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

The bone transcription factor Osterix controls extracellular matrix- and node of Ranvier-related gene expression in oligodendrocytes

Oligodendrocytes are the primary producers of many extracellular matrix (ECM)-related proteins found in the CNS. Therefore, oligodendrocytes play a critical role in the determination of brain stiffness, node of Ranvier formation, perinodal ECM deposition, and perineuronal net formation, all of which depend on the ECM. Nevertheless, the transcription factors that control ECM-related gene expression in oligodendrocytes remain unknown. Here, we found that the transcription factor Osterix (also known as Sp7) binds in proximity to genes important for CNS ECM and node of Ranvier formation and mediates their expression. Oligodendrocyte-specific ablation of Sp7 changes ECM composition and brain stiffness and results in aberrant node of Ranvier formation. Sp7 is known to control osteoblast maturation and bone formation. Our comparative analyses suggest that Sp7 plays a conserved biological role in oligodendrocytes and in bone-forming cells, where it mediates brain and bone tissue stiffness by controlling expression of ECM components.

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

Comparative genomics of rainbow trout (Oncorhynchus mykiss): Is the genetic architecture of migratory behavior conserved among populations?

Rainbow trout (Oncorhynchus mykiss) are a partially migratory species wherein some individuals undergo long-distance anadromous migrations, and others stay as residents in their native freshwater streams. The decision to migrate is known to be highly heritable, and yet, the underlying genes and alleles associated with migration are not fully characterized. Here we used a pooled approach of whole-genome sequence data from migratory and resident trout of two native populations-Sashin Creek, Alaska and Little Sheep Creek, Oregon-to obtain a genome-wide perspective of the genetic architecture of resident and migratory life history. We calculated estimates of genetic differentiation, genetic diversity, and selection between the two phenotypes to locate regions of interest and then compared these associations between populations. We identified numerous genes and alleles associated with life history development in the Sashin Creek population with a notable area on chromosome 8 that may play a critical role in the development of the migratory phenotype. However, very few alleles appeared to be associated with life history development in the Little Sheep Creek system, suggesting population-specific genetic effects are likely important in the development of anadromy. Our results indicate that a migratory life history is not controlled by a singular gene or region but supports the idea that there are many independent ways for a migratory phenotype to emerge in a population. Therefore, conserving and promoting genetic diversity in migratory individuals is paramount to conserving these populations. Ultimately, our data add to a growing body of literature that suggests that population-specific genetic effects, likely mediated through environmental variation, contribute to life history development in rainbow trout.

Genome-wide selection signatures reveal widespread synergistic effects of two different stressors in Drosophila melanogaster

Experimental evolution combined with whole-genome sequencing (evolve and resequence (E&R)) is a powerful approach to study the adaptive architecture of selected traits. Nevertheless, so far the focus has been on the selective response triggered by a single stressor. Building on the highly parallel selection response of founder populations with reduced variation, we evaluated how the presence of a second stressor affects the genomic selection response. After 20 generations of adaptation to laboratory conditions at either 18°C or 29°C, strong genome-wide selection signatures were observed. Only 38% of the selection signatures can be attributed to laboratory adaptation (no difference between temperature regimes). The remaining selection responses are either caused by temperature-specific effects, or reflect the joint effects of temperature and laboratory adaptation (same direction, but the magnitude differs between temperatures). The allele frequency changes resulting from the combined effects of temperature and laboratory adaptation were more extreme in the hot environment for 83% of the affected genomic regions-indicating widespread synergistic effects of the two stressors. We conclude that E&R with reduced genetic variation is a powerful approach to study genome-wide fitness consequences driven by the combined effects of multiple environmental factors.

