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Despite the increasing use of mussels in environmental monitoring and ecotoxicological studies, their genomes and gene functions have not been thoroughly explored. Several cDNA microarrays were recently proposed for Mytilus spp., but putatively identified partial transcripts have rendered the generation of robust transcriptional responses difficult in terms of pathway identification. We developed a new low density oligonucleotide microarray with 465 probes covering the same number of genes. Target genes were selected to cover most of the well-known biological processes in the stress response documented over the last decade in bivalve species at the cellular and tissue levels. Our new 'STressREsponse Microarray' (STREM) platform consists of eight sub-arrays with three replicates for each target in each sub-array. To assess the potential use of the new array, we tested the effect of the ubiquitous environmental pollutant benzo[a]pyrene (B[a]P) at 5, 50, and 100 μg/L on two target tissues, the gills and digestive gland, of Mytilus galloprovincialis exposed invivo for three days. Bioaccumulation of B[a]P was also determined demonstrating exposure in both tissues. In addition to the well-known effects of B[a]P on DNA metabolism and oxidative stress, the new array data provided clues about the implication of other biological processes, such as cytoskeleton, immune response, adhesion to substrate, and mitochondrial activities. Transcriptional data were confirmed using qRT-PCR. We further investigated cellular functions and possible alterations related to biological processes highlighted by the microarray data using oxidative stress biomarkers (Lipofuscin content) and the assessment of genotoxicity. DNA damage, as measured by the alkaline comet assay, increased as a function of dose.DNA adducts measurements using 32P-postlabeling method also showed the presence of bulky DNA adducts (i.e. dG-N2-BPDE). Lipofiscin content increased significantly in B[a]P exposed mussels. Immunohistochemical analysis of tubulin and actin showed changes in cytoskeleton organisation. Our results adopting an integrated approach confirmed that the combination of newly developed transcriptomic approcah, classical biomarkers along with chemical analysis of water and tissue samples should be considered for environmental bioimonitoring and ecotoxicological studies to obtain holistic information to assess the impact of contaminants on the biota.

Preoperative chemoradiotherapy (pCRT) followed by surgery is the standard treatment for locally advanced rectal cancer (LARC). However, tumor response to pCRT is not uniform, and there are no effective predictive methods. This study investigated whether specific gene and miRNA expression are associated with tumor response to pCRT. Tissue biopsies were obtained from patients before pCRT and resection. Gene and miRNA expression were analyzed using a one-color microarray technique that compares signatures between responders (R) and non-responders (NR), as measured based on tumor regression grade. Two groups composed of 38 "exploration cohort" and 21 "validation cohort" LARC patients were considered for a total of 32 NR and 27 R patients. In the first cohort, using SAM Two Class analysis, 256 genes and 29 miRNAs that were differentially expressed between the NR and R patients were identified. The anti-correlation analysis showed that the same 8 miRNA interacted with different networks of transcripts. The miR-630 appeared only with the NR patients and was anti-correlated with a single transcript: RAB5B. After PAM, the following eight transcripts were strong predictors of tumor response: TMEM188, ITGA2, NRG, TRAM1, BCL2L13, MYO1B, KLF7, and GTSE1. Using this gene set, an unsupervised cluster analysis was applied to the validation cohort and correctly assigned the patients to the NR or R group with 85.7% accuracy, 90% sensitivity, and 82% specificity. All three parameters reached 100% when both cohorts were considered together. In conclusion, gene and miRNA expression profiles may be helpful for predicting response to pCRT in LARC patients. J. Cell. Physiol. 232: 426-435, 2017. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

The large dimension of microarray data and the complex dependence structure among genes make data analysis extremely challenging. In the last decade several statistical techniques have been proposed to tackle genome-wide expression data; however, clinical and molecular data associated to pathologies have often been considered as separate dimensions of the same phenomenon, especially when clinical variables lie on a multidimensional space. A better comprehension of the relationships between clinical and molecular data can be obtained if both data types are combined and integrated. In this work we adopt a multidimensional correlation strategy together with linear and nonlinear principal component, to integrate genetic and clinical information obtained from two sets of dystrophic patients. With this approach we decompose different aspects of clinical manifestations and correlate these features with the correspondent patterns of differential gene expression.

