Population genomics from pool sequencing

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.

Allele Frequency Difference AFD⁻An Intuitive Alternative to FST for Quantifying Genetic Population Differentiation

Measuring the magnitude of differentiation between populations based on genetic markers is commonplace in ecology, evolution, and conservation biology. The predominant differentiation metric used for this purpose is F_ST. Based on a qualitative survey, numerical analyses, simulations, and empirical data, I here argue that F_ST does not express the relationship to allele frequency differentiation between populations generally considered interpretable and desirable by researchers. In particular, F_ST (1) has low sensitivity when population differentiation is weak, (2) is contingent on the minor allele frequency across the populations, (3) can be strongly affected by asymmetry in sample sizes, and (4) can differ greatly among the available estimators. Together, these features can complicate pattern recognition and interpretation in population genetic and genomic analysis, as illustrated by empirical examples, and overall compromise the comparability of population differentiation among markers and study systems. I argue that a simple differentiation metric displaying intuitive properties, the absolute allele frequency difference AFD, provides a valuable alternative to F_ST. I provide a general definition of AFD applicable to both bi- and multi-allelic markers and conclude by making recommendations on the sample sizes needed to achieve robust differentiation estimates using AFD.

Population genomic and evolutionary modelling analyses reveal a single major QTL for ivermectin drug resistance in the pathogenic nematode, Haemonchus contortus

BACKGROUND

Infections with helminths cause an enormous disease burden in billions of animals and plants worldwide. Large scale use of anthelmintics has driven the evolution of resistance in a number of species that infect livestock and companion animals, and there are growing concerns regarding the reduced efficacy in some human-infective helminths. Understanding the mechanisms by which resistance evolves is the focus of increasing interest; robust genetic analysis of helminths is challenging, and although many candidate genes have been proposed, the genetic basis of resistance remains poorly resolved.

RESULTS

Here, we present a genome-wide analysis of two genetic crosses between ivermectin resistant and sensitive isolates of the parasitic nematode Haemonchus contortus, an economically important gastrointestinal parasite of small ruminants and a model for anthelmintic research. Whole genome sequencing of parental populations, and key stages throughout the crosses, identified extensive genomic diversity that differentiates populations, but after backcrossing and selection, a single genomic quantitative trait locus (QTL) localised on chromosome V was revealed to be associated with ivermectin resistance. This QTL was common between the two geographically and genetically divergent resistant populations and did not include any leading candidate genes, suggestive of a previously uncharacterised mechanism and/or driver of resistance. Despite limited resolution due to low recombination in this region, population genetic analyses and novel evolutionary models supported strong selection at this QTL, driven by at least partial dominance of the resistant allele, and that large resistance-associated haplotype blocks were enriched in response to selection.

CONCLUSIONS

We have described the genetic architecture and mode of ivermectin selection, revealing a major genomic locus associated with ivermectin resistance, the most conclusive evidence to date in any parasitic nematode. This study highlights a novel genome-wide approach to the analysis of a genetic cross in non-model organisms with extreme genetic diversity, and the importance of a high-quality reference genome in interpreting the signals of selection so identified.

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.

Genomic dissection of pod shattering in common bean: mutations at non-orthologous loci at the basis of convergent phenotypic evolution under domestication of leguminous species

The complete or partial loss of shattering ability occurred independently during the domestication of several crops. Therefore, the study of this trait can provide an understanding of the link between phenotypic and molecular convergent evolution. The genetic dissection of 'pod shattering' in Phaseolus vulgaris is achieved here using a population of introgression lines and next-generation sequencing techniques. The 'occurrence' of the indehiscent phenotype (indehiscent versus dehiscent) depends on a major locus on chromosome 5. Furthermore, at least two additional genes are associated with the 'level' of shattering (number of shattering pods per plant: low versus high) and the 'mode' of shattering (non-twisting versus twisting pods), with all of these loci contributing to the phenotype by epistatic interactions. Comparative mapping indicates that the major gene identified on common bean chromosome 5 corresponds to one of the four quantitative trait loci for pod shattering in Vigna unguiculata. None of the loci identified comprised genes that are homologs of the known shattering genes in Glycine max. Therefore, although convergent domestication can be determined by mutations at orthologous loci, this was only partially true for P. vulgaris and V. unguiculata, which are two phylogenetically closely related crop species, and this was not the case for the more distant P. vulgaris and G. max. Conversely, comparative mapping suggests that the convergent evolution of the indehiscent phenotype arose through mutations in different genes from the same underlying gene networks that are involved in secondary cell-wall biosynthesis and lignin deposition patterning at the pod level.

