Sequence diversity lost in early pregnancy

Every generation, the human genome is shuffled during meiosis and a single fertilized egg gives rise to all of the cells of the body1. Meiotic errors leading to chromosomal abnormalities are known causes of pregnancy loss2,3, but genetic aetiologies of euploid pregnancy loss remain largely unexplained4. Here we characterize sequence diversity in early pregnancy loss through whole-genome sequencing of 1,007 fetal samples and 934 parental samples from 467 trios affected by pregnancy loss (fetus, mother and father). Sequenced parental genomes enabled us to determine both the parental and meiotic origins of chromosomal abnormalities, detected in half of our set. It further enabled us to assess de novo mutations on both homologous chromosomes from parents transmitting extra chromosomes, and date them, revealing that 6.6% of maternal mutations occurred before sister chromatid formation in fetal oocytes. We find a similar number of de novo mutations in the trios affected by pregnancy loss as in 9,651 adult trios, but three times the number of pathogenic small (<50 bp) sequence variant genotypes in the loss cases compared with adults. Overall, our findings indicate that around 1 in 136 pregnancies is lost due to a pathogenic small sequence variant genotype in the fetus. Our results highlight the vast sequence diversity that is lost in early pregnancy.

py_ped_sim: a flexible forward pedigree and genetic simulator for complex family pedigree analysis

BACKGROUND

Large-scale family pedigrees are commonly used across medical, evolutionary, and forensic genetics. These pedigrees are tools for identifying genetic disorders, tracking evolutionary patterns, and establishing familial relationships via forensic genetic identification. However, there is a lack of software to accurately simulate different pedigree structures along with genomes corresponding to those individuals in a family pedigree. This limits simulation-based evaluations of methods that use pedigrees.

RESULTS

We have developed a python command-line-based tool called py_ped_sim that facilitates the simulation of pedigree structures and the genomes of individuals in a pedigree. py_ped_sim represents pedigrees as directed acyclic graphs, enabling conversion between standard pedigree formats and integration with the forward population genetic simulator, SLiM. Notably, py_ped_sim allows the simulation of varying numbers of offspring for a set of parents, with the capacity to shift the distribution of sibship sizes over generations. We additionally add simulations for events of misattributed paternity, which offers a way to simulate half-sibling relationships, and simulations to extend the breadth of a family pedigree. We validated the accuracy of both our genome simulator and pedigree simulator. We show that we can simulate genomes onto family pedigrees with levels of expected kinship.

CONCLUSIONS

py_ped_sim is a user-friendly and open-source solution for simulating pedigree structures and conducting pedigree genome simulations. It empowers medical, forensic, and evolutionary genetics researchers to gain deeper insights into the dynamics of genetic inheritance and relatedness within families.

Comparative Phylogenetics Reveal Clade-specific Drivers of Recombination Rate Evolution Across Vertebrates

Meiotic recombination is an integral cellular process, required for the production of viable gametes. Recombination rate is a fundamental genomic parameter, modulating genomic responses to selection. Our increasingly detailed understanding of its molecular underpinnings raises the prospect that we can gain insight into trait divergence by examining the molecular evolution of recombination genes from a pathway perspective, as in mammals, where protein-coding changes in later stages of the recombination pathway are connected to divergence in intra-clade recombination rate. Here, we leverage increased availability of avian and teleost genomes to reconstruct the evolution of the recombination pathway across two additional vertebrate clades: birds, which have higher and more variable rates of recombination and similar divergence times to mammals, and teleost fish, which have much deeper divergence times. Rates of molecular evolution of recombination genes are highly correlated between vertebrate clades and significantly elevated compared to control panels, suggesting that they experience similar selective pressures. Avian recombination genes are significantly more likely to exhibit signatures of positive selection than other clades, unrestricted to later stages of the pathway. Signatures of positive selection in genes linked to recombination rate variation in mammalian populations and those with signatures of positive selection across the avian phylogeny are highly correlated. In contrast, teleost fish recombination genes have significantly less evidence of positive selection despite high intra-clade recombination rate variability. Gaining clade-specific understanding of patterns of variation in recombination genes can elucidate drivers of recombination rate and thus, factors influencing genetic diversity, selection efficacy, and species divergence.

An Upper Bound on the Power of DNA to Distinguish Pedigree Relationships

Background/Objectives: Dense genetic marker panels are increasingly used in kinship analysis for the identification of distant relatives. As more markers are available, it is possible to pinpoint IBD segments more precisely and more reliably, ultimately approaching close to continuously observed IBD. This study investigates the evidential value obtained for discrimination between common pedigree relationships if IBD is observed continuously across the autosomal genome without error. In the continuous case, the evidential value is limited only by the pedigree relationship and the recombination rates. Methods: We conducted simulations to generate IBD segments across the autosomal genome for individuals with defined pedigree relationships. The evidential value for relationship discrimination was then calculated exactly from the underlying model, assuming no genotyping error and full genome coverage. Results: The simulations show that the ability to distinguish pedigree relationships quickly diminishes as relationships become more distant. First cousins can be distinguished from second cousins with 99.9% accuracy which drops to 94% when distinguishing second and third cousins. Relationships with the same expected degree of relatedness can be discriminated using continuously observed IBD, although the effectiveness decreases with more distant relationships. Conclusions: Continuous IBD observation establishes a theoretical upper bound on the power to distinguish relationships if a large but finite number of markers is used. The findings provide a benchmark for evaluating kinship analyses based on finite genetic marker panels.

Human de novo mutation rates from a four-generation pedigree reference

Understanding the human de novo mutation (DNM) rate requires complete sequence information1. Here using five complementary short-read and long-read sequencing technologies, we phased and assembled more than 95% of each diploid human genome in a four-generation, twenty-eight-member family (CEPH 1463). We estimate 98-206 DNMs per transmission, including 74.5 de novo single-nucleotide variants, 7.4 non-tandem repeat indels, 65.3 de novo indels or structural variants originating from tandem repeats, and 4.4 centromeric DNMs. Among male individuals, we find 12.4 de novo Y chromosome events per generation. Short tandem repeats and variable-number tandem repeats are the most mutable, with 32 loci exhibiting recurrent mutation through the generations. We accurately assemble 288 centromeres and six Y chromosomes across the generations and demonstrate that the DNM rate varies by an order of magnitude depending on repeat content, length and sequence identity. We show a strong paternal bias (75-81%) for all forms of germline DNM, yet we estimate that 16% of de novo single-nucleotide variants are postzygotic in origin with no paternal bias, including early germline mosaic mutations. We place all this variation in the context of a high-resolution recombination map (~3.4 kb breakpoint resolution) and find no correlation between meiotic crossover and de novo structural variants. These near-telomere-to-telomere familial genomes provide a truth set to understand the most fundamental processes underlying human genetic variation.

