Summary

Vorhersage und Validierung von Gen-regulatorischen Elementen Activated Während Retinsäure Induced Embryonic Stem Zelldifferenzierung

Published: June 21, 2016
doi:

Summary

In this work we provide an experimental workflow of how active enhancers can be identified and experimentally validated.

Abstract

Embryonale Entwicklung ist ein mehrstufiger Prozess, Aktivierung und Unterdrückung vieler Gene beteiligt sind. Enhancer-Elemente im Genom sind dafür bekannt, Gewebe und Zelltyp-spezifische Regulation der Genexpression während der Zelldifferenzierung beizutragen. Somit ist die Identifizierung und die weitere Untersuchung wichtig, um zu verstehen, wie das Zellschicksal bestimmt wird. Integration von Genexpressionsdaten (zB Microarray oder RNA-seq) und die Ergebnisse der Chromatin – Immunopräzipitation (ChIP) -basierten genomweite Studien (ChIP-seq) ermöglicht große Identifizierung dieser Regulationsregionen. Jedoch funktionellen Validierung von zelltypspezifischen Enhancern erfordert weitere in vitro- und in vivo experimentellen Verfahren. Hier beschreiben wir, wie aktive Enhancer kann experimentell identifiziert und validiert werden. Dieses Protokoll stellt eine Schritt-für-Schritt-Workflow, der folgendes beinhaltet: 1) Identifizierung der regulatorischen Regionen von ChIP-seq Datenanalyse, 2) Klonierung und expertellen Validierung putative regulatorische Potential der identifizierten genomischen Sequenzen in einem Reporter – Assay, und 3) Bestimmung der Enhancer – Aktivität in vivo durch Enhancer – RNA – Transkript Ebene zu messen. Das vorgestellte Protokoll ist detailliert genug, jedem zu helfen diesen Workflow im Labor einzurichten. Wichtig ist, dass das Protokoll einfach und in jedem zellulären Modellsystem verwendet, angepasst werden.

Introduction

Development of a multicellular organism requires precisely regulated expression of thousands of genes across developing tissues. Regulation of gene expression is accomplished in large part by enhancers. Enhancers are short non-coding DNA elements that can be bound with transcription factors (TFs) and act from a distance to activate transcription of a target gene1. Enhancers are generally cis-acting and most frequently found just upstream of the transcription start site (TSS), but recent studies also described examples where enhancers were found much further upstream, on the 3′ of the gene or even within the introns and exons2.

There are hundreds of thousands of potential enhancers in the vertebrate genomes1. Recent methods based on chromatin immunoprecipitation (ChIP) provide high-throughput data of the whole genome that can be used for enhancer analysis3-9. Though data obtained by ChIP-seq experiments greatly increases the likelihood to identify cell and tissue-specific enhancers, it is important to keep in mind that detected binding sites do not necessarily identify direct DNA binding and/or functional enhancers. Thus, further functional analysis of newly identified enhancers is indispensable. In this work, we present a basic three-step process of putative active enhancer identification and validation. This includes: 1) selection of putative transcription factor binding sites by bioinformatics analysis of ChIP-seq data, 2) cloning and validation of these regulatory sequences in reporter constructs, and 3) measurement of enhancer RNA (eRNA).

Exposure of embryonic stem (ES) cells to retinoic acid (RA) is frequently used to promote neural differentiation of the pluripotent cells 10. RA exerts its effects by binding to RA receptors (RARα, β, γ) and retinoid X receptors (RXRα, β, γ). RARs and RXRs in a form of heterodimer bind to DNA motifs called RA-response elements, that is typically arranged as direct repeats of AGGTCA sequence (called as half site) and regulate transcription. Ligand-treatment experiments allowed the identification of several retinoic acid regulated genes in ES cells 11,12. However, enhancer elements for many of these genes has not been described yet. To demonstrate how the here-described workflow can be used for enhancer identification and validation we show step-by-step the selection and characterization of two retinoic acid-dependent enhancers in embryonic stem cells.