Small and genetically highly structured populations in a long-legged bee, Rediviva longimanus, as inferred by pooled RAD-seq

Adaptation to local host plants may impact a pollinator's population genetic structure by reducing gene flow and driving population genetic differentiation, representing an early stage of ecological speciation. South African Rediviva longimanus bees exhibit elongated forelegs, a bizarre adaptation for collecting oil from floral spurs of their Diascia hosts. Furthermore, R. longimanus foreleg length (FLL) differs significantly among populations, which has been hypothesised to result from selection imposed by inter-population variation in Diascia floral spur length. Here, we used a pooled restriction site-associated DNA sequencing (pooled RAD-seq) approach to investigate the population genetic structure of R. longimanus and to test if phenotypic differences in FLL translate into increased genetic differentiation (i) between R. longimanus populations and (ii) between phenotypes across populations. We also inferred the effects of demographic processes on population genetic structure and tested for genetic markers underpinning local adaptation. RESULTS: Populations showed marked genetic differentiation (average FST = 0.165), though differentiation was not statistically associated with differences between populations in FLL. All populations exhibited very low genetic diversity and were inferred to have gone through recent bottleneck events, suggesting extremely low effective population sizes. Genetic differentiation between samples pooled by leg length (short versus long) rather than by population of origin was even higher (FST = 0.260) than between populations, suggesting reduced interbreeding between long and short-legged individuals. Signatures of selection were detected in 1119 (3.8%) of a total of 29,721 SNP markers, CONCLUSIONS: Populations of R. longimanus appear to be small, bottlenecked and isolated. Though we could not detect the effect of local adaptation (FLL in response to floral spurs of host plants) on population genetic differentiation, short and long legged bees appeared to be partially differentiated, suggesting incipient ecological speciation. To test this hypothesis, greater resolution through the use of individual-based whole-genome analyses is now needed to quantify the degree of reproductive isolation between long and short legged bees between and even within populations.

The genomic basis of adaptation to calcareous and siliceous soils in Arabidopsis lyrata

Edaphic conditions are important determinants of plant fitness. While much has been learnt in recent years about plant adaptation to heavy metal contaminated soils, the genomic basis underlying adaptation to calcareous and siliceous substrates remains largely unknown. We performed a reciprocal germination experiment and whole-genome resequencing in natural calcareous and siliceous populations of diploid Arabidopsis lyrata to test for edaphic adaptation and detect signatures of selection at loci associated with soil-mediated divergence. In parallel, genome scans on respective diploid ecotypes from the Arabidopsis arenosa species complex were undertaken, to search for shared patterns of adaptive genetic divergence. Soil ecotypes of A. lyrata display significant genotype-by-treatment responses for seed germination. Sequence (SNPs) and copy-number variants (CNVs) point towards loci involved in ion transport as the main targets of adaptive genetic divergence. Two genes exhibiting high differentiation among soil types in A. lyrata further share trans-specific single nucleotide polymorphisms with A. arenosa. This work applies experimental and genomic approaches to study edaphic adaptation in A. lyrata and suggests that physiological response to elemental toxicity and deficiency underlies the evolution of calcareous and siliceous ecotypes. The discovery of shared adaptive variation between sister species indicates that ancient polymorphisms contribute to adaptive evolution.

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.

The Site Frequency/Dosage Spectrum of Autopolyploid Populations

The Site Frequency Spectrum (SFS) and the heterozygosity of allelic variants are among the most important summary statistics for population genetic analysis of diploid organisms. We discuss the generalization of these statistics to populations of autopolyploid organisms in terms of the joint Site Frequency/Dosage Spectrum and its expected value for autopolyploid populations that follow the standard neutral model. Based on these results, we present estimators of nucleotide variability from High-Throughput Sequencing (HTS) data of autopolyploids and discuss potential issues related to sequencing errors and variant calling. We use these estimators to generalize Tajima's D and other SFS-based neutrality tests to HTS data from autopolyploid organisms. Finally, we discuss how these approaches fail when the number of individuals is small. In fact, in autopolyploids there are many possible deviations from the Hardy–Weinberg equilibrium, each reflected in a different shape of the individual dosage distribution. The SFS from small samples is often dominated by the shape of these deviations of the dosage distribution from its Hardy–Weinberg expectations.

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.

Identifying genomic hotspots of differentiation and candidate genes involved in the adaptive divergence of pea aphid host races

