Biology subjects

Donnelly, P.

Publications and source records attributed to Donnelly, P..

10 recordsLinked to original sources

bioRxiv2026

A genome-wide atlas of meiotic recombination intermediates reveals distinct modes of DNA repair that direct crossovers away from transcriptionally marked genes

Crossovers are essential for accurate chromosome segregation in meiosis. Yet the programmed DNA double-strand breaks that initiate them frequently occur in genes and pose a risk to transcription required for gametogenesis. How meiotic cells reconcile these competing demands has remained unclear. Here, we generate a genome-wide in vivo atlas of meiotic recombination intermediates across [~]42,000 hotspots by mapping repair proteins BLM, HFM1, and RPA in wild-type and genome-engineered mutant mouse testes. These maps reveal two distinct modes of break repair: a fast-resolving class with short-lived intermediates that are repaired predominantly as non-crossovers, and a slower class with persistent intermediates that give rise to nearly all crossovers. Fast-resolving hotspots occur almost exclusively within a deeply conserved set of [~]4,500 genes marked by structural and chromatin features established during an early stage of meiotic transcription. This transcriptional memory predicts repair fate with high accuracy across mouse subspecies and sexes. Across widely diverged mammals, including humans and cattle, orthologous genes show similar crossover suppression. Our findings reveal an early bifurcation between crossover and non-crossover repair that is governed by the transcriptional context of meiotic breaks. Together, they establish an evolutionarily conserved principle in which crossovers are directed away from transcriptionally important genes, thereby safeguarding gene function and shaping their evolution.

genomics↗

bioRxiv2024

Evolution of dosage-sensitive genes by tissue-restricted expression changes

Dosage-sensitive genes have characteristic patterns of evolution that include being refractory to small-scale duplication, depleted on human benign copy number variants (CNVs) and enriched on pathogenic CNVs. This intolerance to copy number change is likely due to an expression constraint that exists in one or more tissues. While genomic copy number changes alter the encompassed genes expression across all tissues, expression quantitative trait loci (eQTLs) -genomic regions harbouring sequence variants that influence the expression level of one or more genes- can act in a tissue-specific manner. In this work we examine expression variation of presumed dosage-sensitive and non-dosage-sensitive genes to discover how the locus duplicability constraints translate into gene expression constraints. Here we test the hypothesis that expression changes due to the presence of eQTLs acting in unconstrained tissues will not be deleterious and thus allow dosage-sensitive genes to vary expression while obeying constraints in other tissues. Using eQTLs across 48 human tissues from The Genotype-Tissue Expression (GTEx) project, we find that dosage-sensitive genes are enriched for being affected by eQTLs and that the eQTLs affecting dosage-sensitive genes are biased towards having narrow tissue-specificity with these genes having fewer eQTL-affected tissues than non-dosage-sensitive genes. Additionally, we find that dosage-sensitive genes are depleted for being affected by broad tissue breadth eQTLs, likely due to the increased chance of these eQTLs conflicting with expression constraints and being removed by purifying selection. These patterns suggest that dosage-sensitivity shapes the evolution of these genes by precluding copy number evolution and restricting their evolutionary trajectories to changes in expression regulation compatible with their functional constraints. Thus deeper interpretation of the patterns of constraints can be informative of the temporal or spatial location of the gene dosage sensitivity and contribute to our understanding of functional genomics. Author summaryGene duplication is an important and powerful evolutionary force that is responsible for the expansion of the coding capacity of genomes ultimately resulting in great genetic novelty. However, the opportunity for this evolutionary change can be limited by dosage constraints on some genes, meaning they are not normally duplicable, except in a balanced, whole genome event. This results in important, biologically relevant, differences between genes that are retained from whole genome duplication events versus those retained from small scale duplications, especially in terms of dosage sensitivity. We explored how the different dosage sensitivity in these sets of genes relates to quantitative expression variation present in populations. We found that while dosage-sensitive genes are more likely to have their expression levels influenced by genetic variation, these changes are often specific a small number of tissues. In contrast, genes that are less sensitive to dosage changes show greater variation in expression levels across multiple tissues. Our findings suggest that dosage-sensitive genes evolve through fine-tuned adjustments in their expression levels in specific tissues, thus bypassing constraints operating on other tissues. This understanding sheds light on how dosage-sensitive genes evolve and could have implications for understanding human diseases caused by these genes.

evolutionary biology↗

bioRxiv2019

ZCWPW1 is recruited to recombination hotspots by PRDM9, and is essential for meiotic double strand break repair

