The many landscapes of recombination in Drosophila melanogaster

High rates of phasing errors in highly polymorphic species with low levels of linkage disequilibrium

Short read sequencing of diploid individuals does not permit the direct inference of the sequence on each of the two homologous chromosomes. Although various phasing software packages exist, they were primarily tailored for and tested on human data, which differ from other species in factors that influence phasing, such as SNP density, amounts of linkage disequilibrium (LD) and sample sizes. Despite becoming increasingly popular for other species, the reliability of phasing in non-human data has not been evaluated to a sufficient extent. We scrutinized the phasing accuracy for Drosophila melanogaster, a species with high polymorphism levels and reduced LD relative to humans. We phased two D. melanogaster populations and compared the results to the known haplotypes. The performance increased with size of the reference panel and was highest when the reference panel and phased individuals were from the same population. Full genomic SNP data and inclusion of sequence read information also improved phasing. Despite humans and Drosophila having similar switch error rates between polymorphic sites, the distances between switch errors were much shorter in Drosophila with only fragments <300-1500 bp being correctly phased with ≥95% confidence. This suggests that the higher SNP density cannot compensate for the higher recombination rate in D. melanogaster. Furthermore, we show that populations that have gone through demographic events such as bottlenecks can be phased with higher accuracy. Our results highlight that statistically phased data are particularly error prone in species with large population sizes or populations lacking suitable reference panels.

Balancing selection on immunity genes: review of the current literature and new analysis in Drosophila melanogaster

Balancing selection has been widely assumed to be an important evolutionary force, yet even today little is known about its abundance and its impact on the patterns of genetic diversity. Several studies have shown examples of balancing selection in humans, plants or parasites, and many genes under balancing selection are involved in immunity. It has been proposed that host-parasite coevolution is one of the main forces driving immune genes to evolve under balancing selection. In this paper, we review the literature on balancing selection on immunity genes in several organisms, including Drosophila. Furthermore, we performed a genome scan for balancing selection in an African population of Drosophila melanogaster using coalescent simulations of a demographic model with and without selection. We find very few genes under balancing selection and only one novel candidate gene related to immunity. Finally, we discuss the possible causes of the low number of genes under balancing selection.

Whole-Genome Analysis of Individual Meiotic Events in Drosophila melanogaster Reveals That Noncrossover Gene Conversions Are Insensitive to Interference and the Centromere Effect

A century of genetic analysis has revealed that multiple mechanisms control the distribution of meiotic crossover events. In Drosophila melanogaster, two significant positional controls are interference and the strongly polar centromere effect. Here, we assess the factors controlling the distribution of crossovers (COs) and noncrossover gene conversions (NCOs) along all five major chromosome arms in 196 single meiotic divisions to generate a more detailed understanding of these controls on a genome-wide scale. Analyzing the outcomes of single meiotic events allows us to distinguish among different classes of meiotic recombination. In so doing, we identified 291 NCOs spread uniformly among the five major chromosome arms and 541 COs (including 52 double crossovers and one triple crossover). We find that unlike COs, NCOs are insensitive to the centromere effect and do not demonstrate interference. Although the positions of COs appear to be determined predominately by the long-range influences of interference and the centromere effect, each chromosome may display a different pattern of sensitivity to interference, suggesting that interference may not be a uniform global property. In addition, unbiased sequencing of a large number of individuals allows us to describe the formation of de novo copy number variants, the majority of which appear to be mediated by unequal crossing over between transposable elements. This work has multiple implications for our understanding of how meiotic recombination is regulated to ensure proper chromosome segregation and maintain genome stability.

Natural selection in a population of Drosophila melanogaster explained by changes in gene expression caused by sequence variation in core promoter regions

Background

Understanding the evolutionary forces that influence variation in gene regulatory regions in natural populations is an important challenge for evolutionary biology because natural selection for such variations could promote adaptive phenotypic evolution. Recently, whole-genome sequence analyses have identified regulatory regions subject to natural selection. However, these studies could not identify the relationship between sequence variation in the detected regions and change in gene expression levels. We analyzed sequence variations in core promoter regions, which are critical regions for gene regulation in higher eukaryotes, in a natural population of Drosophila melanogaster, and identified core promoter sequence variations associated with differences in gene expression levels subjected to natural selection.

Results

Among the core promoter regions whose sequence variation could change transcription factor binding sites and explain differences in expression levels, three core promoter regions were detected as candidates associated with purifying selection or selective sweep and seven as candidates associated with balancing selection, excluding the possibility of linkage between these regions and core promoter regions. CHKov1, which confers resistance to the sigma virus and related insecticides, was identified as core promoter regions that has been subject to selective sweep, although it could not be denied that selection for variation in core promoter regions was due to linked single nucleotide polymorphisms in the regulatory region outside core promoter regions. Nucleotide changes in core promoter regions of CHKov1 caused the loss of two basal transcription factor binding sites and acquisition of one transcription factor binding site, resulting in decreased gene expression levels. Of nine core promoter regions regions associated with balancing selection, brat, and CG9044 are associated with neuromuscular junction development, and Nmda1 are associated with learning, behavioral plasticity, and memory. Diversity of neural and behavioral traits may have been maintained by balancing selection.

Conclusions

Our results revealed the evolutionary process occurring by natural selection for differences in gene expression levels caused by sequence variation in core promoter regions in a natural population. The sequences of core promoter regions were diverse even within the population, possibly providing a source for natural selection.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-016-0606-3) contains supplementary material, which is available to authorized users.

A Glance at Recombination Hotspots in the Domestic Cat

Recombination has essential roles in increasing genetic variability within a population and in ensuring successful meiotic events. The objective of this study is to (i) infer the population-scaled recombination rate (ρ), and (ii) identify and characterize regions of increased recombination rate for the domestic cat, Felis silvestris catus. SNPs (n = 701) were genotyped in twenty-two East Asian feral cats (random bred). The SNPs covered ten different chromosomal regions (A1, A2, B3, C2, D1, D2, D4, E2, F2, X) with an average region size of 850 Kb and an average SNP density of 70 SNPs/region. The Bayesian method in the program inferRho was used to infer regional population recombination rates and hotspots localities. The regions exhibited variable population recombination rates and four decisive recombination hotspots were identified on cat chromosome A2, D1, and E2 regions. As a description of the identified hotspots, no correlation was detected between the GC content and the locality of recombination spots, and the hotspots enclosed L2 LINE elements and MIR and tRNA-Lys SINE elements.

Repression of harmful meiotic recombination in centromeric regions

During the first division of meiosis, segregation of homologous chromosomes reduces the chromosome number by half. In most species, sister chromatid cohesion and reciprocal recombination (crossing-over) between homologous chromosomes are essential to provide tension to signal proper chromosome segregation during the first meiotic division. Crossovers are not distributed uniformly throughout the genome and are repressed at and near the centromeres. Rare crossovers that occur too near or in the centromere interfere with proper segregation and can give rise to aneuploid progeny, which can be severely defective or inviable. We review here how crossing-over occurs and how it is prevented in and around the centromeres. Molecular mechanisms of centromeric repression are only now being elucidated. However, rapid advances in understanding crossing-over, chromosome structure, and centromere functions promise to explain how potentially deleterious crossovers are avoided in certain chromosomal regions while allowing beneficial crossovers in others.

