Evidence map›Paper›PMID 37120525›Full record

ArticleBMC plant biology2023

Genetic diversity, population structure, and genome-wide association study for the flowering trait in a diverse panel of 428 moth bean (Vigna aconitifolia) accessions using genotyping by sequencing.

Arvind Kumar Yadav, Chandan Kumar Singh, Rajwant K Kalia, Shikha Mittal, Dhammaprakash P Wankhede, Rajesh K Kakani, Shraddha Ujjainwal, Aakash, Ankit Saroha, N S Nathawat and 9 more

Open access · goldAbstract read
In one paragraph

Article in BMC plant biology, 2023. 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
2.4field-weighted citation impact, top 11% 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

1 citing paper in PubMed, 6 citations in OpenAlex.

  1. Review
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

19 authors at 5 institutions in 1 country.

Arvind Kumar Yadav *ICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
Chandan Kumar Singh *ICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
Rajwant K Kalia *ICAR- Central Arid Zone Research Institute, Jodhpur, Rajasthan, India.
Shikha MittalDepartment of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Solan, Himachal Pradesh, India.
Dhammaprakash P WankhedeICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India. d.wankhede@icar.gov.in.
Rajesh K KakaniICAR- Central Arid Zone Research Institute, Jodhpur, Rajasthan, India.
Shraddha UjjainwalICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
AakashICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
Ankit SarohaICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
N S NathawatICAR- Central Arid Zone Research Institute, Regional Research Station, Bikaner, Rajasthan, India.
Reena RaniICAR- Central Arid Zone Research Institute, Jodhpur, Rajasthan, India.
Pooja PanchariyaICAR- Central Arid Zone Research Institute, Jodhpur, Rajasthan, India.
Manoj ChoudharyICAR- Central Arid Zone Research Institute, Jodhpur, Rajasthan, India.
Kantilal SolankiICAR- Central Arid Zone Research Institute, Jodhpur, Rajasthan, India.
K K ChaturvediICAR- Indian Agricultural Statistics Research Institute, New Delhi, Delhi, India.
Sunil ArchakICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
Kuldeep SinghICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
Gyanendra Pratap SinghICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India.
Amit Kumar SinghICAR- National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, Delhi, India. amit.singh5@icar.gov.in.
National Bureau of Plant Genetic Resources · INCentral Arid Zone Research Institute · INIndian Agricultural Statistics Research Institute · INInternational Crops Research Institute for the Semi-Arid Tropics · INJaypee University of Information Technology · IN

Funding

Department of Biotechnology, Ministry of Science and Technology, India BT/Ag/Network/Pulses-1/2017-18
6 · The paper itself

Abstract

backgroundMoth bean (Vigna aconitifolia) is an underutilized, protein-rich legume that is grown in arid and semi-arid areas of south Asia and is highly resistant to abiotic stresses such as heat and drought. Despite its economic importance, the crop remains unexplored at the genomic level for genetic diversity and trait mapping studies. To date, there is no report of SNP marker discovery and association mapping of any trait in this crop. Therefore, this study aimed to dissect the genetic diversity, population structure and marker-trait association for the flowering trait in a diversity panel of 428 moth bean accessions using genotyping by sequencing (GBS) approach.

resultsA total of 9078 high-quality single nucleotide polymorphisms (SNPs) were discovered by genotyping of 428 moth bean accessions. Model-based structure analysis and PCA grouped the moth bean accessions into two subpopulations. Cluster analysis revealed accessions belonging to the Northwestern region of India had higher variability than accessions from the other regions suggesting that this region represents its center of diversity. AMOVA revealed more variations within individuals (74%) and among the individuals (24%) than among the populations (2%). Marker-trait association analysis using seven multi-locus models including mrMLM, FASTmrEMMA FASTmrEMMA, ISIS EM-BLASSO, MLMM, BLINK and FarmCPU revealed 29 potential genomic regions for the trait days to 50% flowering, which were consistently detected in three or more models. Analysis of the allelic effect of the major genomic regions explaining phenotypic variance of more than 10% and those detected in at least 2 environments showed 4 genomic regions with significant phenotypic effect on this trait. Further, we also analyzed genetic relationships among the Vigna species using SNP markers. The genomic localization of moth bean SNPs on genomes of closely related Vigna species demonstrated that maximum numbers of SNPs were getting localized on Vigna mungo. This suggested that the moth bean is most closely related to V. mungo.

conclusionOur study shows that the north-western regions of India represent the center of diversity of the moth bean. Further, the study revealed flowering-related genomic regions/candidate genes which can be potentially exploited in breeding programs to develop early-maturity moth bean varieties.

Indexed as

Genome-Wide Association StudyVignaGenotypePlant BreedingPolymorphism, Single NucleotideFlowering timeGBSGWASMoth beanMulti-locus associationSNPs

Identifiers

PMID37120525
PMCPMC10148550
OpenAlexW4367368633

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LicenceCC BY
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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.