Jiao S, Maltecca C, Gray K A, Cassady J P
Department of Animal Science, North Carolina State University, Raleigh 27695.
Department of Animal Science, North Carolina State University, Raleigh 27695
J Anim Sci. 2014 Jul;92(7):2846-60. doi: 10.2527/jas.2014-7337.
Efficient use of feed resources has become a clear challenge for the U.S. pork industry as feed costs continue to be the largest variable expense. The availability of the Illumina Porcine60K BeadChip has greatly facilitated whole-genome association studies to identify chromosomal regions harboring genes influencing those traits. The current study aimed at identifying genomic regions associated with variation in feed efficiency and several production traits in a Duroc terminal sire population, including ADFI, ADG, feed conversion ratio, residual feed intake (RFI), real-time ultrasound back fat thickness (BF), ultrasound muscle depth, intramuscular fat content (IMF), birth weight (BW at birth), and weaning weight (BW at weaning). Single trait association analyses were performed using Bayes B models with 35,140 SNP on 18 autosomes after quality control. Significance of nonoverlapping 1-Mb length windows (n = 2,380) were tested across 3 QTL inference methods: posterior distribution of windows variances from Monte Carlo Markov Chain, naive Bayes factor, and nonparametric bootstrapping. Genes within the informative QTL regions for the traits were annotated. A region ranging from166 to 140 Mb (4-Mb length) on SSC 1, approximately 8 Mb upstream of the MC4R gene, was significantly associated with ADFI, ADG, and BF, where SOCS6 and DOK6 are proposed as the most likely candidate genes. Another region affecting BW at weaning was identified on SSC 4 (84-85 Mb), harboring genes previously found to influence both human and cattle height: PLAG1, CHCHD7, RDHE2 (or SDR16C5), MOS, RPS20, LYN, and PENK. No QTL were identified for RFI, IMF, and BW at birth. In conclusion, we have identified several genomic regions associated with traits affecting nutrient utilization that could be considered for future genomic prediction to improve feed utilization.
由于饲料成本仍是最大的可变支出,有效利用饲料资源已成为美国猪肉行业面临的一项明确挑战。Illumina猪60K SNP芯片的问世极大地推动了全基因组关联研究,以确定含有影响这些性状基因的染色体区域。本研究旨在确定杜洛克终端父本群体中与饲料效率及若干生产性状变异相关的基因组区域,这些性状包括平均日采食量(ADFI)、平均日增重(ADG)、饲料转化率、剩余采食量(RFI)、实时超声背膘厚(BF)、超声肌肉深度、肌内脂肪含量(IMF)、出生体重(出生时BW)和断奶体重(断奶时BW)。在质量控制后,使用贝叶斯B模型对18条常染色体上的35,140个单核苷酸多态性(SNP)进行单性状关联分析。通过3种数量性状位点(QTL)推断方法对2380个不重叠的1兆碱基(Mb)长度窗口(n = 2380)的显著性进行了检验:蒙特卡洛马尔可夫链窗口方差的后验分布、朴素贝叶斯因子和非参数自举法。对性状信息丰富的QTL区域内的基因进行了注释。1号猪染色体(SSC 1)上166至140 Mb(长度4 Mb)的区域,位于黑皮质素4受体(MC4R)基因上游约8 Mb处,与ADFI、ADG和BF显著相关,其中细胞因子信号转导抑制因子6(SOCS6)和对接蛋白6(DOK6)被认为是最有可能的候选基因。在4号猪染色体(SSC 4)上鉴定出另一个影响断奶体重的区域(84 - 85 Mb),该区域含有先前发现影响人类和牛身高的基因:锌指蛋白1(PLAG1)、线粒体载体家族成员25(CHCHD7)、视黄醇脱氢酶/还原酶2(RDHE2,或SDR16C5)、丝裂原活化蛋白激酶(MOS)、核糖体蛋白S20(RPS20)、淋巴细胞特异性蛋白酪氨酸激酶(LYN)和脑啡肽(PENK)。未鉴定出与出生时RFI、IMF和出生体重相关的QTL。总之,我们已经鉴定出几个与影响养分利用性状相关的基因组区域,可考虑将其用于未来的基因组预测,以提高饲料利用率。