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Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities. RESULTS: ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. AVAILABILITY: www.caspur.it/ASPicDB

Motivations One of the main problems in cancer diagnosis by using DNA microarray data is selecting genes relevant for the pathology by analyzing their expression profiles in tissues in two different phenotypical conditions. The question we pose is the following: how do we measure the relevance of a single gene in a given pathology? Methods A gene is relevant for a particular disease if we are able to correctly predict the occurrence of the pathology in new patients on the basis of its expression level only. In other words, a gene is informative for the disease if its expression levels are useful for training a classifier able to generalize, that is, able to correctly predict the status of new patients. In this paper we present a selection bias free, statistically well founded method for finding relevant genes on the basis of their classification ability. Results We applied the method on a colon cancer data set and produced a list of relevant genes, ranked on the basis of their prediction accuracy. We found, out of more than 6500 available genes, 54 overexpressed in normal tissues and 77 overexpressed in tumor tissues having prediction accuracy greater than with p-value. Conclusions The relevance of the selected genes was assessed (a) statistically, evaluating the p-value of the estimate prediction accuracy of each gene; (b) biologically, confirming the involvement of many genes in generic carcinogenic processes and in particular for the colon; (c) comparatively, verifying the presence of these genes in other studies on the same data-set.

Background The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information provided by DNA microarrays allows an approach to the problem of cancer analysis from a quantitative rather than qualitative point of view. Cancer classification requires well founded mathematical methods which are able to predict the status of new specimens with high significance levels starting from a limited number of data. In this paper we assess the performances of Regularized Least Squares (RLS) classifiers, originally proposed in regularization theory, by comparing them with Support Vector Machines (SVM), the state-of-the-art supervised learning technique for cancer classification by DNA microarray data. The performances of both approaches have been also investigated with respect to the number of selected genes and different gene selection strategies. Results We show that RLS classifiers have performances comparable to those of SVM classifiers as the Leave-One-Out (LOO) error evaluated on three different data sets shows. The main advantage of RLS machines is that for solving a classification problem they use a linear system of order equal to either the number of features or the number of training examples. Moreover, RLS machines allow to get an exact measure of the LOO error with just one training. Conclusion RLS classifiers are a valuable alternative to SVM classifiers for the problem of cancer classification by gene expression data, due to their simplicity and low computational complexity. Moreover, RLS classifiers show generalization ability comparable to the ones of SVM classifiers also in the case the classification of new specimens involves very few gene expression levels.

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.).

During the evolution of Metazoa, the mitochondrial genome has remained practically unchanged as indicated by its small size and constant gene content in each lineage, although several evolutionary processes have taken place. In contrast, the nuclear genome of Metazoa has undergone dramatic changes, as is demonstrated by some entire genomes completely sequenced so far. The expansion of gene families and the appearance of new functions and new regulatory circuits are among the most prominent features. Here, we report a description of the evolution of the p53 gene family as an example of expansion of both genetic complexity and gene expression of the nuclear genome

Most evolutionary studies based on molecular data refer to the portion of genomes encoding for proteins. Today, however, more and more attention is paid to the so-called 'non-coding' regions, which constitute a notable portion of the metazoan nuclear genome. Among them, the untranslated regions of messenger RNAs (mRNA UTRs) are particularly important, as they are involved in the regulation of gene expression, controlling translation efficiency as well as mRNA localization and stability. Up to now, only few studies have focused on the analysis of the compositional and structural features of UTRs, or carried out to investigate quantitatively their evolutionary dynamics. For this reason we have carried out an inter-order study on the evolutionary rate of 5' and 3' UTRs with respect to the corresponding coding region in 93 triplets of orthologous genes (selected through a phylogenetic approach, for a total of 645 625 nt) belonging to Primates (Homo sapiens), Artiodactyla (Bos taurus) and Rodentia (Mus spp.). Our study, that considered only likely orthologous genes, has revealed interesting features on the evolution of these regions concerning nucleotide substitution rate and indels and repetitive element distribution. UTRs from different genes showed a remarkable heterogeneity in the evolutionary dynamics, with some homologous so highly divergent to prevent their alignment, and other rather conserved, at least in some regions, most divergent sequence pairs were excluded from our analysis. The comparison between the nucleotide substitution rates calculated for 5' and 3' UTRs with those calculated on synonymous coding position allowed us to verify and measure the existence of functional constraints acting upon the UTRs of different genes which have shown, in many cases, a positive selection driven evolutionary dynamics.

