Genetic Dissection of Leaf Development in Brassica rapa Using a Genetical Genomics Approach

Abstract

The paleohexaploid crop Brassica rapa harbors an enormous reservoir of morphological variation, encompassing leafy vegetables, vegetable and fodder turnips (Brassica rapa, ssp. campestris), and oil crops, with different crops having very different leaf morphologies. In the triplicated B. rapa genome, many genes have multiple paralogs that may be regulated differentially and contribute to phenotypic variation. Using a genetical genomics approach, phenotypic data from a segregating doubled haploid population derived from a cross between cultivar Yellow sarson (oil type) and cultivar Pak choi (vegetable type) were used to identify loci controlling leaf development. Twenty-five colocalized phenotypic quantitative trait loci (QTLs) contributing to natural variation for leaf morphological traits, leaf number, plant architecture, and flowering time were identified. Genetic analysis showed that four colocalized phenotypic QTLs colocalized with flowering time and leaf trait candidate genes, with their cis-expression QTLs and cisor trans-expression QTLs for homologs of genes playing a role in leaf development in Arabidopsis (Arabidopsis thaliana). The leaf gene BRASSICA RAPA KIP-RELATED PROTEIN2_A03 colocalized with QTLs for leaf shape and plant height; BRASSICA RAPA ERECTA_A09 colocalized with QTLs for leaf color and leaf shape; BRASSICA RAPA LONGIFOLIA1_A10 colocalized with QTLs for leaf size, leaf color, plant branching, and flowering time; while the major flowering time gene, BRASSICA RAPA FLOWERING LOCUS C_A02, colocalized with QTLs explaining variation in flowering time, plant architectural traits, and leaf size. Colocalization of these QTLs points to pleiotropic regulation of leaf development and plant architectural traits in B. rapa.Six Brassica species are cultivated worldwide: three diploid Brassica species, Brassica rapa (A genome; n = 10), Brassica nigra (B genome; n = 8), and Brassica oleracea (C genome; n = 9), and three amphidiploids, Brassica juncea (AB; n = 18), Brassica napus (AC; n = 19), and Brassica carinata (BC; n = 17), derived by spontaneous hybridization among the three diploid species (Nagaharu, 1935). All diploid Brassica species have undergone a whole-genome triplication since their divergence from Arabidopsis (Arabidopsis thaliana; Lysak et al., 2005;Town et al.,

A Systems Genetics Approach Identifies Gene Regulatory Networks Associated with Fatty Acid Composition in Brassica rapa Seed

“…4, left). In addition to variation in morphotypes, and, as a result, in many other morphological and biochemical traits (Zhao et al, 2005;Pino Del Carpio et al, 2011;Xiao et al, 2013Xiao et al, , 2014, the yellow sarson and pak choi parents have contrasting seed coat color (Basnet et al, 2013). A strong seed color QTL with 33% explained variance was mapped on A09 (data not shown); the causal gene, the basic helix-loop-helix transcription factor BrTT8, was cloned, and its role in seed color was functionally validated in B. rapa and in other species (Padmaja et al, 2014).…”

“…Genome-wide mapping of gene transcripts in a segregating population was first proposed by Jansen and Nap (2001) and was named genetical genomics. Using genetical genomics, candidate genes were identified in B. rapa for flowering time and leaf development (Xiao et al, 2013(Xiao et al, , 2014, phytonutrient content (Pino Del Carpio et al, 2014), and phosphorus use efficiency (Hammond et al, 2011).…”

Regulatory Network of Secondary Metabolism in Brassica rapa: Insight into the Glucosinolate Pathway

“…Transcripts of these genes were profiled with two technical replications using the RNA samples of the 92 DH68 lines that were previously used for microarray analysis, as described in [40], [37]. The eQTLs for these six single-copy genes identified using the microarray were confirmed by RT-qPCR, with higher LOD scores for RT-qPCR data.…”

7. Themenbereich grüne Gentechnologie: Pflanzenzüchtung und Agrarwirtschaft

“…So können Stoffwechselwege oder Entwicklungsprozesse aufgeklärt werden. Ansätze der genetischen Genomik wurden zunächst in der Modellpflanze Arabidopsis thaliana erprobt und auch bei Nutzpflanzen wie Eukalyptus, Weizen oder BrassicaArten eingesetzt (Joosen et al, 2009;Xiao et al, 2014). Auch die komplexen Wechselwirkungen zwischen molekulargenetischen Faktoren und der Umwelt, die die Genexpression beeinflussen, können aufgedeckt werden, wenn "genetical genomics"-Studien unter unterschiedlichen Umweltbedingungen wiederholt werden (Snoek et al, 2013;Joosen et al, 2013 lung (Schatten) zu Genotyp-Umwelt-Interaktionen führte, die mit einer veränderten Genexpression in bestimmten Genregionen einhergingen (Snoek et al, 2013 Die Anzahl an selektierbaren Markern, die nicht auf einer Antibiotikum-oder Herbizidresistenz beruhen, hat im Untersuchungszeitraum beträchtlich zugenommen.…”