Application of mathematical expectation (ME) strategy for detecting low frequency mutations: An example for evaluating 14-bp insertion/deletion (indel) within the bovine PRNP gene

应用数学期望(ME)策略检测低频突变:以牛PRNP基因内14 bp插入/缺失(indel)的评估为例

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Abstract

The detection method based on the mathematical expectation (ME) strategy is fast and accuracy for low frequency mutation screening in large samples. Previous studies have found that the 14-bp insertion/deletion (indel) variants of the 3' untranslated region (3' UTR) within bovine PRNP gene have been characterized with low frequency (≤5%) in global breeds outside China, which has not been determined in Chinese cattle breeds yet. Therefore, this study aimed to identify the 14-bp indel within PRNP gene in 5 major Chinese indigenous cattle breeds and to evaluate its associations with phenotypic traits. It was the first time to use ME strategy to detect low frequency indel polymorphisms and found that minor allele frequency was 0.038 (Qinchuan), 0.033 (Xianan), 0.013 (Nanyang), 0.003 (Jiaxian), and zero (Ji'an), respectively. Compared to the traditional detection method by which the sample was screened one by one, the reaction time by using the ME method was decreased 62.5%, 64.9%, 77.6%, 88.9% and 66.4%, respectively. In addition, the 14-bp indel was significantly associated with the growth traits in 2 cattle breeds, with the body length of Qinchuan cattle as well as the body weight and waistline of Xianan cattle. Our results have uncovered that the method based on ME strategy is rapid, reliable, and cost-effective for detecting the low frequency mutation as well as our findings provide a potential valuable theoretical basis for the marker-assisted selection (MAS) in beef cattle.

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