Fifty years of twin studies
双胞胎研究五十年
The most interesting aspect of these results is that for many traits there is no detectable non-additivity. That is, gene-gene interactions seem to be insignificant, and a simple linear genetic architecture is consistent with the results.
以下结果中最有意思的一点在于,很多人类的复杂性状都没有检测出非可加性(非线性)。也就是说,基因和基因之间的作用似乎微不足道,而一个简单的线性遗传结构就可以解释这些结果。
Meta-analysis of the heritability of human traits based on fifty years of twin studies
Nature Genetics (2015) doi:10.1038/ng.3285基于五十年双胞胎研究的人类表型遗传率的整合分析
《自然遗传学》(2015年)
Despite a century of research on complex traits in humans, the relative importance and specific nature of the influences of genes and environment on human traits remain controversial.尽管关于人类复杂性状的研究已进行了一个世纪,但基因和环境对人类表型的作用孰轻孰重,以及它们的具体性质如何,都还存在争议。
We report a meta-analysis of twin correlations and reported variance components for 17,804 traits from 2,748 publications including 14,558,903 partly dependent twin pairs, virtually all published twin studies of complex traits. Estimates of heritability cluster strongly within functional domains, and across all traits the reported heritability is 49%.
我们在此发表一项关于双胞胎相关性的整合分析,涵盖几乎所有已发表的双胞胎复杂性状研究,包括2748篇论文中研究的14,558,903对(部分重复研究)双胞胎、其所得出的17,804项表型的方差分量。估算出的遗传率在功能群内呈现群集分布,对于全部性状来说,报告的遗传率为49%。
For a majority (69%) of traits, the observed twin correlations are consistent with a simple and parsimonious model where twin resemblance is solely due to additive genetic variation. The data are inconsistent with substantial influences from shared environment or non-additive genetic variation.
对于多数(69%)性状,观察到的双胞胎相关性可以用一个简单到吝啬的模型解释;在这个模型中,双胞胎的相似之处完全归结于可加的遗传差异。这些数据不支持共同的环境因素或者非可加的遗传差异对于复杂性状有显著影响。
This study provides the most comprehensive analysis of the causes of individual differences in human traits thus far and will guide future gene-mapping efforts.
这项研究提供了目前最为全面的一份关于人类性状的个体差异分析,对以后的基因定位研究具有指导意义。
See also Additivity and complex traits in mice:
另见(作者早先的博文)《小鼠的复杂性状与可加性》:
You may have noticed that I am gradually collecting copious evidence for (approximate) additivity. Far too many scientists and quasi-scientists are infected by the epistasis or epigenetics meme, which is appealing to those who “revel in complexity” and would like to believe that biology is too complex to succumb to equations. (“How can it be? But what about the marvelous incomprehensible beautiful sacred complexity of Nature? But But But …”)
你可能已经注意到,我逐渐在搜集(近似于)可加性的丰富证据。有太多科学家和民科染上了流行的遗传上位或者表观遗传的观念;这些观念对于那些“为复杂而陶醉”、相信生物学太过复杂不可能用简单方程来表达的人非常有吸引力。(他们会说“怎么可能呢?可是自然中那些美妙不可方物、神圣不可侵犯的复杂性呢?可是这个可是那个呢?”)
I sometimes explain things this way:
There is a deep evolutionary reason behind additivity: nonlinear mechanisms are fragile and often “break” due to DNA recombination in sexual reproduction. Effects which are only controlled by a single locus are more robustly passed on to offspring. …我有时候会这样解释:
遗传的可加性背后有很深的进化上的原因:非线性的机制过于脆弱,常常会在有性生殖DNA重组中“断开”。而仅由单个位点控制的性状则更易于被传给后代。
Many people confuse the following statements:
“The brain is complex and nonlinear and many genes interact in its construction and operation.”
“Differences in brain performance between two individuals of the same species must be due to nonlinear (non-additive) effects of genes.”The first statement is true, but the second does not appear to be true across a range of species and quantitative traits.
很多人会把下面的两个陈述混淆:
“大脑是复杂且非线性的,有很多基因在它的构成和功能中相互作用。”
“同一物种的不同个体之间大脑性能的差异一定是由于非线性(非可加性)的基因作用。”
第一个说法是正确的,但第二个在很多物种和可量化的性状中似乎都不成立。On the genetic architecture of intelligence and other quantitative traits (p.16):
(作者早先的学术论文)《智力及其他可量化表型的遗传结构》(第16页):
… The preceding discussion is not intended to convey an overly simplistic view of genetics or systems biology. Complex nonlinear genetic systems certainly exist and are realized in every organism. However, quantitative differences between individuals within a species may be largely due to independent linear effects of specific genetic variants.
前面讨论的用意并非要给遗传学或者系统生物学一个过于简化的看法。复杂、非线性的遗传系统肯定存在,而且在任何有机体中都有实现。然而,一个物种中不同个体间的定量差异,在很大程度上可能取决于某些基因差异的独立线性效果。
As noted, linear effects are the most readily evolvable in response to selection, whereas nonlinear gadgets are more likely to be fragile to small changes. (Evolutionary adaptations requiring significant changes to nonlinear gadgets are improbable and therefore require exponentially more time than simple adjustment of frequencies of alleles of linear effect.)
上面说过,线性作用在自然选择中最容易进化出来,而非线性的小把戏则更可能被很小的变化破坏。(非线性机制作出大量改变而得到的进化适应不太可能出现,因此相比于仅需要简单调整基因频率的线性机制来说,它们需要更多时间。)
One might say that, to first approximation, Biology = linear combinations of nonlinear gadgets, and most of the variation between individuals is in the (linear) way gadgets are combined, rather than in the realization of different gadgets in different individuals.
有人可能会说,做个简单的近似,生物学等于非线性机制的线性组合,而且大部分个体间差异是来自各种机制被(线性)组合的方式,而不是这些机制本身在个体间的差异。
Linear models work well in practice, allowing, for example, SNP-based prediction of quantitative traits (milk yield, fat and protein content, productive life, etc.) in dairy cattle. …线性的模型在实践中有广泛用途,比方说用奶牛的单核酸多态性(SNP)来预测可量化的表型(产奶量、奶制品的脂肪和蛋白含量、生产时限等等)。…
翻译:demo
编辑:辉格@whigzhou