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Accurate prediction and genome-wide association analysis of digital intramuscular fat content in longissimus muscle of pigs
Animal Genetics ( IF 2.4 ) Pub Date : 2021-07-21 , DOI: 10.1111/age.13121
L Xie 1 , J Qin 1 , L Rao 1 , X Tang 1 , D Cui 1 , L Chen 1 , W Xu 1 , S Xiao 1 , Z Zhang 1 , L Huang 1
Affiliation  

Intramuscular fat (IMF) content is a critical indicator of pork quality that affects directly the purchasing desire of consumers. However, to measure IMF content is both laborious and costly, preventing our understanding of its genetic determinants and improvement. In the present study, we constructed an accurate and fast image acquisition and analysis system, to extract and calculate the digital IMF content, the proportion of fat areas in the image (PFAI) of the longissimus muscle of 1709 animals from multiple pig populations. PFAI was highly significantly correlated with marbling scores (MS; 0.95, r2 = 0.90), and also with IMF contents chemically defined for 80 samples (0.79, r2 = 0.63; more accurate than direct analysis between IMF contents and MS). The processing time for one image is only 2.31 s. Genome-wide association analysis on PFAI for all 1709 animals identified 14 suggestive significant SNPs and 1 genome-wide significant SNP. On MS, we identified nine suggestive significant SNPs, and seven of them were also identified in PFAI. Furthermore, the significance (−log P) values of the seven common SNPs are higher in PFAI than in MS. Novel candidate genes of biological importance for IMF content were also discovered. Our imaging systems developed for prediction of digital IMF content is closer to IMF measured by Soxhlet extraction and slightly more accurate than MS. It can achieve fast and high-throughput IMF phenotype, which can be used in improvement of pork quality.

中文翻译:

猪最长肌数字肌内脂肪含量的准确预测及全基因组关联分析

肌内脂肪(IMF)含量是猪肉质量的重要指标,直接影响消费者的购买欲望。然而,测量 IMF 的内容既费力又费钱,阻碍了我们对其遗传决定因素的理解和改进。在本研究中,我们构建了一个准确、快速的图像采集和分析系统,以提取和计算来自多个猪群的 1709 只动物的最长肌的数字 IMF 含量、图像中脂肪区域的比例 (PFAI)。PFAI 与大理石花纹分数 (MS; 0.95, r 2  = 0.90) 以及化学定义的 80 个样品的 IMF 含量 (0.79, r 2 = 0.63; IMF 内容和 MS 之间的直接分析比直接分析更准确)。一张图像的处理时间仅为 2.31 s。对所有 1709 只动物的 PFAI 进行全基因组关联分析,确定了 14 个具有暗示意义的 SNP 和 1 个全基因组显着 SNP。在 MS 上,我们确定了 9 个具有暗示意义的 SNP,其中 7 个也在 PFAI 中被确定。此外,PFAI 中七个常见 SNP的显着性 (-log P ) 值高于 MS。还发现了对 IMF 含量具有生物学重要性的新候选基因。我们为预测数字 IMF 含量而开发的成像系统更接近于通过索氏提取测量的 IMF,并且比 MS 更准确。可实现快速、高通量的IMF表型,可用于猪肉品质的改善。
更新日期:2021-09-06
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