Regions Of Low Recombination Research Articles

A framework for gene mapping in wheat demonstrated using the Yr7 yellow rust resistance gene.

We used three approaches to map the yellow rust resistance gene Yr7 and identify associated SNPs in wheat. First, we used a traditional QTL mapping approach using a double haploid (DH) population and mapped Yr7 to a low-recombination region of chromosome 2B. To fine map the QTL, we then used an association mapping panel. Both populations were SNP array genotyped allowing alignment of QTL and genome-wide association scans based on common segregating SNPs. Analysis of the association panel spanning the QTL interval, narrowed the interval down to a single haplotype block. Finally, we used mapping-by-sequencing of resistant and susceptible DH bulks to identify a candidate gene in the interval showing high homology to a previously suggested Yr7 candidate and to populate the Yr7 interval with a higher density of polymorphisms. We highlight the power of combining mapping-by-sequencing, delivering a complete list of gene-based segregating polymorphisms in the interval with the high recombination, low LD precision of the association mapping panel. Our mapping-by-sequencing methodology is applicable to any trait and our results validate the approach in wheat, where with a near complete reference genome sequence, we are able to define a small interval containing the causative gene.

Lep-Anchor: automated construction of linkage map anchored haploid genomes.

Linkage mapping provides a practical way to anchor de novo genome assemblies into chromosomes and to detect chimeric or otherwise erroneous contigs. Such anchoring improves with higher number of markers and individuals, as long as the mapping software can handle all the information. Recent software Lep-MAP3 can robustly construct linkage maps for millions of genotyped markers and on thousands of individuals, providing optimal maps for genome anchoring. For such large datasets, automated and robust genome anchoring tool is especially valuable and can significantly reduce intensive computational and manual work involved. Here, we present a software Lep-Anchor (LA) to anchor genome assemblies automatically using dense linkage maps. As the main novelty, it takes into account the uncertainty of the linkage map positions caused by low recombination regions, cross type or poor mapping data quality. Furthermore, it can automatically detect and cut chimeric contigs, and use contig-contig, single read or alternative genome assembly alignments as additional information on contig order and orientations and to collapse haplotype contigs. We demonstrate the performance of LA using real data and show that it outperforms ALLMAPS on anchoring completeness and speed. Accuracy-wise LA and ALLMAPS are about equal, but at the expense of lower completeness of ALLMAPS. The software Chromonomer was faster than the other two methods but has major limitations and is lower in accuracy. We also show that with additional information, such as contig-contig and read alignments, the anchoring completeness can be improved by up to 70% without significant loss in accuracy. Based on simulated data, we conclude that the anchoring accuracy can be improved by utilizing information about map position uncertainty. Accuracy is the rate of contigs in correct orientation and completeness is the number contigs with inferred orientation. Lep-Anchor is available with the source code under GNU general public license from http://sourceforge.net/projects/lep-anchor. All the scripts and code used to produce the reported results are included with Lep-Anchor.

Genetic Variation: Harmful Recessive Mutations Have Unexpected Effects on Variation

New data are causing the standard model for the effect of selection on linked neutral variation in low recombination regions, combining the effects of background selection and selective sweeps, to be refined to include harmful recessive mutations creating associative overdominance.

Transition from Background Selection to Associative Overdominance Promotes Diversity in Regions of Low Recombination

Linked selection is a major driver of genetic diversity. Selection against deleterious mutations removes linked neutral diversity (background selection [BGS]) [1], creating a positive correlation between recombination rates and genetic diversity. Purifying selection against recessive variants, however, can also lead to associative overdominance (AOD) [2, 3], due to an apparent heterozygote advantage at linked neutral loci that opposes the loss ofneutral diversity by BGS. Zhao and Charlesworth [3] identified the conditions under which AOD should dominate over BGS in a single-locus model and suggested that the effect of AOD could become stronger if multiple linked deleterious variants co-segregate. We present a model describing how and under which conditions multi-locus dynamics can amplify the effects of AOD. We derive the conditions for a transition from BGS to AOD due to pseudo-overdominance [4], i.e., a form of balancing selection that maintains complementary deleterious haplotypes that mask the effect of recessive deleterious mutations. Simulations confirm these findings and show that multi-locus AOD can increase diversity in low-recombination regions much more strongly than previously appreciated. While BGS is known to drive genome-wide diversity in humans [5], the observation of a resurgence of genetic diversity in regions of very low recombination is indicative of AOD. We identify 22 such regions in the human genome consistent with multi-locus AOD. Our results demonstrate that AOD may play an important role in the evolution of low-recombination regions of many species.

