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High-Throughput Sequencing technologies are transforming many research fields, including the analysis of phage display libraries. The phage display technology coupled with deep sequencing was introduced more than a decade ago and holds the potential to circumvent the traditional laborious picking and testing of individual phage rescued clones. However, from a bioinformatics point of view, the analysis of this kind of data was always performed by adapting tools designed for other purposes, thus not considering the noise background typical of the ‘interactome sequencing’ approach and the heterogeneity of the data. InteractomeSeq is a web server allowing data analysis of protein domains (‘domainome’) or epitopes (‘epitome’) from either Eukaryotic or Prokaryotic genomic phage libraries generated and selected by following an Interactome sequencing approach. InteractomeSeq allows users to upload raw sequencing data and to obtain an accurate characterization of domainome/epitome profiles after setting the parameters required to tune the analysis. The release of this tool is relevant for the scientific and clinical community, because InteractomeSeq will fill an existing gap in the field of large-scale biomarkers profiling, reverse vaccinology, and structural/functional studies, thus contributing essential information for gene annotation or antigen identification. InteractomeSeq is freely available at https://InteractomeSeq.ba.itb.cnr.it/

A holistic understanding of environmental communities is the new challenge of metagenomics. Accordingly, the amplicon-based or metabarcoding approach, largely applied to investigate bacterial microbiomes, is moving to the eukaryotic world too. Indeed, the analysis of metabarcoding data may provide a comprehensive assessment of both bacterial and eukaryotic composition in a variety of environments, including human body. In this respect, whereas hypervariable regions of the 16S rRNA are the de facto standard barcode for bacteria, the Internal Transcribed Spacer 1 (ITS1) of ribosomal RNA gene cluster has shown a high potential in discriminating eukaryotes at deep taxonomic levels. As metabarcoding data analysis rely on the availability of a well-curated barcode reference resource, a comprehensive collection of ITS1 sequences supplied with robust taxonomies, is highly needed. To address this issue, we created ITSoneDB (available at http://itsonedb.cloud.ba.infn.it/) which in its current version hosts 985 240 ITS1 sequences spanning over 134 000 eukaryotic species. Each ITS1 is mapped on the NCBI reference taxonomy with its start and end positions precisely annotated. ITSoneDB has been developed in agreement to the FAIR guidelines by enabling the users to query and download its content through a simple web-interface and access relevant metadata by cross-linking to European Nucleotide Archive.

The structural and conformational organization of chromosomes is crucial for gene expression regulation in eukaryotes and prokaryotes as well. Up to date, gene expression data generated using either microarray or RNA-sequencing are available for many bacterial genomes. However, differential gene expression is usually investigated with methods considering each gene independently, thus not taking into account the physical localization of genes along a bacterial chromosome. Here, we present WoPPER, a web tool integrating gene expression and genomic annotations to identify differentially expressed chromosomal regions in bacteria. RNA-sequencing or microarray-based gene expression data are provided as input, along with gene annotations. The user can select genomic annotations from an internal database including 2780 bacterial strains, or provide custom genomic annotations. The analysis produces as output the lists of positionally related genes showing a coordinated trend of differential expression. Graphical representations, including a circular plot of the analyzed chromosome, allow intuitive browsing of the results. The analysis procedure is based on our previously published R-package PREDA. The release of this tool is timely and relevant for the scientific community, as WoPPER will fill an existing gap in prokaryotic gene expression data analysis and visualization tools. WoPPER is open to all users and can be reached at the following URL: https://WoPPER.ba.itb.cnr.it

Multiple sclerosis (MS) is a complex disease of the CNS that usually affects young adults, although 3-5% of cases are diagnosed in childhood and adolescence (hence called pediatric MS, PedMS). Genetic predisposition, among other factors, seems to contribute to the risk of the onset, in pediatric as in adult ages, but few studies have investigated the genetic 'environmentally naïve' load of PedMS. The main goal of this study was to identify circulating markers (miRNAs), target genes (mRNAs) and functional pathways associated with PedMS; we also verified the impact of miRNAs on clinical features, i.e. disability and cognitive performances. The investigation was performed in 19 PedMS and 20 pediatric controls (PCs) using a High-Throughput Next-generation Sequencing (HT-NGS) approach followed by an integrated bioinformatics/biostatistics analysis. Twelve miRNAs were significantly upregulated (let-7a-5p, let-7b-5p, miR-25-3p, miR-125a-5p, miR-942-5p, miR-221-3p, miR-652-3p, miR-182-5p, miR-185-5p, miR-181a-5p, miR-320a, miR-99b-5p) and 1 miRNA was downregulated (miR-148b-3p) in PedMS compared with PCs. The interactions between the significant miRNAs and their targets uncovered predicted genes (i.e. TNFSF13B, TLR2, BACH2, KLF4) related to immunological functions, as well as genes involved in autophagy-related processes (i.e. ATG16L1, SORT1, LAMP2) and ATPase activity (i.e. ABCA1, GPX3). No significant molecular profiles were associated with any PedMS demographic/clinical features. Both miRNAs and mRNA expressions predicted the phenotypes (PedMS-PC) with an accuracy of 92% and 91%, respectively. In our view, this original strategy of contemporary miRNA/mRNA analysis may help to shed light in the genetic background of the disease, suggesting further molecular investigations in novel pathogenic mechanisms.

