Evidence map›Paper›PMID 39026715›Full record

ArticlebioRxiv : the preprint server for biology2024

Improved characterization of single-cell RNA-seq libraries with paired-end avidity sequencing.

John T Chamberlin, Austin E Gillen, Aaron R Quinlan

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

5 · Who and what money

Authors and funding

3 authors.

John T ChamberlinDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA.ORCID 0000-0003-0267-0385
Austin E GillenRNA Bioscience Initiative, University of Colorado School of Medicine, Aurora, CO, 80045, USA.ORCID 0000-0003-2928-6308
Aaron R QuinlanDepartment of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA.ORCID 0000-0003-1756-0859

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
From genomics to natural language processing: A protected environment for research computing in the health scienceS10OD021644 · OD · UNIVERSITY OF UTAH · PI CHEATHAM, THOMAS E. · 2017 to 2017
$494k
NIH HHS S10 OD021644NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

Prevailing poly(dT)-primed 3' single-cell RNA-seq protocols generate barcoded cDNA fragments containing the reverse transcriptase priming site, which is expected to be the poly(A) tail or a genomic adenine homopolymer. Direct sequencing across this priming site was historically difficult because of DNA sequencing errors induced by the homopolymeric primer at the 'barcode' end. Here, we evaluate the capability of "avidity base chemistry" DNA sequencing from Element Biosciences to sequence through this homopolymer accurately, and the impact of the additional cDNA sequence on read alignment and precise quantification of polyadenylation site usage. We find that the Element Aviti instrument sequences through the thymine homopolymer into the subsequent cDNA sequence without detectable loss of accuracy. The resulting paired-end alignments enable direct and independent assignment of reads to polyadenylation sites, which bypasses complexities and limitations of conventional approaches but does not consistently improve read mapping rates compared to single-end alignment. We also characterize low-level artifacts and arrive at an adjusted adapter trimming and alignment workflow that significantly improves the alignment of sequence data from Element and Illumina, particularly in the context of extended read lengths. Our analyses confirm that Element avidity sequencing is an effective alternative to Illumina sequencing for standard single-cell RNA-seq, particularly for polyadenylation site analyses but do not rule out the potential for similar performance from other emerging platforms.

Identifiers

PMID39026715
PMCPMC11257511

What OpenQuestion holds

Textmetadata
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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.