Identification of key genes affecting porcine fat deposition based on co-expression network analysis of weighted genes.
Fat deposition
Pigs
RNA-seq
WGCNA
Journal
Journal of animal science and biotechnology
ISSN: 1674-9782
Titre abrégé: J Anim Sci Biotechnol
Pays: England
ID NLM: 101581293
Informations de publication
Date de publication:
20 Aug 2021
20 Aug 2021
Historique:
received:
14
01
2021
accepted:
01
07
2021
entrez:
22
8
2021
pubmed:
23
8
2021
medline:
23
8
2021
Statut:
epublish
Résumé
Fat deposition is an important economic consideration in pig production. The amount of fat deposition in pigs seriously affects production efficiency, quality, and reproductive performance, while also affecting consumers' choice of pork. Weighted gene co-expression network analysis (WGCNA) is effective in pig genetic studies. Therefore, this study aimed to identify modules that co-express genes associated with fat deposition in pigs (Songliao black and Landrace breeds) with extreme levels of backfat (high and low) and to identify the core genes in each of these modules. We used RNA sequences generated in different pig tissues to construct a gene expression matrix consisting of 12,862 genes from 36 samples. Eleven co-expression modules were identified using WGCNA and the number of genes in these modules ranged from 39 to 3,363. Four co-expression modules were significantly correlated with backfat thickness. A total of 16 genes (RAD9A, IGF2R, SCAP, TCAP, SMYD1, PFKM, DGAT1, GPS2, IGF1, MAPK8, FABP, FABP5, LEPR, UCP3, APOF, and FASN) were associated with fat deposition. RAD9A, TCAP, SMYD1, PFKM, GPS2, and APOF were the key genes in the four modules based on the degree of gene connectivity. Combining these results with those from differential gene analysis, SMYD1 and PFKM were proposed as strong candidate genes for body size traits. This study explored the key genes that regulate porcine fat deposition and lays the foundation for further research into the molecular regulatory mechanisms underlying porcine fat deposition.
Sections du résumé
BACKGROUND
BACKGROUND
Fat deposition is an important economic consideration in pig production. The amount of fat deposition in pigs seriously affects production efficiency, quality, and reproductive performance, while also affecting consumers' choice of pork. Weighted gene co-expression network analysis (WGCNA) is effective in pig genetic studies. Therefore, this study aimed to identify modules that co-express genes associated with fat deposition in pigs (Songliao black and Landrace breeds) with extreme levels of backfat (high and low) and to identify the core genes in each of these modules.
RESULTS
RESULTS
We used RNA sequences generated in different pig tissues to construct a gene expression matrix consisting of 12,862 genes from 36 samples. Eleven co-expression modules were identified using WGCNA and the number of genes in these modules ranged from 39 to 3,363. Four co-expression modules were significantly correlated with backfat thickness. A total of 16 genes (RAD9A, IGF2R, SCAP, TCAP, SMYD1, PFKM, DGAT1, GPS2, IGF1, MAPK8, FABP, FABP5, LEPR, UCP3, APOF, and FASN) were associated with fat deposition.
CONCLUSIONS
CONCLUSIONS
RAD9A, TCAP, SMYD1, PFKM, GPS2, and APOF were the key genes in the four modules based on the degree of gene connectivity. Combining these results with those from differential gene analysis, SMYD1 and PFKM were proposed as strong candidate genes for body size traits. This study explored the key genes that regulate porcine fat deposition and lays the foundation for further research into the molecular regulatory mechanisms underlying porcine fat deposition.
Identifiants
pubmed: 34419151
doi: 10.1186/s40104-021-00616-9
pii: 10.1186/s40104-021-00616-9
pmc: PMC8379819
doi:
Types de publication
Journal Article
Langues
eng
Pagination
100Subventions
Organisme : the Beijing Municipal Education Commission Science and Technology Program General Project
ID : KM201910020010
Organisme : Beijing Innovation Consortium of Agriculture Research System
ID : BAIC02-2021
Organisme : the National Key Research and Development Project
ID : 2019YFE0106800
Organisme : China Agriculture Research System
ID : CARS-35
Organisme : National Key R&D Program of China
ID : 2018YFD0501000
Informations de copyright
© 2021. The Author(s).
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