From molecules to populations: appreciating and estimating recombination rate variation

The Density of Recombination-Associated Genomic Features Does Not Generally Explain the Broad-Scale Crossover Patterns in Chicken and Guinea Fowl

Meiotic recombination is essential for chromosomal segregation and facilitates the exchange between homologs, which leads to the transmission of new combinations of linked alleles to the progeny. The eukaryotic meiotic machinery is generally highly conserved, but the frequency of crossover occurrence can vary dramatically across species and populations, between individuals, and across sexes. The chicken and the guinea fowl exhibit interspecific variation in the distribution of crossovers along their largest chromosomes. In many organisms, an association has been observed between the preferred crossover location and certain sequence parameters, such as high GC content, CpG islands, or gene promoters. Here, we compared the distribution of these genomic parameters with the recombination landscape, represented by MLH1 focus frequencies, in the two birds. We found an association between GC content density and recombination in the chicken, but the remaining parameters showed weak or no association with recombination, especially in the guinea fowl. We conclude that despite the different broad-scale crossover distribution, the investigated genomic parameters remained remarkably similar in these two species. We suggest that the density of these genomic features is more likely related to microscale variations in recombination rates, such as those determined by open chromatin configurations.

A Pedigree-Based Map of Crossovers and Noncrossovers in Aye-Ayes (Daubentonia madagascariensis)

Gaining a better understanding of the rates and patterns of meiotic recombination is crucial for improving evolutionary genomic modeling, with applications ranging from demographic to selective inference. Although previous research has provided important insights into the landscape of crossovers in humans and other haplorrhines, our understanding of both the considerably more common outcome of recombination (i.e. noncrossovers) as well as the landscapes in more distantly related primates (i.e. strepsirrhines) remains limited owing to difficulties associated with both the identification of noncrossover tracts as well as species sampling. Thus, in order to elucidate recombination patterns in this understudied branch of the primate clade, we here characterize crossover and noncrossover landscapes in aye-ayes utilizing whole-genome sequencing data from six three-generation pedigrees and three two-generation multi-sibling families, and in so doing provide novel insights into this important evolutionary process shaping genomic diversity in one of the world's most critically endangered primate species.

Population genomics advances in frontier ethnic minorities in China

China, with its large geographic span, possesses rich genetic diversity across vast frontier regions in addition to the Han Chinese majority. Importantly, demographic events and various natural and cultural environments in Chinese frontier regions have shaped the genomic diversity of ethnic minorities via local adaptations. Thus, insights into the genetic diversity and adaptive evolution of these under-represented ethnic groups are crucial for understanding evolutionary scenarios and biomedical implications in East Asian populations. Here, we focus on ethnic minorities in Chinese frontier regions and review research advances regarding genomic diversity, genetic structure, population history, genetic admixture, and local adaptation. We first provide an overview of the extensive genetic diversity across populations in different Chinese frontier regions. Next, we summarize research progress regarding genetic ancestry, demographic history, the adaptive process, and the archaic identification of multiple ethnic minorities in different Chinese frontier regions. Finally, we discuss the gaps and opportunities in genomic studies of Chinese populations and the need for a more comprehensive understanding of genomic diversity and the evolution of populations of East Asian ancestry in the post-genomic era.

Incorporating genetic load contributes to predicting Arabidopsis thaliana's response to climate change

Understanding how species respond to climate change can facilitate species conservation and crop breeding. Current prediction frameworks about population vulnerability focused on predicting range shifts or local adaptation but ignored genetic load, which is also crucial for adaptation. By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species' range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. Overall, here we deciphered the driving forces of genetic load in A. thaliana, and incorporated SDM, local adaptation and genetic load to predict the fate of populations under future climate change.

Hi-reComb: constructing recombination maps from bulk gamete Hi-C sequencing

Recombination is central to genetics and to evolution of sexually reproducing organisms. However, obtaining accurate estimates of recombination rates, and of how they vary along chromosomes, continues to be challenging. To advance our ability to estimate recombination rates, we present Hi-reComb, a new method and software for estimation of recombination maps from bulk gamete chromosome conformation capture sequencing (Hi-C). Simulations show that Hi-reComb produces robust, accurate recombination landscapes. With empirical data from sperm of five fish species we show the advantages of this approach, including joint assessment of recombination maps and large structural variants, map comparisons using bootstrap, and workflows with trio phasing vs. Hi-C phasing. With off-the-shelf library construction and a straightforward rapid workflow, our approach will facilitate routine recombination landscape estimation for a broad range of studies and model organisms in genetics and evolutionary biology. Hi-reComb is open-source and freely available at https://github.com/millanek/Hi-reComb.

Rapid evolution of recombination landscapes during the divergence of cichlid ecotypes in Lake Masoko

Variation of recombination rate along the genome is of crucial importance to rapid adaptation and organismal diversification. Many unknowns remain regarding how and why recombination landscapes evolve in nature. Here, we reconstruct recombination maps based on linkage disequilibrium and use subsampling and simulations to derive a new measure of recombination landscape evolution: the Population Recombination Divergence Index (PRDI). Using PRDI, we show that fine-scale recombination landscapes differ substantially between two cichlid fish ecotypes of Astatotilapia calliptera that diverged only ~2,500 generations ago. Perhaps surprisingly, recombination landscape differences are not driven by divergence in terms of allele frequency (FST) and nucleotide diversity (Δ(π)): although there is some association, we observe positive PRDI in regions where FST and Δ(π) are zero. We found a stronger association between the evolution of recombination and 47 large haplotype blocks that are polymorphic in Lake Masoko, cover 21% of the genome, and appear to include multiple inversions. Among haplotype blocks, there is a strong and clear association between the degree of recombination divergence and differences between ecotypes in heterozygosity, consistent with recombination suppression in heterozygotes. Overall, our work provides a holistic view of changes in population recombination landscapes during the early stages of speciation with gene flow.

Controlling noise with self-organized resetting

Biological systems often consist of a small number of constituents and are therefore inherently noisy. To function effectively, these systems must employ mechanisms to constrain the accumulation of noise. Such mechanisms have been extensively studied and comprise the constraint by external forces, nonlinear interactions, or the resetting of the system to a predefined state. Here, we propose a fourth paradigm for noise constraint: self-organized resetting, where the resetting rate and position emerge from self-organization through time-discrete interactions. We study general properties of self-organized resetting systems using the paradigmatic example of cooperative resetting, where random pairs of Brownian particles are reset to their respective average. We demonstrate that such systems undergo a delocalization phase transition, separating regimes of constrained and unconstrained noise accumulation. Additionally, we show that systems with self-organized resetting can adapt to external forces and optimize search behavior for reaching target values. Self-organized resetting has various applications in nature and technology, which we demonstrate in the context of sexual interactions in fungi and spatial dispersion in shared mobility services. This work opens routes into the application of self-organized resetting across various systems in biology and technology.

