Evidence map›Paper›PMID 35704209›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Quantitative, Convenient, and Efficient Genome-Wide R-Loop Profiling by ssDRIP-Seq in Multiple Organisms.

Wei Xu, Kuan Li, Qin Li, Shuai Li, Jincong Zhou, Qianwen Sun

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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Wei Xu *Center for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Kuan Li *Center for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Qin LiCenter for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Shuai LiCenter for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Jincong ZhouCenter for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, China.
Qianwen SunCenter for Plant Biology, School of Life Sciences, Tsinghua University, Beijing, China. sunqianwen@mail.tsinghua.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

R-loop is a three-stranded chromatin structure, comprising one single-stranded DNA and another DNA:RNA hybrid strand, plays various and essential biological functions in many organisms. Developing a precise, efficient, faithful, and unbiased genome-wide R-loop detection method with extensive adaptability in all organisms is at the top priority for R-loop biology. Here, we provide a straightforward and highly efficient protocol for genome-wide strand-specific R-loop profiling in various organisms. In brief, genomic DNA is extracted and fragmented by the cocktail of restriction enzymes, and then the DNA:RNA hybrids are immunoprecipitated, following by the single-stranded DNA adaptor ligation and next-generation sequencing (named as ssDRIP-seq). Coupling with a straightforward and step-by-step bioinformatic pipeline, this method can provide high resolution and comprehensive strand-specific information for R-loop formation. ssDRIP-seq has been successfully applied for detecting R-loops from prokaryotes such as E. coli, to eukaryotes such as S. cerevisiae, mammalian cell culture and tissues, as well as plants Arabidopsis and rice, with high reproducibility and sensitivity.

Indexed as

DNA, Single-StrandedR-Loop StructuresAnimalsDNAEscherichia coliMammalsReproducibility of ResultsRNASaccharomyces cerevisiaeDNADNA, Single-StrandedRNAGenomeNext-generation sequencingNoncoding RNANucleic acidR-loop

Identifiers

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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.