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Transcript
Uncovering the regulatory networks of gastrulation: A systems biology approach! David-Emlyn Parfitt1,2,6, Hui Zhao1,2,6, Mariano Alvarez3,4,6, Saeed Tavazoie3,5, Andrea Califano3,4,6 and Michael M. Shen1,2,6! 1Department of Medicine, 2Department of Genetics and Development, 3Joint Centers for Systems Biology, 4Department of Biomedical Informatics, 5Department of Biochemistry and Molecular Biophysics, 6Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York! ʻPre-Streakʼ ! ~ Day 6! INTRODUCTION! Gastrulation is the complex process during embryogenesis by which pluripotent epiblast cells give rise to the three primary germ layers: endoderm, ectoderm, and mesoderm. Despite extensive investigation of pre-gastrulation and gastrulation stages of mammalian development, relatively little is known about the regulatory network that controls these critical stages of development. Indeed, the known signaling events and master regulators (MRs) - genes that serve as central control points of the regulatory network for gastrulation - have generally been identified by mutational analyses and reverse-genetic approaches. To date, an unbiased methodology that is not dependent upon prior knowledge from the literature has not been used to identify a regulatory network (ʻinteractomeʼ) or master regulators. Here we present a novel and innovative systems-based approach for modeling the genetic regulatory network for gastrulation.! ! 1. Constructing the first epiblast stem cell interactome Epiblast stem cells (EpiSCs) are a pluripotent cell type that are derived from (and resemble) pre-gastrulation mouse epiblast tissue in vivo. Hence, we used ARACNe (Algorithm for the accurate reconstruction of cellular networks) to construct an unbiased interactome for mouse EpiSCs, which we hypothesized can be used to model the regulatory network for the epiblast at pre-gastrulation and gastrulation stages. ! ʻEarly-Streakʼ! ~ Day 7! ʻEarly-Budʼ! ~Day 8! Extraembryonic ! ectoderm! Endoderm! Primitive ! streak! Epiblast! Ectoderm! Mesoderm! AVE! Regulatory network and MRs implementing morphogenetic changes? ! 2. Systematic discovery of regulatory events of mouse epiblast during gastrulation. We used MARINa and FIRE algorithms to interrogate the EpiSC interactome with gene expression signatures corresponding to mouse epiblast tissue of different stages of gastrulation in vivo. MARINa and FIRE identify candidate MR genes and active RNA/DNA binding sites that putatively regulate the transition between two states, represented by the expression signatures. ! Pre-streak! Early streak! EpiSCs ! n= 5! n= 5! (4 pooled epiblasts per sample)! MARINa (Master Regulator Inference Agorithm)! 2 Mouse ! Strains! RNA Seq! FIRE (Finding Informative Regulatory Elements)! Small molecule ʻperturbagenʼ! acid! SB431542! Dexamethasone! Docetaxel! Dorsomorphin! FGF2! Forskolin! Genistein! IDE1! Indolactam! IPA-3! IWP-2! KAADCyclopamine! KT5720! LDN-193189! LIF! Locostatin! Olomoucine! Purmorphamine! Rapamycin! SB202190! STAT3_inh! SU5402! Telomerase_inh! 15 of 76 candidate MRs of early gastrulation identified! p−value Set 4e−04 Foxm1 6e−04 Erf 0.003 Myst2 0.003 Nfe2l1 0.004 Elf3 0.005 Foxh1 Sox11 0.005 Smad5 0.003 Zfp238 0.002 Ctnnb1 0.002 Zdhhc17 0.001 Tcf12 0.001 Tardbp 22K genes! EpiSC Interactome! RNA Expression Profiles! • 1,393 transcription factors! ! • 20,285 Target Genes ! ! • 310,387 Interactions! 3ʼ UTR! Zkscan3 Gene expression signature! (22,000 genes)! ARACNe! 4 Motifs active during onset of gastrulation ! 0.005 3e−04 278 samples! ê! Eomes 0.01 Valproic_Acid! wnt_agonist! wortmannin! Y-27632! Act 10058-F4! Morphogen! (5Z)-7-Oxozeaenol! BAY-11-7082! BMP4! BIO! Embryod Bix01294! body! PD0325901! CHIR99021! DAPT! Retinoic Co-regulators! Zfp238--Zdhhc17! Ctnnb1--Tcf12! Nfe2l1--Zdhhc17! Sox11--Ctnnb1! Sox11--Zfp238! é! Activity! Synergistic pairs of MRs of early gastrulation! p-value! 0.0006! 0.0007! 0.0011! 0.0016! 0.0026! Target of! unidentified RNA binding protein! 5ʼ ELK4! Target for ETS transcription factors! 5ʼbZIP! Target for bZip transcription factors! Our preliminary data demonstrate that the EpiSC interactome will provide a basis for modeling the pre-gastrulation epiblast and that we can identify candidate MRs by interrogating the EpiSC interactome with signatures of pre-gastrulation and gastrulation stages. Functional analyses of these candidate MRs and active motifs will include validation of transcriptional targets by ChIP, and loss- and gain-offunction experiments in both EpiSCs and in vivo.!
