The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

HmtVar: a new resource for human mitochondrial variations and pathogenicity data.

Interest in human mitochondrial genetic data is constantly increasing among both clinicians and researchers, due to the involvement of mitochondrial DNA (mtDNA) in a number of physiological and pathological processes. Thanks to new sequencing technologies and modern databases, the large amount of information on mtDNA variability may be exploited to gain insights into the relationship between mtDNA variants, phenotypes and diseases. To facilitate this process, we have developed the HmtVar resource, a variant-focused database that allows the exploration of a dataset of over 40 000 human mitochondrial variants. Mitochondrial variation data, initially gathered from the HmtDB platform, are integrated with in-house pathogenicity assessments based on various evaluation criteria and with a set of additional annotations from third-party resources. The result is a comprehensive collection of information of crucial importance for human mitochondrial variation studies and investigation of common and rare diseases in which the mitochondrion may be involved. HmtVar is accessible at https://www.hmtvar.uniba.it and data may be retrieved using either a web interface through the Query page or a state-of-the-art API for programmatic access.

Specifications of the ACMG/AMP standards and guidelines for mitochondrial DNA variant interpretation.

Mitochondrial DNA (mtDNA) variant pathogenicity interpretation has special considerations given unique features of the mtDNA genome, including maternal inheritance, variant heteroplasmy, threshold effect, absence of splicing, and contextual effects of haplogroups. Currently, there are insufficient standardized criteria for mtDNA variant assessment, which leads to inconsistencies in clinical variant pathogenicity reporting. An international working group of mtDNA experts was assembled within the Mitochondrial Disease Sequence Data Resource Consortium and obtained Expert Panel status from ClinGen. This group reviewed the 2015 American College of Medical Genetics and Association of Molecular Pathology standards and guidelines that are widely used for clinical interpretation of DNA sequence variants and provided further specifications for additional and specific guidance related to mtDNA variant classification. These Expert Panel consensus specifications allow for consistent consideration of the unique aspects of the mtDNA genome that directly influence variant assessment, including addressing mtDNA genome composition and structure, haplogroups and phylogeny, maternal inheritance, heteroplasmy, and functional analyses unique to mtDNA, as well as specifications for utilization of mtDNA genomic databases and computational algorithms.

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/.

MSeqDR mvTool: A mitochondrial DNA Web and API resource for comprehensive variant annotation, universal nomenclature collation, and reference genome conversion.

Accurate mitochondrial DNA (mtDNA) variant annotation is essential for the clinical diagnosis of diverse human diseases. Substantial challenges to this process include the inconsistency in mtDNA nomenclatures, the existence of multiple reference genomes, and a lack of reference population frequency data. Clinicians need a simple bioinformatics tool that is user-friendly, and bioinformaticians need a powerful informatics resource for programmatic usage. Here, we report the development and functionality of the MSeqDR mtDNA Variant Tool set (mvTool), a one-stop mtDNA variant annotation and analysis Web service. mvTool is built upon the MSeqDR infrastructure (https://mseqdr.org), with contributions of expert curated data from MITOMAP (https://www.mitomap.org) and HmtDB (https://www.hmtdb.uniba.it/hmdb). mvTool supports all mtDNA nomenclatures, converts variants to standard rCRS- and HGVS-based nomenclatures, and annotates novel mtDNA variants. Besides generic annotations from dbNSFP and Variant Effect Predictor (VEP), mvTool provides allele frequencies in more than 47,000 germline mitogenomes, and disease and pathogenicity classifications from MSeqDR, Mitomap, HmtDB and ClinVar (Landrum et al., 2013). mvTools also provides mtDNA somatic variants annotations. "mvTool API" is implemented for programmatic access using inputs in VCF, HGVS, or classical mtDNA variant nomenclatures. The results are reported as hyperlinked html tables, JSON, Excel, and VCF formats. MSeqDR mvTool is freely accessible at https://mseqdr.org/mvtool.php.

A comprehensive collection of annotations to interpret sequence variation in human mitochondrial transfer RNAs.

