Evidence map›Paper›PMID 29170422›Full record

ArticleScientific reports2017

Species composition and environmental adaptation of indigenous Chinese cattle.

Yahui Gao, Mathieu Gautier, Xiangdong Ding, Hao Zhang, Yachun Wang, Xi Wang, Md Omar Faruque, Junya Li, Shaohui Ye, Xiao Gou and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–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

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

13 authors.

Yahui GaoNational Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOA, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Mathieu GautierINRA, UMR CBGP (INRA-IRD-Cirad-Montpellier SupAgro), Campus international de Baillarguet, Montferrier-sur-Lez, France.
Xiangdong DingNational Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOA, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Hao ZhangNational Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOA, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Yachun WangNational Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOA, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
Xi WangInstitute of Animal Science and Veterinary Medicine, Shanxi Academy of Agricultural Science, Taiyuan, 030032, China.
Md Omar FaruqueDepartment of Animal Breeding and Genetics, Bangladesh Agricultural University, Mymensingh, 2202, Bangladesh.
Junya LiInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
Shaohui YeCollege of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, China.
Xiao GouCollege of Animal Science and Technology, Yunnan Agricultural University, Kunming, 650201, China.
Jianlin HanCAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China.
Johannes A LenstraFaculty of Veterinary Medicine, Utrecht University, Yalelaan 104, 3584 CM, Utrecht, The Netherlands.ORCID 0000-0003-1745-7739
Yi ZhangNational Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics and Breeding and Reproduction of MOA, College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China. yizhang@cau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Indigenous Chinese cattle combine taurine and indicine origins and occupy a broad range of different environments. By 50 K SNP genotyping we found a discontinuous distribution of taurine and indicine cattle ancestries with extremes of less than 10% indicine cattle in the north and more than 90% in the far south and southwest China. Model-based clustering and f4-statistics indicate introgression of both banteng and gayal into southern Chinese cattle while the sporadic yak influence in cattle in or near Tibetan area validate earlier findings of mitochondrial DNA analysis. Geographic patterns of taurine and indicine mitochondrial and Y-chromosomal DNA diversity largely agree with the autosomal cline. The geographic distribution of the genomic admixture of different bovine species is proposed to be the combined effect of prehistoric immigrations, gene flow, major rivers acting as genetic barriers, local breeding objectives and environmental adaptation. Whole-genome scan for genetic differentiation and association analyses with both environmental and morphological covariables are remarkably consistent with previous studies and identify a number of genes implicated in adaptation, which include TNFRSF19, RFX4, SP4 and several coat color genes. We propose indigenous Chinese cattle as a unique and informative resource for gene-level studies of climate adaptation in mammals.

Indexed as

AllelesAnimalsCattleChinaDNA, MitochondrialGene FrequencyGenetic VariationHaplotypesMicrosatellite RepeatsPolymorphism, Single NucleotideY ChromosomeDNA, Mitochondrial

Identifiers

PMID29170422
PMCPMC5700937

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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.