Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài: Global and unbiased detection of splice junctions from RNA-seq data. | Ameur et al. Genome Biology 2010 11 R34 http 2010 11 3 R34 Genome Biology METHOD Open Access Global and unbiased detection of splice junctions from RNA-seq data Adam Ameur Anna Wetterbom Lars Feuk Ulf Gyllensten Abstract We have developed a new strategy for de novo prediction of splice junctions in short-read RNA-seq data suitable for detection of novel splicing events and chimeric transcripts. When tested on mouse RNA-seq data 31 000 splice events were predicted of which 88 bridged between two regions separated by 100 kb and 74 connected two exons of the same RefSeq gene. Our method also reports genomic rearrangements such as insertions and deletions. Introduction High-throughput sequencing of mRNA opens unprecedented opportunities to identify the spectrum of splice events in a sample on a global scale. The typical approach for detecting splicing in RNA-seq experiments has been to map the reads to a junction library consisting of predefined exon-exon boundaries 1-6 . Although these strategies can successfully recover many splice events they do not analyze splicing from a truly global and unprejudiced perspective. Only splice junctions present in the library can be identified and it is simply not feasible to match against all possible combinations of exons. For example a genome with 100 000 105 exons which is a low estimate for mammalian genomes would yield 1010 combinations. To address this problem the size of the junction library must be reduced dramatically and consequently most methods consider only the candidates involving known exons within the same gene. A severe limitation with this approach is that splicing events involving previously unknown exons cannot be identified. Also this type of analysis is restricted to the relatively small number of species in which coordinates of genes and exons have been found. To overcome some of these limitations the splicejunction library can instead be created directly from the RNA-seq data without .
