A new RNASeq-based reference transcriptome for sugar beet and its application in transcriptome-scale analysis of vernalization and gibberellin responses.

摘要: Sugar beet (Beta vulgaris sp. vulgaris) crops account for about 30% of world sugar. yield is compromised by reproductive growth hence must remain vegetative until harvest. Prolonged exposure to cold temperature (vernalization) in the range 6°C 12°C induces growth, leading bolting (rapid elongation main stem) and flowering. Spring cultivation cool temperate climates makes them vulnerable vernalization bolting, which initiated apical shoot meristem processes involving interaction between gibberellin (GA) hormones vernalization. The underlying mechanisms are unknown genome scale next generation sequencing approaches now offer comprehensive strategies investigate them; enabling identification novel targets control sugar crops. In this study, we demonstrate application an mRNA-Seq based strategy purpose. There no reference genome, or public expression array platforms. We therefore used RNA-Seq generate first transcriptome. performed digital gene profiling using apex mRNA from two cultivars with without applied GA, also a vernalized cultivar GA. Subsequent bioinformatics analyses identified transcriptional changes associated genotypic difference experimental treatments. Analysis profiles response GA treatment suggested previously unsuspected roles RAV1-like AP2/B3 domain protein efflux transporters response. Next enabled transcriptome study global responses treatment, need established Comprehensive bioinformatic analysis programmes different genotypes as well biological treatments; thus providing important new opportunities basic scientists breeders. Transcriptome-scale agronomically traits should be widely applicable all crop plants where genomic resources limiting.