The mitochondrial genome (mtDNA), due to its peculiar features such as exclusive presence of orthologous genes, uniparental inheritance, lack of recombination, small size and constant gene content, certainly represents a major model system in studies on evolutionary genomics in metazoan. In 800 million years of evolution the gene content of metazoan mitochondrial genomes has remained practically frozen but several evolutionary processes have taken place. These processes, reviewed here, include rearrangements of gene order, changes in base composition and arising of compositional asymmetry between the two strands, variations in the genetic code and evolution of codon usage, lineage-specific nucleotide substitution rates and evolutionary patterns of mtDNA control regions

Gene expression is finely regulated at the post-transcriptional level. Features of the untranslated regions of mRNAs that control their translation, degradation and localization include stem-loop structures, upstream initiation codons and open reading frames, internal ribosome entry sites and various cis-acting elements that are bound by RNA-binding proteins.

This paper reports an intraorder study on the D-loop-containing region of the mitochondrial DNA in rodents. A complete multialignment of this region is not feasible with the exception of some conserved regions. The comparative analysis of 25 complete rodent sequences from 23 species plus one lagomorph has revealed that only the central domain (CD), a conserved region of about 80 bp in the extended termination-associated sequences (ETAS) domain, adjacent to the CD, the ETAS1, and conserved sequence block (CSB) 1 blocks are present in all rodent species, whereas the presence of CSB2 and CSB3 is erratic within the order. We have also found a conserved region of 90 bp located between tRNAPro and ETAS1 present in fat dormouse, squirrel, guinea pig, and rabbit. Repeated sequences are present in both the ETAS and the CSB domain, but the repeats differ in length, copy number, and base composition in different species. The potential use of the D-loop for evolutionary studies has been investigated; the presence/absence of conserved blocks and/or repeated sequences cannot be used as a reliable phylogenetic marker, since in some cases they may be shared by distantly related organisms but not by close ones, while in other ones a relationship between tree topology and presence/absence of such motifs is observed. Better results can be obtained by the use of the CD, which, however, due to its reduced size, when used for tracing a phylogenetic tree, shows some nodes with low statistical support

De novo high-throughput pyrosequencing was used to detect and characterize 2009 pandemic influenza A (H1N1) virus directly in nasopharyngeal swabs in the context of the microbial community. Data were generated with a prior sequenceindependent amplification by 454 pyrosequencing on GS-FLX platform (Roche). Influenza A assembled reads allowed near full-length genome reconstruction with the simultaneous analysis of site-specific heterogeneity. The molecular approach applied proved to be a powerful tool to characterize the new pandemic H1N1 influenza virus in clinical samples. This approach could be of great value in identifying possibly new reassortants that may occur in the near future.

Background Despite their lethality and ensuing clinical and therapeutic relevance, circulating tumor cells (CTCs) from colorectal carcinoma (CRC) remain elusive, poorly characterized biological entities. Methods and findings We perfected a cell system of stable, primary lines from human CRC showing that they possess the full complement of ex- and in-vivo, in xenogeneic models, characteristics of CRC stem cells (CCSCs). Here we show how tumor-initiating, CCSCs cells can establish faithful orthotopic phenocopies of the original disease, which contain cells that spread into the circulatory system. While in the vascular bed, these cells retain stemness, thus qualifying as circulating CCSCs (cCCSCs). This is followed by the establishment of lesions in distant organs, which also contain resident metastatic CCSCs (mCCSCs). Interpretation Our results support the concept that throughout all the stages of CRC, stemness is retained as a continuous property by some of their tumor cells. Importantly, we describe a useful standardized model that can enable isolation and stable perpetuation of human CRC's CCSCs, cCCSCs and mCCSCs, providing a useful platform for studies of CRC initiation and progression that is suitable for the discovery of reliable stage-specific biomarkers and the refinement of new patient-tailored therapies. Fund This work was financially supported by grants from "Ministero della Salute Italiano"(GR-2011-02351534, RC1703IC36 and RC1803IC35) to Elena Binda and from "Associazione Italiana Cancro" (IG-14368) Angelo L. Vescovi. None of the above funders have any role in study design, data collection, data analysis, interpretation, writing the project.

