and temporal variance of selection coefficients. For nucleotide sites that pass the test of neutrality, the current effective population size can be estimated by a method of moments, and expressions for its sampling variance provide insight into the degree to which such methodology can yield meaningful results under alternative sampling schemes. Finally, some caveats are raised regarding the use of the temporal covariance of allele-frequency change to infer selection. Taken together, these results provide a statistical view of the limits to population-genetic inference in even the simplest case of a closed population.

Clinal and seasonal changes are correlated in Drosophila melanogaster natural populations

Spatial and seasonal variations in the environment are ubiquitous. Environmental heterogeneity can affect natural populations and lead to covariation between environment and allele frequencies. Drosophila melanogaster is known to harbor polymorphisms that change both with latitude and seasons. Identifying the role of selection in driving these changes is not trivial, because nonadaptive processes can cause similar patterns. Given the environment changes in similar ways across seasons and along the latitudinal gradient, one promising approach may be to look for parallelism between clinal and seasonal changes. Here, we test whether there is a genome-wide correlation between clinal and seasonal changes, and whether the pattern is consistent with selection. Allele frequency estimates were obtained from pooled samples from seven different locations along the east coast of the United States, and across seasons within Pennsylvania. We show that there is a genome-wide correlation between clinal and seasonal variations, which cannot be explained by linked selection alone. This pattern is stronger in genomic regions with higher functional content, consistent with natural selection. We derive a way to biologically interpret these correlations and show that around 3.7% of the common, autosomal variants could be under parallel seasonal and spatial selection. Our results highlight the contribution of natural selection in driving fluctuations in allele frequencies in natural fly populations and point to a shared genomic basis to climate adaptation that happens over space and time in D. melanogaster.

Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution

Similar forms often evolve repeatedly in nature, raising long-standing questions about the underlying mechanisms. Here, we use repeated evolution in stickleback to identify a large set of genomic loci that change recurrently during colonization of freshwater habitats by marine fish. The same loci used repeatedly in extant populations also show rapid allele frequency changes when new freshwater populations are experimentally established from marine ancestors. Marked genotypic and phenotypic changes arise within 5 years, facilitated by standing genetic variation and linkage between adaptive regions. Both the speed and location of changes can be predicted using empirical observations of recurrence in natural populations or fundamental genomic features like allelic age, recombination rates, density of divergent loci, and overlap with mapped traits. A composite model trained on these stickleback features can also predict the location of key evolutionary loci in Darwin's finches, suggesting that similar features are important for evolution across diverse taxa.

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.

Big Data in Conservation Genomics: Boosting Skills, Hedging Bets, and Staying Current in the Field

A current challenge in the fields of evolutionary, ecological, and conservation genomics is balancing production of large-scale datasets with additional training often required to handle such datasets. Thus, there is an increasing need for conservation geneticists to continually learn and train to stay up-to-date through avenues such as symposia, meetings, and workshops. The ConGen meeting is a near-annual workshop that strives to guide participants in understanding population genetics principles, study design, data processing, analysis, interpretation, and applications to real-world conservation issues. Each year of ConGen gathers a diverse set of instructors, students, and resulting lectures, hands-on sessions, and discussions. Here, we summarize key lessons learned from the 2019 meeting and more recent updates to the field with a focus on big data in conservation genomics. First, we highlight classical and contemporary issues in study design that are especially relevant to working with big datasets, including the intricacies of data filtering. We next emphasize the importance of building analytical skills and simulating data, and how these skills have applications within and outside of conservation genetics careers. We also highlight recent technological advances and novel applications to conservation of wild populations. Finally, we provide data and recommendations to support ongoing efforts by ConGen organizers and instructors-and beyond-to increase participation of underrepresented minorities in conservation and eco-evolutionary sciences. The future success of conservation genetics requires both continual training in handling big data and a diverse group of people and approaches to tackle key issues, including the global biodiversity-loss crisis.

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.

