Bioinformatics analysis of candidate genes for milk production and littersize in goat

Authors

1 Master student, Department of Animal Science, Faculty of Animal Science and Fisheries, Sari University of Agricultural Sciences and Natural Resources.

2 Associate Professor, Department of Animal Science, Faculty of Animal Science and Fisheries, Sari University of Agricultural Sciences and Natural Resources,

3 Professor, Department of Animal Science, Faculty of Animal Science and Fisheries, Sari Agricultural Sciences and Natural Resources University, Sari, Iran

4 Researcher, Center for Immunity and Immunotherapy, Seattle Children's Research Institute, Seattle, USA

Abstract

Background and Objectives: Milk production and reproductive traits are important economic traits in goat. The different approaches including candidate gene mapping and genome-wide association studies (GWAS) are now implemented in goats in an attempt to identify the molecular mechanisms affecting these economically important traits. The gene ontology (GO) analysis gives a controlled vocabulary for describing attributes of genes and gene products. Kyoto Encyclopedia of Genes and Genomes (KEGG) provides the mythology for the careful examination of gene functions in respect of networks of genes and molecules. Gene network analysis can also identify paths and processes shared by candidate genes. The purpose of the present study was to bioinformatics analysis (GO, path enrichment, and network analysis of the effects of protein-protein interaction) of genes effective in litter size and milk production in goat.
Materials and Methods: Candidate genes associated with studied traits were retrieved from literature review, review of candidate gene studies, GWAS and NCBI database. GO analysis and enrichment analysis of the signaling pathways of KEGG were performed using online database of G: Profiler. The String database was used to infer the network of protein-protein interactions (PPI) and the selection of performance module. Cytoscape software was used to draw the resultant networks of protein-protein interactions. Finally, cytoHubba was used to identify Hub genes.
Results: GO analysis for litter size showed that, for molecular function the candidates genes enriched in signaling receptor binding, signaling receptor active activity, hormone activity, protein binding and transforming growth factor beta receptor activity. The effect of the transforming growth factor β (TGF-β) family on fertility and reproduction, embryonic development, organogenesis, and uterine growth and function is remarkable in a wide range of organisms. In mammals, even early stages of reproductive development, including male and female germline specification, are controlled by TGF-β-related proteins. Hormone binding play an important role in fertility and reproduction. Sex hormone-binding globulin (SHBG), specifically bound to the biologically active androgens and estrogens that are key regulators of the reproductive organs as well as other sex-differentiated tissues such as muscle, adipose tissue, and bone. KEGG analysis also identified some signaling pathways including ، PI3K-Akt signaling pathway، TGF-beta signaling pathway and ovarian steroidogenesis which are significantly associated with litter size. GO analysis for 33 candidate genes related to milk production traits identified only one GO category for biological process namely linoleic acid metabolic process.
Conclusion: In this study, we identified several significant biological and signaling pathways that can be used to better understand the biological processes associated with litter size and milk production in goats.

Keywords

Main Subjects

References

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Journal of Ruminant Research
Volume 12, Issue 1
April 2024
Pages 101-118

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