During meiosis, homologous chromosomes pair (synapse) and recombine, enabling balanced segregation and generating genetic diversity. In many vertebrates, recombination initiates with double-strand breaks (DSBs) within hotspots where PRDM9 binds, and deposits H3K4me3 and H3K36me3. However, no protein(s) recognising this unique combination of histone marks have yet been identified.\n\nWe identified Zcwpw1, which possesses H3K4me3 and H3K36me3 recognition domains, as highly co-expressed with Prdm9. Here, we show that ZCWPW1 has co-evolved with PRDM9 and, in human cells, is strongly and specifically recruited to PRDM9 binding sites, with higher affinity than sites possessing H3K4me3 alone. Surprisingly, ZCWPW1 also recognizes CpG dinucleotides, including within many Alu transposons.\n\nMale Zcwpw1 homozygous knockout mice show completely normal DSB positioning, but persistent DMC1 foci at many hotspots, particularly those more strongly bound by PRDM9, severe DSB repair and synapsis defects, and downstream sterility. Our findings suggest a model where ZCWPW1 recognition of PRDM9-bound sites on either the homologous, or broken, chromosome is critical for synapsis, and hence fertility.\n\nGraphical Abstract LegendIn humans and other species, recombination is initiated by double strand breaks at sites bound by PRDM9. Upon binding, PRDM9 deposits the histone marks H3K4me3 and H3K36me, but the functional importance of these marks has remained unknown. Here, we show that PRDM9 recruits ZCWPW1, a reader of both these marks, to its binding sites genome-wide. ZCWPW1 does not help position the breaks themselves, but is essential for their downstream repair and chromosome pairing, and ultimately meiotic success and fertility in mice.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=153 SRC=\"FIGDIR/small/821678v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (31K):\norg.highwire.dtl.DTLVardef@141deb9org.highwire.dtl.DTLVardef@18559deorg.highwire.dtl.DTLVardef@1cf380borg.highwire.dtl.DTLVardef@1689072_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2018

Long-read whole genome sequencing and comparative analysis of six strains of the human pathogen Orientia tsutsugamushi

BackgroundOrientia tsutsugamushi is a clinically important but neglected obligate intracellular bacterial pathogen of the Rickettsiaceae family that causes the potentially life-threatening human disease scrub typhus. In contrast to the genome reduction seen in many obligate intracellular bacteria, early genetic studies of Orientia have revealed one of the most repetitive bacterial genomes sequenced to date. The dramatic expansion of mobile elements has hampered efforts to generate complete genome sequences using short read sequencing methodologies, and consequently there have been few studies of the comparative genomics of this neglected species.\n\nResultsWe report new high-quality genomes of Orientia tsutsugamushi, generated using PacBio single molecule long read sequencing, for six strains: Karp, Kato, Gilliam, TA686, UT76 and UT176. In comparative genomics analyses of these strains together with existing reference genomes from Ikeda and Boryong strains, we identify a relatively small core genome of 657 genes, grouped into core gene islands and separated by repeat regions, and use the core genes to infer the first whole-genome phylogeny of Orientia.\n\nConclusionsComplete assemblies of multiple Orientia genomes verify initial suggestions that these are remarkable organisms. They have large genomes with widespread amplification of repeat elements and massive chromosomal rearrangements between strains. At the gene level, Orientia has a relatively small set of universally conserved genes, similar to other obligate intracellular bacteria, and the relative expansion in genome size can be accounted for by gene duplication and repeat amplification. Our study demonstrates the utility of long read sequencing to investigate complex bacterial genomes and characterise genomic variation.

genomics↗

bioRxiv2018

Patterns of genetic differentiation and the footprints of historical migrations in the Iberian Peninsula

Genetic differences within or between human populations (population structure) has been studied using a variety of approaches over many years. Recently there has been an increasing focus on studying genetic differentiation at fine geographic scales, such as within countries. Identifying such structure allows the study of recent population history, and identifies the potential for confounding in association studies, particularly when testing rare, often recently arisen variants. The Iberian Peninsula is linguistically diverse, has a complex demographic history, and is unique among European regions in having a centuries-long period of Muslim rule. Previous genetic studies of Spain have examined either a small fraction of the genome or only a few Spanish regions. Thus, the overall pattern of fine-scale population structure within Spain remains uncharacterised. Here we analyse genome-wide genotyping array data for 1,413 Spanish individuals sampled from all regions of Spain. We identify extensive fine-scale structure, down to unprecedented scales, smaller than 10 Km in some places. We observe a major axis of genetic differentiation that runs from east to west of the peninsula. In contrast, we observe remarkable genetic similarity in the north-south direction, and evidence of historical north-south population movement. Finally, without making particular prior assumptions about source populations, we show that modern Spanish people have regionally varying fractions of ancestry from a group most similar to modern north Moroccans. The north African ancestry results from an admixture event, which we date to 860 - 1120 CE, corresponding to the early half of Muslim rule. Our results indicate that it is possible to discern clear genetic impacts of the Muslim conquest and population movements associated with the subsequent Reconquista.

genomics↗

bioRxiv2017

Insights into platypus population structure and history from whole-genome sequencing