Genetic and phenotypic variation exhibit both predictable and stochastic patterns across an intertidal fish metapopulation

Interactions among selection, gene flow, and drift affect the trajectory of adaptive evolution. In natural populations, the direction and magnitude of these processes can be variable across different spatial, temporal, or ontogenetic scales. Consequently, variability in evolutionary processes affects the predictability or stochasticity of microevolutionary outcomes. We studied an intertidal fish, Bathygobius cocosensis (Bleeker, 1854), to understand how space, time, and life stage structure genetic and phenotypic variation in a species with potentially extensive dispersal and a complex life cycle (larval dispersal preceding benthic recruitment). We sampled juvenile and adult life stages, at three sites, over three years. Genome-wide SNPs uncovered a pattern of chaotic genetic patchiness, that is, weak-but-significant patchy spatial genetic structure that was variable through time and between life stages. Outlier locus analyses suggested that targets of spatially divergent selection were mostly temporally variable, though a significant number of spatial outlier loci were shared between life stages. Head shape, a putatively ecologically responsive (adaptive) phenotype in B. cocosensis also exhibited high temporal variability within sites. However, consistent spatial relationships between sites indicated that environmental similarities among sites may generate predictable phenotype distributions across space. Our study highlights the complex microevolutionary dynamics of marine systems, where consideration of multiple ecological dimensions can reveal both predictable and stochastic patterns in the distributions of genetic and phenotypic variation. Such considerations probably apply to species that possess short, complex life cycles, have large dispersal potential and fecundities, and that inhabit heterogeneous environments.

The Compact Macronuclear Genome of the Ciliate Halteria grandinella: A Transcriptome-Like Genome with 23,000 Nanochromosomes

How to achieve protein diversity by genome and transcriptome processing is essential for organismal complexity and adaptation. The present work identifies that the macronuclear genome of Halteria grandinella, a cosmopolitan unicellular eukaryote, is composed almost entirely of gene-sized nanochromosomes with extremely short nongenic regions.

How to achieve protein diversity by genome and transcriptome processing is essential for organismal complexity and adaptation. The present work identifies that the macronuclear genome of Halteria grandinella, a cosmopolitan unicellular eukaryote, is composed almost entirely of gene-sized nanochromosomes with extremely short nongenic regions. This challenges our usual understanding of chromosomal structure and suggests the possibility of novel mechvanisms in transcriptional regulation. Comprehensive analysis of multiple data sets reveals that Halteria transcription dynamics are influenced by: (i) nonuniform nanochromosome copy numbers correlated with gene-expression level; (ii) dynamic alterations at both the DNA and RNA levels, including alternative internal eliminated sequence (IES) deletions during macronucleus formation and large-scale alternative splicing in transcript maturation; and (iii) extremely short 5′ and 3′ untranslated regions (UTRs) and universal TATA box-like motifs in the compact 5′ subtelomeric regions of most chromosomes. This study broadens the view of ciliate biology and the evolution of unicellular eukaryotes, and identifies Halteria as one of the most compact known eukaryotic genomes, indicating that complex cell structure does not require complex gene architecture.

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.

Genome-wide variation and transcriptional changes in diverse developmental processes underlie the rapid evolution of seasonal adaptation

Many organisms enter a dormant state in their life cycle to deal with predictable changes in environments over the course of a year. The timing of dormancy is therefore a key seasonal adaptation, and it evolves rapidly with changing environments. We tested the hypothesis that differences in the timing of seasonal activity are driven by differences in the rate of development during diapause in Rhagoletis pomonella, a fly specialized to feed on fruits of seasonally limited host plants. Transcriptomes from the central nervous system across a time series during diapause show consistent and progressive changes in transcripts participating in diverse developmental processes, despite a lack of gross morphological change. Moreover, population genomic analyses suggested that many genes of small effect enriched in developmental functional categories underlie variation in dormancy timing and overlap with gene sets associated with development rate in Drosophila melanogaster Our transcriptional data also suggested that a recent evolutionary shift from a seasonally late to a seasonally early host plant drove more rapid development during diapause in the early fly population. Moreover, genetic variants that diverged during the evolutionary shift were also enriched in putative cis regulatory regions of genes differentially expressed during diapause development. Overall, our data suggest polygenic variation in the rate of developmental progression during diapause contributes to the evolution of seasonality in R. pomonella We further discuss patterns that suggest hourglass-like developmental divergence early and late in diapause development and an important role for hub genes in the evolution of transcriptional divergence.

