基于RNA-seq数据识别胚胎发育相关的lncRNA及新候选lncRNA的鉴定及功能研究

Non-coding RNA are closely related to the regulation of gene expression and embryonic development on the level of epigenetic and post-transcriptional. The potential long non-coding RNA (lncRNA) associated with the developmen have been predicted by based on bioinformatics methods. The candidate lncRNAs are screened by using transcriptome reconstruction methods based on RNA-seq data, combined with functional data, including of histone modifications, cDNA, coding potentials screening and so on. The specific expression patterns and transcripts are studied during mouse different development stages. The over-expression vector containing the full length of candidate lncRNA and the knockout vector are constructed except for making mouse models. By high-throughput microarray and histological changes analysis, the functions of the candidate lncRNA are initially identified, initial recognition, furthermore, the interaction network among lncRNA, miRNA and mRNA are constructed. The study of this project will enrich the lncRNA library, especially the lncRNAs which closely related to embryonic development, and clarify the mechanism of lncRNAs during embryonic development. This study will provide new ideas for future epigenetic studies, stem cell differentiation, developmental regulation and tumor risk assessment.

非编码RNA在表观遗传及转录后调控等层面上调控基因表达并与胚胎发育密切相关。我们基于生物信息学方法预测出潜在与发育关联的长非编码RNA（lncRNA）。利用RNA-seq数据为基础的转录组重建方法并结合功能数据包括组蛋白修饰、cDNA和编码潜能等筛选候选的lncRNA。对候选的发育相关的新lncRNA进行实验验证。采取不同发育阶段的胚胎，通过分子生物学手段确定其时空特异表达模式及转录本。构建候选lncRNA的全长过表达载体及敲除载体，制作候选lncRNA的小鼠模型。通过高通量芯片分析及组织形态学变化，初步确认候选lncRNA的功能，在此基础上，构建lncRNA、miRNA和mRNA的互作网络。本课题的成果将丰富已有lncRNA库，尤其是胚胎发育密切相关的lncRNA，并阐明lncRNA在胚胎发育过程中的作用机制。为今后表观遗传学研究、干细胞分化、发育的调控和肿瘤的风险评估提供新的思路。

长非编码RNAs（lncRNAs）在胚胎发育、癌症、疾病等过程中发挥重要作用，而目前公共数据库中小鼠lncRNAs数据较少。脑组织是lncRNAs表达的主要器官，预测脑表达lncRNAs对于全面识别小鼠脑发育相关的lncRNAs及认识其在脑发育中的作用具有重要意义。本课题对已有的RNS-seq流程进行优化，筛选胚胎脑发育相关的基金间、内含子和顺反义3种类型lncRNAs，分别从基因组、转录组、表观基因组和功能基因组学方法表征胚胎脑发育新lncRNAs，结果表明新lncRNAs具有相对完整的基因结构及较低的编码潜能，具有与已知lncRNAs相似的组织特异性，并与典型的染色质修饰相关。利用LASSO调整罗杰斯特回归模型来筛选lncRNAs和编码转录本之间的基因组和表观基因组学差异。研究lncRNAs与临近编码基因的关系后发现lncRNAs倾向于与临近编码基因共表达，表明lncRNAs可能调控临近基因。我们选取了LncRNA-Ptma，利用Northen和RACE获取了该lncRNAs的全长，并验证了其调控功能。最后，本课题对lncRNAs合集中脑表达的lncRNAs进行筛选，对其进行基因组和功能基因组注释，构建了Incbrain注释平台。