Comparative Genome Viewer

The amount of information about genomes, both in the form of complete sequences and annotations, has been exponentially increasing in the last few years. As a result there is the need for tools providing a graphical representation of such information that should be comprehensive and intuitive. Visual representation is especially important in the comparative genomics field since it should provide a combined view of data belonging to different genomes. We believe that existing tools are limited in this respect as they focus on a single genome at a time (conservation histograms) or compress alignment representation to a single dimension. We have therefore developed a web-based tool called Comparative Genome Viewer (CGV): it integrates a bidimensional representation of alignments between two regions, both at small and big scales, with the richness of annotations present in other genome browsers. We give access to our system through a web-based interface that provides the user with an interactive representation that can be updated in real time using the mouse to move from region to region and to zoom in on intereseting details

The Trithorax protein Ash1L promotes myoblast fusion by activating Cdon expression

Myoblast fusion (MF) is required for muscle growth and repair, and its alteration contributes to muscle diseases. The mechanisms governing this process are incompletely understood, and no epigenetic regulator has been previously described. Ash1L is an epigenetic activator belonging to the Trithorax group of proteins and is involved in FSHD muscular dystrophy, autism and cancer. Its physiological role in skeletal muscle is unknown. Here we report that Ash1L expression is positively correlated with MF and reduced in Duchenne muscular dystrophy. In vivo, ex vivo\ua0and in vitro experiments support a selective and evolutionary conserved requirement for Ash1L in MF. RNA- and ChIP-sequencing indicate that Ash1L is required to counteract Polycomb repressive activity to allow activation of selected myogenesis genes, in particular the key MF gene Cdon. Our results promote Ash1L as\ua0an important epigenetic regulator of MF and suggest that its activity could be targeted to improve cell therapy for muscle diseases

Dihydroorotate dehydrogenase inhibition reveals metabolic vulnerability in chronic myeloid leukemia

The development of different generations of BCR-ABL1 tyrosine kinase inhibitors (TKIs) has led to the high overall survival of chronic myeloid leukemia (CML) patients. However, there are CML patients who show resistance to TKI therapy and are prone to progress to more advanced phases of the disease. So, implementing an alternative approach for targeting TKIs insensitive cells would be of the essence. Dihydroorotate dehydrogenase (DHODH) is an enzyme in the de novo pyrimidine biosynthesis pathway that is located in the inner membrane of mitochondria. Here, we found that CML cells are vulnerable to DHODH inhibition mediated by Meds433, a new and potent DHODH inhibitor recently developed by our group. Meds433 significantly activates the apoptotic pathway and leads to the reduction of amino acids and induction of huge metabolic stress in CML CD34+ cells. Altogether, our study shows that DHODH inhibition is a promising approach for targeting CML stem/progenitor cells and may help more patients discontinue the therapy

Graph theory analysis of genomic problems: community analysis of fragile sites correlations and of pseudogenes alignments

Graph theory offers the ideal framework to model biological systemic properties. Recently these methods were successfully applied in proteomics and in the study of metabolic networks. In this paper we want to show that these same tools are equally powerful also to address genomic problems, like alignment networks or the networks obtained by looking at suitable correlators of chromosomic features. We shall in particular address two examples. In the first example we shall study human common fragile sites (CFS), a class of “hyper-sensitive” segments of DNA. The interest in CFS is motivated by their largely debated role in cancerogenesis. In order to functionally characterize them we developed a novel genome-wide approach based on graph theory and Gene Ontology vocabulary. We obtain a few non-trivial results fitting with largely accepted knowledge and a more recently advanced proposal about the role of CFS in tumor cell biology. The second application is a preliminary work on a potential new type of transcriptional regulatory mechanism. It involves pseudogenes which are non-functional copies of genes. This mechanism should imply similarity between the upstream sequences of genes and pseudogenes. We constructed the upstream similarity network in the budding yeast S. Cerevisiae. Network properties suggest that pseudogenes-mediated regulation could be a common feature in eukaryotic organisms

Machine learning for RNA sequencing-based intrinsic subtyping of breast cancer

Stratification of breast cancer (BC) into molecular subtypes by multigene expression assays is of demonstrated clinical utility. In principle, global RNA-sequencing (RNA-seq) should enable reconstructing existing transcriptional classifications of BC samples. Yet, it is not clear whether adaptation to RNA-seq of classifiers originally developed using PCR or microarrays, or reconstruction through machine learning (ML) is preferable. Hence, we focused on robustness and portability of PAM50, a nearest-centroid classifier developed on microarray data to identify five BC “intrinsic subtypes”. We found that standard PAM50 is profoundly affected by the composition of the sample cohort used for reference construction, and we propose a strategy, named AWCA, to mitigate this issue, improving classification robustness, with over 90% of concordance, and prognostic ability; we also show that AWCA-based PAM50 can even be applied as single-sample method. Furthermore, we explored five supervised learners to build robust, single-sample intrinsic subtype callers via RNA-seq. From our ML-based survey, regularized multiclass logistic regression (mLR) displayed the best performance, further increased by ad-hoc gene selection on the global transcriptome. On external test sets, mLR classifications reached 90% concordance with PAM50-based calls, without need of reference sample; mLR proven robustness and prognostic ability make it an equally valuable single-sample method to strengthen BC subtyping

The RacGAP ArhGAP15 is a master negative regulator of neutrophil functions

In phagocytes, GTPases of the Rac family control crucial antimicrobial functions. The RacGAP ArhGAP15 negatively modulates Rac activity in leukocytes, but its in vivo role in innate immunity remains largely unknown. Here we show that neutrophils and macrophages derived from mice lacking ArhGAP15 presented higher Rac activity but distinct phenotypes. In macrophages, the loss of ArhGAP15 induced increased cellular elongation and membrane protrusions but did not modify chemotactic responses. Conversely, the lack of ArhGAP15 in neutrophils affected critical Rac-dependent antimicrobial functions, specifically causing enhanced chemotactic responses, straighter directional migration, amplified reactive oxygen species production, increased phagocytosis, and improved bacterial killing. In vivo, in a model of severe abdominal sepsis, these effects contributed to increase neutrophil recruitment to the site of infection, thereby limiting bacterial growth, controlling infection spread, reducing systemic inflammation, and ultimately improving survival in ArhGAP15-null mice. Altogether, these results demonstrate the relevance of ArhGAP15 in the selective regulation of multiple neutrophil functions, suggesting that ArhGAP15 targeting might be beneficial in specific pathologic settings like severe sepsis