Genome-wide mapping of transcription factor Oct4, Sox2 and Nanog binding-sites in mouse embryonic stem cells Genome Institute of Singapore Department of.

Slides:



Advertisements
Similar presentations
Methods to read out regulatory functions
Advertisements

Special Topics in Genomics Case Studies of Transcriptional Regulation.
Computational discovery of gene modules and regulatory networks Ziv Bar-Joseph et al (2003) Presented By: Dan Baluta.
Manolis Kellis: Research synopsis Brief overview 1 slide each vignette Why biology in a computer science group? Big biological questions: 1.Interpreting.
Table 2 shows that the set TFsf-TGblbs of predicted regulatory links has better results than the other two sets, based on having a significantly higher.
Combined analysis of ChIP- chip data and sequence data Harbison et al. CS 466 Saurabh Sinha.
20,000 GENES IN HUMAN GENOME; WHAT WOULD HAPPEN IF ALL THESE GENES WERE EXPRESSED IN EVERY CELL IN YOUR BODY? WHAT WOULD HAPPEN IF THEY WERE EXPRESSED.
Finding regulatory modules from local alignment - Department of Computer Science & Helsinki Institute of Information Technology HIIT University of Helsinki.
Transcriptome Sequencing with Reference
Gene regulatory network
Gene regulation in cancer 11/14/07. Overview The hallmark of cancer is uncontrolled cell proliferation. Oncogenes code for proteins that help to regulate.
Genome-wide prediction and characterization of interactions between transcription factors in S. cerevisiae Speaker: Chunhui Cai.
[Bejerano Fall10/11] 1 Thank you for the midterm feedback! Projects will be assigned shortly.
Reconstructing Transcription Network in S.cerevisiae WANG Chao Oct. 4, 2004.
[Bejerano Fall09/10] 1 Thank you for the midterm feedback!
A Computational Analysis of the H Region of Mouse Olfactory Receptor Locus 28 Deanna Mendez SoCalBSI August 2004.
Sox2 : Oct-3/4 partnership. Sox2 and Oct-3/4 work together cooperatively to regulate their own transcription and the transcription of a large set of downstream.
Computational Molecular Biology Biochem 218 – BioMedical Informatics Gene Regulatory.
P300 Marks Active Enhancers Ruijuan LiChao HeRui Fu.
Mapping protein-DNA interactions by ChIP-seq Zsolt Szilagyi Institute of Biomedicine.
About OMICS Group OMICS Group is an amalgamation of Open Access publications and worldwide international science conferences and events. Established in.
A systems biology approach to the identification and analysis of transcriptional regulatory networks in osteocytes Angela K. Dean, Stephen E. Harris, Jianhua.
Analyzing ChIP-seq data
Regulation of Gene Expression: An Overview  Transcriptional  Tissue-specific transcription factors  Direct binding of hormones, growth factors, etc.
* only 17% of SNPs implicated in freshwater adaptation map to coding sequences Many, many mapping studies find prevalent noncoding QTLs.
Next Generation Sequencing and its data analysis challenges Background Alignment and Assembly Applications Genome Epigenome Transcriptome.
Stefan Aigner Christian Carson Rusty Gage Gene Yeo Crick-Jacobs Center Salk Institute Analysis of Small RNAs in Stem Cell Differentiation.
MicroRNA regulation in Arabidopsis thaliana
Data Mining the Yeast Genome Expression and Sequence Data Alvis Brazma European Bioinformatics Institute.
The dependence of expression of NF- κ B- dependent genes: statistics and evolutionary conservation of control sequences in the promoter and in the 3 ’
Recombination breakpoints Family Inheritance Me vs. my brother My dad (my Y)Mom’s dad (uncle’s Y) Human ancestry Disease risk Genomics: Regions  mechanisms.
Who can Replace Oct4? Reporter : XueBinghua Date :
A high-resolution map of human evolutionary constraints using 29 mammals Kerstin Lindblad-Toh et al Presentation by Robert Lewis and Kaylee Wells.
Enhancers and 3D genomics Noam Bar RESEARCH METHODS IN COMPUTATIONAL BIOLOGY.
Human long non ‐ coding RNAs promote pluripotency and neuronal differentiation by association with chromatin modifiers and transcription factors by Shi.
Do we know it all?. John L. Rinn and Howard Y. Chang Annu. Rev. Biochem
Takahashi and Yamanaka, 2006 Fig 1. Takahashi and Yamanaka, 2006 Fig 1.
The Transcriptional Landscape of the Mammalian Genome
Detection of genome regulation sequences
Poster: Session B #114: 1pm-2pm
ENCODE Pseudogenes and Transcription
Volume 16, Issue 3, Pages (March 2015)
FoxO: A New Addition to the ESC Cartel
Ling Guo, Robert C.H. Zhao, Yaojiong Wu  Experimental Hematology 
Genome organization and Bioinformatics
Regulation of Gene Expression
Screening for Novel Regulators of Embryonic Stem Cell Identity
Control of Gene Expression in Eukaryotic cells
Wing Y. Chang, William L. Stanford  Cell Stem Cell 
Screening for Novel Regulators of Embryonic Stem Cell Identity
Volume 124, Issue 1, Pages (January 2006)
Volume 2, Issue 2, Pages (February 2008)
Volume 134, Issue 3, Pages (August 2008)
ChIP-seq Robert J. Trumbly
Control of the Embryonic Stem Cell State
Volume 16, Issue 3, Pages (March 2015)
Volume 24, Issue 4, Pages (November 2006)
Volume 46, Issue 1, Pages (April 2012)
Volume 3, Issue 5, Pages (November 2008)
Volume 1, Issue 3, Pages (September 2007)
Volume 133, Issue 6, Pages (June 2008)
Volume 132, Issue 6, Pages (March 2008)
Volume 122, Issue 6, Pages (September 2005)
Nanog Cell Volume 113, Issue 5, Pages (May 2003)
Volume 55, Issue 5, Pages (September 2014)
Volume 55, Issue 5, Pages (September 2014)
TGFβ and SMADs Talk to NANOG in Human Embryonic Stem Cells
Regulation of developmental pathways by core transcription factors via their target genes in the EpiSC model. Regulation of developmental pathways by core.
Volume 24, Issue 8, Pages e7 (August 2018)
Volume 14, Issue 6, Pages (February 2016)
Presentation transcript:

