Ignatieva Anastasia, Favero Martina, Koskela Jere, Sant Jaromir, Myers Simon R
Department of Statistics, University of Oxford, Oxford, UK.
School of Mathematics and Statistics, University of Glasgow, Glasgow, UK.
Mol Biol Evol. 2025 Sep 1;42(9). doi: 10.1093/molbev/msaf190.
Recent breakthroughs have enabled the accurate inference of large-scale genealogies. Through modelling the impact of recombination on the correlation structure between genealogical local trees, we evaluate how this structure is reconstructed by leading approaches. Despite identifying pervasive biases, we show that applying a simple correction recovers the desired distributions for one algorithm, Relate. We develop a statistical test to identify clades spanning unexpectedly long genomic regions, likely reflecting regional suppression of recombination in some individuals. Our approach allows a systematic scan for inter-individual recombination rate variation at an intermediate scale, between genome-wide differences and individual hotspots. Using genealogies reconstructed with Relate for 2,504 human genomes, we identify 50 regions possessing clades with unexpectedly long genomic spans (P<1⋅10-12). The strongest signal corresponds to a known inversion on chromosome 17. The second strongest uncovers a novel 760-kb inversion on chromosome 10, common (21%) in S. Asians and correlated with GWAS hits for a range of phenotypes. Other regions indicate additional genomic rearrangements: inversions (8), copy number changes (2), or other variants (12). The remaining regions appear to reflect recombination suppression by previously unevidenced mechanisms. They are enriched for precisely spanning single genes (P=5⋅10-10), specifically those expressed in male gametogenesis, and for eQTLs (P=2⋅10-3). This suggests an extension of previously hypothesized crossover suppression within meiotic genes, towards a model of suppression varying across individuals with different expression levels. Our methods can be readily applied to other species, showing that genealogies offer previously untapped potential to study structural variation and other phenomena impacting evolution.
近期的突破使得大规模谱系的准确推断成为可能。通过对重组对谱系局部树之间相关结构的影响进行建模，我们评估了领先方法是如何重建这种结构的。尽管发现了普遍存在的偏差，但我们表明，应用一种简单的校正方法可以恢复一种算法Relate的期望分布。我们开发了一种统计检验方法，以识别跨越意外长基因组区域的进化枝，这可能反映了某些个体中区域重组抑制现象。我们的方法允许在全基因组差异和个体热点之间的中间尺度上系统地扫描个体间重组率的变化。使用Relate为2504个人类基因组重建的谱系，我们识别出50个区域，这些区域拥有基因组跨度意外长的进化枝（P<1×10⁻¹²）。最强的信号对应于17号染色体上一个已知的倒位。第二强的信号揭示了10号染色体上一个新的760kb倒位，在南亚人中很常见（21%），并且与一系列表型的全基因组关联研究（GWAS）结果相关。其他区域表明存在额外的基因组重排：倒位（8个）、拷贝数变化（2个）或其他变异（12个）。其余区域似乎反映了以前未被证实的机制导致的重组抑制。它们富含精确跨越单个基因（P=5×10⁻¹⁰），特别是那些在雄性配子发生中表达的基因，以及表达数量性状基因座（eQTLs）（P=2×10⁻³）。这表明，先前假设的减数分裂基因内交叉抑制扩展到了一个不同个体间抑制程度随表达水平变化的模型。我们的方法可以很容易地应用于其他物种，这表明谱系为研究影响进化的结构变异和其他现象提供了以前未被挖掘的潜力。
