Hum Mol Genet. 2013 Oct 15;22(R1):R16-21. doi: 10.1093/hmg/ddt376. Epub 2013 Aug 6.
The allelic architecture of complex traits is likely to be underpinned by a combination of multiple common frequency and rare variants. Targeted genotyping arrays and next-generation sequencing technologies at the whole-genome sequencing (WGS) and whole-exome scales (WES) are increasingly employed to access sequence variation across the full minor allele frequency (MAF) spectrum. Different study design strategies that make use of diverse technologies, imputation and sample selection approaches are an active target of development and evaluation efforts. Initial insights into the contribution of rare variants in common diseases and medically relevant quantitative traits point to low-frequency and rare alleles acting either independently or in aggregate and in several cases alongside common variants. Studies conducted in population isolates have been successful in detecting rare variant associations with complex phenotypes. Statistical methodologies that enable the joint analysis of rare variants across regions of the genome continue to evolve with current efforts focusing on incorporating information such as functional annotation, and on the meta-analysis of these burden tests. In addition, population stratification, defining genome-wide statistical significance thresholds and the design of appropriate replication experiments constitute important considerations for the powerful analysis and interpretation of rare variant association studies. Progress in addressing these emerging challenges and the accrual of sufficiently large data sets are poised to help the field of complex trait genetics enter a promising era of discovery.
复杂性状的等位基因结构很可能是由多种常见频率和罕见变异共同作用的结果。靶向基因分型阵列和新一代测序技术,包括全基因组测序 (WGS) 和全外显子组测序 (WES),越来越多地用于获取整个次要等位基因频率 (MAF) 谱范围内的序列变异。不同的研究设计策略,利用多种技术、推断和样本选择方法,是开发和评估工作的一个活跃目标。对常见疾病和医学相关数量性状中罕见变异的贡献的初步见解表明,低频和罕见等位基因要么独立作用,要么聚合作用,在某些情况下还与常见变异一起作用。在人群隔离区进行的研究成功地检测到了与复杂表型相关的罕见变异关联。能够对基因组区域内的罕见变异进行联合分析的统计方法学在不断发展,目前的重点是纳入功能注释等信息,并对这些负担测试进行荟萃分析。此外,群体分层、定义全基因组统计显著性阈值和设计适当的复制实验,是对罕见变异关联研究进行有力分析和解释的重要考虑因素。解决这些新出现的挑战并积累足够大的数据集的进展,有望帮助复杂性状遗传学领域进入一个充满希望的发现时代。