Performances de la puce exon et son application dans l’analyse de l’épissage alternatif associé à la métastase du cancer de sein

Nous montrons l’utilisation de la puce exon d’Affymetrix pour l’analyse simultanée de l’expression des gènes et de la variation d’isoformes. Nous avons utilisé les échantillons d’ARN du cerveau et des tissus de référence qui ont été antérieurement utilisés dans l’étude du consortium MicroArray Quality Control (MAQC). Nous démontrons une forte concordance de la quantification de l’expression des gènes entre trois plateformes d’expression populaires à savoir la puce exon d’Affymetrix, la puce Illumina et la puce U133A d’Affymetrix. Plus intéressant nous montrons que la majorité des discordances entre les trois plateformes résulterait des positions différentes des sondes à travers les plateformes et que les variations d’isoforme exactes ne peuvent être identifiées que par la puce exon. Nous avons détecté avec succès, entre les tissus de référence et ceux du cerveau, une centaine de cas d’évènements d’épissage alternatif. La puce exon est requise dans l’analyse de l’épissage alternatif associé aux pathologies telles que les cancers et les troubles neurologiques. Comme application de cette technologie, nous avons analysé les variations d’épissage dans la métastase du cancer de sein développé dans le model de la souris. Nous avons utilisé une gamme bien définie de trois lignées de tumeur mammaire ayant différents potentiels métastatiques. Par des analyses statistiques, nous avons répertorié 2623 transcripts présentant des variations d’expression et d’isoformes entre les types de tumeur. Une analyse du réseau de gènes montre qu’environ la moitié d’entre eux est impliquée dans plusieurs activités cellulaires, ainsi que dans nombreux cancers et désordres génétiques.We demonstrate how the Affymetrix Exon Array, can be used to simultaneously profile gene expression level, and detect variations at the isoform level. We use a well studied set of brain and reference RNA samples previously used by the MicroArray Quality Control (MAQC) consortium study. We demonstrate a high concordance of gene expression measurements among three popular expression platforms – Affymetrix Exon Array, Illumina, and Affymetrix 3’ targeted array (U133A). More interestingly, we show that in many cases of discordant results, the effect can be explained by differential probe placements across platforms, and that the exact isoform change can only be captured by the Exon Array. Finally, we are able to detect hundreds of cases of splicing, transcript initiation, and termination differences between the brain and reference tissue samples. We propose that the Exon Array is a highly effective tool for transcript isoform profiling, and that it should be used in a variety of systems where such changes are known to be associated with diseases, such as neurological disorders and cancer. As application, we used the Affymetrix Exon Array to identify metastatis-specific alternative splicing in mouse model of breast cancer at the whole genome level. We utilize a well characterized series of three mouse mammary tumor lines exhibiting varying levels of metastatic potential. We catalogued 2623 transcripts which exhibit splicing aberrations during the progression of cancer. A genetic pathway analysis shows the half of them implicated in several cell activities, cancers and genetic disorders

Gene Expression and Isoform Variation Analysis using Affymetrix Exon Arrays

Correction to Bemmo A, Benovoy D, Kwan T, Gaffney DJ, Jensen RV, Majewski J: Gene expression and isoform variation analysis using Affymetrix Exon Arrays. BMC Genomics 2008, 9: 529

Overestimation of alternative splicing caused by variable probe characteristics in exon arrays

In higher eukaryotes, alternative splicing is a common mechanism for increasing transcriptome diversity. Affymetrix exon arrays were designed as a tool for monitoring the relative expression levels of hundreds of thousands of known and predicted exons with a view to detecting alternative splicing events. In this article, we have analyzed exon array data from many different human and mouse tissues and have uncovered a systematic relationship between transcript-fold change and alternative splicing as reported by the splicing index. Evidence from dilution experiments and deep sequencing suggest that this effect is of technical rather than biological origin and that it is driven by sequence features of the probes. This effect is substantial and results in a 12-fold overestimation of alternative splicing events in genes that are differentially expressed. By cross-species exon array comparison, we could further show that the systematic bias persists even across species boundaries. Failure to consider this effect in data analysis would result in the reproducible false detection of apparently conserved alternative splicing events. Finally, we have developed a software in R called COSIE (Corrected Splicing Indices for Exon arrays) that for any given set of new exon array experiments corrects for the observed bias and improves the detection of alternative splicing (available at www.fmi.ch/groups/gbioinfo)

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

Neuron-specific ELAV/Hu proteins suppress HuR mRNA during neuronal differentiation by alternative polyadenylation

The ubiquitously expressed RNA-binding protein HuR increases the stability and translation of mRNAs encoding growth regulatory proteins that promote proliferation in a variety of cell types. However, the three neuron-specific ELAV/Hu proteins, HuB, HuC and HuD, while binding to the same types of mRNAs, are required instead for neuronal differentiation, and it becomes difficult to reconcile these contrary functions when all four Hu proteins are expressed in the same neuron. HuR mRNA exists as three alternatively polyadenylated variants, a 1.5-kb testes-specific mRNA isoform, a ubiquitous 2.4-kb isoform and a 6.0-kb isoform that we now show is induced during neuronal differentiation and appears to be neuron-specific. This 6.0-kb neuron-specific mRNA isoform is inherently less stable and produces less HuR protein than the ubiquitous 2.4-kb mRNA. Furthermore, we show that neuronal HuB, HuC and HuD, as well as HuR itself, can bind at the 2.4-kb mRNA polyadenylation site, and when overexpressed can affect alternative polyadenylation to generate an extended HuR 3′-UTR that is translationally suppressed. We propose that the regulation of HuR protein expression by alternative polyadenylation allows neurons to post-transcriptionally regulate mRNAs-encoding factors required for proliferation versus differentiation to facilitate neuronal differentiation

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