Abstract: A system and method for analyzing splicing codes of spliceosomal introns is disclosed. One embodiment comprises methods of identifying introns and exons in genomic DNA or pre-mRNA sequences by locating characteristic markers in splicing junctions by computation and/or manually. Exon sequences predicted by computation can be verified and characterized by employing standard amplification methods, such as comparative genomic, RNA-seq, next-generation sequencing, RT-PCR. DNA/RNA/oligo, electrophoretic or protein chip technologies. If a given sample is verified, its polypeptide can be translated based on genetic codons. Its functions can be deduced based on its characteristics, computation predictions and related knowledge databases. These data can be used to compare databases which correlate the characterized intron or exon or gene to characterized diseases or genetic mutations.

Abstract: This present disclosure provides a kit and method for detecting at least one KANSARL fusion transcript from a biological sample from a subject. The kit comprises at least one of the following components: (a) at least one probe, wherein each of the at least one probe comprises a sequence that hybridizes specifically to a junction of the at least one KANSARL fusion transcript; (b) at least one pair of probes, wherein each of the at least one pair of probes comprises: a first probe comprising a sequence that hybridizes specifically to KANSL1; and a second probe comprising a sequence that hybridizes specifically to ARL17A; or (c) at least one pair of amplification primers, wherein each of the at least one pair of amplification primers are configured to specifically amplify the at least one KANSARL fusion transcript.

Abstract: This present disclosure generally relates to compositions and methods for cancer diagnosis, research and therapy, including but not limited to, cancer markers. In particular, the present disclosure provides a computerized method for detecting fusion transcripts from RNA-seq data and provides the fusion transcripts identified thereby in human cancers. Compositions and methods for identifying the fusion transcripts are also provided.

Abstract: Novel introns and exons are detected by selecting for a specific group of known correlating splice junctions, then searching for unknown introns and exons within that group. Also, diseases are detected by selecting for introns and exons associated with diseases or mutations. Detections are achieved using comparative genomics, gel electrophoresis or protein chip technologies.