The 5' and 3' untranslated regions of eukaryotic mRNAs (UTRs) play crucial roles in the post-trans-criptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and message stability. UTRdb is a curated database of 5' and 3' untranslated sequences of eukaryotic mRNAs, derived from several sources of primary data. Experimentally validated functional motifs are annotated and also collated as the UTRsite database where more specific information on the functional motifs and cross-links to interacting regulatory protein are provided. In the current update, the UTR entries have been organized in a gene-centric structure to better visualize and retrieve 5' and 3' UTR variants generated by alter-native initiation and termination of transcription and alternative splicing. Experimentally validated miRNA targets and conserved sequence elements are also annotated. The integration of UTRdb with genomic data has allowed the implementation of an efficient annotation system and a powerful retrieval resource for the selection and extraction of specific UTR subsets. All internet resources implemented for retrieval and functional analysis of 5' and 3' untranslated regions of eukaryotic mRNAs are accessible at http://utrdb.ba.itb.cnr.it/.

We present here a novel methodology for the identification of genome regions potentially spanning one or more protein coding genes. It is based on the detection of clusters of conserved sequence tags whose evolutionary dynamics, based on the observation of an excess bias of synonymous substitutions at nucleotide level and of conservative replacements at protein level, suggests a likely protein coding role. A benchmark test carried out on a 236 Mbp of human-mouse syntenic regions from human chromosomes 15, 21 and 22 identified 25 CST clusters potentially containing unannotated genes. A further annotation update of the human genome assembly revealed that 11/25 clusters actually contained a total of 20 validated genes and 10 of the remaining 14 clusters had several experimental evidence in support of the presence of protein coding genes. These findings demonstrate the effectiveness and high prediction reliability of the proposed methodology which could specifically be applied to the annotation of novel genome sequences.

The 5' and 3' untranslated regions of eukaryotic mRNAs play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and message stability. UTRdb is a curated database of 5' and 3' untranslated sequences of eukaryotic mRNAs, derived from several sources of primary data. Experimentally validated functional motifs are annotated (and also collated as the UTRsite database) and cross-links to genomic and protein data are provided. The integration of UTRdb with genomic and protein data has allowed the implementation of a powerful retrieval resource for the selection and extraction of UTR subsets based on their genomic coordinates and/or features of the protein encoded by the relevant mRNA (e.g. GO term, PFAM domain, etc.). All internet resources implemented for retrieval and functional analysis of 5' and 3' untranslated regions of eukaryotic mRNAs are accessible at http://www.ba.itb.cnr.it/UTR/.

The crucial role of the non-coding portion of genomes is now widely acknowledged. In particular, mRNA untranslated regions are involved in many post-transcriptional regulatory pathways that control mRNA localisation, stability and translation efficiency. A review is given of the most recent research works on the functional characterisation of eukaryotic mRNA untranslated regions. In order to make possible a systematic and detailed sequence analysis of mRNA untranslated regions (UTRs), a non-redundant database of metazoan mRNA untranslated sequences annotated for the occurrence of specific functional elements, UTRdb, was devised. These elements, whose consensus structure has been devised on the basis of experimental assays and of comparative analyses, have been collected in the UTRsite database. A suitable pattern-matching software has been devised to search UTRsite patterns in user-submitted sequences, also assessing their statistical significance. Structural, compositional and evolutionary features of untranslated sequences of metazoan mRNAs have been investigated showing peculiar intra- and interspecific patterns.

