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Transcriptomic and metabolomic dissection of skeletal muscle of crossbred Chongming white goats with different meat production performance

文献类型： 外文期刊

作者： Lin, Yuexia 1 ; Sun, Lingwei 1 ; Lv, Yuhua 1 ; Liao, Rongrong 1 ; Zhang, Keqing 2 ; Zhou, Jinyong 2 ; Zhang, Shushan 1 ; Xu, Jiehuan 1 ; He, Mengqian 1 ; Wu, Caifeng 1 ; Zhang, Defu 1 ; Shen, Xiaohui 4 ; Dai, Jianjun 1 ; Gao, Jun 1 ;

作者机构： 1.Shanghai Acad Agr Sci, Inst Anim Husb & Vet Sci, Shanghai 201106, Peoples R China

2.Shanghai Municipal Key Lab Agrigenet & Breeding, Shanghai 201106, Peoples R China

3.Minist Agr & Rural Affairs, Key Lab Livestock & Poultry Resources Evaluat & Ut, Shanghai 201106, Peoples R China

4.Shanghai Acad Agr Sci, Shanghai 201106, Peoples R China

关键词： RNA-seq; Differentially expressed gene; Liquid chromatography-mass spectrometry; Goat meat development

期刊名称：BMC GENOMICS （ 影响因子：4.4； 五年影响因子：4.7 ）

ISSN： 1471-2164

年卷期： 2024 年 25 卷 1 期

页码：

收录情况： SCI

摘要： Background The transcriptome and metabolome dissection of the skeletal muscle of high- and low- growing individuals from a crossbred population of the indigenous Chongming white goat and the Boer goat were performed to discover the potential functional differentially expressed genes (DEGs) and differential expression metabolites (DEMs).Results A total of 2812 DEGs were detected in 6 groups at three time stages (3,6,12 Month) in skeletal muscle using the RNA-seq method. A DEGs set containing seven muscle function related genes (TNNT1, TNNC1, TNNI1, MYBPC2, MYL2, MHY7, and CSRP3) was discovered, and their expression tended to increase as goat muscle development progressed. Seven DEGs (TNNT1, FABP3, TPM3, DES, PPP1R27, RCAN1, LMOD2) in the skeletal muscle of goats in the fast-growing and slow-growing groups was verified their expression difference by reverse transcription-quantitative polymerase chain reaction. Further, through the Liquid chromatography-mass spectrometry (LC-MS) approach, a total of 183 DEMs in various groups of the muscle samples and these DEMs such as Queuine and Keto-PGF1 alpha, which demonstrated different abundance between the goat fast-growing group and slow-growing group. Through weighted correlation network analysis (WGCNA), the study correlated the DEGs with the DEMs and identified 4 DEGs modules associated with 18 metabolites.Conclusion This study benefits to dissection candidate genes and regulatory networks related to goat meat production performance, and the joint analysis of transcriptomic and metabolomic data provided insights into the study of goat muscle development.

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