Ontology type: schema:ScholarlyArticle
2019-03-21
AUTHORSSang-Moo Lee, Hayoung Song, Hankuil Yi, Yoonkang Hur
ABSTRACTBACKGROUND: Leaf morphology influences plant growth and productivity and is controlled by genetic and environmental cues. The various morphotypes of Brassica rapa provide an excellent resource for genetic and molecular studies of morphological traits. OBJECTIVE: This study aimed to identify genes regulating leaf morphology using segregating B. rapa p F2 population. METHODS: Phenotyping and transcriptomic analyses were performed on an F2 population derived from a cross between Rapid cycling B. rapa (RCBr) and B. rapa ssp. penkinensis, inbred line Kenshin. Analyses focused on four target traits: lamina (leaf) length (LL), lamina width (LW), petiole length (PL), and leaf margin (LM). RESULTS: All four traits were controlled by multiple QTLs, and expression of 466 and 602 genes showed positive and negative correlation with leaf phenotypes, respectively. From this microarray analysis, large numbers of genes were putatively identified as leaf morphology-related genes. The Gene Ontology (GO) category containing the highest number of differentially expressed genes (DEGs) was "phytohormones". The sets of genes enriched in the four leaf phenotypes did not overlap, indicating that each phenotype was regulated by a different set of genes. The expression of BrAS2, BrAN3, BrCYCB1;2, BrCYCB2;1,4, BrCYCB3;1, CrCYCBD3;2, BrULT1, and BrANT seemed to be related to leaf size traits (LL and LW), whereas BrCUC1, BrCUC2, and BrCUC3 expression for LM trait. CONCLUSION: An analysis integrating the results of the current study with previously published data revealed that Kenshin alleles largely determined LL and LW but LM resulted from RCBr alleles. Genes identified in this study could be used to develop molecular markers for use in Brassica breeding projects and for the dissection of gene function. More... »
PAGES1-19
http://scigraph.springernature.com/pub.10.1007/s13258-019-00809-7
DOIhttp://dx.doi.org/10.1007/s13258-019-00809-7
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1112919054
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/30900192
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