畜禽群体中基于SNP标记的亲子鉴定及亲本推断方法

Parentage identification and paternity inference based on SNP markers in livestock population

利用双亲高密度SNP标记信息,在畜禽群体中进行亲子鉴定及亲本推断新方法的计算机程序开发,并使用模拟的600 000个SNP标记对该程序进行测试。结果表明:对系谱正确性进行鉴定时,SNP标记数大于100即可达到100%的亲子鉴定准确率;对错误的系谱关系进行潜在亲子关系推断时,SNP标记数大于300可保证100%的推断准确率。标记平均MAF较低会降低亲子推断准确率。在程序运行效率方面,当使用50 000的SNP标记对1 000条错误率为10%的系谱进行亲子鉴定和推断时,共耗时332.87s,且计算耗时与标记数及个体数呈线性变化。本研究基于孟德尔遗传原理,设计并开发了基于双亲及后代基因型的亲子鉴定及亲本推断程序,该方法运行速度快,操作简单,准确性高,值得在畜禽群体基因组相关研究方面进行推广应用。

A computer program was developed for parentage identification and paternity inference based on the single nucleotide polymorphisms(SNPs)of parents and offspring from known livestock population.Furthermore,the approach was tested with a simulated population with 600 000 SNP markers.Results showed that at least 100 SNPs are needed for correct parentage identification and a minimum of 300 SNPs for correct paternity inference.However,using markers with low average minor allele frequency can decrease the accuracy of paternity inference.The time for parentage identification of 1 000 pedigrees with 10%errors genotyped with 50 000 SNPs was 332.87 s,which showed linearly relationship with the number of markers and individuals.In this study,a computer program was developed for parentage identification and paternity inference according to Mendel's law and testified with markers from known genotypes of parents and their offspring.The program runs fast and simply with higher accuracy,and hence can be implemented potentially in relevant studies of genomics in livestock population.