Parallel Evolution of Copy-Number Variation across Continents in Drosophila melanogaster

Genetic differentiation across populations that is maintained in the presence of gene flow is a hallmark of spatially varying selection. In Drosophila melanogaster, the latitudinal clines across the eastern coasts of Australia and North America appear to be examples of this type of selection, with recent studies showing that a substantial portion of the D. melanogaster genome exhibits allele frequency differentiation with respect to latitude on both continents. As of yet there has been no genome-wide examination of differentiated copy-number variants (CNVs) in these geographic regions, despite their potential importance for phenotypic variation in Drosophila and other taxa. Here, we present an analysis of geographic variation in CNVs in D. melanogaster. We also present the first genomic analysis of geographic variation for copy-number variation in the sister species, D. simulans, in order to investigate patterns of parallel evolution in these close relatives. In D. melanogaster we find hundreds of CNVs, many of which show parallel patterns of geographic variation on both continents, lending support to the idea that they are influenced by spatially varying selection. These findings support the idea that polymorphic CNVs contribute to local adaptation in D. melanogaster In contrast, we find very few CNVs in D. simulans that are geographically differentiated in parallel on both continents, consistent with earlier work suggesting that clinal patterns are weaker in this species.

Genomic Patterns of Geographic Differentiation in Drosophila simulans

Geographic patterns of genetic differentiation have long been used to understand population history and to learn about the biological mechanisms of adaptation. Here we present an examination of genomic patterns of differentiation between northern and southern populations of Australian and North American Drosophila simulans, with an emphasis on characterizing signals of parallel differentiation. We report on the genomic scale of differentiation and functional enrichment of outlier SNPs. While, overall, signals of shared differentiation are modest, we find the strongest support for parallel differentiation in genomic regions that are associated with regulation. Comparisons to Drosophila melanogaster yield potential candidate genes involved in local adaptation in both species, providing insight into common selective pressures and responses. In contrast to D. melanogaster, in D. simulans we observe patterns of variation that are inconsistent with a model of temperate adaptation out of a tropical ancestral range, highlighting potential differences in demographic and colonization histories of this cosmopolitan species pair.

Secondary contact and local adaptation contribute to genome-wide patterns of clinal variation in Drosophila melanogaster

Populations arrayed along broad latitudinal gradients often show patterns of clinal variation in phenotype and genotype. Such population differentiation can be generated and maintained by both historical demographic events and local adaptation. These evolutionary forces are not mutually exclusive and can in some cases produce nearly identical patterns of genetic differentiation among populations. Here, we investigate the evolutionary forces that generated and maintain clinal variation genome-wide among populations of Drosophila melanogaster sampled in North America and Australia. We contrast patterns of clinal variation in these continents with patterns of differentiation among ancestral European and African populations. Using established and novel methods we derive here, we show that recently derived North America and Australia populations were likely founded by both European and African lineages and that this hybridization event likely contributed to genome-wide patterns of parallel clinal variation between continents. The pervasive effects of admixture mean that differentiation at only several hundred loci can be attributed to the operation of spatially varying selection using an FST outlier approach. Our results provide novel insight into the well-studied system of clinal differentiation in D. melanogaster and provide a context for future studies seeking to identify loci contributing to local adaptation in a wide variety of organisms, including other invasive species as well as temperate endemics.

Convergent Balancing Selection on an Antimicrobial Peptide in Drosophila

Genes of the immune system often evolve rapidly and adaptively, presumably driven by antagonistic interactions with pathogens [1-4]. Those genes encoding secreted antimicrobial peptides (AMPs), however, have failed to exhibit conventional signatures of strong adaptive evolution, especially in arthropods (e.g., [5, 6]) and often segregate for null alleles and gene deletions [3, 4, 7, 8]. Furthermore, quantitative genetic studies have failed to associate naturally occurring polymorphism in AMP genes with variation in resistance to infection [9-11]. Both the lack of signatures of positive selection in AMPs and lack of association between genotype and immune phenotypes have yielded an interpretation that AMP genes evolve under relaxed evolutionary constraint, with enough functional redundancy that variation in, or even loss of, any particular peptide would have little effect on overall resistance [12, 13]. In stark contrast to the current paradigm, we identified a naturally occurring amino acid polymorphism in the AMP Diptericin that is highly predictive of resistance to bacterial infection in Drosophila melanogaster [13]. The identical amino acid polymorphism arose in parallel in the sister species D. simulans, by independent mutation with equivalent phenotypic effect. Convergent substitutions at the same amino acid residue have evolved at least five times across the Drosophila genus. We hypothesize that the alternative alleles are maintained by balancing selection through context-dependent or fluctuating selection. This pattern of evolution appears to be common in AMPs but is invisible to conventional screens for adaptive evolution that are predicated on elevated rates of amino acid divergence.

The population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens

Drug resistance is a costly consequence of pathogen evolution and a major concern in public health. In this review, we show how population genetics can be used to study the evolution of drug resistance and also how drug resistance evolution is informative as an evolutionary model system. We highlight five examples from diverse organisms with particular focus on: (i) identifying drug resistance loci in the malaria parasite Plasmodium falciparum using the genomic signatures of selective sweeps, (ii) determining the role of epistasis in drug resistance evolution in influenza, (iii) quantifying the role of standing genetic variation in the evolution of drug resistance in HIV, (iv) using drug resistance mutations to study clonal interference dynamics in tuberculosis and (v) analysing the population structure of the core and accessory genome of Staphylococcus aureus to understand the spread of methicillin resistance. Throughout this review, we discuss the uses of sequence data and population genetic theory in studying the evolution of drug resistance.

Meiotic DSB patterning: A multifaceted process

Meiosis is a specialized two-step cell division responsible for genome haploidization and the generation of genetic diversity during gametogenesis. An integral and distinctive feature of the meiotic program is the evolutionarily conserved initiation of homologous recombination (HR) by the developmentally programmed induction of DNA double-strand breaks (DSBs). The inherently dangerous but essential act of DSB formation is subject to multiple forms of stringent and self-corrective regulation that collectively ensure fruitful and appropriate levels of genetic exchange without risk to cellular survival. Within this article we focus upon an emerging element of this control--spatial regulation--detailing recent advances made in understanding how DSBs are evenly distributed across the genome, and present a unified view of the underlying patterning mechanisms employed.

Sporadic, Global Linkage Disequilibrium Between Unlinked Segregating Sites

Demographic, genetic, or stochastic factors can lead to perfect linkage disequilibrium (LD) between alleles at two loci without respect to the extent of their physical distance, a phenomenon that Lawrence et al. (2005a) refer to as "genetic indistinguishability." This phenomenon can complicate genotype-phenotype association testing by hindering the ability to localize causal alleles, but has not been thoroughly explored from a theoretical perspective or using large, dense whole-genome polymorphism data sets. We derive a simple theoretical model of the prevalence of genetic indistinguishability between unlinked loci and verify its accuracy via simulation. We show that sample size and minor allele frequency are the major determinants of the prevalence of perfect LD between unlinked loci but that demographic factors, such as deviations from random mating, can produce significant effects as well. Finally, we quantify this phenomenon in three model organisms and find thousands of pairs of moderate-frequency ([Formula: see text]) genetically indistinguishable variants in relatively large data sets. These results clarify a previously underexplored population genetic phenomenon with important implications for association studies and define conditions under which it is likely to manifest.

Molecular Evolution of Drosophila Germline Stem Cell and Neural Stem Cell Regulating Genes

Here, we study the molecular evolution of a near complete set of genes that had functional evidence in the regulation of the Drosophila germline and neural stem cell. Some of these genes have previously been shown to be rapidly evolving by positive selection raising the possibility that stem cell genes as a group have elevated signatures of positive selection. Using recent Drosophila comparative genome sequences and population genomic sequences of Drosophila melanogaster, we have investigated both long- and short-term evolution occurring across these two different stem cell systems, and compared them with a carefully chosen random set of genes to represent the background rate of evolution. Our results showed an excess of genes with evidence of a recent selective sweep in both germline and neural stem cells in D. melanogaster. However compared with their control genes, both stem cell systems had no significant excess of genes with long-term recurrent positive selection in D. melanogaster, or across orthologous sequences from the melanogaster group. The evidence of long-term positive selection was limited to a subset of genes with specific functions in both the germline and neural stem cell system.

