Evidence map›Paper›PMID 33111104›Full record

ArticleSTAR protocols2020

Tissue-Specific

Martyna Lukoseviciute, Irving T C Ling, Upeka Senanayake, Ivan Candido-Ferreira, Gunes Taylor, Ruth M Williams, Tatjana Sauka-Spengler

Open access · goldAbstract read
In one paragraph

Article in STAR protocols, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
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

7 authors at 1 institution in 1 country.

Martyna LukoseviciuteUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
Irving T C LingUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
Upeka SenanayakeUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
Ivan Candido-FerreiraUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
Gunes TaylorUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
Ruth M WilliamsUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
Tatjana Sauka-SpenglerUniversity of Oxford, MRC Weatherall Institute for Molecular Medicine, John Radcliffe, Oxford OX3 9DS, UK.
University of Oxford · GB

Funding

Medical Research Council G0902418Wellcome TrustWellcome Trust 215615/Z/19/Z
6 · The paper itself

Abstract

Chromatin immunoprecipitation with sequencing (ChIP-seq) has been instrumental in understanding transcription factor (TF) binding during gene regulation. ChIP-seq requires specific antibodies against desired TFs, which are not available for numerous species. Here, we describe a tissue-specific biotin ChIP-seq protocol for zebrafish and chicken embryos which utilizes AVI tagging of TFs, permitting their biotinylation by a co-expressed nuclear biotin ligase. Subsequently, biotinylated factors can be precipitated with streptavidin beads, enabling the user to construct TF genome-wide binding landscapes like conventional ChIP-seq methods. For complete details on the use and execution of this protocol, please see Lukoseviciute et al. (2018) and Ling and Sauka-Spengler (2019).

Indexed as

AnimalsBiotinCells, CulturedChickensChromatin ImmunoprecipitationOrgan SpecificitySequence Analysis, DNAStreptavidinTranscription FactorsZebrafishBiotinStreptavidinTranscription Factors

Identifiers

PMID33111104
PMCPMC7580215
OpenAlexW3046591340

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.