Back to Search
Start Over
Muscle transcriptome analysis reveal candidate genes and pathways related to fat and lipid metabolism in Yunling cattle.
- Source :
-
Animal Biotechnology . 2023, Vol. 34 Issue 4, p1022-1029. 8p. - Publication Year :
- 2023
-
Abstract
- Yunling cattle (YL) is a recently developed beef breed harboring a quarter of Yunnan ancestral cattle genome, spanning over past 30 years. Compared with Diqing cattle (DQ), a Yunnan native cattle breed, YL presents various advantages, including rapid growth and exquisite meat quality. However, the molecular mechanisms underlying these phenotypic differences are not clearly understood. To further identify the candidate genes responsible for the quality of the meat in the muscle, longissimus dorsi (LD) muscle was used for RNA-Seq analysis. A total of 508 differentially expressed genes (DEGs) were identified in YL (adjusted p-value <0.01 and log2FoldChange >1), of which 243 were up-regulated and 265 were down-regulated. Functional association analysis showed that the identified DEGs mainly enriched the lipid and fat metabolism pathways. Moreover, it was also observed that several fat-related genes were differentially expressed in both cattle breeds, including three up-regulated genes (MOGAT1, ACSM3, PLPP2) and two down-regulated genes (ADIG, GPAT3). In addition, alternative splice analysis was also performed revealing an important 9–11 exon skipping variation of GPAM gene (crucial for beef marbling) in YL, which is three times higher than that in DQ, suggesting that this variation might have played the central role in the 'snow beef' effect in YL. We believe that our results will help in understanding the mechanism of muscle development and promote the further breeding programs in YL cattle. [ABSTRACT FROM AUTHOR]
- Subjects :
- *LIPID metabolism
*CATTLE breeds
*ALTERNATIVE RNA splicing
*CATTLE
*GENES
*BREEDING
Subjects
Details
- Language :
- English
- ISSN :
- 10495398
- Volume :
- 34
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Animal Biotechnology
- Publication Type :
- Academic Journal
- Accession number :
- 169807942
- Full Text :
- https://doi.org/10.1080/10495398.2021.2009846