Jellyfish represent an important component of marine food webs characterized by large fluctuations of population density, with the ability to abruptly form outbreaks, followed by rarity periods. In spite of considerable efforts to investigate how jellyfish populations are responding globally to anthropogenic change, available evidence still remains unclear. In the last 50 years, jellyfish arc seemingly on the rise in a number of coastal areas, including the Mediterranean Sea, where jellyfish blooms periodically become an issue to marine and maritime human activities. Their impacts on marine organism welfare have been poorly quantified. The jellyfish, Rhizostoma pulmo, is an outbreak-forming scyphomedusa whose large populations spread across the Mediterranean, with increasing periodicity and variable abundance. Studies on cnidarian jellyfish suggested being important vectors of bacterial pathogens. In the present study, by combination of conventional culture-based methods and a high-throughput amplicon sequencing (HTS) approach, we characterized the diversity of the bacterial community associated with this jellyfish during their summer outbreak. Three distinct jellyfish compartments, namely umbrella, oral arms, and the mucus secretion obtained from whole specimens were screened for specifically associated microbiota. A total of 17 phyla, 30 classes, 73 orders, 146 families and 329 genera of microbial organisms were represented in R. pulmo samples with three major lades (ie. Spiroplasma, Mycoplasma and Wolinella) representing over 90% of the retrieved total sequences. The taxonomic microbial inventory was then combined with metabolic profiling data obtained from the Biolog Eco-Plate system. Significant differences among the jellyfish compartments were detected in terms of bacterial abundance, diversity and metabolic utilization of 31 different carbon sources with the highest value of abundance and metabolic potential in the mucus secretion compared to the umbrella and oral arms. Results are discussed in the framework of the species ecology as well as the potential health hazard for marine organisms and humans. (C) 2019 Elsevier B.V. All rights reserved.

EphB2 and EphA2 control stemness and differentiation in the intestinal mucosa, but the way they cooperate with the complex mechanisms underlying tumor heterogeneity and how they affect the therapeutic outcome in colorectal cancer (CRC) patients, remain unclear. MicroRNA (miRNA) expression profiling along with pathway analysis provide comprehensive information on the dysregulation of multiple crucial pathways in CRC. Through a network-based approach founded on the characterization of progressive miRNAomes centered on EphA2/EphB2 signaling during tumor development in the AOM/DSS murine model, we found a miRNA-dependent orchestration of EphB2-specific stem-like properties in earlier phases of colorectal tumorigenesis and the EphA2-specific control of tumor progression in the latest CRC phases. Furthermore, two transcriptional signatures that are specifically dependent on the EphA2/EphB2 signaling pathways were identified, namely EphA2, miR-423-5p, CREB1, ADAMTS14, and EphB2, miR-31-5p, mir-31-3p, CRK, CXCL12, ARPC5, SRC. EphA2- and EphB2-related signatures were validated for their expression and clinical value in 1663 CRC patients. In multivariate analysis, both signatures were predictive of survival and tumor progression. The early dysregulation of miRs-31, as observed in the murine samples, was also confirmed on 49 human tissue samples including preneoplastic lesions and tumors. In light of these findings, miRs-31 emerged as novel potential drivers of CRC initiation. Our study evidenced a miRNA-dependent orchestration of EphB2 stem-related networks at the onset and EphA2-related cancer-progression networks in advanced stages of CRC evolution, suggesting new predictive biomarkers and potential therapeutic targets. Electronic supplementary material The online version of this article (10.1186/s12943-018-0912-z) contains supplementary material, which is available to authorized users.

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/.

Alternative Splicing (AS) is the molecular phenomenon whereby multiple transcripts are produced from the same gene locus. As a consequence, it is responsible for the expansion of eukaryotic transcriptomes. Aberrant AS is involved in the onset and progression of several human diseases. Therefore, the characterization of exon-intron structure of a gene and the detection of corresponding transcript isoforms is an extremely relevant biological task. Nonetheless, the computational prediction of AS events and the repertoire of alternative transcripts is yet a challenging issue. Hereafter we introduce PIntron, a software package to predict the exon-intron structure and the full-length isoforms of a gene given a genomic region and a set of transcripts (ESTs and/or mRNAs). The software is open source and available at http://pintron.algolab.eu. PIntron has been designed for (and extensively tested on) a standard workstation without requiring dedicated expensive hardware. It easily manages large genomic regions and more than 20,000 ESTs, achieving good accuracy as shown in an experimental evaluation performed on 112 well-annotated genes selected from the ENCODE human regions used as training set in the EGASP competition.

