Evidence map›Paper›PMID 39080407›Full record

ArticleScientific reports2024

Analyzing Medicago spp. seed morphology using GWAS and machine learning.

Jacob Botkin, Cesar Medina, Sunchung Park, Kabita Poudel, Minhyeok Cha, Yoonjung Lee, Louis K Prom, Shaun J Curtin, Zhanyou Xu, Ezekiel Ahn

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PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2024. 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

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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

10 authors.

Jacob Botkin *Department of Plant Pathology, University of Minnesota, St. Paul, MN, 55108, USA.
Cesar Medina *Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
Sunchung ParkSustainable Perennial Crops Laboratory, United States Department of Agriculture- Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, MD, 20705, USA.
Kabita PoudelDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
Minhyeok ChaDepartment of Biotechnology, Korea University, Seoul, 02841, Republic of Korea.
Yoonjung LeeDepartment of Plant Pathology, University of Minnesota, St. Paul, MN, 55108, USA.
Louis K PromUnited States Department of Agriculture- Agricultural Research Service, Southern Plains Agricultural Research Center, 2765 F & B Road, College Station, TX, 77845, USA.
Shaun J CurtinDepartment of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.
Zhanyou XuPlant Science Research Unit, United States Department of Agriculture- Agricultural Research Service, St. Paul, MN, 55108, USA. Zhanyou.Xu@usda.gov.
Ezekiel AhnSustainable Perennial Crops Laboratory, United States Department of Agriculture- Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, MD, 20705, USA. Ezekiel.Ahn@usda.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alfalfa is widely recognized as an important forage crop. To understand the morphological characteristics and genetic basis of seed morphology in alfalfa, we screened 318 Medicago spp., including 244 Medicago sativa subsp. sativa (alfalfa) and 23 other Medicago spp., for seed area size, length, width, length-to-width ratio, perimeter, circularity, the distance between the intersection of length & width (IS) and center of gravity (CG), and seed darkness & red-green-blue (RGB) intensities. The results revealed phenotypic diversity and correlations among the tested accessions. Based on the phenotypic data of M. sativa subsp. sativa, a genome-wide association study (GWAS) was conducted using single nucleotide polymorphisms (SNPs) called against the Medicago truncatula genome. Genes in proximity to associated markers were detected, including CPR1, MON1, a PPR protein, and Wun1(threshold of 1E-04). Machine learning models were utilized to validate GWAS, and identify additional marker-trait associations for potentially complex traits. Marker S7_33375673, upstream of Wun1, was the most important predictor variable for red color intensity and highly important for brightness. Fifty-two markers were identified in coding regions. Along with strong correlations observed between seed morphology traits, these genes will facilitate the process of understanding the genetic basis of seed morphology in Medicago spp.

Indexed as

Genome-Wide Association StudyMachine LearningMedicagoPolymorphism, Single NucleotideSeedsGenome, PlantMedicago sativaMedicago truncatulaPhenotypeQuantitative Trait LociAlfalfaArea sizeGWASMachine learningMedicago sativaRGBSeed colorSeed morphology

Identifiers

PMID39080407
PMCPMC11289399

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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.