Population-level inferences from environmental DNA-Current status and future perspectives

Environmental DNA (eDNA) extracted from water samples has recently shown potential as a valuable source of population genetic information for aquatic macroorganisms. This approach offers several potential advantages compared with conventional tissue-based methods, including the fact that eDNA sampling is noninvasive and generally more cost-efficient. Currently, eDNA approaches have been limited to single-marker studies of mitochondrial DNA (mtDNA), and the relationship between eDNA haplotype composition and true haplotype composition still needs to be thoroughly verified. This will require testing of bioinformatic and statistical software to correct for erroneous sequences, as well as biases and random variation in relative sequence abundances. However, eDNA-based population genetic methods have far-reaching potential for both basic and applied research. In this paper, we present a brief overview of the achievements of eDNA-based population genetics to date, and outline the prospects for future developments in the field, including the estimation of nuclear DNA (nuDNA) variation and epigenetic information. We discuss the challenges associated with eDNA samples as opposed to those of individual tissue samples and assess whether eDNA might offer additional types of information unobtainable with tissue samples. Lastly, we provide recommendations for determining whether an eDNA approach would be a useful and suitable choice in different research settings. We limit our discussion largely to contemporary aquatic systems, but the advantages, challenges, and perspectives can to a large degree be generalized to eDNA studies with a different spatial and temporal focus.

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.

Distinct genomic signals of lifespan and life history evolution in response to postponed reproduction and larval diet in Drosophila

Reproduction and diet are two major factors controlling the physiology of aging and life history, but how they interact to affect the evolution of longevity is unknown. Moreover, although studies of large-effect mutants suggest an important role of nutrient sensing pathways in regulating aging, the genetic basis of evolutionary changes in lifespan remains poorly understood. To address these questions, we analyzed the genomes of experimentally evolved Drosophila melanogaster populations subjected to a factorial combination of two selection regimes: reproductive age (early versus postponed), and diet during the larval stage ("low," "control," "high"), resulting in six treatment combinations with four replicate populations each. Selection on reproductive age consistently affected lifespan, with flies from the postponed reproduction regime having evolved a longer lifespan. In contrast, larval diet affected lifespan only in early-reproducing populations: flies adapted to the "low" diet lived longer than those adapted to control diet. Here, we find genomic evidence for strong independent evolutionary responses to either selection regime, as well as loci that diverged in response to both regimes, thus representing genomic interactions between the two. Overall, we find that the genomic basis of longevity is largely independent of dietary adaptation. Differentiated loci were not enriched for "canonical" longevity genes, suggesting that naturally occurring genic targets of selection for longevity differ qualitatively from variants found in mutant screens. Comparing our candidate loci to those from other "evolve and resequence" studies of longevity demonstrated significant overlap among independent experiments. This suggests that the evolution of longevity, despite its presumed complex and polygenic nature, might be to some extent convergent and predictable.

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.

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.

Patterns of genomic differentiation between two Lake Victoria cichlid species, Haplochromis pyrrhocephalus and H. sp. 'macula'

BACKGROUND

The molecular basis of the incipient stage of speciation is still poorly understood. Cichlid fish species in Lake Victoria are a prime example of recent speciation events and a suitable system to study the adaptation and reproductive isolation of species.