Understanding the complex mechanisms governing basic biological processes requires the characterisation of regulatory motifs modulating gene expression at transcriptional and post-transcriptional level. In particular, extent, chronology and cell-specificity of transcription are modulated by the interaction of transcription factors with their corresponding binding sites, mostly located near (or sometimes quite far away from) the transcription start site of the gene. The constantly growing amount of genomic data, complemented by other sources of information such as expression data derived from microarray experiments, has opened new opportunities to researchers in this field. Many different methods have been proposed for the identification of transcription factor binding sites in the regulatory regions of co-expressed genes: unfortunately this is a very challenging problem both from the computational and the biological viewpoint. This paper provides a survey of existing methods proposed for the problem, focusing both on the ideas underlying them and their availability to the scientific community.

The mRNA of Scamper, a putative intracellular calcium channel activated by sphingosylphosphocholine, contains a long 5' transcript leader with several upstream AUGs. In this work we have investigated the role this sequence plays in the translational control of Scamper expression. The cytosolic transcription machinery of a T7 RNA polymerase recombinant vaccinia virus was used to avoid artifacts arising from cryptic promoters or mRNA processing. Based on transient transfection experiments of dicistronic and bi-monocistronic plasmids expressing reporter genes, we present evidence that the 5' transcript leader of Scamper contains a functional internal ribosome entry site (IRES). Our data indicate that Scamper translation in Madin-Darby canine kidney cells is driven by a cap-independent mechanism supported by the IRES activity of its mRNA. Finally, the Scamper IRES appears to be the first IRES with specificity for kidney epithelial cells.

GeneSyn is a software tool that allows automatic detection of conserved gene order from annotated genomes. The increasing amount of available genome data makes it possible now to shed light on the molecular dynamics shaping their evolution. Genome evolution not only involves changes at the sequence level with base substitutions and/or insertion/deletion events but also rearrangements of the gene order along the genome. Comparative analysis of gene order in multiple genomes may help in investigating general or lineage-specific genome plasticity as well as in the inference of phylogenetic relationships. In particular, investigation of gene contiguity on a chromosome (sometimes improperly referred to as conserved gene synteny), even if sometimes interrupted by intervening genes, suggests a functional coupling. We present here an algorithm and software to detect gene strings conserved in at least a given fraction of input genomes and present a simple example application in animal mitochondrial gene order

Background A challenging issue in designing computational methods for predicting the gene structure into exons and introns from a cluster of transcript (EST, mRNA) sequences, is guaranteeing accuracy as well as efficiency in time and space, when large clusters of more than 20,000 ESTs and genes longer than 1 Mb are processed. Traditionally, the problem has been faced by combining different tools, not specifically designed for this task. Results We propose a fast method based on ad hoc procedures for solving the problem. Our method combines two ideas: a novel algorithm of proved small time complexity for computing spliced alignments of a transcript against a genome, and an efficient algorithm that exploits the inherent redundancy of information in a cluster of transcripts to select, among all possible factorizations of EST sequences, those allowing to infer splice site junctions that are largely confirmed by the input data. The EST alignment procedure is based on the construction of maximal embeddings, that are sequences obtained from paths of a graph structure, called embedding graph, whose vertices are the maximal pairings of a genomic sequence T and an EST P. The procedure runs in time linear in the length of P and T and in the size of the output. The method was implemented into the PIntron package. PIntron requires as input a genomic sequence or region and a set of EST and/or mRNA sequences. Besides the prediction of the full-length transcript isoforms potentially expressed by the gene, the PIntron package includes a module for the CDS annotation of the predicted transcripts. Conclusions PIntron, the software tool implementing our methodology, is available at http://www.algolab.eu/PIntron under GNU AGPL. PIntron has been shown to outperform state-of-the-art methods, and to quickly process some critical genes. At the same time, PIntron exhibits high accuracy (sensitivity and specificity) when benchmarked with ENCODE annotations.

