Evidence map›Paper›PMID 40682201›Full record

ArticleG3 (Bethesda, Md.)2025

MINE: maximally informative next experiment-toward a new GWAS experimental design and methodology.

Isaac Torres, Shufan Zhang, Amanda Bouffier, Bernd Schüttler, Jonathan Arnold

Abstract read
In one paragraph

Article in G3 (Bethesda, Md.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Isaac TorresInstitute of Bioinformatics, University of Georgia, Athens, GA 30602, United States.ORCID 0009-0002-4817-6438
Shufan ZhangInstitute of Bioinformatics, University of Georgia, Athens, GA 30602, United States.
Amanda BouffierInstitute of Bioinformatics, University of Georgia, Athens, GA 30602, United States.
Bernd SchüttlerInstitute of Bioinformatics, University of Georgia, Athens, GA 30602, United States.
Jonathan ArnoldInstitute of Bioinformatics, University of Georgia, Athens, GA 30602, United States.ORCID 0000-0001-5845-1048

Funding

DOE DE-SC0021386
6 · The paper itself

Abstract

The computational methodology of Genome Wide Association Studies (GWAS) currently has several limitations: (i) the number of observations (rows) on a quantitative trait tends to be smaller than the number of single nucleotide polymorphisms (SNPs) (columns) in the design matrix; (ii) each SNP is usually modeled separately, failing to acknowledge interaction between each other (ie epistasis); (iii) there is implicit linkage disequilibrium (LD) between neighboring SNPs due to their linkage. To overcome these issues, we developed a tool that uses ensemble methods to fit mixed linear models to GWAS data, and these ensemble methods include the development of a new experimental design approach in GWAS, which uses the resultant models and data to select the next informative experiment over time. This new adaptive and staged approach for GWAS experimental design was developed and tested in a 3 yr adaptive model-guided discovery experiment against a fixed classical design. In Sorghum bicolor a total of 79, 86, and 78 accessions were tested in years 1, 2, and 3, respectively out of 343 accessions available in the Bioenergy Association Panel (BAP) each identified for 232,303 SNPs, 1 every 2-3 kb in the genomes. We demonstrated the feasibility of MINE enacted with 8 people in the field per year over 3 yr vs in 1 large classical design enacted with 20 people in 1 yr. The MINE results for chromosomal regions identified controlling dry weight were confirmed against results from previous sorghum GWAS experiments and 1 large classical design for the BAP panel.

Indexed as

Genome-Wide Association StudySorghumLinkage DisequilibriumModels, GeneticPolymorphism, Single NucleotideQuantitative Trait LociResearch Designbioinformaticsexperimental designGWASMCMC

Identifiers

PMID40682201
PMCPMC12405896

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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.