Deciphering allelic variations for seed glucosinolate traits in oilseed mustard (Brassica juncea) using two bi-parental mapping populations

Abstract

QTL mapping by two DH mapping populations deciphered allelic variations for five different seed glucosinolate traits in B. juncea. Allelic variations for five different seed glucosinolate (GS) traits, namely % propyl, % butyl, % pentyl, aliphatics and total GS content were studied through QTL analysis using two doubled haploid (DH) mapping populations. While the high GS parents in two populations differed in their profiles of seed aliphatic GS, the low GS parents were similar. Phenotypic data of seed GS traits from three environments of the two populations were subjected to QTL analysis. The first population (referred to as DE population) detected a total of 60 QTL from three environments which upon intra-population meta-QTL analysis were merged to 17 S-QTL (Stable QTL) and 15 E-QTL (Environment QTL). The second population (referred to as VH population) detected 58 QTL from the three environments that were merged to 15S-QTL and 16E-QTL. In both the populations, majority of S-QTL were detected as major QTL. Inter-population meta-analysis identified three C-QTL (consensus QTL) formed by merging major QTL from the two populations. Candidate genes of GS pathway were co-localized to the QTL regions either through genetic mapping or through in silico comparative analysis. Parental allelic variants of QTL or of the co-mapped candidate gene(s) were determined on the basis of the significantly different R (2) values of the component QTL from the two populations which were merged to form C-QTL. The results of the study are significant for marker-assisted transfer of the low GS trait and also for developing lines with lower GS than are present in Brassica juncea.

A chromosome-scale assembly of allotetraploid Brassica juncea (AABB) elucidates comparative architecture of the A and B genomes

“…The east-European lines, as such, are ill-adapted to the growing conditions in South Asia due to photoperiod sensitivity but contain a large number of positive traits like high pod density [38][39][40] , oil and seed meal quality [41][42] , and disease resistance 43 . Several QTL have been mapped in the Indian and East European gene pool lines [38][39][40][41][42][43][44] . The Chinese vegetable types like Tumida constitute another divergent gene pool 5 that contains potentially useful traits like serrated leaves, basal branching 45 , and stem strength.…”

BjuB.CYP79F1 Regulates Synthesis of Propyl Fraction of Aliphatic Glucosinolates in Oilseed Mustard Brassica juncea: Functional Validation through Genetic and Transgenic Approaches

“…juncea was performed using hypocotyl explants following the protocol described by Jagannath et al [ 25 ]. Extraction and estimation of seed GS content and analysing the GS profiles was done by HPLC [ 20 ].…”

“…A follow up exercise of QTL mapping in B . juncea using an east European high seed GS line (Donskaja IV) that primarily synthesizes sinigrin also identified a QTL corresponding to J16Gsl4 [ 20 ].…”

Isolate Dependency of Brassica rapa Resistance QTLs to Botrytis cinerea

“…In addition to necrotrophic resistance, these compounds also alter resistance to biotrophic pathogens, insects and aphids indicating that they are likely key players in numerous biotic interactions of Brassica plants ( Kroymann and Mitchell-Olds, 2005 ; Pfalz et al, 2007 , 2009 ; Fan et al, 2011 ; Weis et al, 2014 ; Kerwin et al, 2015 ). As a result of this role in numerous different biotic interactions, GSLs show extensive genetic variation in all tested Brassica’s but the link between this natural genetic variation and quantitative resistance to pathogens including B. cinerea has not been queried ( Kliebenstein et al, 2002a , b ; Wentzell et al, 2007 ; Chan et al, 2010 ; Velasco et al, 2011 ; Feng et al, 2012 ; Zou et al, 2013 ; Rahman et al, 2014 ; Brown et al, 2015 ; Gupta et al, 2015 ; Rout et al, 2015 ).…”