Maintenance of long-term transposable element activity through regulation by nonautonomous elements

Transposable elements are DNA sequences that can move and replicate within genomes. Broadly, there are 2 types: autonomous elements, which encode the necessary enzymes for transposition, and nonautonomous elements, which rely on the enzymes produced by autonomous elements for their transposition. Nonautonomous elements have been proposed to regulate the numbers of transposable elements, which is a possible explanation for the persistence of transposition activity over long evolutionary times. However, previous modeling studies indicate that interactions between autonomous and nonautonomous elements usually result in the extinction of one type. Here, we study a stochastic model that allows for the stable coexistence of autonomous and nonautonomous retrotransposons. We determine the conditions for this coexistence and derive an analytical expression for the stationary distribution of their copy numbers, showing that nonautonomous elements regulate stochastic fluctuations and the number of autonomous elements in stationarity. We find that the stationary variances of each element can be expressed as a function of the average copy numbers and their covariance, enabling data comparison and model validation. These results suggest that continued transposition activity of transposable elements, regulated by nonautonomous elements, is a possible evolutionary outcome that could for example explain the long coevolutionary history of autonomous LINE1 and nonautonomous Alu element transposition in the human ancestry.

Inferring fine-scale mutation and recombination rate maps in aye-ayes ( Daubentonia madagascariensis )

The rate of input of new genetic mutations, and the rate at which that variation is reshuffled, are key evolutionary processes shaping genomic diversity. Importantly, these rates vary not just across populations and species, but also across individual genomes. Despite previous studies having demonstrated that failing to account for rate heterogeneity across the genome can bias the inference of both selective and neutral population genetic processes, mutation and recombination rate maps have to date only been generated for a relatively small number of organisms. Here, we infer such fine-scale maps for the aye-aye ( Daubentonia madagascariensis ) - a highly endangered strepsirrhine that represents one of the earliest splits in the primate clade, and thus stands as an important outgroup to the more commonly-studied haplorrhines - utilizing a recently released fully-annotated genome combined with high-quality population sequencing data. We compare our indirectly inferred rates to previous pedigree-based estimates, finding further evidence of relatively low mutation and recombination rates in aye-ayes compared to other primates.

Digital Image Processing to Detect Adaptive Evolution

In recent years, advances in image processing and machine learning have fueled a paradigm shift in detecting genomic regions under natural selection. Early machine learning techniques employed population-genetic summary statistics as features, which focus on specific genomic patterns expected by adaptive and neutral processes. Though such engineered features are important when training data are limited, the ease at which simulated data can now be generated has led to the recent development of approaches that take in image representations of haplotype alignments and automatically extract important features using convolutional neural networks. Digital image processing methods termed α-molecules are a class of techniques for multiscale representation of objects that can extract a diverse set of features from images. One such α-molecule method, termed wavelet decomposition, lends greater control over high-frequency components of images. Another α-molecule method, termed curvelet decomposition, is an extension of the wavelet concept that considers events occurring along curves within images. We show that application of these α-molecule techniques to extract features from image representations of haplotype alignments yield high true positive rate and accuracy to detect hard and soft selective sweep signatures from genomic data with both linear and nonlinear machine learning classifiers. Moreover, we find that such models are easy to visualize and interpret, with performance rivaling those of contemporary deep learning approaches for detecting sweeps.

A pedigree-based map of crossovers and non-crossovers in aye-ayes (Daubentonia madagascariensis)

Gaining a better understanding of rates and patterns of meiotic recombination is crucial for improving evolutionary genomic modelling, with applications ranging from demographic to selective inference. Although previous research has provided important insights into the landscape of crossovers in humans and other haplorrhines, our understanding of both the considerably more common outcome of recombination (i.e., non-crossovers) as well as the landscapes in more distantly-related primates (i.e., strepsirrhines) remains limited owing to difficulties associated with both the identification of non-crossover tracts as well as species sampling. Thus, in order to elucidate recombination patterns in this under-studied branch of the primate clade, we here characterize crossover and non-crossover landscapes in aye-ayes utilizing whole-genome sequencing data from six three-generation pedigrees as well as three two-generation multi-sibling families, and in so doing provide novel insights into this important evolutionary process shaping genomic diversity in one of the world's most critically endangered primate species.

Refinement of the Antarctic fur seal (Arctocephalus gazella) reference genome increases continuity and completeness

The Antarctic fur seal (Arctocephalus gazella) is an important top predator and indicator of the health of the Southern Ocean ecosystem. Although abundant, this species narrowly escaped extinction due to historical sealing and is currently declining as a consequence of climate change. Genomic tools are essential for understanding these anthropogenic impacts and for predicting long-term viability. However, the current reference genome ("arcGaz3") shows considerable room for improvement in terms of both completeness and contiguity. We therefore combined PacBio sequencing, haplotype-aware HiRise assembly, and scaffolding based on Hi-C information to generate a refined assembly of the Antarctic fur seal reference genome ("arcGaz4_h1"). The new assembly is 2.53 Gb long, has a scaffold N50 of 55.6 Mb and includes 18 chromosome-sized scaffolds, which correspond to the 18 chromosomes expected in otariids. Genome completeness is greatly improved, with 23,408 annotated genes and a Benchmarking Universal Single-Copy Orthologs score raised from 84.7% to 95.2%. We furthermore included the new genome in a reference-free alignment of the genomes of 11 pinniped species to characterize evolutionary conservation across the Pinnipedia using genome-wide Genomic Evolutionary Rate Profiling. We then implemented Gene Ontology enrichment analyses to identify biological processes associated with those genes showing the highest levels of either conservation or differentiation between the 2 major pinniped families, the Otariidae and Phocidae. We show that processes linked to neuronal development, the circulatory system, and osmoregulation are overrepresented both in conserved as well as in differentiated regions of the genome.

A high-density linkage map reveals broad- and fine-scale sex differences in recombination in the hihi (stitchbird; Notiomystis cincta)

Recombination, the process of DNA exchange between homologous chromosomes during meiosis, plays a major role in genomic diversity and evolutionary change. Variation in recombination rate is widespread despite recombination often being essential for progression of meiosis. One such variation is heterochiasmy, where recombination rates differ between sexes. Heterochiasmy has been observed across broad taxonomic groups, yet it remains an evolutionary enigma. We used Lep-MAP3, a pedigree-based software that is efficient in handling large datasets, to generate linkage maps for the hihi or stitchbird (Notiomystis cincta), utilising information from >36 K SNPs and 36 families. We constructed 29 linkage maps, including for the previously unscaffolded Z chromosome. The hihi is an endangered passerine endemic to Aotearoa New Zealand that is sexually dimorphic and exhibits high levels of sexual conflict, including sperm competition. Patterns in recombination in the hihi are consistent with those in other birds, including higher recombination rates in micro-chromosomes. Heterochiasmy in the hihi is male-biased, in line with predictions of the Haldane-Huxley rule, with the male linkage map being 15% longer. Micro-chromosomes exhibit heterochiasmy to a greater extent, contrary to that reported in other birds. At the intra-chromosomal level, heterochiasmy is higher nearer to chromosome ends and in gene-rich regions. Regions of extreme heterochiasmy are enriched for genes implicated in cell structure. This study adds an important contribution in assessing evolutionary theories of heterochiasmy and provides a framework for future studies investigating fine-scale heterochiasmy.