Protocol

1. Enhancer Auswahl Basierend auf Chip-seq Analyse Laden Sie die RXR ChIP-seq Rohdaten fastq Datei (mm_ES_RXR_24h_ATRA.fastq.gz) von http://ngsdebftp.med.unideb.hu/bioinformatics/ Download und Dekomprimierung der erforderlichen BWA-Index-Datei für die Ausrichtung (in unserem Fall: Mus_musculus_UCSC_mm10).(ftp://igenome:G3nom3s4u@ussd-ftp.illumina.com/Mus_musculus/UCSC/mm10/Mus_musculus_UCSC_mm10.tar.gz HINWEIS: Besuch https://github.com/ahorvath/Bioinformatics_scripts für weitere Informatio…

Representative Results

Wir haben eine pan-spezifischen Antikörper RXR um Gene Rezeptor genomweite, welche RA-geregelt zu identifizieren Anreicherung in ihrer Nähe. Bioinformatik – Analyse von RXR ChIP-seq Daten aus ES – Zellen mit Retinsäure behandelt erhalten zeigten die Anreicherung des Kernrezeptor – Halbstelle (AGGTCA) unter der RXR Stellen besetzt (Abbildung 1). Mit Hilfe eines bioinformatischen Algorithmus abgebildet wir das Motiv Suchergebnisse der Hälfte Website zu den RXR ChIP-seq…

Discussion

In recent years, advances in sequencing technology have allowed large-scale predictions of enhancers in many cell types and tissues 7-9. The workflow described above allows one to perform primary characterization of candidate enhancers chosen based on ChIP-seq data. The detailed steps and notes will help anyone to set up a routine enhancer validation in the lab.

The most critical step in the luciferase reporter assay is the transfection efficiency. It is recommended to include a GFP…

Disclosures

The authors have nothing to disclose.

Acknowledgements

The authors would like to acknowledge Dr. Bence Daniel, Matt Peloquin, Dr. Endre Barta, Dr. Balint L Balint and members of the Nagy laboratory for discussions and comments on the manuscript. L.N is supported by grants from the Hungarian Scientific Research Fund (OTKA K100196 and K111941) and co-financed by the European Social Fund and the European Regional Development Fund and Hungarian Brain Research Program – Grant No. KTIA_13_NAP-A-I/9.

Materials

KOD DNA polymerase Merck Millipore 71085-3 for PCR amplification of enhancer from gDNA
DNeasy Blood & Tissue kit  Qiagen 69504 for genomic DNA isolation
QIAquick PCR Purification kit Qiagen 28106 for PCR product purification
Gel extraction kit  Qiagen 28706 for gel extraction if there are more PCR product
HindIII NEB R3104L restriction enzyme
BamHI NEB R3136L restriction enzyme
FastAP Thermo Scientific EF0651 release of 5'- and 3'-phosphate groups from DNA
T4 DNA ligase NEB M0202 for ligation
QIAprep Spin Miniprep kit Qiagen 27106 for plasmid isolation
DMEM Gibco 31966-021 ES media
FBS Hyclone SH30070.03 ES media
MEM Non-Essential Amino Acid Sigma M7145 ES media
Penicillin-Streptomycin Sigma P4333 ES media
Beta Mercaptoethanol Sigma M6250 ES media
FuGENE HD  Promega E2311 transfection reagent
Opti-MEM® I Reduced Serum Medium Life Technologies 31985-062 for transfection
All-trans retinoic acid Sigma R2625 ligand, for activation of RAR/RXR
96-well clear plate Greiner 655101 for Beta galactosidase assay
96-well white plate Greiner 655075 for Luciferase assay
D-luciferin, potassium salt Goldbio.com 115144-35-9 for Luciferase assay
ATP salt Sigma A7699-1G for Luciferase assay
MgSO4x 7H2O Sigma 230391-25G for Luciferase assay
HEPES Sigma H3375-25G for Luciferase assay
Na2HPO4 x 7H2O Sigma 431478-50G for Beta galactosidase assay
NaH2PO4 x H2O Sigma S9638-25G for Beta galactosidase assay
MgSO4 x 7H2O Sigma 230391-25G for Beta galactosidase assay
KCl Sigma P9541-500G for Beta galactosidase assay
ONPG (o-nitrophenyl-β-D-galactosidase) Sigma N1127-1G for Beta galactosidase assay
TRIzol® Life Technologies 15596-026 RNA isolation
High-Capacity cDNA Reverse Transcription Kit Life Technologies 4368814 reverse transcription of eRNA
Rnase-free Dnase Promega M6101 Dnase treatment
SsoFast Eva Green BioRad 750000105 RT-qPCR mastermix
CFX384 Touch™ Real-Time PCR Detection System BioRad qPCR machine
BioTek Synergy 4 microplate reader BioTek luminescent counter

