Exon Array Data for Colerectal Tumor and Normal Samples
ABSTRACT: Exon-Level and Gene-Level Expression analysis of Tumor and Normal Samples The effect of somatic copy number alterations at the functional level can be analyzed by looking into the expression pattern of the affected genes. The task of identifying the ‘affected’ genes is facilitated by robust algorithms that carry out sensitive and confident localization of the targets of somatic copy number alterations in cancer. We had earlier identified 144 genes by GISTIC analysis that were potential targets of SCNAs. In this study we report our findings based on exon level analysis of these genes. Only a subset of these genes was found to have significant changes in expression levels. 8/24 genes were found to have fold change value >1.5 and 3 of them were reported as novel in their association with CRC. The splice index of 29 exons corresponding to 13 genes was found to be significantly altered in tumor samples. Causal network analysis was carried out to study the difference in patterns of target genes affected by transcription factors identified by the GISTIC analysis. LIMMA analysis was carried out to find differentially expressed genes and their functional significance was studied using ingenuity pathway analysis. We conducted a group-wise comparison of Tumor vs Normal samples obtained from cancer patients. Array data was processed using Expression Console and AltAnalyze
Project description:Genomic abnormalities leading to colorectal cancer (CRC) include somatic events causing copy number aberrations (CNAs) as well as copy neutral manifestations such as loss of heterozygosity (LOH) and uniparental disomy (UPD). We studied the causal effect of these events by analyzing high resolution cytogenetic microarray data of 15 tumor-normal paired samples. We detected 144 genes affected by CNAs. A subset of 91 genes are known to be CRC related yet high GISTIC scores indicate 24 genes on chromosomes 7, 8, 18 and 20 to be strongly relevant. Combining GISTIC ranking with functional analyses and degree of loss/gain we identify three genes in regions of significant loss (ATP8B1, NARS, and ATP5A1) and eight in regions of gain (CTCFL, SPO11, ZNF217, PLEKHA8, HOXA3, GPNMB, IGF2BP3 and PCAT1) as novel in their association with CRC. Pathway analysis indicates TGF-β signaling pathway to be affected by the cytogenetic events causing CRC as evidenced by the action of genes impacted by CNAs on SMAD family of proteins. Finally, LOH and UPD collectively affected nine cancer related genes. Transcription factor binding sites on regions of >35% copy number loss/gain influenced 16 CRC genes. Our analysis shows patient specific CRC manifestations at the genomic level and that these different events affect individual CRC patients differently. Copy number analysis of Affymetrix CytoScanHD arrays was performed for 15 Tumors and 15 Adjacent Normals from Colorectal Tissue was used as reference for the study.
Project description:Purpose: Age-related degeneration (AMD) is a major cause of blindness in developed countries. The molecular pathogenesis of early events in AMD is poorly understood. We investigated differential gene expression in samples of human retinal pigment epithelium (RPE)/choroid from early AMD and control maculas using exon-based arrays. Methods: Gene expression levels in nine early AMD and nine control human donor eyes were assessed using Affymetrix Human Exon ST 1.0 arrays. Two controls did not pass quality control and were removed. Differentially expressed genes were annotated using DAVID, and gene set enrichment analysis (GSEA) was performed on RPE-specific and endothelium-associated gene sets. CFH genotype was also assessed and differential expression was analyzed with respect to high AMD risk (YH/HH) and low AMD risk (YY) genotypes. Results: Seventy-five genes were identified as differentially expressed (raw p-value < 0.01; >50% fold change, mean log2 expression level in AMD or control ≥ median of all average gene expression values); however, no genes were significant (adj. p-value < 0.01) after correction for multiple hypothesis testing. Of 52 genes with decreased expression in AMD (fold change < 0.5; raw p-value < 0.01), 18 genes were identified by DAVID analysis as associated with vision or neurological processes. GSEA of RPE-associated and endothelium-associated genes revealed a significant decrease in genes typically expressed by endothelial cells in the early AMD group compared to controls, consistent with previous histologic and proteomic studies. Analysis with respect to CFH genotype indicated decreased expression of ADAMTS9 in eyes with high-risk genotypes (fold change = -2.61; raw p-value = 0.0008). Conclusions: GSEA results suggest that RPE transcripts are preserved or elevated in early AMD, concomitant with loss of endothelial cell marker expression. These results are consistent with the notion that choroidal endothelial cell dropout occurs early in the pathogenesis of AMD. Using AltAnalyze (ver. 2.0.7 beta), we analyzed nine early AMD and nine control eyes using Affymetrix Human Exon ST 1.0 arrays. Following initial processing in AltAnalyze, two control arrays were identified as potential outliers by tests implement in arrayQualityMetrics, a package for R.
