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PSIV-37 Development of a genomic selection strategy to include meat quality traits in turkeys (Meleagris gallopavo).

机译:PSIV-37开发了一种基因组选择策略将火鸡的肉质性状纳入其中(Meleagris gallopavo)。

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摘要

Genetic improvement of meat quality traits is challenging, as the phenotype is measured on an animal that can no longer be a selection candidate. Information from relatives, such as siblings, must therefore be used to estimate the breeding value of selection candidates. The objective of this research is to adapt meat quality traits developed in other livestock species, such as chicken and pigs, and apply them to a genomic selection program in turkeys. The project will consist of three main activities. The first activity consists of identifying meat quality traits, such as the rate of pH decline, ultimate pH, colour, and shear force. Body conformation will also be measured. Once identified and clearly defined, important traits will be measured on a large number of turkeys in the processing plant and the laboratory. In the second activity, genetic parameters will be estimated for the collected traits. Genetic correlations between the identified traits and other economically important traits, such as body weight and feed efficiency, will be estimated. In the final activity, genome-wide association studies and functional analyses will be performed using information from a 65K SNP array. In total, approximately 3,000 birds will be phenotyped for meat quality traits, providing a reference population for SNP effect estimation. By defining relevant meat quality traits, estimating their genetic variances and correlations to production traits, and identifying genomic regions associated with these traits, the groundwork for implementing genomic selection for meat quality will be laid.
机译:肉质性状的遗传改良具有挑战性,因为表型是在不能再选择的动物身上测得的。因此,必须使用来自亲戚(例如兄弟姐妹)的信息来估计候选候选人的育种价值。这项研究的目的是适应在其他牲畜物种(例如鸡和猪)中发展的肉质性状,并将其应用于火鸡的基因组选择程序。该项目将包括三个主要活动。第一项活动包括识别肉质特征,例如pH下降速率,最终pH,颜色和剪切力。身体形态也将被测量。一旦确定并明确定义,将在加工厂和实验室中的大量火鸡上测量重要性状。在第二项活动中,将为收集的性状估计遗传参数。估计的性状与其他经济上重要的性状(例如体重和饲料效率)之间的遗传相关性将得到估算。在最后的活动中,将使用来自65K SNP阵列的信息进行全基因组关联研究和功能分析。总共将对约3,000只禽的肉品质性状进行表型分析,为SNP效应估计提供参考种群。通过定义相关的肉质性状,估计其遗传变异和与生产性状的相关性,并确定与这些性状相关的基因组区域,将为实施肉质基因组选择奠定基础。

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