Genome-wide mapping of transcription factor Oct4, Sox2 and Nanog binding-sites in mouse embryonic stem cells Genome Institute of Singapore Department of Biological Sciences National University of Singapore

ChIP-PET technology to map ES cell specific transcription factors Yijun Ruan / Chia-Lin Wei (Cloning & Sequencing, Genome Institute of Singapore)

ChIP-PET captures Oct4 binding profile

Determination of cutoff for ChIP-PET data cutoff

Oct4 Sox2 Nanog No. of binding sites~1000 ~1000 ~3000 Based on 4 PET overlap as a cutoff.

Distribution of Oct4 binding sites

Binding site in gene desert

Sox2

Distribution of Nanog binding sites

Oct4Sox2 de novo prediction of motifs Oct4Sox2 The code for targeting Oct4 to the genome

Oct4Sox2 Oct4Sox Sox2 binding sites Sox2 binding sites contain a prominent Sox2-Oct4 motif de novo prediction of motif

Question 1: What are the motifs bound by these TFs? Oct4Sox2Nanog Oct4 Sox2 ? Oct4 and Sox2 are primarily recruited to the genome through the joint sox2 oct4 motifs de novo prediction of motifs using the ChIP-PET data

What are the motifs bound by Nanog?

Refined using ChIP-PET data Sequences found in EMSA validated probes

Oct4 positively regulates the expression of novel target genes

Oct4 negatively regulates the expression of Cdx2 (trophectoderm transcription factor)

Nanog

Sox2

microRNAs targeted by Nanog

“Core” Target Genes of Oct4, Sox2 and Nanog in mouse ES cells

Nanog Sox2 Oct4 Configuration of transcription factors interaction with upstream regulatory region

Co-occupancy of sites by OCt4/Sox2/nanog

Whole genome maps For Oct4 and Nanog

Oct4NanogSox2 Mouse vs Human comparison of Oct4, Nanog and Sox2 TFBS

Comparison between mouse and human Sox2 binding sites Sox2

Summary Oct4 and Sox2 make use of oct-sox joint motifs for binding (increased specificities?) Nanog’s motif is abundant in the genome Co-targeting of genes by the 3 transcription factors  Coordinated regulation The 3 transcription factors can regulate positively and negatively regulate transcription The target genes fall into diverse functional categories  DNA response pathway  Cellular proliferation  Inhibitors of lineage specific genes

Acknowledgement: Huck Hui Ng Qiang Wu Joon-Lin Chew Yuin-Han Loh Xi Chen Weiwei Zhang Cloning & Sequencing Group Yijun Ruan Chia-Lin Wei Stem Cell Biology Group Bing Lim Paul Robson Larry Stanton Informatics Vega Ken Sung Guillaume Bourque Vlad Leonard Funding: Biomedical Research Council A*STAR National University of Singapore Singapore Millennium Foundation

Comparison between mouse and human Oct4 binding sites Oct4