Uncovering the expression patterns of chimeric transcripts using surveys of affymetrix GeneChips.

BACKGROUND: A chimeric transcript is a single RNA sequence which results from the transcription of two adjacent genes. Recent studies estimate that at least 4% of tandem human gene pairs may form chimeric transcripts. Affymetrix GeneChip data are used to study the expression patterns of tens of thousands of genes and the probe sequences used in these microarrays can potentially map to exotic RNA sequences such as chimeras. RESULTS: We have studied human chimeras and investigated their expression patterns using large surveys of Affymetrix microarray data obtained from the Gene Expression Omnibus. We show that for six probe sets, a unique probe mapping to a transcript produced by one of the adjacent genes can be used to identify the expression patterns of readthrough transcripts. Furthermore, unique probes mapping to an intergenic exon present only in the MASK-BP3 chimera can be used directly to study the expression levels of this transcript. CONCLUSIONS: We have attempted to implement a new method for identifying tandem chimerism. In this analysis unambiguous probes are needed to measure run-off transcription and probes that map to intergenic exons are particularly valuable for identifying the expression of chimeras

Global isoform-specific transcript alterations and deregulated networks in clear cell renal cell carcinoma.

Extensive genome-wide analyses of deregulated gene expression have now been performed for many types of cancer. However, most studies have focused on deregulation at the gene-level, which may overlook the alterations of specific transcripts for a given gene. Clear cell renal cell carcinoma (ccRCC) is one of the best-characterized and most pervasive renal cancers, and ccRCCs are well-documented to have aberrant RNA processing. In the present study, we examine the extent of aberrant isoform-specific RNA expression by reporting a comprehensive transcript-level analysis, using the new kallisto-sleuth-RATs pipeline, investigating coding and non-coding differential transcript expression in ccRCC. We analyzed 50 ccRCC tumors and their matched normal samples from The Cancer Genome Altas datasets. We identified 7,339 differentially expressed transcripts and 94 genes exhibiting differential transcript isoform usage in ccRCC. Additionally, transcript-level coexpression network analyses identified vasculature development and the tricarboxylic acid cycle as the most significantly deregulated networks correlating with ccRCC progression. These analyses uncovered several uncharacterized transcripts, including lncRNAs FGD5-AS1 and AL035661.1, as potential regulators of the tricarboxylic acid cycle associated with ccRCC progression. As ccRCC still presents treatment challenges, our results provide a new resource of potential therapeutics targets and highlight the importance of exploring alternative methodologies in transcriptome-wide studies

Dynamic Patterns of Transcript Abundance of Transposable Element Families in Maize.

Transposable Elements (TEs) are mobile elements that contribute the majority of DNA sequences in the maize genome. Due to their repetitive nature, genomic studies of TEs are complicated by the difficulty of properly attributing multi-mapped short reads to specific genomic loci. Here, we utilize a method to attribute RNA-seq reads to TE families rather than particular loci in order to characterize transcript abundance for TE families in the maize genome. We applied this method to assess per-family expression of transposable elements in >800 published RNA-seq libraries representing a range of maize development, genotypes, and hybrids. While a relatively small proportion of TE families are transcribed, expression is highly dynamic with most families exhibiting tissue-specific expression. A large number of TE families were specifically detected in pollen and endosperm, consistent with reproductive dynamics that maintain silencing of TEs in the germ line. We find that B73 transcript abundance is a poor predictor of TE expression in other genotypes and that transcript levels can differ even for shared TEs. Finally, by assessing recombinant inbred line and hybrid transcriptomes, complex patterns of TE transcript abundance across genotypes emerged. Taken together, this study reveals a dynamic contribution of TEs to maize transcriptomes

Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors.