Genome-enabled discovery of candidate virulence loci in Striga hermonthica, a devastating parasite of African cereal crops

Parasites have evolved proteins, virulence factors (VFs), that facilitate plant colonisation, however VFs mediating parasitic plant-host interactions are poorly understood. Striga hermonthica is an obligate, root-parasitic plant of cereal hosts in sub-Saharan Africa, causing devastating yield losses. Understanding the molecular nature and allelic variation of VFs in S. hermonthica is essential for breeding resistance and delaying the evolution of parasite virulence. We assembled the S. hermonthica genome and identified secreted proteins using in silico prediction. Pooled sequencing of parasites growing on a susceptible and a strongly resistant rice host allowed us to scan for loci where selection imposed by the resistant host had elevated the frequency of alleles contributing to successful colonisation. Thirty-eight putatively secreted VFs had very different allele frequencies with functions including host cell wall modification, protease or protease inhibitor and kinase activities. These candidate loci had significantly higher Tajima's D than the genomic background, consistent with balancing selection. Our results reveal diverse strategies used by S. hermonthica to overcome different layers of host resistance. Understanding the maintenance of variation at virulence loci by balancing selection will be critical to managing the evolution of virulence as part of a sustainable control strategy.

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.

Batch effects in population genomic studies with low-coverage whole genome sequencing data: Causes, detection and mitigation

Over the past few decades, there has been an explosion in the amount of publicly available sequencing data. This opens new opportunities for combining data sets to achieve unprecedented sample sizes, spatial coverage or temporal replication in population genomic studies. However, a common concern is that nonbiological differences between data sets may generate patterns of variation in the data that can confound real biological patterns, a problem known as batch effects. In this paper, we compare two batches of low-coverage whole genome sequencing (lcWGS) data generated from the same populations of Atlantic cod (Gadus morhua). First, we show that with a "batch-effect-naive" bioinformatic pipeline, batch effects systematically biased our genetic diversity estimates, population structure inference and selection scans. We then demonstrate that these batch effects resulted from multiple technical differences between our data sets, including the sequencing chemistry (four-channel vs. two-channel), sequencing run, read type (single-end vs. paired-end), read length (125 vs. 150 bp), DNA degradation level (degraded vs. well preserved) and sequencing depth (0.8× vs. 0.3× on average). Lastly, we illustrate that a set of simple bioinformatic strategies (such as different read trimming and single nucleotide polymorphism filtering) can be used to detect batch effects in our data and substantially mitigate their impact. We conclude that combining data sets remains a powerful approach as long as batch effects are explicitly accounted for. We focus on lcWGS data in this paper, which may be particularly vulnerable to certain causes of batch effects, but many of our conclusions also apply to other sequencing strategies.

The genetic architecture of temperature adaptation is shaped by population ancestry and not by selection regime

Background

Understanding the genetic architecture of temperature adaptation is key for characterizing and predicting the effect of climate change on natural populations. One particularly promising approach is Evolve and Resequence, which combines advantages of experimental evolution such as time series, replicate populations, and controlled environmental conditions, with whole genome sequencing. Recent analysis of replicate populations from two different Drosophila simulans founder populations, which were adapting to the same novel hot environment, uncovered very different architectures—either many selection targets with large heterogeneity among replicates or fewer selection targets with a consistent response among replicates.

Results

Here, we expose the founder population from Portugal to a cold temperature regime. Although almost no selection targets are shared between the hot and cold selection regime, the adaptive architecture was similar. We identify a moderate number of targets under strong selection (19 selection targets, mean selection coefficient = 0.072) and parallel responses in the cold evolved replicates. This similarity across different environments indicates that the adaptive architecture depends more on the ancestry of the founder population than the specific selection regime.

Conclusions

These observations will have broad implications for the correct interpretation of the genomic responses to a changing climate in natural populations.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-021-02425-9.

Secondary Evolve and Resequencing: An Experimental Confirmation of Putative Selection Targets without Phenotyping

Evolve and resequencing (E&R) studies investigate the genomic responses of adaptation during experimental evolution. Because replicate populations evolve in the same controlled environment, consistent responses to selection across replicates are frequently used to identify reliable candidate regions that underlie adaptation to a new environment. However, recent work demonstrated that selection signatures can be restricted to one or a few replicate(s) only. These selection signatures frequently have weak statistical support, and given the difficulties of functional validation, additional evidence is needed before considering them as candidates for functional analysis. Here, we introduce an experimental procedure to validate candidate loci with weak or replicate-specific selection signature(s). Crossing an evolved population from a primary E&R experiment to the ancestral founder population reduces the frequency of candidate alleles that have reached a high frequency. We hypothesize that genuine selection targets will experience a repeatable frequency increase after the mixing with the ancestral founders if they are exposed to the same environment (secondary E&R experiment). Using this approach, we successfully validate two overlapping selection targets, which showed a mutually exclusive selection signature in a primary E&R experiment of Drosophila simulans adapting to a novel temperature regime. We conclude that secondary E&R experiments provide a reliable confirmation of selection signatures that either are not replicated or show only a low statistical significance in a primary E&R experiment unless epistatic interactions predominate. Such experiments are particularly helpful to prioritize candidate loci for time-consuming functional follow-up investigations.

