UMMS Affiliation

Program in Bioinformatics and Integrative Biology; Program in Molecular Medicine, Diabetes Center of Excellence; Department of Medicine

Publication Date

2016-10-01

Document Type

Article

Disciplines

Biochemistry | Bioinformatics | Computational Biology | Genomics | Integrative Biology | Molecular Biology | Molecular Genetics

Abstract

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.

Rights and Permissions

© 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

10.1101/gr.207902.116

Source

Genome Res. 2016 Oct;26(10):1397-1410. Epub 2016 Jul 28. Link to article on publisher's site

Journal/Book/Conference Title

Genome research

Related Resources

Link to Article in PubMed

PubMed ID

27470110

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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