Sign in
GenomicsScientific Reports
Peer-reviewed journal article

Improved TGIRT-seq methods for comprehensive transcriptome profiling with decreased adapter dimer formation and bias correction

Hengyi XuiD, Jun YaoiD, Douglas C. WuiD, Alan M. LambowitziD

Abstract

Thermostable group II intron reverse transcriptases (TGIRTs) with high fidelity and processivity have been used for a variety of RNA sequencing (RNA-seq) applications, including comprehensive profiling of whole-cell, exosomal, and human plasma RNAs; quantitative tRNA-seq based on the ability of TGIRT enzymes to give full-length reads of tRNAs and other structured small ncRNAs; high-throughput mapping of post-transcriptional modifications; and RNA structure mapping. Here, we improved TGIRT-seq methods for comprehensive transcriptome profiling by (i) rationally designing RNA-seq adapters that minimize adapter dimer formation, and (ii) developing biochemical and computational methods that remediate 5- and 3-end biases. These improvements, some of which may be applicable to other RNA-seq methods, increase the efficiency of TGIRT-seq library construction and improve coverage of very small RNAs, such as miRNAs. Our findings provide insight into the biochemical basis of 5- and 3-end biases in RNA-seq and suggest general approaches for remediating biases and decreasing adapter dimer formation.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
75
FWCI
2.57
Field percentile
top 9%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISLentzsch '19Colville '26Ferguson '24Pedor '26Di '20Shivram '18
63% semantic matchMolecular Biology
Alfred M. Lentzsch, Jun Yao, Rick Russell+1 more·Journal of Biological Chemistry·Nov 11, 2019· 22 citations