An Integrated Analysis Of QTL Mapping And RNA Sequencing Identifys Candidate Genes For Pod Number Variation In Rapeseed (Brassica Napus L.)

As one of the three yield components in rapeseed(Brassica napus L.), pod number shows the highest correlation with yield and thus it contributes largely to yield. It is determined by a series of successive growth and developmental processes, which include flower bud differentiation, flower differentiation and development, double fertilization and pod development etc. In addition, pod number is affected by external factors(such as light, temperature, water, and fertilizer etc.). Pod number is a typically quantitative trait, which shows continuous distribution and is easily affected by the environment. Pod number shows extensive variation in rapeseed natural germplasm which is valuable for genetic improvement. The developmental processes affecting final pod number is relatively clear. However, the genetic and especially the molecular mechanism for this kind of variation remains poorly understood.In our previous study, Preliminary mapping for pod number was performed in F2/F2:3 and RIL population derived from rapeseed sequencing cultivars Zhongshuang11(low pod number) and No.73290(high pod number) which showed significant difference in pod number. A major QTL(q PN.A6) on the A6 linkage group was identified. Through constructing near-isogenic lines(NIL) population, the fine mapping for pod number major QTL was completed. To narrow down the candidate genes, the shoot apical meristems(SAMs) of ten plants at 6-8 leaf stage from Zhonghusang11 and No.73290, respectively, were collected. RNA was extracted and pooled. Then, RNA sequencing of the SAM was conducted. The significantly enriched pathways were identified and their relations with pod number variation were analyzed. Eventually, an integrated analysis of QTL mapping, transcriptome analysis and bioinformatics analysis identified several candidate genes, which laid a foundation for gene clone. The main results and conclusions are as follows:1. A total of 13 QTLs for pod number were identified in the RIL population, and were integrated with those previously detected in F2/F2:3 population, which resulted in a total of 19 consensus-QTLs. These QTLs were distributed on ten linkage groups(A1-6, A9, C2, C4 and C6). A major QTL(designated as q PN.A6)on A06 linkage group was detected, which explained 18.5% of phenotypic variance.2. To narrow down the QTL, large population was constructed and seven markers were used to genotype individuals. Based on phenotype and genotype data, the major QTL was narrowed down to approximately 120 Kb, including 26 annotated genes. In addition, through measurement for floral organ number at the final flowering and pod number at maturity of No.73290 and Zhongshuang11, we found that q PN.A6 increased ten pod number, however, increased 20 more floral organs in main inflorescence in NIL;3. RNA sequencing of the SAMs identified 9135 genes those were differentially expressed between the two parents. KEGG analysis showed that the top three overrepresented pathways were carbohydrate(707 genes), amino acid(390 genes) and lipid metabolisms(322 genes),which were belonged to metabolism. Gene ontology(GO) analysis showed that the top two enriched groups are S-assimilation and polyamine metabolism. To date, a total of 2296 transcription factors(TFs) have been identified and classified into 58 families in Arabidopsis. Based on the functional annotation of corresponding Arabidopsis homologous of these DEGs, nearly all TFs families(52 of the total 58 families) were found;4. Six candidate genes underlying q PN.A6 were identified and used to further functional validation by homologous annotation, differential expression analysis and bioinformatics analysis. Additionally, nine candidates underlying other QTLs were identified using differential expression analysis, DEGs annotation and bioinformatics analysis. Of the nine genes, Bna C06g29980 D, Bna C02g03640 D and Bna A01g22100 D were transcription factor-encoding gene, Bna A03g25890 D functions as an auxin receptor, Bna A03g29180 D and Bna A05g12220 D encode protein kinase, Bna C02g02900 D, Bna A03g29810 D and Bna C06g28880 D encode other molecules.