Evolutionary Genomics of Structural Variation in Asian Rice (Oryza sativa) Domestication

Structural variants (SVs) are a largely unstudied feature of plant genome evolution, despite the fact that SVs contribute substantially to phenotypes. In this study, we discovered SVs across a population sample of 347 high-coverage, resequenced genomes of Asian rice (Oryza sativa) and its wild ancestor (O. rufipogon). In addition to this short-read data set, we also inferred SVs from whole-genome assemblies and long-read data. Comparisons among data sets revealed different features of genome variability. For example, genome alignment identified a large (∼4.3 Mb) inversion in indica rice varieties relative to japonica varieties, and long-read analyses suggest that ∼9% of genes from the outgroup (O. longistaminata) are hemizygous. We focused, however, on the resequencing sample to investigate the population genomics of SVs. Clustering analyses with SVs recapitulated the rice cultivar groups that were also inferred from SNPs. However, the site-frequency spectrum of each SV type-which included inversions, duplications, deletions, translocations, and mobile element insertions-was skewed toward lower frequency variants than synonymous SNPs, suggesting that SVs may be predominantly deleterious. Among transposable elements, SINE and mariner insertions were found at especially low frequency. We also used SVs to study domestication by contrasting between rice and O. rufipogon. Cultivated genomes contained ∼25% more derived SVs and mobile element insertions than O. rufipogon, indicating that SVs contribute to the cost of domestication in rice. Peaks of SV divergence were enriched for known domestication genes, but we also detected hundreds of genes gained and lost during domestication, some of which were enriched for traits of agronomic interest.

Fitness effects for Ace insecticide resistance mutations are determined by ambient temperature

BACKGROUND

Insect pest control programs often use periods of insecticide treatment with intermittent breaks, to prevent fixing of mutations conferring insecticide resistance. Such mutations are typically costly in an insecticide-free environment, and their frequency is determined by the balance between insecticide treatment and cost of resistance. Ace, a key gene in neuronal signaling, is a prominent target of many insecticides and across several species, three amino acid replacements (I161V, G265A, and F330Y) provide resistance against several insecticides. Because temperature disturbs neuronal signaling homeostasis, we reasoned that the cost of insecticide resistance could be modulated by ambient temperature.

RESULTS

Experimental evolution of a natural Drosophila simulans population at hot and cold temperature regimes uncovered a surprisingly strong effect of ambient temperature. In the cold temperature regime, the resistance mutations were strongly counter selected (s = - 0.055), but in a hot environment, the fitness costs of resistance mutations were reduced by almost 50% (s = - 0.031). We attribute this unexpected observation to the advantage of the reduced enzymatic activity of resistance mutations in hot environments.

CONCLUSION

We show that fitness costs of insecticide resistance genes are temperature-dependent and suggest that the duration of insecticide-free periods need to be adjusted for different climatic regions to reflect these costs. We suggest that such environment-dependent fitness effects may be more common than previously assumed and pose a major challenge for modeling climate change.

Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

BACKGROUND

As global change and anthropogenic pressures continue to increase, conservation and management increasingly needs to consider species' potential to adapt to novel environmental conditions. Therefore, it is imperative to characterise the main selective forces acting on ecosystems, and how these may influence the evolutionary potential of populations and species. Using a multi-model seascape genomics approach, we compare putative environmental drivers of selection in three sympatric southern African marine invertebrates with contrasting ecology and life histories: Cape urchin (Parechinus angulosus), Common shore crab (Cyclograpsus punctatus), and Granular limpet (Scutellastra granularis).

