Alternative Splicing Prediction and Identification of Cancer-Specific Isoforms Alternative splicing is a major factor in the expansion of transcript and protein complexity in eukaryotes. The huge number of genome and transcript sequences available provides an essential information source for the computational detection of genes alternative splicing patterns. We contributed to the development of two tools that allow single-gene or genome-wide alternative splicing prediction and analysis. Both these applications are freely accessible through web-interfaces (www.caspur.it/ASPIC/ and www.caspur.it/ASPicDB/). We also studied the connection of alternative splicing and the neoplastic state of a cell. We developed a strategy for the statistical evaluation of splicing events in terms of histology- and tissue- specificity taking advantage of the availability of ESTs annotation. In order to find putative cancer-biomarkers we have looked for genes characterized by cancer- or normal- specific cassette exons or mutually exclusive exons. We have found 36 cases satisfying our selection standard. A preliminary experimental analysis through RT-PCR confirmed the effective histological specificity of the predicted cassette exons. We also performed a high-throughput analysis to study the correlation between SNPs and the splicing pattern of a gene. This work made in collaboration with the Wellcome Trust Sanger Institute (UK) - was done using genotype data obtained from the HapMap project and expression data deriving from the Illumina Whole Genome Expression Array.
Alternative splicing prediction and identification of cancer-specific isoforms
ANSELMO, ANNA
2008
Abstract
Alternative Splicing Prediction and Identification of Cancer-Specific Isoforms Alternative splicing is a major factor in the expansion of transcript and protein complexity in eukaryotes. The huge number of genome and transcript sequences available provides an essential information source for the computational detection of genes alternative splicing patterns. We contributed to the development of two tools that allow single-gene or genome-wide alternative splicing prediction and analysis. Both these applications are freely accessible through web-interfaces (www.caspur.it/ASPIC/ and www.caspur.it/ASPicDB/). We also studied the connection of alternative splicing and the neoplastic state of a cell. We developed a strategy for the statistical evaluation of splicing events in terms of histology- and tissue- specificity taking advantage of the availability of ESTs annotation. In order to find putative cancer-biomarkers we have looked for genes characterized by cancer- or normal- specific cassette exons or mutually exclusive exons. We have found 36 cases satisfying our selection standard. A preliminary experimental analysis through RT-PCR confirmed the effective histological specificity of the predicted cassette exons. We also performed a high-throughput analysis to study the correlation between SNPs and the splicing pattern of a gene. This work made in collaboration with the Wellcome Trust Sanger Institute (UK) - was done using genotype data obtained from the HapMap project and expression data deriving from the Illumina Whole Genome Expression Array.I documenti in UNITESI sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/20.500.14242/72913
URN:NBN:IT:UNIMI-72913