Data from: Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

It has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. However, it is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We investigate a number of questions pertaining to the distribution of mutations using more than 130,000 DNMs from three large datasets. We demonstrate that the amount and pattern of variation differs between datasets at the 1MB and 100KB scales probably as a consequence of differences in sequencing technology and processing. In particular, datasets show different patterns of correlation to genomic variables such as replication time. Never-the-less there are many commonalities between datasets, which likely represent true patterns. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that cannot be explained by variation at smaller scales, however the level of this variation is modest at large scales–at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome. We demonstrate that variation in the mutation rate does not generate large-scale variation in GC-content, and hence that mutation bias does not maintain the isochore structure of the human genome. We find that genomic features explain less than 40% of the explainable variance in the rate of DNM. As expected the rate of divergence between species is correlated to the rate of DNM. However, the correlations are weaker than expected if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered.

长期以来，学界基于人类与其他物种的演化分化程度，早已提出人类基因组的突变率在大尺度上存在异质性的假说。然而如今，借助通过亲子三人组测序技术在人类中发现的大量新生突变（de novo mutations, DNMs），我们可以直接对这一假说展开研究。本研究依托来自三个大型数据集的13万余条新生突变数据，对突变分布相关的多个问题展开探究。研究表明，在1兆碱基（1MB）与100千碱基（100KB）尺度下，不同数据集间的变异程度与变异模式存在差异，这一现象大概率源于测序技术与数据处理流程的不同。具体而言，不同数据集与复制时间等基因组变量的关联模式存在显著差异。尽管如此，不同数据集仍存在诸多共性，这些共性大概率反映了真实的突变分布规律。本研究证实，在100KB、1MB以及10兆碱基（10MB）尺度下，突变率存在无法由更小尺度的变异所解释的异质性；但在大尺度下，这类变异的程度较为温和：在1MB尺度下，我们推断约90%的区域的突变率处于平均值的±50%范围内。不同类型的突变表现出相似的变异程度，且变异趋势趋于一致，这表明突变模式在整个基因组中相对恒定。本研究表明，突变率的异质性并不会导致基因组GC含量出现大尺度的变异，因此突变偏好性并非维持人类基因组等容区结构的原因。研究发现，基因组特征仅能解释新生突变率中不到40%的可解释方差。正如预期，物种间的序列分化速率与新生突变率存在相关性。但如果分化程度的所有变异均由突变率差异所致，那么二者的相关性会比实际观测到的更强。本研究提供证据表明，这一现象源于偏向性基因转换对突变固定概率的影响。与序列分化不同，我们发现遗传多样性的大部分变异可由突变率的差异所解释。最后，本研究证实，随着所比对物种的分化程度不断升高，序列分化与新生突变密度之间的相关性会逐渐减弱。