Evidence map›Paper›PMID 32117428›Full record

ArticleFrontiers in genetics2019

Population Structure, and Selection Signatures Underlying High-Altitude Adaptation Inferred From Genome-Wide Copy Number Variations in Chinese Indigenous Cattle.

Yaran Zhang, Yan Hu, Xiuge Wang, Qiang Jiang, Han Zhao, Jinpeng Wang, Zhihua Ju, Liguo Yang, Yaping Gao, Xiaochao Wei and 3 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

25 citing papers in PubMed, 47 citations in OpenAlex.

  1. Review
  2. Exploring the genetic footprints of high altitude adapted humans and livestock.Mammalian genome : official journal of the International Mammalian Genome Society · 2025
    Review
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  10. Exploring the role of theFrontiers in genetics · 2024
    Article
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  18. Review
  19. Copy Number Variations in theAnimals : an open access journal from MDPI · 2022
    Article
  20. 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

13 authors at 2 institutions in 1 country.

Yaran ZhangDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Yan HuKey Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.
Xiuge WangDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Qiang JiangDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Han ZhaoDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Jinpeng WangDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Zhihua JuDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Liguo YangKey Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.
Yaping GaoDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Xiaochao WeiDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Jiachen BaiDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Yang ZhouKey Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, China.
Jinming HuangDairy Cattle Research Center, Shandong Academy of Agricultural Sciences, Jinan, China.
Shandong Academy of Agricultural Sciences · CNHuazhong Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Copy number variations (CNVs) have been demonstrated as crucial substrates for evolution, adaptation and breed formation. Chinese indigenous cattle breeds exhibit a broad geographical distribution and diverse environmental adaptability. Here, we analyzed the population structure and adaptation to high altitude of Chinese indigenous cattle based on genome-wide CNVs derived from the high-density BovineHD SNP array. We successfully detected the genome-wide CNVs of 318 individuals from 24 Chinese indigenous cattle breeds and 37 yaks as outgroups. A total of 5,818 autosomal CNV regions (683 bp-4,477,860 bp in size), covering ~14.34% of the bovine genome (UMD3.1), were identified, showing abundant CNV resources. Neighbor-joining clustering, principal component analysis (PCA), and population admixture analysis based on these CNVs support that most Chinese cattle breeds are hybrids of

Indexed as

Chinese cattlecopy number variationshigh-altitude adaptationpopulation structureselection signatures

Identifiers

PMID32117428
PMCPMC7033542
OpenAlexW3006074903

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.