Evidence map›Paper›PMID 37510213›Full record

ArticleGenes2023

Identifying Genetic Architecture of Carcass and Meat Quality Traits in a Ningxiang Indigenous Pig Population.

Shishu Yin, Gang Song, Ning Gao, Hu Gao, Qinghua Zeng, Peng Lu, Qin Zhang, Kang Xu, Jun He

Abstract read
In one paragraph

Article in Genes, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. NCells · 2024
    Article
  5. Article
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.

Shishu YinCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.
Gang SongCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.
Ning GaoCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.
Hu GaoCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.ORCID 0000-0003-2402-9978
Qinghua ZengCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.
Peng LuCenter of Ningxiang Animal Husbandry and Fishery Affairs, Ningxiang 410625, China.
Qin ZhangCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.
Kang XuLaboratory of Animal Nutrition Physiology and Metabolism, The Chinese Academy of Sciences, The Institute of Subtropical Agriculture, Changsha 410128, China.
Jun HeCollege of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ningxiang pig is a breed renowned for its exceptional meat quality, but it possesses suboptimal carcass traits. To elucidate the genetic architecture of meat quality and carcass traits in Ningxiang pigs, we assessed heritability and executed a genome-wide association study (GWAS) concerning carcass length, backfat thickness, meat color parameters (L.LD, a.LD, b.LD), and pH at two postmortem intervals (45 min and 24 h) within a Ningxiang pig population. Heritability estimates ranged from moderate to high (0.30~0.80) for carcass traits and from low to high (0.11~0.48) for meat quality traits. We identified 21 significant SNPs, the majority of which were situated within previously documented QTL regions. Furthermore, the

Indexed as

Genome-Wide Association StudyMeatAnimalsGenes, cdcGenotypePhenotypeSwinecarcass lengthgenetic parametergenome-wide association studymeat color

Identifiers

PMID37510213
PMCPMC10378861

What OpenQuestion holds

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LicenceCC BY
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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.