Yao Junpeng, Bottema Cynthia D K, Khatkar Mehar Singh
School of Animal and Veterinary Sciences, The University of Adelaide, Roseworthy Campus, Roseworthy, South Australia, 5371, Australia.
BMC Genomics. 2024 Dec 24;25(1):1242. doi: 10.1186/s12864-024-11159-4.
Fat traits in cattle are considered important due to their contribution to beef eating quality and carcass economic value. Discovering the genes controlling fat traits in cattle will enable better selection of these traits, but identifying these genes in individual experiments has proven difficult. Compared to individual experiments, meta-analyses allow greater statistical power for detecting quantitative trait loci and identifying genes that influence single and multiple economically important fat traits.
This meta-analysis study focussed on fat traits related to the major adipose depots in cattle (namely, carcass fat, intramuscular fat, internal fat, intermuscular fat, and subcutaneous fat) and was conducted using data from the Animal Quantitative Trait Loci (QTL) database. There were more Meta-QTL regions for intramuscular fat and subcutaneous fat (n = 158 and n = 55 regions, respectively) and far fewer for carcass fat and internal fat (n = 2 regions each). There were no Meta-QTL regions found for intermuscular fat. Of these 216 Meta-QTL regions, only 16 regions overlapped and affected two or more fat depots. The number of genes found for the fat depots was reflected in the size and number of the Meta-QTL regions (n = 20, 84, 1336 and 3853 genes for the carcass, internal, subcutaneous and intramuscular fat, respectively). The identification of these QTL allowed a more refined search for candidate genes. For example, the 232 genes in the Meta-QTL regions for carcass fat on BTA2, for intramuscular fat on BTA12, and the overlapping Meta-QTL regions on BTA2, BTA5, and BTA6 were readily screened, and 26 candidate genes were nominated based on their physiological roles using the GeneCards and DAVID databases.
The number of Meta-QTL regions for the various fat depots was relative to the number of associations in the database. However, the scarcity of overlapping Meta-QTL regions suggests that pleiotropic gene variants, which control multiple fat depots in cattle, are rare. The identification of candidate genes in the Meta-QTL regions will improve our knowledge of the genes with regulatory functions in adipose metabolism affecting meat quality and carcass economic value.
牛的脂肪性状因其对牛肉食用品质和胴体经济价值的贡献而被认为很重要。发现控制牛脂肪性状的基因将有助于更好地选择这些性状，但在单个实验中识别这些基因已被证明很困难。与单个实验相比，荟萃分析在检测数量性状基因座和识别影响单个和多个经济上重要的脂肪性状的基因方面具有更大的统计效力。
这项荟萃分析研究聚焦于与牛主要脂肪库相关的脂肪性状（即胴体脂肪、肌内脂肪、内脏脂肪、肌间脂肪和皮下脂肪），并使用来自动物数量性状基因座（QTL）数据库的数据进行。肌内脂肪和皮下脂肪的元QTL区域更多（分别为n = 158和n = 55个区域），而胴体脂肪和内脏脂肪的元QTL区域则少得多（各为n = 2个区域）。未发现肌间脂肪的元QTL区域。在这216个元QTL区域中，只有16个区域重叠并影响两个或更多脂肪库。为脂肪库发现的基因数量反映在元QTL区域的大小和数量上（胴体、内脏、皮下和肌内脂肪分别为n = 20、84、1336和3853个基因）。这些QTL的识别使得对候选基因的搜索更加精确。例如，很容易筛选出BTA2上胴体脂肪元QTL区域中的232个基因、BTA12上肌内脂肪元QTL区域中的基因以及BTA2、BTA5和BTA6上重叠的元QTL区域中的基因，并使用GeneCards和DAVID数据库根据其生理作用提名了26个候选基因。
各种脂肪库的元QTL区域数量与数据库中的关联数量相关。然而，重叠的元QTL区域稀少表明，控制牛多个脂肪库的多效基因变异很少见。在元QTL区域中识别候选基因将增进我们对在脂肪代谢中具有调节功能、影响肉质和胴体经济价值的基因的了解。