Ankrd2 is a member of the Muscle Ankyrin Repeat Protein family (MARPs), consisting of sarcomere-associated proteins that can also localize in the nucleus. There are indications that MARPs might function as shuttle proteins between the cytoplasm and nucleus, likely sending information to the nucleus concerning the changes in the structure or function of the contractile machinery. Even though recent findings suggest that the MARP gene family is not essential for the basal functioning of skeletal muscle, its influence on the gene expression program of skeletal muscle cells was highlighted. To investigate this regulatory role we produced and examined both morphological and functional features of myocytes stable overexpressing or silencing the Ankrd2 protein. The transcriptional profiles of the myocytes revealed that the molecular pathways perturbed by changes in Ankrd2 protein level are congruent with the morpho-physiological and biochemical data obtained in Ankrd2-modified myoblasts induced to differentiate. Our results suggest that Ankrd2 gives an important contribution to the coordination of proliferation and apoptosis during myogenic differentiation in vitro, mainly through the p53 network.

Gene expression profiling by microarray technologies has been successfully applied to study the transcriptional changes that occur in tissues such as heart, vessels and blood cells in different cardiovascular disorders. Such studies have been performed in human cardiovascular syndromes and in animal models with the aim of unraveling the complex molecular pictures underlying human pathophysiology. As already observed in cancer research, gene expression studies in humans may provide a finer molecular classification of patients with cardiovascular diseases and indicate new markers useful for prognostic and therapeutic strategies. In this paper, we present the findings obtained with microarray platforms to explore transcriptome alterations in cardiovascular diseases. To describe the potential of global expression profiling approach in this field, we have chosen to review the genomic findings obtained in some classic heart diseases with genetic transmission such as hyperthrophic cardiomyopathy and Fabry disease, together with findings obtained in common multifactorial cardiovascular disorders such as heart failure, atherosclerosis and infarction. Wherever feasible, we present the results obtained in patients together with those obtained in the corresponding animal and cellular models.

Marine bivalves of the genus Mytilus are intertidal filter-feeders commonly used as biosensors of coastal pollution. Mussels adjust their functions to ordinary environmental changes, e.g. temperature fluctuations and emersion-related hypoxia, and react to various contaminants, accumulated from the surrounding water and defining a potential health risk for sea-food consumers. Despite the increasing use of mussels in environmental monitoring, their genome and gene functions are largely unexplored. Hence, we started the systematic identification of expressed sequence tags and prepared a cDNA microarray of Mytilus galloprovincialis including 1714 mussel probes (76% singletons, approximately 50% putatively identified transcripts) plus unrelated controls. To assess the potential use of the gene set represented in MytArray 1.0, we tested different tissues and groups of mussels. The resulting data highlighted the transcriptional specificity of the mussel tissues. Further testing of the most responsive digestive gland allowed correct classification of mussels treated with mixtures of heavy metals or organic contaminants (expression changes of specific genes discriminated the two pollutant cocktails). Similar analyses made a distinction possible between mussels living in the Venice lagoon (Italy) at the petrochemical district and mussels close to the open sea. The suggestive presence of gene markers tracing organic contaminants more than heavy metals in mussels from the industrial district is consistent with reported trends of chemical contamination. Further study is necessary in order to understand how much gene expression profiles can disclose the signatures of pollutants in mussel cells and tissues. Nevertheless, the gene expression patterns described in this paper support a wider characterization of the mussel transcriptome and point to the development of novel environmental metrics.

