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Revealing the Genetic Architecture of Yield-Related and Quality Traits in Indian Mustard [ Brassica juncea (L.) Czern. and Coss.] Using Meta-QTL Analysis.

Authors :
Kumar, Rahul
Saini, Dinesh Kumar
Kumar, Mukesh
Priyanka, Veerala
Akhatar, Javed
Kaushik, Deepak
Sharma, Amit
Dhanda, Parmdeep Singh
Kaushik, Prashant
Source :
Agronomy. Oct2022, Vol. 12 Issue 10, pN.PAG-N.PAG. 27p.
Publication Year :
2022

Abstract

A meta-QTL analysis was conducted in Indian mustard to identify robust and stable meta-QTLs (MQTLs) by utilizing 1504 available QTLs, which included 891 QTLs for yield-related traits and 613 QTLs for quality traits. For yield-related traits, a total of 57 MQTLs (YRTs_MQTLs) were uncovered from the clustering of 560 projected QTLs, which had a 4.18-fold smaller confidence interval (CI) than that of the initial QTLs, whereas, for quality traits, as many as 51 MQTLs (Quality_MQTLs) were derived from 324 projected QTLs, which had a 2.65-fold smaller CI than that of the initial QTLs. Sixteen YRTs_MQTLs were observed to share chromosomal positions with 16 Quality_MQTLs. Moreover, four most promising YRTs_MQTLs and eight Quality-MQTLs were also selected and recommended for use in breeding programs. Four of these selected MQTLs were also validated with significant SNPs that were identified in previously published genome-wide association studies. Further, in silico functional analysis of some promising MQTLs allowed the detection of as many as 1435 genes, which also involved 15 high-confidence candidate genes (CGs) for yield-related traits and 46 high-confidence CGs for quality traits. After validation, the identified CGs can also be exploited to model the plant architecture and to improve quality traits through marker-assisted breeding, genetic engineering, and genome editing approaches. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734395
Volume :
12
Issue :
10
Database :
Academic Search Index
Journal :
Agronomy
Publication Type :
Academic Journal
Accession number :
159870954
Full Text :
https://doi.org/10.3390/agronomy12102442