Rothamsted Research-Broom's Barn, Department of Applied Crop Science, Higham, Bury St Edmunds, Suffolk IP26 6NP, UK.
BMC Genomics. 2012 Mar 19;13:99. doi: 10.1186/1471-2164-13-99.
Sugar beet (Beta vulgaris sp. vulgaris) crops account for about 30% of world sugar. Sugar yield is compromised by reproductive growth hence crops must remain vegetative until harvest. Prolonged exposure to cold temperature (vernalization) in the range 6 °C to 12 °C induces reproductive growth, leading to bolting (rapid elongation of the main stem) and flowering. Spring cultivation of crops in cool temperate climates makes them vulnerable to vernalization and hence bolting, which is initiated in the apical shoot meristem in processes involving interaction between gibberellin (GA) hormones and vernalization. The underlying mechanisms are unknown and genome scale next generation sequencing approaches now offer comprehensive strategies to investigate them; enabling the identification of novel targets for bolting control in sugar beet crops. In this study, we demonstrate the application of an mRNA-Seq based strategy for this purpose.
There is no sugar beet reference genome, or public expression array platforms. We therefore used RNA-Seq to generate the first reference transcriptome. We next performed digital gene expression profiling using shoot apex mRNA from two sugar beet cultivars with and without applied GA, and also a vernalized cultivar with and without applied GA. Subsequent bioinformatics analyses identified transcriptional changes associated with genotypic difference and experimental treatments. Analysis of expression profiles in response to vernalization and GA treatment suggested previously unsuspected roles for a RAV1-like AP2/B3 domain protein in vernalization and efflux transporters in the GA response.
Next generation RNA-Seq enabled the generation of the first reference transcriptome for sugar beet and the study of global transcriptional responses in the shoot apex to vernalization and GA treatment, without the need for a reference genome or established array platforms. Comprehensive bioinformatic analysis identified transcriptional programmes associated with different sugar beet genotypes as well as biological treatments; thus providing important new opportunities for basic scientists and sugar beet breeders. Transcriptome-scale identification of agronomically important traits as used in this study should be widely applicable to all crop plants where genomic resources are limiting.
糖用甜菜（Beta vulgaris sp. vulgaris）作物约占世界糖产量的 30%。生殖生长会降低糖产量，因此作物在收获前必须保持营养生长。在 6°C 到 12°C 的范围内，长时间暴露于低温（春化作用）会诱导生殖生长，导致抽薹（主茎迅速伸长）和开花。在凉爽的温带气候中种植作物，使它们容易受到春化作用和抽薹的影响，而春化作用是在顶端分生组织中启动的，涉及赤霉素（GA）激素和春化作用的相互作用。其潜在机制尚不清楚，而基于基因组规模的下一代测序方法现在提供了全面的策略来研究这些机制；能够为糖用甜菜作物的抽薹控制确定新的目标。在这项研究中，我们展示了一种基于 mRNA-Seq 的策略的应用。
没有糖用甜菜参考基因组或公共表达数组平台。因此，我们使用 RNA-Seq 生成了第一个参考转录组。接下来，我们使用来自两个具有和不具有施加 GA 的糖用甜菜品种以及一个施加 GA 的春化品种的顶端分生组织 mRNA 进行数字基因表达谱分析。随后的生物信息学分析确定了与基因型差异和实验处理相关的转录变化。对春化作用和 GA 处理的表达谱分析表明，RAV1 样 AP2/B3 结构域蛋白在春化作用以及外排转运蛋白在 GA 反应中的作用以前未被怀疑。
下一代 RNA-Seq 使我们能够为糖用甜菜生成第一个参考转录组，并研究顶端分生组织对春化作用和 GA 处理的全转录响应，而无需参考基因组或已建立的数组平台。全面的生物信息学分析确定了与不同糖用甜菜基因型以及生物处理相关的转录程序；从而为基础科学家和糖用甜菜育种者提供了重要的新机会。本研究中使用的基于转录组的鉴定农艺性状的方法应该广泛适用于所有基因组资源有限的作物植物。