RESULTS

Here, we report the pattern of genomic differentiation between two Lake Victoria cichlid species collected in sympatry, Haplochromis pyrrhocephalus and H. sp. 'macula,' based on the pooled genome sequences of 20 individuals of each species. Despite their ecological differences, population genomics analyses demonstrate that the two species are very close to a single panmictic population due to extensive gene flow. However, we identified 21 highly differentiated short genomic regions with fixed nucleotide differences. At least 15 of these regions contained genes with predicted roles in adaptation and reproductive isolation, such as visual adaptation, circadian clock, developmental processes, adaptation to hypoxia, and sexual selection. The nonsynonymous fixed differences in one of these genes, LWS, were reported as substitutions causing shift in absorption spectra of LWS pigments. Fixed differences were found in the promoter regions of four other differentially expressed genes, indicating that these substitutions may alter gene expression levels.

CONCLUSIONS

These diverged short genomic regions may have contributed to the differentiation of two ecologically different species. Moreover, the origins of adaptive variants within the differentiated regions predate the geological formation of Lake Victoria; thus Lake Victoria cichlid species diversified via selection on standing genetic variation.

Increased burden of rare deleterious variants of the KCNQ1 gene in patients with large‑vessel ischemic stroke

The impact of rare and damaging variants in genes associated with platelet function in large‑vessel ischemic stroke (LVIS) remains unknown. The aim of this study was to investigate the contribution of some of these variants to the genetic susceptibility to LVIS in Polish patients using a deep re‑sequencing of 54 selected genes, coding for proteins associated with altered platelet function. Targeted pooled re‑sequencing (Illumina HiSeq 2500) was performed on genomic DNA of 500 cases (patients with history of clinically proven diagnosis of LVIS) and 500 age‑, smoking status‑, and sex‑matched controls (no history of any type of stroke), and from the same population as patients with LVIS. After quality control and prioritization based on allele frequency and damaging probability, individual genotyping of all deleterious rare variants was performed in patients from the original cohort, and stratified to concomitant cardiac conditions differing between the study and stroke groups. We demonstrated a statistically significant increase in the number of rare and potentially damaging variants in some of the investigated genes in the LVIS pool (an increase in the genomic variants burden). Furthermore, we identified an association between LVIS and 6 rare functional and damaging variants in the Kv7.1 potassium channel gene (KCNQ1). The predicted functional properties (partial loss‑of function) for the three most damaging variants in KCNQ1 coding locus were further confirmed in vitro by analyzing the membrane potential changes in cell lines co‑transfected heterogeneously with human muscarinic type 1 receptor and wild‑type or mutated KCNQ1 cDNA constructs using fluorescence imaging plate reader. The study demonstrated an increased rare variants burden for 54 genes associated with platelet function, and identified a putative role for rare damaging variants in the KCNQ1 gene on LVIS susceptibility in the Polish population.

Extreme copy number variation at a tRNA ligase gene affecting phenology and fitness in yellow monkeyflowers

Copy number variation (CNV) is a major part of the genetic diversity segregating within populations, but remains poorly understood relative to single nucleotide variation. Here, we report on a tRNA ligase gene (Migut.N02091; RLG1a) exhibiting unprecedented, and fitness-relevant, CNV within an annual population of the yellow monkeyflower Mimulus guttatus. RLG1a variation was associated with multiple traits in pooled population sequencing (PoolSeq) scans of phenotypic and phenological cohorts. Resequencing of inbred lines revealed intermediate-frequency three-copy variants of RLG1a (trip+; 5/35 = 14%), and trip+ lines exhibited elevated RLG1a expression under multiple conditions. trip+ carriers, in addition to being over-represented in late-flowering and large-flowered PoolSeq populations, flowered later under stressful conditions in a greenhouse experiment (p < 0.05). In wild population samples, we discovered an additional rare RLG1a variant (high+) that carries 250-300 copies of RLG1a totalling ~5.7 Mb (20-40% of a chromosome). In the progeny of a high+ carrier, Mendelian segregation of diagnostic alleles and qPCR-based copy counts indicate that high+ is a single tandem array unlinked to the single-copy RLG1a locus. In the wild, high+ carriers had highest fitness in two particularly dry and/or hot years (2015 and 2017; both p < 0.01), while single-copy individuals were twice as fecund as either CNV type in a lush year (2016: p < 0.005). Our results demonstrate fluctuating selection on CNVs affecting phenological traits in a wild population, suggest that plant tRNA ligases mediate stress-responsive life-history traits, and introduce a novel system for investigating the molecular mechanisms of gene amplification.