Identifying the genomic bases of adaptation to novel environments is a long-term objective in evolutionary biology. Because genetic differentiation is expected to increase between locally adapted populations at the genes targeted by selection, scanning the genome for elevated levels of differentiation is a first step towards deciphering the genomic architecture underlying adaptive divergence. The pea aphid Acyrthosiphon pisum is a model of choice to address this question, as it forms a large complex of plant-specialized races and cryptic species, resulting from recent adaptive radiation. Here, we characterized genomewide polymorphisms in three pea aphid races specialized on alfalfa, clover and pea crops, respectively, which we sequenced in pools (poolseq). Using a model-based approach that explicitly accounts for selection, we identified 392 genomic hotspots of differentiation spanning 47.3 Mb and 2,484 genes (respectively, 9.12% of the genome size and 8.10% of its genes). Most of these highly differentiated regions were located on the autosomes, and overall differentiation was weaker on the X chromosome. Within these hotspots, high levels of absolute divergence between races suggest that these regions experienced less gene flow than the rest of the genome, most likely by contributing to reproductive isolation. Moreover, population-specific analyses showed evidence of selection in every host race, depending on the hotspot considered. These hotspots were significantly enriched for candidate gene categories that control host-plant selection and use. These genes encode 48 salivary proteins, 14 gustatory receptors, 10 odorant receptors, five P450 cytochromes and one chemosensory protein, which represent promising candidates for the genetic basis of host-plant specialization and ecological isolation in the pea aphid complex. Altogether, our findings open new research directions towards functional studies, for validating the role of these genes on adaptive phenotypes.

Reassembling haplotypes in a mixture of pooled amplicons when the relative concentrations are known: A proof-of-concept study on the efficient design of next-generation sequencing strategies

Next-generation sequencing can be costly and labour intensive. Usually, the sequencing cost per sample is reduced by pooling amplified DNA = amplicons) derived from different individuals on the same sequencing lane. Barcodes unique to each amplicon permit short-read sequences to be assigned appropriately. However, the cost of the library preparation increases with the number of barcodes used. We propose an alternative to barcoding: by using different known proportions of individually-derived amplicons in a pooled sample, each is characterised a priori by an expected depth of coverage. We have developed a Hidden Markov Model that uses these expected proportions to reconstruct the input sequences. We apply this method to pools of mitochondrial DNA amplicons extracted from kangaroo meat, genus Macropus. Our experiments indicate that the sequence coverage can be efficiently used to index the short-reads and that we can reassemble the input haplotypes when secondary factors impacting the coverage are controlled. We therefore demonstrate that, by combining our approach with standard barcoding, the cost of the library preparation is reduced to a third.

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.

Variance in estimated pairwise genetic distance under high versus low coverage sequencing: The contribution of linkage disequilibrium

The mean pairwise genetic distance among haplotypes is an estimator of the population mutation rate θ and a standard measure of variation in a population. With the advent of next-generation sequencing (NGS) methods, this and other population parameters can be estimated under different modes of sampling. One approach is to sequence individual genomes with high coverage, and to calculate genetic distance over all sample pairs. The second approach, typically used for microbial samples or for tumor cells, is sequencing a large number of pooled genomes with very low individual coverage. With low coverage, pairwise genetic distances are calculated across independently sampled sites rather than across individual genomes. In this study, we show that the variance in genetic distance estimates is reduced with low coverage sampling if the mean pairwise linkage disequilibrium weighted by allele frequencies is positive. Practically, this means that if on average the most frequent alleles over pairs of loci are in positive linkage disequilibrium, low coverage sequencing results in improved estimates of θ, assuming similar per-site read depths. We show that this result holds under the expected distribution of allele frequencies and linkage disequilibria for an infinite sites model at mutation-drift equilibrium. From simulations, we find that the conditions for reduced variance only fail to hold in cases where variant alleles are few and at very low frequency. These results are applied to haplotype frequencies from a lung cancer tumor to compute the weighted linkage disequilibria and the expected error in estimated genetic distance using high versus low coverage.

Investigating the genomic basis of discrete phenotypes using a Pool-Seq-only approach: New insights into the genetics underlying colour variation in diverse taxa

While large-scale genomic approaches are increasingly revealing the genetic basis of polymorphic phenotypes such as colour morphs, such approaches are almost exclusively conducted in species with high-quality genomes and annotations. Here, we use Pool-Seq data for both genome assembly and SNP frequency estimation, followed by scanning for F_ST outliers to identify divergent genomic regions. Using paired-end, short-read sequencing data from two groups of individuals expressing divergent phenotypes, we generate a de novo rough-draft genome, identify SNPs and calculate genomewide F_ST differences between phenotypic groups. As genomes generated by Pool-Seq data are highly fragmented, we also present an approach for super-scaffolding contigs using existing protein-coding data sets. Using this approach, we reanalysed genomic data from two recent studies of birds and butterflies investigating colour pattern variation and replicated their core findings, demonstrating the accuracy and power of a Pool-Seq-only approach. Additionally, we discovered new regions of high divergence and new annotations that together suggest novel parallels between birds and butterflies in the origins of their colour pattern variation.

