Separated Siamese Twins: Intronic Small Nucleolar RNAs and Matched Host Genes May be Altered in Conjunction or Separately in Multiple Cancer Types

Small nucleolar RNAs (snoRNAs) are non-coding RNAs involved in RNA modification and processing. Approximately half of the so far identified snoRNA genes map within the intronic regions of host genes, and their expression, as well as the expression of their host genes, is dependent on transcript splicing and maturation. Growing evidence indicates that mutations and/or deregulations that affect snoRNAs, as well as host genes, play a significant role in oncogenesis. Among the possible factors underlying snoRNA/host gene expression deregulation is copy number alteration (CNA). We analyzed the data available in The Cancer Genome Atlas database, relative to CNA and expression of 295 snoRNA/host gene couples in 10 cancer types, to understand whether the genetic or expression alteration of snoRNAs and their matched host genes would have overlapping trends. Our results show that, counterintuitively, copy number and expression alterations of snoRNAs and matched host genes are not necessarily coupled. In addition, some snoRNA/host genes are mutated and overexpressed recurrently in multiple cancer types. Our findings suggest that the differential contribution to cancer development of both snoRNAs and host genes should always be considered, and that snoRNAs and their host genes may contribute to cancer development in conjunction or independently

HmtDB 2016: data update, a better performing query system and human mitochondrial DNA haplogroup predictor

The HmtDB resource hosts a database of human mitochondrial genome sequences from individuals with healthy and disease phenotypes. The database is intended to support both population geneticists as well as clinicians undertaking the task to assess the pathogenicity of specific mtDNA mutations. The wide application of next-generation sequencing (NGS) has provided an enormous volume of high-resolution data at a low price, increasing the availability of human mitochondrial sequencing data, which called for a cogent and significant expansion of HmtDB data content that has more than tripled in the current release. We here describe additional novel features, including: (i) a complete, user-friendly restyling of the web interface, (ii) links to the command-line stand-alone and web versions of the MToolBox package, an up-to-date tool to reconstruct and analyze human mitochondrial DNA from NGS data and (iii) the implementation of the Reconstructed Sapiens Reference Sequence (RSRS) as mitochondrial reference sequence. The overall update renders HmtDB an even more handy and useful resource as it enables a more rapid data access, processing and analysis. HmtDB is accessible at http://www.hmtdb.uniba.it/

A comprehensive characterization of rare mitochondrial DNA variants in neuroblastoma

Neuroblastoma, a tumor of the developing sympathetic nervous system, is a common childhood neoplasm that is often lethal. Mitochondrial DNA (mtDNA) mutations have been found in most tumors including neuroblastoma. We extracted mtDNA data from a cohort of neuroblastoma samples that had undergone Whole Exome Sequencing (WES) and also used snap-frozen samples in which mtDNA was entirely sequenced by Sanger technology. We next undertook the challenge of determining those mutations that are relevant to, or arisen during tumor development. The bioinformatics pipeline used to extract mitochondrial variants from matched tumor/blood samples was enriched by a set of filters inclusive of heteroplasmic fraction, nucleotide variability, and in silico prediction of pathogenicity

A Comprehensive Characterization of Mitochondrial DNA Mutations in Glioblastoma Multiforme

Glioblastoma Multiforme (GBM) is the most malignant brain cancer in adults, with a poor prognosis, whose molecular stratification still represents a challenge in pathology and clinics. On the other hand, mitochondrial DNA (mtDNA) mutations have been found in most tumors as modifiers of the bioenergetics state, albeit in GBM a characterization of the mtDNA status is lacking to date. Here, a large characterization of the burden of mtDNA mutations in GBM samples was performed. First, investigation of tumor-specific vs. non tumor-specific mutations was carried out with the MToolBox bioinformatics pipeline by analyzing 46 matched tumor/blood samples, from whole genome or whole exome sequencing datasets obtained from The Cancer Genome Atlas (TCGA) consortium. Additionally, the entire mtDNA sequence was obtained in a dataset of 104 fresh-frozen GBM samples. Mitochondrial mutations with potential pathogenic interest were prioritized based on heteroplasmic fraction, nucleotide variability, and in silico prediction of pathogenicity. A preliminary biochemical analysis of the activity of mitochondrial respiratory complexes was also performed on fresh-frozen GBM samples. Although a high number of mutations were detected, we report that the large majority of them do not pass the prioritization filters. Therefore, a relatively limited burden of pathogenic mutations is indeed carried by GBM, which did not appear to determine a general impairment of the respiratory chain

Mitochondrial Disease Sequence Data Resource (MSeqDR): A global grass-roots consortium to facilitate deposition, curation, annotation, and integrated analysis of genomic data for the mitochondrial disease clinical and research communities

Success rates for genomic analyses of highly heterogeneous disorders can be greatly improved if a large cohort of patient data is assembled to enhance collective capabilities for accurate sequence variant annotation, analysis, and interpretation. Indeed, molecular diagnostics requires the establishment of robust data resources to enable data sharing that informs accurate understanding of genes, variants, and phenotypes. The "Mitochondrial Disease Sequence Data Resource (MSeqDR) Consortium" is a grass-roots effort facilitated by the United Mitochondrial Disease Foundation to identify and prioritize specific genomic data analysis needs of the global mitochondrial disease clinical and research community. A central Web portal (. https://mseqdr.org) facilitates the coherent compilation, organization, annotation, and analysis of sequence data from both nuclear and mitochondrial genomes of individuals and families with suspected mitochondrial disease. This Web portal provides users with a flexible and expandable suite of resources to enable variant-, gene-, and exome-level sequence analysis in a secure, Web-based, and user-friendly fashion. Users can also elect to share data with other MSeqDR Consortium members, or even the general public, either by custom annotation tracks or through the use of a convenient distributed annotation system (DAS) mechanism. A range of data visualization and analysis tools are provided to facilitate user interrogation and understanding of genomic, and ultimately phenotypic, data of relevance to mitochondrial biology and disease. Currently available tools for nuclear and mitochondrial gene analyses include an MSeqDR GBrowse instance that hosts optimized mitochondrial disease and mitochondrial DNA (mtDNA) specific annotation tracks, as well as an MSeqDR locus-specific database (LSDB) that curates variant data on more than 1300 genes that have been implicated in mitochondrial disease and/or encode mitochondria-localized proteins. MSeqDR is integrated with a diverse array of mtDNA data analysis tools that are both freestanding and incorporated into an online exome-level dataset curation and analysis resource (GEM.app) that is being optimized to support needs of the MSeqDR community. In addition, MSeqDR supports mitochondrial disease phenotyping and ontology tools, and provides variant pathogenicity assessment features that enable community review, feedback, and integration with the public ClinVar variant annotation resource. A centralized Web-based informed consent process is being developed, with implementation of a Global Unique Identifier (GUID) system to integrate data deposited on a given individual from different sources. Community-based data deposition into MSeqDR has already begun. Future efforts will enhance capabilities to incorporate phenotypic data that enhance genomic data analyses. MSeqDR will fill the existing void in bioinformatics tools and centralized knowledge that are necessary to enable efficient nuclear and mtDNA genomic data interpretation by a range of shareholders across both clinical diagnostic and research settings. Ultimately, MSeqDR is focused on empowering the global mitochondrial disease community to better define and explore mitochondrial diseases