Evidence map›Paper›PMID 31956652›Full record

ArticleFrontiers in bioengineering and biotechnology2019

A Novel Approach to Identify Enhancer lincRNAs by Integrating Genome, Epigenome, and Regulatome.

Hui Liu, Tiantongfei Jiang, Shuyuan Wang, Xiang Chen, Xiaoyan Jin, Qi Wang, Xinhui Li, Jiaqi Yin, Tingting Shao, Yongsheng Li and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 56% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

12 authors at 3 institutions in 1 country.

Hui LiuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Tiantongfei JiangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Shuyuan WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xiang ChenCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xiaoyan JinCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qi WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xinhui LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jiaqi YinCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Tingting ShaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yongsheng LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Juan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Qiong WuSchool of Life Science and Technology, Harbin Institute of Technology, Harbin, China.
Harbin Medical University · CNHainan Medical University · CNHarbin Institute of Technology · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

LincRNAs enriched with high H3K4me1 and low H3K4me3 signals often have the enhancer-like features which are named as enhancer-associated lincRNAs (elincRNAs). ElincRNAs are considered to be indispensable for target gene transcription, which play important roles in development, signaling events, and even diseases. In this study, we developed a regularized regression model to identify elincRNAs by integrating the genomic, epigenomic, and regulatory data. Application of the proposed method to mouse ESCs reveals that besides the basic well-known epigenetic features H3K4me1 and H3K4me3, more specific epigenetic features, such as high DNA methylation, high H3K122ac, and H3K36me3 were contributed to mark elincRNAs with the best accuracy and precision. Finally, 3729 elincRNAs were identified in mouse ESCs. Furthermore, the elincRNAs and canonical lincRNAs exhibit distinct genomic features, and elincRNAs have the higher CGI enrichment and lower sequence conservation. Through the analysis of transcription regulation, we found that elincRNAs were significantly regulated by NANOG, POU5F1, SOX2 and ESRRB, and were involved in the core transcriptional regulatory circuitry controlling ES cell state Function enrichment analysis further discovered that elincRNAs tended to regulate specific embryonic development biological processes. These results indicated that these two types of lincRNAs had both specific epigenetic and transcriptional regulation mechanism and display distinct functional characters. In conclusion, we presented a credible computational model to prioritize novel elincRNAs, and depicted the atlas of elincRNAs in mouse ESCs, which would help dissect the function roles of lncRNAs during the mammalian development and diseases.

Indexed as

enhancer lincRNAepigenomemouse embryonic stem cellregularized regression modelregulatome

Identifiers

PMID31956652
PMCPMC6951418
OpenAlexW2996675351

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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.