Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors.
Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors.
复制标题
DOI：
10.1186/1297-9686-45-42
复制
发表时间：
2013-10-29
期刊：
影响因子：
--
通讯作者：
Curik I
中科院分区：
文献类型：
--
作者：
Ferenčaković M;Sölkner J;Curik I
纯合性片段是长的、不间断的纯合基因型片段，其使得能够可靠地估计近交水平（即，同源性），基于高通量、基于芯片的单核苷酸多态性（SNP）基因型。虽然纯合性运行的理论定义很简单，但它们的经验鉴定取决于用于获得数据的SNP芯片的类型和许多因素，包括允许解释基因分型错误的杂合调用的数量。我们分析了SNP芯片密度和基因分型错误如何影响估计的纯合性的基础上运行的纯合性在三个牛种群，使用基因型数据从SNP芯片与777 972 SNP和50 k芯片。来自50 k芯片的数据导致高估了短于4 Mb的纯合性运行的数量，因为该分析不能识别存在于更密集芯片上的杂合SNP。相反，来自更密集芯片的数据导致低估了大于8 Mb的纯合性运行的数量，除非在纯合性运行内允许存在少量杂合SNP基因型。我们已经表明，SNP芯片密度和基因分型错误引入模式的偏见估计的纯合性的基础上运行的纯合性。具有50 000至60 000个标记的SNP芯片经常可用于家畜物种，并且它们的信息导致从大于4 Mb的纯合性运行保守预测纯合性。不允许杂合SNP基因型存在于纯合性运行中，如已经提倡的用于人类群体，对于牲畜群体是不够的，因为它们具有高得多的自体接合性水平，因此具有更长的纯合性运行。当允许少量杂合调用时，当前软件不区分这些调用相邻并因此指示运行的实际中断的情况与它们分散在纯合区段的长度上的情况。本文中使用的简单图形测试是一种当前但繁琐的解决方案。
Runs of homozygosity are long, uninterrupted stretches of homozygous genotypes that enable reliable estimation of levels of inbreeding (i.e., autozygosity) based on high-throughput, chip-based single nucleotide polymorphism (SNP) genotypes. While the theoretical definition of runs of homozygosity is straightforward, their empirical identification depends on the type of SNP chip used to obtain the data and on a number of factors, including the number of heterozygous calls allowed to account for genotyping errors. We analyzed how SNP chip density and genotyping errors affect estimates of autozygosity based on runs of homozygosity in three cattle populations, using genotype data from an SNP chip with 777 972 SNPs and a 50 k chip. Data from the 50 k chip led to overestimation of the number of runs of homozygosity that are shorter than 4 Mb, since the analysis could not identify heterozygous SNPs that were present on the denser chip. Conversely, data from the denser chip led to underestimation of the number of runs of homozygosity that were longer than 8 Mb, unless the presence of a small number of heterozygous SNP genotypes was allowed within a run of homozygosity. We have shown that SNP chip density and genotyping errors introduce patterns of bias in the estimation of autozygosity based on runs of homozygosity. SNP chips with 50 000 to 60 000 markers are frequently available for livestock species and their information leads to a conservative prediction of autozygosity from runs of homozygosity longer than 4 Mb. Not allowing heterozygous SNP genotypes to be present in a homozygosity run, as has been advocated for human populations, is not adequate for livestock populations because they have much higher levels of autozygosity and therefore longer runs of homozygosity. When allowing a small number of heterozygous calls, current software does not differentiate between situations where these calls are adjacent and therefore indicative of an actual break of the run versus those where they are scattered across the length of the homozygous segment. Simple graphical tests that are used in this paper are a current, yet tedious solution.