Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2024 Mar 4;25(1):234.
doi: 10.1186/s12864-024-10151-2.

An across breed, diet and tissue analysis reveals the transcription factor NR1H3 as a key mediator of residual feed intake in beef cattle

Affiliations

An across breed, diet and tissue analysis reveals the transcription factor NR1H3 as a key mediator of residual feed intake in beef cattle

Kate Keogh et al. BMC Genomics. .

Abstract

Background: Provision of feed is a major determinant of overall profitability in beef production systems, accounting for up to 75% of the variable costs. Thus, improving cattle feed efficiency, by way of determining the underlying genomic control and subsequently selecting for feed efficient cattle, provides a method through which feed input costs may be reduced. The objective of this study was to undertake gene co-expression network analysis using RNA-Sequence data generated from Longissimus dorsi and liver tissue samples collected from steers of two contrasting breeds (Charolais and Holstein-Friesian) divergent for residual feed intake (RFI), across two consecutive distinct dietary phases (zero-grazed grass and high-concentrate). Categories including differentially expressed genes (DEGs) based on the contrasts of RFI phenotype, breed and dietary source, as well as key transcription factors and proteins secreted in plasma were utilised as nodes of the gene co-expression network.

Results: Of the 2,929 DEGs within the network analysis, 1,604 were reported to have statistically significant correlations (≥ 0.80), resulting in a total of 43,876 significant connections between genes. Pathway analysis of clusters of co-expressed genes revealed enrichment of processes related to lipid metabolism (fatty acid biosynthesis, fatty acid β-oxidation, cholesterol biosynthesis), immune function, (complement cascade, coagulation system, acute phase response signalling), and energy production (oxidative phosphorylation, mitochondrial L-carnitine shuttle pathway) based on genes related to RFI, breed and dietary source contrasts.

Conclusions: Although similar biological processes were evident across the three factors examined, no one gene node was evident across RFI, breed and diet contrasts in both liver and muscle tissues. However within the liver tissue, the IRX4, NR1H3, HOXA13 and ZNF648 gene nodes, which all encode transcription factors displayed significant connections across the RFI, diet and breed comparisons, indicating a role for these transcription factors towards the RFI phenotype irrespective of diet and breed. Moreover, the NR1H3 gene encodes a protein secreted into plasma from the hepatocytes of the liver, highlighting the potential for this gene to be explored as a robust biomarker for the RFI trait in beef cattle.

Keywords: Beef cattle; Feed efficiency; Gene co-expression network analysis.

PubMed Disclaimer

Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Venn diagrams showing DEGs for each RFI, diet and breed contrast in (a) liver and (b) muscle. Within the liver tissue two genes, SPP1 and ABHD2 were differentially expressed across RFI, breed and diet contrasts, whilst BDH1, CDK5RAP2 and METTL21C were differentially expressed across the three contrasts tested in the skeletal muscle tissue
Fig. 2
Fig. 2
Gene co-expression network constructed using PCIT algorithm on 1,604 selected genes displaying significant correlations ( 0.8), with a total of 43,876 connections presented. Gene nodes were based on DEGs pertaining to contrasts of High- versus Low-RFI, Charolais versus Holstein-Friesian and HC diet versus ZG diet. Legend: RL = RFI in liver contrast; RM = RFI in muscle contrast; DL = diet contrast in liver; DM = diet contrast in muscle; BL = breed contrast in liver and; BM = breed contrast in muscle tissue
Fig. 3
Fig. 3
Venn diagrams showing significant connections for each RFI, diet and breed contrast in (a) liver and (b) muscle. Within the liver tissue three connections were common across the RFI, breed and diet contrasts examined, whilst no commonality was detected within the skeletal muscle tissue
Fig. 4
Fig. 4
Biological interactions of the four genes (HOXA13, IRX3, NR1H3 and ZNF648) identified within the RFI, breed and diet contrasts within the liver tissue. The interactions between the four genes examined were retrieved from the GeneMANIA database [29]
Fig. 5
Fig. 5
Network depicting the interaction between the most interconnected genes within each of the six contrasts of diet, RFI and breed across liver and muscle tissues undertaken. Most interconnected genes are highlighted in yellow and include ARID4B in the liver-RFI contrast; CPNE3 in the muscle-RFI contrast; ENSBTAG00000049594 in the liver-diet contrast; MAFG in the muscle-diet contrast and; GIMAP7 and ACSL5 in liver and muscle, respectively for the breed contrasts. Legend: RL = RFI in liver contrast; ML = RFI in muscle contrast; DL = diet contrast in liver; DM = diet contrast in muscle; BL = breed contrast in liver and; BM = breed contrast in muscle tissue
Fig. 6
Fig. 6
Overview of experimental design

Similar articles

Cited by

References

    1. Gill M, Gibson JP, Lee MRF. Livestock production evolving to contribute to sustainable societies. Animal. 2018;12:1696–8. doi: 10.1017/S1751731118000861. - DOI - PubMed
    1. Kenny DA, Fitzsimons C, Waters SM, McGee M. Improving feed efficiency of beef cattle; current state of the art and future challenges. Animal. 2018;12:1815–26. doi: 10.1017/S1751731118000976. - DOI - PubMed
    1. Bes A, Noziere P, Renand G, Rochette Y, Guarnido-Lopez P, Cantalapiedra-Hijar G, Martin C, et al. Individual methane emissions (and other gas flows) are repeatable and their relationships with feed efficiency are similar across two contrasting diets in growing bulls. Animal. 2022;16:100583. doi: 10.1016/j.animal.2022.100583. - DOI - PubMed
    1. Berry DP, Crowley JJ. Cell biology symposium: genetics of feed efficiency in dairy and beef cattle. J Anim Sci. 2013;91:1594–1613. - PubMed
    1. Fitzsimons C, McGee M, Keogh K, Waters SM, Kenny DA. Molecular physiology of feed efficiency in beef cattle in Biology of Domestic Animals (ed. Hill, R.) CRC Press. 2017;180–231.

LinkOut - more resources