Evidence map›Paper›PMID 38704563›Full record

ArticleBMC genomics2024

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

Yuexia Lin, Lingwei Sun, Yuhua Lv, Rongrong Liao, Keqing Zhang, Jinyong Zhou, Shushan Zhang, Jiehuan Xu, Mengqian He, Caifeng Wu and 4 more

Abstract read
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Yuexia Lin *Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Lingwei Sun *Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Yuhua LvInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Rongrong LiaoInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Keqing ZhangShanghai Municipal Key Laboratory of Agri-Genetics and Breeding, Shanghai, 201106, China.
Jinyong ZhouShanghai Municipal Key Laboratory of Agri-Genetics and Breeding, Shanghai, 201106, China.
Shushan ZhangInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Jiehuan XuInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Mengqian HeInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Caifeng WuInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Defu ZhangInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China.
Xiaohui ShenShanghai Academy of Agricultural Sciences, Shanghai, 201106, China. shenxiaohui@saas.sh.cn.
Jianjun DaiInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China. daijianjun@saas.sh.cn.
Jun GaoInstitute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, 201106, China. gaojun@saas.sh.cn.

Funding

National Nature Fund Youth Fund of China 32202640Shanghai Academy of Agricultural Sciences Run Up Program ZP22171Shanghai Agriculture Applied Technology Development Program, China 2021-02-08-00-12-F00785Shanghai Science and Technology Innovation Action Plan 22140900400
6 · The paper itself

Abstract

backgroundThe 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).

resultsA 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-PGF1α, 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.

conclusionThis 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.

Indexed as

GoatsMeatMuscle, SkeletalTranscriptomeAnimalsGene Expression ProfilingMetabolomeMetabolomicsDifferentially expressed geneGoat meat developmentLiquid chromatography-mass spectrometryRNA-seq

Identifiers

PMID38704563
PMCPMC11069289

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.