In the Caucasian population, patients affected by the most frequent forms of congenital muscular dystrophies (MDC) are commonly divided into two groups. The first is characterized by mutations of the gene for the laminin alpha-2 (LAMA2). The second is positive for this protein, highly heterogeneous, and has no specific genetic defect associated yet. We studied the skeletal muscle transcriptome of four LAMA2 deficient and six LAMA2 positive MDC patients by cDNA microarrays. The expression profiling defined two patients groups: one mild and one severe phenotype. This result was in agreement with histopathological features but only partially with the clinical classification. The mild phenotype is characterized by a delayed maturation from slow to fast muscle fibers. Other muscle transcripts, such as telethonin, myosin light-chains 3 and 1V, are underexpressed in this group. We suggest that expression profiling will provide important information to improve our understanding of the molecular basis of laminin alpha-2 positive MDC.

We analyzed the expression signatures of 14 tumor biopsies from children affected by alveolar rhabdomyosarcoma (ARMS) to identify genes correlating to biological features of this tumor. Seven of these patients were positive for the PAX3-FKHR fusion gene and 7 were negative. We used a cDNA platform containing a large majority of probes derived from muscle tissues. The comparison of transcription profiles of tumor samples with fetal skeletal muscle identified 171 differentially expressed genes common to all ARMS patients. The functional classification analysis of altered genes led to the identification of a group of transcripts (LGALS1, BIN1) that may be relevant for the tumorigenic processes. The muscle-specific microarray platform was able to distinguish PAX3-FKHR positive and negative ARMS through the expression pattern of a limited number of genes (RAC1, CFL1, CCND1, IGFBP2) that might be biologically relevant for the different clinical behavior and aggressiveness of the 2 ARMS subtypes. Expression levels for selected candidate genes were validated by quantitative real-time reverse-transcription PCR.

MIDAW (microarray data analysis web tool) is a web interface integrating a series of statistical algorithms that can be used for processing and interpretation of microarray data. MIDAW consists of two main sections: data normalization and data analysis. In the normalization phase the simultaneous processing of several experiments with background correction, global and local mean and variance normalization are carried out. The data analysis section allows graphical display of expression data for descriptive purposes, estimation of missing values, reduction of data dimension, discriminant analysis and identification of marker genes. The statistical results are organized in dynamic web pages and tables, where the transcript/gene probes contained in a specific microarray platform can be linked (according to user choice) to external databases (GenBank, Entrez Gene, UniGene). Tutorial files help the user throughout the statistical analysis to ensure that the forms are filled out correctly. MIDAW has been developed using Perl and PHP and it uses R/Bioconductor languages and routines. MIDAW is GPL licensed and freely accessible at http://muscle.cribi.unipd.it/midaw/. Perl and PHP source codes are available from the authors upon request.

Background and Objectives: Microarray gene expression profiling has been widely applied to characterize hematologic malignancies, has attributed a molecular signature to leukemia subclasses and has allowed new subclasses to be distinguished. We set out to use microarray technology to identify novel genes relevant for leukemogenesis. To this end we used a unique leukemia-enriched cDNA microarray platform., Design and Methods: The systematic sequencing of cDNA libraries of normal and leukemic bone marrow allowed us to increase the number of genes to yield a new release of a previously generated cDNA microarray. Using this platform we analyzed the expression profiles of 4,670 genes in bone marrow samples from 18 pediatric patients with acute lymphoblastic leukemia (ALL)., Results: Expression profiling consistently distinguished the leukemia patients into three groups, those with T-ALL, B-ALL and B-ALL with MLL/AF4 rearrangement, in agreement with the clinical classification. Our platform identified 30 genes that best discriminate these three subtypes. Using mini-array technology these 30 genes were validated in another cohort of 17 patients. In particular we identified two novel genes not previously reported: endomucin (EMCN) and ubiquitin specific protease 33 (USP33) that appear to be over-expressed in B-ALL relative to their expression in T-ALL., Interpretation and Conclusions: Microarray technology not only allows the distinction between disease subclasses but also offers a chance to identify new genes involved in leukemogenesis. Our approach of using a unique platform has proven to be fruitful in identifying new genes and we suggest exploration of other malignancies using this approach.

