Biology subjects

Lindsay, S. J.

Publications and source records attributed to Lindsay, S. J..

3 recordsLinked to original sources

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↗

bioRxiv2021

Signatures of Mutational Processes in Human DNA Evolution

The human genome contains over 100 million SNPs, most of which are C/T (G/A) variations. The type and sequence context of these SNPs are not random, suggesting that they are caused by distinct mutational processes. Deciphering the mutational signatures is a crucial step to discovering the molecular processes responsible for DNA variations across human populations, and potentially for causing genetic diseases. Our analyses of the 1000 Genomes Project SNPs and germline de novo mutations suggest that at least four mutational processes are responsible for human genetic variations. One process is European-specific and no longer active. The remaining three processes are currently active in all human populations. Two of the active processes co-occur and leave a single joint mutational signature in human nuclear DNA. The third active process is specific to mitochondrial DNA, and inflicts C-to-T mutations at mostly non-CG sites. We found neither evidence of APOBEC-induced cytosine deamination in the human germline, nor de novo mutation enrichment within certain regions of the human genome.

evolutionary biology↗

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↗