BACKGROUND: The abundance of biological data characterizing the genomics era is contributing to a comprehensive understanding of human mitochondrial genetics. Nevertheless, many aspects are still unclear, specifically about the variability of the 22 human mitochondrial transfer RNA (tRNA) genes and their involvement in diseases. The complex enrichment and isolation of tRNAs in vitro leads to an incomplete knowledge of their post-transcriptional modifications and three-dimensional folding, essential for correct tRNA functioning. An accurate annotation of mitochondrial tRNA variants would be definitely useful and appreciated by mitochondrial researchers and clinicians since the most of bioinformatics tools for variant annotation and prioritization available so far cannot shed light on the functional role of tRNA variations. RESULTS: To this aim, we updated our MToolBox pipeline for mitochondrial DNA analysis of high throughput and Sanger sequencing data by integrating tRNA variant annotations in order to identify and characterize relevant variants not only in protein coding regions, but also in tRNA genes. The annotation step in the pipeline now provides detailed information for variants mapping onto the 22 mitochondrial tRNAs. For each mt-tRNA position along the entire genome, the relative tRNA numbering, tRNA type, cloverleaf secondary domains (loops and stems), mature nucleotide and interactions in the three-dimensional folding were reported. Moreover, pathogenicity predictions for tRNA and rRNA variants were retrieved from the literature and integrated within the annotations provided by MToolBox, both in the stand-alone version and web-based tool at the Mitochondrial Disease Sequence Data Resource (MSeqDR) website. All the information available in the annotation step of MToolBox were exploited to generate custom tracks which can be displayed in the GBrowse instance at MSeqDR website. CONCLUSIONS: To the best of our knowledge, specific data regarding mitochondrial variants in tRNA genes were introduced for the first time in a tool for mitochondrial genome analysis, supporting the interpretation of genetic variants in specific genomic contexts.

MSeqDR: A Centralized Knowledge Repository and Bioinformatics Web Resource to Facilitate Genomic Investigations in Mitochondrial Disease.

MSeqDR is the Mitochondrial Disease Sequence Data Resource, a centralized and comprehensive genome and phenome bioinformatics resource built by the mitochondrial disease community to facilitate clinical diagnosis and research investigations of individual patient phenotypes, genomes, genes, and variants. A central Web portal (https://mseqdr.org) integrates community knowledge from expert-curated databases with genomic and phenotype data shared by clinicians and researchers. MSeqDR also functions as a centralized application server for Web-based tools to analyze data across both mitochondrial and nuclear DNA, including investigator-driven whole exome or genome dataset analyses through MSeqDR-Genesis. MSeqDR-GBrowse genome browser supports interactive genomic data exploration and visualization with custom tracks relevant to mtDNA variation and mitochondrial disease. MSeqDR-LSDB is a locus-specific database that currently manages 178 mitochondrial diseases, 1,363 genes associated with mitochondrial biology or disease, and 3,711 pathogenic variants in those genes. MSeqDR Disease Portal allows hierarchical tree-style disease exploration to evaluate their unique descriptions, phenotypes, and causative variants. Automated genomic data submission tools are provided that capture ClinVar compliant variant annotations. PhenoTips will be used for phenotypic data submission on deidentified patients using human phenotype ontology terminology. The development of a dynamic informed patient consent process to guide data access is underway to realize the full potential of these resources.

A multi-parametric workflow for the prioritization of mitochondrial DNA variants of clinical interest.

Assigning a pathogenic role to mitochondrial DNA (mtDNA) variants and unveiling the potential involvement of the mitochondrial genome in diseases are challenging tasks in human medicine. Assuming that rare variants are more likely to be damaging, we designed a phylogeny-based prioritization workflow to obtain a reliable pool of candidate variants for further investigations. The prioritization workflow relies on an exhaustive functional annotation through the mtDNA extraction pipeline MToolBox and includes Macro Haplogroup Consensus Sequences to filter out fixed evolutionary variants and report rare or private variants, the nucleotide variability as reported in HmtDB and the disease score based on several predictors of pathogenicity for non-synonymous variants. Cutoffs for both the disease score as well as for the nucleotide variability index were established with the aim to discriminate sequence variants contributing to defective phenotypes. The workflow was validated on mitochondrial sequences from Leber's Hereditary Optic Neuropathy affected individuals, successfully identifying 23 variants including the majority of the known causative ones. The application of the prioritization workflow to cancer datasets allowed to trim down the number of candidate for subsequent functional analyses, unveiling among these a high percentage of somatic variants. Prioritization criteria were implemented in both standalone ( http://sourceforge.net/projects/mtoolbox/ ) and web version ( https://mseqdr.org/mtoolbox.php ) of MToolBox.

Somatic complex I disruptive mitochondrial DNA mutations are modifiers of tumorigenesis that correlate with low genomic instability in pituitary adenomas.