Measuring Genetic Differentiation from Pool-seq Data

The advent of high throughput sequencing and genotyping technologies enables the comparison of patterns of polymorphisms at a very large number of markers. While the characterization of genetic structure from individual sequencing data remains expensive for many nonmodel species, it has been shown that sequencing pools of individual DNAs (Pool-seq) represents an attractive and cost-effective alternative. However, analyzing sequence read counts from a DNA pool instead of individual genotypes raises statistical challenges in deriving correct estimates of genetic differentiation. In this article, we provide a method-of-moments estimator of [Formula: see text] for Pool-seq data, based on an analysis-of-variance framework. We show, by means of simulations, that this new estimator is unbiased and outperforms previously proposed estimators. We evaluate the robustness of our estimator to model misspecification, such as sequencing errors and uneven contributions of individual DNAs to the pools. Finally, by reanalyzing published Pool-seq data of different ecotypes of the prickly sculpin Cottus asper, we show how the use of an unbiased [Formula: see text] estimator may question the interpretation of population structure inferred from previous analyses.

Whole-genome amplification in double-digest RADseq results in adequate libraries but fewer sequenced loci

Whole-genome amplification by multiple displacement amplification (MDA) is a promising technique to enable the use of samples with only limited amount of DNA for the construction of RAD-seq libraries. Previous work has shown that, when the amount of DNA used in the MDA reaction is large, double-digest RAD-seq (ddRAD) libraries prepared with amplified genomic DNA result in data that are indistinguishable from libraries prepared directly from genomic DNA. Based on this observation, here we evaluate the quality of ddRAD libraries prepared from MDA-amplified genomic DNA when the amount of input genomic DNA and the coverage obtained for samples is variable. By simultaneously preparing libraries for five species of weevils (Coleoptera, Curculionidae), we also evaluate the likelihood that potential contaminants will be encountered in the assembled dataset. Overall, our results indicate that MDA may not be able to rescue all samples with small amounts of DNA, but it does produce ddRAD libraries adequate for studies of phylogeography and population genetics even when conditions are not optimal. We find that MDA makes it harder to predict the number of loci that will be obtained for a given sequencing effort, with some samples behaving like traditional libraries and others yielding fewer loci than expected. This seems to be caused both by stochastic and deterministic effects during amplification. Further, the reduction in loci is stronger in libraries with lower amounts of template DNA for the MDA reaction. Even though a few samples exhibit substantial levels of contamination in raw reads, the effect is very small in the final dataset, suggesting that filters imposed during dataset assembly are important in removing contamination. Importantly, samples with strong signs of contamination and biases in heterozygosity were also those with fewer loci shared in the final dataset, suggesting that stringent filtering of samples with significant amounts of missing data is important when assembling data derived from MDA-amplified genomic DNA. Overall, we find that the combination of MDA and ddRAD results in high-quality datasets for population genetics as long as the sequence data is properly filtered during assembly.

