Advances in Transcriptomics: Investigating Cardiovascular Disease at Unprecedented Resolution.

Whole genome transcriptional profiling has become a standard genomic approach to investigate biological processes. RNA sequencing (RNAseq) in particular has witnessed myriad applications in genetics and various biomedical fields. RNAseq involves a relatively simple experimental protocol of RNA extraction and cDNA library preparation, and because of decreasing next-generation sequencing cost and lower computational burden for data processing, has obtained a central role in the modern biology. The recent application of RNAseq methodology to single cell transcriptional profiling has enabled the more precise characterization of cell lineage and cell state genetic profiles. The development of bioinformatic and statistical tools have provided for differential gene expression (DE) analysis, RNA isoform analysis, haplotype specific analysis of gene expression (allele specific expression - ASE), and analysis of expression quantitative trait loci (eQTL). We give an overview of these and recent developments in RNAseq methodology with emphasis on quality control, read mapping, feature counting, DE, ASE and eQTL analysis, and fusion transcript detection. We describe utilization of RNAseq as a diagnostic tool in Mendelian diseases, complex phenotypes and cancer and give an overview of long read RNAseq technology. Furthermore, we discuss in detail the recent revolution in single cell transcriptomics that is reshaping modern biology.

全基因组转录谱分析已成为研究生物过程的一种标准基因组学方法。特别是RNA测序（RNAseq）在遗传学和各种生物医学领域有着无数的应用。RNAseq涉及相对简单的RNA提取和cDNA文库制备实验流程，并且由于下一代测序成本的降低以及数据处理的计算负担减轻，它在现代生物学中占据了核心地位。最近RNAseq方法在单细胞转录谱分析中的应用使得细胞谱系和细胞状态基因谱能够得到更精确的表征。生物信息学和统计学工具的发展为差异基因表达（DE）分析、RNA异构体分析、基因表达的单倍型特异性分析（等位基因特异性表达 - ASE）以及表达数量性状位点（eQTL）分析提供了条件。我们对RNAseq方法的这些方面以及近期的发展进行了综述，重点关注质量控制、读段比对、特征计数、DE、ASE和eQTL分析以及融合转录本检测。我们描述了RNAseq作为孟德尔疾病、复杂表型和癌症的诊断工具的应用，并对长读长RNAseq技术进行了综述。此外，我们详细讨论了正在重塑现代生物学的单细胞转录组学的近期革命。