Single Cell RNA-Sequencing for the Study of Atherosclerosis

Atherosclerosis is a major cause of coronary artery disease and stroke. A massive and new type of data has finally arrived in the field of atherosclerosis: single cell RNA sequencing (scRNAseq). Recently, scRNAseq has been successfully applied to the study of atherosclerosis to identify previously uncharacterized cell populations. scRNAseq is an effective approach to evaluate heterogeneous cell populations by measuring the transcriptomic profiles at the single cell level. Besides the studies of atherosclerosis, scRNAseq is being employed in various areas of biology, including cancer research and organ development. In order to analyze these new massive datasets, various analytic approaches have been developed. This review aims to enhance the understanding of this new technology by exploring how the single cell transcriptome has been applied to the study of atherosclerosis and further discuss potential analysis of using scRNAseq.

Human Transcriptome and Chromatin Modifications: An ENCODE Perspective

A decade-long project, led by several international research groups, called the Encyclopedia of DNA Elements (ENCODE), recently released an unprecedented amount of data. The ambitious project covers transcriptome, cistrome, epigenome, and interactome data from more than 1,600 sets of experiments in human. To make use of this valuable resource, it is important to understand the information it represents and the techniques that were used to generate these data. In this review, we introduce the data that ENCODE generated, summarize the observations from the data analysis, and revisit a computational approach that ENCODE used to predict gene expression, with a focus on the human transcriptome and its association with chromatin modifications.