Genome Scans Reveal Homogenization and Local Adaptations in Populations of the Soybean Cyst Nematode

Determining the adaptive potential of alien invasive species in a new environment is a key concern for risk assessment. As climate change is affecting local climatic conditions, widespread modifications in species distribution are expected. Therefore, the genetic mechanisms underlying local adaptations must be understood in order to predict future species distribution. The soybean cyst nematode (SCN), Heterodera glycines Ichinohe, is a major pathogen of soybean that was accidentally introduced in most soybean-producing countries. In this study, we explored patterns of genetic exchange between North American populations of SCN and the effect of isolation by geographical distance. Genotyping-by-sequencing was used to sequence and compare 64 SCN populations from the United States and Canada. At large scale, only a weak correlation was found between genetic distance (Wright's fixation index, FST) and geographic distance, but local effects were strong in recently infested states. Our results also showed a high level of genetic differentiation within some populations, allowing them to adapt to new environments and become established in new soybean-producing areas. Bayesian genome scan methods identified 15 loci under selection for climatic or geographic co-variables. Among these loci, two non-synonymous mutations were detected in SMAD-4 (mothers against decapentaplegic homolog 4) and DOP-3 (dopamine receptor 3). High-impact variants linked to these loci by genetic hitchhiking were also highlighted as putatively involved in local adaptation of SCN populations to new environments. Overall, it appears that strong selective pressure by resistant cultivars is causing a large scale homogenization with virulent populations.

Selection Mapping Identifies Loci Underpinning Autumn Dormancy in Alfalfa (Medicago sativa)

Autumn dormancy in alfalfa (Medicago sativa) is associated with agronomically important traits including regrowth rate, maturity, and winter survival. Historical recurrent selection experiments have been able to manipulate the dormancy response. We hypothesized that artificial selection for dormancy phenotypes in these experiments had altered allele frequencies of dormancy-related genes. Here, we follow this hypothesis and analyze allele frequency changes using genome-wide polymorphisms in the pre- and postselection populations from one historical selection experiment. We screened the nondormant cultivar CUF 101 and populations developed by three cycles of recurrent phenotypic selection for taller and shorter plants in autumn with markers derived from genotyping-by-sequencing (GBS). We validated the robustness of our GBS-derived allele frequency estimates using an empirical approach. Our results suggest that selection mapping is a powerful means of identifying genomic regions associated with traits, and that it can be exploited to provide regions on which to focus further mapping and cloning projects.

Signatures of Selection in the Genomes of Chinese Chestnut (Castanea mollissima Blume): The Roots of Nut Tree Domestication

Chestnuts (Castanea) are major nut crops in East Asia and southern Europe, and are unique among temperate nut crops in that the harvested seeds are starchy rather than oily. Chestnut species have been cultivated for three millennia or more in China, so it is likely that artificial selection has affected the genome of orchard-grown chestnuts. The genetics of Chinese chestnut (Castanea mollissima Blume) domestication are also of interest to breeders of hybrid American chestnut, especially if the low-growing, branching habit of Chinese chestnut, an impediment to American chestnut restoration, is partly the result of artificial selection. We resequenced genomes of wild and orchard-derived Chinese chestnuts and identified selective sweeps based on pooled whole-genome SNP datasets. We present candidate gene loci for chestnut domestication and discuss the potential phenotypic effects of candidate loci, some of which may be useful genes for chestnut improvement in Asia and North America. Selective sweeps included predicted genes potentially related to flower phenology and development, fruit maturation, and secondary metabolism, and included some genes homologous to domestication candidates in other woody plants.

Parent-progeny imputation from pooled samples for cost-efficient genotyping in plant breeding