Adaptive Evolution Is Substantially Impeded by Hill-Robertson Interference in Drosophila

Hill-Robertson interference (HRi) is expected to reduce the efficiency of natural selection when two or more linked selected sites do not segregate freely, but no attempt has been done so far to quantify the overall impact of HRi on the rate of adaptive evolution for any given genome. In this work, we estimate how much HRi impedes the rate of adaptive evolution in the coding genome of Drosophila melanogaster. We compiled a data set of 6,141 autosomal protein-coding genes from Drosophila, from which polymorphism levels in D. melanogaster and divergence out to D. yakuba were estimated. The rate of adaptive evolution was calculated using a derivative of the McDonald-Kreitman test that controls for slightly deleterious mutations. We find that the rate of adaptive amino acid substitution at a given position of the genome is positively correlated to both the rate of recombination and the mutation rate, and negatively correlated to the gene density of the region. These correlations are robust to controlling for each other, for synonymous codon bias and for gene functions related to immune response and testes. We show that HRi diminishes the rate of adaptive evolution by approximately 27%. Interestingly, genes with low mutation rates embedded in gene poor regions lose approximately 17% of their adaptive substitutions whereas genes with high mutation rates embedded in gene rich regions lose approximately 60%. We conclude that HRi hampers the rate of adaptive evolution in Drosophila and that the variation in recombination, mutation, and gene density along the genome affects the HRi effect.

Recombining without Hotspots: A Comprehensive Evolutionary Portrait of Recombination in Two Closely Related Species of Drosophila

Meiotic recombination rate varies across the genome within and between individuals, populations, and species in virtually all taxa studied. In almost every species, this variation takes the form of discrete recombination hotspots, determined in some mammals by a protein called PRDM9. Hotspots and their determinants have a profound effect on the genomic landscape, and share certain features that extend across the tree of life. Drosophila, in contrast, are anomalous in their absence of hotspots, PRDM9, and other species-specific differences in the determination of recombination. To better understand the evolution of meiosis and general patterns of recombination across diverse taxa, we present a truly comprehensive portrait of recombination across time, combining recently published cross-based contemporary recombination estimates from each of two sister species with newly obtained linkage-disequilibrium-based historic estimates of recombination from both of these species. Using Drosophila pseudoobscura and Drosophila miranda as a model system, we compare recombination rate between species at multiple scales, and we suggest that Drosophila replicate the pattern seen in human-chimpanzee in which recombination rate is conserved at broad scales. We also find evidence of a species-wide recombination modifier(s), resulting in both a present and historic genome-wide elevation of recombination rates in D. miranda, and identify broad scale effects on recombination from the presence of an inversion. Finally, we reveal an unprecedented view of the distribution of recombination in D. pseudoobscura, illustrating patterns of linked selection and where recombination is taking place. Overall, by combining these estimation approaches, we highlight key similarities and differences in recombination between Drosophila and other organisms.

Fifteen years of genomewide scans for selection: trends, lessons and unaddressed genetic sources of complication

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example F(ST), cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach.

The Nature, Extent, and Consequences of Genetic Variation in the opa Repeats of Notch in Drosophila

Polyglutamine (pQ) tracts are abundant in proteins co-interacting on DNA. The lengths of these pQ tracts can modulate their interaction strengths. However, pQ tracts >40 residues are pathologically prone to amyloidogenic self-assembly. Here, we assess the extent and consequences of variation in the pQ-encoding opa repeats of Notch in Drosophila melanogaster. We use Sanger sequencing to genotype opa sequences (5′-CAX repeats), which have resisted assembly using short sequence reads. While most sampled lines carry the major allele opa31 encoding Q₁₃HQ₁₇ or the opa32 allele encoding Q₁₃HQ₁₈, many lines carry rare alleles encoding pQ tracts >32 residues: opa33a (Q₁₄HQ₁₈), opa33b (Q₁₅HQ₁₇), opa34 (Q₁₆HQ₁₇), opa35a1/opa35a2 (Q₁₃HQ₂₁), opa36 (Q₁₃HQ₂₂), and opa37 (Q₁₃HQ₂₃). Only one rare allele encodes a tract <31 residues: opa23 (Q₁₃–Q₁₀). This opa23 allele shortens the pQ tract while simultaneously eliminating the interrupting histidine. We introgressed these opa variant alleles into common backgrounds and measured the frequency of Notch-type phenotypes. Homozygotes for the short and long opa alleles have defects in embryonic survival and sensory bristle organ patterning, and sometimes show wing notching. Consistent with functional differences between Notch opa variants, we find that a scute inversion carrying the rare opa33b allele suppresses the bristle patterning defect caused by achaete/scute insufficiency, while an equivalent scute inversion carrying opa31 manifests the patterning defect. Our results demonstrate the existence of potent pQ variants of Notch and the need for long read genotyping of key repeat variables underlying gene regulatory networks.

The Mosaic Ancestry of the Drosophila Genetic Reference Panel and the D. melanogaster Reference Genome Reveals a Network of Epistatic Fitness Interactions

North American populations of Drosophila melanogaster derive from both European and African source populations, but despite their importance for genetic research, patterns of ancestry along their genomes are largely undocumented. Here, I infer geographic ancestry along genomes of the Drosophila Genetic Reference Panel (DGRP) and the D. melanogaster reference genome, which may have implications for reference alignment, association mapping, and population genomic studies in Drosophila. Overall, the proportion of African ancestry was estimated to be 20% for the DGRP and 9% for the reference genome. Combining my estimate of admixture timing with historical records, I provide the first estimate of natural generation time for this species (approximately 15 generations per year). Ancestry levels were found to vary strikingly across the genome, with less African introgression on the X chromosome, in regions of high recombination, and at genes involved in specific processes (e.g., circadian rhythm). An important role for natural selection during the admixture process was further supported by evidence that many unlinked pairs of loci showed a deficiency of Africa–Europe allele combinations between them. Numerous epistatic fitness interactions may therefore exist between African and European genotypes, leading to ongoing selection against incompatible variants. By focusing on hubs in this network of fitness interactions, I identified a set of interacting loci that include genes with roles in sensation and neuropeptide/hormone reception. These findings suggest that admixed D. melanogaster samples could become an important study system for the genetics of early-stage isolation between populations.

DNA Crossover Motifs Associated with Epigenetic Modifications Delineate Open Chromatin Regions in Arabidopsis

The rate of crossover, the reciprocal exchanges of homologous chromosomal segments, is not uniform along chromosomes differing between male and female meiocytes. To better understand the factors regulating this variable landscape, we performed a detailed genetic and epigenetic analysis of 737 crossover events in Arabidopsis thaliana. Crossovers were more frequent than expected in promoters. Three DNA motifs enriched in crossover regions and less abundant in crossover-poor pericentric regions were identified. One of these motifs, the CCN repeat, was previously unknown in plants. The A-rich motif was preferentially associated with promoters, while the CCN repeat and the CTT repeat motifs were preferentially associated with genes. Analysis of epigenetic modifications around the motifs showed, in most cases, a specific epigenetic architecture. For example, we show that there is a peak of nucleosome occupancy and of H3K4me3 around the CCN and CTT repeat motifs while nucleosome occupancy was lowest around the A-rich motif. Cytosine methylation levels showed a gradual decrease within ∼2 kb of the three motifs, being lowest at sites where crossover occurred. This landscape was conserved in the decreased DNA methylation1 mutant. In summary, the crossover motifs are associated with epigenetic landscapes corresponding to open chromatin and contributing to the nonuniformity of crossovers in Arabidopsis.