RESULTS

Using pooled (Pool-seq), restriction-site associated DNA sequencing (RAD-seq), and seven outlier detection methods, we characterise genomic variation between populations along a strong biogeographical gradient. Of the three species, only S. granularis showed significant isolation-by-distance, and isolation-by-environment driven by sea surface temperatures (SST). In contrast, sea surface salinity (SSS) and range in air temperature correlated more strongly with genomic variation in C. punctatus and P. angulosus. Differences were also found in genomic structuring between the three species, with outlier loci contributing to two clusters in the East and West Coasts for S. granularis and P. angulosus, but not for C. punctatus.

CONCLUSION

The findings illustrate distinct evolutionary potential across species, suggesting that species-specific habitat requirements and responses to environmental stresses may be better predictors of evolutionary patterns than the strong environmental gradients within the region. We also found large discrepancies between outlier detection methodologies, and thus offer a novel multi-model approach to identifying the principal environmental selection forces acting on species. Overall, this work highlights how adding a comparative approach to seascape genomics (both with multiple models and species) can elucidate the intricate evolutionary responses of ecosystems to global change.

Resource quality determines the evolution of resistance and its genetic basis

Parasites impose strong selection on their hosts, but the level of any evolved resistance may be constrained by the availability of resources. However, studies identifying the genomic basis of such resource-mediated selection are rare, particularly in nonmodel organisms. Here, we investigated the role of nutrition in the evolution of resistance to a DNA virus (PiGV), and any associated trade-offs in a lepidopteran pest species (Plodia interpunctella). Through selection experiments and whole-genome resequencing, we identify genetic markers of resistance that vary between the nutritional environments during selection. We do not find consistent evolution of resistance in the presence of virus but rather see substantial variation among replicate populations. Resistance in a low-nutrition environment is negatively correlated with growth rate, consistent with an established trade-off between immunity and development, but this relationship is highly context dependent. Whole-genome resequencing of the host shows that resistance mechanisms are likely to be highly polygenic and although the underlying genetic architecture may differ between high and low-nutrition environments, similar mechanisms are commonly used. As a whole, our results emphasize the importance of the resource environment on influencing the evolution of resistance.

Long-Term Dynamics Among Wolbachia Strains During Thermal Adaptation of Their Drosophila melanogaster Hosts

Climate change is a major evolutionary force triggering thermal adaptation in a broad range of species. While the consequences of global warming are being studied for an increasing number of species, limited attention has been given to the evolutionary dynamics of endosymbionts in response to climate change. Here, we address this question by studying the dynamics of Wolbachia, a well-studied endosymbiont of Drosophila melanogaster. D. melanogaster populations infected with 13 different Wolbachia strains were exposed to novel hot and cold laboratory environments for up to 180 generations. The short-term dynamics suggested a temperature-related fitness difference resulting in the increase of clade V strains in the cold environment only. Our long-term analysis now uncovers that clade V dominates in all replicates after generation 60 irrespective of temperature treatment. We propose that adaptation of the Drosophila host to either temperature or Drosophila C virus (DCV) infection are the cause of the replicated, temporally non-concordant Wolbachia dynamics. Our study provides an interesting case demonstrating that even simple, well-controlled experiments can result in complex, but repeatable evolutionary dynamics, thus providing a cautionary note on too simple interpretations on the impact of climate change.

Phosphorylation State of ZFP24 Controls Oligodendrocyte Differentiation

Zinc finger protein ZFP24, formerly known as ZFP191, is essential for oligodendrocyte maturation and CNS myelination. Nevertheless, the mechanism by which ZFP24 controls these processes is unknown. We demonstrate that ZFP24 binds to a consensus DNA sequence in proximity to genes important for oligodendrocyte differentiation and CNS myelination, and we show that this binding enhances target gene expression. We also demonstrate that ZFP24 DNA binding is controlled by phosphorylation. Phosphorylated ZFP24, which does not bind DNA, is the predominant form in oligodendrocyte progenitor cells. As these cells mature into oligodendrocytes, the non-phosphorylated, DNA-binding form accumulates. Interestingly, ZFP24 displays overlapping genomic binding sites with the transcription factors MYRF, SOX10, and OLIG2, which are known to control oligodendrocyte differentiation. Our findings provide a mechanism by which dephosphorylation of ZFP24 mediates its binding to regulatory regions of genes important for oligodendrocyte maturation, controls their expression, and thereby regulates oligodendrocyte differentiation and CNS myelination.