The Fate of Deleterious Variants in a Barley Genomic Prediction Population.

Targeted identification and purging of deleterious genetic variants has been proposed as a novel approach to animal and plant breeding. This strategy is motivated, in part, by the observation that demographic events and strong selection associated with cultivated species pose a "cost of domestication." This includes an increase in the proportion of genetic variants that are likely to reduce fitness. Recent advances in DNA resequencing and sequence constraint-based approaches to predict the functional impact of a mutation permit the identification of putatively deleterious SNPs (dSNPs) on a genome-wide scale. Using exome capture resequencing of 21 barley lines, we identified 3855 dSNPs among 497,754 total SNPs. We generated whole-genome resequencing data of Hordeum murinum ssp. glaucum as a phylogenetic outgroup to polarize SNPs as ancestral vs. derived. We also observed a higher proportion of dSNPs per synonymous SNPs (sSNPs) in low-recombination regions of the genome. Using 5215 progeny from a genomic prediction experiment, we examined the fate of dSNPs over three breeding cycles. Adjusting for initial frequency, derived alleles at dSNPs reduced in frequency or were lost more often than other classes of SNPs. The highest-yielding lines in the experiment, as chosen by standard genomic prediction approaches, carried fewer homozygous dSNPs than randomly sampled lines from the same progeny cycle. In the final cycle of the experiment, progeny selected by genomic prediction had a mean of 5.6% fewer homozygous dSNPs relative to randomly chosen progeny from the same cycle.

Environmental Genome-Wide Association Reveals Climate Adaptation Is Shaped by Subtle to Moderate Allele Frequency Shifts in Loblolly Pine.

Understanding the genomic basis of local adaptation is crucial to determine the potential of long-lived woody species to withstand changes in their natural environment. In the past, efforts to dissect the genomic architecture in gymnosperms species have been limited due to the absence of reference genomes. Recently, the genomes of some commercially important conifers, such as loblolly pine, have become available, allowing whole-genome studies of these species. In this study, we test for associations between 87k SNPs, obtained from whole-genome resequencing of loblolly pine individuals, and 270 environmental variables and combinations of them. We determine the geographic location of significant loci and identify their genomic location using our newly constructed ultradense 26k SNP linkage map. We found that water availability is the main climatic variable shaping local adaptation of the species, and found 821 SNPs showing significant associations with climatic variables or combinations of them based on the consistent results of three different genotype–environment association methods. Our results suggest that adaptation to climate in the species might have occurred by many changes in the frequency of alleles with moderate to small effect sizes, and by the smaller contribution of large effect alleles in genes related to moisture deficit, temperature and precipitation. Genomic regions of low recombination and high population differentiation harbored SNPs associated with groups of environmental variables, suggesting climate adaptation might have evolved as a result of different selection pressures acting on groups of genes associated with an aspect of climate rather than on individual environmental variables.

Recombination between homoeologous chromosomes induced in durum wheat by the Aegilops speltoides Su1-Ph1 suppressor