A Male-Specific Genetic Map of the Microcrustacean Daphnia pulex Based on Single-Sperm Whole-Genome Sequencing

Genetic linkage maps are critical for assembling draft genomes to a meaningful chromosome level and for deciphering the genomic underpinnings of biological traits. The estimates of recombination rates derived from genetic maps also play an important role in understanding multiple aspects of genomic evolution such as nucleotide substitution patterns and accumulation of deleterious mutations. In this study, we developed a high-throughput experimental approach that combines fluorescence-activated cell sorting, whole-genome amplification, and short-read sequencing to construct a genetic map using single-sperm cells. Furthermore, a computational algorithm was developed to analyze single-sperm whole-genome sequencing data for map construction. These methods allowed us to rapidly build a male-specific genetic map for the freshwater microcrustacean Daphnia pulex, which shows significant improvements compared to a previous map. With a total of mapped 1672 haplotype blocks and an average intermarker distance of 0.87 cM, this map spans a total genetic distance of 1451 Kosambi cM and comprises 90% of the resolved regions in the current Daphnia reference assembly. The map also reveals the mistaken mapping of seven scaffolds in the reference assembly onto chromosome II by a previous microsatellite map based on F2 crosses. Our approach can be easily applied to many other organisms and holds great promise for unveiling the intragenomic and intraspecific variation in the recombination rates.

The Role of piRNA-Mediated Epigenetic Silencing in the Population Dynamics of Transposable Elements in Drosophila melanogaster

The piwi-interacting RNAs (piRNA) are small RNAs that target selfish transposable elements (TEs) in many animal genomes. Until now, piRNAs’ role in TE population dynamics has only been discussed in the context of their suppression of TE transposition, which alone is not sufficient to account for the skewed frequency spectrum and stable containment of TEs. On the other hand, euchromatic TEs can be epigenetically silenced via piRNA-dependent heterochromatin formation and, similar to the widely known “Position-effect variegation”, heterochromatin induced by TEs can “spread” into nearby genes. We hypothesized that the piRNA-mediated spread of heterochromatin from TEs into adjacent genes has deleterious functional effects and leads to selection against individual TEs. Unlike previously identified deleterious effects of TEs due to the physical disruption of DNA, the functional effect we investigated here is mediated through the epigenetic influences of TEs. We found that the repressive chromatin mark, H3K9me, is elevated in sequences adjacent to euchromatic TEs at multiple developmental stages in Drosophila melanogaster. Furthermore, the heterochromatic states of genes depend not only on the number of and distance from adjacent TEs, but also on the likelihood that their nearest TEs are targeted by piRNAs. These variations in chromatin status probably have functional consequences, causing genes near TEs to have lower expression. Importantly, we found stronger selection against TEs that lead to higher H3K9me enrichment of adjacent genes, demonstrating the pervasive evolutionary consequences of TE-induced epigenetic silencing. Because of the intrinsic biological mechanism of piRNA amplification, spread of TE heterochromatin could result in the theoretically required synergistic deleterious effects of TE insertions for stable containment of TE copy number. The indirect deleterious impact of piRNA-mediated epigenetic silencing of TEs is a previously unexplored, yet important, element for the evolutionary dynamics of TEs.

The piwi-interacting RNAs (piRNAs) are small RNAs that can suppress the expression of selfish transposable elements (TEs) in many animal genomes. One mechanism by which piRNAs silence TEs is through the formation of heterochromatin, which is condensed chromatin and generally associated with repressed gene expression. Several functional studies have demonstrated that piRNA-mediated heterochromatin of TEs can spread to adjacent genes. We hypothesized that this spread of TE-induced heterochromatin influences the function of adjacent genes, ultimately resulting in selection against individual TEs. Consistent with our hypothesis, we found that sequences and genes adjacent to TEs are enriched in heterochromatic marks. We determine that this TE-induced variation in epigenetic status is probably piRNA-dependent and that this change in chromatin state influences the expression levels of adjacent genes. Importantly, TEs that lead to higher heterochromatin enrichment of adjacent genes are more strongly selected against, demonstrating the evolutionary consequences of TE-induced epigenetic silencing. In contrast to previously studied deleterious impacts of TEs, which depend on TEs’ physical disruptions of DNAs, our proposed functional effect of TEs is mediated through their epigenetic influence. Our study suggests that the piRNA-dependent epigenetic impact of TEs may play an important role in the evolutionary dynamics of TEs.

Widely distributed hot and cold spots in meiotic recombination as shown by the sequencing of rice F2 plants

Numerous studies have argued that environmental variations may contribute to evolution through the generation of novel heritable variations via meiotic recombination, which plays a crucial role in crop domestication and improvement. Rice is one of the most important staple crops, but no direct estimate of recombination events has yet been made at a fine scale. Here, we address this limitation by sequencing 41 rice individuals with high sequencing coverage and c. 900 000 accurate markers. An average of 33.9 crossover (c. 4.53 cM Mb(-1) ) and 2.47 non-crossover events were detected per F2 plant, which is similar to the values in Arabidopsis. Although not all samples in the stress treatment group showed an increased number of crossover events, environmental stress increased the recombination rate in c. 28.5% of samples. Interestingly, the crossovers showed a highly uneven distribution among and along chromosomes, with c. 13.9% of the entire genome devoid of crossovers, including 11 of the 12 centromere regions, and c. 0.72% of the genome containing large numbers of crossovers (> 50 cM Mb(-1) ). The gene ontology (GO) categories showed that genes clustered within the recombination hot spot regions primarily tended to be involved in responses to environmental stimuli, suggesting that recombination plays an important role for adaptive evolution in rapidly changing environments.

Phyloproteomic Analysis of 11780 Six-Residue-Long Motifs Occurrences

How is it possible to find good traits for phylogenetic reconstructions? Here, we present a new phyloproteomic criterion that is an occurrence of simple motifs which can be imprints of evolution history. We studied the occurrences of 11780 six-residue-long motifs consisting of two randomly located amino acids in 97 eukaryotic and 25 bacterial proteomes. For all eukaryotic proteomes, with the exception of the Amoebozoa, Stramenopiles, and Diplomonadida kingdoms, the number of proteins containing the motifs from the first group (one of the two amino acids occurs once at the terminal position) made about 20%; in the case of motifs from the second (one of two amino acids occurs one time within the pattern) and third (the two amino acids occur randomly) groups, 30% and 50%, respectively. For bacterial proteomes, this relationship was 10%, 27%, and 63%, respectively. The matrices of correlation coefficients between numbers of proteins where a motif from the set of 11780 motifs appears at least once in 9 kingdoms and 5 phyla of bacteria were calculated. Among the correlation coefficients for eukaryotic proteomes, the correlation between the animal and fungi kingdoms (0.62) is higher than between fungi and plants (0.54). Our study provides support that animals and fungi are sibling kingdoms. Comparison of the frequencies of six-residue-long motifs in different proteomes allows obtaining phylogenetic relationships based on similarities between these frequencies: the Diplomonadida kingdoms are more close to Bacteria than to Eukaryota; Stramenopiles and Amoebozoa are more close to each other than to other kingdoms of Eukaryota.