Male-biased recombination at chromosome ends in a songbird revealed by precisely mapping crossover positions

Recombination plays a crucial role in evolution by generating novel haplotypes and disrupting linkage between genes, thereby enhancing the efficiency of selection. Here, we analyze the genomes of 12 great reed warblers (Acrocephalus arundinaceus) in a 3-generation pedigree to identify precise crossover positions along the chromosomes. We located more than 200 crossovers and found that these were highly concentrated toward the telomeric ends of the chromosomes. Apart from this major pattern in the recombination landscape, we found significantly higher frequencies of crossovers in genic compared with intergenic regions, and in exons compared with introns. Moreover, while the number of recombination events was similar between the sexes, the crossovers were located significantly closer to the ends of paternal compared with maternal chromosomes. In conclusion, our study of the great reed warbler revealed substantial variation in crossover frequencies within chromosomes, with a distinct bias toward the sub-telomeric regions, particularly on the paternal side. These findings emphasize the importance of thoroughly screening the entire length of chromosomes to characterize the recombination landscape and uncover potential sex-biases in recombination.

Peering into the gaps: Long-read sequencing illuminates structural variants and genomic evolution in the Australasian snapper

Even before genome sequencing, genetic resources have supported species management and breeding programs. Current technologies, such as long-read sequencing, resolve complex genomic regions, like those rich in repeats or high in GC content. Improved genome contiguity enhances accuracy in identifying structural variants (SVs) and transposable elements (TEs). We present an improved genome assembly and SV catalogue for the Australasian snapper (Chrysophrys auratus). The new assembly is more contiguous, allowing for putative identification of 14 centromeres and transfer of 26,115 gene annotations from yellowfin seabream. Compared to the previous assembly, 35,000 additional SVs, including larger and more complex rearrangements, were annotated. SVs and TEs exhibit a distribution pattern skewed towards chromosome ends, likely influenced by recombination. Some SVs overlap with growth-related genes, underscoring their significance. This upgraded genome serves as a foundation for studying natural and artificial selection, offers a reference for related species, and sheds light on genome dynamics shaped by evolution.

Impact of feralization on evolutionary trajectories in the genomes of feral cat island populations

Feralization is the process of domesticated animals returning to the wild and it is considered the counterpart of domestication. Molecular genetic changes are well documented in domesticated organisms but understudied in feral populations. In this study, the genetic differentiation between domestic and feral cats was inferred by analysing whole-genome sequencing data of two geographically distant feral cat island populations, Dirk Hartog Island (Australia) and Kaho'olawe (Hawaii) as well as domestic cats and European wildcats. The study investigated population structure, genetic differentiation, genetic diversity, highly differentiated genes, and recombination rates. Genetic structure analyses linked both feral cat populations to North American domestic and European cat populations. Recombination rates in feral cats were lower than in domestic cats but higher than in wildcats. For Australian and Hawaiian feral cats, 105 and 94 highly differentiated genes compared to domestic cats respectively, were identified. Annotated genes had similar functions, with almost 30% of the divergent genes related to nervous system development in both feral groups. Twenty mutually highly differentiated genes were found in both feral populations. Evolution of highly differentiated genes was likely driven by specific demographic histories, the relaxation of the selective pressures associated with domestication, and adaptation to novel environments to a minor extent. Random drift was the prevailing force driving highly divergent regions, with relaxed selection in feral populations also playing a significant role in differentiation from domestic cats. The study demonstrates that feralization is an independent process that brings feral cats on a unique evolutionary trajectory.

Understanding the Genetic Basis of Variation in Meiotic Recombination: Past, Present, and Future

Meiotic recombination is a fundamental feature of sexually reproducing species. It is often required for proper chromosome segregation and plays important role in adaptation and the maintenance of genetic diversity. The molecular mechanisms of recombination are remarkably conserved across eukaryotes, yet meiotic genes and proteins show substantial variation in their sequence and function, even between closely related species. Furthermore, the rate and distribution of recombination shows a huge diversity within and between chromosomes, individuals, sexes, populations, and species. This variation has implications for many molecular and evolutionary processes, yet how and why this diversity has evolved is not well understood. A key step in understanding trait evolution is to determine its genetic basis-that is, the number, effect sizes, and distribution of loci underpinning variation. In this perspective, I discuss past and current knowledge on the genetic basis of variation in recombination rate and distribution, explore its evolutionary implications, and present open questions for future research.

On the estimation of genome-average recombination rates

The rate at which recombination events occur in a population is an indicator of its effective population size and the organism's reproduction mode. It determines the extent of linkage disequilibrium along the genome and, thereby, the efficacy of both purifying and positive selection. The population recombination rate can be inferred using models of genome evolution in populations. Classic methods based on the patterns of linkage disequilibrium provide the most accurate estimates, providing large sample sizes are used and the demography of the population is properly accounted for. Here, the capacity of approaches based on the sequentially Markov coalescent (SMC) to infer the genome-average recombination rate from as little as a single diploid genome is examined. SMC approaches provide highly accurate estimates even in the presence of changing population sizes, providing that (1) within genome heterogeneity is accounted for and (2) classic maximum-likelihood optimization algorithms are employed to fit the model. SMC-based estimates proved sensitive to gene conversion, leading to an overestimation of the recombination rate if conversion events are frequent. Conversely, methods based on the correlation of heterozygosity succeed in disentangling the rate of crossing over from that of gene conversion events, but only when the population size is constant and the recombination landscape homogeneous. These results call for a convergence of these two methods to obtain accurate and comparable estimates of recombination rates between populations.

Evolution of Chromosomal Inversions across an Avian Radiation

Chromosomal inversions are structural mutations that can play a prominent role in adaptation and speciation. Inversions segregating across species boundaries (trans-species inversions) are often taken as evidence for ancient balancing selection or adaptive introgression, but can also be due to incomplete lineage sorting. Using whole-genome resequencing data from 18 populations of 11 recognized munia species in the genus Lonchura (N = 176 individuals), we identify four large para- and pericentric inversions ranging in size from 4 to 20 Mb. All four inversions cosegregate across multiple species and predate the numerous speciation events associated with the rapid radiation of this clade across the prehistoric Sahul (Australia, New Guinea) and Bismarck Archipelago. Using coalescent theory, we infer that trans-specificity is improbable for neutrally segregating variation despite substantial incomplete lineage sorting characterizing this young radiation. Instead, the maintenance of all three autosomal inversions (chr1, chr5, and chr6) is best explained by selection acting along ecogeographic clines not observed for the collinear parts of the genome. In addition, the sex chromosome inversion largely aligns with species boundaries and shows signatures of repeated positive selection for both alleles. This study provides evidence for trans-species inversion polymorphisms involved in both adaptation and speciation. It further highlights the importance of informing selection inference using a null model of neutral evolution derived from the collinear part of the genome.