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Estimating mutation rate and characterising single nucleotide de novo mutations in pigs

BACKGROUND

Direct estimates of mutation rates in humans have changed our understanding of evolutionary timing and de novo mutations (DNM) have been associated with several developmental disorders in humans. Livestock species, including pigs, can contribute to the study of DNM because of their ideal population structure and routine phenotype collection. In principle, there is the potential for livestock populations to quickly accumulate new genetic variants because of short generation intervals and high selection intensity. However, the impact of DNM on the fitness of individuals is not known and with current genomic selection programs they cannot contribute to estimated breeding values. The aims of our project were to detect and validate single nucleotide DNM in two commercial pig breeding lines, estimate the single nucleotide mutation rate, and characterise DNM.

RESULTS

We sequenced (150 bp paired end reads, 30X coverage) 46 pig trios from two commercial lines. Single nucleotide DNM were detected using a trio-aware method. We defined candidate DNM as single nucleotide variants (SNVs) found in heterozygous state in trio-offspring with both trio-parents homozygous for the reference allele. In this study, we estimate a lower threshold of the DNM rate in pigs of 6.3 × 10-9 per site per gamete. Our findings are consistent with those from other mammals and those published for a small number of livestock species. Most DNM we detected were in introns (47%) and intergenic regions (49%). The mutational spectrum in pigs differs from that in humans and we found several DNM predicted to have an effect on animal's fitness based on the base pair change and their location in the genome.

CONCLUSIONS

With this study, we have generated fundamental knowledge on mutation rate in a non-primate species and identified DNM that could have an impact on the fitness of individuals.

Rare biochemical & genetic conditions: clues for broader mechanistic insights

Rare disorders often represent a molecular deviation from hi-fidelity genomic integrity networks and are often perceived as too difficult or unimportant for further mechanistic studies. Here, we synthesize evidence demonstrating how valuable knowledge of biochemical pathways related to rare disorders can be for biomedicine. To this end, we describe several rare congenital lipid, protein, organic acid, and glycan metabolism disorders and discuss how rare phenotypes (such as "extreme responders") and case reports (such as the lenalidomide cases) have provided clues for drug discovery or repurposing. We also discuss how rare disorders such as Gaucher disease and ultra-rare genetic syndromes can provide insights into cancer and mTOR-driven metabolism, respectively. Our discussion highlights the continued value of biochemical pathways and studies in understanding human pathophysiology and drug discovery even in the genomics era.

Common variation in meiosis genes shapes human recombination phenotypes and aneuploidy risk

The leading cause of human pregnancy loss is aneuploidy, often tracing to errors in chromosome segregation during female meiosis. While abnormal crossover recombination is known to confer risk for aneuploidy, limited data have hindered understanding of the potential shared genetic basis of these key molecular phenotypes. To address this gap, we performed retrospective analysis of preimplantation genetic testing data from 139,416 in vitro fertilized embryos from 22,850 sets of biological parents. By tracing transmission of haplotypes, we identified 3,656,198 crossovers, as well as 92,485 aneuploid chromosomes. Counts of crossovers were lower in aneuploid versus euploid embryos, consistent with their role in chromosome pairing and segregation. Our analyses further revealed that a common haplotype spanning the meiotic cohesin SMC1B is significantly associated with both crossover count and maternal meiotic aneuploidy, with evidence supporting a non-coding cis-regulatory mechanism. Transcriptome- and phenome-wide association tests also implicated variation in the synaptonemal complex component C14orf39 and crossover-regulating ubiquitin ligases CCNB1IP1 and RNF212 in meiotic aneuploidy risk. More broadly, recombination and aneuploidy possess a partially shared genetic basis that also overlaps with reproductive aging traits. Our findings highlight the dual role of recombination in generating genetic diversity, while ensuring meiotic fidelity.

Dimension Reduction Using Local Principal Components for Regression-Based Multi-SNP Analysis in 1000 Genomes and the Canadian Longitudinal Study on Aging (CLSA)

For genetic association analysis based on multiple SNP regression of genotypes obtained by dense DNA sequencing or array data imputation, multi-collinearity can be a severe issue causing failure to fit the regression model. In this study, we propose a method of Dimension Reduction using Local Principal Components (DRLPC) which aims to resolve multi-collinearity by removing SNPs under the assumption that the remaining SNPs can capture the effect of a removed SNP due to high linear dependency. This approach to dimension reduction is expected to improve the power of regression-based statistical tests. We apply DRLPC to chromosome 22 SNPs of two data sets, the 1000 Genomes Project (phase 3) and the Canadian Longitudinal Study on Aging (CLSA), and calculate variance inflation factors (VIF) in various SNP-sets before and after implementing DRLPC as a metric of collinearity. Notably, DRLPC addresses multi-collinearity by excluding variables with a VIF exceeding a predetermined threshold (VIF = 20), thereby improving applicability for subsequent regression analyses. The number of variables in a final set for regression analysis is reduced to around 20% on average for larger-sized genes, whereas for smaller ones, the proportion is around 48%; suggesting that DRLPC is particularly effective for larger genes. We also compare the power of several multi-SNP statistics constructed for gene-specific analysis to evaluate power gains achieved by DRLPC. In simulation studies based on 100 genes with ≤ 500 SNPs per gene, DRLPC increases the power of the multiple regression Wald test from 60% to around 80%.

Germline mutation rates and fine-scale recombination parameters in zebra finch

Most of our understanding of the fundamental processes of mutation and recombination stems from a handful of disparate model organisms and pedigree studies of mammals, with little known about other vertebrates. To gain a broader comparative perspective, we focused on the zebra finch (Taeniopygia castanotis), which, like other birds, differs from mammals in its karyotype (which includes many micro-chromosomes), in the mechanism by which recombination is directed to the genome, and in aspects of ontogenesis. We collected genome sequences from three generation pedigrees that provide information about 80 meioses, inferring 202 single-point de novo mutations, 1,088 crossovers, and 275 non-crossovers. On that basis, we estimated a sex-averaged mutation rate of 5.0 × 10-9 per base pair per generation, on par with mammals that have a similar generation time (~2-3 years). Also as in mammals, we found a paternal germline mutation bias at later stages of gametogenesis (of 1.7:1) but no discernible difference between sexes in early development. Examining recombination patterns, we found that the sex-averaged crossover rate on macro-chromosomes is 0.93 cM/Mb, with a pronounced enrichment of crossovers near telomeres. In contrast, non-crossover rates are more uniformly distributed. On micro-chromosomes, sex-averaged crossover rates are substantially higher (3.96 cM/Mb), in accordance with crossover homeostasis, and both crossover and non-crossover events are more uniformly distributed. At a finer scale, recombination events overlap CpG islands more often than expected by chance, as expected in the absence of PRDM9. Estimates of the degree of GC-biased gene conversion (59%), the mean non-crossover conversion tract length (~32 bp), and the non-crossover-to-crossover ratio (5.4:1) are all comparable to those reported in primates and mice. Therefore, properties of germline mutation and recombination resolutions remain similar over large phylogenetic distances.

