遗传相关性分析：现代数据与新挑战。

Genetic relatedness analysis: modern data and new challenges.

作者信息

Weir Bruce S, Anderson Amy D, Hepler Amanda B

机构信息

Department of Biostatistics, University of Washington, BOX 357232, Seattle, Washington 98195-7232, USA.

出版信息

Nat Rev Genet. 2006 Oct;7(10):771-80. doi: 10.1038/nrg1960.

DOI:10.1038/nrg1960

PMID:16983373

Abstract

Individuals who belong to the same family or the same population are related because of their shared ancestry. Population and quantitative genetics theory is built with parameters that describe relatedness, and the estimation of these parameters from genetic markers enables progress in fields as disparate as plant breeding, human disease gene mapping and forensic science. The large number of multiallelic microsatellite loci and biallelic SNPs that are now available have markedly increased the precision with which relationships can be estimated, although they have also revealed unexpected levels of genomic heterogeneity of relationship measures.

摘要

属于同一家族或同一群体的个体因共同的祖先而具有亲缘关系。群体遗传学和数量遗传学理论是基于描述亲缘关系的参数构建的，从遗传标记估计这些参数有助于植物育种、人类疾病基因定位和法医学等不同领域取得进展。尽管目前可用的大量多等位基因微卫星位点和双等位基因单核苷酸多态性也揭示了亲缘关系测量中意想不到的基因组异质性水平，但它们显著提高了估计亲缘关系的精度。