Genomic architecture of parallel ecological divergence: Beyond a single environmental contrast

The study of parallel ecological divergence provides important clues to the operation of natural selection. Parallel divergence often occurs in heterogeneous environments with different kinds of environmental gradients in different locations, but the genomic basis underlying this process is unknown. We investigated the genomics of rapid parallel adaptation in the marine snail Littorina saxatilis in response to two independent environmental axes (crab-predation versus wave-action and low-shore versus high-shore). Using pooled whole-genome resequencing, we show that sharing of genomic regions of high differentiation between environments is generally low but increases at smaller spatial scales. We identify different shared genomic regions of divergence for each environmental axis and show that most of these regions overlap with candidate chromosomal inversions. Several inversion regions are divergent and polymorphic across many localities. We argue that chromosomal inversions could store shared variation that fuels rapid parallel adaptation to heterogeneous environments, possibly as balanced polymorphism shared by adaptive gene flow.

Exploring a Pool-seq-only approach for gaining population genomic insights in nonmodel species

Developing genomic insights is challenging in nonmodel species for which resources are often scarce and prohibitively costly. Here, we explore the potential of a recently established approach using Pool-seq data to generate a de novo genome assembly for mining exons, upon which Pool-seq data are used to estimate population divergence and diversity. We do this for two pairs of sympatric populations of brown trout (Salmo trutta): one naturally sympatric set of populations and another pair of populations introduced to a common environment. We validate our approach by comparing the results to those from markers previously used to describe the populations (allozymes and individual-based single nucleotide polymorphisms [SNPs]) and from mapping the Pool-seq data to a reference genome of the closely related Atlantic salmon (Salmo salar). We find that genomic differentiation (F ST) between the two introduced populations exceeds that of the naturally sympatric populations (F ST = 0.13 and 0.03 between the introduced and the naturally sympatric populations, respectively), in concordance with estimates from the previously used SNPs. The same level of population divergence is found for the two genome assemblies, but estimates of average nucleotide diversity differ ( π ¯  ≈ 0.002 and π ¯  ≈ 0.001 when mapping to S. trutta and S. salar, respectively), although the relationships between population values are largely consistent. This discrepancy might be attributed to biases when mapping to a haploid condensed assembly made of highly fragmented read data compared to using a high-quality reference assembly from a divergent species. We conclude that the Pool-seq-only approach can be suitable for detecting and quantifying genome-wide population differentiation, and for comparing genomic diversity in populations of nonmodel species where reference genomes are lacking.

Origin and Consequences of Chromosomal Inversions in the virilis Group of Drosophila

In Drosophila, large variations in rearrangement rate have been reported among different lineages and among Muller’s elements. Nevertheless, the mechanisms that are involved in the generation of inversions, their increase in frequency, as well as their impact on the genome are not completely understood. This is in part due to the lack of comparative studies on species distantly related to Drosophila melanogaster. Therefore, we sequenced and assembled the genomes of two species of the virilis phylad (Drosophila novamexicana [15010-1031.00] and Drosophila americana [SF12]), which are diverging from D. melanogaster for more than 40 Myr. Based on these data, we identified the precise location of six novel inversion breakpoints. A molecular characterization provided clear evidence that DAIBAM (a miniature inverted–repeat transposable element) was involved in the generation of eight out of the nine inversions identified. In contrast to what has been previously reported for D. melanogaster and close relatives, ectopic recombination is thus the prevalent mechanism of generating inversions in species of the virilis phylad. Using pool-sequencing data for three populations of D. americana, we also show that common polymorphic inversions create a high degree of genetic differentiation between populations for chromosomes X, 4, and 5 over large physical distances. We did not find statistically significant differences in expression levels between D. americana (SF12) and D. novamexicana (15010-1031.00) strains for the three genes surveyed (CG9588, Fig 4, and fab1) flanking three inversion breakpoints.