CTCF-anchored chromatin loop dynamics during human meiosis

BACKGROUND

During meiosis, the mammalian genome is organised within chromatin loops, which facilitate synapsis, crossing over and chromosome segregation, setting the stage for recombination events and the generation of genetic diversity. Chromatin looping is thought to play a major role in the establishment of cross overs during prophase I of meiosis, in diploid early primary spermatocytes. However, chromatin conformation dynamics during human meiosis are difficult to study experimentally, due to the transience of each cell division and the difficulty of obtaining stage-resolved cell populations. Here, we employed a machine learning framework trained on single cell ATAC-seq and RNA-seq data to predict CTCF-anchored looping during spermatogenesis, including cell types at different stages of meiosis.

RESULTS

We find dramatic changes in genome-wide looping patterns throughout meiosis: compared to pre-and-post meiotic germline cell types, loops in meiotic early primary spermatocytes are more abundant, more variable between individual cells, and more evenly spread throughout the genome. In preparation for the first meiotic division, loops also include longer stretches of DNA, encompassing more than half of the total genome. These loop structures then influence the rate of recombination initiation and resolution as cross overs. In contrast, in later mature sperm stages, we find evidence of genome compaction, with loops being confined to the telomeric ends of the chromosomes.

CONCLUSION

Overall, we find that chromatin loops do not orchestrate the gene expression dynamics seen during spermatogenesis, but loops do play important roles in recombination, influencing the positions of DNA breakage and cross over events.

Direct measurement of the male germline mutation rate in individuals using sequential sperm samples

Mutations that accumulate in the human male germline with age are a major driver of genetic diversity and contribute to genetic diseases. However, aging-related male germline mutation rates have not been measured directly in germline cells (sperm) at the level of individuals. We developed a study design in which we recalled 23 sperm donors with prior banked samples to provide new sperm samples. The old and new sequential sperm samples were separated by long timespans, ranging from 10 to 33 years. We profiled these samples by high-fidelity duplex sequencing and demonstrate that direct high-fidelity sequencing of sperm yields cohort-wide mutation rates and patterns consistent with prior family-based (trio) studies. In every individual, we detected an increase in sperm mutation burden between the two sequential samples, yielding individual-specific measurements of germline mutation rate. Deep whole-genome sequencing of sequential sperm samples from two individuals followed by targeted validation measured remarkably stable mosaicism of clonal mutations that likely arose during embryonic and germline development, suggesting that age did not substantially impact the diversity of spermatogonial stem cell pools in these individuals. Our application of high-fidelity and deep whole-genome sequencing to sequential sperm samples provides insight into aging-related mutation processes in the male germline.

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.

Quantitative trait loci concentrate in specific regions of the Mexican cavefish genome and reveal key candidate genes for cave-associated evolution

A major goal of modern biology is connecting phenotype with its underlying genetic basis. The Mexican cavefish (Astyanax mexicanus), a characin fish species comprised of a surface ecotype and a cave-derived ecotype, is well suited as a model to study the genetic mechanisms underlying adaptation to extreme environments. Here, we map 206 previously published quantitative trait loci (QTL) for cave-derived traits in A. mexicanus to the newest version of the surface fish genome assembly, AstMex3. These analyses revealed that QTL clusters in the genome more than expected by chance, and this clustering is not explained by the distribution of genes in the genome. To investigate whether certain characteristics of the genome facilitate phenotypic evolution, we tested whether genomic characteristics associated with increased opportunities for mutation, such as highly mutagenic CpG sites, are reliable predictors of the sites of trait evolution but did not find any significant trends. Finally, we combined the QTL map with previously collected expression and selection data to identify 36 candidate genes that may underlie the repeated evolution of cave phenotypes, including rgrb, which is predicted to be involved in phototransduction. We found this gene has disrupted exons in all non-hybrid cave populations but intact reading frames in surface fish. Overall, our results suggest specific regions of the genome may play significant roles in driving adaptation to the cave environment in A. mexicanus and demonstrate how this compiled dataset can facilitate our understanding of the genetic basis of repeated evolution in the Mexican cavefish.

Complete human recombination maps

Human recombination maps are a valuable resource for association and linkage studies and crucial for many inferences of population history and natural selection. Existing maps1-5 are based solely on cross-over (CO) recombination, omitting non-cross-overs (NCOs)-the more common form of recombination6-owing to the difficulty in detecting them. Using whole-genome sequence data in families, we estimate the number of NCOs transmitted from parent to offspring and derive complete, sex-specific recombination maps including both NCOs and COs. Mothers have fewer but longer NCOs than fathers, and oocytes accumulate NCOs in a non-regulated fashion with maternal age. Recombination, primarily NCO, is responsible for 1.8% (95% confidence interval: 1.3-2.3) and 11.3% (95% confidence interval: 9.0-13.6) of paternal and maternal de novo mutations, respectively, and may drive the increase in de novo mutations with maternal age. NCOs are substantially more prominent than COs in centromeres, possibly to avoid large-scale genomic changes that may cause aneuploidy. Our results demonstrate that NCOs highlight to a much greater extent than COs the differences in the meiotic process between the sexes, in which maternal NCOs may reflect the safeguarding of oocytes from infancy until ovulation.

A T2T-CHM13 recombination map and globally diverse haplotype reference panel improves phasing and imputation

The T2T-CHM13 complete human reference genome contains ~200 Mb of newly resolved sequence, improving read mapping and variant calling compared to GRCh38. However, the benefits of using complete reference genomes in other contexts are unclear. Here, we present a reference T2T-CHM13 recombination map and phased haplotype panel derived from 3202 samples from the 1000 Genomes Project (1KGP). Using published long-read based assemblies as a reference-neutral ground truth, we compared our T2T-CHM13 1KGP panel to the previously released GRCh38 1KGP phased callset. We find that alignment to T2T-CHM13 resulted in 38% fewer assembly-discordant genotypes and 16% fewer switch errors. The largest gains in panel accuracy are observed on chromosome X and in the regions flanking disease-causing CNVs. Simons Genome Diversity Project samples were more accurately imputed when using the T2T-CHM13 panel. Our study demonstrates that use of a T2T-native phased haplotype panel improves statistical phasing and imputation for samples from diverse human populations.

