Histone H4 acetylation regulates behavioral inter-individual variability in zebrafish

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Abstract

Background

Animals can show very different behaviors even in isogenic populations, but the underlying mechanisms to generate this variability remain elusive. We use the zebrafish ( Danio rerio) as a model to test the influence of histone modifications on behavior.

Results

We find that laboratory and isogenic zebrafish larvae show consistent individual behaviors when swimming freely in identical wells or in reaction to stimuli. This behavioral inter-individual variability is reduced when we impair the histone deacetylation pathway. Individuals with high levels of histone H4 acetylation, and specifically H4K12, behave similarly to the average of the population, but those with low levels deviate from it. More precisely, we find a set of genomic regions whose histone H4 acetylation is reduced with the distance between the individual and the average population behavior. We find evidence that this modulation depends on a complex of Yin-yang 1 (YY1) and histone deacetylase 1 (HDAC1) that binds to and deacetylates these regions. These changes are not only maintained at the transcriptional level but also amplified, as most target regions are located near genes encoding transcription factors.

Conclusions

We suggest that stochasticity in the histone deacetylation pathway participates in the generation of genetic-independent behavioral inter-individual variability.

Electronic supplementary material

The online version of this article (10.1186/s13059-018-1428-y) contains supplementary material, which is available to authorized users.

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Most cited references 33

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DAVID: Database for Annotation, Visualization, and Integrated Discovery.

Glynn Dennis, Brad T. Sherman, Douglas A Hosack … (2003)

Functional annotation of differentially expressed genes is a necessary and critical step in the analysis of microarray data. The distributed nature of biological knowledge frequently requires researchers to navigate through numerous web-accessible databases gathering information one gene at a time. A more judicious approach is to provide query-based access to an integrated database that disseminates biologically rich information across large datasets and displays graphic summaries of functional information. Database for Annotation, Visualization, and Integrated Discovery (DAVID; http://www.david.niaid.nih.gov) addresses this need via four web-based analysis modules: 1) Annotation Tool - rapidly appends descriptive data from several public databases to lists of genes; 2) GoCharts - assigns genes to Gene Ontology functional categories based on user selected classifications and term specificity level; 3) KeggCharts - assigns genes to KEGG metabolic processes and enables users to view genes in the context of biochemical pathway maps; and 4) DomainCharts - groups genes according to PFAM conserved protein domains. Analysis results and graphical displays remain dynamically linked to primary data and external data repositories, thereby furnishing in-depth as well as broad-based data coverage. The functionality provided by DAVID accelerates the analysis of genome-scale datasets by facilitating the transition from data collection to biological meaning.

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Identifying ChIP-seq enrichment using MACS.

Jianxing Feng, Tao Liu, Bo Qin … (2012)

Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.

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5-Azacytidine and 5-aza-2'-deoxycytidine as inhibitors of DNA methylation: mechanistic studies and their implications for cancer therapy.

Judith Christman (2002)

5-Azacytidine was first synthesized almost 40 years ago. It was demonstrated to have a wide range of anti-metabolic activities when tested against cultured cancer cells and to be an effective chemotherapeutic agent for acute myelogenous leukemia. However, because of 5-azacytidine's general toxicity, other nucleoside analogs were favored as therapeutics. The finding that 5-azacytidine was incorporated into DNA and that, when present in DNA, it inhibited DNA methylation, led to widespread use of 5-azacytidine and 5-aza-2'-deoxycytidine (Decitabine) to demonstrate the correlation between loss of methylation in specific gene regions and activation of the associated genes. There is now a revived interest in the use of Decitabine as a therapeutic agent for cancers in which epigenetic silencing of critical regulatory genes has occurred. Here, the current status of our understanding of the mechanism(s) by which 5-azacytosine residues in DNA inhibit DNA methylation is reviewed with an emphasis on the interactions of these residues with bacterial and mammalian DNA (cytosine-C5) methyltransferases. The implications of these mechanistic studies for development of less toxic inhibitors of DNA methylation are discussed.

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Author and article information

Contributors

Angel-Carlos Román:

ORCID: http://orcid.org/0000-0002-5868-6768

angel.roman@neuro.fchampalimaud.org

Gonzalo G. de Polavieja:

ORCID: http://orcid.org/0000-0001-5359-3426

gonzalo.polavieja@neuro.fchampalimaud.org

Journal

Journal ID (nlm-ta): Genome Biol

Journal ID (iso-abbrev): Genome Biol

Title: Genome Biology

Publisher: BioMed Central (London )

ISSN (Print): 1474-7596

ISSN (Electronic): 1474-760X

Publication date (Electronic): 25 April 2018

Publication date PMC-release: 25 April 2018

Publication date Collection: 2018

Volume: 19

Electronic Location Identifier: 55

Affiliations

[1 ]ISNI 0000 0004 0453 9636, GRID grid.421010.6, Champalimaud Neuroscience Programme, , Champalimaud Centre for the Unknown, ; Avenida Brasília s/n, 1400-038 Lisbon, Portugal

[2 ]ISNI 0000 0001 2177 5516, GRID grid.419043.b, Instituto Cajal, Consejo Superior de Investigaciones Científicas, ; Av. Doctor Arce, 37, 28002 Madrid, Spain

[3 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Physics Department, , MIT, ; Cambridge, Massachusetts USA

[4 ]ISNI 0000000119412521, GRID grid.8393.1, Departamento de Bioquímica y Biología Molecular y Genética, , Universidad de Extremadura, ; Av. de Elvas s/n, 06071 Badajoz, Spain

Author information

Angel-Carlos Román http://orcid.org/0000-0002-5868-6768

Gonzalo G. de Polavieja http://orcid.org/0000-0001-5359-3426

Article

Publisher ID: 1428

DOI: 10.1186/s13059-018-1428-y

PMC ID: 5922312

PubMed ID: 29695303

SO-VID: 685fd32f-4367-49d6-807e-5db74ed4aef8

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 30 August 2017

Date accepted : 29 March 2018

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100003329, Ministerio de Economía y Competitividad;

Award ID: BFU2012-33448

Award ID: BFU2011-22678

Award ID: BFU2014-54699-P

Award Recipient : Jose M. Carvajal-González Pedro M. Fernández-Salguero Gonzalo G. de Polavieja

Funded by: FundRef http://dx.doi.org/10.13039/501100001871, Fundação para a Ciência e a Tecnologia;

Award ID: PTDC/NEU-751 SCC/0948/2014

Award Recipient : Gonzalo G. de Polavieja

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: epigenetics,hdac,yy1,behavior,inter-individual variability,zebrafish

Data availability:

ScienceOpen disciplines: Genetics

Keywords: epigenetics, hdac, yy1, behavior, inter-individual variability, zebrafish

Histone H4 acetylation regulates behavioral inter-individual variability in zebrafish

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Most cited references 33

DAVID: Database for Annotation, Visualization, and Integrated Discovery.

Identifying ChIP-seq enrichment using MACS.

5-Azacytidine and 5-aza-2'-deoxycytidine as inhibitors of DNA methylation: mechanistic studies and their implications for cancer therapy.

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