Differential splicing using whole-transcript microarrays

<p>Abstract</p> <p>Background</p> <p>The latest generation of Affymetrix microarrays are designed to interrogate expression over the entire length of every locus, thus giving the opportunity to study alternative splicing genome-wide. The Exon 1.0 ST (sense target) platform, with versions for Human, Mouse and Rat, is designed primarily to probe every known or predicted exon. The smaller Gene 1.0 ST array is designed as an expression microarray but still interrogates expression with probes along the full length of each well-characterized transcript. We explore the possibility of using the Gene 1.0 ST platform to identify differential splicing events.</p> <p>Results</p> <p>We propose a strategy to score differential splicing by using the auxiliary information from fitting the statistical model, RMA (robust multichip analysis). RMA partitions the probe-level data into probe effects and expression levels, operating robustly so that if a small number of probes behave differently than the rest, they are downweighted in the fitting step. We argue that adjacent poorly fitting probes for a given sample can be evidence of <it>differential </it>splicing and have designed a statistic to search for this behaviour. Using a public tissue panel dataset, we show many examples of tissue-specific alternative splicing. Furthermore, we show that evidence for putative alternative splicing has a strong correspondence between the Gene 1.0 ST and Exon 1.0 ST platforms.</p> <p>Conclusion</p> <p>We propose a new approach, FIRMAGene, to search for differentially spliced genes using the Gene 1.0 ST platform. Such an analysis complements the search for differential expression. We validate the method by illustrating several known examples and we note some of the challenges in interpreting the probe-level data.</p> <p>Software implementing our methods is freely available as an <monospace>R</monospace> package.</p

Exon-Level Transcriptome Profiling in Murine Breast Cancer Reveals Splicing Changes Specific to Tumors with Different Metastatic Abilities

In breast cancer patients, tumor metastases at distant sites are the main cause of death. However, the molecular mechanisms of metastasis of breast cancer remain unclear. It is thought that changes occurring at the level of RNA processing contribute to cancer. Alternative splicing (AS) of pre-mRNA, a key post-transcriptional mechanism allowing for the production of distinct proteins from a single gene, affects over 90% of human genes. Such splicing events are responsible for generating mRNAs that encode protein isoforms that can have very different biological properties and functions. A well-studied example is the BCL-X gene, whose two major transcript isoforms produce two proteins having antagonistic functions: the short form (BCL-XS) promotes apoptosis while the long form (BCL-XL) is anti-apoptotic. Moreover, overexpression of BCL-XL has been reported to enhance the metastatic potential of breast tumor cells in patients

Implementation of exon arrays: alternative splicing during T-cell proliferation as determined by whole genome analysis

<p>Abstract</p> <p>Background</p> <p>The contribution of alternative splicing and isoform expression to cellular response is emerging as an area of considerable interest, and the newly developed exon arrays allow for systematic study of these processes. We use this pilot study to report on the feasibility of exon array implementation looking to replace the 3' <it>in vitro </it>transcription expression arrays in our laboratory.</p> <p>One of the most widely studied models of cellular response is T-cell activation from exogenous stimulation. Microarray studies have contributed to our understanding of key pathways activated during T-cell stimulation. We use this system to examine whole genome transcription and alternate exon usage events that are regulated during lymphocyte proliferation in an attempt to evaluate the exon arrays.</p> <p>Results</p> <p>Peripheral blood mononuclear cells form healthy donors were activated using phytohemagglutinin, IL2 and ionomycin and harvested at 5 points over a 7 day period. Flow cytometry measured cell cycle events and the Affymetrix exon array platform was used to identify the gene expression and alternate exon usage changes. Gene expression changes were noted in a total of 2105 transcripts, and alternate exon usage identified in 472 transcript clusters. There was an overlap of 263 transcripts which showed both differential expression and alternate exon usage over time. Gene ontology enrichment analysis showed a broader range of biological changes in biological processes for the differentially expressed genes, which include cell cycle, cell division, cell proliferation, chromosome segregation, cell death, component organization and biogenesis and metabolic process ontologies. The alternate exon usage ontological enrichments are in metabolism and component organization and biogenesis. We focus on alternate exon usage changes in the transcripts of the spliceosome complex. The real-time PCR validation rates were 86% for transcript expression and 71% for alternate exon usage.</p> <p>Conclusions</p> <p>This study illustrates that the Exon array technology has the potential to provide information on both transcript expression and isoform usage, with very little increase in expense.</p

Fine-Scale Variation and Genetic Determinants of Alternative Splicing across Individuals