Project description:The incidence of cancer is not only influenced by exposure to environmental factors such as toxic substances and chemotherapy, but is also a result of individual predispositions. Single Nucleotide Polymorphisms (SNPs) represent one such individual predisposition to cancer1. Gfi136N is a SNP in the coding region of the gene “Growth factor independence 1 (Gfi1)” predisposing to development of Acute myeloid leukemia (AML). However, the mechanisms how this polymorphism is associated with AML are unknown. Here we present a mouse model in which the presence of Gfi136N leads to altered epigenetic modifications in the myeloid progenitor fraction “Granulocytic Monocytic Progenitor (GMP)” and demonstrates how this might predispose to AML. Presence of Gfi136N leads to a different epigenetic programming of the GMPs resulting in higher levels of the leukemogenic transcription factor Hoxa9. To our knowledge, this is the first mouse model of a SNP leading to epigenetic changes. Thus, SNPs not only result in an altered structure or expression level of certain proteins but here we show that SNPs might also lead to different cancer related epigenetic modifications. We used microarrays to detail the changes in the program of gene expression of GMPs induced by the knock in of human Gfi1 variants in the mouse Gfi1 locus Bone marrow derived granulocyte monocyte precursors (GMPs) from wt.-,Gfi1 knock-out.-, human Gfi1-knock in and human Gfi1-SNP36N knock in mice were collected by fluorescence activated cell sorting (FACS) for total RNA extraction and gene expression analysis on affymetrix mouse Gene 1.0 ST arrays. We aimed to identify differentially regulated target genes of the human Gfi1-SNP36N variant in a mouse model system which mit contribute to the development of acute myeloid leukemia (AML).
Project description:Exon and expression analysis of HeLa cells after knockdown of SON Serine-arginine-rich (SR) proteins play a key role in alternative pre-mRNA splicing in eukaryotes. Our laboratory recently showed that a large SR protein called Son has unique repeat motifs that are essential for maintaining the subnuclear organization of pre-mRNA processing factors in nuclear speckles. Motif analysis of Son highlights putative RNA interaction domains that suggest a direct role for Son in pre-mRNA splicing. A genome-wide screen was performed to identify putative human transcription and splicing targets of Son. HeLa cells were transfected with siRNA against SON or a control siRNA (siLuciferase) for 48 hours. Five biological replicates were used for each condition.
Project description:Craniosynostosis (CS) is the congenital premature fusion of one or more cranial sutures and represents the more prevalent craniofacial malformation in humans, with an overall incidence of 1 out of 2000-3000 live births. Non-syndromic craniosynostoses (NSC) are believed to be multifactorial disorders, with a strong genetic component, due to possible gene–gene or gene–environment interactions that remain to be clearly identified. In this study we delved into the molecular signaling acting in calvarial tissue and cells from patients affected by nonsynodromic midline craniosynostosis, using a comparative analysis between fused and unfused sutures of each affected individuals. Using comparative microarray tissue gene expression profiling we have identified a subset of genes involved in the structure and function of the primary cilium, including the Bardet-Biedl syndrome 9 (BBS9) gene, which was recently associated to sagittal synostosis in a GWAS study. We therefore characterized BBS9 expression and cilium-related signaling in cells isolated from patients’ calvarial bone. Overall design: 5 patients affected by nonsynodromic sagittal synostosis or nonsyndromic metopic synostosis were enrolled in this study. Tissue specimens were collected, from each patients, both from patent and fused calvarial sutures and cryopreservated in liquid nitrogen. Total RNA was extracted from snap-frozen calvarial tissue specimens using pestel and TRIzol Reagent (Invitrogen), and subsequently purified using silica membrane spin columns from RNeasy Mini kit (Qiagen). The yield, quality and integrity of RNA were determined using the Agilent 2100 Bioanalyzer (Agilent Technologies). The resulting total RNA was then used to created the biotin-labeled library to be hybridized on GeneChip® Exon 1.0 ST human microarrays following the procedure described by the manufacturer (Affymetrix). The CEL files resulting from the hybridization were analyzed using oneChannelGUI 1.6.5 (Sanges et al. Bioinformatics 2007, 23, 3406-3408). Exon and gene-level probeset summarization was done by mean of RMA and sketch quantile normalization. Gene-level differential expression: to assess differential expression at gene-level, we used an empirical Bayes method together with a false discovery rate (FDR) correction of the p-value Thus, the list of differentially expressed genes was generated using an FDR ≤ 0.05 together with an absolute log2(fold-change) threshold of 1. Exon-level analysis: an intensity filter was subsequently applied at gene-level to remove not expressed and low expressed genes, i.e. genes were retained for exon-level analysis if in all biological replication gene-level signal was greater than 5. Subsequently, only genes characterized to have at least two RNA isoforms annotated in Ensembl database were retained for further analysis. The Splicing Index value was calculated by taking the log2 ratio of the normalized exon intensity (NI) in Sample 1 and the NI in Sample 2. The normalized exon intensity (NI) is the ratio of the probe set intensity to the gene intensity. Alternative splicing events (ASEs) were detected as described in (Della Beffa et al. BMC Genomics 2008, 9, 571).
