Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq

摘要: Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for affects many underlying molecular networks and physiological traits. This study describes differences between steer progeny two influential Angus bulls with divergent predictions residual intake (RFI). Eight each sire were phenotyped growth from 8 mo. age (average BW 254 kg, a mean difference groups 4.8 kg) until slaughter at 14–16 534 group 28.8 kg). Terminal samples pituitary gland, skeletal muscle, liver, adipose, duodenum collected transcriptome sequencing. Gene expression derived using partial correlation information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) transcription factors (TF), genes associated RFI genome-wide association (GWAS). Relative to high sire, low had -0.56 kg/d finishing period (P = 0.05), -1.08 ratio 0.01), +3.3 kg^0.75 metabolic mid-weight (MMW; P 0.04), +28.8 kg final body weight -12.9 bunk visits per day 0.02) +0.60 min/visit duration +0.0045 carcass gravity (weight air/weight air—weight water, predictor fat content; 0.03). RNA-seq identified 633 DE among 17,016 genes. PCIT analysis >115,000 significant co-expression correlations 25 TF hubs, i.e. controllers clusters DE, TS, GWAS SNP Pathway suggests bull possess heightened gut inflammation reduced deposition. multi-omics shows how breeding values impact other traits gene networks.