The long noncoding RNA FEDORA is a cell type– and sex-specific regulator of depression

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Abstract

Women suffer from depression at twice the rate of men, but the underlying molecular mechanisms are poorly understood. Here, we identify marked baseline sex differences in the expression of long noncoding RNAs (lncRNAs), a class of regulatory transcripts, in human postmortem brain tissue that are profoundly lost in depression. One such human lncRNA, RP11-298D21.1 (which we termed FEDORA), is enriched in oligodendrocytes and neurons and up-regulated in the prefrontal cortex (PFC) of depressed females only. We found that virally expressing FEDORA selectively either in neurons or in oligodendrocytes of PFC promoted depression-like behavioral abnormalities in female mice only, changes associated with cell type–specific regulation of synaptic properties, myelin thickness, and gene expression. We also found that blood FEDORA levels have diagnostic implications for depressed women and are associated with clinical response to ketamine. These findings demonstrate the important role played by lncRNAs, and FEDORA in particular, in shaping the sex-specific landscape of the brain and contributing to sex differences in depression.

Abstract

Depression causes a loss of lncRNA sex differences, such as FEDORA, which is linked to anomalies in the depressed female PFC.

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Michael Love, Wolfgang Huber, Simon Anders (2014)

In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.

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Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

Daehwan Kim, Joseph M Paggi, Chanhee Park … (2021)

Rapid advances in next-generation sequencing technologies have dramatically changed our ability to perform genome-scale analyses. The human reference genome used for most genomic analyses represents only a small number of individuals, limiting its usefulness for genotyping. We designed a novel method, HISAT2, for representing and searching an expanded model of the human reference genome, in which a large catalogue of known genomic variants and haplotypes is incorporated into the data structure used for searching and alignment. This strategy for representing a population of genomes, along with a fast and memory-efficient search algorithm, enables more detailed and accurate variant analyses than previous methods. We demonstrate two initial applications of HISAT2: HLA typing, a critical need in human organ transplantation, and DNA fingerprinting, widely used in forensics. These applications are part of HISAT-genotype, with performance not only surpassing earlier computational methods, but matching or exceeding the accuracy of laboratory-based assays.

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Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Maxim Kuleshov, Matthew Jones, Andrew D. Rouillard … (2016)

Enrichment analysis is a popular method for analyzing gene sets generated by genome-wide experiments. Here we present a significant update to one of the tools in this domain called Enrichr. Enrichr currently contains a large collection of diverse gene set libraries available for analysis and download. In total, Enrichr currently contains 180 184 annotated gene sets from 102 gene set libraries. New features have been added to Enrichr including the ability to submit fuzzy sets, upload BED files, improved application programming interface and visualization of the results as clustergrams. Overall, Enrichr is a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries. Enrichr is freely available at: http://amp.pharm.mssm.edu/Enrichr.

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Author and article information

Contributors

Orna Issler:

ORCID: https://orcid.org/0000-0003-1473-8295

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Yentl Y. van der Zee: Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ValidationRole: Visualization

Aarthi Ramakrishnan:

ORCID: https://orcid.org/0000-0002-6329-6502

Role: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: ValidationRole: Visualization

Sunhui Xia:

ORCID: https://orcid.org/0000-0001-7667-7614

Role: Formal analysisRole: Investigation

Alexander K. Zinsmaier:

ORCID: https://orcid.org/0000-0001-5197-8525

Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draft

Chunfeng Tan:

ORCID: https://orcid.org/0000-0001-7083-1529

Role: InvestigationRole: Resources

Wei Li: Role: Formal analysisRole: Investigation

Caleb J. Browne:

ORCID: https://orcid.org/0000-0003-0089-5433

Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Project administrationRole: Software

Deena M. Walker:

ORCID: https://orcid.org/0000-0002-2085-3751

Role: ConceptualizationRole: Investigation

Marine Salery:

ORCID: https://orcid.org/0000-0003-3543-2156

Role: Investigation

Angélica Torres-Berrío:

ORCID: https://orcid.org/0000-0002-4740-0293

Role: InvestigationRole: MethodologyRole: ResourcesRole: Validation

Rita Futamura: Role: Investigation

Julia E. Duffy: Role: ConceptualizationRole: Investigation

Benoit Labonte: Role: Data curationRole: InvestigationRole: ResourcesRole: SupervisionRole: Writing - review & editing

Jeffrey L. Dupree:

ORCID: https://orcid.org/0000-0002-1136-4972

Role: InvestigationRole: Resources

Yan Dong: Role: Data curationRole: Formal analysisRole: MethodologyRole: ValidationRole: VisualizationRole: Writing - review & editing

James W. Murrough:

ORCID: https://orcid.org/0000-0001-6286-1242

Role: Data curationRole: InvestigationRole: MethodologyRole: ResourcesRole: Writing - review & editing

Li Shen:

ORCID: https://orcid.org/0000-0002-5190-2851

Role: Data curationRole: Formal analysisRole: ResourcesRole: SoftwareRole: VisualizationRole: Writing - review & editing

Eric J. Nestler:

ORCID: https://orcid.org/0000-0002-7905-2000

Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Journal

Journal ID (nlm-ta): Sci Adv

Journal ID (iso-abbrev): Sci Adv

Journal ID (publisher-id): sciadv

Journal ID (hwp): advances

Title: Science Advances

Publisher: American Association for the Advancement of Science

ISSN (Electronic): 2375-2548

Publication date Collection: November 2022

Publication date (Electronic, pub): 30 November 2022

Volume: 8

Issue: 48

Electronic Location Identifier: eabn9494

Affiliations

[ ¹ ]Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.

[ ² ]Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.

[ ³ ]Department of Psychiatry, UT Southwestern, Dallas, TX, USA.

[ ⁴ ]Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA, USA.

[ ⁵ ]Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.

Author notes

[* ]Corresponding author. Email: eric.nestler@ 123456mssm.edu

Author information

Orna Issler https://orcid.org/0000-0003-1473-8295

Aarthi Ramakrishnan https://orcid.org/0000-0002-6329-6502

Sunhui Xia https://orcid.org/0000-0001-7667-7614

Alexander K. Zinsmaier https://orcid.org/0000-0001-5197-8525

Chunfeng Tan https://orcid.org/0000-0001-7083-1529

Caleb J. Browne https://orcid.org/0000-0003-0089-5433

Deena M. Walker https://orcid.org/0000-0002-2085-3751

Marine Salery https://orcid.org/0000-0003-3543-2156

Angélica Torres-Berrío https://orcid.org/0000-0002-4740-0293

Matthew J. Girgenti https://orcid.org/0000-0003-1647-326X

Jeffrey L. Dupree https://orcid.org/0000-0002-1136-4972

James W. Murrough https://orcid.org/0000-0001-6286-1242

Li Shen https://orcid.org/0000-0002-5190-2851

Eric J. Nestler https://orcid.org/0000-0002-7905-2000

Article

Publisher ID: abn9494

DOI: 10.1126/sciadv.abn9494

PMC ID: 9710883

PubMed ID: 36449610

SO-VID: 3fec3f0a-a08a-4878-94fb-d8ad0b386215

Copyright © Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.

History

Date received : 03 January 2022

Date accepted : 12 October 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;

Award ID: R01MH051399

Funded by: FundRef http://dx.doi.org/10.13039/100000025, National Institute of Mental Health;

Award ID: R01MH051399

Funded by: FundRef http://dx.doi.org/10.13039/100006346, Hope for Depression Research Foundation;

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The long noncoding RNA FEDORA is a cell type– and sex-specific regulator of depression

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RNA drug delivery

Most cited references 97

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

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