Evidence map›Paper›PMID 42106557›Full record

ArticleCommunications biology2026

Gel-free library preparation for next-generation RNA sequencing and small RNA quantification.

Ruixi Chen, Daniel Yim, Lili Liu, Michael S DeMott, Bo Cao, Peter C Dedon

Abstract read
In one paragraph

Article in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ruixi ChenDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Daniel YimAntimicrobial Resistance IRG, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore.ORCID http://orcid.org/0000-0001-6153-4725
Lili LiuAntimicrobial Resistance IRG, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore.
Michael S DeMottDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Bo CaoSchool of Life Sciences and Biotechnology, Shanghai Jiaotong University, Shanghai, PR China.
Peter C DedonDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. pcdedon@mit.edu.ORCID http://orcid.org/0000-0003-0011-3067

Funding

TOXICOLOGY CORE UNITP30ES002109 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LEVINE, STUART S · 1985 to 2020
$25.6M
Supplement: Epigenetics of the Human Gut MicrobiomeR01ES031576 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI ALM, ERIC JOHN, DEDON, PETER C · 2019 to 2023
$1.9M
NIEHS NIH HHS P30 ES002109NIEHS NIH HHS R01 ES031576U.S. Department of Health & Human Services | NIH | National Institute of Environmental Health Sciences (NIEHS) ES031576
6 · The paper itself

Abstract

Next-generation RNA sequencing (RNA-seq) is hampered by "primer dimer" (PD) artifacts and its quantitative performance reduced by polymerase fall-off (PF) at RNA modifications and secondary structures. Here we improve RNA-seq efficiency by incorporating (i) a post-reverse-transcription (RT) digestion of excess primers with Escherichia coli exonuclease I for PD mitigation, thus obviating gel purification during RNA-seq library preparation, and (ii) a high-processivity reverse transcriptase to increase full-length reads. A full factorial experimental design is applied to absolute quantification RNA sequencing (AQRNA-seq), the most accurate NGS-based method for quantifying small RNAs, using cDNA libraries constructed from E. coli small RNAs (>85% tRNA) followed by sequencing, data processing, and data analysis. The novel PF and PD mitigation approaches increased AQRNA-seq sensitivity >10-fold by minimizing PF and maximizing target RNA reads. By increasing sensitivity and obviating gel electrophoresis for removing PD, AQRNA-seq and other NGS-based RNA-seq methods can now be automated to increase throughput and reduce RNA sample size.

Indexed as

Gene LibraryHigh-Throughput Nucleotide SequencingSequence Analysis, RNAEscherichia coli

Identifiers

PMID42106557
PMCPMC13376629

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.