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 β-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.
journal_name
Genome Resjournal_title
Genome researchauthors
Derr A,Yang C,Zilionis R,Sergushichev A,Blodgett DM,Redick S,Bortell R,Luban J,Harlan DM,Kadener S,Greiner DL,Klein A,Artyomov MN,Garber Mdoi
10.1101/gr.207902.116subject
Has Abstractpub_date
2016-10-01 00:00:00pages
1397-1410issue
10eissn
1088-9051issn
1549-5469pii
gr.207902.116journal_volume
26pub_type
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