Mitochondrial DNA (mtDNA) mutations leading to the disruption of respiratory complex I (CI) have been shown to exhibit anti-tumorigenic effects, at variance with those impairing only the function but not the assembly of the complex, which appear to contribute positively to cancer development. Owing to the challenges in the analysis of the multi-copy mitochondrial genome, it is yet to be determined whether tumour-associated mtDNA lesions occur as somatic modifying factors or as germ-line predisposing elements. Here we investigated the whole mitochondrial genome sequence of 20 pituitary adenomas with oncocytic phenotype and identified pathogenic and/or novel mtDNA mutations in 60% of the cases. Using highly sensitive techniques, namely fluorescent PCR and allele-specific locked nucleic acid quantitative PCR, we identified the most likely somatic nature of these mutations in our sample set, since none of the mutations was detected in the corresponding blood tissue of the patients analysed. Furthermore, we have subjected a series of 48 pituitary adenomas to a high-resolution array comparative genomic hybridization analysis, which revealed that CI disruptive mutations, and the oncocytic phenotype, significantly correlate with low number of chromosomal aberrations in the nuclear genome. We conclude that CI disruptive mutations in pituitary adenomas are somatic modifiers of tumorigenesis most likely contributing not only to the development of oncocytic change, but also to a less aggressive tumour phenotype, as indicated by a stable karyotype.

MToolBox: a highly automated pipeline for heteroplasmy annotation and prioritization analysis of human mitochondrial variants in high-throughput sequencing.

MOTIVATION: The increasing availability of mitochondria-targeted and off-target sequencing data in whole-exome and whole-genome sequencing studies (WXS and WGS) has risen the demand of effective pipelines to accurately measure heteroplasmy and to easily recognize the most functionally important mitochondrial variants among a huge number of candidates. To this purpose, we developed MToolBox, a highly automated pipeline to reconstruct and analyze human mitochondrial DNA from high-throughput sequencing data. RESULTS: MToolBox implements an effective computational strategy for mitochondrial genomes assembling and haplogroup assignment also including a prioritization analysis of detected variants. MToolBox provides a Variant Call Format file featuring, for the first time, allele-specific heteroplasmy and annotation files with prioritized variants. MToolBox was tested on simulated samples and applied on 1000 Genomes WXS datasets. AVAILABILITY AND IMPLEMENTATION: MToolBox package is available at https://sourceforge.net/projects/mtoolbox/.

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.

Extraction and annotation of human mitochondrial genomes from 1000 Genomes Whole Exome Sequencing data.

BACKGROUND: Whole Exome Sequencing (WES) is one of the most used and cost-effective next generation technologies that allows sequencing of all nuclear exons. Off-target regions may be captured if they present high sequence similarity with baits. Bioinformatics tools have been optimized to retrieve a large amount of WES off-target mitochondrial DNA (mtDNA), by exploiting the aspecificity of probes, partially overlapping to Nuclear mitochondrial Sequences (NumtS). The 1000 Genomes project represents one of the widest resources to extract mtDNA sequences from WES data, considering the large effort the scientific community is undertaking to reconstruct human population history using mtDNA as marker, and the involvement of mtDNA in pathology. RESULTS: A previously published pipeline aimed at assembling mitochondrial genomes from off-target WES reads and further improved to detect insertions and deletions (indels) and heteroplasmy in a dataset of 1242 samples from the 1000 Genomes project, enabled to obtain a nearly complete mitochondrial genome from 943 samples (76% analyzed exomes). The robustness of our computational strategy was highlighted by the reduction of reads amount recognized as mitochondrial in the original annotation produced by the Consortium, due to NumtS filtering. CONCLUSIONS: To the best of our knowledge, this is likely the most extended population-scale mitochondrial genotyping in humans enriched with the estimation of heteroplasmies.

Deep sequencing unearths nuclear mitochondrial sequences under Leber's hereditary optic neuropathy-associated false heteroplasmic mitochondrial DNA variants.

Leber's hereditary optic neuropathy (LHON) is associated with mitochondrial DNA (mtDNA) ND mutations that are mostly homoplasmic. However, these mutations are not sufficient to explain the peculiar features of penetrance and the tissue-specific expression of the disease and are believed to be causative in association with unknown environmental or other genetic factors. Discerning between clear-cut pathogenetic variants, such as those that appear to be heteroplasmic, and less penetrant variants, such as the homoplasmic, remains a challenging issue that we have addressed here using next-generation sequencing approach. We set up a protocol to quantify MTND5 heteroplasmy levels in a family in which the proband manifests a LHON phenotype. Furthermore, to study this mtDNA haplotype, we applied the cybridization protocol. The results demonstrate that the mutations are mostly homoplasmic, whereas the suspected heteroplasmic feature of the observed mutations is due to the co-amplification of Nuclear mitochondrial Sequences.