Recently, thanks to the increasing throughput of new technologies, we have begun to explore the full extent of alternative pre–mRNA splicing (AS) in the human transcriptome. This is unveiling a vast layer of complexity in isoform-level expression differences between individuals. We used previously published splicing sensitive microarray data from lymphoblastoid cell lines to conduct an in-depth analysis on splicing efficiency of known and predicted exons. By combining publicly available AS annotation with a novel algorithm designed to search for AS, we show that many real AS events can be detected within the usually unexploited, speculative majority of the array and at significance levels much below standard multiple-testing thresholds, demonstrating that the extent of cis-regulated differential splicing between individuals is potentially far greater than previously reported. Specifically, many genes show subtle but significant genetically controlled differences in splice-site usage. PCR validation shows that 42 out of 58 (72%) candidate gene regions undergo detectable AS, amounting to the largest scale validation of isoform eQTLs to date. Targeted sequencing revealed a likely causative SNP in most validated cases. In all 17 incidences where a SNP affected a splice-site region, in silico splice-site strength modeling correctly predicted the direction of the micro-array and PCR results. In 13 other cases, we identified likely causative SNPs disrupting predicted splicing enhancers. Using Fst and REHH analysis, we uncovered significant evidence that 2 putative causative SNPs have undergone recent positive selection. We verified the effect of five SNPs using in vivo minigene assays. This study shows that splicing differences between individuals, including quantitative differences in isoform ratios, are frequent in human populations and that causative SNPs can be identified using in silico predictions. Several cases affected disease-relevant genes and it is likely some of these differences are involved in phenotypic diversity and susceptibility to complex diseases

RNA-Seq Analyses Generate Comprehensive Transcriptomic Landscape and Reveal Complex Transcript Patterns in Hepatocellular Carcinoma

RNA-seq is a powerful tool for comprehensive characterization of whole transcriptome at both gene and exon levels and with a unique ability of identifying novel splicing variants. To date, RNA-seq analysis of HBV-related hepatocellular carcinoma (HCC) has not been reported. In this study, we performed transcriptome analyses for 10 matched pairs of cancer and non-cancerous tissues from HCC patients on Solexa/Illumina GAII platform. On average, about 21.6 million sequencing reads and 10.6 million aligned reads were obtained for samples sequenced on each lane, which was able to identify >50% of all the annotated genes for each sample. Furthermore, we identified 1,378 significantly differently expressed genes (DEGs) and 24, 338 differentially expressed exons (DEEs). Comprehensive function analyses indicated that cell growth-related, metabolism-related and immune-related pathways were most significantly enriched by DEGs, pointing to a complex mechanism for HCC carcinogenesis. Positional gene enrichment analysis showed that DEGs were most significantly enriched at chromosome 8q21.3–24.3. The most interesting findings were from the analysis at exon levels where we characterized three major patterns of expression changes between gene and exon levels, implying a much complex landscape of transcript-specific differential expressions in HCC. Finally, we identified a novel highly up-regulated exon-exon junction in ATAD2 gene in HCC tissues. Overall, to our best knowledge, our study represents the most comprehensive characterization of HBV-related HCC transcriptome including exon level expression changes and novel splicing variants, which illustrated the power of RNA-seq and provided important clues for understanding the molecular mechanisms of HCC pathogenesis at system-wide levels

Alternative splicing and transcriptome profiling of experimental autoimmune encephalomyelitis using genome-wide exon arrays

BACKGROUND: Multiple Sclerosis (MS) is a chronic inflammatory disease causing demyelination and nerve loss in the central nervous system. Experimental autoimmune encephalomyelitis (EAE) is an animal model of MS that is widely used to investigate complex pathogenic mechanisms. Transcriptional control through isoform selection and mRNA levels determines pathway activation and ultimately susceptibility to disease. METHODOLOGY/PRINCIPAL FINDINGS: We have studied the role of alternative splicing and differential expression in lymph node cells from EAE-susceptible Dark Agouti (DA) and EAE-resistant Piebald Virol Glaxo.AV1 (PVG) inbred rat strains using Affymetrix Gene Chip Rat Exon 1.0 ST Arrays. Comparing the two strains, we identified 11 differentially spliced and 206 differentially expressed genes at day 7 post-immunization, as well as 9 differentially spliced and 144 differentially expressed genes upon autoantigen re-stimulation. Functional clustering and pathway analysis implicate genes for glycosylation, lymphocyte activation, potassium channel activity and cellular differentiation in EAE susceptibility. CONCLUSIONS/SIGNIFICANCE: Our results demonstrate that alternative splicing occurs during complex disease and may govern EAE susceptibility. Additionally, transcriptome analysis not only identified previously defined EAE pathways regulating the immune system, but also novel mechanisms. Furthermore, several identified genes overlap known quantitative trait loci, providing novel causative candidate targets governing EAE