Skeletal muscle development requires the coordinated expression of numerous transcription factors to control the specification of the muscle fate in mesodermal cells and the differentiation of the committed myoblasts into functional contractile fibers. The bHLH transcription factor MyoD plays a key role in these processes, since its forced expression is sufficient to induce the myogenesis in a variety of non-muscle cells in culture. Consistent with this observation, the majority of skeletal muscle genes require MyoD to activate their own transcription. In order to identify novel MyoD-target genes we generated C2C12 MyoD-silenced clones, and used a muscle-specific cDNA microarray to study the induced modifications of the transcriptional profile. Gene expression was analyzed at three different stages in differentiating MyoD(-)C2C12 myoblasts. These microarray data sets identified many additional uncharacterized downstream MyoD transcripts that may play important functions in muscle cell differentiation. Among these genes, we concentrated our study on the cell cycle regulators Cdkn1c and calcyclin and on the muscle-specific putative myogenic regulator Ankrd2. Bioinformatic and functional studies on the promoters of these genes clarified their dependence on MyoD activity. Clues of other regulatory mechanisms that might interact with the principal bHLH transcription factor have been revealed by the unexpected up-regulation in MyoD(-) cells of these novel (and other) target transcripts, at the differentiation stage in which MyoD became normally down-regulated.

The variability of results in microarray technology is in part due to the fact that independent scans of a single hybridised microarray give spot images that are not quite the same. To solve this problem and turn it to our advantage, we introduced the approach of multiple scanning and of image integration of microarrays. To this end, we have developed specific software that creates a virtual image that statistically summarises a series of consecutive scans of a microarray. We provide evidence that the use of multiple imaging (i) enhances the detection of differentially expressed genes; (ii) increases the image homogeneity; and (iii) reveals false-positive results such as differentially expressed genes that are detected by a single scan but not confirmed by successive scanning replicates. The increase in the final number of differentially expressed genes detected in a microarray experiment with this approach is remarkable; 50% more for microarrays hybridised with targets labelled by reverse transcriptase, and 200% more for microarrays developed with the tyramide signal amplification (TSA) technique. The results have been confirmed by semi-quantitative RT-PCR tests.

About 10% of cases of hypertrophic cardiomyopathy (HCM) evolve into dilated cardiomyopathy (DCM) with unknown causes. We studied 11 unrelated patients (pts) with HCM who progressed to DCM (group A) and 11 who showed "typical" HCM (group B). Mutational analysis of the beta-myosin heavy chain (MYH7), myosin-binding protein C (MYBPC3), and cardiac troponin T (TNNT2) genes demonstrated eight mutations affecting MYH7 or MYBPC3 gene, five of which were new mutations. In group A-pts, the first new mutation occurred in the myosin head-rod junction and the second occurred in the light chain-binding site. The third new mutation leads to a MYBPC3 lacking titin and myosin binding sites. In group B, two pts with severe HCM carried two homozygous MYBPC3 mutations and one with moderate hypertrophy was a compound heterozygous for MYBPC3 gene. We identified five unreported mutations, potentially "malignant" defects as for the associated phenotypes, but no specific mutations of HCM/DCM.

Large-scale parallel measurements of the expression of many thousands genes are now available with high-density array made with collections of cDNA fragments, or oligonucleotide corresponding to different transcripts. These technologies have been applied to cancer investigations since the availability of such a large number of markers makes DNA array a powerful diagnostic tool for tumour and patient classification. Over the last two years, a series of computational tools have been developed for the analysis of different aspects of gene profiling. Our work tries to compare a series of supervised statistical techniques on the basis of their ability to correctly classify different types of tumours. A simulation approach was initially used to control the huge source of variation among and between patients, and to evaluate the ability of algorithms to classify tumours in relation to different types of experimental variables. Different techniques for reduction of data dimension were then added to the discriminant analysis and compared according to their ability to capture the main genetic information. The simulation results have been tested by applying the selected classification algorithms to two experimental microarray datasets of human cancers, and by measuring the correspondent rates of misclassification. Our analyses identify in these datasets a series of genes principally involved in tumour characterization. The functional role of these discriminant transcripts is discussed.