The increased usage of whole-genome selection (WGS) and other molecular evaluation methods in plant breeding relies on the ability to genotype a very large number of untested individuals in each breeding cycle. Many plant breeding programs evaluate large biparental populations of homozygous individuals derived from homozygous parent inbred lines. This structure lends itself to parent-progeny imputation, which transfers the genotype scores of the parents to progeny individuals that are genotyped for a much smaller number of loci. Here we introduce a parent-progeny imputation method that infers individual genotypes from non-barcoded pooled samples of DNA of multiple individuals using a Hidden Markov Model (HMM). We demonstrate the method for pools of simulated maize double haploids (DH) from biparental populations, genotyped using a genotyping by sequencing (GBS) approach for 3,000 loci at 0.125x to 4x coverage. We observed high concordance between true and imputed marker scores and the HMM produced well-calibrated genotype probabilities that correctly reflected the uncertainty of the imputed scores. Genomic estimated breeding values (GEBV) calculated from the imputed scores closely matched GEBV calculated from the true marker scores. The within-population correlation between these sets of GEBV approached 0.95 at 1x and 4x coverage when pooling two or four individuals, respectively. Our approach can reduce the genotyping cost per individual by a factor up to the number of pooled individuals in GBS applications without the need for extra sequencing coverage, thereby enabling cost-effective large scale genotyping for applications such as WGS in plant breeding.

Population-Specific Associations of Deleterious Rare Variants in Coding Region of P2RY1-P2RY12 Purinergic Receptor Genes in Large-Vessel Ischemic Stroke Patients

The contribution of low-frequency and damaging genetic variants associated with platelet function to ischemic stroke (IS) susceptibility remains unknown. We employed a deep re-sequencing approach in Polish patients in order to investigate the contribution of rare variants (minor allele frequency, MAF < 1%) to the IS genetic susceptibility in this population. The genes selected for re-sequencing consisted of 26 genes coding for proteins associated with the surface membrane of platelets. Targeted pooled re-sequencing (Illumina HiSeq 2500) was performed on genomic DNA of 500 cases (patients with history of clinically proven diagnosis of large-vessel IS) and 500 controls. After quality control and prioritization based on allele frequency and damaging probability, follow-up individual genotyping of deleterious rare variants was performed in patients from the original cohort. Gene-based analyses identified an association between IS and 6 rare functional and damaging variants in the purinergic genes (P2RY1 and P2RY12 locus). The predicted properties of the most damaging rare variants in P2RY1 and P2RY12 were confirmed by using mouse fibroblast cell cultures transfected with plasmid constructs containing cDNA of mutated variants (FLIPR on FlexStation3). This study identified a putative role for rare variants in P2RY1 and P2RY12 genes involved in platelet reactivity on large-vessel IS susceptibility in a Polish population.

How to optimize the precision of allele and haplotype frequency estimates using pooled-sequencing data

Sequencing pools of individuals rather than individuals separately reduces the costs of estimating allele frequencies at many loci in many populations. Theoretical and empirical studies show that sequencing pools comprising a limited number of individuals (typically fewer than 50) provides reliable allele frequency estimates, provided that the DNA pooling and DNA sequencing steps are carefully controlled. Unequal contributions of different individuals to the DNA pool and the mean and variance in sequencing depth both can affect the standard error of allele frequency estimates. To our knowledge, no study separately investigated the effect of these two factors on allele frequency estimates; so that there is currently no method to a priori estimate the relative importance of unequal individual DNA contributions independently of sequencing depth. We develop a new analytical model for allele frequency estimation that explicitly distinguishes these two effects. Our model shows that the DNA pooling variance in a pooled sequencing experiment depends solely on two factors: the number of individuals within the pool and the coefficient of variation of individual DNA contributions to the pool. We present a new method to experimentally estimate this coefficient of variation when planning a pooled sequencing design where samples are either pooled before or after DNA extraction. Using this analytical and experimental framework, we provide guidelines to optimize the design of pooled sequencing experiments. Finally, we sequence replicated pools of inbred lines of the plant Medicago truncatula and show that the predictions from our model generally hold true when estimating the frequency of known multilocus haplotypes using pooled sequencing.

Genome-wide analysis of ivermectin response by Onchocerca volvulus reveals that genetic drift and soft selective sweeps contribute to loss of drug sensitivity

Background

Treatment of onchocerciasis using mass ivermectin administration has reduced morbidity and transmission throughout Africa and Central/South America. Mass drug administration is likely to exert selection pressure on parasites, and phenotypic and genetic changes in several Onchocerca volvulus populations from Cameroon and Ghana—exposed to more than a decade of regular ivermectin treatment—have raised concern that sub-optimal responses to ivermectin's anti-fecundity effect are becoming more frequent and may spread.