Exploration of Genome-Wide Recombination Rate Variation Patterns at Different Scales in Pigs

Meiotic recombination is a prevalent process in eukaryotic sexual reproduction organisms that plays key roles in genetic diversity, breed selection, and species evolution. However, the recombination events differ across breeds and even within breeds. In this study, we initially computed large-scale population recombination rates of both sexes using approximately 52 K SNP genotypes in a total of 3279 pigs from four different Chinese and Western breeds. We then constructed a high-resolution historical recombination map using approximately 16 million SNPs from a sample of unrelated individuals. Comparative analysis of porcine recombination events from different breeds and at different resolutions revealed the following observations: Firstly, the 1Mb-scale pig recombination maps of the same sex are moderately conserved among different breeds, with the similarity of recombination events between Western pigs and Chinese indigenous pigs being lower than within their respective groups. Secondly, we identified 3861 recombination hotspots in the genome and observed medium- to high-level correlation between historical recombination rates (0.542~0.683) and estimates of meiotic recombination rates. Third, we observed that recombination hotspots are significantly far from the transcription start sites of pig genes, and the silico-predicted PRDM9 zinc finger domain DNA recognition motif is significantly enriched in the regions of recombination hotspots compared to recombination coldspots, highlighting the potential role of PRDM9 in regulating recombination hotspots in pigs. Our study analyzed the variation patterns of the pig recombination map at broad and fine scales, providing a valuable reference for genomic selection breeding and laying a crucial foundation for further understanding the molecular mechanisms of pig genome recombination.

How admixed captive breeding populations could be rescued using local ancestry information

This paper asks the question: can genomic information be used to recover a species that is already on the pathway to extinction due to genetic swamping from a related and more numerous population? We show that a breeding strategy in a captive breeding program can use whole genome sequencing to identify and remove segments of DNA introgressed through hybridisation. The proposed policy uses a generalized measure of kinship or heterozygosity accounting for local ancestry, that is, whether a specific genetic location was inherited from the target of conservation. We then show that optimizing these measures would minimize undesired ancestry while also controlling kinship and/or heterozygosity, in a simulated breeding population. The process is applied to real data representing the hybridized Scottish wildcat breeding population, with the result that it should be possible to breed out domestic cat ancestry. The ability to reverse introgression is a powerful tool brought about through the combination of sequencing with computational advances in ancestry estimation. Since it works best when applied early in the process, important decisions need to be made about which genetically distinct populations should benefit from it and which should be left to reform into a single population.

Divergence time shapes gene reuse during repeated adaptation

When diverse lineages repeatedly adapt to similar environmental challenges, the extent to which the same genes are involved (gene reuse) varies across systems. We propose that divergence time among lineages is a key factor driving this variability: as lineages diverge, the extent of gene reuse should decrease due to reductions in allele sharing, functional differentiation among genes, and restructuring of genome architecture. Indeed, we show that many genomic studies of repeated adaptation find that more recently diverged lineages exhibit higher gene reuse during repeated adaptation, but the relationship becomes less clear at older divergence time scales. Thus, future research should explore the factors shaping gene reuse and their interplay across broad divergence time scales for a deeper understanding of evolutionary repeatability.

The genetic changes that shaped Neandertals, Denisovans, and modern humans

Modern human ancestors diverged from the ancestors of Neandertals and Denisovans about 600,000 years ago. Until about 40,000 years ago, these three groups existed in parallel, occasionally met, and exchanged genes. A critical question is why modern humans, and not the other two groups, survived, became numerous, and developed complex cultures. Here, we discuss genetic differences among the groups and some of their functional consequences. As more present-day genome sequences become available from diverse groups, we predict that very few, if any, differences will distinguish all modern humans from all Neandertals and Denisovans. We propose that the genetic basis of what constitutes a modern human is best thought of as a combination of genetic features, where perhaps none of them is present in each and every present-day individual.

Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos

Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes rely either on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or on direct detection of crossovers in gametes or multigeneration pedigrees, which limits data set scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, and the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations show our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ∼150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared with disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.

GC heterogeneity reveals sequence-structures evolution of angiosperm ITS2

BACKGROUND

Despite GC variation constitutes a fundamental element of genome and species diversity, the precise mechanisms driving it remain unclear. The abundant sequence data available for the ITS2, a commonly employed phylogenetic marker in plants, offers an exceptional resource for exploring the GC variation across angiosperms.

RESULTS

A comprehensive selection of 8666 species, comprising 165 genera, 63 families, and 30 orders were used for the analyses. The alignment of ITS2 sequence-structures and partitioning of secondary structures into paired and unpaired regions were performed using 4SALE. Substitution rates and frequencies among GC base-pairs in the paired regions of ITS2 were calculated using RNA-specific models in the PHASE package. The results showed that the distribution of ITS2 GC contents on the angiosperm phylogeny was heterogeneous, but their increase was generally associated with ITS2 sequence homogenization, thereby supporting the occurrence of GC-biased gene conversion (gBGC) during the concerted evolution of ITS2. Additionally, the GC content in the paired regions of the ITS2 secondary structure was significantly higher than that of the unpaired regions, indicating the selection of GC for thermodynamic stability. Furthermore, the RNA substitution models demonstrated that base-pair transformations favored both the elevation and fixation of GC in the paired regions, providing further support for gBGC.

CONCLUSIONS

Our findings highlight the significance of secondary structure in GC investigation, which demonstrate that both gBGC and structure-based selection are influential factors driving angiosperm ITS2 GC content.

Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos

Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes either rely on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or direct detection of crossovers in gametes or multi-generation pedigrees, which limits dataset scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, as well as the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations demonstrate our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ~150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared to disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.

The effects of mutation and recombination rate heterogeneity on the inference of demography and the distribution of fitness effects

Disentangling the effects of demography and selection has remained a focal point of population genetic analysis. Knowledge about mutation and recombination is essential in this endeavour; however, despite clear evidence that both mutation and recombination rates vary across genomes, it is common practice to model both rates as fixed. In this study, we quantify how this unaccounted for rate heterogeneity may impact inference using common approaches for inferring selection (DFE-alpha, Grapes, and polyDFE) and/or demography (fastsimcoal2 and δaδi). We demonstrate that, if not properly modelled, this heterogeneity can increase uncertainty in the estimation of demographic and selective parameters and in some scenarios may result in mis-leading inference. These results highlight the importance of quantifying the fundamental evolutionary parameters of mutation and recombination prior to utilizing population genomic data to quantify the effects of genetic drift (i.e., as modulated by demographic history) and selection; or, at the least, that the effects of uncertainty in these parameters can and should be directly modelled in downstream inference.

Genomic and demographic processes differentially influence genetic variation across the human X chromosome

Many forces influence genetic variation across the genome including mutation, recombination, selection, and demography. Increased mutation and recombination both lead to increases in genetic diversity in a region-specific manner, while complex demographic patterns shape patterns of diversity on a more global scale. While these processes act across the entire genome, the X chromosome is particularly interesting because it contains several distinct regions that are subject to different combinations and strengths of these forces: the pseudoautosomal regions (PARs) and the X-transposed region (XTR). The X chromosome thus can serve as a unique model for studying how genetic and demographic forces act in different contexts to shape patterns of observed variation. We therefore sought to explore diversity, divergence, and linkage disequilibrium in each region of the X chromosome using genomic data from 26 human populations. Across populations, we find that both diversity and substitution rate are consistently elevated in PAR1 and the XTR compared to the rest of the X chromosome. In contrast, linkage disequilibrium is lowest in PAR1, consistent with the high recombination rate in this region, and highest in the region of the X chromosome that does not recombine in males. However, linkage disequilibrium in the XTR is intermediate between PAR1 and the autosomes, and much lower than the non-recombining X. Finally, in addition to these global patterns, we also observed variation in ratios of X versus autosomal diversity consistent with population-specific evolutionary history as well. While our results were generally consistent with previous work, two unexpected observations emerged. First, our results suggest that the XTR does not behave like the rest of the recombining X and may need to be evaluated separately in future studies. Second, the different regions of the X chromosome appear to exhibit unique patterns of linked selection across different human populations. Together, our results highlight profound regional differences across the X chromosome, simultaneously making it an ideal system for exploring the action of evolutionary forces as well as necessitating its careful consideration and treatment in genomic analyses.

