Project description:Profiling miRNA levels in cells with miRNA-microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. Here, we developed a method to select non-changing miRNAs (“invariants”) and used them to compute linear regression normalization coefficients or Variance Stabilizing Normalization (VSN) parameters. We compared the invariant normalizations to normalization by, scaling, quantile and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only few miRNAs are affected (p53 overexpression in SCC13 cells versus GFP vector control transfected cells). All normalization methods performed better than no normalization. Normalizations procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other datasets from one color miRNA microarray platforms, focused gene expression arrays and gene expression analysis using quantitative PCR. Keywords: miRNA profiling
Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs.
Project description:We have sequenced miRNA libraries from human embryonic, neural and foetal mesenchymal stem cells. We report that the majority of miRNA genes encode mature isomers that vary in size by one or more bases at the 3’ and/or 5’ end of the miRNA. Northern blotting for individual miRNAs showed that the proportions of isomiRs expressed by a single miRNA gene often differ between cell and tissue types. IsomiRs were readily co-immunoprecipitated with Argonaute proteins in vivo and were active in luciferase assays, indicating that they are functional. Bioinformatics analysis predicts substantial differences in targeting between miRNAs with minor 5’ differences and in support of this we report that a 5’ isomiR-9-1 gained the ability to inhibit the expression of DNMT3B and NCAM2 but lost the ability to inhibit CDH1 in vitro. This result was confirmed by the use of isomiR-specific sponges. Our analysis of the miRGator database indicates that a small percentage of human miRNA genes express isomiRs as the dominant transcript in certain cell types and analysis of miRBase shows that 5’ isomiRs have replaced canonical miRNAs many times during evolution. This strongly indicates that isomiRs are of functional importance and have contributed to the evolution of miRNA genes
Project description:Transcriptional profiling of human mesenchymal stem cells comparing normoxic MSCs cells with hypoxic MSCs cells. Hypoxia may inhibit senescence of MSCs during expansion. Goal was to determine the effects of hypoxia on global MSCs gene expression.
Project description:Gene expression profiling of immortalized human mesenchymal stem cells with hTERT/E6/E7 transfected MSCs. hTERT may change gene expression in MSCs. Goal was to determine the gene expressions of immortalized MSCs. One-condition experment, gene expression of 3A6
Project description:Profiling miRNA levels in cells with miRNA-microarrays is becoming a widely used technique. Although normalization methods for mRNA gene expression arrays are well established, miRNA array normalization has so far not been investigated in detail. In this study we investigate the impact of normalization on data generated with the Agilent miRNA array platform. Here, we developed a method to select non-changing miRNAs (“invariants”) and used them to compute linear regression normalization coefficients or Variance Stabilizing Normalization (VSN) parameters. We compared the invariant normalizations to normalization by, scaling, quantile and VSN with default parameters as well as to no normalization using samples with strong differential expression of miRNAs (heart-brain comparison) and samples where only few miRNAs are affected (p53 overexpression in SCC13 cells versus GFP vector control transfected cells). All normalization methods performed better than no normalization. Normalizations procedures based on the set of invariants and quantile were the most robust over all experimental conditions tested. Our method of invariant selection and normalization is not limited to Agilent miRNA arrays and can be applied to other datasets from one color miRNA microarray platforms, focused gene expression arrays and gene expression analysis using quantitative PCR. Keywords: miRNA profiling To assay technical reproducibility, 3 technical replicates from brain and heart RNA (Stratagene) were hybridized on Agilent human miRNA microarrays. To determine sensitivity and specificity, heart and brain RNA were mixed in the following ratios: 50% heart 50% brain, 25% heart 75% brain and 5% heart 95% brain. Each of the dilutions was hybridized in a technical duplicate on Agilent human miRNA arrays. To assay the effect of p53 expression on miRNA levels in the human SCC13 cell line, RNA from 3 biological replicates of p53-expressing or control cells were hybridized in technical duplicates on the microarrays, resulting in a total of 12 hybridizations.