Evidence map›Paper›PMID 30794545›Full record

ArticlePloS one2019

Genome-wide association studies for yield-related traits in soft red winter wheat grown in Virginia.

Brian P Ward, Gina Brown-Guedira, Frederic L Kolb, David A Van Sanford, Priyanka Tyagi, Clay H Sneller, Carl A Griffey

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
19.2field-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

48 citing papers in PubMed, 92 citations in OpenAlex.

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  13. Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
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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

7 authors at 6 institutions in 1 country.

Brian P WardDepartment Of Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.ORCID 0000-0002-4129-7934
Gina Brown-GuediraEastern Regional Small Grains Genotyping Laboratory, USDA-ARS, Raleigh, North Carolina, United States of America.
Frederic L KolbDepartment of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America.
David A Van SanfordDepartment of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky, United States of America.
Priyanka TyagiDepartment of Crop and Soil Sciences, North Carolina State University, Raleigh, North Carolina, United States of America.
Clay H SnellerOhio Agricultural Research and Development Center, The Ohio State University, Wooster, Ohio, United States of America.
Carl A GriffeyDepartment Of Crop and Soil Environmental Sciences, Virginia Tech, Blacksburg, Virginia, United States of America.
Virginia Tech · USAgricultural Research Service · USNorth Carolina State University · USThe Ohio State University · USUniversity of Illinois Urbana-Champaign · USUniversity of Kentucky · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Grain yield is a trait of paramount importance in the breeding of all cereals. In wheat (Triticum aestivum L.), yield has steadily increased since the Green Revolution, though the current rate of increase is not forecasted to keep pace with demand due to growing world population and increasing affluence. While several genome-wide association studies (GWAS) on yield and related component traits have been performed in wheat, the previous lack of a reference genome has made comparisons between studies difficult. In this study, a GWAS for yield and yield-related traits was carried out on a population of 322 soft red winter wheat lines across a total of four rain-fed environments in the state of Virginia using single-nucleotide polymorphism (SNP) marker data generated by a genotyping-by-sequencing (GBS) protocol. Two separate mixed linear models were used to identify significant marker-trait associations (MTAs). The first was a single-locus model utilizing a leave-one-chromosome-out approach to estimating kinship. The second was a sub-setting kinship estimation multi-locus method (FarmCPU). The single-locus model identified nine significant MTAs for various yield-related traits, while the FarmCPU model identified 74 significant MTAs. The availability of the wheat reference genome allowed for the description of MTAs in terms of both genetic and physical positions, and enabled more extensive post-GWAS characterization of significant MTAs. The results indicate a number of promising candidate genes contributing to grain yield, including an ortholog of the rice aberrant panicle organization (APO1) protein and a gibberellin oxidase protein (GA2ox-A1) affecting the trait grains per square meter, an ortholog of the Arabidopsis thaliana mother of flowering time and terminal flowering 1 (MFT) gene affecting the trait seeds per square meter, and a B2 heat stress response protein affecting the trait seeds per head.

Indexed as

Genome-Wide Association StudyQuantitative Trait, HeritableChromosome MappingCrop ProductionEdible GrainGenetic Association StudiesGenetic MarkersGenotypeLinkage DisequilibriumPhenotypePolymorphism, Single NucleotideSeedsTriticumVirginiaGenetic Markers

Identifiers

PMID30794545
PMCPMC6386437
OpenAlexW2951505541

What OpenQuestion holds

Textmetadata
LicenceCC0
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.