Motivations. Short non-coding RNA molecules (20-30 nucleotides long) play an important role in the regulation of gene expression by interacting with their target RNAs. This interaction generally downregulates gene expression either affecting RNA stability or repressing translation. Different classes of small regulatory non coding RNAs (sncRNAs) have been discovered and studied so far, and new families continue to be described, which differ in the proteins required for their biogenesis, the mechanism of target recognition and regulation, and the biological pathways they control [1,2]. In particular, three major classes of sncRNAs have been mostly investigated: small interfering RNAs (siRNAs), micro-RNAs (miRNAs) and PIWI-interacting RNAs (piRNAs) [1,2,3]. siRNAs direct the endonucleolytic cleavage of their target RNAs through a mechanism known as RNA interference (RNAi), miRNAs can repress translation or direct degradation of their target mRNA generally through imperfect complementary pairing on their 3'UTRs, whereas the major role of piRNAs is to ensure germline stability by repressing transposable elements (TEs). Recently, the advent of new Next-Generation Sequencing (NGS) technologies has awfully increased the throughput of transcriptome studies, thus allowing an unprecedented investigation of non-coding RNAs. Regulatory pathways involving ncRNAs, such as miRNAs, are now being elucidated in detail and functions for long non-coding RNAs are also emerging. The huge amount of transcript data produced by high-throughput sequencing requires the development and implementation of suitable bioinformatics workflows for their analysis and interpretation. Here we describe here a bioinformatics resource to classify and analyze the non-coding RNA component of human transcriptome sequence data obtained by different NGS platforms (Roche 454, Illumina and Solid). Methods. The ncRNAs bioinformatics platform is organized according to a typical three tier architecture: an analysis tier for ncRNAs detection, classification and functional analyses; a data tier made up of a data-warehouse used to store the analysis results, the ncRNAs reference database (a non-redundant collection of ncRNAs sequence retrieved from fRNAdb, RNAdb, mirBASE, NONCODE and others), the reference genome and other useful annotation database like HGNC nomenclature [4], Sequence Ontology (SO) [5] and Entrez Gene; a web tier module for querying the analysis results and the annotation stored in the ncRNAs reference database. The core of the platform is the analysis workflow. In figure 1 we show the pipeline for classification and functional annotations of non-coding RNAs (ncRNAs) fraction obtained through high-throughput sequencing (HTS) experiments using different NGS technologies. The input data for the bioinformatics platform can be either the reads data obtained by different NGS platforms (Roche 454, Illumina and Solid) or previously mapped reads stored in users' SAM/BAM files. Results. The ncRNA bioinformatics platform - through a combination of an analyses pipeline, a datawarehouse and a user-friendly web interface - is able to: i. detect and classify reads in known functional ncRNA categories using Sequence Ontology classification, HGNC nomenclature, gene names and miRNA accessions; ii. extract reads collections belonging to a givencategory for further analysis; iii. quantify ncRNA expression based on annotations derived from different reference ncRNA databases; iv. generate some statistics of expressed ncRNAs, indicating the RPKM (reads per kilobase of RNA model per million mapped reads)value for each Sequence Ontology class; v. detect differential expression of ncRNAs between two conditions (i.e. normal/pathological); vi. create a collections of interesting clusters of reads mapped on the genome but not detected as known ncRNA; vii. filter out reads mapping to ribosomal RNAs and mtDNA transcripts; viii. create a collection of unmapped residual reads (chimeras, artifacts, and contaminations). References 1. Ghildiyal, M. and Zamore, P. D. Small (2009) Silencing RNAs: an expanding universe. Nature Rev. Genet. 10, 94-108. 2. Malone, C. D. and Hannon, G. J. (2009) Small RNAs as guardians of the genome. Cell 136, 656-668 3. Kim, N. V., Han, J. '& Siomi M. C. (2009) Biogenesis of small RNAs in animals. Nature Rev. Mol. Cell Biol. 10, 126-139 4. Wright M '& Bruford E (2011) Naming 'junk': Human non-protein coding RNA (ncRNA) gene nomenclature. Human Genomics, VOL 5. NO 2. 90-98. 5. Eilbeck et al. (2005) The Sequence Ontology: A tool for the unification of genome annotations. Genome Biology 6:R44

