Genome-wide Association Study for Yield and Yield-Related Traits in Diverse Blackgram Panel (Vigna mungo L. Hepper) Reveals Novel Putative Alleles for Future Breeding Programs.

Publication Overview
TitleGenome-wide Association Study for Yield and Yield-Related Traits in Diverse Blackgram Panel (Vigna mungo L. Hepper) Reveals Novel Putative Alleles for Future Breeding Programs.
AuthorsSingh L, Dhillon GS, Kaur S, Dhaliwal SK, Kaur A, Malik P, Kumar A, Gill RK, Kaur S
TypeJournal Article
Journal NameFrontiers in genetics
Volume13
Year2022
Page(s)849016
CitationSingh L, Dhillon GS, Kaur S, Dhaliwal SK, Kaur A, Malik P, Kumar A, Gill RK, Kaur S. Genome-wide Association Study for Yield and Yield-Related Traits in Diverse Blackgram Panel (Vigna mungo L. Hepper) Reveals Novel Putative Alleles for Future Breeding Programs.. Frontiers in genetics. 2022; 13:849016.

Abstract

Blackgram (Vigna mungo L. Hepper) is an important tropical and sub-tropical short-duration legume that is rich in dietary protein and micronutrients. Producing high-yielding blackgram varieties is hampered by insufficient genetic variability, absence of suitable ideotypes, low harvest index and susceptibility to biotic-abiotic stresses. Seed yield, a complex trait resulting from the expression and interaction of multiple genes, necessitates the evaluation of diverse germplasm for the identification of novel yield contributing traits. Henceforth, a panel of 100 blackgram genotypes was evaluated at two locations (Ludhiana and Gurdaspur) across two seasons (Spring 2019 and Spring 2020) for 14 different yield related traits. A wide range of variability, high broad-sense heritability and a high correlation of grain yield were observed for 12 out of 14 traits studied among all environments. Investigation of population structure in the panel using a set of 4,623 filtered SNPs led to identification of four sub-populations based on ad-hoc delta K and Cross entropy value. Using Farm CPU model and Mixed Linear Model algorithms, a total of 49 significant SNP associations representing 42 QTLs were identified. Allelic effects were found to be statistically significant at 37 out of 42 QTLs and 50 known candidate genes were identified in 24 of QTLs.

Features
This publication contains information about 116 features:
Feature NameUniquenameType
Internode lengthGWAS0000418GWAS
Internode lengthGWAS0000419GWAS
Internode lengthGWAS0000420GWAS
Number of clustersGWAS0000421GWAS
Number of clustersGWAS0000422GWAS
Number of clustersGWAS0000423GWAS
Number of clustersGWAS0000424GWAS
Number of clustersGWAS0000425GWAS
Number of clustersGWAS0000426GWAS
Number of clustersGWAS0000427GWAS
Number of clustersGWAS0000428GWAS
Number of clustersGWAS0000429GWAS
Number of clustersGWAS0000430GWAS
Pod lengthGWAS0000431GWAS
Seed number per podGWAS0000432GWAS
Seed number per podGWAS0000433GWAS
Seed number per podGWAS0000434GWAS
Seed number per podGWAS0000435GWAS
Seed number per podGWAS0000436GWAS
Biomass yield per plantGWAS0000437GWAS
Biomass yield per plantGWAS0000438GWAS
Seed yield per plantGWAS0000439GWAS
Seed yield per plantGWAS0000440GWAS
Seed yield per plantGWAS0000441GWAS
Seed yield per plantGWAS0000442GWAS

Pages

Projects
This publication contains information about 1 projects:
Project NameDescription
Blackgram-Yield_traits-Singh-2022
Properties
Additional details for this publication include:
Property NameValue
Publication ModelElectronic-eCollection
ISSN1664-8021
pISSN1664-8021
Publication Date2022
Journal AbbreviationFront Genet
DOI10.3389/fgene.2022.849016
Elocation10.3389/fgene.2022.849016
CopyrightCopyright © 2022 Singh, Dhillon, Kaur, Dhaliwal, Kaur, Malik, Kumar, Gill and Kaur.
LanguageEnglish
Language Abbreng
Publication TypeJournal Article
Journal CountrySwitzerland