Su1-Ph1, which we previously introgressed into wheat from Aegilops speltoides, is a potent suppressor of Ph1 and a valuable tool for gene introgression in tetraploid wheat. We previously introgressed Su1-Ph1, a suppressor of the wheat Ph1 gene, from Aegilops speltoides into durum wheat cv Langdon (LDN). Here, we evaluated the utility of the introgressed suppressor for inducing introgression of alien germplasm into durum wheat. We built LDN plants heterozygous for Su1-Ph1 that simultaneously contained a single LDN chromosome 5B and a single Ae. searsii chromosome 5Sse, which targeted them for recombination. We genotyped 28 BC1F1 and 84 F2 progeny with the wheat 90-K Illumina single-nucleotide polymorphism assay and detected extensive recombination between the two chromosomes, which we confirmed by non-denaturing fluorescence in situ hybridization (ND-FISH). We constructed BC1F1 and F2 genetic maps that were 65.31 and 63.71cM long, respectively. Recombination rates between the 5B and 5Sse chromosomes were double the expected rate computed from their meiotic pairing, which we attributed to selection against aneuploid gametes. Recombination rate between 5B and 5Sse was depressed compared to that between 5B chromosomes in the proximal region of the long arm. We integrated ND-FISH signals into the genetic map and constructed a physical map, which we used to map a 172,188,453-bp Ph1 region. Despite the location of the region in a low-recombination region of the 5B chromosome, we detected three crossovers in it. Our data show that Su1-Ph1 is a valuable tool for gene introgression and gene mapping based on recombination between homoeologous chromosomes in wheat.

Recombination-Aware Phylogenomics Reveals the Structured Genomic Landscape of Hybridizing Cat Species.

Current phylogenomic approaches implicitly assume that the predominant phylogenetic signal within a genome reflects the true evolutionary history of organisms, without assessing the confounding effects of postspeciation gene flow that can produce a mosaic of phylogenetic signals that interact with recombinational variation. Here, we tested the validity of this assumption with a phylogenomic analysis of 27 species of the cat family, assessing local effects of recombination rate on species tree inference and divergence time estimation across their genomes. We found that the prevailing phylogenetic signal within the autosomes is not always representative of the most probable speciation history, due to ancient hybridization throughout felid evolution. Instead, phylogenetic signal was concentrated within regions of low recombination, and notably enriched within large X chromosome recombination cold spots that exhibited recurrent patterns of strong genetic differentiation and selective sweeps across mammalian orders. By contrast, regions of high recombination were enriched for signatures of ancient gene flow, and these sequences inflated crown-lineage divergence times by ∼40%. We conclude that existing phylogenomic approaches to infer the Tree of Life may be highly misleading without considering the genomic architecture of phylogenetic signal relative to recombination rate and its interplay with historical hybridization.

The Effect of Neutral Recombination Variation on Genome Scans for Selection.

Recently, there has been an increasing interest in identifying the role that regions of low recombination or inversion play in adaptation of species to local environments. Many examples of groups of adapted genes located within inversions are arising in the literature, in part inspired by theory that predicts the evolution of these so-called “supergenes.” We still, however, have a poor understanding of how genomic heterogeneity, such as varying rates of recombination, may confound signals of selection. Here, I evaluate the effect of neutral inversions and recombination variation on genome scans for selection, including tests for selective sweeps, differentiation outlier tests, and association tests. There is considerable variation among methods in their performance, with some methods being unaffected and some showing elevated false positive signals within a neutral inversion or region of low recombination. In some cases the false positive signal can be dampened or removed, if it is possible to use a quasi-independent set of SNPs to parameterize the model before performing the test. These results will be helpful to those seeking to understand the importance of regions of low recombination in adaptation.

Overcoming Self-Incompatibility in Diploid Potato Using CRISPR-Cas9.

Potato breeding can be redirected to a diploid inbred/F1 hybrid variety breeding strategy if self-compatibility can be introduced into diploid germplasm. However, the majority of diploid potato clones (Solanum spp.) possess gametophytic self-incompatibility that is primarily controlled by a single multiallelic locus called the S-locus which is composed of tightly linked genes, S-RNase (S-locus RNase) and multiple SLFs (S-locus F-box proteins), which are expressed in the style and pollen, respectively. Using S-RNase genes known to function in the Solanaceae gametophytic SI mechanism, we identified S-RNase alleles with flower-specific expression in two diploid self-incompatible potato lines using genome resequencing data. Consistent with the location of the S-locus in potato, we genetically mapped the S-RNase gene using a segregating population to a region of low recombination within the pericentromere of chromosome 1. To generate self-compatible diploid potato lines, a dual single-guide RNA (sgRNA) strategy was used to target conserved exonic regions of the S-RNase gene and generate targeted knockouts (KOs) using a Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein 9 (Cas9) approach. Self-compatibility was achieved in nine S-RNase KO T0 lines which contained bi-allelic and homozygous deletions/insertions in both genotypes, transmitting self compatibility to T1 progeny. This study demonstrates an efficient approach to achieve stable, consistent self-compatibility through S-RNase KO for use in diploid potato breeding approaches.