Genomic architecture of resistance to latania scale (H. lataniae) in kiwifruit (A. chinensis var. chinensis)

BACKGROUND

Latania scale (Hemiberlesia lataniae Signoret) is an armoured scale insect known to cause damage to kiwifruit plants and fruit, which ultimately reduces crop values and creates post-harvest export and quarantine issues. Resistance to H. lataniae does exist in some commercial cultivars of kiwifruit. However, some of the commercial cultivars bred in New Zealand have not inherited alleles for resistance to H. lataniae carried by their parents. To elucidate the architecture of resistance in the parents and develop molecular markers to assist breeding, these experiments analysed the inheritance of resistance to H. lataniae from families related to commercial cultivars.

RESULTS

The first experiment identified a 15.97 Mb genomic region of interest for resistance to H. lataniae in rtGBS data of 3.23 to 19.20 Mb on chromosome 10. A larger population was then QTL mapped, which confirmed the region of interest as the sole locus contributing to H. lataniae resistance. inDel markers mapping the region of low recombination under the QTL peak further narrowed the region associated with H. lataniae resistance to a 5.73 Mb region.

CONCLUSIONS

The kiwifruit populations and genomic methods used in this study identify the same non-recombinant region of chromosome 10 which confers resistance of A. chinensis var. chinensis to H. lataniae. The markers developed to target the H. lataniae resistance loci will reduce the amount of costly and time-consuming phenotyping required for breeding H. lataniae scale resistance into new kiwifruit cultivars.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modeled by a realistic mutation rate and as part of a realistic distribution of fitness effects, as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modeled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false-positive rates are in excess of true-positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

The Recombination Hotspot Paradox: Co-evolution between PRDM9 and its target sites

Recombination often concentrates in small regions called recombination hotspots where recombination is much higher than the genome's average. In many vertebrates, including humans, gene PRDM9 specifies which DNA motifs will be the target for breaks that initiate recombination, ultimately determining the location of recombination hotspots. Because the sequence that breaks (allowing recombination) is converted into the sequence that does not break (preventing recombination), the latter sequence is over-transmitted to future generations and recombination hotspots are self-destructive. Given their self-destructive nature, recombination hotspots should eventually become extinct in genomes where they are found. While empirical evidence shows that individual hotspots do become inactive over time (die), hotspots are abundant in many vertebrates: a contradiction called the Recombination Hotspot Paradox. What saves recombination hotspots from their foretold extinction? Here we formulate a co-evolutionary model of the interaction among sequence-specific gene conversion, fertility selection, and recurrent mutation. We find that allelic frequencies oscillate leading to stable limit cycles. From a biological perspective this means that when fertility selection is weaker than gene conversion, it cannot stop individual hotspots from dying but can save them from extinction by driving their re-activation (resuscitation). In our model, mutation balances death and resuscitation of hotspots, thus maintaining their number over evolutionary time. Interestingly, we find that multiple alleles result in oscillations that are chaotic and multiple targets in oscillations that are asynchronous between targets thus helping to maintain the average genomic recombination probability constant. Furthermore, we find that the level of expression of PRDM9 should control for the fraction of targets that are hotspots and the overall temperature of the genome. Therefore, our co-evolutionary model improves our understanding of how hotspots may be replaced, thus contributing to solve the Recombination Hotspot Paradox. From a more applied perspective our work provides testable predictions regarding the relation between mutation probability and fertility selection with life expectancy of hotspots.

Efficient targeted recombination with CRISPR/Cas9 in hybrids of Caenorhabditis nematodes with suppressed recombination

BACKGROUND

Homology-based recombination (HR) is the cornerstone of genetic mapping. However, a lack of sufficient sequence homology or the presence of a genomic rearrangement prevents HR through crossing, which inhibits genetic mapping in relevant genomic regions. This is particularly true in species hybrids whose genomic sequences are highly divergent along with various genome arrangements, making the mapping of genetic loci, such as hybrid incompatibility (HI) loci, through crossing impractical. We previously mapped tens of HI loci between two nematodes, Caenorhabditis briggsae and C. nigoni, through the repeated backcrossing of GFP-linked C. briggsae fragments into C. nigoni. However, the median introgression size was over 7 Mb, indicating apparent HR suppression and preventing the subsequent cloning of the causative gene underlying a given HI phenotype. Therefore, a robust method that permits recombination independent of sequence homology is desperately desired.

RESULTS

Here, we report a method of highly efficient targeted recombination (TR) induced by CRISPR/Cas9 with dual guide RNAs (gRNAs), which circumvents the HR suppression in hybrids between the two species. We demonstrated that a single gRNA was able to induce efficient TR between highly homologous sequences only in the F1 hybrids but not in the hybrids that carry a GFP-linked C. briggsae fragment in an otherwise C. nigoni background. We achieved highly efficient TR, regardless of sequence homology or genetic background, when dual gRNAs were used that each specifically targeted one parental chromosome. We further showed that dual gRNAs were able to induce efficient TR within genomic regions that had undergone inversion, in which HR-based recombination was expected to be suppressed, supporting the idea that dual-gRNA-induced TR can be achieved through nonhomology-based end joining between two parental chromosomes.

CONCLUSIONS

Recombination suppression can be circumvented through CRISPR/Cas9 with dual gRNAs, regardless of sequence homology or the genetic background of the species hybrid. This method is expected to be applicable to other situations in which recombination is suppressed in interspecies or intrapopulation hybrids.

Recombulator-X: A fast and user-friendly tool for estimating X chromosome recombination rates in forensic genetics

Genetic markers (especially short tandem repeats or STRs) located on the X chromosome are a valuable resource to solve complex kinship cases in forensic genetics in addition or alternatively to autosomal STRs. Groups of tightly linked markers are combined into haplotypes, thus increasing the discriminating power of tests. However, this approach requires precise knowledge of the recombination rates between adjacent markers. The International Society of Forensic Genetics recommends that recombination rate estimation on the X chromosome is performed from pedigree genetic data while taking into account the confounding effect of mutations. However, implementations that satisfy these requirements have several drawbacks: they were never publicly released, they are very slow and/or need cluster-level hardware and strong computational expertise to use. In order to address these key concerns we developed Recombulator-X, a new open-source Python tool. The most challenging issue, namely the running time, was addressed with dynamic programming techniques to greatly reduce the computational complexity of the algorithm. Compared to the previous methods, Recombulator-X reduces the estimation times from weeks or months to less than one hour for typical datasets. Moreover, the estimation process, including preprocessing, has been streamlined and packaged into a simple command-line tool that can be run on a normal PC. Where previous approaches were limited to small panels of STR markers (up to 15), our tool can handle greater numbers (up to 100) of mixed STR and non-STR markers. In conclusion, Recombulator-X makes the estimation process much simpler, faster and accessible to researchers without a computational background, hopefully spurring increased adoption of best practices.