Genome-wide tests for introgression between cactophilic Drosophila implicate a role of inversions during speciation

Models of speciation‐with‐gene‐flow have shown that the reduction in recombination between alternative chromosome arrangements can facilitate the fixation of locally adaptive genes in the face of gene flow and contribute to speciation. However, it has proven frustratingly difficult to show empirically that inversions have reduced gene flow and arose during or shortly after the onset of species divergence rather than represent ancestral polymorphisms. Here, we present an analysis of whole genome data from a pair of cactophilic fruit flies, Drosophila mojavensis and D. arizonae, which are reproductively isolated in the wild and differ by several large inversions on three chromosomes. We found an increase in divergence at rearranged compared to colinear chromosomes. Using the density of divergent sites in short sequence blocks we fit a series of explicit models of species divergence in which gene flow is restricted to an initial period after divergence and may differ between colinear and rearranged parts of the genome. These analyses show that D. mojavensis and D. arizonae have experienced postdivergence gene flow that ceased around 270 KY ago and was significantly reduced in chromosomes with fixed inversions. Moreover, we show that these inversions most likely originated around the time of species divergence which is compatible with theoretical models that posit a role of inversions in speciation with gene flow.

Origin, evolution, and population genetics of the selfish Segregation Distorter gene duplication in European and African populations of Drosophila melanogaster

Meiotic drive elements are a special class of evolutionarily "selfish genes" that subvert Mendelian segregation to gain preferential transmission at the expense of homologous loci. Many drive elements appear to be maintained in populations as stable polymorphisms, their equilibrium frequencies determined by the balance between drive (increasing frequency) and selection (decreasing frequency). Here we show that a classic, seemingly balanced, drive system is instead characterized by frequent evolutionary turnover giving rise to dynamic, rather than stable, equilibrium frequencies. The autosomal Segregation Distorter (SD) system of the fruit fly Drosophila melanogaster is a selfish coadapted meiotic drive gene complex in which the major driver corresponds to a partial duplication of the gene Ran-GTPase activating protein (RanGAP). SD chromosomes segregate at similar, low frequencies of 1-5% in natural populations worldwide, consistent with a balanced polymorphism. Surprisingly, our population genetic analyses reveal evidence for parallel, independent selective sweeps of different SD chromosomes in populations on different continents. These findings suggest that, rather than persisting at a single stable equilibrium, SD chromosomes turn over frequently within populations.

A Composite-Likelihood Method for Detecting Incomplete Selective Sweep from Population Genomic Data

Adaptive evolution occurs as beneficial mutations arise and then increase in frequency by positive natural selection. How, when, and where in the genome such evolutionary events occur is a fundamental question in evolutionary biology. It is possible to detect ongoing positive selection or an incomplete selective sweep in species with sexual reproduction because, when a beneficial mutation is on the way to fixation, homologous chromosomes in the population are divided into two groups: one carrying the beneficial allele with very low polymorphism at nearby linked loci and the other carrying the ancestral allele with a normal pattern of sequence variation. Previous studies developed long-range haplotype tests to capture this difference between two groups as the signal of an incomplete selective sweep. In this study, we propose a composite-likelihood-ratio (CLR) test for detecting incomplete selective sweeps based on the joint sampling probabilities for allele frequencies of two groups as a function of strength of selection and recombination rate. Tested against simulated data, this method yielded statistical power and accuracy in parameter estimation that are higher than the iHS test and comparable to the more recently developed nSL test. This procedure was also applied to African Drosophila melanogaster population genomic data to detect candidate genes under ongoing positive selection. Upon visual inspection of sequence polymorphism, candidates detected by our CLR method exhibited clear haplotype structures predicted under incomplete selective sweeps. Our results suggest that different methods capture different aspects of genetic information regarding incomplete sweeps and thus are partially complementary to each other.

Extreme recombination frequencies shape genome variation and evolution in the honeybee, Apis mellifera

Meiotic recombination is a fundamental cellular process, with important consequences for evolution and genome integrity. However, we know little about how recombination rates vary across the genomes of most species and the molecular and evolutionary determinants of this variation. The honeybee, Apis mellifera, has extremely high rates of meiotic recombination, although the evolutionary causes and consequences of this are unclear. Here we use patterns of linkage disequilibrium in whole genome resequencing data from 30 diploid honeybees to construct a fine-scale map of rates of crossing over in the genome. We find that, in contrast to vertebrate genomes, the recombination landscape is not strongly punctate. Crossover rates strongly correlate with levels of genetic variation, but not divergence, which indicates a pervasive impact of selection on the genome. Germ-line methylated genes have reduced crossover rate, which could indicate a role of methylation in suppressing recombination. Controlling for the effects of methylation, we do not infer a strong association between gene expression patterns and recombination. The site frequency spectrum is strongly skewed from neutral expectations in honeybees: rare variants are dominated by AT-biased mutations, whereas GC-biased mutations are found at higher frequencies, indicative of a major influence of GC-biased gene conversion (gBGC), which we infer to generate an allele fixation bias 5 – 50 times the genomic average estimated in humans. We uncover further evidence that this repair bias specifically affects transitions and favours fixation of CpG sites. Recombination, via gBGC, therefore appears to have profound consequences on genome evolution in honeybees and interferes with the process of natural selection. These findings have important implications for our understanding of the forces driving molecular evolution.

Evolution results from changes in allele frequencies in populations. The main forces that cause such changes are natural selection and random genetic drift. However, an additional process, GC-biased gene conversion (gBGC), associated with meiotic recombination, affects the probability that alleles are passed from one generation to the next. The honeybee, Apis mellifera, has extremely high recombination rates—more than 20 times to those observed in humans. However, the reason for this is unknown and the effects of such high recombination rates on evolution are not well understood. Here we use patterns of genetic variation in the genomes of 30 honeybees to infer variation in the rate of recombination across the genome. We find that recombination rates and levels of genetic variation are strongly correlated, which is indicative of a pervasive impact of natural selection on genetic variation. We also infer a major role of DNA methylation in determining recombination rates in genes. Patterns of genetic variation appear to be strongly skewed due to the effects of gBGC, suggesting that recombination generates a bias in transmission of alleles during meiosis. This process seems to be interfering with the efficacy of selection at removing deleterious alleles and favouring beneficial ones. Recombination therefore has a huge impact on genetic variation and evolution in honeybees and appears to play a dominant role in genome evolution.

Enhancing the mathematical properties of new haplotype homozygosity statistics for the detection of selective sweeps

Soft selective sweeps represent an important form of adaptation in which multiple haplotypes bearing adaptive alleles rise to high frequency. Most statistical methods for detecting selective sweeps from genetic polymorphism data, however, have focused on identifying hard selective sweeps in which a favored allele appears on a single haplotypic background; these methods might be underpowered to detect soft sweeps. Among exceptions is the set of haplotype homozygosity statistics introduced for the detection of soft sweeps by Garud et al. (2015). These statistics, examining frequencies of multiple haplotypes in relation to each other, include H12, a statistic designed to identify both hard and soft selective sweeps, and H2/H1, a statistic that conditional on high H12 values seeks to distinguish between hard and soft sweeps. A challenge in the use of H2/H1 is that its range depends on the associated value of H12, so that equal H2/H1 values might provide different levels of support for a soft sweep model at different values of H12. Here, we enhance the H12 and H2/H1 haplotype homozygosity statistics for selective sweep detection by deriving the upper bound on H2/H1 as a function of H12, thereby generating a statistic that normalizes H2/H1 to lie between 0 and 1. Through a reanalysis of resequencing data from inbred lines of Drosophila, we show that the enhanced statistic both strengthens interpretations obtained with the unnormalized statistic and leads to empirical insights that are less readily apparent without the normalization.