Alternative splicing (AS) is currently considered as one of the main mechanisms able to explain the huge gap between the number of predicted genes and the high complexity of the proteome in humans. The rapid growth of Expressed Sequence Tag (EST) data has encouraged the development of computational methods to predict alternative splicing from the analysis of EST alignment to genome sequences. EST data are also a valuable source to reconstruct the different transcript isoforms that derive from the same gene structure as a consequence of AS, as indeed EST sequences are obtained by fragmenting mRNAs from the same gene. The most recent studies on alternative splice sites detection have revealed that this topic is a quite challenging computational problem, far from a solution. The main computational issues related to the problem of detecting alternative splicing are investigated in this paper, and we analyze algorithmic solutions for this problem. We first formalize an optimization problem related to the prediction of constitutive and alternative splicing sites from EST sequences, the Minimum Exons ESTs Factorization problem (in short, MEF), and show that it is Np-hard, even for restricted instances. This problem leads us to define sets of spliced EST, that is, a set of EST factorized into their constitutive exons with respect to a gene. Then we investigate the computational problem of predicting transcript isoforms from spliced EST sequences. We propose a graph algorithm for the problem that is linear in the number of predicted isoforms and size of the graph. Finally, an experimental analysis of the method is performed to assess the reliability of the predictions.

Glutamine synthetase (EC 6.3.1.2) gene evolution in various animals, plants, and bacteria was evaluated by a general stationary Markov model. The evolutionary process proved to be unexpectedly regular even for a time span as long as that between the divergence of prokaryotes from eukaryotes. This enabled us to draw phylogenetic trees for species whose phylogeny cannot be easily reconstructed from the fossil record. Our calculation of the times of divergence of the various organelle-specific enzymes led us to hypothesize that the pea and bean chloroplast genes for these enzymes originated from the duplication of nuclear genes as a result of the different metabolic needs of the various species. Our data indicate that the duplication of plastid glutamine synthetase genes occurred long after the endosymbiotic events that produced the organelles themselves.

Understanding the complex mechanisms regulating gene expression at the transcriptional and post-transcriptional levels is one of the greatest challenges of the post-genomic era. The MoD (MOtif Discovery) Tools web server comprises a set of tools for the discovery of novel conserved sequence and structure motifs in nucleotide sequences, motifs that in turn are good candidates for regulatory activity. The server includes the following programs: Weeder, for the discovery of conserved transcription factor binding sites (TFBSs) in nucleotide sequences from co-regulated genes; WeederH, for the discovery of conserved TFBSs and distal regulatory modules in sequences from homologous genes; RNAProfile, for the discovery of conserved secondary structure motifs in unaligned RNA sequences whose secondary structure is not known. In this way, a given gene can be compared with other co-regulated genes or with its homologs, or its mRNA can be analyzed for conserved motifs regulating its post-transcriptional fate. The web server thus provides researchers with different strategies and methods to investigate the regulation of gene expression, at both the transcriptional and post-transcriptional levels. Available at http://www.pesolelab.it/modtools/ and http://www.beacon.unimi. it/modtools/.

Background: Currently available methods to predict splice sites are mainly based on the independent and progressive alignment of transcript data (mostly ESTs) to the genomic sequence. Apart from often being computationally expensive, this approach is vulnerable to several problems – hence the need to develop novel strategies. Results: We propose a method, based on a novel multiple genome-EST alignment algorithm, for the detection of splice sites. To avoid limitations of splice sites prediction (mainly, over-predictions) due to independent single EST alignments to the genomic sequence our approach performs a multiple alignment of transcript data to the genomic sequence based on the combined analysis of all available data. We recast the problem of predicting constitutive and alternative splicing as an optimization problem, where the optimal multiple transcript alignment minimizes the number of exons and hence of splice site observations. We have implemented a splice site predictor based on this algorithm in the software tool ASPIC (Alternative Splicing PredICtion). It is distinguished from other methods based on BLAST-like tools by the incorporation of entirely new ad hoc procedures for accurate and computationally efficient transcript alignment and adopts dynamic programming for the refinement of intron boundaries. ASPIC also provides the minimal set of non-mergeable transcript isoforms compatible with the detected splicing events. The ASPIC web resource is dynamically interconnected with the Ensembl and Unigene databases and also implements an upload facility. Conclusion: Extensive bench marking shows that ASPIC outperforms other existing methods in the detection of novel splicing isoforms and in the minimization of over-predictions. ASPIC also requires a lower computation time for processing a single gene and an EST cluster. The ASPIC web resource is available at http://aspic.algo.disco.unimib.it/aspic-devel/.