HmtDB, a genomic resource for mitochondrion-based human variability studies.

HmtDB (http://www.hmtdb.uniba.it:8080/hmdb) is a open resource created to support population genetics and mitochondrial disease studies. The database hosts human mitochondrial genome sequences annotated with population and variability data, the latter being estimated through the application of the SiteVar software based on site-specific nucleotide and amino acid variability calculations. The annotations are manually curated thus adding value to the quality of the information provided to the end-user. Classifier tools implemented in HmtDB allow the prediction of the haplogroup for any human mitochondrial genome currently stored in HmtDB or externally submitted de novo by an end-user. Haplogroup definition is based on the Phylotree system. End-users accessing HmtDB are hence allowed to (i) browse the database through the use of a multi-criterion 'query' system; (ii) analyze their own human mitochondrial sequences via the 'classify' tool (for complete genomes) or by downloading the 'fragment-classifier' tool (for partial sequences); (iii) download multi-alignments with reference genomes as well as variability data.

A platform independent RNA-Seq protocol for the detection of transcriptome complexity.

BACKGROUND: Recent studies have demonstrated an unexpected complexity of transcription in eukaryotes. The majority of the genome is transcribed and only a little fraction of these transcripts is annotated as protein coding genes and their splice variants. Indeed, most transcripts are the result of antisense, overlapping and non-coding RNA expression. In this frame, one of the key aims of high throughput transcriptome sequencing is the detection of all RNA species present in the cell and the first crucial step for RNA-seq users is represented by the choice of the strategy for cDNA library construction. The protocols developed so far provide the utilization of the entire library for a single sequencing run with a specific platform. RESULTS: We set up a unique protocol to generate and amplify a strand-specific cDNA library representative of all RNA species that may be implemented with all major platforms currently available on the market (Roche 454, Illumina, ABI/SOLiD). Our method is reproducible, fast, easy-to-perform and even allows to start from low input total RNA. Furthermore, we provide a suitable bioinformatics tool for the analysis of the sequences produced following this protocol. CONCLUSION: We tested the efficiency of our strategy, showing that our method is platform-independent, thus allowing the simultaneous analysis of the same sample with different NGS technologies, and providing an accurate quantitative and qualitative portrait of complex whole transcriptomes.

Placing mitochondrial DNA mutations within the progression model of type I endometrial carcinoma.

Mitochondrial DNA (mtDNA) mutations have been described in almost all types of cancer. However, their exact role and timing of occurrence during tumor development and progression are still a matter of debate. A Vogelstein-like model of progression is well established for endometrial carcinoma (EC), however, mtDNA has been scarcely investigated in these tumors despite the fact that mitochondrial biogenesis increase has been shown to be a hallmark of type I EC. Here, we screened a panel of 23 type I EC tissues and matched typical hyperplasia for mutations in mtDNA and in four oncosupressors/oncogenes, namely PTEN, KRAS, CTNNB1 and TP53. Overall, mtDNA mutations were identified in 69% of cases, while mutational events in nuclear genes occurred in 56% of the cases, indicating that mtDNA mutations may precede the genetic instability of these genes canonically involved in progression from hyperplasia to tumor. Protein expression analysis revealed an increase in mitochondrial biogenesis and activation of oxidative stress response mechanisms in tumor tissues, but not in hyperplasia, in correlation with the occurrence of pathogenic mtDNA mutations. Our results point out an involvement of mtDNA mutations in EC progression and explain the increase in mitochondrial biogenesis of type I EC. Last, since mtDNA mutations occur after hyperplasia, their potential role in contributing to genetic instability may be envisioned.

Immunohistochemical, pharmacovigilance, and omics analyses reveal the involvement of ATP-sensitive K+ channel subunits in cancers: role in drug-disease interactions.