Multi-locus analysis of genomic time series data from experimental evolution

Genomic time series data generated by evolve-and-resequence (E&R) experiments offer a powerful window into the mechanisms that drive evolution. However, standard population genetic inference procedures do not account for sampling serially over time, and new methods are needed to make full use of modern experimental evolution data. To address this problem, we develop a Gaussian process approximation to the multi-locus Wright-Fisher process with selection over a time course of tens of generations. The mean and covariance structure of the Gaussian process are obtained by computing the corresponding moments in discrete-time Wright-Fisher models conditioned on the presence of a linked selected site. This enables our method to account for the effects of linkage and selection, both along the genome and across sampled time points, in an approximate but principled manner. We first use simulated data to demonstrate the power of our method to correctly detect, locate and estimate the fitness of a selected allele from among several linked sites. We study how this power changes for different values of selection strength, initial haplotypic diversity, population size, sampling frequency, experimental duration, number of replicates, and sequencing coverage depth. In addition to providing quantitative estimates of selection parameters from experimental evolution data, our model can be used by practitioners to design E&R experiments with requisite power. We also explore how our likelihood-based approach can be used to infer other model parameters, including effective population size and recombination rate. Then, we apply our method to analyze genome-wide data from a real E&R experiment designed to study the adaptation of D. melanogaster to a new laboratory environment with alternating cold and hot temperatures.

A growing number of experimental biologists are generating “evolve-and-resequence” (E&R) data in which the genomes of an experimental population are repeatedly sequenced over time. The resulting time series data provide important new insights into the dynamics of evolution. This type of analysis has only recently been made possible by next-generation sequencing, and new statistical procedures are required to analyze this novel data source. We present such a procedure here, and apply it to both simulated and real E&R data.

Parallel faster-X evolution of gene expression and protein sequences in Drosophila: beyond differences in expression properties and protein interactions

Population genetics models predict that the X (or Z) chromosome will evolve at faster rates than the autosomes in XY (or ZW) systems. Studies of molecular evolution using large datasets in multiple species have provided evidence supporting this faster-X effect in protein-coding sequences and, more recently, in transcriptomes. However, X-linked and autosomal genes differ significantly in important properties besides hemizygosity in males, including gene expression levels, tissue specificity in gene expression, and the number of interactions in which they are involved (i.e., protein-protein or DNA-protein interactions). Most important, these properties are known to correlate with rates of evolution, which raises the question of whether differences between the X chromosome and autosomes in gene properties, rather than hemizygosity, are sufficient to explain faster-X evolution. Here I investigate this possibility using whole genome sequences and transcriptomes of Drosophila yakuba and D. santomea and show that this is not the case. Additional factors are needed to account for faster-X evolution of both gene expression and protein-coding sequences beyond differences in gene properties, likely a higher incidence of positive selection in combination with the accumulation of weakly deleterious mutations.

Soft shoulders ahead: spurious signatures of soft and partial selective sweeps result from linked hard sweeps

Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of "soft shoulders" underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.

Recent selective sweeps in North American Drosophila melanogaster show signatures of soft sweeps

Adaptation from standing genetic variation or recurrent de novo mutation in large populations should commonly generate soft rather than hard selective sweeps. In contrast to a hard selective sweep, in which a single adaptive haplotype rises to high population frequency, in a soft selective sweep multiple adaptive haplotypes sweep through the population simultaneously, producing distinct patterns of genetic variation in the vicinity of the adaptive site. Current statistical methods were expressly designed to detect hard sweeps and most lack power to detect soft sweeps. This is particularly unfortunate for the study of adaptation in species such as Drosophila melanogaster, where all three confirmed cases of recent adaptation resulted in soft selective sweeps and where there is evidence that the effective population size relevant for recent and strong adaptation is large enough to generate soft sweeps even when adaptation requires mutation at a specific single site at a locus. Here, we develop a statistical test based on a measure of haplotype homozygosity (H12) that is capable of detecting both hard and soft sweeps with similar power. We use H12 to identify multiple genomic regions that have undergone recent and strong adaptation in a large population sample of fully sequenced Drosophila melanogaster strains from the Drosophila Genetic Reference Panel (DGRP). Visual inspection of the top 50 candidates reveals that in all cases multiple haplotypes are present at high frequencies, consistent with signatures of soft sweeps. We further develop a second haplotype homozygosity statistic (H2/H1) that, in combination with H12, is capable of differentiating hard from soft sweeps. Surprisingly, we find that the H12 and H2/H1 values for all top 50 peaks are much more easily generated by soft rather than hard sweeps. We discuss the implications of these results for the study of adaptation in Drosophila and in species with large census population sizes.

Evolutionary adaptation is a process in which beneficial mutations increase in frequency in response to selective pressures. If these mutations were previously rare or absent from the population, adaptation should generate a characteristic signature in the genetic diversity around the adaptive locus, known as a selective sweep. Such selective sweeps can be distinguished into hard selective sweeps, where only a single adaptive mutation rises in frequency, or soft selective sweeps, where multiple adaptive mutations at the same locus sweep through the population simultaneously. Here we design a new statistical method that can identify both hard and soft sweeps in population genomic data and apply this method to a Drosophila melanogaster population genomic dataset consisting of 145 sequenced strains collected in North Carolina. We find that selective sweeps were abundant in the recent history of this population. Interestingly, we also find that practically all of the strongest and most recent sweeps show patterns that are more consistent with soft rather than hard sweeps. We discuss the implications of these findings for the discovery and quantification of adaptation from population genomic data in Drosophila and other species with large population sizes.

Genomic correlates of recombination rate and its variability across eight recombination maps in the western honey bee (Apis mellifera L.)

Background

Meiotic recombination has traditionally been explained based on the structural requirement to stabilize homologous chromosome pairs to ensure their proper meiotic segregation. Competing hypotheses seek to explain the emerging findings of significant heterogeneity in recombination rates within and between genomes, but intraspecific comparisons of genome-wide recombination patterns are rare. The honey bee (Apis mellifera) exhibits the highest rate of genomic recombination among multicellular animals with about five cross-over events per chromatid.

Results

Here, we present a comparative analysis of recombination rates across eight genetic linkage maps of the honey bee genome to investigate which genomic sequence features are correlated with recombination rate and with its variation across the eight data sets, ranging in average marker spacing ranging from 1 Mbp to 120 kbp. Overall, we found that GC content explained best the variation in local recombination rate along chromosomes at the analyzed 100 kbp scale. In contrast, variation among the different maps was correlated to the abundance of microsatellites and several specific tri- and tetra-nucleotides.

Conclusions

The combined evidence from eight medium-scale recombination maps of the honey bee genome suggests that recombination rate variation in this highly recombining genome might be due to the DNA configuration instead of distinct sequence motifs. However, more fine-scale analyses are needed. The empirical basis of eight differing genetic maps allowed for robust conclusions about the correlates of the local recombination rates and enabled the study of the relation between DNA features and variability in local recombination rates, which is particularly relevant in the honey bee genome with its exceptionally high recombination rate.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1281-2) contains supplementary material, which is available to authorized users.

Power analysis of artificial selection experiments using efficient whole genome simulation of quantitative traits

Evolve and resequence studies combine artificial selection experiments with massively parallel sequencing technology to study the genetic basis for complex traits. In these experiments, individuals are selected for extreme values of a trait, causing alleles at quantitative trait loci (QTL) to increase or decrease in frequency in the experimental population. We present a new analysis of the power of artificial selection experiments to detect and localize quantitative trait loci. This analysis uses a simulation framework that explicitly models whole genomes of individuals, quantitative traits, and selection based on individual trait values. We find that explicitly modeling QTL provides qualitatively different insights than considering independent loci with constant selection coefficients. Specifically, we observe how interference between QTL under selection affects the trajectories and lengthens the fixation times of selected alleles. We also show that a substantial portion of the genetic variance of the trait (50–100%) can be explained by detected QTL in as little as 20 generations of selection, depending on the trait architecture and experimental design. Furthermore, we show that power depends crucially on the opportunity for recombination during the experiment. Finally, we show that an increase in power is obtained by leveraging founder haplotype information to obtain allele frequency estimates.

