Evidence map›Paper›PMID 36207301›Full record

ArticleNature communications2022

GWAS, MWAS and mGWAS provide insights into precision agriculture based on genotype-dependent microbial effects in foxtail millet.

Yayu Wang, Xiaolin Wang, Shuai Sun, Canzhi Jin, Jianmu Su, Jinpu Wei, Xinyue Luo, Jiawen Wen, Tong Wei, Sunil Kumar Sahu and 10 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed
23.0field-weighted citation impact, top 1% 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

78 citing papers in PubMed, 135 citations in OpenAlex.

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  13. Identifying genetic loci associated with drought tolerance in foxtail millet (Setaria italica).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
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18 more citing papers are in PubMed but not listed here.

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

20 authors at 5 institutions in 2 countries.

Yayu Wang *State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0003-4490-6376
Xiaolin Wang *National Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200032, China.
Shuai SunState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0003-1092-3186
Canzhi JinState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Jianmu SuState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Jinpu WeiState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0002-1463-0236
Xinyue LuoState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Jiawen WenState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Tong WeiState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Sunil Kumar SahuState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0002-4742-9870
Hongfeng ZouState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Hongyun ChenState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0001-8422-9619
Zhixin MuCenter for Agricultural Genetic Resources Research, Shanxi Agricultural University, Taiyuan, 030031, China.
Gengyun ZhangState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Xin LiuState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0003-3256-2940
Xun XuState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.ORCID 0000-0002-5338-5173
Lone GramDepartment of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads, 2800 Kgs, Lyngby, Denmark.ORCID 0000-0002-1076-5723
Huanming YangState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
Ertao WangNational Key Laboratory of Plant Molecular Genetics, Chinese Academy of Sciences Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200032, China. etwang@cemps.ac.cn.ORCID 0000-0002-5178-3530
Huan LiuState Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China. liuhuan@genomics.cn.ORCID 0000-0003-3909-0931
University of Chinese Academy of Sciences · CNBGI Group (China) · CNChinese Academy of Sciences · CNShanxi Agricultural University · CNTechnical University of Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic and environmental factors collectively determine plant growth and yield. In the past 20 years, genome-wide association studies (GWAS) have been conducted on crops to decipher genetic loci that contribute to growth and yield, however, plant genotype appears to be insufficient to explain the trait variations. Here, we unravel the associations between genotypic, phenotypic, and rhizoplane microbiota variables of 827 foxtail millet cultivars by an integrated GWAS, microbiome-wide association studies (MWAS) and microbiome genome-wide association studies (mGWAS) method. We identify 257 rhizoplane microbial biomarkers associated with six key agronomic traits and validated the microbial-mediated growth effects on foxtail millet using marker strains isolated from the field. The rhizoplane microbiota composition is mainly driven by variations in plant genes related to immunity, metabolites, hormone signaling and nutrient uptake. Among these, the host immune gene FLS2 and transcription factor bHLH35 are widely associated with the microbial taxa of the rhizoplane. We further uncover a plant genotype-microbiota interaction network that contributes to phenotype plasticity. The microbial-mediated growth effects on foxtail millet are dependent on the host genotype, suggesting that precision microbiome management could be used to engineer high-yielding cultivars in agriculture systems.

Indexed as

MicrobiotaSetaria PlantAgricultureGenome-Wide Association StudyGenotypeHormonesTranscription FactorsHormonesTranscription Factors

Identifiers

PMID36207301
PMCPMC9546826
OpenAlexW4303423749

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.