Evidence map›Paper›PMID 32938376›Full record

ArticleBMC bioinformatics2020

Multi-omics profiling reveals microRNA-mediated insulin signaling networks.

Yang-Chi-Dung Lin, Hsi-Yuan Huang, Sirjana Shrestha, Chih-Hung Chou, Yen-Hua Chen, Chi-Ru Chen, Hsiao-Chin Hong, Jing Li, Yi-An Chang, Men-Yee Chiew and 6 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

6 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
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  3. Article
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  5. Article
  6. Epigenetics, microRNA and Metabolic Syndrome: A Comprehensive Review.International journal of molecular sciences · 2021
    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

16 authors at 4 institutions in 3 countries.

Yang-Chi-Dung LinSchool of Life and Health Sciences, The Chinese University of Hong Kong, Longgang District, Shenzhen, 518172, Guangdong Province, China.
Hsi-Yuan HuangSchool of Life and Health Sciences, The Chinese University of Hong Kong, Longgang District, Shenzhen, 518172, Guangdong Province, China.
Sirjana ShresthaInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Chih-Hung ChouInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Yen-Hua ChenDepartment of Microbiology and Immunology, Weill Cornell Medicine, Cornell University, New York, NY, 10021, USA.
Chi-Ru ChenDepartment of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Hsiao-Chin HongSchool of Life and Health Sciences, The Chinese University of Hong Kong, Longgang District, Shenzhen, 518172, Guangdong Province, China.
Jing LiSchool of Life and Health Sciences, The Chinese University of Hong Kong, Longgang District, Shenzhen, 518172, Guangdong Province, China.
Yi-An ChangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Men-Yee ChiewDepartment of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Ya-Rong HuangInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Siang-Jyun TuInstitute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Ting-Hsuan SunDepartment of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan.
Shun-Long WengDepartment of Obstetrics and Gynecology, Hsinchu Mackay Memorial Hospital, Hsinchu, 300, Taiwan.
Ching-Ping TsengDepartment of Biological Science and Technology, National Chiao Tung University, Hsinchu, 300, Taiwan. cpts@cc.nctu.edu.tw.
Hsien-Da HuangSchool of Life and Health Sciences, The Chinese University of Hong Kong, Longgang District, Shenzhen, 518172, Guangdong Province, China. huanghsienda@cuhk.edu.cn.
National Yang Ming Chiao Tung University · TWChinese University of Hong Kong, Shenzhen · CNCornell University · USMackay Memorial Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicroRNAs (miRNAs) play a key role in mediating the action of insulin on cell growth and the development of diabetes. However, few studies have been conducted to provide a comprehensive overview of the miRNA-mediated signaling network in response to glucose in pancreatic beta cells. In our study, we established a computational framework integrating multi-omics profiles analyses, including RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) data analysis, inverse expression pattern analysis, public data integration, and miRNA targets prediction to illustrate the miRNA-mediated regulatory network at different glucose concentrations in INS-1 pancreatic beta cells (INS-1), which display important characteristics of the pancreatic beta cells.

resultsWe applied our computational framework to the expression profiles of miRNA/mRNA of INS-1, at different glucose concentrations. A total of 1437 differentially expressed genes (DEGs) and 153 differentially expressed miRNAs (DEmiRs) were identified from multi-omics profiles. In particular, 121 DEmiRs putatively regulated a total of 237 DEGs involved in glucose metabolism, fatty acid oxidation, ion channels, exocytosis, homeostasis, and insulin gene regulation. Moreover, Argonaute 2 immunoprecipitation sequencing, qRT-PCR, and luciferase assay identified Crem, Fn1, and Stc1 are direct targets of miR-146b and elucidated that miR-146b acted as a potential regulator and promising target to understand the insulin signaling network.

conclusionsIn this study, the integration of experimentally verified data with system biology framework extracts the miRNA network for exploring potential insulin-associated miRNA and their target genes. The findings offer a potentially significant effect on the understanding of miRNA-mediated insulin signaling network in the development and progression of pancreatic diabetes.

Indexed as

Gene Expression RegulationGene Regulatory NetworksHumansInsulinMicroRNAsSignal TransductionInsulinMicroRNAsmiRNAMulti-omicsPancreatic beta-cellRNA-seq

Identifiers

PMID32938376
PMCPMC7496206
OpenAlexW3086091645

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.