One of the greatest challenges that modern molecular biology is facing is the understanding of the complex mechanisms regulating gene expression. A fundamental step in this process requires the characterization of regulatory motifs playing key roles in the regulation of gene expression at transcriptional and post-transcriptional levels. In particular, transcription is modulated by the interaction of transcription factors with their corresponding binding sites. Weeder Web is a web interface to Weeder, an algorithm for the automatic discovery of conserved motifs in a set of related regulatory DNA sequences. The motifs found are in turn likely to be instances of binding sites for some transcription factor. Other than providing access to the program, the interface has been designed so to make usage of the program itself as simple as possible, and to require very little prior knowledge about the length and the conservation of the motifs to be found. In fact, the interface automatically starts different runs of the program, each one with different parameters, and provides the user with an overall summary of the results as well as some 'advice' on which motifs look more interesting according to their statistical significance and some simple considerations. The web interface is available at the address www.pesolelab.it by following the 'Tools' link.

Upon cold shock Escherichia coli transiently stops growing and adapts to the new temperature (acclimatization phase). The major physiological effects of cold temperature are a decrease in membrane fluidity and the stabilization of secondary structures of RNA and DNA, which may affect the efficiencies of translation, transcription, and replication. Specific proteins are transiently induced in the acclimatization phase. mRNA stabilization and increased translatability play a major role in this phenomenon. Polynucleotide phosphorylase (PNPase) is one of the cold-induced proteins and is essential for E. coli growth at low temperatures. We investigated the global changes in mRNA abundance during cold adaptation both in wild type E. coli MG1655 and in a PNPase-deficient mutant. We observed a twofold or greater variation in the relative mRNA abundance of 20 genes upon cold shock, notably the cold-inducible subset of csp genes and genes not previously associated with cold shock response, among these, the extracytoplasmic stress response regulators rpoE and rseA, and eight genes with unknown function. Interestingly, we found that PNPase both negatively and positively modulated the transcript abundance of some of these genes, thus suggesting a complex role of PNPase in controlling cold adaptation.

CUG, a universal leucine codon, has been reported to be read as serine in various yeast species belonging to the genus Candida. To gain a deeper insight into the origin of this deviation from the universal genetic code, we carried out a phylogenetic analysis based on the small-subunit ribosomal RNA genes from some Candida and other related Hemiascomycetes. Furthermore, we determined the phylogenetic relationships between the tRNA(Ser)CAG, responsible for the translation of CUG, from some Candida species and the other serine and leucine isoacceptor tRNAs in C. cylindracea. We demonstrate that the group of Candida showing the genetic code deviation is monophyletic and that this deviation could have originated more than 150 million years ago. We also describe how phylogenetic analysis can be used for genetic code predictions.

Several experiments and observations have revealed the fact that small local distinct structural features in RNA molecules are correlated with their biological function, for example in post-transcriptional regulation of gene expression. Thus, finding similar structural features in a set of RNA sequences known to play the same biological function could provide substantial information concerning which parts of the sequences are responsible for the function itself. The main difficulty lies in the fact that in nearly all the cases the structure of the molecules is unknown, has to be somehow predicted, and that sequences with little or no similarity can fold into similar structures. The algorithm we present searches for regions of the sequences that, according to base pairing rules, can fold into similar structures, where the degree of similarity can be defined by the user. Any information concerning sequence similarity in the motifs can be used either as a search constraint, or a posteriori, by post- processing the output. The search for the regions sharing structural similarity is implemented with the affix tree, a novel text- indexing structure that significantly accelerates the search for patterns having a symmetric layout, like those forming RNA hairpins. Tests based on experimentally known structures have shown that the algorithm is able to identify functional motifs in the secondary structure of non coding RNA, such as Iron Responsive Elements (IRE) in the untranslated regions of ferritin mRNA, and the domain IV stem-loop structure in SRP RNA.

In this paper we propose a new approach to the problem of predicting constitutive and alternative splicing sites by defining it as an optimization problem (MEFC). Then, we develop an algorithm to detect splicing sites based on the idea of using a combined analysis of a set of ESTs alignments to a genomic sequence instead of considering single EST alignments. In this way we require that all ESTs alignments must agree, i.e. are compatible to a plausible exon-intron structure of the genomic sequence. Indeed, we show that a progressive and independent alignment of ESTs may produce unsupported splicing forms. Our method has been implemented and experimental results show that it predicts alternative splicings with high accuracy and in a small amount of time. More precisely, compared to published splicing data, the method confirms validated data while in many cases it provides novel splicing forms supported by several ESTs alignments.