Welzenbach Julia, Neuhoff Christiane, Heidt Hanna, Cinar Mehmet Ulas, Looft Christian, Schellander Karl, Tholen Ernst, Große-Brinkhaus Christine
Institute of Animal Science, University of Bonn, Endenicher Allee 15, 53115 Bonn, Germany.
Institute for Organic Agriculture Luxembourg, Association sans but lucratif (A.S.B.L.), 13 Rue Gabriel Lippmann, L-5365 Munsbach, Luxembourg.
Int J Mol Sci. 2016 Aug 30;17(9):1426. doi: 10.3390/ijms17091426.
The aim of this study was to integrate multi omics data to characterize underlying functional pathways and candidate genes for drip loss in pigs. The consideration of different omics levels allows elucidating the black box of phenotype expression. Metabolite and protein profiling was applied in Musculus longissimus dorsi samples of 97 Duroc × Pietrain pigs. In total, 126 and 35 annotated metabolites and proteins were quantified, respectively. In addition, all animals were genotyped with the porcine 60 k Illumina beadchip. An enrichment analysis resulted in 10 pathways, amongst others, sphingolipid metabolism and glycolysis/gluconeogenesis, with significant influence on drip loss. Drip loss and 22 metabolic components were analyzed as intermediate phenotypes within a genome-wide association study (GWAS). We detected significantly associated genetic markers and candidate genes for drip loss and for most of the metabolic components. On chromosome 18, a region with promising candidate genes was identified based on SNPs associated with drip loss, the protein "phosphoglycerate mutase 2" and the metabolite glycine. We hypothesize that association studies based on intermediate phenotypes are able to provide comprehensive insights in the genetic variation of genes directly involved in the metabolism of performance traits. In this way, the analyses contribute to identify reliable candidate genes.
本研究的目的是整合多组学数据，以表征猪滴水损失的潜在功能途径和候选基因。考虑不同的组学水平有助于阐明表型表达的黑箱。对97头杜洛克×皮特兰猪的背最长肌样本进行了代谢物和蛋白质谱分析。总共分别对126种和35种注释的代谢物和蛋白质进行了定量。此外，所有动物都用猪60k Illumina芯片进行了基因分型。富集分析产生了10条途径，其中包括鞘脂代谢和糖酵解/糖异生，对滴水损失有显著影响。在全基因组关联研究（GWAS）中，将滴水损失和22种代谢成分作为中间表型进行了分析。我们检测到了与滴水损失以及大多数代谢成分显著相关的遗传标记和候选基因。在18号染色体上，基于与滴水损失、蛋白质“磷酸甘油酸变位酶2”和代谢物甘氨酸相关的单核苷酸多态性，鉴定出了一个有前景的候选基因区域。我们假设基于中间表型的关联研究能够为直接参与生产性能性状代谢的基因的遗传变异提供全面的见解。通过这种方式，这些分析有助于识别可靠的候选基因。
