Original Research ARTICLE
Overcoming cabbage crossing incompatibility by the development and application of self-compatibility-QTL- specific markers and genome-wide background analysis
- 1Chinese Academy of Agricultural Sciences, China
Cabbage hybrids, which clearly present heterosis vigour, are widely used in agricultural production. CB201 and 96-100 are elite cabbage inbred lines; in this study, we crossed CB201 × 96-100, which yielded an excellent hybrid, 06-88. However, F1 seeds cannot be produced at the anthesis stage because the parents share the same S-haplotype (S57, class I). To overcome crossing incompatibility, we first introduced another highly self-compatible (SC) elite line, 87-534 (S5, class II), and performed whole-genome mapping of the quantitative trait loci (QTLs) governing self-compatibility using an F2 population derived from 87-534 × 96-100. Eight QTLs were detected, and high contribution rates (CRs) were observed for three QTLs: qSC7.2 (54.8%), qSC9.1 (14.1%) and qSC5.1 (11.2%). To overcome the crossing incompatibility, we performed rapid introgression of the self-compatibility trait from 87-534 to 96-100 using two self-compatibility-QTL-specific markers, BoID0709 and BoID0992, as well as 36 genome-wide markers that were evenly distributed along nine chromosomes for background analysis in recurrent back-crossing (BC). The transfer process showed that the proportion of recurrent parent genome (PRPG) in BC4F1 was greater than 94%, and the ratio of individual SC plants in BC4F1 reached 100%. The newly created line, which was designated SC96-100 and exhibited both agronomic traits that were similar to those of 96-100 and a compatibility index (CI) greater than 5.0, was successfully used in the production of the commercial hybrid 06-88. The study herein provides new insight into the genetic basis of self-compatibility in cabbage and facilitates cabbage breeding using SC lines in the male-sterile (MS) system.
Keywords: Cabbage, Crossing incompatibility, Quantitative Trait Loci, genetic mapping, genomic background analysis
Received: 29 Aug 2018;
Accepted: 05 Feb 2019.
Edited by:Jianjun Chen, University of Florida, United States
Copyright: © 2019 Lv, Zhuang, xiao, han, hu, xue, fang, yang, zhang, liu, li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
PhD. Honghao Lv, Chinese Academy of Agricultural Sciences, Beijing, China, firstname.lastname@example.org
Dr. Mu Zhuang, Chinese Academy of Agricultural Sciences, Beijing, China, email@example.com