Patterns of linkage disequilibrium and long range hitchhiking in evolving experimental Drosophila melanogaster populations

Whole-genome resequencing of experimental populations evolving under a specific selection regime has become a popular approach to determine genotype-phenotype maps and understand adaptation to new environments. Despite its conceptual appeal and success in identifying some causative genes, it has become apparent that many studies suffer from an excess of candidate loci. Several explanations have been proposed for this phenomenon, but it is clear that information about the linkage structure during such experiments is needed. Until now only Pool-Seq (whole-genome sequencing of pools of individuals) data were available, which do not provide sufficient information about the correlation between linked sites. We address this problem in two complementary analyses of three replicate Drosophila melanogaster populations evolving to a new hot temperature environment for almost 70 generations. In the first analysis, we sequenced 58 haploid genomes from the founder population and evolved flies at generation 67. We show that during the experiment linkage disequilibrium (LD) increased almost uniformly over much greater distances than typically seen in Drosophila. In the second analysis, Pool-Seq time series data of the three replicates were combined with haplotype information from the founder population to follow blocks of initial haplotypes over time. We identified 17 selected haplotype-blocks that started at low frequencies in the base population and increased in frequency during the experiment. The size of these haplotype-blocks ranged from 0.082 to 4.01 Mb. Moreover, between 42% and 46% of the top candidate single nucleotide polymorphisms from the comparison of founder and evolved populations fell into the genomic region covered by the haplotype-blocks. We conclude that LD in such rising haplotype-blocks results in long range hitchhiking over multiple kilobase-sized regions. LD in such haplotype-blocks is therefore a major factor contributing to an excess of candidate loci. Although modifications of the experimental design may help to reduce the hitchhiking effect and allow for more precise mapping of causative variants, we also note that such haplotype-blocks might be well suited to study the dynamics of selected genomic regions during experimental evolution studies.

Footprints of ancient-balanced polymorphisms in genetic variation data from closely related species

When long-lasting, balancing selection can lead to “trans-species” polymorphisms that are shared by two or more species identical by descent. In such cases, the gene genealogy at the selected site clusters by allele instead of by species, and nearby neutral sites also have unusual genealogies because of linkage. While this scenario is expected to leave discernible footprints in genetic variation data, the specific patterns remain poorly characterized. Motivated by recent findings in primates, we focus on the case of a biallelic polymorphism under ancient balancing selection and derive approximations for summaries of the polymorphism data from two species. Specifically, we characterize the length of the segment that carries most of the footprints, the expected number of shared neutral single nucleotide polymorphisms (SNPs), and the patterns of allelic associations among them. We confirm the accuracy of our approximations by coalescent simulations. We further show that for humans and chimpanzees—more generally, for pairs of species with low genetic diversity levels—these patterns are highly unlikely to be generated by neutral recurrent mutations. We discuss the implications for the design and interpretation of genome scans for ancient balanced polymorphisms in primates and other taxa.

Causes and consequences of crossing-over evidenced via a high-resolution recombinational landscape of the honey bee

Background

Social hymenoptera, the honey bee (Apis mellifera) in particular, have ultra-high crossover rates and a large degree of intra-genomic variation in crossover rates. Aligned with haploid genomics of males, this makes them a potential model for examining the causes and consequences of crossing over. To address why social insects have such high crossing-over rates and the consequences of this, we constructed a high-resolution recombination atlas by sequencing 55 individuals from three colonies with an average marker density of 314 bp/marker.

Results

We find crossing over to be especially high in proximity to genes upregulated in worker brains, but see no evidence for a coupling with immune-related functioning. We detect only a low rate of non-crossover gene conversion, contrary to current evidence. This is in striking contrast to the ultrahigh crossing-over rate, almost double that previously estimated from lower resolution data. We robustly recover the predicted intragenomic correlations between crossing over and both population level diversity and GC content, which could be best explained as indirect and direct consequences of crossing over, respectively.

Conclusions

Our data are consistent with the view that diversification of worker behavior, but not immune function, is a driver of the high crossing-over rate in bees. While we see both high diversity and high GC content associated with high crossing-over rates, our estimate of the low non-crossover rate demonstrates that high non-crossover rates are not a necessary consequence of high recombination rates.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0566-0) contains supplementary material, which is available to authorized users.

The molecular biology of meiosis in plants

Meiosis is the cell division that reshuffles genetic information between generations. Recently, much progress has been made in understanding this process; in particular, the identification and functional analysis of more than 80 plant genes involved in meiosis have dramatically deepened our knowledge of this peculiar cell division. In this review, we provide an overview of advancements in the understanding of all aspects of plant meiosis, including recombination, chromosome synapsis, cell cycle control, chromosome distribution, and the challenge of polyploidy.

Genomic evidence of rapid and stable adaptive oscillations over seasonal time scales in Drosophila

In many species, genomic data have revealed pervasive adaptive evolution indicated by the fixation of beneficial alleles. However, when selection pressures are highly variable along a species' range or through time adaptive alleles may persist at intermediate frequencies for long periods. So called “balanced polymorphisms” have long been understood to be an important component of standing genetic variation, yet direct evidence of the strength of balancing selection and the stability and prevalence of balanced polymorphisms has remained elusive. We hypothesized that environmental fluctuations among seasons in a North American orchard would impose temporally variable selection on Drosophila melanogaster that would drive repeatable adaptive oscillations at balanced polymorphisms. We identified hundreds of polymorphisms whose frequency oscillates among seasons and argue that these loci are subject to strong, temporally variable selection. We show that these polymorphisms respond to acute and persistent changes in climate and are associated in predictable ways with seasonally variable phenotypes. In addition, our results suggest that adaptively oscillating polymorphisms are likely millions of years old, with some possibly predating the divergence between D. melanogaster and D. simulans. Taken together, our results are consistent with a model of balancing selection wherein rapid temporal fluctuations in climate over generational time promotes adaptive genetic diversity at loci underlying polygenic variation in fitness related phenotypes.

Herein, we investigate the genomic basis of rapid adaptive evolution in response to seasonal fluctuations in the environment. We identify hundreds of polymorphisms (seasonal SNPs) that undergo dramatic shifts in allele frequency – on average between 40 and 60% – and oscillate between seasons repeatedly over multiple years, likely inducing high levels of genome-wide genetic differentiation. We provide evidence that seasonal SNPs are functional, being both sensitive to an acute frost event and associated with two stress tolerance traits. Finally, we show that some seasonal SNPs are possibly ancient balanced polymorphisms. Taken together, our results suggest that environmental heterogeneity can promote the long-term persistence of functional polymorphisms within populations that fuels fast directional adaptive response at any one time.

Msh4 and Msh5 function in SC-independent chiasma formation during the streamlined meiosis of Tetrahymena

ZMM proteins have been defined in budding yeast as factors that are collectively involved in the formation of interfering crossovers (COs) and synaptonemal complexes (SCs), and they are a hallmark of the predominant meiotic recombination pathway of most organisms. In addition to this so-called class I CO pathway, a minority of crossovers are formed by a class II pathway, which involves the Mus81-Mms4 endonuclease complex. This is the only CO pathway in the SC-less meiosis of the fission yeast. ZMM proteins (including SC components) were always found to be co-occurring and hence have been regarded as functionally linked. Like the fission yeast, the protist Tetrahymena thermophila does not possess a SC, and its COs are dependent on Mus81-Mms4. Here we show that the ZMM proteins Msh4 and Msh5 are required for normal chiasma formation, and we propose that they have a pro-CO function outside a canonical class I pathway in Tetrahymena. Thus, the two-pathway model is not tenable as a general rule.

