Mapping of quantitative trait loci for the bolting trait in Brassica rapa under vernalizing conditions

Abstract

ABSTRACT. Premature bolting can occur occasionally during spring cultivation of heading Chinese cabbage in East Asia when the plants encounter low temperatures (vernalization), leading to economic loss. Breeding bolting-resistant cultivars is the best choice for solving this problem. We looked for QTLs responsible for varietal differences in the bolting trait in Brassica rapa under environmental conditions that promote vernalization. To achieve this goal, we constructed a linkage map with 107 simple sequence repeats and 54 insertion/deletion markers based on a segregating population of 186 F 2 individuals. The resulting map consisted of 10 linkage groups and covered a total length of 947.1 cM, with an average genetic distance of 5.84 cM between adjacent markers. QTL analysis of the bolting trait was performed by two phenotypic evaluations (bolting index and flowering time) based on the scores in an F 2 population in the spring of 2010, and scores in F 2:3 families in autumn 2010 and spring 2011, respectively. Twenty-six QTLs that controlled bolting were detected, accounting for 2.6 to 31.2% of the phenotypic variance. The detected QTLs with large effects co-localized mainly on linkage groups A02, A06, and A07. These QTLs may provide useful information for marker-assisted selection in a breeding program for late bolting or bolting-resistant cultivars in B. rapa crops.

Fine Mapping and Analysis of Candidate Genes for qFT7.1, a Major Quantitative Trait Locus Controlling Flowering Time in Brassica Rapa L

“…4c) and a physical position of 15,539,588 to 15,595,959 on chromosome A07. In our previous studies, we did not detected any QTLs in the candidate region basing on F 2 , RIL, and CSSLs derived from the identical parent, RcBr and 08A061 (Wang et al 2014;Liu et al 2016;Wang et al 2018b). The CSSLs were constructed using 166 InDel and SSR markers that were distributed relatively evenly on the ten chromosomes; however, a low marker density is likely to lead to small introgression segments being missed.…”

Recent progress in the use of ‘omics technologies in brassicaceous vegetables

“…A segregating population of a cross between a Chinese cabbage with a turnip was used to identify loci related to morphological characteristics of the tap root ( Lu et al, 2008 ). To investigate the genetic background of premature bolting under cold stress, a Chinese cabbage population was constructed based on crossing early and late bolting genotypes and QTL analysis identified 26 QTL ( Wang et al, 2014c ). Seven morphological traits were screened in a population derived from crossing a Chinese cabbage with a vegetable turnip and resulted in the detection of eight QTL ( Kubo et al, 2010 ).…”

Advancing utilization of diverse global carrot (Daucus carota L.) germplasm with flowering habit trait ontology

“…When these plants transition from their vegetative growth phase to their reproductive growth phase, they channel resources to the growth and development of the seed stalk; this in turn causes rapid deterioration of the vegetative tissues, which senesce and become unmarketable ( Quiros, 1993 ). In vegetable crops where the economic product is the vegetative shoot tissue, bolting initiates biochemical changes that cause edible vegetative shoot tissue to become unpalatable due to damage and hardening from senescence in lettuce ( Rosental et al., 2021 ), Chinese cabbage ( Yui and Yoshikawa, 1991 ; Wang et al., 2014 ; Jiang et al., 2023 ), celery ( Quiros et al., 1987 ; Quiros, 1993 ), and spinach ( Ribera et al., 2020 ), as well as to secretion of latex and bitter secondary metabolites in lettuce ( Ciriaci et al, 2013 ) and spinach ( Abe et al., 2014 ). In vegetable crops where the fleshy storage root is the economic product, bolting gives way to root lignification, preventing tap root thickening ( Villeneuve, 2020 ), and rendering an inedible, woody, unmarketable product, thus causing serious economic losses to growers of carrot ( Dowker and Jackson, 1975 ; Prohens and Nuez, 2008 ; Simon and Grzebelus, 2020 ), table beet ( Holland and Dowker, 1969 ; Dowker et al., 1971 ; Goldman, 2004 ), onion ( Khokhar et al., 2007 ; Hyun et al., 2009 ; Baldwin et al., 2014 ; Havey, 2018 ), and turnip ( Nishioka et al., 2005 ).…”