Cited by 219MicroRNA in disease regulationRNA Research and SplicingRNA regulation and disease

The DOI matches its Crossref record; 66 of the 67 references it cites were found in a registry or an index; 10 of the 46 sources its claims cite were checked for support.

Transcriptome-wide Discovery of microRNA Binding Sites in Human Brain

Open access

Abstract

Summary The orchestration of brain function requires complex gene regulatory networks that are modulated, in part, by microRNAs (miRNAs). These noncoding RNAs associate with argonaute (Ago) proteins in order to direct posttranscriptional gene suppression via base pairing with target transcripts. In order to better understand how miRNAs contribute to human-specialized brain processes and neurological phenotypes, identifying their targets is of paramount importance. Here, we address the latter by profiling Ago2:RNA interactions using HITS-CLIP to generate a transcriptome-wide map of miRNA binding sites in human brain. We uncovered ∼7,000 stringent Ago2 binding sites that are highly enriched for conserved sequences corresponding to abundant brain miRNAs. This interactome points to functional miRNA:target pairs across >3,000 genes and represents a valuable resource for accelerating our understanding of miRNA functions in brain. We demonstrate the utility of this map for exploring clinically relevant miRNA binding sites that may facilitate the translation of genetic studies of complex neuropsychiatric diseases into therapeutics.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This paper uses Ago2 HITS-CLIP to map microRNA binding sites transcriptome-wide in human brain, identifying 7,153 high-confidence Ago2 clusters across >3,300 genes. It demonstrates the resource’s utility by validating disease-relevant miRNA:target interactions, including miR-137 and miR-23b targets, and by intersecting sites with neuropsychiatric disease-associated SNPs.

Key findings

  • Ago2 HITS-CLIP in 11 adult human brain samples yielded 7,153 high-confidence Ago2 brain clusters (Bonferroni adjusted p < 5%) associated with >3,300 brain-expressed genes; >80% of clusters were ≤60 nt, and only 6% were >100 nt.
  • Clusters were highly enriched for conserved sequences matching abundant brain miRNA seeds: the top five seed families (Let-7, miR-125, miR-124, miR-9, and miR-29) comprised nearly 55% of total Ago2 seed load, and the top 20 seeds accounted for 75%.
  • 97% of clusters resided within mRNA transcripts, with 41% in 3′ UTRs and 40% in coding regions; >25% of 3′ UTR clusters overlapped TargetScan-predicted conserved miRNA binding sites (>2-fold enrichment, p < 2.2 × 10−16).
  • Intersection with mouse brain Ago HITS-CLIP identified 646 shared regions (~5-fold enrichment, p < 2.2 × 10−16); 59% were in coding regions. For miR-137, 88 putative sites were found, 24 within schizophrenia-related and/or prefrontal-cortex-correlated genes, and all seven tested 3′ UTR reporters were suppressed by miR-137 (~30%–50% silencing).

Methods

  • Ago2 HITS-CLIP was performed on 11 postmortem adult human brain samples from motor cortex and cingulate gyrus (all male, ages 44–68), with immunoprecipitation using anti-Ago2-3148, RNA linker ligation, RT-PCR, and Illumina Hi-Seq 2000 sequencing.
  • Reads were mapped to hg19 and miRBase; peak calling used a zero-truncated negative binomial model with Fisher’s method across replicates and Bonferroni correction, merging significant positions within 60 nt and extending short regions to 50 nt.
  • Functional validation included microarray analyses of miRNA overexpression/inhibition datasets and luciferase reporter assays in HEK 293 cells for selected 3′ UTRs and SNP alleles.