Background The p53 gene family consists of the three genes p53, p63 and p73, which have polyhedral non-overlapping functions in pivotal cellular processes such as DNA synthesis and repair, growth arrest, apoptosis, genome stability, angiogenesis, development and differentiation. These genes encode sequence-specific nuclear transcription factors that recognise the same responsive element (RE) in their target genes. Their inactivation or aberrant expression may determine tumour progression or developmental disease. The discovery of several protein isoforms with antagonistic roles, which are produced by the expression of different promoters and alternative splicing, widened the complexity of the scenario of the transcriptional network of the p53 family members. Therefore, the identification of the genes transactivated by p53 family members is crucial to understand the specific role for each gene in cell cycle regulation. We have combined a genome-wide computational search of p53 family REs and microarray analysis to identify new direct target genes. The huge amount of biological data produced has generated a critical need for bioinformatic tools able to manage and integrate such data and facilitate their retrieval and analysis. Description We have developed the p53FamTaG database (p53 FAMily TArget Genes), a modular relational database, which contains p53 family direct target genes selected in the human genome searching for the presence of the REs and the expression profile of these target genes obtained by microarray experiments. p53FamTaG database also contains annotations of publicly available databases and links to other experimental data. The genome-wide computational search of the REs was performed using PatSearch, a pattern-matching program implemented in the DNAfan tool. These data were integrated with the microarray results we produced from the overexpression of different isoforms of p53, p63 and p73 stably transfected in isogenic cell lines, allowing the comparative study of the transcriptional activity of all the proteins in the same cellular background. p53FamTaG database is available free at http://www2.ba.itb.cnr.it/p53FamTaG/ Conclusion p53FamTaG represents a unique integrated resource of human direct p53 family target genes that is extensively annotated and provides the users with an efficient query/retrieval system which displays the results of our microarray experiments and allows the export of RE sequences. The database was developed for supporting and integrating high-throughput in silico and experimental analyses and represents an important reference source of knowledge for research groups involved in the field of oncogenesis, apoptosis and cell cycle regulation.

Summary: GenoMiner is a software tool that searches for regions of similarity between user-submitted genome or transcript sequences and user-specified whole genome assemblies. The program then identifies conserved sequence tags (CSTs) in these homologous regions and provides a prediction of their coding or non-coding nature. The analysis is carried out through three steps: (1) definition of sequence regions homologous to the query sequence in the selected target genomes by a fast BLAT alignment; (2) identification of CSTs by a more sensitive BLAST-like alignment between the query and the homologous regions in the target genomes and (3) assessment of the coding or non-coding nature of detected CSTs through the computation of a suitable coding potential score. GenoMiner allows the user to search the query sequence against a number of vertebrate genome assemblies in a single run providing a user-friendly graphical output. Availability: . GenoMiner software and documentation is available from the authors upon request. Contact: graziano.pesole@unimi.it

Background Mitochondria are sub-cellular organelles that have a central role in energy production and in other metabolic pathways of all eukaryotic respiring cells. In the last few years, with more and more genomes being sequenced, a huge amount of data has been generated providing an unprecedented opportunity to use the comparative analysis approach in studies of evolution and functional genomics with the aim of shedding light on molecular mechanisms regulating mitochondrial biogenesis and metabolism. In this context, the problem of the optimal extraction of representative datasets of genomic and proteomic data assumes a crucial importance. Specialised resources for nuclear-encoded mitochondria-related proteins already exist; however, no mitochondrial database is currently available with the same features of MitoRes, which is an update of the MitoNuc database extensively modified in its structure, data sources and graphical interface. It contains data on nuclear-encoded mitochondria-related products for any metazoan species for which this type of data is available and also provides comprehensive sequence datasets (gene, transcript and protein) as well as useful tools for their extraction and export. Description MitoRes http://www2.ba.itb.cnr.it/MitoRes/ consolidates information from publicly external sources and automatically annotates them into a relational database. Additionally, it also clusters proteins on the basis of their sequence similarity and interconnects them with genomic data. The search engine and sequence management tools allow the query/retrieval of the database content and the extraction and export of sequences (gene, transcript, protein) and related sub-sequences (intron, exon, UTR, CDS, signal peptide and gene flanking regions) ready to be used for in silico analysis. Conclusion The tool we describe here has been developed to support lab scientists and bioinformaticians alike in the characterization of molecular features and evolution of mitochondrial targeting sequences. The way it provides for the retrieval and extraction of sequences allows the user to overcome the obstacles encountered in the integrative use of different bioinformatic resources and the completeness of the sequence collection allows intra- and interspecies comparison at different biological levels (gene, transcript and protein).

