Project description:Purpose: The goal of this study was to use deep sequencing to identify all splice variants of Calcium/calmodulin-dependent kinase II (CaMKII) expressed in the human hippocampus. Methods: Transcripts of CaMKII-encoding genes (CAMK2A, CAMK2B, CAMK2G, and CAMK2D) were sub-amplified by PCR from total RNA extracted from human hippocampal tissue samples from 3 donors. Illumina sequencing libraries were constructed by PCR from these initial pools of amplicons and sequenced on an Illumina MiSeq instrument. Sequencing reads passing quality controls were clustered on the basis of sequence identity or near-identity. Consensus sequences of clusters were mapped with known exons of CaMKII genes to identify the splice variant represented by each cluster. Donor 1 replicate 2, Donor 2, and Donor 3 libraries from genes CAMK2B, CAMK2G, and CAMK2D were first sequenced on a MiSeq Nano flow cell, then re-pooled for read balancing and sequenced again of a full-size MiSeq flow cell. For each library, reads from Nano and full-size flow cells were combined for subsequent analysis. Results: We perfomed the first comprehensive survey of CaMKII transcripts expressed in individual tissue samples (human hippocampus). We detected a total of 79 splice variants of the four human CaMKIIs: CaMKIIα (3), CaMKIIβ (30), CaMKIIγ (24), and CaMKIIδ (22), across tissue samples from 3 donors. This represents the vast majority of possible in-frame CaMKII splice variants (Sloutsky and Stratton, European Journal of Neuroscience, 2020; https://doi.org/10.1111/ejn.14761).
Project description:gene expression and alternative splicing analysis in human macrophages versus dorsal root ganglia and heart the focus was on alternatively spliced channel proteins in macrophages versus those expressed in excitable tissues
Project description:Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histological subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was performed on 26 glioblastomas, 22 oligodendrogliomas and 6 control brain samples. Our results demonstrate that Human Exon arrays can identify subgroups of gliomas based on their histological appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas a subset of which (47% and 33%) were confirmed by RT-PCR. In addition, exon-level expression profiling also identified >700 novel exons. Expression of ~67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon-level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants and can identify novel exons. The splice variants identified by exon-level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets. Keywords: cell type comparison 6 adult non diseased brain, 26 glioblastomas, 21 oligodendrogliomas
Project description:The identifcation of alternatively spliced transcript variants specific to particular biological processes in tumours should increase our understanding of cancer. Hypoxia is an important factor in cancer biology and associated splice variants may present new markers to help with planning treatment. A method was developed to analyse alternative splicing in exon array data, using probeset multiplicity to identify genes with changes in expression across their loci, and a combination of the splicing index and a new metric based on the variation of reliability weighted fold changes to detect changes in the splicing patterns. The approach was validated on a cancer/normal sample dataset in which alternative splicing events had been confirmed using RT-PCR. We then analysed ten head and neck squamous cell carcinomas using exon arrays and identified differentially expressed splice variants in five samples with high versus five with low levels of hypoxia-associated genes (Winter et al, 2007; Cancer Res 67:3441-9). The analysis identified a splice variant of LAMA3 (Laminin 3), LAMA3-A, known to be involved in tumour cell invasion and progression. The full-length transcript of the gene (LAMA3-B) did not appear to be hypoxia-associated. The results were confirmed using qualitative real time PCR. In a series of 59 prospectively-collected head and neck tumours (Winter et al, 2007; Cancer Res 67:3441-9), expression of LAMA3-A had prognostic significance whereas LAMA3-B did not. This work illustrates the potential for alternatively spliced transcripts to act as biomarkers of disease prognosis with improved specificity for particular tissues or conditions over assays which do not discriminate between splice variants.
Project description:Aberrant splice variants are involved in the initiation and/or progression of glial brain tumors. We therefore set out to identify splice variants that are differentially expressed between histological subgroups of gliomas. Splice variants were identified using a novel platform that profiles the expression of virtually all known and predicted exons present in the human genome. Exon-level expression profiling was performed on 26 glioblastomas, 22 oligodendrogliomas and 6 control brain samples. Our results demonstrate that Human Exon arrays can identify subgroups of gliomas based on their histological appearance and genetic aberrations. We next used our expression data to identify differentially expressed splice variants. In two independent approaches, we identified 49 and up to 459 exons that are differentially spliced between glioblastomas and oligodendrogliomas a subset of which (47% and 33%) were confirmed by RT-PCR. In addition, exon-level expression profiling also identified >700 novel exons. Expression of ~67% of these candidate novel exons was confirmed by RT-PCR. Our results indicate that exon-level expression profiling can be used to molecularly classify brain tumor subgroups, can identify differentially regulated splice variants and can identify novel exons. The splice variants identified by exon-level expression profiling may help to detect the genetic changes that cause or maintain gliomas and may serve as novel treatment targets. Keywords: cell type comparison
Project description:Alternative splicing is a mechanism in eukaryotes by which different forms of messenger RNAs (mRNAs) are generated from the same gene. Identification of alternative splice variants requires the identification of peptides specific for alternative splice forms. For this purpose, we generated a human database which contains only proteotypic tryptic peptides specific for alternative splice forms from Swiss-Prot entries. Using this database allows an easy access to the peptide sequences that matches the unique amino acid sequence of splice variants to MS data. Furthermore, we combined this database without isoform 1-specific peptides with human Swiss-Prot. This combined database can be used as a general database for searching of LC-MS data. LC-MS data derived from in-solution digests of two different cell lines (LNCaP, HeLa), and phosphoproteomics studies were analyzed using these two databases. Several non-isoform 1-specific peptides were found in both cell lines, some of them seemed to be cell line specific. Control and apoptotic phosphoproteomes from Jurkat T cells revealed several non-isoform 1-specific peptides and some of them showed clear quantitative differences between the two states.
Project description:Our previous study using nude rats revealed that the parental JDCaP xenografts predominantly expressed full-length androgen receptor (AR) whereas the relapsed JDCaP xenografts after castration acquired AR splice variants including AR-V7 and ARv567es. To understand molecular mechanisms underlying the acquisition of AR splice variants in the JDCaP model, we performed microarray analysis using RNA samples of the xenografts without castration (Parent), the relapsed xenografts overexpressing full-length AR and AR-V7 (ARhiV7hi), and the relapsed xenografts expressing ARv567es (ARv567es).