A simple genetic basis of adaptation to a novel thermal environment results in complex metabolic rewiring in Drosophila

BACKGROUND

Population genetic theory predicts that rapid adaptation is largely driven by complex traits encoded by many loci of small effect. Because large-effect loci are quickly fixed in natural populations, they should not contribute much to rapid adaptation.

RESULTS

To investigate the genetic architecture of thermal adaptation - a highly complex trait - we performed experimental evolution on a natural Drosophila simulans population. Transcriptome and respiration measurements reveal extensive metabolic rewiring after only approximately 60 generations in a hot environment. Analysis of genome-wide polymorphisms identifies two interacting selection targets, Sestrin and SNF4Aγ, pointing to AMPK, a central metabolic switch, as a key factor for thermal adaptation.

CONCLUSIONS

Our results demonstrate that large-effect loci segregating at intermediate allele frequencies can allow natural populations to rapidly respond to selection. Because SNF4Aγ also exhibits clinal variation in various Drosophila species, we suggest that this large-effect polymorphism is maintained by temporal and spatial temperature variation in natural environments.

Complex signatures of genomic variation of two non-model marine species in a homogeneous environment

BACKGROUND

Genomic tools are increasingly being used on non-model organisms to provide insights into population structure and variability, including signals of selection. However, most studies are carried out in regions with distinct environmental gradients or across large geographical areas, in which local adaptation is expected to occur. Therefore, the focus of this study is to characterize genomic variation and selective signals over short geographic areas within a largely homogeneous region. To assess adaptive signals between microhabitats within the rocky shore, we compared genomic variation between the Cape urchin (Parechinus angulosus), which is a low to mid-shore species, and the Granular limpet (Scutellastra granularis), a high shore specialist.

RESULTS

Using pooled restriction site associated DNA (RAD) sequencing, we described patterns of genomic variation and identified outlier loci in both species. We found relatively low numbers of outlier SNPs within each species, and identified outlier genes associated with different selective pressures than those previously identified in studies conducted over larger environmental gradients. The number of population-specific outlier loci differed between species, likely owing to differential selective pressures within the intertidal environment. Interestingly, the outlier loci were highly differentiated within the two northernmost populations for both species, suggesting that unique evolutionary forces are acting on marine invertebrates within this region.

CONCLUSIONS

Our study provides a background for comparative genomic studies focused on non-model species, as well as a baseline for the adaptive potential of marine invertebrates along the South African west coast. We also discuss the caveats associated with Pool-seq and potential biases of sequencing coverage on downstream genomic metrics. The findings provide evidence of species-specific selective pressures within a homogeneous environment, and suggest that selective forces acting on small scales are just as crucial to acknowledge as those acting on larger scales. As a whole, our findings imply that future population genomic studies should expand from focusing on model organisms and/or studying heterogeneous regions to better understand the evolutionary processes shaping current and future biodiversity patterns, particularly when used in a comparative phylogeographic context.

Utility of pooled sequencing for association mapping in nonmodel organisms

High-density genome-wide sequencing increases the likelihood of discovering genes of major effect and genomic structural variation in organisms. While there is an increasing availability of reference genomes across broad taxa, the greatest limitation to whole-genome sequencing of multiple individuals continues to be the costs associated with sequencing. To alleviate excessive costs, pooling multiple individuals with similar phenotypes and sequencing the homogenized DNA (Pool-Seq) can achieve high genome coverage, but at the loss of individual genotypes. Although Pool-Seq has been an effective method for association mapping in model organisms, it has not been frequently utilized in natural populations. To extend bioinformatic tools for rapid implementation of Pool-Seq data in nonmodel organisms, we developed a pipeline called PoolParty and illustrate its effectiveness in genetic association mapping. Alignment expectations based on five pooled Chinook salmon (Oncorhynchus tshawytscha) libraries showed that approximately 48% genome coverage per library could be achieved with reasonable sequencing effort. We additionally examined male and female O. tshawytscha libraries to illustrate how Pool-Seq techniques can successfully map known genes associated with functional differences among sexes such as growth hormone 2. Finally, we compared pools of individuals of different spawning ages for each sex to discover novel genes involved with age at maturity in O. tshawytscha such as opsin4 and transmembrane protein19. While not appropriate for every system, Pool-Seq data processed by the PoolParty pipeline is a practical method for identifying genes of major effect in nonmodel organisms when high genome coverage is necessary and cost is a limiting factor.

