Differential expression of alternatively spliced transcripts related to energy metabolism in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the most common malignant tumors worldwide. CRC molecular pathogenesis is heterogeneous and may be followed by mutations in oncogenes and tumor suppressor genes, chromosomal and microsatellite instability, alternative splicing alterations, hypermethylation of CpG islands, oxidative stress, impairment of different signaling pathways and energy metabolism. In the present work, we have studied the alterations of alternative splicing patterns of genes related to energy metabolism in CRC. RESULTS: Using CrossHub software, we analyzed The Cancer Genome Atlas (TCGA) RNA-Seq datasets derived from colon tumor and matched normal tissues. The expression of 1014 alternative mRNA isoforms involved in cell energy metabolism was examined. We found 7 genes with differentially expressed alternative transcripts whereas overall expression of these genes was not significantly altered in CRC. A set of 8 differentially expressed transcripts of interest has been validated by qPCR. These eight isoforms encoded by OGDH, COL6A3, ICAM1, PHPT1, PPP2R5D, SLC29A1, and TRIB3 genes were up-regulated in colorectal tumors, and this is in concordance with the bioinformatics data. The alternative transcript NM_057167 of COL6A3 was also strongly up-regulated in breast, lung, prostate, and kidney tumors. Alternative transcript of SLC29A1 (NM_001078177) was up-regulated only in CRC samples, but not in the other tested tumor types. CONCLUSIONS: We identified tumor-specific expression of alternative spliced transcripts of seven genes involved in energy metabolism in CRC. Our results bring new knowledge on alternative splicing in colorectal cancer and suggest a set of mRNA isoforms that could be used for cancer diagnosis and development of treatment methods.

PPLine: An Automated Pipeline for SNP, SAP, and Splice Variant Detection in the Context of Proteogenomics.

The fundamental mission of the Chromosome-Centric Human Proteome Project (C-HPP) is the research of human proteome diversity, including rare variants. Liver tissues, HepG2 cells, and plasma were selected as one of the major objects for C-HPP studies. The proteogenomic approach, a recently introduced technique, is a powerful method for predicting and validating proteoforms coming from alternative splicing, mutations, and transcript editing. We developed PPLine, a Python-based proteogenomic pipeline providing automated single-amino-acid polymorphism (SAP), indel, and alternative-spliced-variants discovery based on raw transcriptome and exome sequence data, single-nucleotide polymorphism (SNP) annotation and filtration, and the prediction of proteotypic peptides (available at https://sourceforge.net/projects/ppline). In this work, we performed deep transcriptome sequencing of HepG2 cells and liver tissues using two platforms: Illumina HiSeq and Applied Biosystems SOLiD. Using PPLine, we revealed 7756 SAP and indels for HepG2 cells and liver (including 659 variants nonannotated in dbSNP). We found 17 indels in transcripts associated with the translation of alternate reading frames (ARF) longer than 300 bp. The ARF products of two genes, SLMO1 and TMEM8A, demonstrate signatures of caspase-binding domain and Gcn5-related N-acetyltransferase. Alternative splicing analysis predicted novel proteoforms encoded by 203 (liver) and 475 (HepG2) genes according to both Illumina and SOLiD data. The results of the present work represent a basis for subsequent proteomic studies by the C-HPP consortium.