Evidence map›Paper›PMID 39695159›Full record

ArticleScientific data2024

Gene expression profiles in specific skeletal muscles and meat quality characteristics of sheep and goats.

Dong Leng, Zhiying Huang, Xue Bai, Tao Wang, Yi Zhang, Weihua Chang, Wei Zhao, Diyan Li, Binlong Chen

Abstract readDataset
In one paragraph

Article in Scientific data, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
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  5. Animals : an open access journal from MDPI · 2025
    Article
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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

9 authors.

Dong Leng *College of Animal Science, Xichang University, Xichang, 615000, China.
Zhiying Huang *School of Pharmacy, Chengdu University, Chengdu, 610106, China.
Xue BaiSchool of Pharmacy, Chengdu University, Chengdu, 610106, China.
Tao WangSchool of Pharmacy, Chengdu University, Chengdu, 610106, China.
Yi ZhangCollege of Animal Science, Xichang University, Xichang, 615000, China.
Weihua ChangCollege of Animal Science, Xichang University, Xichang, 615000, China.
Wei ZhaoCollege of Animal Science, Xichang University, Xichang, 615000, China.
Diyan LiSchool of Pharmacy, Chengdu University, Chengdu, 610106, China. lidiyan@cdu.edu.cn.ORCID 0000-0001-7490-3550
Binlong ChenCollege of Animal Science, Xichang University, Xichang, 615000, China. binlong2369@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lamb meat is highly valued across various cultures and regions due to its unique flavor and nutritional benefits. As the primary component of edible meat, skeletal muscle holds significant economic value and research importance. However, previous studies have largely focused on a limited array of muscle groups, overlooking the differences between various types. Therefore, a comprehensive transcriptomic and meat quality analysis of the skeletal muscles of sheep and goats is essential to improve meat production traits. In this study, we performed RNA sequencing and assessed meat quality in 10 different skeletal muscles from 2-year-old Liangshan Black sheep and Meigu Black goats. We generated 803.16 Gb of high-quality bulk RNA sequencing data with six biological replicates for each muscle. This dataset provides a deeper understanding of the gene expression profiles and meat quality characteristics of different muscle tissues in sheep and goats, laying the foundation for broader comparative research.

Indexed as

GoatsMeatMuscle, SkeletalTranscriptomeAnimalsSequence Analysis, RNASheep

Identifiers

PMID39695159
PMCPMC11655546

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.