Cell Stem Cell, volume 9 Supplemental Information

Transcription

1 Cell Stem Cell, volume 9 Supplemental Information Large-Scale Analysis Reveals Acquisition of Lineage-Specific Chromosomal Aberrations in Human Adult Stem Cells Uri Ben-David, Yoav Mayshar, and Nissim Benvenisty 1

2 2

3 3

4 Legend to Supplementary Figures and Tables Supplementary Figure 1: Further identification of chromosomal aberrations in human stem cells. (a-b) Identification of chromosomal aberrations in human mesenchymal stem cells: bone marrow-derived MSC line, A18, demonstrates monosomy 6q (a, red line, p=8xe-5) and trisomy 19 (b, red line, p=6xe-20). Another MSC cell line from the same study, A23, is presented as control (blue line). (c) Identification of chromosomal aberrations in human neural stem cells: hesc-derived NSC line, H9 hes cell derived d17 definitive neural epithelial (pool #3), demonstrates trisomy 19 (red line, p=10xe-15). Another NSC sample from the same study, H9 hes cell derived d17 definitive neural epithelial (pool #2), is presented as control (blue line). (d) Identification of chromosomal aberrations in human hematopoietic stem/progenitor cells: bone marrow-derived CD34+ sample from MDS patient27 demonstrates trisomy 8 (red line, p=1xe- 15). 17 healthy donors-derived CD34+ samples from the same study are presented as controls (blue lines). Related to Figure 1. Supplementary Figure 2: Ideogram of the common chromosomal aberrations in various types of stem cells. Each chromosome is colored by the type/s of stem cells in which it was found to be aberrant in the current study. Stem cells are color-coded, so that red represents PSCs, green represents MSCs, and blue represents NSCs. Asterisks indicate common aberrations, found here or reported elsewhere in at least two independent studies. For instance, monosomy 6q was found in two independent studies of MSCs, and is therefore marked with a green asterisk. Related to Figure 2. Supplementary Table 1: A complete list of chromosomal aberrations identified in PSCs, MSCs, NSCs, and HSPCs. All stem cell samples that passed quality control were analyzed by the CGH-explorer software. Whenever aberrations were detected, the samples were subjected to a second bioinformatic test of chromosomal location enrichment, using the Expander tool (see Supplemental Experimental Procedures). Results of both analyses are listed in the table. Passages are mentioned wherever data were available. Previous reports on the chromosomal integrity of the cell lines are also mentioned where data were available. Related to Figures 1 and 2. 4

5 Supplemental Experimental Procedures Gene expression profiles database Gene expression profiles from studies which involved human embryonic stem cells (hescs), human induced pluripotent stem cells (hipscs), neural stem/progenitor cells (NSCs), mesenchymal stem cells (MSCs) and CD34+ hematopoietic stem/progenitor cells (HSPCs), and which conducted DNA microarray analysis using HG_U95A,HG-U133plus2, HG-ST1.0 (Affymetrix, CA) or HumanRef-8v3.0 (Illumina, CA) microarray platforms, were obtained from the GEO ( and from EMBL-EBI ( databases. Raw.CEL files for all samples were analyzed using MAS5 (for HG-U133plus2 arrays) or RMA (for HG-ST1.0 arrays) probeset condensation algorithm using Expression Console (Affymetrix, CA). Arrays were analyzed for quality control and outliers removed. Further outliers were removed following hierarchical clustering analysis. Normalized files were obtained for HG_U95A and HumanRef-8v3.0 arrays. Thus, the final dataset consisted of 208 samples of pluripotent stem cells, 144 samples of MSCs, 97 samples of NSCs and 177 samples of HSPCs, from 58 independent studies (See Table S1). For each cell type, in the HG-U133plus2 and HG_U95A platforms, probes absent in over 20% of the samples were discarded. In the HG- ST1.0 and HumanRef-8v3.0 platforms, probes whose expression was lower than 5.0 or 50 (respectively) in over 20% of the samples were discarded. In the case of multiple probesets for any given gene, multiple instances were discarded, so that each gene would be represented by one probeset only. Whenever possible, probesets ending with _at were used for the analysis (otherwise probesets were randomly selected). Probesets without documented chromosomal location were also removed. Thus, separate datasets containing a single probeset for each expressed gene were generated for each stem cell group. In order to reduce bias due to low expression levels, values under 50 (for HG-U133plus2, HG_U95A, and HumanRef-8v3.0) or 6.0 (for HG-ST1.0) were collectively raised to this level. In order to further reduce noise, the sum of squares of the relative expression values was calculated for each gene and highly variable genes (SSQ>150 for MSCs and HSPCs, SSQ>10 for NSCs) were removed as well. CGH-PCF over-expression analysis For each sample, the expression value of each gene was divided by the median of the same gene across the entire dataset, in order to obtain a comparative value. In order to reduce possible bias from any given experiment, groups of similar samples with highly similar gene expression profiles (as judged by hierarchical clustering) were averaged for the sake of calculating the grand population median. This median then served as the baseline for examining expression bias. The data was then processed using a freely available comparative genomic hybridization (CGH) analysis software program, CGH-Explorer ( Papers/CGH). Gene expression regional bias was detected using the program s piecewise constant fit (PCF) algorithm, using a set of parameters as follows: Least allowed deviation = 5

6 ; Least allowed aberration size = 50-80; Winsorize at quantile = 0.001; Penalty = 10-12; Threshold = Deletions in chromosome 19 could not be accurately detected, and were thus removed from the analysis. Moving-average plots of lines and regions of interest were drawn using the moving-average fit tool. Location enrichment analysis For each sample in which an aberration was detected, a list of genes that are over-expressed (>1.5 fold, for trisomies) or under-expressed (<1.5 fold, for monosomies) relative to the median expression of that gene, was comprised. In order to test for enrichment of whole chromosomes or chromosome arms, this list was subjected to location enrichment analysis, using the Expander software ( Significance was determined as Bonferroni corrected p-values lower than 1.0E-4, which is the default value of the Expander program. Cancer database analysis Data from the Mitelman Database of Chromosome Aberrations and Gene Fusions in Cancer were derived using the National Cancer Institute Recurrent Chromosome Aberrations in Cancer Database Searcher ( For each tumor of interest, the number of cases with numerical aberrations in each chromosome was calculated. Unbalanced Chromosomal Abnormalities were added to the Numerical Chromosomal Trisomy Abnormalities when they involved gains or isochromosomes, and to the Numerical Chromosomal Monosomy Abnormalities when they involved deletions. The relative frequency of the aberrations in each chromosome was then calculated, separately for trisomies/gains/isochromosomes and for monosomies/deletions. Statistical analysis Hierarchical clustering was performed using Partek Genomics Suite version 6.3 (Partek, MO; RB1 expression values were compared between the diploid and the aneuploid lines using Student s t-test. The sensitivity of the analysis was estimated using known aberrations from the dataset, revealing a false negative rate of ~5% (34/36 aberrations correctly identified). In order to test the specificity of our methodology, randomized data were generated for each cell line using its own gene expression data. This was performed five times for each of the stem cell types, and no false positive aberrations were found. The chromosomal aberrations were tested for uniform distribution using Pearson s chi-square goodness-of-fit test (with simulations). Fisher s exact test (with simulations) was used to test the dependence between the type of aberration (i.e. gain or deletion) and the type of stem cell, and 6

7 was similarly used to test the dependence between the identity of the aberration (i.e. chromosomes involved) and the type of stem cell. All of these tests were performed using the R language and environment for statistical computing ( Similar aberrations in multiple samples from the same study were considered as one aberration for the purpose of all statistical analyses. 7