Evidence map›Paper›PMID 36062164›Full record

ArticleNAR genomics and bioinformatics2022

Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes.

Matthew Lalli, Allen Yen, Urvashi Thopte, Fengping Dong, Arnav Moudgil, Xuhua Chen, Jeffrey Milbrandt, Joseph D Dougherty, Robi D Mitra

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. bioRxiv : the preprint server for biology · 2026
    Article
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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

9 authors.

Matthew LalliDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.ORCID https://orcid.org/0000-0003-0419-1206
Allen YenDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.ORCID https://orcid.org/0000-0002-3984-541X
Urvashi ThopteSeaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Fengping DongDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.
Arnav MoudgilDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.ORCID https://orcid.org/0000-0002-0544-3463
Xuhua ChenDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.
Jeffrey MilbrandtDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.ORCID https://orcid.org/0000-0002-5477-7689
Joseph D DoughertyDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.
Robi D MitraDepartment of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.ORCID https://orcid.org/0000-0002-2680-4264

Funding

WUIDDRC Supplement-Supporting the health and well-being of children with intellectual and developmental disability during COVID-19 pandemicP50HD103525 · NICHD · WASHINGTON UNIVERSITY · PI JOSEPH D DOUGHERTY, Natasha Marrus · 2020 to 2026
$15.5M
INSTITUTIONAL TRAINING GRANT IN GENOMIC SCIENCET32HG000045 · NHGRI · WASHINGTON UNIVERSITY · PI MICHAEL R BRENT, Barak A Cohen · 1997 to 2026
$8.4M
Molecular recording to predict cell fate decisions and animal behaviorRF1MH126723 · NIMH · WASHINGTON UNIVERSITY · PI DOUGHERTY, JOSEPH D, MITRA, ROBI D · 2021 to 2021
$3.7M
PARALLEL ANALYSIS OF TRANSCRIPTION AND PROTEIN-DNAINTERACTIONS IN SINGLE CNS CELLSRF1MH117070 · NIMH · WASHINGTON UNIVERSITY · PI DOUGHERTY, JOSEPH D, MITRA, ROBI D · 2018 to 2020
$3.2M
NHGRI NIH HHS T32 HG000045NICHD NIH HHS P50 HD103525NIMH NIH HHS RF1 MH117070NIMH NIH HHS RF1 MH126723
6 · The paper itself

Abstract

Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover

Identifiers

PMID36062164
PMCPMC9428926

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Registered trials

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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.