Genome scans on experimentally evolved populations reveal candidate regions for adaptation to plant resistance in the potato cyst nematode Globodera pallida

Improving resistance durability involves to be able to predict the adaptation speed of pathogen populations. Identifying the genetic bases of pathogen adaptation to plant resistances is a useful step to better understand and anticipate this phenomenon. Globodera pallida is a major pest of potato crop for which a resistance QTL, GpaV_vrn , has been identified in Solanum vernei. However, its durability is threatened as G. pallida populations are able to adapt to the resistance in few generations. The aim of this study was to investigate the genomic regions involved in the resistance breakdown by coupling experimental evolution and high-density genome scan. We performed a whole-genome resequencing of pools of individuals (Pool-Seq) belonging to G. pallida lineages derived from two independent populations having experimentally evolved on susceptible and resistant potato cultivars. About 1.6 million SNPs were used to perform the genome scan using a recent model testing for adaptive differentiation and association to population-specific covariables. We identified 275 outliers and 31 of them, which also showed a significant reduction in diversity in adapted lineages, were investigated for their genic environment. Some candidate genomic regions contained genes putatively encoding effectors and were enriched in SPRYSECs, known in cyst nematodes to be involved in pathogenicity and in (a)virulence. Validated candidate SNPs will provide a useful molecular tool to follow frequencies of virulence alleles in natural G. pallida populations and define efficient strategies of use of potato resistances maximizing their durability.

Pooled-DNA sequencing identifies genomic regions of selection in Nigerian isolates of Plasmodium falciparum

Background

The burden of falciparum malaria is especially high in sub-Saharan Africa. Differences in pressure from host immunity and antimalarial drugs lead to adaptive changes responsible for high level of genetic variations within and between the parasite populations. Population-specific genetic studies to survey for genes under positive or balancing selection resulting from drug pressure or host immunity will allow for refinement of interventions.

Methods

We performed a pooled sequencing (pool-seq) of the genomes of 100 Plasmodium falciparum isolates from Nigeria. We explored allele-frequency based neutrality test (Tajima’s D) and integrated haplotype score (iHS) to identify genes under selection.

Results

Fourteen shared iHS regions that had at least 2 SNPs with a score > 2.5 were identified. These regions code for genes that were likely to have been under strong directional selection. Two of these genes were the chloroquine resistance transporter (CRT) on chromosome 7 and the multidrug resistance 1 (MDR1) on chromosome 5. There was a weak signature of selection in the dihydrofolate reductase (DHFR) gene on chromosome 4 and MDR5 genes on chromosome 13, with only 2 and 3 SNPs respectively identified within the iHS window. We observed strong selection pressure attributable to continued chloroquine and sulfadoxine-pyrimethamine use despite their official proscription for the treatment of uncomplicated malaria. There was also a major selective sweep on chromosome 6 which had 32 SNPs within the shared iHS region. Tajima’s D of circumsporozoite protein (CSP), erythrocyte-binding antigen (EBA-175), merozoite surface proteins - MSP3 and MSP7, merozoite surface protein duffy binding-like (MSPDBL2) and serine repeat antigen (SERA-5) were 1.38, 1.29, 0.73, 0.84 and 0.21, respectively.

Conclusion

We have demonstrated the use of pool-seq to understand genomic patterns of selection and variability in P. falciparum from Nigeria, which bears the highest burden of infections. This investigation identified known genomic signatures of selection from drug pressure and host immunity. This is evidence that P. falciparum populations explore common adaptive strategies that can be targeted for the development of new interventions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-017-2260-z) contains supplementary material, which is available to authorized users.

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.

HacDivSel: Two new methods (haplotype-based and outlier-based) for the detection of divergent selection in pairs of populations

The detection of genomic regions involved in local adaptation is an important topic in current population genetics. There are several detection strategies available depending on the kind of genetic and demographic information at hand. A common drawback is the high risk of false positives. In this study we introduce two complementary methods for the detection of divergent selection from populations connected by migration. Both methods have been developed with the aim of being robust to false positives. The first method combines haplotype information with inter-population differentiation (FST). Evidence of divergent selection is concluded only when both the haplotype pattern and the FST value support it. The second method is developed for independently segregating markers i.e. there is no haplotype information. In this case, the power to detect selection is attained by developing a new outlier test based on detecting a bimodal distribution. The test computes the FST outliers and then assumes that those of interest would have a different mode. We demonstrate the utility of the two methods through simulations and the analysis of real data. The simulation results showed power ranging from 60-95% in several of the scenarios whilst the false positive rate was controlled below the nominal level. The analysis of real samples consisted of phased data from the HapMap project and unphased data from intertidal marine snail ecotypes. The results illustrate that the proposed methods could be useful for detecting locally adapted polymorphisms. The software HacDivSel implements the methods explained in this manuscript.

