Transcriptome and methylome profile of Brassica napus seed development

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Khan, Deirdre
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Brassica napus L. (canola) is one of the world’s most economically important oilseeds. Despite our growing knowledge of Brassica genetics, we still know little about the genes and gene regulatory networks underlying early seed development. We profiled the gene regulatory landscape of Brassica napus reproductive development using RNA sequencing. Global mRNA profiling revealed lower accumulation of Cn subgenome transcripts relative to the An subgenome. Subgenome-specific transcriptional networks identified distinct transcription factor families enriched in each of the An and Cn subgenome early in seed development. Data suggest subgenome bias are characteristic features of the B. napus seed throughout development. We characterize the transcription factor BnBZIP11, a putative regulator of early seed development, as proof of concept to validate our predictive regulatory networks. To deepen our understanding of the genome architecture underlying patterns of gene expression, we profiled the Brassica napus seed methylome. Seed development was characterized by large swathes of hypomethylation early in development, and aggressive de novo methylation of promoters and transposable elements during maturation. Taken together, our data indicate that in addition to subgenome expression bias, bias in DNA methylation is a characteristic feature of the B, napus seed throughout its development. We further expand on our transcriptome profile of the B. napus seed using LMD-RNAseq to profile the embryo, endosperm, and seed coat subregions throughout ovule development, morphogenesis, and maturation. The higher spatial resolution of our dataset results in a dramatic increase in transcript detection compared to whole seeds. We find the transition from morphogenesis to maturation represents the greatest transcriptional shift within the LMD-RNAseq dataset, regardless of subregion.
Brassica napus, Canola, Transcriptomics, Epigenetics, DNA methylation, Laser microdissection, Plant development, Seed biology, Data resource, Computational biology, Transcriptional networks, Transcription factors