Evidence map›Paper›PMID 39141241›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

ChEC-Seq: A Comprehensive Guide for Scalable and Cost-Efficient Genome-Wide Profiling in Saccharomyces cerevisiae.

Tamar Gera, Divya Krishna Kumar, Gilad Yaakov, Naama Barkai, Felix Jonas

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. 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
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.

  1. aBIOTECH · 2025
    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

5 authors.

Tamar GeraDepartment of Molecular Genetics, Weizmann Institute, Rehovot, Israel.ORCID 0000-0002-8216-2411
Divya Krishna KumarDepartment of Molecular Genetics, Weizmann Institute, Rehovot, Israel.ORCID 0000-0002-8889-9262
Gilad YaakovDepartment of Molecular Genetics, Weizmann Institute, Rehovot, Israel.ORCID 0000-0002-9478-2298
Naama BarkaiDepartment of Molecular Genetics, Weizmann Institute, Rehovot, Israel.ORCID 0000-0002-2444-6061
Felix JonasSchool of Science, Constructor University, Bremen, Germany. fjonas@constructor.university.ORCID 0000-0001-7214-8942

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chromatin endogenous cleavage coupled with high-throughput sequencing (ChEC-seq) is a profiling method for protein-DNA interactions that can detect binding locations in vivo, does not require antibodies or fixation, and provides genome-wide coverage at near nucleotide resolution.The core of this method is an MNase fusion of the target protein, which allows it, when triggered by calcium exposure, to cut DNA at its binding sites and to generate small DNA fragments that can be readily separated from the rest of the genome and sequenced.Improvements since the original protocol have increased the ease, lowered the costs, and multiplied the throughput of this method to enable a scale and resolution of experiments not available with traditional methods such as ChIP-seq. This method describes each step from the initial creation and verification of the MNase-tagged yeast strains, over the ChEC MNase activation and small fragment purification procedure to the sequencing library preparation. It also briefly touches on the bioinformatic steps necessary to create meaningful genome-wide binding profiles.

Indexed as

Genome, FungalHigh-Throughput Nucleotide SequencingSaccharomyces cerevisiaeBinding SitesChromatinComputational BiologyMicrococcal NucleaseSequence Analysis, DNAChromatinMicrococcal NucleaseChEC-seqGenome-wideHigh-throughputIn vivo bindingS. cerevisiaeShort-read sequencingTranscription factors

Identifiers

What Socratic 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 Socratic graph.