Ontology highlight
ABSTRACT:
PROVIDER: PRJNA779020 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR16930883_1.fastq.gz | Fastqsanger.gz | |||
| SRR16930883_2.fastq.gz | Fastqsanger.gz | |||
| SRR16930884_1.fastq.gz | Fastqsanger.gz | |||
| SRR16930884_2.fastq.gz | Fastqsanger.gz | |||
| SRR16930885_1.fastq.gz | Fastqsanger.gz |
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Project description:The selection of cattle with high feed efficiency is of paramount importance with regard to reducing feed costs in the beef industry. Global gene expression patterns in metabolically important tissues can be used to identify genes that are potentially involved in regulating feed efficiency. We identified 5 genes (p<0.001;FDR <0.1) to be differentially expressed in skeletal skeletal muscle between high and low residual feed intake heifers with all 5 transcripts being upregulated in the low residual feed intake phenotype. Among these differentially expressed genes, all transcripts were related to oxidative phosphorylation and mitochondrial homeostasis. A total of 11 genes (p<0.001;FDR <0.1) were differentially expressed in hepatic tissue tissue between high and low residual feed intake bulls with 8 transcripts being upregulated and 3 being downregulated in the low residual feed intake phenotype. These differentially expressed genes were related to oxidative response, protein mediation and cell signalling. Pathway analysis on the RNAseq data indicates a relationship between oxidative phosphorylation and residual feed intake in skeletal muscle and aldosterone signalling and NRF2 mediated oxidative stress in hepatic tissue.
2021-05-05 | GSE112793 | GEO
Project description:The biological mechanisms associated with the residual feed intake in ruminants have been harnessed immensely via transcriptome analysis of liver and ruminal epithelium, however, this concept has not been fully explored using whole blood. We applied whole blood transcriptome analysis and gene set enrichment analysis to identify key pathways associated with divergent selection for low or high RFI in beef cattle. A group of 56 crossbred beef steers (average BW = 261.3 ± 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, weekly whole blood samples were collected three times 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.
2022-04-07 | GSE198068 | GEO
Project description:Identification of key pathways associated with residual feed intake of beef cattle
| PRJNA813568 | ENA
Project description:MicroRNAs (miRNAs) are short non-coding RNAs that post-transcriptionally regulate expression of mRNAs in many biological pathways. Here we report comprehensive miRNAs profiles by next-gen deep sequencing in Angus cattle divergently selected for residual feed intake (RFI) and identify miRNAs related to feed efficiency in beef cattle Results: Two microRNA libraries were constructed from pooled RNA extracted from livers of low and high RFI cattle, and sequenced by Illumina genome analyser. In total, 23,628,103 high quality short sequence reads were obtained and more than half of these reads were matched to the bovine genome (UMD 3.1). We identified 305 known bovine miRNAs (miRBase v.19). Bta-miR-143, bta-miR-30, bta-miR-122, bta-miR-378 and bta-let-7 were the top five most abundant miRNAs families expressed in liver, representing more than 63% of expressed miRNAs. We also identified 52 homologous miRNAs and 10 novel putative bovine-specific miRNAs, based on precursor sequence and the secondary structure and utilizing the miRBase (version 19). We compared the miRNAs profile between high and low RFI animals and ranked the most differentially expressed bovine known miRNAs. Bovine miR-143 was the most abundant miRNA in the bovine liver and comprised 20% of total expressed mapped miRNAs. The most highly expressed miRNA in liver of mice and humans, miR-122, was the third most abundant in our cattle liver samples. We also identified 10 putative novel bovine-specific miRNA candidates. Differentially expressed miRNAs between high and low RFI cattle were identified with 18 miRNAs being up-regulated and 7 other miRNAs down-regulated in low RFI cattle Conclusions: Our study has identified comprehensive miRNAs expressed in bovine liver. Some of the expressed miRNAs are novel in cattle. The differentially expressed miRNAs between high and low RFI give some insights into liver miRNAs regulating physiological pathways underlying residual feed intake in bovine
2015-11-27 | GSE63691 | GEO
Project description:An accumulation of over a decade of research in cattle has shown that genetic selection for decreased residual feed intake (RFI), defined as the difference between an animal’s actual feed intake and its expected feed intake, is a viable option for improving feed efficiency and reducing the feed requirements of herds, thereby improving the profitability of cattle producers. Hormonal regulation is one of the most important factors in feed intake. To determine the relationship between hormones and feed efficiency, we performed gene expression profiling of hormonal regulation in whole blood of Chinese Holstein cattle with low and high RFI coefficients. 857 differential expression genes (from 24683 genes) were found. Among these, 415 genes were up-regulated and 442 genes were down-regulated in the low RFI group. The gene ontology (GO) search revealed 6 significant terms and 64 genes associated with hormonal regulation, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) selected the adipocytokine signaling pathway, insulin signaling pathway. In conclusion, the study indicated that the molecular expression of genes associated with hormonal regulation differs in dairy cows, depending on their RFI coefficients, and that these differences may be related to the molecular regulation of the leptin-NPY and insulin signaling pathways.
2015-03-24 | GSE67176 | GEO
Project description:Transcriptome Profiling of the Rumen Epithelial Tissues of Beef Cattle Differing in Residual Feed Intake
| PRJNA307579 | ENA
Project description:The aim of this study was to measure the effect of contrasting breed and dietary source on the skeletal muscle miRNA profile of beef cattle divergent for feed efficiency (RFI). Charolais (n=90) and Holstein-Fresian (N=77) steers) were offered two consecutive diets; namely a zero-grazed grass diet followed by a high concentrate diet. Dietary intakes were recorded for all steers throughout each dietary phase and residual feed intake values dertermined for each steer. At the end of each dietary phase the most efficient (Low-RFI; n=8) and least efficient (High-RFI; n=8) steers were selected across each breed for longissmus dorsi biopsy collection. RNA was isolated from all muscle tissue samples and subsequently used for small RNA sequencing. Ten miRNA were differentially expressed between the steers divergent for RFI across each diet and breed contrast. Biological pathway analyssi revealed enrichment of pathways related to both metabolic and growth processes.
2024-09-13 | GSE269311 | GEO