To investigate the molecular mechanisms of fiber initiation in cotton (Gossypium spp.), an integrated approach combining transcriptome, iTRAQ-based proteome and genetic mapping was taken to compare the ovules of the Xuzhou 142 wild type (WT) with its fuzzless-lintless (fl) mutant at −3 and 0 day post-anthesis. A total of 1,953 mRNAs, 187 proteins, and 131 phosphoproteins were differentially expressed (DE) between WT and fl, and the levels of transcripts and their encoded proteins and phosphoproteins were highly congruent. A functional analysis suggested that the abundance of proteins were mainly involved in amino sugar, nucleotide sugar and fatty acid metabolism, one carbon pool for folate metabolism and flavonoid biosynthesis. qRT-PCR, Western blotting, and enzymatic assays were performed to confirm the regulation of these transcripts and proteins. A molecular mapping located the lintless gene li3 in the fl mutant on chromosome 26 for the first time. A further in-silico physical mapping of DE genes with sequence variations between fl and WT identified one and four candidate genes in the li3 and n2 regions, respectively. Taken together, the transcript abundance, phosphorylation status of proteins at the fiber initiation stage and candidate genes have provided insights into regulatory processes underlying cotton fiber initiation.

No abstract

High‐density marker‐based QTL mapping can serve as an effective strategy to identify novel genomic information to facilitate crop improvement. In this study, we genotyped an F2 population (KB12‐1 × PP12‐1) using a RAD‐seq approach and constructed a high‐density linkage map for radish. After a series of filtering procedures were performed, 17,124 SNPs and 3,336 indels with aa × bb genotyping were retained to obtain bin markers. Then, a linkage map comprising a total of 1,221 bin markers in nine linkage groups spanning 1,467.3 cM with an average marker interval of 1.2 cM was constructed. We evaluated the resistance of the F2 mapping population to black rot using F3 progeny, and two major QTLs related to black rot resistance were identified based on this map. Among these QTLs, qBRR2 on Chr.2 explained 26.97% of the phenotypic variation with a LOD score of 11.93, and qBRR7 on Chr.7 accounted for 27.06% of the phenotypic variation with a LOD score of 11.83. The additive effect of qBRR2 was positive (14.97); however, qBRR7 had the opposite effect (−11.99). The high‐density linkage map and the major QTLs qBRR2 and qBRR7 provide new important information for disease resistance gene discovery and utilization in genetic improvement.