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摩拉水牛乳脂率、乳蛋白率、产奶量及泌乳期、泌乳持久力的遗传参数和全基因组关联研究。

Genetic parameters and genome-wide association studies for mozzarella and milk production traits, lactation length, and lactation persistency in Murrah buffaloes.

机构信息

Department of Animal Sciences, Purdue University, West Lafayette, IN 47907; Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil.

Department of Animal Science, College of Agricultural and Veterinary Sciences, São Paulo State University (UNESP), Jaboticabal, 14884-900, SP, Brazil.

出版信息

J Dairy Sci. 2024 Feb;107(2):992-1021. doi: 10.3168/jds.2023-23284. Epub 2023 Sep 18.

Abstract

Genetic and genomic analyses of longitudinal traits related to milk production efficiency are paramount for optimizing water buffaloes breeding schemes. Therefore, this study aimed to (1) compare single-trait random regression models under a single-step genomic BLUP setting based on alternative covariance functions (i.e., Wood, Wilmink, and Ali and Schaeffer) to describe milk (MY), fat (FY), protein (PY), and mozzarella (MZY) yields, fat-to-protein ratio (FPR), somatic cell score (SCS), lactation length (LL), and lactation persistency (LP) in Murrah dairy buffaloes (Bubalus bubalis); (2) combine the best functions for each trait under a multiple-trait framework; (3) estimate time-dependent SNP effects for all the studied longitudinal traits; and (4) identify the most likely candidate genes associated with the traits. A total of 323,140 test-day records from the first lactation of 4,588 Murrah buffaloes were made available for the study. The model included the average curve of the population nested within herd-year-season of calving, systematic effects of number of milkings per day, and age at first calving as linear and quadratic covariates, and additive genetic, permanent environment, and residual as random effects. The Wood model had the best goodness of fit based on the deviance information criterion and posterior model probabilities for all traits. Moderate heritabilities were estimated over time for most traits (0.30 ± 0.02 for MY; 0.26 ± 0.03 for FY; 0.45 ± 0.04 for PY; 0.28 ± 0.05 for MZY; 0.13 ± 0.02 for FPR; and 0.15 ± 0.03 for SCS). The heritability estimates for LP ranged from 0.38 ± 0.02 to 0.65 ± 0.03 depending on the trait definition used. Similarly, heritabilities estimated for LL ranged from 0.10 ± 0.01 to 0.14 ± 0.03. The genetic correlation estimates across days in milk (DIM) for all traits ranged from -0.06 (186-215 DIM for MY-SCS) to 0.78 (66-95 DIM for PY-MZY). The SNP effects calculated for the random regression model coefficients were used to estimate the SNP effects throughout the lactation curve (from 5 to 305 d). Numerous relevant genomic regions and candidate genes were identified for all traits, confirming their polygenic nature. The candidate genes identified contribute to a better understanding of the genetic background of milk-related traits in Murrah buffaloes and reinforce the value of incorporating genomic information in their breeding programs.

摘要

对与牛奶生产效率相关的纵向性状进行遗传和基因组分析对于优化水牛养殖计划至关重要。因此,本研究旨在:(1) 比较基于替代协方差函数(即 Wood、Wilmink、Ali 和 Schaeffer)的单步基因组 BLUP 设定下的单一性状随机回归模型,以描述牛奶 (MY)、脂肪 (FY)、蛋白质 (PY) 和马苏里拉 (MZY) 产量、脂肪-蛋白质比 (FPR)、体细胞评分 (SCS)、泌乳长度 (LL) 和泌乳持续时间 (LP) ;(2) 在多性状框架下结合每个性状的最佳函数;(3) 估计所有研究的纵向性状的时变 SNP 效应;(4) 鉴定与性状相关的最可能候选基因。本研究共使用了 4588 头摩拉水牛首胎泌乳期的 323140 个测试日记录。模型包括嵌套在 herd-year-season of calving 内的群体平均曲线、每日挤奶次数的系统效应以及初配年龄的线性和二次协变量,以及加性遗传、永久环境和残差作为随机效应。Wood 模型基于偏差信息准则和后验模型概率,在所有性状上均具有最佳的拟合优度。大多数性状的遗传力随时间呈中度变化(0.30 ± 0.02 for MY;0.26 ± 0.03 for FY;0.45 ± 0.04 for PY;0.28 ± 0.05 for MZY;0.13 ± 0.02 for FPR;0.15 ± 0.03 for SCS)。LP 的遗传力估计值因性状定义而异,范围从 0.38 ± 0.02 到 0.65 ± 0.03。类似地,LL 的遗传力估计值范围从 0.10 ± 0.01 到 0.14 ± 0.03。所有性状的跨泌乳天数 (DIM) 的遗传相关估计值范围从 -0.06(186-215 DIM 时 MY-SCS)到 0.78(66-95 DIM 时 PY-MZY)。随机回归模型系数的 SNP 效应计算用于估计整个泌乳曲线(从 5 天到 305 天)的 SNP 效应。为所有性状鉴定了许多相关的基因组区域和候选基因,证实了它们的多基因性质。鉴定的候选基因有助于更好地理解摩拉水牛与牛奶相关性状的遗传背景,并加强了在其育种计划中纳入基因组信息的价值。

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