Whole Genome Association Studies of Residual Feed Intake and Related Traits in the Pig.
Whole Genome Association Studies of Residual Feed Intake and Related Traits in the Pig.
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DOI：
10.1371/journal.pone.0061756
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发表时间：
2013
期刊：
影响因子：
3.7
通讯作者：
Rothschild MF
中科院分区：
文献类型：
--
作者：
Onteru SK;Gorbach DM;Young JM;Garrick DJ;Dekkers JC;Rothschild MF
剩余采食量 (RFI) 是饲料效率的衡量标准，是观察到的采食量与根据生长和维持预测的预期饲料需求之间的差异。低 RFI 的猪可以降低饲料成本，但不会影响其生长。与 RFI 相关的基因或遗传标记的鉴定将有助于在动物早期进行标记辅助选择，从而提高饲料效率。使用 Illumina PorcineSNP60 BeadChip 对来自不同选择的 ISU-RFI 品系的 1,400 头猪进行了 RFI、平均日采食量 (ADFI)、平均日增重 (ADG)、背膘 (BF) 和腰肌面积 (LMA) 的全基因组关联研究 (WGAS)。应用各种统计方法来查找与性状相关的 SNP 和基因组区域，包括使用 GenSel 软件的贝叶斯方法，以及频率论方法，例如品系之间的等位基因频率差异、使用 PLINK 软件的单个 SNP 和单倍型分析。单一 SNP 和单倍型分析显示在基因组控制和 FDR 后没有显着关联（LMA 除外）。贝叶斯分析发现，每个性状至少有 2 个关联，假阳性概率为 0.5。在第 8 代，RFI 选择系的主要差异在于调节胰岛素释放和瘦素功能的基因 (<0.05 Mb) 附近的 SNP 等位基因频率。贝叶斯方法确定了包含胰岛素释放基因（例如 GLP1R、CDKAL、SGMS1）的基因组区域与 RFI 和 ADFI 的关联、能量稳态区域（例如 MC4R、PGM1、GPR81）和肌肉生长相关基因（例如 TGFB1）与 ADG 的关联、以及脂肪代谢基因（例如 ACOXL、AEBP1）与 BF 的关联。具体来说，鉴定出SSC7上LMA与骨骼肌生成基因（例如KLHL31）高度显着相关的QTL，用于后续精细作图。在将其纳入标记辅助选择程序之前，确定了与 RFI 相关性状相关的重要基因组区域，用于未来的验证研究。
Residual feed intake (RFI), a measure of feed efficiency, is the difference between observed feed intake and the expected feed requirement predicted from growth and maintenance. Pigs with low RFI have reduced feed costs without compromising their growth. Identification of genes or genetic markers associated with RFI will be useful for marker-assisted selection at an early age of animals with improved feed efficiency. Whole genome association studies (WGAS) for RFI, average daily feed intake (ADFI), average daily gain (ADG), back fat (BF) and loin muscle area (LMA) were performed on 1,400 pigs from the divergently selected ISU-RFI lines, using the Illumina PorcineSNP60 BeadChip. Various statistical methods were applied to find SNPs and genomic regions associated with the traits, including a Bayesian approach using GenSel software, and frequentist approaches such as allele frequency differences between lines, single SNP and haplotype analyses using PLINK software. Single SNP and haplotype analyses showed no significant associations (except for LMA) after genomic control and FDR. Bayesian analyses found at least 2 associations for each trait at a false positive probability of 0.5. At generation 8, the RFI selection lines mainly differed in allele frequencies for SNPs near (<0.05 Mb) genes that regulate insulin release and leptin functions. The Bayesian approach identified associations of genomic regions containing insulin release genes (e.g., GLP1R, CDKAL, SGMS1) with RFI and ADFI, of regions with energy homeostasis (e.g., MC4R, PGM1, GPR81) and muscle growth related genes (e.g., TGFB1) with ADG, and of fat metabolism genes (e.g., ACOXL, AEBP1) with BF. Specifically, a very highly significantly associated QTL for LMA on SSC7 with skeletal myogenesis genes (e.g., KLHL31) was identified for subsequent fine mapping. Important genomic regions associated with RFI related traits were identified for future validation studies prior to their incorporation in marker-assisted selection programs.
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影响因子：
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通讯作者：
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