Correlated patterns of genetic diversity and differentiation across an avian family

Comparative studies of closely related taxa can provide insights into the evolutionary forces that shape genome evolution and the prevalence of convergent molecular evolution. We investigated patterns of genetic diversity and differentiation in stonechats (genus Saxicola), a widely distributed avian species complex with phenotypic variation in plumage, morphology and migratory behaviour, to ask whether similar genomic regions have become differentiated in independent, but closely related, taxa. We used whole-genome pooled sequencing of 262 individuals from five taxa and found that levels of genetic diversity and divergence are strongly correlated among different stonechat taxa. We then asked whether these patterns remain correlated at deeper evolutionary scales and found that homologous genomic regions have become differentiated in stonechats and the closely related Ficedula flycatchers. Such correlation across a range of evolutionary divergence and among phylogenetically independent comparisons suggests that similar processes may be driving the differentiation of these independently evolving lineages, which in turn may be the result of intrinsic properties of particular genomic regions (e.g. areas of low recombination). Consequently, studies employing genome scans to search for areas important for reproductive isolation or adaptation should account for corresponding regions of differentiation, as these regions may not necessarily represent speciation islands or evidence of local adaptation.

Suitability of Different Mapping Algorithms for Genome-Wide Polymorphism Scans with Pool-Seq Data

The cost-effectiveness of sequencing pools of individuals (Pool-Seq) provides the basis for the popularity and widespread use of this method for many research questions, ranging from unraveling the genetic basis of complex traits, to the clonal evolution of cancer cells. Because the accuracy of Pool-Seq could be affected by many potential sources of error, several studies have determined, for example, the influence of sequencing technology, the library preparation protocol, and mapping parameters. Nevertheless, the impact of the mapping tools has not yet been evaluated. Using simulated and real Pool-Seq data, we demonstrate a substantial impact of the mapping tools, leading to characteristic false positives in genome-wide scans. The problem of false positives was particularly pronounced when data with different read lengths and insert sizes were compared. Out of 14 evaluated algorithms novoalign, bwa mem and clc4 are most suitable for mapping Pool-Seq data. Nevertheless, no single algorithm is sufficient for avoiding all false positives. We show that the intersection of the results of two mapping algorithms provides a simple, yet effective, strategy to eliminate false positives. We propose that the implementation of a consistent Pool-Seq bioinformatics pipeline, building on the recommendations of this study, can substantially increase the reliability of Pool-Seq results, in particular when libraries generated with different protocols are being compared.

A variant reference data set for the Africanized honeybee, Apis mellifera

The Africanized honeybee (AHB) is a population of Apis mellifera found in the Americas. AHBs originated in 1956 in Rio Clara, Brazil where imported African A. m. scutellata escaped and hybridized with local populations of European A. mellifera. Africanized populations can now be found from Northern Argentina to the Southern United States. AHBs—often referred to as ‘Killer Bees’— are a major concern to the beekeeping industry as well as a model for the evolutionary genetics of colony defence. We performed high coverage pooled-resequencing of 360 diploid workers from 30 Brazilian AHB colonies using Illumina Hi-Seq (150 bp PE). This yielded a high density SNP data set with an average read depth at each site of 20.25 reads. With 3,606,720 SNPs and 155,336 SNPs within 11,365 genes, this data set is the largest genomic resource available for AHBs and will enable high-resolution studies of the population dynamics, evolution, and genetics of this successful biological invader, in addition to facilitating the development of SNP-based tools for identifying AHBs.

Adaptive evolution and segregating load contribute to the genomic landscape of divergence in two tree species connected by episodic gene flow

Speciation often involves repeated episodes of genetic contact between divergent populations before reproductive isolation (RI) is complete. Whole-genome sequencing (WGS) holds great promise for unravelling the genomic bases of speciation. We have studied two ecologically divergent, hybridizing species of the 'model tree' genus Populus (poplars, aspens, cottonwoods), Populus alba and P. tremula, using >8.6 million single nucleotide polymorphisms (SNPs) from WGS of population pools. We used the genomic data to (i) scan these species' genomes for regions of elevated and reduced divergence, (ii) assess key aspects of their joint demographic history based on genomewide site frequency spectra (SFS) and (iii) infer the potential roles of adaptive and deleterious coding mutations in shaping the genomic landscape of divergence. We identified numerous small, unevenly distributed genome regions without fixed polymorphisms despite high overall genomic differentiation. The joint SFS was best explained by ancient and repeated gene flow and allowed pinpointing candidate interspecific migrant tracts. The direction of selection (DoS) differed between genes in putative migrant tracts and the remainder of the genome, thus indicating the potential roles of adaptive divergence and segregating deleterious mutations on the evolution and breakdown of RI. Genes affected by positive selection during divergence were enriched for several functionally interesting groups, including well-known candidate 'speciation genes' involved in plant innate immunity. Our results suggest that adaptive divergence affects RI in these hybridizing species mainly through intrinsic and demographic processes. Integrating genomic with molecular data holds great promise for revealing the effects of particular genetic pathways on speciation.

