Evidence map›Paper›PMID 32554187›Full record

ArticleiScience2020

Microevolutionary Dynamics of Chicken Genomes under Divergent Selection for Adiposity.

Hui Zhang, Qiqi Liang, Ning Wang, Qigui Wang, Li Leng, Jie Mao, Yuxiang Wang, Shouzhi Wang, Jiyang Zhang, Hao Liang and 14 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2020. 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. Article
  2. 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

24 authors.

Hui ZhangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Qiqi LiangNovogene Bioinformatics Institute, Beijing 10089, P. R. China.
Ning WangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Qigui WangChongqing Academy of Animal Science, Chongqing 402460, P. R. China.
Li LengKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Jie MaoNovogene Bioinformatics Institute, Beijing 10089, P. R. China.
Yuxiang WangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Shouzhi WangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Jiyang ZhangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Hao LiangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Xun ZhouNovogene Bioinformatics Institute, Beijing 10089, P. R. China.
Yumao LiKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Zhiping CaoKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Peng LuanKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Zhipeng WangKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Hui YuanKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
Zhiquan WangDepartment of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, AB T6G 2C8, Canada.
Xuming ZhouKey Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, P. R. China.
Susan J LamontDepartment of Animal Science, Iowa State University, Ames 50011, USA.
Yang DaDepartment of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA.
Ruiqiang LiNovogene Bioinformatics Institute, Beijing 10089, P. R. China.
Shilin TianNovogene Bioinformatics Institute, Beijing 10089, P. R. China. Electronic address: tianshilin@novogene.com.
Zhiqiang DuKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China. Electronic address: zhqdu@neau.edu.cn.
Hui LiKey Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China. Electronic address: lihui@neau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decades of artificial selection have significantly improved performance and efficiency of animal production systems. However, little is known about the microevolution of genomes due to intensive breeding. Using whole-genome sequencing, we document dynamic changes of chicken genomes under divergent selection on adiposity over 19 generations. Directional selection reduced within-line but increased between-line genomic differences. We observed that artificial selection tended to result in recruitment of preexisting variations of genes related to adipose tissue growth. In addition, novel mutations contributed to divergence of phenotypes under selection but contributed significantly less than preexisting genomic variants. Integration of 15 generations genome sequencing, genome-wide association study, and multi-omics data further identified that genes involved in signaling pathways important to adipogenesis, such as autophagy and lysosome (URI1, MBL2), neural system (CHAT), and endocrine (PCSK1) pathways, were under strong selection. Our study provides insights into the microevolutionary dynamics of domestic animal genomes under artificial selection.

Indexed as

Biological SciencesEvolutionary BiologyGeneticsGenomics

Identifiers

PMID32554187
PMCPMC7303556

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.