Evidence map›Paper›PMID 36449161›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Quantification of LINE-1 RNA Expression from Bulk RNA-seq Using L1EM.

Wilson McKerrow

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 67% of its field
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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Review
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

1 author at 1 institution in 1 country.

Wilson McKerrowInstitute for Systems Genetics, NYU Langone Health, New York, NY, USA. willmckerrow@gmail.com.
Institute for Systems Biology · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

LINE-1 retrotransposons have the potential to cause DNA damage, contribute to genome instability, and induce an interferon response. Thus, accurate measurements of their expression, especially in disease contexts where genome instability and the interferon response are relevant, are of particular importance. Illumina-based bulk RNA sequencing remains the most abundant datatype for measuring gene expression. However, "active" expression from its own internal promoter is only one source of LINE-1 aligning reads in an RNA-seq experiment. With about half a million LINE-1 sequences scattered throughout the genome, many are incorporated into other transcripts that have nothing to do with LINE-1 activity. We call this "passive" co-transcription. Here we will describe how to use L1EM, a computational method that separates active from passive LINE-1 expression at the locus-specific level.

Indexed as

Antiviral AgentsInterferonsExome SequencingGenomic InstabilityHumansRNARNA-SeqAntiviral AgentsInterferonsRNACo-transcriptionL1LINE-1RNA-seqShort readsTransposable elements

Identifiers

PMID36449161
OpenAlexW4310425532

What OpenQuestion holds

Textmetadata
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.