Physical mapping of QTL for tuber yield, starch content and starch yield in tetraploid potato (Solanum tuberosum L.) by means of genome wide genotyping by sequencing and the 8.3 K SolCAP SNP array

Background

Tuber yield and starch content of the cultivated potato are complex traits of decisive importance for breeding improved varieties. Natural variation of tuber yield and starch content depends on the environment and on multiple, mostly unknown genetic factors. Dissection and molecular identification of the genes and their natural allelic variants controlling these complex traits will lead to the development of diagnostic DNA-based markers, by which precision and efficiency of selection can be increased (precision breeding).

Results

Three case-control populations were assembled from tetraploid potato cultivars based on maximizing the differences between high and low tuber yield (TY), starch content (TSC) and starch yield (TSY, arithmetic product of TY and TSC). The case-control populations were genotyped by restriction-site associated DNA sequencing (RADseq) and the 8.3 k SolCAP SNP genotyping array. The allele frequencies of single nucleotide polymorphisms (SNPs) were compared between cases and controls. RADseq identified, depending on data filtering criteria, between 6664 and 450 genes with one or more differential SNPs for one, two or all three traits. Differential SNPs in 275 genes were detected using the SolCAP array. A genome wide association study using the SolCAP array on an independent, unselected population identified SNPs associated with tuber starch content in 117 genes. Physical mapping of the genes containing differential or associated SNPs, and comparisons between the two genome wide genotyping methods and two different populations identified genome segments on all twelve potato chromosomes harboring one or more quantitative trait loci (QTL) for TY, TSC and TSY.

Conclusions

Several hundred genes control tuber yield and starch content in potato. They are unequally distributed on all potato chromosomes, forming clusters between 0.5–4 Mbp width. The largest fraction of these genes had unknown function, followed by genes with putative signalling and regulatory functions. The genetic control of tuber yield and starch content is interlinked. Most differential SNPs affecting both traits had antagonistic effects: The allele increasing TY decreased TSC and vice versa. Exceptions were 89 SNP alleles which had synergistic effects on TY, TSC and TSY. These and the corresponding genes are primary targets for developing diagnostic markers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3979-9) contains supplementary material, which is available to authorized users.

Variant profiling of evolving prokaryotic populations

Genomic heterogeneity of bacterial species is observed and studied in experimental evolution experiments and clinical diagnostics, and occurs as micro-diversity of natural habitats. The challenge for genome research is to accurately capture this heterogeneity with the currently used short sequencing reads. Recent advances in NGS technologies improved the speed and coverage and thus allowed for deep sequencing of bacterial populations. This facilitates the quantitative assessment of genomic heterogeneity, including low frequency alleles or haplotypes. However, false positive variant predictions due to sequencing errors and mapping artifacts of short reads need to be prevented. We therefore created VarCap, a workflow for the reliable prediction of different types of variants even at low frequencies. In order to predict SNPs, InDels and structural variations, we evaluated the sensitivity and accuracy of different software tools using synthetic read data. The results suggested that the best sensitivity could be reached by a union of different tools, however at the price of increased false positives. We identified possible reasons for false predictions and used this knowledge to improve the accuracy by post-filtering the predicted variants according to properties such as frequency, coverage, genomic environment/localization and co-localization with other variants. We observed that best precision was achieved by using an intersection of at least two tools per variant. This resulted in the reliable prediction of variants above a minimum relative abundance of 2%. VarCap is designed for being routinely used within experimental evolution experiments or for clinical diagnostics. The detected variants are reported as frequencies within a VCF file and as a graphical overview of the distribution of the different variant/allele/haplotype frequencies. The source code of VarCap is available at https://github.com/ma2o/VarCap. In order to provide this workflow to a broad community, we implemeted VarCap on a Galaxy webserver, which is accessible at http://galaxy.csb.univie.ac.at.