Estimating gene conversion rates from population data using multi-individual identity by descent

In humans, homologous gene conversions occur at a higher rate than crossovers, however gene conversion tracts are small and often unobservable. As a result, estimating gene conversion rates is more difficult than estimating crossover rates. We present a method for multi-individual identity-by-descent (IBD) inference that allows for mismatches due to genotype error and gene conversion. We use the inferred IBD to detect alleles that have changed due to gene conversion in the recent past. We analyze data from the TOPMed and UK Biobank studies to estimate autosome-wide maps of gene conversion rates. For 10 kb, 100kb, and 1 Mb windows, the correlation between our TOPMed gene conversion map and the deCODE sex-averaged crossover map ranges from 0.56 to 0.67. We find that the strongest gene conversion hotspots typically die back to the baseline gene conversion rate within 1 kb. In 100 kb and 1 Mb windows, our estimated gene conversion map has higher correlation than the deCODE sex-averaged crossover map with PRDM9 binding enrichment (0.34 vs 0.29 for 100 kb windows and 0.52 vs 0.34 for 1 Mb windows), suggesting that the effect of PRDM9 is greater on gene conversion than on crossover recombination. Our TOPMed gene conversion maps are constructed from 55-fold more observed allele conversions than the recently published deCODE gene conversion maps. Our map provides sex-averaged estimates for 10 kb, 100 kb, and 1 Mb windows, whereas the deCODE gene conversion maps provide sex-specific estimates for 3 Mb windows.

Mutation and recombination parameters in zebra finch are similar to those in mammals

Most of our understanding of the fundamental processes of mutation and recombination stems from a handful of disparate model organisms and pedigree studies of mammals, with little known about other vertebrates. To gain a broader comparative perspective, we focused on the zebra finch (Taeniopygia castanotis), which, like other birds, differs from mammals in its karyotype (which includes many micro-chromosomes), in the mechanism by which recombination is directed to the genome, and in aspects of ontogenesis. We collected genome sequences from three generation pedigrees that provide information about 80 meioses, inferring 202 single-point de novo mutations, 1,174 crossovers, and 275 non-crossovers. On that basis, we estimated a sex-averaged mutation rate of 5.0 × 10-9 per base pair per generation, on par with mammals that have a similar generation time (~2-3 years). Also as in mammals, we found a paternal germline mutation bias at later stages of gametogenesis (of 1.7:1) but no discernible difference between sexes in early development. Examining recombination patterns, we found that the sex-averaged crossover rate on macro-chromosomes (1.05 cM/Mb) is again similar to values observed in mammals, as is the spatial distribution of crossovers, with a pronounced enrichment near telomeres. In contrast, non-crossover rates are more uniformly distributed. On micro-chromosomes, sex-averaged crossover rates are substantially higher (4.21 cM/Mb), as expected from crossover homeostasis, and both crossover and non-crossover events are more uniformly distributed. At a finer scale, recombination events overlap CpG islands more often than expected by chance, as expected in the absence of PRDM9. Despite differences in the mechanism by which recombination events are specified and the presence of many micro-chromosomes, estimates of the degree of GC-biased gene conversion (59%), the mean non-crossover conversion tract length (~32 bp), and the non-crossover-to-crossover ratio (5.4:1) are all comparable to those reported in primates and mice. The similarity of mutation and recombination properties in zebra finch to those in mammals suggest that they are conserved by natural selection.

Earliest modern human genomes constrain timing of Neanderthal admixture

Modern humans arrived in Europe more than 45,000 years ago, overlapping at least 5,000 years with Neanderthals1-4. Limited genomic data from these early modern humans have shown that at least two genetically distinct groups inhabited Europe, represented by Zlatý kůň, Czechia3 and Bacho Kiro, Bulgaria2. Here we deepen our understanding of early modern humans by analysing one high-coverage genome and five low-coverage genomes from approximately 45,000-year-old remains from Ilsenhöhle in Ranis, Germany4, and a further high-coverage genome from Zlatý kůň. We show that distant familial relationships link the Ranis and Zlatý kůň individuals and that they were part of the same small, isolated population that represents the deepest known split from the Out-of-Africa lineage. Ranis genomes harbour Neanderthal segments that originate from a single admixture event shared with all non-Africans that we date to approximately 45,000-49,000 years ago. This implies that ancestors of all non-Africans sequenced so far resided in a common population at this time, and further suggests that modern human remains older than 50,000 years from outside Africa represent different non-African populations.

Ignoring population structure in hominin evolutionary models can lead to the inference of spurious admixture events

Genomic and ancient DNA data have revolutionized palaeoanthropology and our vision of human evolution, with indisputable landmarks like the sequencing of Neanderthal and Denisovan genomes. Yet, using genetic data to identify, date and quantify evolutionary events-such as ancient bottlenecks or admixture-is not straightforward, as inferences may depend on model assumptions. In the last two decades, the idea that Neanderthals and members of the Homo sapiens lineage interbred has gained momentum. From the status of unlikely theory, it has reached consensus among human evolutionary biologists. This theory is mainly supported by statistical approaches that depend on demographic models minimizing or ignoring population structure, despite its widespread occurrence and the fact that, when ignored, population structure can lead to the inference of spurious demographic events. We simulated genomic data under a structured and admixture-free model of human evolution, and found that all the tested admixture approaches identified long Neanderthal fragments in our simulated genomes and an admixture event that never took place. We also observed that several published admixture models failed to predict important empirical diversity or admixture statistics, and that we could identify several scenarios from our structured model that better predicted these statistics jointly. Using a simulated time series of ancient DNA, the structured scenarios could also predict the trajectory of the empirical D statistics. Our results suggest that models accounting for population structure are fundamental to improve our understanding of human evolution, and that admixture between Neanderthals and H. sapiens needs to be re-evaluated in the light of structured models. Beyond the Neanderthal case, we argue that ancient hybridization events, which are increasingly documented in many species, including with other hominins, may also benefit from such re-evaluation.