Genomic diversity landscapes in outcrossing and selfing Caenorhabditis nematodes

Caenorhabditis nematodes form an excellent model for studying how the mode of reproduction affects genetic diversity, as some species reproduce via outcrossing whereas others can self-fertilize. Currently, chromosome-level patterns of diversity and recombination are only available for self-reproducing Caenorhabditis, making the generality of genomic patterns across the genus unclear given the profound potential influence of reproductive mode. Here we present a whole-genome diversity landscape, coupled with a new genetic map, for the outcrossing nematode C. remanei. We demonstrate that the genomic distribution of recombination in C. remanei, like the model nematode C. elegans, shows high recombination rates on chromosome arms and low rates toward the central regions. Patterns of genetic variation across the genome are also similar between these species, but differ dramatically in scale, being tenfold greater for C. remanei. Historical reconstructions of variation in effective population size over the past million generations echo this difference in polymorphism. Evolutionary simulations demonstrate how selection, recombination, mutation, and selfing shape variation along the genome, and that multiple drivers can produce patterns similar to those observed in natural populations. The results illustrate how genome organization and selection play a crucial role in shaping the genomic pattern of diversity whereas demographic processes scale the level of diversity across the genome as a whole.

The roles of sexual selection and sexual conflict in shaping patterns of genome and transcriptome variation

Sexual dimorphism is one of the most prevalent, and often the most extreme, examples of phenotypic variation within species, and arises primarily from genomic variation that is shared between females and males. Many sexual dimorphisms arise through sex differences in gene expression, and sex-biased expression is one way that a single, shared genome can generate multiple, distinct phenotypes. Although many sexual dimorphisms are expected to result from sexual selection, and many studies have invoked the possible role of sexual selection to explain sex-specific traits, the role of sexual selection in the evolution of sexually dimorphic gene expression remains difficult to differentiate from other forms of sex-specific selection. In this Review, we propose a holistic framework for the study of sex-specific selection and transcriptome evolution. We advocate for a comparative approach, across tissues, developmental stages and species, which incorporates an understanding of the molecular mechanisms, including genomic variation and structure, governing gene expression. Such an approach is expected to yield substantial insights into the evolution of genetic variation and have important applications in a variety of fields, including ecology, evolution and behaviour.

Evaluating power to detect recurrent selective sweeps under increasingly realistic evolutionary null models

The detection of selective sweeps from population genomic data often relies on the premise that the beneficial mutations in question have fixed very near the sampling time. As it has been previously shown that the power to detect a selective sweep is strongly dependent on the time since fixation as well as the strength of selection, it is naturally the case that strong, recent sweeps leave the strongest signatures. However, the biological reality is that beneficial mutations enter populations at a rate, one that partially determines the mean wait time between sweep events and hence their age distribution. An important question thus remains about the power to detect recurrent selective sweeps when they are modelled by a realistic mutation rate and as part of a realistic distribution of fitness effects (DFE), as opposed to a single, recent, isolated event on a purely neutral background as is more commonly modelled. Here we use forward-in-time simulations to study the performance of commonly used sweep statistics, within the context of more realistic evolutionary baseline models incorporating purifying and background selection, population size change, and mutation and recombination rate heterogeneity. Results demonstrate the important interplay of these processes, necessitating caution when interpreting selection scans; specifically, false positive rates are in excess of true positive across much of the evaluated parameter space, and selective sweeps are often undetectable unless the strength of selection is exceptionally strong.

Teaser Text

Outlier-based genomic scans have proven a popular approach for identifying loci that have potentially experienced recent positive selection. However, it has previously been shown that an evolutionarily appropriate baseline model that incorporates non-equilibrium population histories, purifying and background selection, and variation in mutation and recombination rates is necessary to reduce often extreme false positive rates when performing genomic scans. Here we evaluate the power to detect recurrent selective sweeps using common SFS-based and haplotype-based methods under these increasingly realistic models. We find that while these appropriate evolutionary baselines are essential to reduce false positive rates, the power to accurately detect recurrent selective sweeps is generally low across much of the biologically relevant parameter space.

An estimator for the recombination rate from a continuously observed diffusion of haplotype frequencies

Recombination is a fundamental evolutionary force, but it is difficult to quantify because the effect of a recombination event on patterns of variation in a sample of genetic data can be hard to discern. Estimators for the recombination rate, which are usually based on the idea of integrating over the unobserved possible evolutionary histories of a sample, can therefore be noisy. Here we consider a related question: how would an estimator behave if the evolutionary history actually was observed? This would offer an upper bound on the performance of estimators used in practice. In this paper we derive an expression for the maximum likelihood estimator for the recombination rate based on a continuously observed, multi-locus, Wright-Fisher diffusion of haplotype frequencies, complementing existing work for an estimator of selection. We show that, contrary to selection, the estimator has unusual properties because the observed information matrix can explode in finite time whereupon the recombination parameter is learned without error. We also show that the recombination estimator is robust to the presence of selection in the sense that incorporating selection into the model leaves the estimator unchanged. We study the properties of the estimator by simulation and show that its distribution can be quite sensitive to the underlying mutation rates.

Leaky barriers to gene sharing between locally co-existing coagulase-negative Staphylococcus species

Coagulase-negative Staphylococcus (CoNS) are opportunistic pathogens implicated in many human and animal infections. The evolutionary history of CoNS remains obscure because of the historical lack of recognition for their clinical importance and poor taxonomic sampling. Here, we sequenced the genomes of 191 CoNS isolates representing 15 species sampled from diseased animals diagnosed in a veterinary diagnostic laboratory. We found that CoNS are important reservoirs of diverse phages, plasmids and mobilizable genes encoding antimicrobial resistance, heavy metal resistance, and virulence. Frequent exchange of DNA between certain donor-recipient partners suggests that specific lineages act as hubs of gene sharing. We also detected frequent recombination between CoNS regardless of their animal host species, indicating that ecological barriers to horizontal gene transfer can be surmounted in co-circulating lineages. Our findings reveal frequent but structured patterns of transfer that exist within and between CoNS species, which are driven by their overlapping ecology and geographical proximity.

The fine-scale recombination rate variation and associations with genomic features in a butterfly

Recombination is a key molecular mechanism that has profound implications on both micro- and macroevolutionary processes. However, the determinants of recombination rate variation in holocentric organisms are poorly understood, in particular in Lepidoptera (moths and butterflies). The wood white butterfly (Leptidea sinapis) shows considerable intraspecific variation in chromosome numbers and is a suitable system for studying regional recombination rate variation and its potential molecular underpinnings. Here, we developed a large whole-genome resequencing data set from a population of wood whites to obtain high-resolution recombination maps using linkage disequilibrium information. The analyses revealed that larger chromosomes had a bimodal recombination landscape, potentially caused by interference between simultaneous chiasmata. The recombination rate was significantly lower in subtelomeric regions, with exceptions associated with segregating chromosome rearrangements, showing that fissions and fusions can have considerable effects on the recombination landscape. There was no association between the inferred recombination rate and base composition, supporting a limited influence of GC-biased gene conversion in butterflies. We found significant but variable associations between the recombination rate and the density of different classes of transposable elements, most notably a significant enrichment of short interspersed nucleotide elements in genomic regions with higher recombination rate. Finally, the analyses unveiled significant enrichment of genes involved in farnesyltranstransferase activity in recombination coldspots, potentially indicating that expression of transferases can inhibit formation of chiasmata during meiotic division. Our results provide novel information about recombination rate variation in holocentric organisms and have particular implications for forthcoming research in population genetics, molecular/genome evolution, and speciation.

