Estimation and partition of heritability in human populations using whole-genome analysis methods.
Estimation and partition of heritability in human populations using whole-genome analysis methods.
复制标题
DOI：
10.1146/annurev-genet-111212-133258
复制
发表时间：
2013
影响因子：
11.1
通讯作者：
Visscher PM
中科院分区：
文献类型：
--
作者：
Vinkhuyzen AA;Wray NR;Yang J;Goddard ME;Visscher PM
对人类群体中复杂性状的遗传变异的理解已经从量化近亲之间的相似性转向对遗传变异的剖析，再到单个基因组座位的贡献。但主要问题仍未得到解答：有多少表型变异是遗传的，有多少遗传变异是相加的，因果变异的效应大小和等位基因频率的联合分布是什么？我们回顾和比较了三种全基因组分析方法，它们使用混合线性模型(MLM)来估计遗传变异，使用基于系谱或SNPs的近亲或远亲之间的关系。我们讨论了每种方法的原理、估计过程、偏差和精度，并综述了基于最大似然方法的人类群体复杂性状的加性遗传变异剖析的最新进展。使用全基因组数据，SNPs对遗传变异的解释远远超过与一个性状相关的高度显著的SNPs，但它们并不能解释用基于系谱的方法估计的所有遗传变异。我们解释了这种“缺失”遗传性的可能原因。
Understanding genetic variation of complex traits in human populations has moved from the quantification of the resemblance between close relatives to the dissection of genetic variation into the contributions of individual genomic loci. But major questions remain unanswered: how much phenotypic variation is genetic, how much of the genetic variation is additive and what is the joint distribution of effect size and allele frequency at causal variants? We review and compare three whole-genome analysis methods that use mixed linear models (MLM) to estimate genetic variation, using the relationship between close or distant relatives based on pedigree or SNPs. We discuss theory, estimation procedures, bias and precision of each method and review recent advances in the dissection of additive genetic variation of complex traits in human populations that are based upon the application of MLM. Using genome wide data, SNPs account for far more of the genetic variation than the highly significant SNPs associated with a trait, but they do not account for all of the genetic variance estimated by pedigree based methods. We explain possible reasons for this ‘missing’ heritability.