Long contiguous stretches of homozygosity detected by chromosomal microarrays (CMA) in patients with neurodevelopmental disorders in the South of Brazil

BackgroundCurrently, chromosomal microarrays (CMA) are recommended as first-tier test in the investigation of developmental disorders to examine copy number variations. The modern platforms also include probes for single nucleotide polymorphisms (SNPs) that detect homozygous regions in the genome, such as long contiguous stretches of homozygosity (LCSH) also named runs of homozygosity (ROH). LCHS are chromosomal segments resulting from complete or segmental chromosomal homozygosity, which may be indicative of uniparental disomy (UPD), consanguinity, as well as replicative DNA repair events, however also are common findings in normal populations. Knowing common LCSH of a population, which probably represent ancestral haplotypes of low-recombination regions in the genome, facilitates the interpretation of LCSH found in patients, allowing to prioritize those with possible clinical significance. However, population records of ancestral haplotype derived LCSH by SNP arrays are still scarce, particularly for countries such as Brazil where even for the clinic, microarrays that include SNPs are difficult to request due to their high cost.MethodsIn this study, we evaluate the frequencies and implications of LCSH detected by Affymetrix CytoScan® HD or 750 K platforms in 430 patients with neurodevelopmental disorders in southern Brazil. LCSH were analyzed in the context of pathogenic significance and also explored to identify ancestral haplotype derived LCSH. The criteria for considering a region as LCSH was homozygosis ≥3 Mbp on an autosome.ResultsIn 95% of the patients, at least one LCSH was detected, a total of 1478 LCSH in 407 patients. In 2.6%, the findings were suggestive of UPD. For about 8.5% LCSH suggest offspring from first to fifth grade, more likely to have a clinical impact. Considering recurrent LCSH found at a frequency of 5% or more, we outline 11 regions as potentially representing ancestral haplotypes in our population. The region most involved with homozygosity was 16p11.2p11.1 (49%), followed by 1q21.2q21.3 (21%), 11p11.2p11.12 (19%), 3p21.31p21.2 (16%), 15q15 1q33p32.3 (12%), 2q11.1q12.1 (9%), 1p33p32.3 (6%), 20q11.21q11.23 (6%), 10q22.1q23.31 (5%), 6p22.2p22 (5%), and 7q11.22q11.23 (5%).ConclusionsIn this work, we show the importance and usefulness of interpreting LCSH in the results of CMA wich incorporate SNPs.

A Single Interacting Species Leads to Widespread Parallel Evolution of the Stickleback Genome

Biotic interactions are potent, widespread causes of natural selection and divergent phenotypic evolution and can lead to genetic differentiation with gene flow among wild populations ("isolation by ecology") [1-4]. Biotic selection has been predicted to act onmore genes than abiotic selection thereby drivinggreater adaptation [5]. However, difficulties in isolating the genome-wide effect of single biotic agents of selection have limited our ability to identify and quantify the number and type of genetic regions responding to biotic selection [6-9]. We identified geographically interspersed lakes in which threespine stickleback fish (Gasterosteus aculeatus) have repeatedly adapted to the presence or absence of a single member of the ecological community, prickly sculpin (Cottus asper), a fish that is both a competitor and a predator of the stickleback [10]. Whole-genome sequencing revealed that sculpin presence or absence accounted for the majority of genetic divergence among stickleback populations, more so than geography. The major axis of genomic variation within and between the two lake types was correlated with multiple traits, indicating parallel natural selection across a gradient of biotic environments. A large proportion of the genome-about 1.8%, encompassing more than 600 genes-differentiated stickleback from the two biotic environments. Divergence occurred in 141 discrete genomic clumps located mainly in regions of low recombination, suggesting that genes brought to lakes by the colonizing ancestral population often evolved together in linked blocks. Strong selection and a wealth of standing genetic variation explain how a single member of the biotic community can have such a rapid and profound evolutionary impact.

