Fu Yun-Xin, Huai Haying
Human Genetics Center, University of Texas, Houston 77030, USA.
Genetics. 2003 Jun;164(2):797-805. doi: 10.1093/genetics/164.2.797.
Mutation rate is an essential parameter in genetic research. Counting the number of mutant individuals provides information for a direct estimate of mutation rate. However, mutant individuals in the same family can share the same mutations due to premeiotic mutation events, so that the number of mutant individuals can be significantly larger than the number of mutation events observed. Since mutation rate is more closely related to the number of mutation events, whether one should count only independent mutation events or the number of mutants remains controversial. We show in this article that counting mutant individuals is a correct approach for estimating mutation rate, while counting only mutation events will result in underestimation. We also derived the variance of the mutation-rate estimate, which allows us to examine a number of important issues about the design of such experiments. The general strategy of such an experiment should be to sample as many families as possible and not to sample much more offspring per family than the reciprocal of the pairwise correlation coefficient within each family. To obtain a reasonably accurate estimate of mutation rate, the number of sampled families needs to be in the same or higher order of magnitude as the reciprocal of the mutation rate.
突变率是基因研究中的一个重要参数。统计突变个体的数量可为直接估计突变率提供信息。然而，由于减数分裂前的突变事件，同一家族中的突变个体可能共享相同的突变，从而使突变个体的数量可能显著大于观察到的突变事件的数量。由于突变率与突变事件的数量更为密切相关，因此是只统计独立的突变事件还是统计突变个体的数量仍存在争议。我们在本文中表明，统计突变个体是估计突变率的正确方法，而仅统计突变事件会导致低估。我们还推导了突变率估计值的方差，这使我们能够研究此类实验设计的一些重要问题。此类实验的总体策略应该是尽可能多地抽样家庭，并且每个家庭抽样的后代数量不要比每个家庭内成对相关系数的倒数多太多。为了获得合理准确的突变率估计值，抽样家庭的数量需要与突变率的倒数处于相同或更高的数量级。