Repeat-Induced Point Mutation and Gene Conversion Coinciding with Heterochromatin Shape the Genome of a Plant-Pathogenic Fungus

Meiosis is associated with genetic changes in the genome-via recombination, gene conversion, and mutations. The occurrence of gene conversion and mutations during meiosis may further be influenced by the chromatin conformation, similar to the effect of the chromatin conformation on the mitotic mutation rate. To date, however, the exact distribution and type of meiosis-associated changes and the role of the chromatin conformation in this context are largely unexplored. Here, we determine recombination, gene conversion, and de novo mutations using whole-genome sequencing of all meiotic products of 23 individual meioses in Zymoseptoria tritici, an important pathogen of wheat. We confirm a high genome-wide recombination rate of 65 centimorgan (cM)/Mb and see higher recombination rates on the accessory compared to core chromosomes. A substantial fraction of 0.16% of all polymorphic markers was affected by gene conversions, showing a weak GC-bias and occurring at higher frequency in regions of constitutive heterochromatin, indicated by the histone modification H3K9me3. The de novo mutation rate associated with meiosis was approximately three orders of magnitude higher than the corresponding mitotic mutation rate. Importantly, repeat-induced point mutation (RIP), a fungal defense mechanism against duplicated sequences, is active in Z. tritici and responsible for the majority of these de novo meiotic mutations. Our results indicate that the genetic changes associated with meiosis are a major source of variability in the genome of an important plant pathogen and shape its evolutionary trajectory. IMPORTANCE The impact of meiosis on the genome composition via gene conversion and mutations is mostly poorly understood, in particular, for non-model species. Here, we sequenced all four meiotic products for 23 individual meioses and determined the genetic changes caused by meiosis for the important fungal wheat pathogen Zymoseptoria tritici. We found a high rate of gene conversions and an effect of the chromatin conformation on gene conversion rates. Higher conversion rates were found in regions enriched with the H3K9me3-a mark for constitutive heterochromatin. Most importantly, meiosis was associated with a much higher frequency of de novo mutations than mitosis; 78% of the meiotic mutations were caused by repeat-induced point mutations-a fungal defense mechanism against duplicated sequences. In conclusion, the genetic changes associated with meiosis are therefore a major factor shaping the genome of this fungal pathogen.

High-resolution mapping reveals hotspots and sex-biased recombination in Populus trichocarpa

Fine-scale meiotic recombination is fundamental to the outcome of natural and artificial selection. Here, dense genetic mapping and haplotype reconstruction were used to estimate recombination for a full factorial Populus trichocarpa cross of 7 males and 7 females. Genomes of the resulting 49 full-sib families (N = 829 offspring) were resequenced, and high-fidelity biallelic SNP/INDELs and pedigree information were used to ascertain allelic phase and impute progeny genotypes to recover gametic haplotypes. The 14 parental genetic maps contained 1,820 SNP/INDELs on average that covered 376.7 Mb of physical length across 19 chromosomes. Comparison of parental and progeny haplotypes allowed fine-scale demarcation of cross-over regions, where 38,846 cross-over events in 1,658 gametes were observed. Cross-over events were positively associated with gene density and negatively associated with GC content and long-terminal repeats. One of the most striking findings was higher rates of cross-overs in males in 8 out of 19 chromosomes. Regions with elevated male cross-over rates had lower gene density and GC content than windows showing no sex bias. High-resolution analysis identified 67 candidate cross-over hotspots spread throughout the genome. DNA sequence motifs enriched in these regions showed striking similarity to those of maize, Arabidopsis, and wheat. These findings, and recombination estimates, will be useful for ongoing efforts to accelerate domestication of this and other biomass feedstocks, as well as future studies investigating broader questions related to evolutionary history, perennial development, phenology, wood formation, vegetative propagation, and dioecy that cannot be studied using annual plant model systems.

Rapid Evolution of the Fine-scale Recombination Landscape in Wild House Mouse (Mus musculus) Populations

Meiotic recombination is an important evolutionary force and an essential meiotic process. In many species, recombination events concentrate into hotspots defined by the site-specific binding of PRMD9. Rapid evolution of Prdm9's zinc finger DNA-binding array leads to remarkably abrupt shifts in the genomic distribution of hotspots between species, but the question of how Prdm9 allelic variation shapes the landscape of recombination between populations remains less well understood. Wild house mice (Mus musculus) harbor exceptional Prdm9 diversity, with >150 alleles identified to date, and pose a particularly powerful system for addressing this open question. We employed a coalescent-based approach to construct broad- and fine-scale sex-averaged recombination maps from contemporary patterns of linkage disequilibrium in nine geographically isolated wild house mouse populations, including multiple populations from each of three subspecies. Comparing maps between wild mouse populations and subspecies reveals several themes. First, we report weak fine- and broad-scale recombination map conservation across subspecies and populations, with genetic divergence offering no clear prediction for recombination map divergence. Second, most hotspots are unique to one population, an outcome consistent with minimal sharing of Prdm9 alleles between surveyed populations. Finally, by contrasting aggregate hotspot activity on the X versus autosomes, we uncover evidence for population-specific differences in the degree and direction of sex dimorphism for recombination. Overall, our findings illuminate the variability of both the broad- and fine-scale recombination landscape in M. musculus and underscore the functional impact of Prdm9 allelic variation in wild mouse populations.

NanoCross: A pipeline that detecting recombinant crossover using ONT sequencing data

Meiotic recombination is crucial for eukaryotes but varies among taxonomic scales (between individuals, groups, species, etc.) and genome resolutions. Studying how and why recombination rates change can help us understand the molecular basis and mechanisms of genetics and evolution. We introduce a genome-wide identification script called NanoCross, which uses ONT sequences to detect pooled gamete DNA cross recombination events. NanoCross first reduced sequencing errors and then constructed individual haplotypes based on homopolymer-filtered ONT sequences. Then, each molecule read is used to estimate cross recombination. In the case of moderate heterozygous variation density and sequencing depth, simulations revealed that our technique offers a good level of sensitivity and specificity. We constructed a high-resolution recombination map of wild boar genomes using NanoCross and compared it to recombination maps of male breeding pig populations. NanoCross provides us with a method and scripts for constructing a high-resolution individual genome recombination map utilizing long-read sequencing, as well as a novel approach for examining the variation in individual recombination rate. The source code and data mechanism are hosted on GitHub (https://github.com/zuoquanchen/NanoCross).