Estimating the Effective Population Size from Temporal Allele Frequency Changes in Experimental Evolution

The effective population size (Ne) is a major factor determining allele frequency changes in natural and experimental populations. Temporal methods provide a powerful and simple approach to estimate short-term Ne. They use allele frequency shifts between temporal samples to calculate the standardized variance, which is directly related to Ne. Here we focus on experimental evolution studies that often rely on repeated sequencing of samples in pools (Pool-seq). Pool-seq is cost-effective and often outperforms individual-based sequencing in estimating allele frequencies, but it is associated with atypical sampling properties: Additional to sampling individuals, sequencing DNA in pools leads to a second round of sampling, which increases the variance of allele frequency estimates. We propose a new estimator of Ne, which relies on allele frequency changes in temporal data and corrects for the variance in both sampling steps. In simulations, we obtain accurate Ne estimates, as long as the drift variance is not too small compared to the sampling and sequencing variance. In addition to genome-wide Ne estimates, we extend our method using a recursive partitioning approach to estimate Ne locally along the chromosome. Since the type I error is controlled, our method permits the identification of genomic regions that differ significantly in their Ne estimates. We present an application to Pool-seq data from experimental evolution with Drosophila and provide recommendations for whole-genome data. The estimator is computationally efficient and available as an R package at https://github.com/ThomasTaus/Nest.

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.

Evolutionary genomics of Culex pipiens: global and local adaptations associated with climate, life-history traits and anthropogenic factors

We present the first genome-wide study of recent evolution in Culex pipiens species complex focusing on the genomic extent, functional targets and likely causes of global and local adaptations. We resequenced pooled samples of six populations of C. pipiens and two populations of the outgroup Culex torrentium. We used principal component analysis to systematically study differential natural selection across populations and developed a phylogenetic scanning method to analyse admixture without haplotype data. We found evidence for the prominent role of geographical distribution in shaping population structure and specifying patterns of genomic selection. Multiple adaptive events, involving genes implicated with autogeny, diapause and insecticide resistance were limited to specific populations. We estimate that about 5–20% of the genes (including several histone genes) and almost half of the annotated pathways were undergoing selective sweeps in each population. The high occurrence of sweeps in non-genic regions and in chromatin remodelling genes indicated the adaptive importance of gene expression changes. We hypothesize that global adaptive processes in the C. pipiens complex are potentially associated with South to North range expansion, requiring adjustments in chromatin conformation. Strong local signature of adaptation and emergence of hybrid bridge vectors necessitate genomic assessment of populations before specifying control agents.

Harnessing the power of RADseq for ecological and evolutionary genomics

High-throughput techniques based on restriction site-associated DNA sequencing (RADseq) are enabling the low-cost discovery and genotyping of thousands of genetic markers for any species, including non-model organisms, which is revolutionizing ecological, evolutionary and conservation genetics. Technical differences among these methods lead to important considerations for all steps of genomics studies, from the specific scientific questions that can be addressed, and the costs of library preparation and sequencing, to the types of bias and error inherent in the resulting data. In this Review, we provide a comprehensive discussion of RADseq methods to aid researchers in choosing among the many different approaches and avoiding erroneous scientific conclusions from RADseq data, a problem that has plagued other genetic marker types in the past.

The vgll3 Locus Controls Age at Maturity in Wild and Domesticated Atlantic Salmon (Salmo salar L.) Males

Wild and domesticated Atlantic salmon males display large variation for sea age at sexual maturation, which varies between 1-5 years. Previous studies have uncovered a genetic predisposition for variation of age at maturity with moderate heritability, thus suggesting a polygenic or complex nature of this trait. The aim of this study was to identify associated genetic loci, genes and ultimately specific sequence variants conferring sea age at maturity in salmon. We performed a genome wide association study (GWAS) using a pool sequencing approach (20 individuals per river and phenotype) of male salmon returning to rivers as sexually mature either after one sea winter (2009) or three sea winters (2011) in six rivers in Norway. The study revealed one major selective sweep, which covered 76 significant SNPs in which 74 were found in a 370 kb region of chromosome 25. Genotyping other smolt year classes of wild and domesticated salmon confirmed this finding. Genotyping domesticated fish narrowed the haplotype region to four SNPs covering 2386 bp, containing the vgll3 gene, including two missense mutations explaining 33-36% phenotypic variation. A single locus was found to have a highly significant role in governing sea age at maturation in this species. The SNPs identified may be both used as markers to guide breeding for late maturity in salmon aquaculture and in monitoring programs of wild salmon. Interestingly, a SNP in proximity of the VGLL3 gene in humans (Homo sapiens), has previously been linked to age at puberty suggesting a conserved mechanism for timing of puberty in vertebrates.

