Multi-Omic Analysis of CIC's Functional Networks Reveals Novel Interaction Partners and a Potential Role in Mitotic Fidelity.

CIC encodes a transcriptional repressor and MAPK signalling effector that is inactivated by loss-of-function mutations in several cancer types, consistent with a role as a tumour suppressor. Here, we used bioinformatic, genomic, and proteomic approaches to investigate CIC's interaction networks. We observed both previously identified and novel candidate interactions between CIC and SWI/SNF complex members, as well as novel interactions between CIC and cell cycle regulators and RNA processing factors. We found that CIC loss is associated with an increased frequency of mitotic defects in human cell lines and an in vivo mouse model and with dysregulated expression of mitotic regulators. We also observed aberrant splicing in CIC-deficient cell lines, predominantly at 3' and 5' untranslated regions of genes, including genes involved in MAPK signalling, DNA repair, and cell cycle regulation. Our study thus characterises the complexity of CIC's functional network and describes the effect of its loss on cell cycle regulation, mitotic integrity, and transcriptional splicing, thereby expanding our understanding of CIC's potential roles in cancer. In addition, our work exemplifies how multi-omic, network-based analyses can be used to uncover novel insights into the interconnected functions of pleiotropic genes/proteins across cellular contexts.

Comparative transcriptome analysis of isogenic cell line models and primary cancers links capicua (CIC) loss to activation of the MAPK signalling cascade.

CIC encodes a transcriptional repressor, capicua (CIC), whose disrupted activity appears to be involved in several cancer types, including type I low-grade gliomas (LGGs) and stomach adenocarcinomas (STADs). To explore human CIC's transcriptional network in an isogenic background, we developed novel isogenic CIC knockout cell lines as model systems, and used these in transcriptome analyses to study the consequences of CIC loss. We also compared our results with analyses of transcriptome data from TCGA for type I LGGs and STADs. We identified 39 candidate targets of CIC transcriptional regulation, and confirmed seven of these as direct targets. We showed that, although many CIC targets appear to be context-specific, the effects of CIC loss converge on the dysregulation of similar biological processes in different cancer types. For example, we found that CIC deficiency was associated with disruptions in the expression of genes involved in cell-cell adhesion, and in the development of several cell and tissue types. We also showed that loss of CIC leads to overexpression of downstream members of the mitogen-activated protein kinase (MAPK) signalling cascade, indicating that CIC deficiency may present a novel mechanism for activation of this oncogenic pathway. © 2017 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Alternative expression analysis by RNA sequencing.

In alternative expression analysis by sequencing (ALEXA-seq), we developed a method to analyze massively parallel RNA sequence data to catalog transcripts and assess differential and alternative expression of known and predicted mRNA isoforms in cells and tissues. As proof of principle, we used the approach to compare fluorouracil-resistant and -nonresistant human colorectal cancer cell lines. We assessed the sensitivity and specificity of the approach by comparison to exon tiling and splicing microarrays and validated the results with reverse transcription-PCR, quantitative PCR and Sanger sequencing. We observed global disruption of splicing in fluorouracil-resistant cells characterized by expression of new mRNA isoforms resulting from exon skipping, alternative splice site usage and intron retention. Alternative expression annotation databases, source code, a data viewer and other resources to facilitate analysis are available at http://www.alexaplatform.org/alexa_seq/.

Assessment of algorithms for high throughput detection of genomic copy number variation in oligonucleotide microarray data.

BACKGROUND: Genomic deletions and duplications are important in the pathogenesis of diseases, such as cancer and mental retardation, and have recently been shown to occur frequently in unaffected individuals as polymorphisms. Affymetrix GeneChip whole genome sampling analysis (WGSA) combined with 100 K single nucleotide polymorphism (SNP) genotyping arrays is one of several microarray-based approaches that are now being used to detect such structural genomic changes. The popularity of this technology and its associated open source data format have resulted in the development of an increasing number of software packages for the analysis of copy number changes using these SNP arrays. RESULTS: We evaluated four publicly available software packages for high throughput copy number analysis using synthetic and empirical 100 K SNP array data sets, the latter obtained from 107 mental retardation (MR) patients and their unaffected parents and siblings. We evaluated the software with regards to overall suitability for high-throughput 100 K SNP array data analysis, as well as effectiveness of normalization, scaling with various reference sets and feature extraction, as well as true and false positive rates of genomic copy number variant (CNV) detection. CONCLUSION: We observed considerable variation among the numbers and types of candidate CNVs detected by different analysis approaches, and found that multiple programs were needed to find all real aberrations in our test set. The frequency of false positive deletions was substantial, but could be greatly reduced by using the SNP genotype information to confirm loss of heterozygosity.

The Genome sequence of the SARS-associated coronavirus.

We sequenced the 29,751-base genome of the severe acute respiratory syndrome (SARS)-associated coronavirus known as the Tor2 isolate. The genome sequence reveals that this coronavirus is only moderately related to other known coronaviruses, including two human coronaviruses, HCoV-OC43 and HCoV-229E. Phylogenetic analysis of the predicted viral proteins indicates that the virus does not closely resemble any of the three previously known groups of coronaviruses. The genome sequence will aid in the diagnosis of SARS virus infection in humans and potential animal hosts (using polymerase chain reaction and immunological tests), in the development of antivirals (including neutralizing antibodies), and in the identification of putative epitopes for vaccine development.

An efficient strategy for large-scale high-throughput transposon-mediated sequencing of cDNA clones.

We describe an efficient high-throughput method for accurate DNA sequencing of entire cDNA clones. Developed as part of our involvement in the Mammalian Gene Collection full-length cDNA sequencing initiative, the method has been used and refined in our laboratory since September 2000. Amenable to large scale projects, we have used the method to generate >7 Mb of accurate sequence from 3695 candidate full-length cDNAs. Sequencing is accomplished through the insertion of Mu transposon into cDNAs, followed by sequencing reactions primed with Mu-specific sequencing primers. Transposon insertion reactions are not performed with individual cDNAs but rather on pools of up to 96 clones. This pooling strategy reduces the number of transposon insertion sequencing libraries that would otherwise be required, reducing the costs and enhancing the efficiency of the transposon library construction procedure. Sequences generated using transposon-specific sequencing primers are assembled to yield the full-length cDNA sequence, with sequence editing and other sequence finishing activities performed as required to resolve sequence ambiguities. Although analysis of the many thousands (22 785) of sequenced Mu transposon insertion events revealed a weak sequence preference for Mu insertion, we observed insertion of the Mu transposon into 1015 of the possible 1024 5mer candidate insertion sites.