The platypus is an egg-laying mammal which, alongside the echidna, occupies a unique place in the mammalian phylogenetic tree. Despite widespread interest in its unusual biology, little is known about its population structure or recent evolutionary history. To provide new insights into the dispersal and demographic history of this iconic species, we sequenced the genomes of 57 platypuses from across the whole species range in eastern mainland Australia and Tasmania. Using a highly-improved reference genome, we called over 6.7M SNPs, providing an informative genetic data set for population analyses. Our results show very strong population structure in the platypus, with our sampling locations corresponding to discrete groupings between which there is no evidence for recent gene flow. Genome-wide data allowed us to establish that 28 of the 57 sampled individuals had at least a third-degree relative amongst other samples from the same river, often taken at different times. Taking advantage of a sampled family quartet, we estimated the de novo mutation rate in the platypus at 7.0x10-9/bp/generation (95% CI 4.1x10-9 - 1.2x10-8/bp/generation). We estimated effective population sizes of ancestral populations and haplotype sharing between current groupings, and found evidence for bottlenecks and long-term population decline in multiple regions, and early divergence between populations in different regions. This study demonstrates the power of whole-genome sequencing for studying natural populations of an evolutionarily important species.

genomics↗

bioRxiv2017

Phenome-wide association studies (PheWAS) across large "real-world data" population cohorts support drug target validation

Phenome-wide association studies (PheWAS), which assess whether a genetic variant is associated with multiple phenotypes across a phenotypic spectrum, have been proposed as a possible aid to drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we evaluate whether PheWAS can inform target validation during drug development. We selected 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease therapeutic indications. We independently interrogated these SNPs through PheWAS in four large \"real-world data\" cohorts (23andMe, UK Biobank, FINRISK, CHOP) for association with a total of 1,892 binary endpoints. We then conducted meta-analyses for 145 harmonized disease endpoints in up to 697,815 individuals and joined results with summary statistics from 57 published GWAS. Our analyses replicate 70% of known GWAS associations and identify 10 novel associations with study-wide significance after multiple test correction (P<1.8x10-6; out of 72 novel associations with FDR<0.1). By leveraging directionality and point estimate of the effect sizes, we describe new associations that may predict ADEs, e.g., acne, high cholesterol, gout and gallstones for rs738409 (p.I148M) in PNPLA3; or asthma for rs1990760 (p.T946A) in IFIH1. We further propose how quantitative estimates of genetic safety/efficacy profiles can be used to help prioritize candidate targets for a specific indication. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.\n\nOne Sentence SummaryMatching genetics with phenotypes in 800,000 individuals predicts efficacy and on-target safety of future drugs.

genetics↗

bioRxiv2017

Genome-wide genetic data on ~500,000 UK Biobank participants

The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data - such as population structure and relatedness - that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.

genetics↗

bioRxiv2017

Bayesian analysis of genetic association across tree-structured routine healthcare data in the UK Biobank

Genetic discovery from the multitude of phenotypes extractable from routine healthcare data has the ability to radically transform our understanding of the human phenome, thereby accelerating progress towards precision medicine. However, a critical question when analysing high-dimensional and heterogeneous data is how to interrogate increasingly specific subphenotypes whilst retaining statistical power to detect genetic associations. Here we develop and employ a novel Bayesian analysis framework that exploits the hierarchical structure of diagnosis classifications to jointly analyse genetic variants against UK Biobank healthcare phenotypes. Our method displays a more than 20% increase in power to detect genetic effects over other approaches, such that we uncover the broader burden of genetic variation: we identify associations with over 2,000 diagnostic terms. We find novel associations with common immune-mediated diseases (IMD), we reveal the extent of genetic sharing between specific IMDs, and we expose differences in disease perception or diagnosis with potential clinical implications.

genetics↗

bioRxiv2016

Practical Use of Methods for Imputation of HLA Alleles from SNP Genotype Data

The human leukocyte antigen (HLA) genes play an essential role in immune function. Typing of HLA alleles is critical for transplantation and is informative for many disease associations. The high cost of accurate lab-based HLA typing has precluded its use in large-scale disease-association studies. The development of statistical methods to type alleles using linkage disequilibrium with nearby SNPs, called HLA imputation, has allowed large cohorts of individuals to be typed accurately, so that massive numbers of affected individuals and controls may be studied. This has resulted in many important findings. Several HLA imputation methods have been widely used, however their relative performance has not been adequately addressed. We have conducted a comprehensive study to evaluate the most widely used HLA imputation methods. We assembled a multi-ethnic panel of 10,561 individuals with SNP genotype data and lab-based typing of alleles at 11 HLA genes at two-field resolution, and used it to train and validate each method. Use of this panel leads to imputation accuracy far superior to what is currently publicly available. We present a highly-accurate new imputation method, HLA*IMP:03. We address the question of optimal use of HLA imputations in tests of genetic association, showing that it is usually not necessary to apply a probability threshold to achieve maximal power. We also investigated the effect on accuracy of SNP density and population stratification at the continental level and show that neither of these are a significant concern.

genetics↗