TRAIT is a knowledgebase integrating information on transcripts with related data from genome, proteins, ortholog genes and diseases. It was initially built as a system to manage an EST-based gene discovery project on human skeletal muscle, which yielded over 4500 independent sequence clusters. Transcripts are annotated using automatic as well as manual procedures, linking known transcripts to public databases and unknown transcripts to tables of predicted features. Data are stored in a MySQL database. Complex queries are automatically built by means of a user-friendly web interface that allows the concurrent selection of many fields such as ontology, expression level, map position and protein domains. The results are parsed by the system and returned in a ranked order, in respect to the number of satisfied criteria.

We have characterized a novel unconventional myosin heavy chain, named MYO18B, that appears to be expressed mainly in human cardiac and skeletal muscles and, at lower levels, in testis. MYO18B transcript is detected in all types of striated muscles but at much lower levels compared to class II sarcomeric myosins, and it is up regulated after in vitro differentiation of myoblasts into myotubes. Phylogenetic analysis shows that this myosin belongs to the recently identified class XVIII, however, unlike the other member of this class, it seems to be unique to Vertebrate since it contains two large amino acid domains of unknown function at the N and C-termini. Immunolocalization of MYO18B protein in skeletal muscle cells shows that this myosin heavy chain is located in the cytoplasm of undifferentiated myoblasts. After in vitro differentiation into myotubes, a fraction of this protein is accumulated in a subset of myonuclei. This nuclear localization was confirmed by immunofluorescence experiments on primary cardiomyocytes and adult muscle sections. In the cytoplasm MYO18B shows a punctate staining, both in cardiac and skeletal fibers. In some cases, cardiomyocytes show a partial sarcomeric pattern of MYO18B alternating that of alpha-actinin-2. In skeletal muscle the cytoplasmic MYO18B results much more evident in the fast type fibers.

We have performed expression profiling to define the molecular changes in dysferlinopathy using a novel dedicated microarray platform made with 3'-end skeletal muscle cDNAs. Eight dysferlinopathy patients, defined by western blot, immunohistochemistry and mutation analysis, were investigated with this technology. In a first experiment RNAs from different limb-girdle muscular dystrophy type 2B patients were pooled and compared with normal muscle RNA to characterize the general transcription pattern of this muscular disorder. Then the expression profiles of patients with different clinical traits were independently obtained and hierarchical clustering was applied to discover patient-specific gene variations. MHC class I genes and genes involved in protein biosynthesis were up-regulated in relation to muscle histopathological features. Conversely, the expression of genes codifying the sarcomeric proteins titin, nebulin and telethonin was down-regulated. Neither calpain-3 nor caveolin, a sarcolemmal protein interacting with dysferlin, was consistently reduced. There was a major up-regulation of proteins interacting with calcium, namely S100 calcium-binding proteins and sarcolipin, a sarcoplasmic calcium regulator.

We have developed a new strategy for producing subtracted cDNA libraries that is optimized for connective and epithelial tissues, where a few exceptionally abundant (super-prevalent) RNA species account for a large fraction of the total mRNA mass. Our method consists of a two-step subtraction of the most abundant mRNAs: the first step involves a novel use of oligo-directed RNase H digestion to lower the concentration of tissue-specific, super-prevalent RNAs. In the second step, a highly specific subtraction is achieved through hybridization with probes from a 3'-end ESTs collection. By applying this technique in skeletal muscle, we have constructed subtracted cDNA libraries that are effectively enriched for genes expressed at low levels. We further report on frequent premature termination of transcription in human muscle mitochondria and discuss the importance of this phenomenon in designing subtractive approaches. The tissue-specific collections of cDNA clones generated by our method are particularly well suited for expression profiling.