Multiple-testing corrections in selection scans using identity-by-descent segments

Failing to correct for multiple testing in selection scans can lead to false discoveries of recent genetic adaptations. The scanning statistics in selection studies are often too complicated to theoretically derive a genome-wide significance level or empirically validate control of the family-wise error rate (FWER). By modeling the autocorrelation of identity-by-descent (IBD) rates, we propose a computationally efficient method to determine genome-wide significance levels in an IBD-based scan for recent positive selection. In whole genome simulations, we show that our method has approximate control of the FWER and can adapt to the spacing of tests along the genome. We also show that these scans can have more than fifty percent power to reject the null model in hard sweeps with a selection coefficient s > = 0.01 and a sweeping allele frequency between twenty-five and seventy-five percent. A few human genes and gene complexes have statistically significant excesses of IBD segments in thousands of samples of African, European, and South Asian ancestry groups from the Trans-Omics for Precision Medicine project and the United Kingdom Biobank. Among the significant loci, many signals of recent selection are shared across ancestry groups. One shared selection signal at a skeletal cell development gene is extremely strong in African ancestry samples.

Mean gene conversion tract length in humans estimated to be 459 bp from UK Biobank sequence data

Non-crossover gene conversion is a type of meiotic recombination characterized by the non-reciprocal transfer of genetic material between homologous chromosomes. Gene conversions are thought to occur within relatively short tracts of DNA, estimated to be in the order of 100-1,000 bp in humans. However, the number of observable gene conversion tracts per study has so far been limited by the use of pedigree or sperm-typing data to detect gene conversion events. In this study, we propose a statistical method to estimate the mean length of gene conversion tracts in humans. Our method can handle a large number of gene conversion tracts, leading to more precise estimates of the mean tract length. We apply our method to gene conversion tracts detected in whole autosome sequence data from the UK Biobank using clusters of identity-by-descent segments. From this dataset, we estimate the mean gene conversion tract length in humans to be 459 bp (95% CI: [457, 461]). Stratifying detected gene conversion tracts by whether they overlapped with a recombination hotspot, we estimate the mean gene conversion tract length to be 418 bp (95% CI: [416, 420]) and 492 bp (95% CI: [489, 494]) respectively, for tracts that overlap and do not overlap with a recombination hotspot.

Inherent instability of simple DNA repeats shapes an evolutionarily stable distribution of repeat lengths

Using the Telomere-to-Telomere reference, we assembled the distribution of simple repeat lengths present in the human genome. Analyzing over two hundred mammalian genomes, we found remarkable consistency in the shape of the distribution across evolutionary epochs. All observed genomes harbor an excess of long repeats, which are prone to developing into repeat expansion disorders. We measured mutation rates for repeat length instability, quantitatively modeled the per-generation action of mutations, and observed the corresponding long-term behavior shaping the repeat length distribution. We found that short repetitive sequences appear to be a straightforward consequence of random substitution. Evolving largely independently, longer repeats (10+ nucleotides) emerge and persist in a rapidly mutating dynamic balance between expansion, contraction and interruption. These mutational processes, collectively, are sufficient to explain the abundance of long repeats, without invoking natural selection. Our analysis constrains properties of molecular mechanisms responsible for maintaining genome fidelity that underlie repeat instability.

The recombination landscape of the barn owl, from families to populations

Homologous recombination is a meiotic process that generates diversity along the genome and interacts with all evolutionary forces. Despite its importance, studies of recombination landscapes are lacking due to methodological limitations and limited data. Frequently used approaches include linkage mapping based on familial data that provides sex-specific broad-scale estimates of realized recombination and inferences based on population linkage disequilibrium that reveal a more fine-scale resolution of the recombination landscape, albeit dependent on the effective population size and the selective forces acting on the population. In this study, we use a combination of these 2 methods to elucidate the recombination landscape for the Afro-European barn owl (Tyto alba). We find subtle differences in crossover placement between sexes that lead to differential effective shuffling of alleles. Linkage disequilibrium-based estimates of recombination are concordant with family-based estimates and identify large variation in recombination rates within and among linkage groups. Larger chromosomes show variation in recombination rates, while smaller chromosomes have a universally high rate that shapes the diversity landscape. We find that recombination rates are correlated with gene content, genetic diversity, and GC content. We find no conclusive differences in the recombination landscapes between populations. Overall, this comprehensive analysis enhances our understanding of recombination dynamics, genomic architecture, and sex-specific variation in the barn owl, contributing valuable insights to the broader field of avian genomics.

The adaptive value of recombination in resolving intralocus sexual conflict by gene duplication

Recombination plays a key role in increasing the efficacy of selection. We investigate whether recombination can also play a role in resolving adaptive conflicts at loci coding for traits shared between the sexes. Errors during recombination events resulting in gene duplications may provide a long-term evolutionary advantage if those loci also experience sexually antagonistic (SA) selection since, after duplication, sex-specific expression profiles will be free to evolve, thereby reducing the load on population fitness and resolving the conflict. The potential advantage of gene duplication may be tempered by the short-term deleterious effects on gamete and zygote survival, which may be tolerable in a species with high reproductive output but not with low reproductive output. We used datasets of candidate SA loci from Drosophila melanogaster and humans to test these ideas. As in humans, sexually antagonistic alleles in flies with net positive effects across the two sexes occurred at higher frequencies than alleles with net negative effects. In flies, higher recombination rates were associated with more intense levels of sexual conflict and genes with paralogues occur in regions with higher recombination rates, indicating gene duplication events are associated with a history of SA selection. Genes experiencing higher levels of conflict also showed both a higher proportion with paralogues and higher numbers of paralogues. Together, our findings reveal multiple lines of evidence for a possible route towards the resolution of an adaptive conflict via gene duplication that is facilitated by higher recombination rates.

Genetics of Recombination Rate Variation Within and Between Species

Recombination diversifies the genomes of offspring, influences the evolutionary dynamics of populations, and ensures that chromosomes segregate properly during meiosis. Individuals recombine at different rates but observed levels of variation in recombination rate remain mostly unexplained. Genetic dissection of differences in recombination rate within and between species provides a powerful framework for understanding how this trait evolves. In this Perspective, I amalgamate published findings from genetic studies of variation in the genome-wide number of crossovers within and between species, and I use exploratory analyses to identify preliminary patterns. The narrow-sense heritability of crossover count is consistently low, indicating limited resemblance among relatives and predicting a weak response to short-term selection. Variants associated with crossover number within populations span the range of minor allele frequency. The size of the additive effect of recombination-associated variants, along with a negative correlation between this effect and minor allele frequency, raises the prospect that mutations inducing phenotypic shifts larger than a few crossovers are deleterious, though the contributions of methodological biases to these patterns deserve investigation. Quantitative trait loci that contribute to differences between populations or species alter crossover number in both directions, a pattern inconsistent with selection toward a constant optimum for this trait. Building on this characterization of genetic variation in crossover number within and between species, I describe fruitful avenues for future research. Better integrating recombination rate into quantitative genetics will reveal the balance of evolutionary forces responsible for genetic variation in this trait that shapes inheritance.