Genome-wide association studies have identified over 70 single-nucleotide polymorphisms (SNPs) associated with breast cancer. A subset of these SNPs are associated with quantitative expression of nearby genes, but the functional effects of the majority remain unknown. We hypothesized that some risk SNPs may regulate alternative splicing. Using RNA-sequencing data from breast tumors and germline genotypes from The Cancer Genome Atlas, we tested the association between each risk SNP genotype and exon-, exon-exon junction- or transcript-specific expression of nearby genes. Six SNPs were associated with differential transcript expression of seven nearby genes at FDR < 0.05 (BABAM1, DCLRE1B/PHTF1, PEX14, RAD51L1, SRGAP2D and STXBP4). We next developed a Bayesian approach to evaluate, for each SNP, the overlap between the signal of association with breast cancer and the signal of association with alternative splicing. At one locus (SRGAP2D), this method eliminated the possibility that the breast cancer risk and the alternate splicing event were due to the same causal SNP. Lastly, at two loci, we identified the likely causal SNP for the alternative splicing event, and at one, functionally validated the effect of that SNP on alternative splicing using a minigene reporter assay. Our results suggest that the regulation of differential transcript isoform expression is the functional mechanism of some breast cancer risk SNPs and that we can use these associations to identify causal SNPs, target genes and the specific transcripts that may mediate breast cancer risk

Prognostic implications of carboxyl-terminus of Hsc70 interacting protein and lysyl-oxidase expression in human breast cancer

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2010 Patani.Background: Ubiquitin modification of proteins influences cellular processes relevant to carcinogenesis. CHIP (carboxyl-terminus of Hsc70-interacting protein) is a chaperone-dependent E3 ubiquitin ligase, regulating the stability of heat shock protein 90 (HSP90) interacting proteins. CHIP is implicated in the modulation of estrogen receptor (ESR1) and Her-2/neu (ERBB2) stability. LOX (lysyl-oxidase) serves intracellular roles and catalyses the cross-linking of extracellular matrix (ECM) collagens and elastin. LOX expression is altered in human malignancies and their peri-tumoral stroma. However, paradoxical roles are reported. In this study, the level of mRNA expression of CHIP and LOX were assessed in normal and malignant breast tissue and correlated with clinico-pathological parameters. Materials and Methods: Breast cancer (BC) tissues (n = 127) and normal tissues (n = 33) underwent RNA extraction and reverse transcription; transcript levels were determined using real-time quantitative PCR and normalized against CK-19. Transcript levels were analyzed against TNM stage, nodal involvement, tumor grade and clinical outcome over a ten-year follow-up period. Results: CHIP expression decreased with increasing Nottingham Prognostic Index (NPI): NPI-1 vs. NPI-3 (12.2 vs. 0.2, P = 0.0264), NPI-2 vs. NPI-3 (3 vs. 0.2, P = 0.0275). CHIP expression decreased with increasing TNM stage: TNM-1 vs. TNM-2 (12 vs. 0, P = 0.0639), TNM-1 vs. TNM-2-4 (12 vs. 0, P = 0.0434). Lower transcript levels were associated with increasing tumor grade: grade 1 vs. grade 3 (17.7 vs. 0.3, P = 0.0266), grade 2 vs. grade 3 (5 vs. 0.3, P = 0.0454). The overall survival (OS) for tumors classified as ‘low-level expression’, was poorer than those with ‘high-level expression’ (118.1 vs. 152.3 months, P = 0.039). LOX expression decreased with increasing NPI: NPI-1 vs. NPI-2 (3 vs. 0, P = 0.0301) and TNM stage: TNM-1 = 3854639, TNM-2 = 908900, TNM-3 = 329, TNM-4 = 1.232 (P = NS). Conclusion: CHIP expression is associated with favorable prognostic parameters, including tumor grade, TNM stage and NPI. CHIP expression predicts OS. LOX expression is associated with improved NPI. In addition to their prognostic utility, mechanistic insights into tumor suppressor function may offer potential therapeutic strategies

Statistical Tests for Detecting Differential RNA-Transcript Expression from Read Counts