Limitations

  • The paper states that human and mouse Ago HITS-CLIP datasets had a larger proportion of nonoverlapping sites than shared sites, which could reflect species, developmental stage, transcriptome/miRNA differences, pan-Ago versus Ago2 antibody, or peak-calling criteria.
  • The paper notes an inherent bias toward identifying Ago2 binding sites in higher-expressed transcripts, and it states that additional studies are needed to determine whether miRNA targeting diverges across species.
  • Evident from the text: the human data are limited to 11 adult male postmortem samples from motor cortex and cingulate gyrus, so findings may not generalize to other brain regions, females, developmental stages, or disease states; luciferase and microarray validations were performed in cultured cells rather than human brain tissue.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.neuron.2013.10.062

Cites

66 of 66 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

10 of 46 cited sources checked · 5 supported · 0 flagged · accuracy not yet measured

  • It may state two separate claims as one. 26
  • Probably not a substantial claim. 27
  • The quote only partly states this claim. 1
46 of 46
  • The paper relies on this without support.

    Bioinformatic approaches tend to overpredict miRNA binding sites.

    “Bioinformatic approaches tend to overpredict miRNA binding sites, supporting the need for complementary wet lab data to assist with identifying bona fide interactions.”
  • The paper relies on this without support.

    Transcriptional and proteomic profiling studies are unable to discern whether observed changes in gene expression are the result of direct miRNA:target interactions.

    “Transcriptional and proteomic profiling studies have aided the search for functional miRNA target sites; however, these approaches are unable to discern whether observed changes in gene expression are the result of direct miRNA:target interactions.”
  • The authors state this as an assumption.

    For each gene in a given sample, the height of each position follows a Poisson distribution (yi ∼ Poisson(λi), yi > 0).

    “For each gene in a given sample, we assume that the height of each position follows the Poisson distribution, yi ∼Poisson (λi), yi > 0.”
  • The authors state this as an assumption.

    λi, the expected height for position i, is a random variable following a gamma distribution (λi ∼ Gamma(1/α, α)).

    “λi is the expected height for position 1, and it is a random variable following a gamma distribution, λi ∼Gamma (1/α, α), where α is the overdispersion parameter.”
4 of 4

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Metadata

Authors
Boudreau, R. L., Jiang, P., Gilmore, B. L., Spengler, R. M., Tirabassi, R., Nelson, J. A., Ross, C. A., Xing, Y., & Davidson, B. L.
Affiliations
  • University of Iowa (US)
  • Oregon Health & Science University (US)
  • Johns Hopkins University (US)
Corresponding author
  • Xing, Yi
  • Davidson, Beverly L.
Venue
Neuron
Publisher
Elsevier BV
Published
2014-01
Volume
81
Issue
2
Pages
294-305
ISSN
0896-6273 (ISSN-L)
OpenAlex
W1965173359
Cited by
217
References
67
Citations by year
2026: 7 · 2025: 14 · 2024: 11 · 2023: 14 · 2022: 24 · 2021: 23 · 2020: 15 · 2019: 16 · 2018: 21 · 2017: 23 · 2016: 17 · 2015: 16 · 2014: 15
FWCI
7.36
Type
journal article
Language
en
Open access
Locations
  • Neuron (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Roy J. Carver Charitable Trust
  • University of California, Santa Cruz
  • Johns Hopkins University
  • National Institutes of Health (HL07121)
  • University of Illinois at Urbana-Champaign
  • Department of Pathology, Johns Hopkins University
  • National Heart, Lung, and Blood Institute (HL-07121, T32HL007121)
  • National Institute on Drug Abuse (R21DA025132)
  • National Institute of General Medical Sciences (R01GM088342)
  • National Institute of Allergy and Infectious Diseases (R01AI021640)
  • National Institute of Neurological Disorders and Stroke (P01NS050210)
  • National Institute of Environmental Health Sciences (P30ES005605)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
Keywords
microRNA binding sites, human brain, Argonaute 2, miRNA-target interactions, post-transcriptional regulation, HITS-CLIP, neuropsychiatric disorders, gene regulatory networks
MeSH terms
Adult, Aged, Animals, Autoradiography, Base Sequence, Binding Sites, Gyrus Cinguli, Humans, Male, Middle Aged, Motor Cortex, Nerve Tissue Proteins, Postmortem Changes, RNA, Messenger, MicroRNAs, Immunoprecipitation, Mice, Gene Regulatory Networks, Transcriptome, Argonaute Proteins

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