Mitochondrial DNA mutations in human oocytes undergo frequency-dependent selection but do not increase with age

Mitochondria, cellular powerhouses, harbor DNA (mtDNA) inherited from the mothers. MtDNA mutations can cause diseases, yet whether they increase with age in human germline cells-oocytes-remains understudied. Here, using highly accurate duplex sequencing of full-length mtDNA, we detected de novo mutations in single oocytes, blood, and saliva in women between 20 and 42 years of age. We found that, with age, mutations increased in blood and saliva but not in oocytes. In oocytes, mutations with high allele frequencies (≥1%) were less prevalent in coding than non-coding regions, whereas mutations with low allele frequencies (<1%) were more uniformly distributed along mtDNA, suggesting frequency-dependent purifying selection. In somatic tissues, mutations caused elevated amino acid changes in protein-coding regions, suggesting positive or destructive selection. Thus, mtDNA in human oocytes is protected against accumulation of mutations having functional consequences and with aging. These findings are particularly timely as humans tend to reproduce later in life.

Analysis of the winter oilseed rape recombination landscape suggests maternal-paternal bias

Recombination, the reciprocal exchange of DNA between homologous chromosomes, is a mandatory step necessary for meiosis progression. Crossovers between homologous chromosomes generate new combinations of alleles and maintain genetic diversity. Due to genetic, epigenetic, and environmental factors, the recombination landscape is highly heterogeneous along the chromosomes and it also differs between populations and between sexes. Here, we investigated recombination characteristics across the 19 chromosomes of the model allopolyploid crop species oilseed rape (Brassica napus L.), using two unique multiparental populations derived from two genetically divergent founder pools, each of which comprised 50 genetically diverse founder accessions. A fully balanced, pairwise chain-crossing scheme was utilized to create each of the two populations. A total of 3213 individuals, spanning five successive generations, were genotyped using a 15K SNP array. We observed uneven distribution of recombination along chromosomes, with some genomic regions undergoing substantially more frequent recombination in both populations. In both populations, maternal recombination events were more frequent than paternal recombination. This study provides unique insight into the recombination landscape at chromosomal level and reveals a maternal-paternal bias for recombination number with implications for breeding.

Adaptation in human immune cells residing in tissues at the frontline of infections

Human immune cells are under constant evolutionary pressure, primarily through their role as first line of defence against pathogens. Most studies on immune adaptation are, however, based on protein-coding genes without considering their cellular context. Here, using data from the Human Cell Atlas, we infer the gene adaptation rate of the human immune landscape at cellular resolution. We find abundant cell types, like progenitor cells during development and adult cells in barrier tissues, to harbour significantly increased adaptation rates. We confirm the adaptation of tissue-resident T and NK cells in the adult lung located in compartments directly facing external challenges, such as respiratory pathogens. Analysing human iPSC-derived macrophages responding to various challenges, we find adaptation in early immune responses. Together, our study suggests host benefits to control pathogen spread at early stages of infection, providing a retrospect of forces that shaped the complexity, architecture, and function of the human body.

Multiple losses of aKRAB from PRDM9 coincide with a teleost-specific intron size distribution

BACKGROUND

Primary transcripts are largely comprised of intronic sequences that are excised and discarded shortly after synthesis. In vertebrates, the shape of the intron size distribution is largely constant; however, most teleost fish have a diverged log-bimodal 'teleost distribution' (TD) that is seen only in teleosts. How the TD evolved and to what extent this was affected by adaptative or non-adaptive mechanisms is unknown.

RESULTS

Here, we show that the TD has evolved independently at least six times and that its appearance is linked to the loss of the aKRAB domain from PRDM9. We determined intron size distributions and identified PRDM9 orthologues from annotated genomes in addition to scanning 1193 teleost assemblies for the aKRAB domain. We show that a diverged form of PRDM9 ( β ) is predominant in teleosts whereas the α version is absent from most species. Only a subset of PRDM9- α proteins contain aKRAB, and hence, it is present only in a small number of teleost lineages. Almost all lineages lacking aKRAB (but no species with) had TDs.

CONCLUSIONS

In mammals, PRDM9 defines the sites of meiotic recombination through a mechanism that increases structural variance and depends on aKRAB. The loss of aKRAB is likely to have shifted the locations of both recombination and structural variance hotspots. Our observations suggest that the TD evolved as a side-effect of these changes and link recombination to the evolution of intron size illustrating how genome architectures can evolve in the absence of selection.

Inferring demographic and selective histories from population genomic data using a two-step approach in species with coding-sparse genomes: an application to human data

The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Modeling recent positive selection using identity-by-descent segments

Recent positive selection can result in an excess of long identity-by-descent (IBD) haplotype segments overlapping a locus. The statistical methods that we propose here address three major objectives in studying selective sweeps: scanning for regions of interest, identifying possible sweeping alleles, and estimating a selection coefficient s. First, we implement a selection scan to locate regions with excess IBD rates. Second, we estimate the allele frequency and location of an unknown sweeping allele by aggregating over variants that are more abundant in an inferred outgroup with excess IBD rate versus the rest of the sample. Third, we propose an estimator for the selection coefficient and quantify uncertainty using the parametric bootstrap. Comparing against state-of-the-art methods in extensive simulations, we show that our methods are more precise at estimating s when s≥0.015. We also show that our 95% confidence intervals contain s in nearly 95% of our simulations. We apply these methods to study positive selection in European ancestry samples from the Trans-Omics for Precision Medicine project. We analyze eight loci where IBD rates are more than four standard deviations above the genome-wide median, including LCT where the maximum IBD rate is 35 standard deviations above the genome-wide median. Overall, we present robust and accurate approaches to study recent adaptive evolution without knowing the identity of the causal allele or using time series data.

Genetic analysis of cognitive preservation in the midwestern Amish reveals a novel locus on chromosome 2

INTRODUCTION

Alzheimer's disease (AD) remains a debilitating condition with limited treatments and additional therapeutic targets needed. Identifying AD protective genetic loci may identify new targets and accelerate identification of therapeutic treatments. We examined a founder population to identify loci associated with cognitive preservation into advanced age.

METHODS

Genome-wide association and linkage analyses were performed on 946 examined and sampled Amish individuals, aged 76-95, who were either cognitively unimpaired (CU) or impaired (CI).

RESULTS

A total of 12 single nucleotide polymorphisms (SNPs) demonstrated suggestive association (P ≤ 5 × 10-4) with cognitive preservation. Genetic linkage analyses identified > 100 significant (logarithm of the odds [LOD] ≥ 3.3) SNPs, some which overlapped with the association results. Only one locus on chromosome 2 retained significance across multiple analyses.