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

Sequencing pooled DNA of multiple individuals from a population instead of sequencing individuals separately has become popular due to its cost-effectiveness and simple wet-lab protocol, although some criticism of this approach remains. Here we validated a protocol for pooled whole-genome re-sequencing (Pool-seq) of Arabidopsis lyrata libraries prepared with low amounts of DNA (1.6 ng per individual). The validation was based on comparing single nucleotide polymorphism (SNP) frequencies obtained by pooling with those obtained by individual-based Genotyping By Sequencing (GBS). Furthermore, we investigated the effect of sample number, sequencing depth per individual and variant caller on population SNP frequency estimates. For Pool-seq data, we compared frequency estimates from two SNP callers, VarScan and Snape; the former employs a frequentist SNP calling approach while the latter uses a Bayesian approach. Results revealed concordance correlation coefficients well above 0.8, confirming that Pool-seq is a valid method for acquiring population-level SNP frequency data. Higher accuracy was achieved by pooling more samples (25 compared to 14) and working with higher sequencing depth (4.1× per individual compared to 1.4× per individual), which increased the concordance correlation coefficient to 0.955. The Bayesian-based SNP caller produced somewhat higher concordance correlation coefficients, particularly at low sequencing depth. We recommend pooling at least 25 individuals combined with sequencing at a depth of 100× to produce satisfactory frequency estimates for common SNPs (minor allele frequency above 0.05).

A new method for studying population genetics of cyst nematodes based on Pool-Seq and genomewide allele frequency analysis

Cyst nematodes are important agricultural pests responsible for billions of dollars of losses each year. Plant resistance is the most effective management tool, but it requires a close monitoring of population genetics. Current technologies for pathotyping and genotyping cyst nematodes are time-consuming, expensive and imprecise. In this study, we capitalized on the reproduction mode of cyst nematodes to develop a simple population genetic analysis pipeline based on genotyping-by-sequencing and Pool-Seq. This method yielded thousands of SNPs and allowed us to study the relationships between populations of different origins or pathotypes. Validation of the method on well-characterized populations also demonstrated that it was a powerful and accurate tool for population genetics. The genomewide allele frequencies of 23 populations of golden nematode, from nine countries and representing the five known pathotypes, were compared. A clear separation of the pathotypes and fine genetic relationships between and among global populations were obtained using this method. In addition to being powerful, this tool has proven to be very time- and cost-efficient and could be applied to other cyst nematode species.

A generalized Watterson estimator for next-generation sequencing: From trios to autopolyploids

Several variations of the Watterson estimator of variability for Next Generation Sequencing (NGS) data have been proposed in the literature. We present a unified framework for generalized Watterson estimators based on Maximum Composite Likelihood, which encompasses most of the existing estimators. We propose this class of unbiased estimators as generalized Watterson estimators for a large class of NGS data, including pools and trios. We also discuss the relation with the estimators proposed in the literature and show that they admit two equivalent but seemingly different forms, deriving a set of combinatorial identities as a byproduct. Finally, we give a detailed treatment of Watterson estimators for single or multiple autopolyploid individuals.

Beyond xeroderma pigmentosum: DNA damage and repair in an ecological context. A tribute to James E. Cleaver

The ability to repair DNA is a ubiquitous characteristic of life on Earth and all organisms possess similar mechanisms for dealing with DNA damage, an indication of a very early evolutionary origin for repair processes. James E. Cleaver's career (initiated in the early 1960s) has been devoted to the study of mammalian ultraviolet radiation (UVR) photobiology, specifically the molecular genetics of xeroderma pigmentosum and other human diseases caused by defects in DNA damage recognition and repair. This work by Jim and others has influenced the study of DNA damage and repair in a variety of taxa. Today, the field of DNA repair is enhancing our understanding of not only how to treat and prevent human disease, but is providing insights on the evolutionary history of life on Earth and how natural populations are coping with UVR-induced DNA damage from anthropogenic changes in the environment such as ozone depletion.

Comparison of whole mitochondrial genome sequences from two clades of the invasive ascidian, Didemnum vexillum

The mitochondria are the main source of cellular energy production and have an important role in development, fertility, and thermal limitations. Adaptive mitochondrial DNA mutations have the potential to be of great importance in determining aspects of the life history of an organism. Phylogenetic analyses of the globally invasive marine ascidian Didemnum vexillum using the mitochondrial cytochrome c oxidase 1 (COX1) coding region, revealed two distinct clades. Representatives of one clade (denoted by 'B') are geographically restricted to D. vexillum's native region (north-west Pacific Ocean, including Japan), whereas members of the other clade (denoted by 'A') have been introduced and become invasive in temperate coastal areas around the world. Persistence of clade B's restricted distribution may reflect it being inherently less invasive than clade A. To investigate this we sought to determine if the two clades differ significantly in other mitochondrial genes of functional significance, specifically, alterations in amino acids encoded in mitochondrial enzyme subunits. Differences in functional mitochondrial genes could indicate an increased ability for clade A colonies to tolerate a wider range of environmental temperature. Full mitochondrial genomic sequences from D. vexillum clades A and B were obtained and they predict significant sequence differences in genes encoding for enzymes involved in oxidative phosphorylation. Diversity levels were relatively high and showed divergence across almost all genes, with p-distance values between the two clades indicating recent divergence. Both clades showed an excess of rare variants, which is consistent with balancing selection or a recent population expansion. Results presented here will inform future research focusing on examining the functional properties of the corresponding mitochondrial respiration enzymes, of A and B clade enzymes. By comparing closely related taxa that have differing distributions it is possible to identify genes and phenotypes suited to particular environments. The examination of mitochondrial genotypes, and associated enzyme functioning, across populations may aid in our understanding of thermal tolerance and environmental adaptation.