The identification and characterization of genome tracts that are highly conserved across species during evolution may contribute significantly to the functional annotation of whole-genome sequences. Indeed, such sequences are likely to correspond to known or unknown coding exons or regulatory motifs. Here, we present a web server implementing a previously developed algorithm that, by comparing user-submitted genome sequences, is able to identify statistically significant conserved blocks and assess their coding or noncoding nature through the measure of a coding potential score. The web tool, available at http://www.caspur.it/CSTminer/, is dynamically interconnected with the Ensembl genome resources and produces a graphical output showing a map of detected conserved sequences and annotated gene features.

The identification of conserved sequence tags (CSTs) through comparative genome analysis may reveal important regulatory elements involved in shaping the spatio-temporal expression of genetic information. It is well known that the most significant fraction of CSTs observed in human-mouse comparisons correspond to protein coding exons, due to their strong evolutionary constraints. As we still do not know the complete gene inventory of the human and mouse genomes it is of the utmost importance to establish if detected conserved sequences are genes or not. We propose here a simple algorithm that, based on the observation of the specific evolutionary dynamics of coding sequences, efficiently discriminates between coding and non-coding CSTs. The application of this method may help the validation of predicted genes, the prediction of alternative splicing patterns in known and unknown genes and the definition of a dictionary of non-coding regulatory elements.

Regulation of gene expression at transcriptional and post-transcriptional level involves the interaction between short DNA or RNA tracts and the corresponding trans-acting protein factors. Detection of such cis-acting elements in genome-wide screenings may significantly contribute to genome annotation and comparative analysis as well as to target functional characterization experiments. We present here PatSearch, a flexible and fast pattern matcher able to search for specific combinations of oligonucleotide consensus sequences, secondary structure elements and position-weight matrices. It can also allow for mismatches/mispairings below a user fixed threshold. We report three different applications of the program in the search of complex patterns such as those of the iron responsive element hairpin-loop structure, the p53 responsive element and a promoter module containing CAAT-, TATA- and cap-boxes. PatSearch is available on the web at http://bighost.area.ba.cnr.it/BIG/PatSearch/.

Mitochondria, besides their central role in energy metabolism, have recently been found to be involved in a number of basic processes of cell life and to contribute to the pathogenesis of many degenerative diseases. All functions of mitochondria depend on the interaction of nuclear and organelle genomes. Mitochondrial genomes have been extensively sequenced and analysed and data have been collected in several specialised databases. In order to collect information on nuclear coded mitochondrial proteins we developed MitoNuc, a database containing detailed information on sequenced nuclear genes coding for mitochondrial proteins in Metazoa. The MitoNuc database can be retrieved through SRS and is available via the web site http://bighost.area.ba.cnr.it/mitochondriome where other mitochondrial databases developed by our group, the complete list of the sequenced mitochondrial genomes, links to other mitochondrial sites and related information, are available. The MitoAln database, related to MitoNuc in the previous release, reporting the multiple alignments of the relevant homologous protein coding regions, is no longer supported in the present release. In order to keep the links among entries in MitoNuc from homologous proteins, a new field in the database has been defined: the cluster identifier, an alpha numeric code used to identify each cluster of homologous proteins. A comment field derived from the corresponding SWISS-PROT entry has been introduced; this reports clinical data related to dysfunction of the protein. The logic scheme of MitoNuc database has been implemented in the ORACLE DBMS. This will allow the end-users to retrieve data through a friendly interface that will be soon implemented.

The crucial role of the non-coding portion of genomes is now widely acknowledged. In particular, mRNA untranslated regions are involved in many post-transcriptional regulatory pathways that control mRNA localization, stability and translation efficiency. We review in this paper the major structural and compositional features of eukaryotic mRNA untranslated regions and provide some examples of bioinformatic analyses for their functional characterization.

The AUG start codon context features have been investigated by analyzing eukaryotic mRNAs belonging to various taxonomic groups. The functional relevance of each specific position surrounding the AUG start codon has been established as a function of the measured shift between base composition observed at that particular position, and base composition averaged over all the 5′untranslated regions. A more detailed analysis carried out on human genes belonging to different isochores showed significant isochore-specific fea-tures that cannot be explained only by a mutational bias effect. The most represented heptamers spanning from position −3 to +4 with respect to the initiator AUG have been determined for mRNAs belonging to different taxonomic groups and a web page utility has been set up (http://bigarea.area.ba.cnr.it:8000/BioWWW/ATG.html) to determine the relative abundance of a user submitted oligonucleotide context in a given species or taxon.