DISCUSSION

A novel significant result for cognitive preservation on chromosome 2 includes the genes LRRTM4 and CTNNA2. Additionally, the lead SNP, rs1402906, impacts the POU3F2 transcription factor binding affinity, which regulates LRRTM4 and CTNNA2.

HIGHLIGHTS

GWAS and linkage identified over 100 loci associated with cognitive preservation. One locus on Chromosome 2 retained significance over multiple analyses. Predicted TFBSs near rs1402906 regulate genes associated with neurocognition.

Frequency and spectrum of mutations in human sperm measured using duplex sequencing correlate with trio-based de novo mutation analyses

De novo mutations (DNMs) are drivers of genetic disorders. However, the study of DNMs is hampered by technological limitations preventing accurate quantification of ultra-rare mutations. Duplex Sequencing (DS) theoretically has < 1 error/billion base-pairs (bp). To determine the DS utility to quantify and characterize DNMs, we analyzed DNA from blood and spermatozoa from six healthy, 18-year-old Swedish men using the TwinStrand DS mutagenesis panel (48 kb spanning 20 genic and intergenic loci). The mean single nucleotide variant mutation frequency (MF) was 1.2 × 10- 7 per bp in blood and 2.5 × 10- 8 per bp in sperm, with the most common base substitution being C > T. Blood MF and substitution spectrum were similar to those reported in blood cells with an orthogonal method. The sperm MF was in the same order of magnitude and had a strikingly similar spectrum to DNMs from publicly available whole genome sequencing data from human pedigrees (1.2 × 10- 8 per bp). DS revealed much larger numbers of insertions and deletions in sperm over blood, driven by an abundance of putative extra-chromosomal circular DNAs. The study indicates the strong potential of DS to characterize human DNMs to inform factors that contribute to disease susceptibility and heritable genetic risks.

Characterization and distribution of de novo mutations in the zebra finch

Germline de novo mutations (DNMs) provide the raw material for evolution. The DNM rate varies considerably between species, sexes and chromosomes. Here, we identify DNMs in the zebra finch (Taeniopygia guttata) across 16 parent-offspring trios using two genome assemblies of different quality. Using an independent genotyping assay, we validate 82% of the 150 candidate DNMs. DNM rates are consistent between both assemblies, with estimates of 6.14 × 10-9 and 6.36 × 10-9 per site per generation. We observe a strong paternal bias in DNM rates (male-to-female ratio ɑ ≈ 4), but this bias is in transition mutations only, leading to a transition-to-transversion ratio of 3.18 and 3.57. Finally, we find that DNMs tend to be randomly distributed across chromosomes, not associated with recombination hotspots or genic regions. However, the sex chromosome chrZ shows a roughly fourfold increased DNM rate compared to autosomes, which is more than the expected increase due to chrZ spending two-thirds of its time in males. Overall, our results further enhance our understanding of DNMs in passerine songbirds.

HEI10 coarsening, chromatin and sequence polymorphism shape the plant meiotic recombination landscape

Meiosis is a conserved eukaryotic cell division that produces spores required for sexual reproduction. During meiosis, chromosomes pair and undergo programmed DNA double-strand breaks, followed by homologous repair that can result in reciprocal crossovers. Crossover formation is highly regulated with typically few events per homolog pair. Crossovers additionally show wider spacing than expected from uniformly random placement - defining the phenomenon of interference. In plants, the conserved HEI10 E3 ligase is initially loaded along meiotic chromosomes, before maturing into a small number of foci, corresponding to crossover locations. We review the coarsening model that explains these dynamics as a diffusion and aggregation process, resulting in approximately evenly spaced HEI10 foci. We review how underlying chromatin states, and the presence of interhomolog polymorphisms, shape the meiotic recombination landscape, in light of the coarsening model. Finally, we consider future directions to understand the control of meiotic recombination in plant genomes.

Recurrent evolution and selection shape structural diversity at the amylase locus

The adoption of agriculture triggered a rapid shift towards starch-rich diets in human populations1. Amylase genes facilitate starch digestion, and increased amylase copy number has been observed in some modern human populations with high-starch intake2, although evidence of recent selection is lacking3,4. Here, using 94 long-read haplotype-resolved assemblies and short-read data from approximately 5,600 contemporary and ancient humans, we resolve the diversity and evolutionary history of structural variation at the amylase locus. We find that amylase genes have higher copy numbers in agricultural populations than in fishing, hunting and pastoral populations. We identify 28 distinct amylase structural architectures and demonstrate that nearly identical structures have arisen recurrently on different haplotype backgrounds throughout recent human history. AMY1 and AMY2A genes each underwent multiple duplication/deletion events with mutation rates up to more than 10,000-fold the single-nucleotide polymorphism mutation rate, whereas AMY2B gene duplications share a single origin. Using a pangenome-based approach, we infer structural haplotypes across thousands of humans identifying extensively duplicated haplotypes at higher frequency in modern agricultural populations. Leveraging 533 ancient human genomes, we find that duplication-containing haplotypes (with more gene copies than the ancestral haplotype) have rapidly increased in frequency over the past 12,000 years in West Eurasians, suggestive of positive selection. Together, our study highlights the potential effects of the agricultural revolution on human genomes and the importance of structural variation in human adaptation.

Estimation of demography and mutation rates from one million haploid genomes

As genetic sequencing costs have plummeted, datasets with sizes previously un-thinkable have begun to appear. Such datasets present new opportunities to learn about evolutionary history, particularly via rare alleles that record the very recent past. However, beyond the computational challenges inherent in the analysis of many large-scale datasets, large population-genetic datasets present theoretical problems. In particular, the majority of population-genetic tools require the assumption that each mutant allele in the sample is the result of a single mutation (the "infinite sites" assumption), which is violated in large samples. Here, we present DR EVIL, a method for estimating mutation rates and recent demographic history from very large samples. DR EVIL avoids the infinite-sites assumption by using a diffusion approximation to a branching-process model with recurrent mutation. The branching-process approach limits the method to rare alleles, but, along with recent results, renders tractable likelihoods with recurrent mutation. We show that DR EVIL performs well in simulations and apply it to rare-variant data from a million haploid samples, identifying a signal of mutation-rate heterogeneity within commonly analyzed classes and predicting that in modern sample sizes, most rare variants at sites with high mutation rates represent the descendants of multiple mutation events.

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.

