Evidence map›Paper›PMID 33832988›Full record

ArticleGenes & development2021

AGO HITS-CLIP reveals distinct miRNA regulation of white and brown adipose tissue identity.

Sean O'Connor, Elisabeth A Murphy, Sarah K Szwed, Matt Kanke, François Marchildon, Praveen Sethupathy, Robert B Darnell, Paul Cohen

Open access · diamondAbstract read
In one paragraph

Article in Genes & development, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Review
  9. Frontiers in endocrinology · 2022
    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

8 authors at 2 institutions in 1 country.

Sean O'Connor *Laboratory of Molecular Metabolism, The Rockefeller University, New York, New York 10065, USA.
Elisabeth A Murphy *Laboratory of Molecular Neuro-Oncology, The Rockefeller University, New York, New York 10065, USA.
Sarah K SzwedLaboratory of Molecular Metabolism, The Rockefeller University, New York, New York 10065, USA.
Matt KankeDepartment of Biomedical Sciences, Cornell University, Ithaca, New York 14853, USA.
François MarchildonLaboratory of Molecular Metabolism, The Rockefeller University, New York, New York 10065, USA.
Praveen SethupathyDepartment of Biomedical Sciences, Cornell University, Ithaca, New York 14853, USA.
Robert B DarnellLaboratory of Molecular Neuro-Oncology, The Rockefeller University, New York, New York 10065, USA.ORCID 0000-0002-5134-8088
Paul CohenLaboratory of Molecular Metabolism, The Rockefeller University, New York, New York 10065, USA.
Rockefeller University · USCornell University · US

Funding

Weill Cornell/Rockefeller/Sloan-Kettering MST ProgramT32GM007739 · NIGMS · WEILL MEDICAL COLL OF CORNELL UNIV · PI HSU, KATHARINE C · 1985 to 2023
$51.1M
Stable Isotope and Metabolomics CoreP60DK020541 · NIDDK · YESHIVA UNIVERSITY · PI PESSIN, JEFFREY E. · 1986 to 2014
$29.8M
Translational Research CoreP30DK020541 · NIDDK · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI STREAMSON C CHUA · 2015 to 2026
$27.7M
The UNC Chapel Hill Superfund Research Program (UNC-SRP)P42ES031007 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI Rebecca Fry · 2020 to 2026
$22.2M
Combining New Molecular and Informatic Strategies to Find Hidden Ways to Treat Brain DiseaseR35NS097404 · NINDS · ROCKEFELLER UNIVERSITY · PI DARNELL, ROBERT B · 2017 to 2024
$9.0M
Molecular and Biological Functions of miR-29 in Lipid HomeostasisR01DK105965 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SETHUPATHY, PRAVEEN · 2016 to 2019
$1.4M
NIDDK NIH HHS P30 DK020541NIDDK NIH HHS P60 DK020541NIDDK NIH HHS R01 DK105965NIEHS NIH HHS P42 ES031007NIGMS NIH HHS T32 GM007739NINDS NIH HHS R35 NS097404
6 · The paper itself

Abstract

MicroRNAs (miRNAs) are short, noncoding RNAs that associate with Argonaute (AGO) to influence mRNA stability and translation, thereby regulating cellular determination and phenotype. While several individual miRNAs have been shown to control adipocyte function, including energy storage in white fat and energy dissipation in brown fat, a comprehensive analysis of miRNA activity in these tissues has not been performed. We used high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation (HITS-CLIP) to comprehensively characterize the network of high-confidence, in vivo mRNA:miRNA interactions across white and brown fat, revealing >20,000 unique AGO binding sites. When coupled with miRNA and mRNA sequencing, we found an inverse correlation between depot-enriched miRNAs and their targets. To illustrate the functionality of our HITS-CLIP data set in identifying specific miRNA:mRNA interactions, we show that miR-29 is a novel regulator of leptin, an adipocyte-derived hormone that coordinates food intake and energy homeostasis. Two independent miR-29 binding sites in the leptin 3' UTR were validated using luciferase assays, and miR-29 gain and loss of function modulated leptin mRNA and protein secretion in primary adipocytes. This work represents the only experimentally generated miRNA targetome in adipose tissue and identifies multiple regulatory pathways that may specify the unique identities of white and brown fat.

Indexed as

Chromatin Immunoprecipitation SequencingGene Expression RegulationAdipocytesAdipose TissueAnimalsArgonaute ProteinsBinding SitesCells, CulturedMiceMice, Inbred C57BLMicroRNAsRNA, MessengerArgonaute ProteinsMicroRNAsRNA, Messengeradiposebrown fatHITS-CLIPmiRNAwhite fat

Identifiers

PMID33832988
PMCPMC8091975
OpenAlexW3145297611

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.