Identification of Key Pathways Associated With Residual Feed Intake of Beef Cattle Based on Whole Blood Transcriptome Data Analyzed Using Gene Set Enrichment Analysis

利用基因集富集分析法分析全血转录组数据,识别与肉牛剩余饲料摄入量相关的关键途径

阅读:11
作者:Godstime A Taiwo, Modoluwamu Idowu, James Denvir, Andres Pech Cervantes, Ibukun M Ogunade

Abstract

We applied whole blood transcriptome analysis and gene set enrichment analysis to identify pathways associated with divergent selection for low or high RFI in beef cattle. A group of 56 crossbred beef steers (average BW = 261 ± 18.5 kg) were adapted to a high-forage total mixed ration in a confinement dry lot equipped with GrowSafe intake nodes for period of 49 d to determine their residual feed intake (RFI). After RFI determination, whole blood samples were collected from beef steers with the lowest RFI (most efficient; low-RFI; n = 8) and highest RFI (least efficient; high-RFI; n = 8). Prior to RNA extraction, whole blood samples collected were composited for each steer. Sequencing was performed on an Illumina NextSeq2000 equipped with a P3 flow. Gene set enrichment analysis (GSEA) was used to analyze differentially expressed gene sets and pathways between the two groups of steers. Results of GSEA revealed pathways associated with metabolism of proteins, cellular responses to external stimuli, stress, and heat stress were differentially inhibited (false discovery rate (FDR) < 0.05) in high-RFI compared to low-RFI beef cattle, while pathways associated with binding and uptake of ligands by scavenger receptors, scavenging of heme from plasma, and erythrocytes release/take up oxygen were differentially enriched (FDR < 0.05) in high-RFI, relative to low-RFI beef cattle. Taken together, our results revealed that beef steers divergently selected for low or high RFI revealed differential expressions of genes related to protein metabolism and stress responsiveness.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。