Dataset Information

ASmodeler: gene modeling of alternative splicing from genomic alignment of mRNA, EST and protein sequences.

ABSTRACT: Alternative splicing is in important mechanism of modulating gene function and expression which greatly expands transcriptome diversity. ASmodeler is a novel web-based utility that finds gene models including alternative splicing events from genomic alignment of mRNA, EST and protein sequences. User-supplied sequences are aligned against the genome map using the BLAT and SIM4 programs. Resulting exon connectivity is analyzed by applying graph-theoretic methods to build all possible gene models including splice variants. The algorithm essentially combines the genome-based sequence clustering and transcript assembly procedures in a coherent fashion. In addition to the user-supplied sequences, UniGene clusters and many well-known gene predictions such as Genscan, Ensembl and Acembly may be included in gene modeling. The current implementation supports human, mouse and rat genomes. ASmodeler is available at http://genome.ewha.ac.kr/ECgene/ASmodeler/.

SUBMITTER: Kim N

PROVIDER: S-EPMC441542 | biostudies-literature | 2004 Jul

REPOSITORIES: biostudies-literature

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ASmodeler: gene modeling of alternative splicing from genomic alignment of mRNA, EST and protein sequences.

Kim Namshin N Shin Seokmin S Lee Sanghyuk S

Nucleic acids research 20040701 Web Server issue

Alternative splicing is in important mechanism of modulating gene function and expression which greatly expands transcriptome diversity. ASmodeler is a novel web-based utility that finds gene models including alternative splicing events from genomic alignment of mRNA, EST and protein sequences. User-supplied sequences are aligned against the genome map using the BLAT and SIM4 programs. Resulting exon connectivity is analyzed by applying graph-theoretic methods to build all possible gene models i ...[more]

PMID: 15215376

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Project description:Splice isoform structure and abundance can be affected by either noncoding or masquerading coding variants that alter the structure or abundance of transcripts. When these variants are common in the population, these nonconstitutive transcripts are sufficiently frequent so as to resemble naturally occurring, alternative mRNA splicing. Prediction of the effects of such variants has been shown to be accurate using information theory-based methods. Single nucleotide polymorphisms (SNPs) predicted to significantly alter natural and/or cryptic splice site strength were shown to affect gene expression. Splicing changes for known SNP genotypes were confirmed in HapMap lymphoblastoid cell lines with gene expression microarrays and custom designed q-RT-PCR or TaqMan assays. The majority of these SNPs (15 of 22) as well as an independent set of 24 variants were then subjected to RNAseq analysis using the ValidSpliceMut web beacon (http://validsplicemut.cytognomix.com), which is based on data from the Cancer Genome Atlas and International Cancer Genome Consortium. SNPs from different genes analyzed with gene expression microarray and q-RT-PCR exhibited significant changes in affected splice site use. Thirteen SNPs directly affected exon inclusion and 10 altered cryptic site use. Homozygous SNP genotypes resulting in stronger splice sites exhibited higher levels of processed mRNA than alleles associated with weaker sites. Four SNPs exhibited variable expression among individuals with the same genotypes, masking statistically significant expression differences between alleles. Genome-wide information theory and expression analyses (RNAseq) in tumor exomes and genomes confirmed splicing effects for 7 of the HapMap SNP and 14 SNPs identified from tumor genomes. q-RT-PCR resolved rare splice isoforms with read abundance too low for statistical significance in ValidSpliceMut. Nevertheless, the web-beacon provides evidence of unanticipated splicing outcomes, for example, intron retention due to compromised recognition of constitutive splice sites. Thus, ValidSpliceMut and q-RT-PCR represent complementary resources for identification of allele-specific, alternative splicing.

Dataset Information

ASmodeler: gene modeling of alternative splicing from genomic alignment of mRNA, EST and protein sequences.

Publications

ASmodeler: gene modeling of alternative splicing from genomic alignment of mRNA, EST and protein sequences.

Similar Datasets

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