Recombination is a main source of genetic variability. However, the potential role of the variation generated by recombination in phenotypic traits, including diseases, remains unexplored because there is currently no method to infer chromosomal subpopulations based on recombination pattern differences. We developed recombClust, a method that uses SNP-phased data to detect differences in historic recombination in a chromosome population. We validated our method by performing simulations and by using real data to accurately predict the alleles of well-known recombination modifiers, including common inversions in Drosophila melanogaster and human, and the chromosomes under selective pressure at the lactase locus in humans. We then applied recombClust to the complex human 1q21.1 region, where nonallelic homologous recombination produces deleterious phenotypes. We discovered and validated the presence of two different recombination histories in these regions that significantly associated with the differential expression of ANKRD35 in whole blood and that were in high linkage with variants previously associated with hypertension. By detecting differences in historic recombination, our method opens a way to assess the influence of recombination variation in phenotypic traits.

中文翻译：

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根据重组历史识别染色体亚群推进了表型性状遗传基础的研究

重组是遗传变异的主要来源。然而，重组产生的变异在表型特征（包括疾病）中的潜在作用仍未得到探索，因为目前没有方法可以根据重组模式差异推断染色体亚群。我们开发了recombClust，这是一种使用 SNP 定相数据来检测染色体群体中历史重组差异的方法。我们通过进行模拟和使用真实数据来准确预测众所周知的重组修饰符的等位基因，包括黑腹果蝇和人类中的常见倒位，以及人类乳糖酶基因座选择压力下的染色体，验证了我们的方法。然后我们应用了recombClust到复杂的人类 1q21.1 区域，其中非等位基因同源重组产生有害表型。我们发现并验证了这些区域中存在两种不同的重组历史，它们与全血中ANKRD35的差异表达显着相关，并且与以前与高血压相关的变异高度相关。通过检测历史重组的差异，我们的方法开辟了一种评估重组变异对表型性状的影响的方法。