Methodology/Principal findings

Pooled next generation sequencing (Pool-seq) was used to characterise genetic diversity within and between 108 adult female worms differing in ivermectin treatment history and response. Genome-wide analyses revealed genetic variation that significantly differentiated good responder (GR) and sub-optimal responder (SOR) parasites. These variants were not randomly distributed but clustered in ~31 quantitative trait loci (QTLs), with little overlap in putative QTL position and gene content between the two countries. Published candidate ivermectin SOR genes were largely absent in these regions; QTLs differentiating GR and SOR worms were enriched for genes in molecular pathways associated with neurotransmission, development, and stress responses. Finally, single worm genotyping demonstrated that geographic isolation and genetic change over time (in the presence of drug exposure) had a significantly greater role in shaping genetic diversity than the evolution of SOR.

Conclusions/Significance

This study is one of the first genome-wide association analyses in a parasitic nematode, and provides insight into the genomics of ivermectin response and population structure of O. volvulus. We argue that ivermectin response is a polygenically-determined quantitative trait (QT) whereby identical or related molecular pathways but not necessarily individual genes are likely to determine the extent of ivermectin response in different parasite populations. Furthermore, we propose that genetic drift rather than genetic selection of SOR is the underlying driver of population differentiation, which has significant implications for the emergence and potential spread of SOR within and between these parasite populations.

Onchocerciasis is a human parasitic disease endemic across large areas of Sub-Saharan Africa, where more than 99% of the estimated 100 million people globally at-risk live. The microfilarial stage of Onchocerca volvulus causes pathologies ranging from mild itching to visual impairment and ultimately, irreversible blindness. Mass administration of ivermectin kills microfilariae and has an anti-fecundity effect on adult worms by temporarily inhibiting the development in utero and/or release into the skin of new microfilariae, thereby reducing morbidity and transmission. Phenotypic and genetic changes in some parasite populations that have undergone multiple ivermectin treatments in Cameroon and Ghana have raised concern that sub-optimal response to ivermectin's anti-fecundity effect may increase in frequency, reducing the impact of ivermectin-based control measures. We used next generation sequencing of small pools of parasites to define genome-wide genetic differences between phenotypically characterised good and sub-optimal responder parasites from Cameroon and Ghana, and identified multiple regions of the genome that differentiated the response types. These regions were largely different between parasites from these two countries but revealed common molecular pathways that might be involved in determining the extent of response to ivermectin's anti-fecundity effect. These data reveal a more complex than previously described pattern of genetic diversity among O. volvulus populations that differ in their geography and response to ivermectin treatment.

Haploid selection within a single ejaculate increases offspring fitness

An inescapable consequence of sex in eukaryotes is the evolution of a biphasic life cycle with alternating diploid and haploid phases. The occurrence of selection during the haploid phase can have far-reaching consequences for fundamental evolutionary processes including the rate of adaptation, the extent of inbreeding depression, and the load of deleterious mutations, as well as for applied research into fertilization technology. Although haploid selection is well established in plants, current dogma assumes that in animals, intact fertile sperm within a single ejaculate are equivalent at siring viable offspring. Using the zebrafish Danio rerio, we show that selection on phenotypic variation among intact fertile sperm within an ejaculate affects offspring fitness. Longer-lived sperm sired embryos with increased survival and a reduced number of apoptotic cells, and adult male offspring exhibited higher fitness. The effect on embryo viability was carried over into the second generation without further selection and was equally strong in both sexes. Sperm pools selected by motile phenotypes differed genetically at numerous sites throughout the genome. Our findings clearly link within-ejaculate variation in sperm phenotype to offspring fitness and sperm genotype in a vertebrate and have major implications for adaptive evolution.