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驱动西班牙阿尔萨夫绵羊产奶和奶酪制作特性遗传变异的基因网络。

Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep.

机构信息

Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Campus de Vegazana s/n, 24071 León, Spain.

CSIRO Agriculture and Food, Queensland Bioscience Precinct, 306 Carmody Rd., St Lucia, Brisbane, Queensland 4067, Australia.

出版信息

Genes (Basel). 2020 Jun 27;11(7):715. doi: 10.3390/genes11070715.

Abstract

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual's genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

摘要

大多数绵羊产的奶用于生产高质量的奶酪。因此,与乳凝特性和奶酪产量相关的特性对西班牙乳制品行业具有重要的经济意义。本研究旨在鉴定与 14 种奶和奶酪生产特性相关的候选基因及其调节剂,并开发一种可用于预测个体奶酪生产效率遗传潜力的低密度标记物面板。在这项研究中,我们将经典的全基因组关联研究 (GWAS) 与逐步回归方法和多效性分析相结合,以确定位于潜在候选基因置信区间内的变异体的最佳组合,这些变异体可能解释了与奶和奶酪生产特性相关的最大遗传方差。使用通过逐步多元回归方法构建的基因组关系矩阵创建了与奶和奶酪生产特性相关的两个基因网络。这些网络中的几个共同关联基因涉及到先前与奶合成和奶酪生产效率相关的生物过程。本研究中应用的方法使得能够选择一个由 374 个位于显示对奶合成和奶酪生产效率有潜在影响的基因周围的变体组成的共同关联网络。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e919/7397207/8712892f3d71/genes-11-00715-g001.jpg

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