Project description:Using bone marrow cells of GFP:Gfi1 knock in mice, we separated Gfi1-high and Gfi1-low expressing cells in the classical CD11b+, GR1-low monocytic cell fraction. We sorted CD11b+, GR1-low GFP:Gfi1-high and low cells as well as CD11b+, GR1-high granulocytes and CD11b-high, GR1-intermediate cells from Gfi1-knock-out mice for further analysis. We used Affymetrix Mouse Genome 430A 2.0 arrays (GPL8321) The study should determine how Gfi1 regulates the cell fate of monocytes/granulocytes in mice
Project description:The Affymetrix Human Exon 1.0 ST array was used to measure differential splicing patterns in archived RNA isolated from 26 of 80 children (11 Rejectors and 15 Non-Rejectors). The gene-level probe summaries reported in this series were computed using the Affymetrix Power Tools (APT) software and 'rma-sketch' normalization method. Keywords: Affymetrix 1.0 ST exon array; gene-level analysis Overall design: The gene-level normalized intensities (NI) were computed with the MiDAS algorithm and both the splicing index (SI) and Student's t-test p-values (two-sided) were computed on the NI values in R. To remove low expressed gene-level probes, those with values less than 3.5 (log2 scale) in >50% of the samples in either group were filtered out leaving 17,242 of the original 22,011 probes. Those gene-level probes that were highly differentially expressed between groups were also removed using a fold change threshold of log2. This step accounts for the tendency for the genelevel probe set intensities in each group to be "disproportionately affected by background noise or saturation" (Affymetrix Technical notes).
Project description:Alternative mRNA splicing is a major mechanism for gene regulation and transcriptome diversity. Despite the extent of the phenomenon, the regulation and specificity of the splicing machinery are only partially understood. Adenosine-to-inosine (A-to-I) RNA editing of pre-mRNA by ADAR enzymes has been linked to splicing regulation in several cases. Here we used bioinformatics approaches, RNA-seq and exon-specific microarray of ADAR knockdown cells to globally examine how ADAR and its A-to-I RNA editing activity influence alternative mRNA splicing. Although A-to-I RNA editing only rarely targets canonical splicing acceptor, donor, and branch sites, it was found to affect splicing regulatory elements (SREs) within exons. Cassette exons were found to be significantly enriched with A-to-I RNA editing sites compared with constitutive exons. RNA-seq and exon-specific microarray revealed that ADAR knockdown in hepatocarcinoma and myelogenous leukemia cell lines leads to global changes in gene expression, with hundreds of genes changing their splicing patterns in both cell lines. This global change in splicing pattern cannot be explained by putative editing sites alone. Genes showing significant changes in their splicing pattern are frequently involved in RNA processing and splicing activity. Analysis of recently published RNA-seq data from glioblastoma cell lines showed similar results. Our global analysis reveals that ADAR plays a major role in splicing regulation. Although direct editing of the splicing motifs does occur, we suggest it is not likely to be the primary mechanism for ADAR-mediated regulation of alternative splicing. Rather, this regulation is achieved by modulating trans-acting factors involved in the splicing machinery. HepG2 and K562 cell lines were stably transfected with plasmids containing siRNA designed to specifically knock down ADAR expression (ADAR KD). This in order to examine how ADAR affects alternative splicing globally.