The important role of 5′ and 3′ untranslated regions of eukaryotic mRNAs in gene regulation and expression is now widely accepted. In order to study the general structural and compositional features of these sequences we developed UTRdb, a specialized database of 5′ and 3′-UTR sequences from seven different taxonomic groups of eukaryotic mRNAs cleaned of redundancy. The analysis of the UTR sequences contained in this database showed that 5′-UTR sequences, on average 200 nucleotides long, are 1.5-3 times shorter than the corresponding 3′-UTR sequences in the various taxonomic groups considered here. As to their compositional properties on average 5′-UTR sequences resulted in all cases GC richer than 3′-UTR sequences, and significant correlations were found between the GC content of 5′ and 3′-UTR sequences and the GC content of the third silent codon positions of the corresponding protein coding genes. The dinucleotide analysis showed a differential depletion of CpG in vertebrate 5′ and 3′-UTR, with 5′-UTR sequences being more CpG-rich, and a generalized depletion of TpA in both 5′ and 3′-UTR was observed in all eukaryotic sequence collections.

The important role that untranslated regions of mRNAs (UTR) may play in gene regulation and expression is now widely accepted. For this reason we developed UTRDB, a specialized database of 5'- and 3'-UTR of eukaryotic mRNAs cleaned of redundancy. This paper describes the composition and the general feature of UTRDB. The analysis of UTRDB by using suitable statistical methods could provide useful information for guiding the experimental work aimed at delucidating the role of UTR sequences in gene regulation and expression.

Mitochondria, besides their central role in energy metabolism, have recently been found to be involved in a number of basic processes of cell life and to contribute to the pathogenesis of many degenerative diseases. All functions of mitochondria depend on the interaction of nuclear and organellar genomes. Mitochondrial genomes have been extensively sequenced and analysed and the data collected in several specialised databases. In order to collect information on nuclear coded mitochondrial proteins we developed MitoNuc and MitoAln, two related databases containing, respectively, detailed information on sequenced nuclear genes coding for mitochondrial proteins in Metazoa and yeast, and the multiple alignments of the relevant homologous protein coding regions. MitoNuc and MitoAln retrieval through SRS at http://bio-www.ba.cnr.it:8000/srs6/ can easily allow the extraction of sequence data, subsequences defined by specific features and nucleotide or amino acid multiple alignments.

The-5' and 3' untranslated regions of eukaryotic mRNAs may play a crucial role in the regulation of gene expression controlling mRNA localization, stability and translational efficiency. For this reason we developed UTRdb, a specialized database of 5' end 3' untranslated sequences of eukaryotic mRNAs cleaned from redundancy. UTRdb entries are enriched with specialized information not present in the primary databases including the presence of nucleotide sequence patterns already demonstrated by experimental analysis to have some functional role. All these patterns have been collected in the UTRsite database so that it is possible to search any input sequence for the presence of annotated functional motifs, Furthermore, UTRdb entries have been annotated for the presence of repetitive elements. All internet resources implemented for retrieval and functional analysis of 5' and 3' untranslated regions of eukaryotic mRNAs are accessible at http://bigarea.area.ba.cnr. it:8000/EmbIT/UTRHome/.

Background The accurate detection of genes and the identification of functional regions is still an open issue in the annotation of genomic sequences. This problem affects new genomes but also those of very well studied organisms such as human and mouse where, despite the great efforts, the inventory of genes and regulatory regions is far from complete. Comparative genomics is an effective approach to address this problem. Unfortunately it is limited by the computational requirements needed to perform genome-wide comparisons and by the problem of discriminating between conserved coding and non-coding sequences. This discrimination is often based (thus dependent) on the availability of annotated proteins. Results In this paper we present the results of a comprehensive comparison of human and mouse genomes performed with a new high throughput grid-based system which allows the rapid detection of conserved sequences and accurate assessment of their coding potential. By detecting clusters of coding conserved sequences the system is also suitable to accurately identify potential gene loci. Following this analysis we created a collection of human-mouse conserved sequence tags and carefully compared our results to reliable annotations in order to benchmark the reliability of our classifications. Strikingly we were able to detect several potential gene loci supported by EST sequences but not corresponding to as yet annotated genes. Conclusion Here we present a new system which allows comprehensive comparison of genomes to detect conserved coding and non-coding sequences and the identification of potential gene loci. Our system does not require the availability of any annotated sequence thus is suitable for the analysis of new or poorly annotated genomes.