Challenges in analysis and interpretation of microsatellite data for population genetic studies

Advancing technologies have facilitated the ever-widening application of genetic markers such as microsatellites into new systems and research questions in biology. In light of the data and experience accumulated from several years of using microsatellites, we present here a literature review that synthesizes the limitations of microsatellites in population genetic studies. With a focus on population structure, we review the widely used fixation (F ST) statistics and Bayesian clustering algorithms and find that the former can be confusing and problematic for microsatellites and that the latter may be confounded by complex population models and lack power in certain cases. Clustering, multivariate analyses, and diversity-based statistics are increasingly being applied to infer population structure, but in some instances these methods lack formalization with microsatellites. Migration-specific methods perform well only under narrow constraints. We also examine the use of microsatellites for inferring effective population size, changes in population size, and deeper demographic history, and find that these methods are untested and/or highly context-dependent. Overall, each method possesses important weaknesses for use with microsatellites, and there are significant constraints on inferences commonly made using microsatellite markers in the areas of population structure, admixture, and effective population size. To ameliorate and better understand these constraints, researchers are encouraged to analyze simulated datasets both prior to and following data collection and analysis, the latter of which is formalized within the approximate Bayesian computation framework. We also examine trends in the literature and show that microsatellites continue to be widely used, especially in non-human subject areas. This review assists with study design and molecular marker selection, facilitates sound interpretation of microsatellite data while fostering respect for their practical limitations, and identifies lessons that could be applied toward emerging markers and high-throughput technologies in population genetics.

Next-generation sequencing for molecular ecology: a caveat regarding pooled samples

We develop a model based on the Dirichlet-compound multinomial distribution (CMD) and Ewens sampling formula to predict the fraction of SNP loci that will appear fixed for alternate alleles between two pooled samples drawn from the same underlying population. We apply this model to next-generation sequencing (NGS) data from Baltic Sea herring recently published by (Corander et al., 2013, Molecular Ecology, 2931-2940), and show that there are many more fixed loci than expected in the absence of genetic structure. However, we show through coalescent simulations that the degree of population structure required to explain the fraction of alternatively fixed SNPs is extraordinarily high and that the surplus of fixed loci is more likely a consequence of limited representation of individual gene copies in the pooled samples, than it is of population structure. Our analysis signals that the use of NGS on pooled samples to identify divergent SNPs warrants caution. With pooled samples, it is hard to diagnose when an NGS experiment has gone awry; especially when NGS data on pooled samples are of low read depth with a limited number of individuals, it may be worthwhile to temper claims of unexpected population differentiation from pooled samples, pending verification with more reliable methods or stricter adherence to recommended sampling designs for pooled sequencing e.g. Futschik & Schlötterer 2010, Genetics, 186, 207; Gautier et al., 2013a, Molecular Ecology, 3766-3779). Analysis of the data and diagnosis of problems is easier and more reliable (and can be less costly) with individually barcoded samples. Consequently, for some scenarios, individual barcoding may be preferable to pooling of samples.

Population-genetic inference from pooled-sequencing data

Although pooled-population sequencing has become a widely used approach for estimating allele frequencies, most work has proceeded in the absence of a proper statistical framework. We introduce a self-sufficient, closed-form, maximum-likelihood estimator for allele frequencies that accounts for errors associated with sequencing, and a likelihood-ratio test statistic that provides a simple means for evaluating the null hypothesis of monomorphism. Unbiased estimates of allele frequencies (where N is the number of individuals sampled) appear to be unachievable, and near-certain identification of a polymorphism requires a minor-allele frequency . A framework is provided for testing for significant differences in allele frequencies between populations, taking into account sampling at the levels of individuals within populations and sequences within pooled samples. Analyses that fail to account for the two tiers of sampling suffer from very large false-positive rates and can become increasingly misleading with increasing depths of sequence coverage. The power to detect significant allele-frequency differences between two populations is very limited unless both the number of sampled individuals and depth of sequencing coverage exceed 100.