The Stem Cell Genomics Project Objective: acquire a complete understanding of the genetic factors that: –specify stem cell identity and function; and –regulate commitment and differentiation Rationale: –Stem cells play an essential role in the human body as they provide the starting material for every organ and tissue –Knowledge of regulatory genes acting in and on stem cells is necessary to exploit their full therapeutic potential
STEM CELL NETWORK +20 GROUPS OHRI – GENOMICS PLATFORM DNA microarray / SAGE / Proteomics Bioinformatics Group StemBase samples data PUBLIC
SCN Sample Contributors Jane Aubin Mick Bhatia John Dick Connie Eaves Jacques Galipeau Alain Garnier Marina Gertsentein John Hassell Keith Humphries Norman Iscove Michael McBurney Lynn Megeney James Piret Derrick Rancourt Janet Rossant Michael Rudnicki Luc Sabourin JP Tremblay T. Michael Underhill Valerie Wallace Peter Zandstra
StemBase Database of gene expression data in mouse and human stem cells Affymetrix DNA microarray data (225 samples) and SAGE (6 samples) Study genes important for stem cell function Perez-Iratxeta, C., G. Palidwor, C.J. Porter, N.A. Sanche, M.R. Huska, B.P. Suomela, E.M. Muro, P. Krzyzanowski, E. Hughes, P.A. Campbell, M.A. Rudnicki and M.A. Andrade (2005) Study of stem cell function using microarray experiments. FEBS Letters. 579, 1795-1801.
Genes expressed in: 80%- 100% of all samples 0%- 20% of all samples mitotic chromosome condensation0.0348GO:0007076 dendrite morphogenesis0.0204GO:0016358 synaptogenesis0.0134GO:0007416 calcium channel regulator activity0.00362GO:0005246 G-protein coupled receptor activity, unknown ligand3.40E-11GO:0016526 establishment of protein localization3.50E-22GO:0045184 RNA splicing1.79E-22GO:0008380 cellular metabolism4.31E-27GO:0044237 protein biosynthesis3.03E-28GO:0006412 mitochondrion9.43E-31GO:0005739 RNA binding1.40E-42GO:0003723 ribonucleoprotein complex1.83E-66GO:0030529 GO as namePvalueGO
Dermis Adipose Neural Myoblasts Bone marrow Muscle Myospheres Bone marrow Osteoblasts Retinal primary Retinal first passage Mammospheres Mammospheres undifferenciated Neurospheres Bone marrow Cancer R1 serum64 Cancer Embyoid bodies R1 serum6999 D4D D4E Embyoid bodies J1 C2E D4A R1 V6.5 C2D Embyoid bodies C2A Dim1 Dim2 Mouse / MOE430
Dim1 Dim2 Cord blood Bone marrow Cord blood Bone marrow Cord blood Peripheral Fetal Myoblasts I6 Retinal first passage Myoblasts differentiated Retinal primary Hela M-O7e M-O7e Smad7 Kidney I6 Human / HGU133
Public web server http://www.scgp.ca:8080/StemBase/
Marker detection Use microarray data to identify probe sets that can act as markers. What and how they mark is a separate issue. Krzyzanowski and Andrade (2007) Identification of novel stem cell markers using gap analysis of gene expression data. Submitted.
Method Overview Identification –Find probe sets which appear to divide samples into two groups binary classifications
Method Overview Identification –Find probe sets which appear to divide samples into two groups binary classifications Cluster expansion –Identify clusters of probe sets which support binary classifications
Receiver Operator Characteristic (ROC) curves are used to generate clusters of probe sets with expression patterns which can reproduce each binary classification. 1402235_at “Pattern X” 1101100101101110 Proposed markers for “Pattern X” Probe setScore 1402235_at 1.00000 1409748_at1.00000 1430293_x_at0.99302 … 1427392_a_at0.90021
embryonichematopoieticP19spheres fibroblastosteoblast Five fold enrichment on 71 stem cell markers. From 71 in about 30,000 genes to 49 in 4,449 genes