As a fruit of the current revolution in sequencing technology, transcriptomes can now be analyzed at an unprecedented level of detail. These advances have been exploited for detecting differential expressed genes across biological samples and for quantifying the abundances of various RNA transcripts within one gene. However, explicit strategies for detecting the hidden differential abundances of RNA transcripts in biological samples have not been defined. In this work, we present two novel statistical tests to address this issue: a 'gene structure sensitive' Poisson test for detecting differential expression when the transcript structure of the gene is known, and a kernel-based test called Maximum Mean Discrepancy when it is unknown. We analyzed the proposed approaches on simulated read data for two artificial samples as well as on factual reads generated by the Illumina Genome Analyzer for two _C. elegans_ samples. Our analysis shows that the Poisson test identifies genes with differential transcript expression considerably better that previously proposed RNA transcript quantification approaches for this task. The MMD test is able to detect a large fraction (75%) of such differential cases without the knowledge of the annotated transcripts. It is therefore well-suited to analyze RNA-Seq experiments when the genome annotations are incomplete or not available, where other approaches have to fail

Identification of new SOX2OT transcript variants highly expressed in human cancer cell lines and down regulated in stem cell differentiation

Long non-coding RNAs are manifested as a new paradigm of molecular effectors in a wide range of human diseases. Human SOX2 overlapping transcript (SOX2OT) gene can generate six lncRNA transcript variants which are functionally assumed to be correlated with cellular differentiation and carcinogenesis. However, the circumstances determining expressional and functional differences between SOX2OT transcript variants remain to be explored. Here, we studied the expression of all SOX2OT transcript variants specifically in five human cancer cell lines by real-time RT-PCR. Changes of the new SOX2OT transcript variants expression were measured during the NT2 teratocarcinoma cell line neuronal-like differentiation and were compared to pluripotency regulators, SOX2 and OCT4A gene expressions. Surprisingly, we identified two new SOX2OT transcripts, named SOX2OT-7, SOX2OT-8 which lack exon 8. We discovered that beside active proximal and distal SOX2OT promoters, different cancer cell lines express high levels of some SOX2OT transcript variants differentially by alternative splicing. Significantly, both SOX2OT-7 and SOX2OT-8 are highly expressed in human cancer cell lines coinciding with SOX2, one of the pluripotency regulators. Our results revealed that SOX2OT-7 is almost the most abundant form of SOX2OT transcript variants in the examined cancer cell lines particularly in NT2 teratocarcinoma cell line where its expression falls upon neuronal-like differentiation similar to SOX2 and OCT4A. We suggest that at least some of SOX2OT transcripts are significantly associated with cancer and stem cell related pathways. © 2015, Springer Science+Business Media Dordrecht

Transcriptome Analyses of Tumor-Adjacent Somatic Tissues Reveal Genes Co-Expressed with Transposable Elements

Background: Despite the long-held assumption that transposons are normally only expressed in the germ-line, recent evidence shows that transcripts of transposable element (TE) sequences are frequently found in the somatic cells. However, the extent of variation in TE transcript levels across different tissues and different individuals are unknown, and the co-expression between TEs and host gene mRNAs have not been examined. Results: Here we report the variation in TE derived transcript levels across tissues and between individuals observed in the non-tumorous tissues collected for The Cancer Genome Atlas. We found core TE co-expression modules consisting mainly of transposons, showing correlated expression across broad classes of TEs. Despite this co-expression within tissues, there are individual TE loci that exhibit tissue-specific expression patterns, when compared across tissues. The core TE modules were negatively correlated with other gene modules that consisted of immune response genes in interferon signaling. KRAB Zinc Finger Proteins (KZFPs) were over-represented gene members of the TE modules, showing positive correlation across multiple tissues. But we did not find overlap between TE-KZFP pairs that are co-expressed and TE-KZFP pairs that are bound in published ChIP-seq studies. Conclusions: We find unexpected variation in TE derived transcripts, within and across non-tumorous tissues. We describe a broad view of the RNA state for non-tumorous tissues exhibiting higher level of TE transcripts. Tissues with higher level of TE transcripts have a broad range of TEs co-expressed, with high expression of a large number of KZFPs, and lower RNA levels of immune genes