Evaluating Natural Selection In Schizophrenia Using Data From Genome-Wide Association Studies

Schizophrenia is a debilitating psychiatric condition that manifests itself in the early adult life and is often associated with poor quality of life and decreased life expectancy. It is both highly heritable and polygenic, with risk variants spanning the full spectrum of population frequencies. There has been a long-standing debate, from an evolutionary perspective, as to how risk alleles persist in the human gene pool, particularly given the decreased fecundity associated with schizophrenia. It has been repeatedly show that rare risk alleles of strong effect persist due to mutation-selection balance, a mechanism which implies that they are removed from the population by natural selection at the same rate that they appear by mutation. However, an explanation for the persistence of common risk alleles of small effect has not been explicitly given, though this is often attributed to various evolutionary scenarios. One of the most popular hypotheses links this persistence to positive selection, arguing that current common risk alleles for schizophrenia might have been beneficial at some point during human evolution, and these benefits resulted in the allele frequencies we observe today.While detecting selection signals in genomic data has been traditionally challenging, recent advances in the statistical and population genetics communities have made possible to systematically test for the presence of selected alleles in GWAS summary statistics. To demonstrate the possibilities of such a procedure, this work uses a large-scale meta-analysis of schizophrenia GWAS data (40,675 cases and 64,643 controls) to test four different metrics of positive selection, each tailored to a particular timeframe of human evolution. The LD-Score framework shows that none of these metrics are significantly associated with common genetic variation, raising doubts into the validity of positive selection as a driver for the persistence of schizophrenia risk alleles. Furthermore, strong association is shown for a metric of negative selection, background selection (h2 enrichment = 1.801; p=0.001), which recurrently affects regions of low recombination and reduces genetic diversity. An examination of the mechanism of action of background selection, coupled with a simulation analysis, allows us to establish that regions with reduced genetic diversity are more likely to harbour common risk alleles in schizophrenia, and that this is compatible with our current knowledge about the epidemiology of the disorder. This also suggests a genetic model for the action of natural selection in schizophrenia, which relates our findings to the nearly-neutral theory of molecular evolution (Ohta 1973) and could be extended to other psychiatric complex traits.

Empirical Comparisons of Different Statistical Models To Identify and Validate Kernel Row Number-Associated Variants from Structured Multi-parent Mapping Populations of Maize.

Advances in next generation sequencing technologies and statistical approaches enable genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS). Although multiple statistical approaches for conducting GWAS are available, the power and cross-validation rates of many approaches have been mostly tested using simulated data. Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have not been conducted to test if a single approach or a combination of SV and MV is effective, through identification and cross-validation of trait-associated loci. In this study, kernel row number (KRN) data were collected from a set of 6,230 entries derived from the Nested Association Mapping (NAM) population and related populations. Three different types of GWAS analyses were performed: 1) single-variant (SV), 2) stepwise regression (STR) and 3) a Bayesian-based multi-variant (BMV) model. Using SV, STR, and BMV models, 257, 300, and 442 KRN-associated variants (KAVs) were identified in the initial GWAS analyses. Of these, 231 KAVs were subjected to genetic validation using three unrelated populations that were not included in the initial GWAS. Genetic validation results suggest that the three GWAS approaches are complementary. Interestingly, KAVs in low recombination regions were more likely to exhibit associations in independent populations than KAVs in recombinationally active regions, probably as a consequence of linkage disequilibrium. The KAVs identified in this study have the potential to enhance our understanding of the genetic basis of ear development.

Analysis of Genome-Wide Differentiation between Native and Introduced Populations of the Cupped Oysters Crassostrea gigas and Crassostrea angulata.

