Evidence map›Paper›PMID 29899660›Full record

ArticleEvolutionary bioinformatics online2018

Detecting the Population Structure and Scanning for Signatures of Selection in Horses (

Cheng Zhang, Pan Ni, Hafiz Ishfaq Ahmad, M Gemingguli, A Baizilaitibei, D Gulibaheti, Yaping Fang, Haiyang Wang, Akhtar Rasool Asif, Changyi Xiao and 5 more

Open access · goldAbstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.2field-weighted citation impact, top 12% of its field
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

15 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Article
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  4. Genetic Diversity of KazakhstaniVeterinary sciences · 2023
    Article
  5. Genome-wide survey on three local horse populations with a focus on runs of homozygosity pattern.Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie · 2022
    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

15 authors at 2 institutions in 1 country.

Cheng ZhangKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Pan NiKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Hafiz Ishfaq AhmadKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
M GemingguliCollege of Animal Science, Tarim University, Alar, China.
A BaizilaitibeiCollege of Animal Science, Tarim University, Alar, China.
D GulibahetiCollege of Animal Science, Tarim University, Alar, China.
Yaping FangHubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China.
Haiyang WangKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Akhtar Rasool AsifKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Changyi XiaoHubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China.
Jianhai ChenKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Yunlong MaKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Xiangdong LiuKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Xiaoyong DuKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Shuhong ZhaoKey Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Education, College of Animal Sciences & Technology, Huazhong Agricultural University, Wuhan, People's Republic of China.
Huazhong Agricultural University · CNTarim University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Animal domestication gives rise to gradual changes at the genomic level through selection in populations. Selective sweeps have been traced in the genomes of many animal species, including humans, cattle, and dogs. However, little is known regarding positional candidate genes and genomic regions that exhibit signatures of selection in domestic horses. In addition, an understanding of the genetic processes underlying horse domestication, especially the origin of Chinese native populations, is still lacking. In our study, we generated whole genome sequences from 4 Chinese native horses and combined them with 48 publicly available full genome sequences, from which 15 341 213 high-quality unique single-nucleotide polymorphism variants were identified. Kazakh and Lichuan horses are 2 typical Asian native breeds that were formed in Kazakh or Northwest China and South China, respectively. We detected 1390 loss-of-function (LoF) variants in protein-coding genes, and gene ontology (GO) enrichment analysis revealed that some LoF-affected genes were overrepresented in GO terms related to the immune response. Bayesian clustering, distance analysis, and principal component analysis demonstrated that the population structure of these breeds largely reflected weak geographic patterns. Kazakh and Lichuan horses were assigned to the same lineage with other Asian native breeds, in agreement with previous studies on the genetic origin of Chinese domestic horses. We applied the composite likelihood ratio method to scan for genomic regions showing signals of recent selection in the horse genome. A total of 1052 genomic windows of 10 kB, corresponding to 933 distinct core regions, significantly exceeded neutral simulations. The GO enrichment analysis revealed that the genes under selective sweeps were overrepresented with GO terms, including "negative regulation of canonical Wnt signaling pathway," "muscle contraction," and "axon guidance." Frequent exercise training in domestic horses may have resulted in changes in the expression of genes related to metabolism, muscle structure, and the nervous system.

Indexed as

horsepopulation genetic structureselective sweepsingle-nucleotide polymorphisms

Identifiers

PMID29899660
PMCPMC5990873
OpenAlexW2807544153

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

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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.