Uncovering the functional constraints underlying the genomic organization of the odorant-binding protein genes

Animal olfactory systems have a critical role for the survival and reproduction of individuals. In insects, the odorant-binding proteins (OBPs) are encoded by a moderately sized gene family, and mediate the first steps of the olfactory processing. Most OBPs are organized in clusters of a few paralogs, which are conserved over time. Currently, the biological mechanism explaining the close physical proximity among OBPs is not yet established. Here, we conducted a comprehensive study aiming to gain insights into the mechanisms underlying the OBP genomic organization. We found that the OBP clusters are embedded within large conserved arrangements. These organizations also include other non-OBP genes, which often encode proteins integral to plasma membrane. Moreover, the conservation degree of such large clusters is related to the following: 1) the promoter architecture of the confined genes, 2) a characteristic transcriptional environment, and 3) the chromatin conformation of the chromosomal region. Our results suggest that chromatin domains may restrict the location of OBP genes to regions having the appropriate transcriptional environment, leading to the OBP cluster structure. However, the appropriate transcriptional environment for OBP and the other neighbor genes is not dominated by reduced levels of expression noise. Indeed, the stochastic fluctuations in the OBP transcript abundance may have a critical role in the combinatorial nature of the olfactory coding process.

Biased gene conversion skews allele frequencies in human populations, increasing the disease burden of recessive alleles

Gene conversion results in the nonreciprocal transfer of genetic information between two recombining sequences, and there is evidence that this process is biased toward G and C alleles. However, the strength of GC-biased gene conversion (gBGC) in human populations and its effects on hereditary disease have yet to be assessed on a genomic scale. Using high-coverage whole-genome sequences of African hunter-gatherers, agricultural populations, and primate outgroups, we quantified the effects of GC-biased gene conversion on population genomic data sets. We find that genetic distances (FST and population branch statistics) are modified by gBGC. In addition, the site frequency spectrum is left-shifted when ancestral alleles are favored by gBGC and right-shifted when derived alleles are favored by gBGC. Allele frequency shifts due to gBGC mimic the effects of natural selection. As expected, these effects are strongest in high-recombination regions of the human genome. By comparing the relative rates of fixation of unbiased and biased sites, the strength of gene conversion was estimated to be on the order of Nb ≈ 0.05 to 0.09. We also find that derived alleles favored by gBGC are much more likely to be homozygous than derived alleles at unbiased SNPs (+42.2% to 62.8%). This results in a curse of the converted, whereby gBGC causes substantial increases in hereditary disease risks. Taken together, our findings reveal that GC-biased gene conversion has important population genetic and public health implications.

Population genomics of transposable elements in Drosophila

Studies of the population dynamics of transposable elements (TEs) in Drosophila melanogaster indicate that consistent forces are affecting TEs independently of their modes of transposition and regulation. New sequencing technologies enable biologists to sample genomes at an unprecedented scale in order to quantify genome-wide polymorphism for annotated and novel TE insertions. In this review, we first present new insights gleaned from high-throughput data for population genomics studies of D. melanogaster. We then consider the latest population genomics models for TE evolution and present examples of functional evidence revealed by genome-wide studies of TE population dynamics in D. melanogaster. Although most of the TE insertions are deleterious or neutral, some TE insertions increase the fitness of the individual that carries them and play a role in genome adaptation.

The effects of purifying selection on patterns of genetic differentiation between Drosophila melanogaster populations

Using the data provided by the Drosophila Population Genomics Project, we investigate factors that affect the genetic differentiation between Rwandan and French populations of D. melanogaster. By examining within-population polymorphisms, we show that sites in long introns (especially those >2000 bp) have significantly lower π (nucleotide diversity) and more low-frequency variants (as measured by Tajima's D, minor allele frequencies, and prevalence of variants that are private to one of the two populations) than short introns, suggesting a positive relationship between intron length and selective constraint. A similar analysis of protein-coding polymorphisms shows that 0-fold (degenerate) sites in more conserved genes are under stronger purifying selection than those in less conserved genes. There is limited evidence that selection on codon bias has an effect on differentiation (as measured by F_ST) at 4-fold (degenerate) sites, and 4-fold sites and sites in 8–30 bp of short introns ⩽65 bp have comparable F_ST values. Consistent with the expected effect of purifying selection, sites in long introns and 0-fold sites in conserved genes are less differentiated than those in short introns and less conserved genes, respectively. Genes in non-crossover regions (for example, the fourth chromosome) have very high F_ST values at both 0-fold and 4-fold degenerate sites, which is probably because of the large reduction in within-population diversity caused by tight linkage between many selected sites. Our analyses also reveal subtle statistical properties of F_ST, which arise when information from multiple single nucleotide polymorphisms is combined and can lead to the masking of important signals of selection.

The relations between recombination rate and patterns of molecular variation and evolution in Drosophila

Genetic recombination affects levels of variability and the efficacy of selection because natural selection acting at one site affects evolutionary processes at linked sites. The variation in local recombination rates across the Drosophila genome provides excellent material for testing hypotheses concerning the evolutionary consequences of recombination. The current state of knowledge from studies of Drosophila genomics and population genetics is reviewed here. Selection at linked sites has influenced the relations between recombination rates and patterns of molecular variation and evolution, such that higher rates of recombination are associated with both higher levels of variability and a greater efficacy of selection. It seems likely that background selection against deleterious mutations is a major factor contributing to these patterns in genome regions in which crossing over is rare or absent, whereas selective sweeps of positively selected mutations probably play an important role in regions with crossing over.

Eliminating both canonical and short-patch mismatch repair in Drosophila melanogaster suggests a new meiotic recombination model

In most meiotic systems, recombination is essential to form connections between homologs that ensure their accurate segregation from one another. Meiotic recombination is initiated by DNA double-strand breaks that are repaired using the homologous chromosome as a template. Studies of recombination in budding yeast have led to a model in which most early repair intermediates are disassembled to produce noncrossovers. Selected repair events are stabilized so they can proceed to form double-Holliday junction (dHJ) intermediates, which are subsequently resolved into crossovers. This model is supported in yeast by physical isolation of recombination intermediates, but the extent to which it pertains to animals is unknown. We sought to test this model in Drosophila melanogaster by analyzing patterns of heteroduplex DNA (hDNA) in recombination products. Previous attempts to do this have relied on knocking out the canonical mismatch repair (MMR) pathway, but in both yeast and Drosophila the resulting recombination products are complex and difficult to interpret. We show that, in Drosophila, this complexity results from a secondary, short-patch MMR pathway that requires nucleotide excision repair. Knocking out both canonical and short-patch MMR reveals hDNA patterns that reveal that many noncrossovers arise after both ends of the break have engaged with the homolog. Patterns of hDNA in crossovers could be explained by biased resolution of a dHJ; however, considering the noncrossover and crossover results together suggests a model in which a two-end engagement intermediate with unligated HJs can be disassembled by a helicase to a produce noncrossover or nicked by a nuclease to produce a crossover. While some aspects of this model are similar to the model from budding yeast, production of both noncrossovers and crossovers from a single, late intermediate is a fundamental difference that has important implications for crossover control.

During meiosis, breaks are introduced into the DNA, then repaired to give either crossovers between homologous chromosomes (these help to ensure correct segregation of these chromosomes from one another), or non-crossover products. Meiotic break repair mechanisms have been best studied in budding yeast, leading to detailed molecular models. Technical limitations have prevented directly testing these models in multi-cellular organisms. One approach that has been tried is to map segments of DNA that are mismatched, since different models predict different arrangements. Mismatches are usually repaired quickly, so analyzing these patterns requires eliminating mismatch repair processes. Although others have knocked out the primary mismatch repair system, we have now, for the first time in an animal, identified the secondary repair pathway and eliminated it and the primary pathway simultaneously. We then analyzed mismatches produced during meiosis. Though the results can be fit to the most popular current model from yeast, if some modifications are made, we also consider a simpler model that incorporates elements of the current model and of earlier models.