Here, we sequenced and functionally annotated the long reads (1-2 kb) cDNAs library of an infratentorial ependymoma tumor tissue on PacBio RSII by Iso-Seq protocol using SMRT technology. 577 MB, data was generated from the brain tissues of ependymoma tumor patient, producing 1,19,313 high-quality reads assembled into 19,878 contigs using Celera assembler followed by Quiver pipelines, which produced 2952 unique protein accessions in the nr protein database and 307 KEGG pathways. Additionally, when we compared GO terms of second and third level with alternative splicing data obtained through HTA Array2.0. We identified four and twelve transcript cluster IDs in Level-2 and Level-3 scores respectively with alternative splicing index predicting mainly the major pathways of hallmarks of cancer. Out of these transcript cluster IDs only transcript cluster IDs of gene PNMT, SNN and LAMB1 showed Reads Per Kilobase of exon model per Million mapped reads (RPKM) values at gene-level expression (GE) and transcript-level (TE) track. Most importantly, brain-specific genes--PNMT, SNN and LAMB1 show their involvement in Ependymoma.
Journal: Meta gene
DOI: 10.1016/j.mgene.2015.11.004
Year: 2016