Program in Bioinformatics and Integrative Biology; Program in Molecular Medicine, Diabetes Center of Excellence; Department of Medicine
Biochemistry | Bioinformatics | Computational Biology | Genomics | Integrative Biology | Molecular Biology | Molecular Genetics
RNA-seq protocols that focus on transcript termini are well suited for applications in which template quantity is limiting. Here we show that, when applied to end-sequencing data, analytical methods designed for global RNA-seq produce computational artifacts. To remedy this, we created the End Sequence Analysis Toolkit (ESAT). As a test, we first compared end-sequencing and bulk RNA-seq using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). As predicted by the telescripting model for transcriptional bursts, ESAT detected an LPS-stimulated shift to shorter 3'-isoforms that was not evident by conventional computational methods. Then, droplet-based microfluidics was used to generate 1000 cDNA libraries, each from an individual pancreatic islet cell. ESAT identified nine distinct cell types, three distinct beta-cell types, and a complex interplay between hormone secretion and vascularization. ESAT, then, offers a much-needed and generally applicable computational pipeline for either bulk or single-cell RNA end-sequencing.
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© 2016 Derr et al. This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
DOI of Published Version
Genome Res. 2016 Oct;26(10):1397-1410. Epub 2016 Jul 28. Link to article on publisher's site
Derr AG, Yang C, Zilionis R, Sergushichev A, Blodgett D, Redick SD, Bortell R, Luban J, Harlan DM, Kadener S, Greiner DL, Klein A, Artyomov MN, Garber M. (2016). End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data. Program in Molecular Medicine Publications and Presentations. https://doi.org/10.1101/gr.207902.116. Retrieved from https://escholarship.umassmed.edu/pmm_pp/75
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.