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Identification and fine mapping of a major locus controlling branching in Brassica napus

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A candidate branching-controlling gene for qDBA09 was identified after delimiting a Brassica napus recessive locus within a 270-kb interval on chromosome A09. Although branching is an important trait associated with… Click to show full abstract

A candidate branching-controlling gene for qDBA09 was identified after delimiting a Brassica napus recessive locus within a 270-kb interval on chromosome A09. Although branching is an important trait associated with the adaptation and yield potential of rapeseed (Brassica napus), the genetic mechanisms underlining branching in this crop remain poorly understood. In this study, we characterized a naturally occurring rapeseed mutant, db1, which showed an ultrahigh branching density phenotype. By combining bulked segregant analysis (BSA) and the Brassica 60K SNP BeadChip Array, we identified two major quantitative trait loci (QTLs), qDBA09 and qDBC06, which were subsequently confirmed using the traditional QTL-mapping approach. Analysis of 208 individuals from a BC1F3 population indicated that the qDBA09 locus is a single Mendelian factor and that the dense branching phenotype is controlled by a single recessive gene. Furthermore, QTL analysis confirmed that qDBA09 explained between 9.5 and 70.5% of the variation in branching-related traits. Using 7785 individuals from the BC1F3 population, we mapped qDBA09 to a DNA fragment of approximately 270 kb in length that contained 27 predicted genes, three of which were identified as potentially involved in the control of the dense branching trait. Based on the reported function of these genes, together with sequence comparisons and co-segregation analysis, we identified a potential candidate gene for the qDBA09 locus. The present findings lay the foundations for further in-depth research on the branching mechanisms of B. napus.

Keywords: brassica; fine mapping; analysis; brassica napus; locus; identification fine

Journal Title: Theoretical and Applied Genetics
Year Published: 2019

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