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间的序列分化程度，推测人类基因组范围内的突变率存在大规模差异。如今，借助对核心家系（trios）进行测序在人类群体中发现的大量新发突变（de novo mutations, DNMs），我们得以直接探究这一问题。我们依托来自三个大型数据集的逾13万条DNM数据，针对突变分布相关的诸多议题展开研究。我们证实，在1MB与100KB基因组尺度下，不同数据集间的变异程度与模式存在差异，这或许源于测序技术与数据分析流程的差异。具体而言，各数据集与复制时间等基因组变量的关联模式各不相同。尽管如此，不同数据集仍存在诸多共性，这些共性大概率代表了真实的突变分布模式。我们的研究表明，在100KB、1MB与10MB尺度下，突变率存在无法由更小尺度变异解释的异质性，但在大尺度下，这类异质性的程度相对温和：在1MB尺度下，我们推断约90%的区域的突变率处于均值的±50%范围内。不同类型的突变表现出相似的异质性程度，且变异趋势趋于一致，这意味着全基因组范围内的突变模式相对恒定。我们证实，突变率的异质性并不会引发GC含量的大规模波动，因此突变偏向性并非维持人类基因组等容区结构（isochore structure）的核心动因。我们发现，基因组特征仅能解释DNM率中不到40%的可解释方差。正如预期，物种间的分化率与DNM率存在显著相关性。然而，若物种分化的所有变异均由突变率变异导致，则实际相关性弱于理论预期。我们提供证据表明，这一现象源于偏向性基因转换对突变固定概率的影响。与物种分化不同，我们发现绝大多数遗传多样性的变异可由突变率的异质性解释。最后，我们证实，随着所研究物种的分化程度不断提升，物种分化率与DNM密度之间的相关性会逐渐减弱。