The Pacific cupped oyster is genetically subdivided into two sister taxa, Crassostrea gigas and Crassostrea angulata, which are in contact in the north-western Pacific. The nature and origin of their genetic and taxonomic differentiation remains controversial due the lack of known reproductive barriers and the high degree of morphologic similarity. In particular, whether the presence of ecological and/or intrinsic isolating mechanisms contributes to species divergence is unknown. The recent co-introduction of both taxa into Europe offers a unique opportunity to test how genetic differentiation is maintained under new environmental and demographic conditions. We generated a pseudochromosome assembly of the Pacific oyster genome using a combination of BAC-end sequencing and scaffold anchoring to a new high-density linkage map. We characterized genome-wide differentiation between C. angulata and C. gigas in both their native and introduced ranges, and showed that gene flow between species has been facilitated by their recent co-introductions in Europe. Nevertheless, patterns of genomic divergence between species remain highly similar in Asia and Europe, suggesting that the environmental transition caused by the co-introduction of the two species did not affect the genomic architecture of their partial reproductive isolation. Increased genetic differentiation was preferentially found in regions of low recombination. Using historical demographic inference, we show that the heterogeneity of differentiation across the genome is well explained by a scenario whereby recent gene flow has eroded past differentiation at different rates across the genome after a period of geographical isolation. Our results thus support the view that low-recombining regions help in maintaining intrinsic genetic differences between the two species.

The Genomic Architecture of a Rapid Island Radiation: Recombination Rate Variation, Chromosome Structure, and Genome Assembly of the Hawaiian Cricket Laupala.

Phenotypic evolution and speciation depend on recombination in many ways. Within populations, recombination can promote adaptation by bringing together favorable mutations and decoupling beneficial and deleterious alleles. As populations diverge, crossing over can give rise to maladapted recombinants and impede or reverse diversification. Suppressed recombination due to genomic rearrangements, modifier alleles, and intrinsic chromosomal properties may offer a shield against maladaptive gene flow eroding coadapted gene complexes. Both theoretical and empirical results support this relationship. However, little is known about this relationship in the context of behavioral isolation, where coevolving signals and preferences are the major hybridization barrier. Here we examine the genomic architecture of recently diverged, sexually isolated Hawaiian swordtail crickets (Laupala). We assemble a de novo genome and generate three dense linkage maps from interspecies crosses. In line with expectations based on the species' recent divergence and successful interbreeding in the laboratory, the linkage maps are highly collinear and show no evidence for large-scale chromosomal rearrangements. Next, the maps were used to anchor the assembly to pseudomolecules and estimate recombination rates across the genome to test the hypothesis that loci involved in behavioral isolation (song and preference divergence) are in regions of low interspecific recombination. Contrary to our expectations, the genomic region where a male song and female preference QTL colocalize is not associated with particularly low recombination rates. This study provides important novel genomic resources for an emerging evolutionary genetics model system and suggests that trait-preference coevolution is not necessarily facilitated by locally suppressed recombination.

A survey of functional genomic variation in domesticated chickens

BackgroundDeleterious genetic variation can increase in frequency as a result of mutations, genetic drift, and genetic hitchhiking. Although individual effects are often small, the cumulative effect of deleterious genetic variation can impact population fitness substantially. In this study, we examined the genome of commercial purebred chicken lines for deleterious and functional variations, combining genotype and whole-genome sequence data.ResultsWe analysed over 22,000 animals that were genotyped on a 60 K SNP chip from four purebred lines (two white egg and two brown egg layer lines) and two crossbred lines. We identified 79 haplotypes that showed a significant deficit in homozygous carriers. This deficit was assumed to stem from haplotypes that potentially harbour lethal recessive variations. To identify potentially deleterious mutations, a catalogue of over 10 million variants was derived from 250 whole-genome sequenced animals from three purebred white-egg layer lines. Out of 4219 putative deleterious variants, 152 mutations were identified that likely induce embryonic lethality in the homozygous state. Inferred deleterious variation showed evidence of purifying selection and deleterious alleles were generally overrepresented in regions of low recombination. Finally, we found evidence that mutations, which were inferred to be evolutionally intolerant, likely have positive effects in commercial chicken populations.ConclusionsWe present a comprehensive genomic perspective on deleterious and functional genetic variation in egg layer breeding lines, which are under intensive selection and characterized by a small effective population size. We show that deleterious variation is subject to purifying selection and that there is a positive relationship between recombination rate and purging efficiency. In addition, multiple putative functional coding variants were discovered in selective sweep regions, which are likely under positive selection. Together, this study provides a unique molecular perspective on functional and deleterious variation in commercial egg-laying chickens, which can enhance current genomic breeding practices to lower the frequency of undesirable variants in the population.

Genomic islands of differentiation in two songbird species reveal candidate genes for hybrid female sterility.

