Evidence map›Paper›PMID 36513408›Full record

ArticleJournal of advanced research2022

A novel Synthetic phenotype association study approach reveals the landscape of association for genomic variants and phenotypes.

Mária Škrabišová, Nicholas Dietz, Shuai Zeng, Yen On Chan, Juexin Wang, Yang Liu, Jana Biová, Trupti Joshi, Kristin D Bilyeu

Open access · goldAbstract read
In one paragraph

Article in Journal of advanced research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
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  5. Soybean pod shattering resistance allele pdh1 and marker-assisted selection.Plant-environment interactions (Hoboken, N.J.) · 2024
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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

9 authors at 3 institutions in 2 countries.

Mária ŠkrabišováDepartment of Biochemistry, Faculty of Science, Palacky University Olomouc, Olomouc 78371, Czech Republic.
Nicholas DietzDivision of Plant Sciences, University of Missouri, Columbia, MO 65201, USA.
Shuai ZengDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA; Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA.
Yen On ChanChristopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA; MU Data Science and Informatics Institute, University of Missouri, Columbia, MO 65212, USA.
Juexin WangDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA; Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA.
Yang LiuChristopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA; MU Data Science and Informatics Institute, University of Missouri, Columbia, MO 65212, USA.
Jana BiováDepartment of Biochemistry, Faculty of Science, Palacky University Olomouc, Olomouc 78371, Czech Republic.
Trupti JoshiDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA; Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65212, USA; MU Data Science and Informatics Institute, University of Missouri, Columbia, MO 65212, USA; Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO 65212, USA. Electronic address: joshitr@missouri.edu.
Kristin D BilyeuPlant Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, University of Missouri, Columbia, MO 65211, USA. Electronic address: kristin.bilyeu@usda.gov.
University of Missouri · USPalacký University Olomouc · CZUniversity of Missouri Health System · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionGenome-Wide Association Studies (GWAS) identify tagging variants in the genome that are statistically associated with the phenotype because of their linkage disequilibrium (LD) relationship with the causative mutation (CM). When both low-density genotyped accession panels with phenotypes and resequenced data accession panels are available, tagging variants can assist with post-GWAS challenges in CM discovery.

objectivesOur objective was to identify additional GWAS evaluation criteria to assess correspondence between genomic variants and phenotypes, as well as enable deeper analysis of the localized landscape of association.

methodsWe used genomic variant positions as Synthetic phenotypes in GWAS that we named "Synthetic phenotype association study" (SPAS). The extreme case of SPAS is what we call an "Inverse GWAS" where we used CM positions of cloned soybean genes. We developed and validated the Accuracy concept as a measure of the correspondence between variant positions and phenotypes.

resultsThe SPAS approach demonstrated that the genotype status of an associated variant used as a Synthetic phenotype enabled us to explore the relationships between tagging variants and CMs, and further, that utilizing CMs as Synthetic phenotypes in Inverse GWAS illuminated the landscape of association. We implemented the Accuracy calculation for a curated accession panel to an online Accuracy calculation tool (AccuTool) as a resource for gene identification in soybean. We demonstrated our concepts on three examples of soybean cloned genes. As a result of our findings, we devised an enhanced "GWAS to Genes" analysis (Synthetic phenotype to CM strategy, SP2CM). Using SP2CM, we identified a CM for a novel gene.

conclusionThe SP2CM strategy utilizing Synthetic phenotypes and the Accuracy calculation of correspondence provides crucial information to assist researchers in CM discovery. The impact of this work is a more effective evaluation of landscapes of GWAS associations.

Indexed as

Genome-Wide Association StudyGenomicsGenotypeLinkage DisequilibriumPhenotypeGenomicsGenotypingGWASPhenotypingResequencingSoybean

Identifiers

PMID36513408
PMCPMC9788956
OpenAlexW4223490067

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.