References

  1. Wamstad, J. A., Wang, X., Demuren, O. O., Boyer, L. A. Distal enhancers: new insights into heart development and disease. Trends in cell biology. 24, 294-302 (2014).
  2. Pennacchio, L. A., Bickmore, W., Dean, A., Nobrega, M. A., Bejerano, G. Enhancers: five essential questions. Nat Rev Genet. 14, 288-295 (2013).
  3. Mardis, E. R. ChIP-seq: welcome to the new frontier. Nature methods. 4, 613-614 (2007).
  4. Muller, F., Tora, L. Chromatin and DNA sequences in defining promoters for transcription initiation. Biochim Biophys Acta. 1839, 118-128 (2013).
  5. Ounzain, S., Pedrazzini, T. The promise of enhancer-associated long noncoding RNAs in cardiac regeneration. Trends Cardiovasc Med. , (2015).
  6. Lam, M. T., Li, W., Rosenfeld, M. G., Glass, C. K. Enhancer RNAs and regulated transcriptional programs. Trends Biochem Sci. 39, 170-182 (2014).
  7. Dickel, D. E., et al. Function-based identification of mammalian enhancers using site-specific integration. Nature methods. 11, 566-571 (2014).
  8. Blum, R., Vethantham, V., Bowman, C., Rudnicki, M., Dynlacht, B. D. Genome-wide identification of enhancers in skeletal muscle: the role of MyoD1. Genes Dev. 26, 2763-2779 (2012).
  9. Vermunt, M. W., et al. Large-scale identification of coregulated enhancer networks in the adult human brain. Cell reports 9. , 767-779 (2014).
  10. Bain, G., Kitchens, D., Yao, M., Huettner, J. E., Gottlieb, D. I. Embryonic stem cells express neuronal properties in vitro. Dev Biol. 168, 342-357 (1995).
  11. Mahony, S., et al. Ligand-dependent dynamics of retinoic acid receptor binding during early neurogenesis. Genome Biol. 12 (R2), (2011).
  12. Simandi, Z., Balint, B. L., Poliska, S., Ruhl, R., Nagy, L. Activation of retinoic acid receptor signaling coordinates lineage commitment of spontaneously differentiating mouse embryonic stem cells in embryoid bodies. FEBS Lett. 584, 3123-3130 (2010).
  13. Li, H., Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 25, 1754-1760 (2009).
  14. Heinz, S., et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 38, 576-589 (2010).
  15. Robinson, J. T., et al. Integrative genomics viewer. Nat Biotechnol. 29, 24-26 (2011).
  16. Daniel, B., et al. The active enhancer network operated by liganded RXR supports angiogenic activity in macrophages. Genes Dev. 28, 1562-1577 (2013).
  17. Zhu, Y., et al. Predicting enhancer transcription and activity from chromatin modifications. Nucleic Acids Res. 41, 10032-10043 (2013).
  18. Visel, A., et al. ChIP-seq accurately predicts tissue-specific activity of enhancers. Nature. 457, 854-858 (2009).
  19. Heintzman, N. D., et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nat Genet. 39, 311-318 (2007).
  20. Rada-Iglesias, A., et al. A unique chromatin signature uncovers early developmental enhancers in humans. Nature. 470, 279-283 (2010).
  21. Bonn, S., et al. Tissue-specific analysis of chromatin state identifies temporal signatures of enhancer activity during embryonic development. Nat Genet. 44, 148-156 (2012).
  22. Hollenberg, S. M., Giguere, V., Segui, P., Evans, R. M. Colocalization of DNA-binding and transcriptional activation functions in the human glucocorticoid receptor. Cell. 49, 39-46 (1987).
  23. Untergasser, A., et al. Primer3–new capabilities and interfaces. Nucleic Acids Res. 40, e115 (2012).
  24. Rhead, B., et al. The UCSC Genome Browser database: update 2010. Nucleic Acids Res. 38, D613-D619 (2010).
  25. Kim, T. K., et al. Widespread transcription at neuronal activity-regulated enhancers. Nature. 465, 182-187 (2010).
  26. Wang, D., et al. Reprogramming transcription by distinct classes of enhancers functionally defined by eRNA. Nature. 474, 390-394 (2011).
  27. Simandi, Z., et al. PRMT1 and PRMT8 regulate retinoic acid-dependent neuronal differentiation with implications to neuropathology. Stem Cells. 33, 726-741 (2014).
  28. Zhou, H. Y., et al. A Sox2 distal enhancer cluster regulates embryonic stem cell differentiation potential. Genes Dev. 28, 2699-2711 (2014).

Play Video

Cite This Article
Simandi, Z., Horvath, A., Nagy, P., Nagy, L. Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation. J. Vis. Exp. (112), e53978, doi:10.3791/53978 (2016).

View Video