Biology subjects

Hurles, M.

Publications and source records attributed to Hurles, M..

4 recordsLinked to original sources

bioRxiv2026

A 4,000-year genomic history of Bantu speakers from the Congo rainforest

The Congo rainforest was the heartland of the Bantu Expansion, yet its demographic history remains partially understood. We inferred past population dynamics using genomes from 960 sub-Saharan Africans, including four newly sequenced ancient individuals from Iroungou cave and 176 present-day individuals from Gabon. Bantu-speaking populations began differentiating ~4,000 years ago, preceding explosive population growth by a millennium. Distinct southward dispersals contributed to the ancestry of Bantu speakers in Gabon and elsewhere in sub-Saharan Africa, with the ~700-year-old Iroungou individuals providing the closest genetic proxies for the latter. Both Bantu speakers and hunter-gatherers from the Congo rainforest experienced a major demographic crisis ~1,500 years ago, coinciding with an archaeological hiatus. These findings illuminate early Bantu dispersals and the subsequent, unexplained collapse of rainforest populations.

genomics↗

bioRxiv2026

Using somatic data to aid germline clinical variant interpretation in developmental disorders

Accurate interpretation of rare germline variants remains a major challenge in developmental disorders (DD). Somatic mutation data represent a largely untapped source of evidence for germline variant classi-fication. Identical or nearby mutations that drive positive selection when present in somatic tissues can cause developmental disorders when present in the germline. We integrated somatic mutation data from the Catalogue Of Somatic Mutations In Cancer (COSMIC), and healthy tissues (sperm and buccal epithelium) with germline variant datasets from ClinVar and large studies of de novo mutations in DD patients. Across 970 dominant DD genes, 195 have evidence of somatic selection, with a majority demonstrating concordant mechanisms between germline and somatic contexts. We benchmark the ability of somatic data to discriminate pathogenic from benign germline missense variation across dominant DD genes, identifying 145 genes in which somatic data are informative. The strongest utility is in altered-function genes where germline and somatic mechanisms are concordant, for example the RASopathy genes. In these genes, codon-level aggregation of somatic missense counts yields predictive performance comparable to computational predictors or MAVE assays (AUC-ROC 0.895 for somatic data, versus 0.893 for REVEL). Combining somatic features with computational scores improves discrimination further. Using likelihood ratios, we map COSMIC missense codon count thresholds onto American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP)-style evidence strengths, showing that somatic data can reach strong levels of evidence in germline variant interpretation in DD and enable reclassification of variants of uncertain significance. Together, these results establish somatic mutation data as a scalable and clinically actionable evidence source for germline variant interpretation in select DD genes. Graphical abstract(Generated using FigureLabs) O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/732808v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1d65659org.highwire.dtl.DTLVardef@beff70org.highwire.dtl.DTLVardef@174396dorg.highwire.dtl.DTLVardef@1662b08_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

Deciphering the role of germline complex de novo structural variations in rare disorders

De novo structural variants (dnSVs) have emerged as crucial genetic factors in the context of rare disorders. However, these variations often go undiagnosed in routine genetic screening practices. To shed light on their significance in rare disease, we conducted a comprehensive analysis of the largest cohort of parent-offspring whole-genome sequencing data from the UK 100,000 Genomes Project. Our study encompassed a vast cohort of 12,568 families, including 13,702 offspring affected by rare genetic diseases. We identified a total of 1,872 dnSVs, revealing that approximately 12% of the probands harboured at least one dnSV, of which 9% were identified as likely pathogenic in affected probands (151/1696). Advanced parents age was found to be associated with an increased chance of having dnSVs in probands. We discovered 148 clustered breakpoints resulting from a single event. 60% of these complex dnSVs were classified into 9 major SV types, and could be observed in multiple individuals, while the remaining 40% were private events and had not been previously reported. We found 12% of pathogenic dnSVs are complex SVs, emphasising the critical importance of thoroughly examining and considering complex dnSVs in the context of rare disorders. Furthermore, we discovered an enrichment of maternal dnSVs at subtelometric, early-replicating regions of chromosome 16, suggesting possible sex-specific mechanisms in generation of dnSVs. This study sheds light on the extent of diversity of dnSVs in the germline and their contribution to rare genetic disorders.

genomics↗

bioRxiv2016

Striking differences in patterns of germline mutation between mice and humans

Recent whole genome sequencing (WGS) studies have estimated that the human germline mutation rate per basepair per generation ([~]1.2-10-8) 1,2 is substantially higher than in mice (3.5-5.4-10-9) 3,4, which has been attributed to more efficient purifying selection due to larger effective population sizes in mice compared to humans.5,6,7. In humans, most germline mutations are paternal in origin and the numbers of mutations per offspring increase markedly with paternal age 2,8,9 and more weakly with maternal age 10. Germline mutations can arise at any stage of the cellular lineage from zygote to gamete, resulting in mutations being represented in different proportion and types of cells, with the earliest embryonic mutations being mosaic in both somatic and germline cells. Here we use WGS of multi-sibling mouse and human pedigrees to show striking differences in germline mutation rate and spectra between the two species, including a dramatic reduction in mutation rate in human spermatogonial stem cell (SSC) divisions, which we hypothesise was driven by selection. The differences we observed between mice and humans result from both biological differences within the same stage of embryogenesis or gametogenesis and species-specific differences in cellular genealogies of the germline.

genomics↗