Laodim Thawee, Elzo Mauricio A, Koonawootrittriron Skorn, Suwanasopee Thanathip, Jattawa Danai
Department of Animal Science, Kasetsart University, Bangkok 10900, Thailand.
Department of Animal Sciences, University of Florida, Gainesville, FL 32611-0910, USA.
Asian-Australas J Anim Sci. 2019 Apr;32(4):508-518. doi: 10.5713/ajas.18.0382. Epub 2018 Jul 26.
This research aimed to determine biological pathways and protein-protein interaction (PPI) networks for 305-d milk yield (MY), 305-d fat yield (FY), and age at first calving (AFC) in the Thai multibreed dairy population.
Genotypic information contained 75,776 imputed and actual single nucleotide polymorphisms (SNP) from 2,661 animals. Single-step genomic best linear unbiased predictions were utilized to estimate SNP genetic variances for MY, FY, and AFC. Fixed effects included herd-year-season, breed regression and heterosis regression effects. Random effects were animal additive genetic and residual. Individual SNP explaining at least 0.001% of the genetic variance for each trait were used to identify nearby genes in the National Center for Biotechnology Information database. Pathway enrichment analysis was performed. The PPI of genes were identified and visualized of the PPI network.
Identified genes were involved in 16 enriched pathways related to MY, FY, and AFC. Most genes had two or more connections with other genes in the PPI network. Genes associated with MY, FY, and AFC based on the biological pathways and PPI were primarily involved in cellular processes. The percent of the genetic variance explained by genes in enriched pathways (303) was 2.63% for MY, 2.59% for FY, and 2.49% for AFC. Genes in the PPI network (265) explained 2.28% of the genetic variance for MY, 2.26% for FY, and 2.12% for AFC.
These sets of SNP associated with genes in the set enriched pathways and the PPI network could be used as genomic selection targets in the Thai multibreed dairy population. This study should be continued both in this and other populations subject to a variety of environmental conditions because predicted SNP values will likely differ across populations subject to different environmental conditions and changes over time.
本研究旨在确定泰国多品种奶牛群体中305天产奶量(MY)、305天脂肪产量(FY)和初产年龄(AFC)的生物学途径和蛋白质-蛋白质相互作用(PPI)网络。
基因型信息包含来自2661头动物的75776个推算和实际单核苷酸多态性(SNP)。采用单步基因组最佳线性无偏预测来估计MY、FY和AFC的SNP遗传方差。固定效应包括畜群-年份-季节、品种回归和杂种优势回归效应。随机效应为动物加性遗传效应和残差效应。用于识别每个性状至少解释0.001%遗传方差的单个SNP,以在国家生物技术信息中心数据库中鉴定附近的基因。进行了途径富集分析。鉴定了基因的PPI并可视化了PPI网络。
鉴定出的基因涉及与MY、FY和AFC相关的16条富集途径。大多数基因在PPI网络中与其他基因有两个或更多的连接。基于生物学途径和PPI与MY、FY和AFC相关的基因主要参与细胞过程。富集途径(303个)中的基因解释的遗传方差百分比,MY为2.63%,FY为2.59%,AFC为2.49%。PPI网络(265个)中的基因解释的遗传方差百分比,MY为2.28%,FY为2.26%,AFC为2.12%。
这些与富集途径和PPI网络中的基因相关的SNP集可作为泰国多品种奶牛群体的基因组选择目标。由于预测的SNP值可能因受不同环境条件影响的群体而异且随时间变化,因此本研究应在该群体以及其他受各种环境条件影响的群体中继续进行。