Project description:Human induced pluripotent stem cells (hiPSCs) are useful as a tool for reproducing neural development in vitro. However, each hiPSC line has a different ability to differentiate into specific lineages, as known as differentiation propensity, resulting in reduced reproducibility and increased time and cost requirements for research use. To overcome this issue, we searched for predictive signatures of neural differentiation propensity of hiPSCs using DNA methylation which is the main modulator of cellular properties. We obtained 32 lines of hiPSC and its comprehensive DNA methylation data by Infinium MethylationEPIC beadchip. To assess the neural differentiation efficiency of these hiPSCs, we measured the percentage of PAX6-positive cells on day 7 of neural stem cell induction by the dual-SMAD inhibition protocol. Using DNA methylation data of undifferentiated hiPSCs and their measured differentiation efficiency into neural stem cells as the set of data, and HSIC Lasso, a machine learning-based nonlinear feature selection method, we attemted to identify neural differentiation associated differentially methylated sites. Epigenome-wide unsupervised clustering could not distinguish between hiPSCs with varying differentiation efficiency. On the other hand, HSIC Lasso identified 62 probes that can explain the neural differentiation efficiency of hiPSCs. Selected features by HSIC Lasso were particularly enriched within the 3 Mbp on chromosome 5, harboring the IRX2, C5orf38, and IRX1 genes. Within this region, DNA methylation rates were correlated with neural differentiation efficiency particular to female hiPSCs and negatively correlated with gene expression of the IRX1/2 genes. In addition, forced expression of the IRX1/2 genes impaired the neural differentiation ability of hiPSCs. We have shown for the first time that DNA methylation state on the IRX1/2 genes of hiPSCs is predictive biomarker of their ability for neural differentiation. The predictive markers for neural differentiation efficiency identified in this study can be useful for selection of suitable undifferetiated hiPSCs prior to differentiation induction.

Project description:In the current study, we have performed a high-throughput CpG methylation analysis of well characterized and defined populations of human adipose-derived stem cells (hASCs) before and after in vitro induction of osteogenic and myogenic differentiation that allows identifying DNA methylation- regulated differentiation genes. We have also address the extent of the epigenetic programming of hASCs- derived differentiated cells by comparing the methylation profiling of these cells with their somatic counterparts from primary tissues. Finally, we also compared the patterns of CpG methylation of hASCs (and their derivatives) with the methylation profiles of myosarcoma and osteosrcoma cell lines. All the CpG methylation studies have been performed with the Infinium 27K methylation arrays (from Illumina). DNA from adipose M-bM-^@M-^Sderived stem cells (n=4), in vitro induced myocytes (n=3), in vitro induced osteocytes (n=3), primary osteocytes obtained from ribs (n=1), primary myocytes (n=1), osteosarcoma cell line (MG63) and myosarcoma cell lines (Te 32.T and RD) was isolated applying the QIAampM-BM-. DNA Mini Kit (Qiagen Iberia, Spain). Microarray- based DNA methylation profiling was performed with the HumanMethylation27 BeadChip Infinium Methylation ArraysM-BM-. (Illumina, Inc.).The panel was designed to compare the DNA methylation status of each group of samples, which allow interrogating 27,578 CpG loci covering 14,495 genes at single-nucleotide resolution by typing bisulfite-converted DNA. The sequences included in the panel are derived from the well-annotated NCBI CCDS database (Genome Build 36) and is supplemented with more than 1,000 cancer-related genes described in published literature. Probe content has been enriched to deeply cover more than 150 well-established cancer genes known to show differential methylation patterns. Methylation array content also targets the promoter regions of 110 miRNA genes. Methylation arrays were performed as follows. Briefly, bisulfite conversion of 1 M-NM-<g of genomic DNA was done using the CpGenomicTM DNA Modification Kit (Intergen Company, Purchase, NY, USA). After sodium bisulfite treatment, the remaining assay steps used Infinium technology and using Illumina-supplied reagents and conditions. A thermocycling program with a short denaturation step included for bisulfite conversion (16 cycles of 95M-BM-:C for 30 seconds followed by 50M-BM-:C for 1 hour) was performed to improve bisulfite conversion efficiency. After bisulfite conversion, each sample was whole-genome amplified (WGA) and enzymatically fragmented. The bisulfite-converted WGA-DNA samples were purified and applied to the BeadChips. During hybridization, the WGA-DNA molecules anneal to locus-specific DNA oligomers linked to individual bead types. The two bead types correspond to each CpG locus -one to the methylated and the other to the unmethylated state. Allele-specific primer annealing is followed by single-base extension using DNP- and Biotin-labeled dNTPs. Both bead types for the same CpG locus will incorporate the same type of labelled nucleotide, determined by the base preceding the interrogated cytosine in the CpG locus, and therefore will be detected in the same colour channel. After extension, the array is fluorescently stained, scanned, and the intensities of the unmethylated and methylated bead types measured. DNA methylation values, described as beta values, are recorded for each locus in each sample via BeadStudio software. DNA methylation beta values are continuous variables between 0 (completely unmethylated) and 1 (completely methylated), representing the ratio of the intensity of the methylated bead type to the combined locus intensity.

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DNA methylation of neural differentiation from human adipose derived stem cells

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