Linkage mapping and genome annotation give novel insights into gene family expansions and regional recombination rate variation in the painted lady (Vanessa cardui) butterfly

Characterization of gene family expansions and crossing over is crucial for understanding how organisms adapt to the environment. Here, we develop a high-density linkage map and detailed genome annotation of the painted lady butterfly (Vanessa cardui) - a non-diapausing, highly polyphagous species famous for its long-distance migratory behavior and almost cosmopolitan distribution. Our results reveal a complex interplay between regional recombination rate variation, gene duplications and transposable element activity shaping the genome structure of the painted lady. We identify several lineage specific gene family expansions. Their functions are mainly associated with protein and fat metabolism, detoxification, and defense against infection - critical processes for the painted lady's unique life-history. Furthermore, the detailed recombination maps allow us to characterize the regional recombination landscape, data that reveal a strong effect of chromosome size on the recombination rate, a limited impact of GC-biased gene conversion and a positive association between recombination and short interspersed elements.

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations.

Simulation-Based Evaluation of Methods, Data Types, and Temporal Sampling Schemes for Detecting Recent Population Declines

Understanding recent population trends is critical to quantifying species vulnerability and implementing effective management strategies. To evaluate the accuracy of genomic methods for quantifying recent declines (beginning <120 generations ago), we simulated genomic data using forward-time methods (SLiM) coupled with coalescent simulations (msprime) under a number of demographic scenarios. We evaluated both site frequency spectrum (SFS)-based methods (momi2, Stairway Plot) and methods that employ linkage disequilibrium information (NeEstimator, GONE) with a range of sampling schemes (contemporary-only samples, sampling two time points, and serial sampling) and data types (RAD-like data and whole-genome sequencing). GONE and momi2 performed best overall, with >80% power to detect severe declines with large sample sizes. Two-sample and serial sampling schemes could accurately reconstruct changes in population size, and serial sampling was particularly valuable for making accurate inferences when genotyping errors or minor allele frequency cutoffs distort the SFS or under model mis-specification. However, sampling only contemporary individuals provided reliable inferences about contemporary size and size change using either site frequency or linkage-based methods, especially when large sample sizes or whole genomes from contemporary populations were available. These findings provide a guide for researchers designing genomics studies to evaluate recent demographic declines.

Gene flow biases population genetic inference of recombination rate

Accurate estimates of the rate of recombination are key to understanding a host of evolutionary processes as well as the evolution of the recombination rate itself. Model-based population genetic methods that infer recombination rates from patterns of linkage disequilibrium in the genome have become a popular method to estimate rates of recombination. However, these linkage disequilibrium-based methods make a variety of simplifying assumptions about the populations of interest that are often not met in natural populations. One such assumption is the absence of gene flow from other populations. Here, we use forward-time population genetic simulations of isolation-with-migration scenarios to explore how gene flow affects the accuracy of linkage disequilibrium-based estimators of recombination rate. We find that moderate levels of gene flow can result in either the overestimation or underestimation of recombination rates by up to 20–50% depending on the timing of divergence. We also find that these biases can affect the detection of interpopulation differences in recombination rate, causing both false positives and false negatives depending on the scenario. We discuss future possibilities for mitigating these biases and recommend that investigators exercise caution and confirm that their study populations meet assumptions before deploying these methods.

Selection on modifiers of genetic architecture under migration load

Gene flow between populations adapting to differing local environmental conditions might be costly because individuals can disperse to habitats where their survival is low or because they can reproduce with locally maladapted individuals. The amount by which the mean relative population fitness is kept below one creates an opportunity for modifiers of the genetic architecture to spread due to selection. Prior work that separately considered modifiers changing dispersal, recombination rates, or altering dominance or epistasis, has typically focused on the direction of selection rather than its absolute magnitude. We here develop methods to determine the strength of selection on modifiers of the genetic architecture, including modifiers of the dispersal rate, in populations that have previously evolved local adaptation. We consider scenarios with up to five loci contributing to local adaptation and derive a new model for the deterministic spread of modifiers. We find that selection for modifiers of epistasis and dominance is stronger than selection for decreased recombination, and that selection for partial reductions in recombination are extremely weak, regardless of the number of loci contributing to local adaptation. The spread of modifiers that reduce dispersal depends on the number of loci, epistasis and extent of local adaptation in the ancestral population. We identify a novel effect, that modifiers of dominance are more strongly selected when they are unlinked to the locus that they modify. These findings help explain population differentiation and reproductive isolation and provide a benchmark to compare selection on modifiers under finite population sizes and demographic stochasticity.

When populations of a species are spread over different habitats the populations can adapt to their local conditions, provided dispersal between habitats is low enough. Natural selection allows the populations to maintain local adaptation, but dispersal and gene flow create a cost called the migration load. The migration load measures how much fitness is lost because of dispersal between different habitats, and also creates an opportunity for selection to act on the arrangement and interaction between genes that are involved in local adaptation. Modifier genes can spread in these linked populations and cause functional, local adaptation genes, to become more closely linked on a chromosome, or change the way that these genes are expressed so that the locally adapted gene copy becomes dominant. We modeled this process and found that selection on modifiers that create tighter linkage between locally adapted genes is generally weak, and modifiers that cause gene interactions are more strongly selected. Even after these gene interactions have begun to evolve, further selection for increased gene interaction is still strong. Our results show that populations are more likely to adapt to local conditions by evolving new gene interactions than by evolving tightly linked gene clusters.

Estimating the rates of crossover and gene conversion from individual genomes

Recombination can occur either as a result of crossover or gene conversion events. Population genetic methods for inferring the rate of recombination from patterns of linkage disequilibrium generally assume a simple model of recombination that only involves crossover events and ignore gene conversion. However, distinguishing the 2 processes is not only necessary for a complete description of recombination, but also essential for understanding the evolutionary consequences of inversions and other genomic partitions in which crossover (but not gene conversion) is reduced. We present heRho, a simple composite likelihood scheme for coestimating the rate of crossover and gene conversion from individual diploid genomes. The method is based on analytic results for the distance-dependent probability of heterozygous and homozygous states at 2 loci. We apply heRho to simulations and data from the house mouse Mus musculus castaneus, a well-studied model. Our analyses show (1) that the rates of crossover and gene conversion can be accurately coestimated at the level of individual chromosomes and (2) that previous estimates of the population scaled rate of recombination ρ=4Ner under a pure crossover model are likely biased.

The recombination landscape of the Khoe-San likely represents the upper limits of recombination divergence in humans

BACKGROUND

Recombination maps are  important resources for epidemiological and evolutionary analyses; however, there are currently no recombination maps representing any African population outside of those with West African ancestry. We infer the demographic history for the Nama, an indigenous Khoe-San population of southern Africa, and derive a novel, population-specific recombination map from the whole genome sequencing of 54 Nama individuals. We hypothesise that there are no publicly available recombination maps representative of the Nama, considering the deep population divergence and subsequent isolation of the Khoe-San from other African groups.

RESULTS

We show that the recombination landscape of the Nama does not cluster with any continental groups with publicly available representative recombination maps. Finally, we use selection scans as an example of how fine-scale differences between the Nama recombination map and the combined Phase II HapMap recombination map can impact the outcome of selection scans.

CONCLUSIONS

Fine-scale differences in recombination can meaningfully alter the results of a selection scan. The recombination map we infer likely represents an upper bound on the extent of divergence we expect to see for a recombination map in humans and would be of interest to any researcher that wants to test the sensitivity of population genetic or GWAS analysis to recombination map input.