Evidence map›Paper›PMID 32034248›Full record

ArticleScientific reports2020

Genome-wide and SNP network analyses reveal genetic control of spikelet sterility and yield-related traits in wheat.

Ahmad M Alqudah, Jemanesh K Haile, Dalia Z Alomari, Curtis J Pozniak, Borislav Kobiljski, Andreas Börner

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. 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
7.0field-weighted citation impact, top 4% 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, 44 citations in OpenAlex.

  1. Article
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  8. Wheat Omics: Advancements and Opportunities.Plants (Basel, Switzerland) · 2023
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  16. Review
  17. GWAS Case Studies in Wheat.Methods in molecular biology (Clifton, N.J.) · 2022
    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

6 authors at 2 institutions in 2 countries.

Ahmad M AlqudahResearch Group Resources Genetics and Reproduction, Department Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Corrensstr. 3, OT Gatersleben, D-06466, Stadt, Seeland, Germany. ahqudah@gmail.com.ORCID http://orcid.org/0000-0002-0436-9724
Jemanesh K HaileDepartment of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, Canada.
Dalia Z AlomariResearch Group Gene and Genome Mapping, Department of Breeding Research, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Corrensstr. 3, OT Gatersleben, D-06466, Stadt, Seeland, Germany.ORCID http://orcid.org/0000-0002-0356-4560
Curtis J PozniakDepartment of Plant Sciences, Crop Development Centre, University of Saskatchewan, Saskatoon, Canada.
Borislav KobiljskiBiogranum, R&D in agriculture, Toplice Milana 20, Novi Sad, 21000, Serbia.
Andreas BörnerResearch Group Resources Genetics and Reproduction, Department Genebank, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Corrensstr. 3, OT Gatersleben, D-06466, Stadt, Seeland, Germany.ORCID http://orcid.org/0000-0003-3301-9026
Leibniz-Institut für Pflanzengenetik und Kulturpflanzenforschung (IPK) · DEUniversity of Saskatchewan · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Revealing the genetic factors underlying yield and agronomic traits in wheat are an imperative need for covering the global food demand. Yield boosting requires a deep understanding of the genetic basis of grain yield-related traits (e.g., spikelet fertility and sterility). Here, we have detected much natural variation among ancient hexaploid wheat accessions in twenty-two agronomic traits collected over eight years of field experiments. A genome-wide association study (GWAS) using 15 K single nucleotide polymorphisms (SNPs) was applied to detect the genetic basis of studied traits. Subsequently, the GWAS output was reinforced via other statistical and bioinformatics analyses to detect putative candidate genes. Applying the genome-wide SNP-phenotype network defined the most decisive SNPs underlying the traits. Six pivotal SNPs, co-located physically within the genes encoding enzymes, hormone response, metal ion transport, and response to oxidative stress have been identified. Of these, metal ion transport and Gibberellin 2-oxidases (GA2oxs) genes showed strong involvement in controlling the spikelet sterility, which had not been reported previously in wheat. SNP-gene haplotype analysis confirmed that these SNPs influence spikelet sterility, especially the SNP co-located on the exon of the GA2ox gene. Interestingly, these genes were highly expressed in the grain and spike, demonstrating their pivotal role in controlling the trait. The integrative analysis strategy applied in this study, including GWAS, SNP-phenotype network, SNP-gene haplotype, expression analysis, and genome-wide prediction (GP), empower the identification of functional SNPs and causal genes. GP outputs obtained in this study are encouraging for the implementation of the traits to accelerate yield improvement by making an early prediction of complex yield-related traits in wheat. Our findings demonstrate the usefulness of the ancient wheat material as a valuable resource for yield-boosting. This is the first comprehensive genome-wide analysis for spikelet sterility in wheat, and the results provide insights into yield improvement.

Indexed as

Quantitative Trait, HeritableCrop ProductionGene Regulatory NetworksGenetic Association StudiesGenome, PlantGenome-Wide Association StudyHaplotypesPlant InfertilityPolymorphism, Single NucleotideTriticum

Identifiers

PMID32034248
PMCPMC7005900
OpenAlexW3004450778

What OpenQuestion holds

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LicenceCC BY
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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.