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.

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/.

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.

BACKGROUND: One of the most frequent uses of bioinformatics tools concerns functional characterization of a newly produced nucleotide sequence (a query sequence) by applying Blast or FASTA against a set of sequences (the subject sequences). However, in some specific contexts, it is useful to compare the query sequence against a cluster such as a MultiAlignment (MA). We present here the RegExpBlasting (REB) algorithm, which compares an unclassified sequence with a dataset of patterns defined by application of Regular Expression rules to a given-as-input MA datasets. The REB algorithm workflow consists in i. the definition of a dataset of multialignments ii. the association of each MA to a pattern, defined by application of regular expression rules; iii. automatic characterization of a submitted biosequence according to the function of the sequences described by the pattern best matching the query sequence. RESULTS: An application of this algorithm is used in the "characterize your sequence" tool available in the PPNEMA resource. PPNEMA is a resource of Ribosomal Cistron sequences from various species, grouped according to nematode genera. It allows the retrieval of plant nematode multialigned sequences or the classification of new nematode rDNA sequences by applying REB. The same algorithm also supports automatic updating of the PPNEMA database. The present paper gives examples of the use of REB within PPNEMA. CONCLUSION: The use of REB in PPNEMA updating, the PPNEMA "characterize your sequence" option clearly demonstrates the power of the method. Using REB can also rapidly solve any other bioinformatics problem, where the addition of a new sequence to a pre-existing cluster is required. The statistical tests carried out here show the powerful flexibility of the method.

BACKGROUND: Population genetics studies based on the analysis of mtDNA and mitochondrial disease studies have produced a huge quantity of sequence data and related information. These data are at present worldwide distributed in differently organised databases and web sites not well integrated among them. Moreover it is not generally possible for the user to submit and contemporarily analyse its own data comparing them with the content of a given database, both for population genetics and mitochondrial disease data. RESULTS: HmtDB is a well-integrated web-based human mitochondrial bioinformatic resource aimed at supporting population genetics and mitochondrial disease studies, thanks to a new approach based on site-specific nucleotide and aminoacid variability estimation. HmtDB consists of a database of Human Mitochondrial Genomes, annotated with population data, and a set of bioinformatic tools, able to produce site-specific variability data and to automatically characterize newly sequenced human mitochondrial genomes. A query system for the retrieval of genomes and a web submission tool for the annotation of new genomes have been designed and will soon be implemented. The first release contains 1255 fully annotated human mitochondrial genomes. Nucleotide site-specific variability data and multialigned genomes can be downloaded. Intra-human and inter-species aminoacid variability data estimated on the 13 coding for proteins genes of the 1255 human genomes and 60 mammalian species are also available. HmtDB is freely available, upon registration, at http://www.hmdb.uniba.it. CONCLUSION: The HmtDB project will contribute towards completing and/or refining haplogroup classification and revealing the real pathogenic potential of mitochondrial mutations, on the basis of variability estimation.

A key concept in comparing sequence collections is the issue of redundancy. The production of sequence collections free from redundancy is undoubtedly very useful, both in performing statistical analyses and accelerating extensive database searching on nucleotide sequences. Indeed, publicly available databases contain multiple entries of identical or almost identical sequences. Performing statistical analysis on such biased data makes the risk of assigning high significance to non-significant patterns very high. In order to carry out unbiased statistical analysis as well as more efficient database searching it is thus necessary to analyse sequence data that have been purged of redundancy. Given that a unambiguous definition of redundancy is impracticable for biological sequence data, in the present program a quantitative description of redundancy will be used, based on the measure of sequence similarity. A sequence is considered redundant if it shows a degree of similarity and overlapping with a longer sequence in the database greater than a threshold fixed by the user. In this paper we present a new algorithm based on an "approximate string matching' procedure, which is able to determine the overall degree of similarity between each pair of sequences contained in a nucleotide sequence database and to generate automatically nucleotide sequence collections free from redundancies.

A new string searching algorithm is presented aimed at searching for the occurrence of character patterns in longer character texts. The algorithm, specifically designed for nucleic acid sequence data, is essentially derived from the Boyer-Moore method (Comm. ACM, 20, 762-772, 1977). Both pattern and text data are compressed so that the natural 4-letter alphabet of nucleic acid sequences is considerably enlarged. The string search starts from the last character of the pattern and proceeds in large jumps through the text to be searched. The data compression and searching algorithm allows one to avoid searching for patterns not present in the text as well as to inspect, for each pattern, all text characters until the exact match with the text is found. These considerations are supported by empirical evidence and comparisons with other methods.

ACNUC is a database structure and retrieval software for use with either the GenBank or EMBL nucleic acid sequence data collections. The nucleotide and textual data furnished by both collections are each restructured into a database that allows sequence retrieval on a multi-criterion basis. The main selection criteria are: species (or higher order taxon), keyword, reference, journal, author, and organelle; all logical combinations of these criteria can be used. Direct access to sequence regions that code for a specific product (protein, tRNA or rRNA) is provided. A versatile extraction procedure copies selected sequences, or fragments of them, from the database to user files suitable to be analysed by user-supplied application programs. A detailed help mechanism is provided to aid the user at any time during the retrieval session. All software has been written in FORTRAN 77 which guarantees a high degree of transportability to minicomputers or mainframes. reference, journal, author, and organelle; all logical combinations of these criteria can be used. Direct access to sequence regions that code for a specific product (protein, tRNA or rRNA) is provided. A versatile extraction procedure copies selected sequences, or fragments of them, from the database to user files suitable to be analysed by user-supplied application programs. A detailed help mechanism is provided to aid the user at any time during the retrieval session. All software has been written in FORTRAN 77 which guarantees a high degree of transportability to minicomputers or mainframes.