End Sequence Analysis ToolKit (ESAT) expands the extractable from single cell RNA-seq experiments

RNA­seq protocols that focus on transcript termini are well­suited for applications in which template quantity is limiting. Here we show that, when applied to end­sequencing data, analytical methods designed for global RNA­seq produce computational artifacts. To remedy this we created the End Sequence Analysis Toolkit (ESAT). As a test, we first compared end­sequencing and bulk RNA­seq using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). As predicted by the telescripting model for transcriptional bursts, ESAT detected an LPS­stimulated shift to shorter 3’­isoforms that was not evident by conventional computational methods. Then, droplet­based microfluidics was used to generate 1,000 cDNA libraries, each from an individual pancreatic islet cell. ESAT identified 9 distinct cell types, three distinct β­cell types, and a complex interplay between hormone secretion and vascularization. ESAT, then, offers a much­needed and generally applicable computational pipeline for either bulk or single cell RNA end­sequencing. Cold Spring Harbor Laboratory Press on August 10, 2016 Published by genome.cshlp.org Downloaded from