对巴西本地适应性牛种的重测序发现了肉脂肪酸谱候选基因和转录因子的变异。

IF 1.9 3区 农林科学 Q2 AGRICULTURE, DAIRY & ANIMAL SCIENCE Journal of Animal Breeding and Genetics Pub Date : 2024-04-30 DOI:10.1111/jbg.12869
João Inácio Gomes Vieira, Larissa Graciano Braga, Tatiane C. S. Chud, Pablo Henrique Ferreira, Simone Eliza Facioni Guimarães, Marta Fonseca Martins, João Cláudio do Carmo Panetto, Marco Antonio Machado, Danielly Beraldo dos Santos Silva, Cristina Moreira Bonafé, Ana Fabrícia Braga Magalhães, Marcos Vinícius G. B. da Silva, Lucas Lima Verardo
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引用次数: 0

摘要

近年来,市场对肉质健康、成本效益和环境可持续性的需求推动肉牛业发生了转变。因此,在肉牛育种计划中,人们越来越关注肉的脂肪酸含量和功能。此外,深入了解影响与脂肪酸谱相关的不同表型表达的生物学机制也至关重要。在本研究中,我们旨在鉴定肉牛品种基因组、转录组和蛋白质组研究中描述的与脂肪酸谱相关的候选基因中的单核苷酸变异(SNV)和插入/缺失(InDels)DNA变异。利用巴西本地适应性牛种(即 Caracu 和 Pantaneiro)的全基因组重测序数据,我们确定了与 23,947 个基因相关的 SNV 和 InDels。从中,我们确定了 318 个与含有变异的脂肪酸谱相关的候选基因。随后,我们只选择了在启动子、5' UTR 和编码区存在 SNV 和 InDels 的基因。通过基因-生物过程网络,大约 19 个基因被突出显示出来。此外,考虑到所研究的性状和文献综述,我们选择了主要的转录因子(TF)。通过基因-转录因子网络的功能分析,我们确定了 30 个最有可能与牛的肉脂肪酸谱有关的候选基因。LIPE、MFSD2A和SREBF1基因因其生物学重要性而在网络中得到强调。对这些基因的进一步分析发现,在卡拉库(Caracu)和潘塔内罗(Pantaneiro)序列的启动子区域发现了 15 个新变体。基因网络有助于更好地了解基因和TF的功能,从而鉴定出可能与牛肉脂肪酸谱候选基因表达有关的变异。
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Resequencing of Brazilian locally adapted cattle breeds revealed variants in candidate genes and transcription factors for meat fatty acid profile

The beef cattle industry has experienced a shift driven by a market demand for healthier meat, cost efficiency and environmental sustainability in recent years. Consequently, there has been a growing focus on the fatty acids content and functions of meat in cattle breeding programmes. Besides, a deeper understanding of the biological mechanisms influencing the expression of different phenotypes related to fatty acid profiles is crucial. In this study, we aimed to identify Single-Nucleotide Variants (SNV) and Insertion/Deletion (InDels) DNA variants in candidate genes related to fatty acid profiles described in genomic, transcriptomic and proteomic studies conducted in beef cattle breeds. Utilizing whole-genome re-sequencing data from Brazilian locally adapted bovine breeds, namely Caracu and Pantaneiro, we identified SNVs and InDels associated with 23,947 genes. From these, we identified 318 candidate genes related to fatty acid profiles that contain variants. Subsequently, we select only genes with SNVs and InDels in their promoter, 5′ UTR and coding region. Through the gene–biological process network, approximately 19 genes were highlighted. Furthermore, considering the studied trait and a literature review, we selected the main transcription factors (TF). Functional analysis via gene–TF network allowed us to identify the 30 most likely candidate genes for meat fatty acid profile in cattle. LIPE, MFSD2A and SREBF1 genes were highlighted in networks due to their biological importance. Further dissection of these genes revealed 15 new variants found in promoter regions of Caracu and Pantaneiro sequences. The gene networks facilitated a better functional understanding of genes and TF, enabling the identification of variants potentially related to the expression of candidate genes for meat fatty acid profiles in cattle.

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来源期刊
Journal of Animal Breeding and Genetics
Journal of Animal Breeding and Genetics 农林科学-奶制品与动物科学
CiteScore
5.20
自引率
3.80%
发文量
58
审稿时长
12-24 weeks
期刊介绍: The Journal of Animal Breeding and Genetics publishes original articles by international scientists on genomic selection, and any other topic related to breeding programmes, selection, quantitative genetic, genomics, diversity and evolution of domestic animals. Researchers, teachers, and the animal breeding industry will find the reports of interest. Book reviews appear in many issues.
期刊最新文献
Issue Information Influence of variance component estimates on genomic predictions for growth and reproductive-related traits in Nellore cattle. Genomic selection strategies for the German Merino sheep breeding programme - A simulation study. Correction to: Rahbar et al., 2023. Defining desired genetic gains for Pacific white shrimp (Litopeneaus vannamei) breeding objectives using participatory approaches. Journal of Animal Breeding and Genetics. 2024;141:390-402. Combining genomics and semen microbiome increases the accuracy of predicting bull prolificacy.
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