The Genetic Architecture of Recombination Rates is Polygenic and Differs Between the Sexes in Wild House Sparrows (Passer domesticus)

Meiotic recombination through chromosomal crossing-over is a fundamental feature of sex and an important driver of genomic diversity. It ensures proper disjunction, allows increased selection responses, and prevents mutation accumulation; however, it is also mutagenic and can break up favorable haplotypes. This cost-benefit dynamic is likely to vary depending on mechanistic and evolutionary contexts, and indeed, recombination rates show huge variation in nature. Identifying the genetic architecture of this variation is key to understanding its causes and consequences. Here, we investigate individual recombination rate variation in wild house sparrows (Passer domesticus). We integrate genomic and pedigree data to identify autosomal crossover counts (ACCs) and intrachromosomal allelic shuffling (r¯intra) in 13,056 gametes transmitted from 2,653 individuals to their offspring. Females had 1.37 times higher ACC, and 1.55 times higher r¯intra than males. ACC and r¯intra were heritable in females and males (ACC h2 = 0.23 and 0.11; r¯intra  h2 = 0.12 and 0.14), but cross-sex additive genetic correlations were low (rA = 0.29 and 0.32 for ACC and r¯intra). Conditional bivariate analyses showed that all measures remained heritable after accounting for genetic values in the opposite sex, indicating that sex-specific ACC and r¯intra can evolve somewhat independently. Genome-wide models showed that ACC and r¯intra are polygenic and driven by many small-effect loci, many of which are likely to act in trans as global recombination modifiers. Our findings show that recombination rates of females and males can have different evolutionary potential in wild birds, providing a compelling mechanism for the evolution of sexual dimorphism in recombination.

Homozygosity for a stop-gain variant in CCDC201 causes primary ovarian insufficiency

Age at menopause (AOM) has a substantial impact on fertility and disease risk. While many loci with variants that associate with AOM have been identified through genome-wide association studies (GWAS) under an additive model, other genetic models are rarely considered1. Here through GWAS meta-analysis under the recessive model of 174,329 postmenopausal women from Iceland, Denmark, the United Kingdom (UK; UK Biobank) and Norway, we study low-frequency variants with a large effect on AOM. We discovered that women homozygous for the stop-gain variant rs117316434 (A) in CCDC201 (p.(Arg162Ter), minor allele frequency ~1%) reached menopause 9 years earlier than other women (P = 1.3 × 10-15). The genotype is present in one in 10,000 northern European women and leads to primary ovarian insufficiency in close to half of them. Consequently, homozygotes have fewer children, and the age at last childbirth is 5 years earlier (P = 3.8 × 10-5). The CCDC201 gene was only found in humans in 2022 and is highly expressed in oocytes. Homozygosity for CCDC201 loss-of-function has a substantial impact on female reproductive health, and homozygotes would benefit from reproductive counseling and treatment for symptoms of early menopause.

Genetic links between ovarian ageing, cancer risk and de novo mutation rates

Human genetic studies of common variants have provided substantial insight into the biological mechanisms that govern ovarian ageing1. Here we report analyses of rare protein-coding variants in 106,973 women from the UK Biobank study, implicating genes with effects around five times larger than previously found for common variants (ETAA1, ZNF518A, PNPLA8, PALB2 and SAMHD1). The SAMHD1 association reinforces the link between ovarian ageing and cancer susceptibility1, with damaging germline variants being associated with extended reproductive lifespan and increased all-cause cancer risk in both men and women. Protein-truncating variants in ZNF518A are associated with shorter reproductive lifespan-that is, earlier age at menopause (by 5.61 years) and later age at menarche (by 0.56 years). Finally, using 8,089 sequenced trios from the 100,000 Genomes Project (100kGP), we observe that common genetic variants associated with earlier ovarian ageing associate with an increased rate of maternally derived de novo mutations. Although we were unable to replicate the finding in independent samples from the deCODE study, it is consistent with the expected role of DNA damage response genes in maintaining the genetic integrity of germ cells. This study provides evidence of genetic links between age of menopause and cancer risk.

A fine-scale genetic map of the Japanese population

Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.

The correlation between CpG methylation and gene expression is driven by sequence variants

Gene promoter and enhancer sequences are bound by transcription factors and are depleted of methylated CpG sites (cytosines preceding guanines in DNA). The absence of methylated CpGs in these sequences typically correlates with increased gene expression, indicating a regulatory role for methylation. We used nanopore sequencing to determine haplotype-specific methylation rates of 15.3 million CpG units in 7,179 whole-blood genomes. We identified 189,178 methylation depleted sequences where three or more proximal CpGs were unmethylated on at least one haplotype. A total of 77,789 methylation depleted sequences (~41%) associated with 80,503 cis-acting sequence variants, which we termed allele-specific methylation quantitative trait loci (ASM-QTLs). RNA sequencing of 896 samples from the same blood draws used to perform nanopore sequencing showed that the ASM-QTL, that is, DNA sequence variability, drives most of the correlation found between gene expression and CpG methylation. ASM-QTLs were enriched 40.2-fold (95% confidence interval 32.2, 49.9) among sequence variants associating with hematological traits, demonstrating that ASM-QTLs are important functional units in the noncoding genome.

The rate and nature of mitochondrial DNA mutations in human pedigrees

We examined the rate and nature of mitochondrial DNA (mtDNA) mutations in humans using sequence data from 64,806 contemporary Icelanders from 2,548 matrilines. Based on 116,663 mother-child transmissions, 8,199 mutations were detected, providing robust rate estimates by nucleotide type, functional impact, position, and different alleles at the same position. We thoroughly document the true extent of hypermutability in mtDNA, mainly affecting the control region but also some coding-region variants. The results reveal the impact of negative selection on viable deleterious mutations, including rapidly mutating disease-associated 3243A>G and 1555A>G and pre-natal selection that most likely occurs during the development of oocytes. Finally, we show that the fate of new mutations is determined by a drastic germline bottleneck, amounting to an average of 3 mtDNA units effectively transmitted from mother to child.

Causes and consequences of a complex recombinational landscape in the ant Cardiocondyla obscurior

Eusocial Hymenoptera have the highest recombination rates among all multicellular animals studied so far, but it is unclear why this is and how this affects the biology of individual species. A high-resolution linkage map for the ant Cardiocondyla obscurior corroborates genome-wide high recombination rates reported for ants (8.1 cM/Mb). However, recombination is locally suppressed in regions that are enriched with TEs, that have strong haplotype divergence, or that show signatures of epistatic selection in C. obscurior The results do not support the hypotheses that high recombination rates are linked to phenotypic plasticity or to modulating selection efficiency. Instead, genetic diversity and the frequency of structural variants correlate positively with local recombination rates, potentially compensating for the low levels of genetic variation expected in haplodiploid social Hymenoptera with low effective population size. Ultimately, the data show that recombination contributes to within-population polymorphism and to the divergence of the lineages within C. obscurior.

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.