Crawford Dana C, Bhangale Tushar, Li Na, Hellenthal Garrett, Rieder Mark J, Nickerson Deborah A, Stephens Matthew
Department of Genome Sciences, University of Washington, Box 354322, Seattle, Washington 98195, USA.
Nat Genet. 2004 Jul;36(7):700-6. doi: 10.1038/ng1376. Epub 2004 Jun 6.
Characterizing fine-scale variation in human recombination rates is important, both to deepen understanding of the recombination process and to aid the design of disease association studies. Current genetic maps show that rates vary on a megabase scale, but studying finer-scale variation using pedigrees is difficult. Sperm-typing experiments have characterized regions where crossovers cluster into 1-2-kb hot spots, but technical difficulties limit the number of studies. An alternative is to use population variation to infer fine-scale characteristics of the recombination process. Several surveys reported 'block-like' patterns of diversity, which may reflect fine-scale recombination rate variation, but limitations of available methods made this impossible to assess. Here, we applied a new statistical method, which overcomes these limitations, to infer patterns of fine-scale recombination rate variation in 74 genes. We found extensive rate variation both within and among genes. In particular, recombination hot spots are a common feature of the human genome: 47% (35 of 74) of genes showed substantive evidence for a hot spot, and many more showed evidence for some rate variation. No primary sequence characteristics are consistently associated with precise hot-spot location, although G+C content and nucleotide diversity are correlated with local recombination rate.
描绘人类重组率的精细尺度变化很重要,这既能加深对重组过程的理解,又有助于疾病关联研究的设计。当前的遗传图谱显示,重组率在兆碱基尺度上存在变化,但利用家系研究更精细尺度的变化很困难。精子分型实验已确定了交叉聚集在1 - 2千碱基热点区域的特征,但技术难题限制了研究数量。另一种方法是利用群体变异来推断重组过程的精细尺度特征。几项调查报道了“块状”多样性模式,这可能反映了精细尺度的重组率变化,但现有方法的局限性使得无法对此进行评估。在此,我们应用了一种新的统计方法,该方法克服了这些局限性,以推断74个基因中精细尺度重组率变化的模式。我们发现基因内部和基因之间都存在广泛的重组率变化。特别是,重组热点是人类基因组的一个常见特征:74个基因中有47%(35个)显示出存在热点的实质性证据,还有更多基因显示出存在某种重组率变化的证据。尽管G + C含量和核苷酸多样性与局部重组率相关,但没有主要序列特征始终与精确的热点位置相关联。