Evidence map›Paper›PMID 31287919›Full record

ArticleMolecular ecology2019

Identifying loci with breeding potential across temperate and tropical adaptation via EigenGWAS and EnvGWAS.

Jing Li, Guo-Bo Chen, Awais Rasheed, Delin Li, Kai Sonder, Cristian Zavala Espinosa, Jiankang Wang, Denise E Costich, Patrick S Schnable, Sarah J Hearne and 1 more

Open access · bronzeAbstract read
In one paragraph

Article in Molecular ecology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
4.8field-weighted citation impact, top 5% 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

24 citing papers in PubMed, 37 citations in OpenAlex.

  1. Article
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  4. Genotype-by-environment interactions and local adaptation shape selection in the US National Chip Processing Trial.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  5. Review
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  7. Article
  8. Analysis of historical selection in winter wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  9. Genetic networks underlying salinity tolerance in wheat uncovered with genome-wide analyses and selective sweeps.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  10. Article
  11. Trends of genetic changes uncovered by Env- and Eigen-GWAS in wheat and barley.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Article
  12. Review
  13. 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

11 authors at 6 institutions in 4 countries.

Jing LiInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Guo-Bo ChenClinical Research Institute, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China.
Awais RasheedInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Delin LiData Biotech (Beijing) Co., Ltd, Beijing, China.
Kai SonderInternational Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
Cristian Zavala EspinosaInternational Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
Jiankang WangInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.
Denise E CostichInternational Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
Patrick S SchnableData Biotech (Beijing) Co., Ltd, Beijing, China.
Sarah J HearneInternational Maize and Wheat Improvement Center (CIMMYT), Texcoco, Mexico.
Huihui LiInstitute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China.ORCID 0000-0002-9117-5011
Centro Internacional de Mejoramiento de Maíz Y Trigo · MXChinese Academy of Agricultural Sciences · CNIowa State University · USQuaid-i-Azam University · PKSinovac Biotech · CNZhejiang Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the genomic basis of adaptation in maize is important for gene discovery and the improvement of breeding germplasm, but much remains a mystery in spite of significant population genetics and archaeological research. Identifying the signals underpinning adaptation are challenging as adaptation often coincided with genetic drift, and the base genomic diversity of the species in massive. In this study, tGBS technology was used to genotype 1,143 diverse maize accessions including landraces collected from 20 countries and elite breeding lines of tropical lowland, highland, subtropical/midaltitude and temperate ecological zones. Based on 355,442 high-quality single nucleotide polymorphisms, 13 genomic regions were detected as being under selection using the bottom-up searching strategy, EigenGWAS. Of the 13 selection regions, 10 were first reported, two were associated with environmental parameters via EnvGWAS, and 146 genes were enriched. Combining large-scale genomic and ecological data in this diverse maize panel, our study supports a polygenic adaptation model of maize and offers a framework to enhance our understanding of both the mechanistic basis and the evolutionary consequences of maize domestication and adaptation. The regions identified here are promising candidates for further, targeted exploration to identify beneficial alleles and haplotypes for deployment in maize breeding.

Indexed as

BreedingEnvironmentGenetic LociGenome-Wide Association StudyAdaptation, PhysiologicalDatabases, GeneticEcotypeGenotypeGeographyModels, GeneticMolecular Sequence AnnotationPhylogenyPolymorphism, Single NucleotidePrincipal Component AnalysisSequence Analysis, DNAZea maysadaptationdomesticationEigenGWASEnvGWASmaizeselection

Identifiers

PMID31287919
PMCPMC6851670
OpenAlexW2960580392

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.