Background: ATP-sensitive-K+ channels (KATP) are involved in diseases, but their role in cancer is poorly described. Pituitary macroadenoma has been observed in Cantu' syndrome (C.S.), which is associated with the gain-of-function mutations of the ABCC9 and KCNJ8 genes. We tested the role of the ABCC8/Sur1, ABCC9/Sur2A/B, KCNJ11/Kir6.2, and KCNJ8/Kir6.1 genes experimentally in a minoxidil-induced renal tumor in male rats and in the female canine breast cancer, a spontaneous animal model of disease, and in the pharmacovigilance and omics databases. Methods: We performed biopsies from renal tissues of male rats (N = 5) following a sub-chronic high dosing topical administration of minoxidil (0.777-77.7 mg/kg/day) and from breast tissues of female dogs for diagnosis (N = 23) that were analyzed by immunohistochemistry. Pharmacovigilance and omics data were extracted from EudraVigilance and omics databases, respectively. Results: An elevated immunohistochemical reactivity to Sur2A-mAb was detected in the cytosol of the Ki67+/G3 cells other than in the surface membrane in the minoxidil-induced renal tumor and the breast tumor samples. KCNJ11, KCNJ8, and ABCC9 genes are upregulated in cancers but ABCC8 is downregulated. The Kir6.2-Sur2A/B-channel opener minoxidil showed 23 case reports of breast cancer and one case of ovarian cancer in line with omics data reporting, respectively, and the negative and positive prognostic roles of the ABCC9 gene in these cancers. Sulfonylureas and glinides blocking the pancreatic Kir6.2-Sur1 subunits showed a higher risk for pancreatic cancer in line with the positive prognostic role of the ABCC8 gene but low risks for common cancers. Glibenclamide, repaglinide, and glimepiride show a lower cancer risk within the KATP channel blockers. The Kir6.2-Sur1 opener diazoxide shows no cancer reactions. Conclusion: An elevated expression of the Sur2A subunit was found in proliferating cells in two animal models of cancer. Immunohistochemistry/omics/pharmacovigilance data reveal the role of the Kir6.1/2-Sur2A/B subunits as a drug target in breast/renal cancers and in C.S.

Genome sequence of the polychlorinated-biphenyl degrader Pseudomonas pseudoalcaligenes KF707.

Pseudomonas pseudoalcaligenes KF707 is a soil polychlorinated biphenyl (PCB) degrader, able to grow both planktonically and as a biofilm in the presence of various toxic metals and metalloids. Here we report the genome sequence (5,957,359 bp) of P. pseudoalcaligenes KF707, which provides insights into metabolic degradation pathways, flagellar motility, and chemotaxis.

Primates and mouse NumtS in the UCSC Genome Browser.

BACKGROUND: NumtS (Nuclear MiTochondrial Sequences) are mitochondrial DNA sequences that, after stress events involving the mitochondrion, colonized the nuclear genome. Accurate mapping of NumtS avoids contamination during mtDNA PCR amplification, thus supplying reliable bases for detecting false heteroplasmies. In addition, since they commonly populate mammalian genomes (especially primates) and are polymorphic, in terms of presence/absence and content of SNPs, they may be used as evolutionary markers in intra- and inter-species population analyses. RESULTS: The need for an exhaustive NumtS annotation led us to produce the Reference Human NumtS compilation, followed, as reported in this paper, by those for chimpanzee, rhesus macaque and mouse ones. Identification of NumtS inside the UCSC Genome Browser and their inter-species comparison required the design and the implementation of NumtS tracks, starting from the compilation data. NumtS retrieval through the UCSC Genome Browser, in the species examined, is now feasible at a glance. CONCLUSIONS: Analyses involving NumtS tracks, together with other genome element tracks publicly available at the UCSC Genome Browser, can provide deep insight into genome evolution and comparative genomics, thus improving studies dealing with the mechanisms that drove the generation of NumtS. In addition, the NumtS tracks constitute a useful tool in the design of mitochondrial DNA primers.

The genetic and metabolic signature of oncocytic transformation implicates HIF1alpha destabilization.

We previously showed that disruptive complex I mutations in mitochondrial DNA are the main genetic hallmark of oncocytic tumors of the thyroid and kidney. We here report a high frequency of homoplasmic disruptive mutations in a large panel of oncocytic pituitary and head-and-neck tumors. The presence of such mutations implicates disassembly of respiratory complex I in vivo which in turn contributes to the inability of oncocytic tumors to stabilize HIF1alpha and to display pseudo-hypoxia. By utilizing transmitochondrial cytoplasmic hybrids (cybrids), we induced the shift to homoplasmy of a truncating mutation in the mitochondria-coded MTND1 gene. Such shift is associated with a profound metabolic impairment leading to the imbalance of alpha-ketoglutarate and succinate, the Krebs cycle metabolites which are the main responsible for HIF1alpha stabilization. We conclude that the main hallmarks of oncocytic transformation, namely the occurrence of homoplasmic disruptive mutations and complex I disassembly, may explain the benign nature of oncocytic neoplasms through lack of HIF1alpha stabilization.