Evidence map›Paper›PMID 41028795›Full record

ArticleScientific reports2025

Decoding the beef cattle genome through whole-genome sequencing reveals the genetic basis of carcass and meat quality traits.

Hojjat Asadollahpour Nanaie, Jing Tian, Guoquan Sun, Xiao Wang, Meng Zhao, Hui Li, Baolige Dalai, Yuan Li, Tingyue Wang, Lu Chen and 6 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Association ofAnimals : an open access journal from MDPI · 2026
    Article
  2. Article
  3. Article
  4. Review
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

16 authors.

Hojjat Asadollahpour Nanaie *Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Jing Tian *Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Guoquan SunInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Xiao WangInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Meng ZhaoInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Hui LiInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Baolige DalaiInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Yuan LiInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Tingyue WangInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Lu ChenInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Yin SaiInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Wenhua GuoInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China.
Guanglei WangInner Mongolia Chifeng Boyuan Cattle Breeding Co., Ltd, Hohhot, China.
Lu CheChifeng Nongmu Jishu Tuiguang Zhongxin, Chifeng, China.
Jianghong WuCollege of Animal Science and Technology, Inner Mongolia Minzu University, Hohhot, China. wujianghonglong@126.com.
Rugang TianInner Mongolia Academy of Agricultural & Animal Husbandry Sciences, Hohhot, 010031, China. tiannky@163.com.

Funding

Scientific and Technological Innovation 2030--Major Project 2023ZD0404803-01
6 · The paper itself

Abstract

Meat quality and carcass traits are the most economically important traits affecting the value and the quality characteristics of the animal at slaughter. In this study, we analyzed the genomes of 295 domestic cattle from 20 global breeds using next-generation sequencing to identify signatures of positive selection associated with meat production and quality traits. The results of population genetic analysis revealed genetic differentiation among worldwide cattle groups. We observed clustering of samples in agreement with their geographic origins and production characteristics. We further observed noticeable genetic variety between cattle groups from different geographical regions. Generally, the lowest genetic diversity was determined for commercial cattle breeds, while the highest genetic diversity was found in African local cattle breeds. Our search for putative selective genomic regions in beef cattle populations revealed several candidate genes such as BMP2, EGR1, MAGEL2, U6, TMEM201, ELK3 and 5S_rRNA that were previously explored to be associated with carcass traits and meat quality in beef cattle. The enriched pathways and candidate genes discovered in this study could supply a basis for future improvement through the use of whole-genome technologies and selective breeding.

Indexed as

GenomeMeatQuantitative Trait, HeritableRed MeatWhole Genome SequencingAnimalsBreedingCattleGenetic VariationPolymorphism, Single NucleotideBeef cattleCandidate genesCarcass traitsMeat qualityWhole-genome sequencing

Identifiers

PMID41028795
PMCPMC12485205

What OpenQuestion holds

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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.