Hybrid sterility is a common first step in the evolution of postzygotic reproductive isolation. According to Haldane's Rule, it affects predominantly the heterogametic sex. While the genetic basis of hybrid male sterility in organisms with heterogametic males has been studied for decades, the genetic basis of hybrid female sterility in organisms with heterogametic females has received much less attention. We investigated the genetic basis of reproductive isolation in two closely related avian species, the common nightingale (Luscinia megarhynchos) and the thrush nightingale (L.luscinia), that hybridize in a secondary contact zone and produce viable hybrid progeny. In accordance with Haldane's Rule, hybrid females are sterile, while hybrid males are fertile, allowing gene flow to occur between the species. Using transcriptomic data from multiple individuals of both nightingale species, we identified genomic islands of high differentiation (FST ) and of high divergence (Dxy ), and we analysed gene content and patterns of molecular evolution within these islands. Interestingly, we found that these islands were enriched for genes related to female meiosis and metabolism. The islands of high differentiation and divergence were also characterized by higher levels of linkage disequilibrium than the rest of the genome in both species indicating that they might be situated in genomic regions of low recombination. This study provides one of the first insights into genetic basis of hybrid female sterility in organisms with heterogametic females.

Ancient polymorphisms and divergence hitchhiking contribute to genomic islands of divergence within a poplar species complex

How genome divergence eventually leads to speciation is a topic of prime evolutionary interest. Genomic islands of elevated divergence are frequently reported between diverging lineages, and their size is expected to increase with time and gene flow under the speciation-with-gene-flow model. However, such islands can also result from divergent sorting of ancient polymorphisms, recent ecological selection regardless of gene flow, and/or recurrent background selection and selective sweeps in low-recombination regions. It is challenging to disentangle these nonexclusive alternatives, but here we attempt to do this in an analysis of what drove genomic divergence between four lineages comprising a species complex of desert poplar trees. Within this complex we found that two morphologically delimited species, Populus euphratica and Populus pruinosa, were paraphyletic while the four lineages exhibited contrasting levels of gene flow and divergence times, providing a good system for testing hypotheses on the origin of divergence islands. We show that the size and number of genomic islands that distinguish lineages are not associated with either rate of recent gene flow or time of divergence. Instead, they are most likely derived from divergent sorting of ancient polymorphisms and divergence hitchhiking. We found that highly diverged genes under lineage-specific selection and putatively involved in ecological and morphological divergence occur both within and outside these islands. Our results highlight the need to incorporate demography, absolute divergence measurement, and gene flow rate to explain the formation of genomic islands and to identify potential genomic regions involved in speciation.

Genome-wide recombination rate variation in a recombination map of cotton.

Recombination is crucial for genetic evolution, which not only provides new allele combinations but also influences the biological evolution and efficacy of natural selection. However, recombination variation is not well understood outside of the complex species’ genomes, and it is particularly unclear in Gossypium. Cotton is the most important natural fibre crop and the second largest oil-seed crop. Here, we found that the genetic and physical maps distances did not have a simple linear relationship. Recombination rates were unevenly distributed throughout the cotton genome, which showed marked changes along the chromosome lengths and recombination was completely suppressed in the centromeric regions. Recombination rates significantly varied between A-subgenome (At) (range = 1.60 to 3.26 centimorgan/megabase [cM/Mb]) and D-subgenome (Dt) (range = 2.17 to 4.97 cM/Mb), which explained why the genetic maps of At and Dt are similar but the physical map of Dt is only half that of At. The translocation regions between A02 and A03 and between A04 and A05, and the inversion regions on A10, D10, A07 and D07 indicated relatively high recombination rates in the distal regions of the chromosomes. Recombination rates were positively correlated with the densities of genes, markers and the distance from the centromere, and negatively correlated with transposable elements (TEs). The gene ontology (GO) categories showed that genes in high recombination regions may tend to response to environmental stimuli, and genes in low recombination regions are related to mitosis and meiosis, which suggested that they may provide the primary driving force in adaptive evolution and assure the stability of basic cell cycle in a rapidly changing environment. Global knowledge of recombination rates will facilitate genetics and breeding in cotton.