Multiscale modeling uncovers 7q11.23 copy number variation-dependent changes in ribosomal biogenesis and neuronal maturation and excitability.

Copy number variation (CNV) at 7q11.23 causes Williams-Beuren syndrome (WBS) and 7q microduplication syndrome (7Dup), neurodevelopmental disorders (NDDs) featuring intellectual disability accompanied by symmetrically opposite neurocognitive features. Although significant progress has been made in understanding the molecular mechanisms underlying 7q11.23-related pathophysiology, the propagation of CNV dosage across gene expression layers and their interplay remains elusive. Here we uncovered 7q11.23 dosage-dependent symmetrically opposite dynamics in neuronal differentiation and intrinsic excitability. By integrating transcriptomics, translatomics, and proteomics of patient-derived and isogenic induced neurons, we found that genes related to neuronal transmission follow 7q11.23 dosage and are transcriptionally controlled, while translational factors and ribosomal genes are posttranscriptionally buffered. Consistently, we found phosphorylated RPS6 (p-RPS6) downregulated in WBS and upregulated in 7Dup. Surprisingly, p-4EBP was changed in the opposite direction, reflecting dosage-specific changes in total 4EBP levels. This highlights different dosage-sensitive dyregulations of the mTOR pathway as well as distinct roles of p-RPS6 and p-4EBP during neurogenesis. Our work demonstrates the importance of multiscale disease modeling across molecular and functional layers, uncovers the pathophysiological relevance of ribosomal biogenesis in a paradigmatic pair of NDDs, and uncouples the roles of p-RPS6 and p-4EBP as mechanistically actionable relays in NDDs.

Curation of causal interactions mediated by genes associated with autism accelerates the understanding of gene-phenotype relationships underlying neurodevelopmental disorders.

Autism spectrum disorder (ASD) comprises a large group of neurodevelopmental conditions featuring, over a wide range of severity and combinations, a core set of manifestations (restricted sociality, stereotyped behavior and language impairment) alongside various comorbidities. Common and rare variants in several hundreds of genes and regulatory regions have been implicated in the molecular pathogenesis of ASD along a range of causation evidence strength. Despite significant progress in elucidating the impact of few paradigmatic individual loci, such sheer complexity in the genetic architecture underlying ASD as a whole has hampered the identification of convergent actionable hubs hypothesized to relay between the vastness of risk alleles and the core phenotypes. In turn this has limited the development of strategies that can revert or ameliorate this condition, calling for a systems-level approach to probe the cross-talk of cooperating genes in terms of causal interaction networks in order to make convergences experimentally tractable and reveal their clinical actionability. As a first step in this direction, we have captured from the scientific literature information on the causal links between the genes whose variants have been associated with ASD and the whole human proteome. This information has been annotated in a computer readable format in the SIGNOR database and is made freely available in the resource website. To link this information to cell functions and phenotypes, we have developed graph algorithms that estimate the functional distance of any protein in the SIGNOR causal interactome to phenotypes and pathways. The main novelty of our approach resides in the possibility to explore the mechanistic links connecting the suggested gene-phenotype relations.

Pyntacle: a parallel computing-enabled framework for large-scale network biology analysis.

BACKGROUND: Some natural systems are big in size, complex, and often characterized by convoluted mechanisms of interaction, such as epistasis, pleiotropy, and trophism, which cannot be immediately ascribed to individual natural events or biological entities but that are often derived from group effects. However, the determination of important groups of entities, such as genes or proteins, in complex systems is considered a computationally hard task. RESULTS: We present Pyntacle, a high-performance framework designed to exploit parallel computing and graph theory to efficiently identify critical groups in big networks and in scenarios that cannot be tackled with traditional network analysis approaches. CONCLUSIONS: We showcase potential applications of Pyntacle with transcriptomics and structural biology data, thereby highlighting the outstanding improvement in terms of computational resources over existing tools.

A Multi-Layered Study on Harmonic Oscillations in Mammalian Genomics and Proteomics.

Cellular, organ, and whole animal physiology show temporal variation predominantly featuring 24-h (circadian) periodicity. Time-course mRNA gene expression profiling in mouse liver showed two subsets of genes oscillating at the second (12-h) and third (8-h) harmonic of the prime (24-h) frequency. The aim of our study was to identify specific genomic, proteomic, and functional properties of ultradian and circadian subsets. We found hallmarks of the three oscillating gene subsets, including different (i) functional annotation, (ii) proteomic and electrochemical features, and (iii) transcription factor binding motifs in upstream regions of 8-h and 12-h oscillating genes that seemingly allow the link of the ultradian gene sets to a known circadian network. Our multifaceted bioinformatics analysis of circadian and ultradian genes suggests that the different rhythmicity of gene expression impacts physiological outcomes and may be related to transcriptional, translational and post-translational dynamics, as well as to phylogenetic and evolutionary components.

Are Gaming-Enabled Graphic Processing Unit Cards Convenient for Molecular Dynamics Simulation?

In several fields of research, molecular dynamics simulation techniques are exploited to evaluate the temporal motion of particles constituting water, ions, small molecules, macromolecules, or more complex systems over time. These techniques are considered difficult to setup, computationally demanding and require high specialization and scientific skills. Moreover, they need specialized computing infrastructures to run faster and make the simulation of big systems feasible. Here, we have simulated 3 systems of increasing sizes on scientific- and gaming-enabled graphic processing unit (GPU) cards with Amber, GROMACS, and NAMD and measured their performance accounting also for the market prices of the GPU cards where they were run on.

Systematic Analysis of Mouse Genome Reveals Distinct Evolutionary and Functional Properties Among Circadian and Ultradian Genes.

In living organisms, biological clocks regulate 24 h (circadian) molecular, physiological, and behavioral rhythms to maintain homeostasis and synchrony with predictable environmental changes, in particular with those induced by Earth's rotation on its axis. Harmonics of these circadian rhythms having periods of 8 and 12 h (ultradian) have been documented in several species. In mouse liver, harmonics of the 24-h period of gene transcription hallmarked genes oscillating with a frequency two or three times faster than circadian periodicity. Many of these harmonic transcripts enriched pathways regulating responses to environmental stress and coinciding preferentially with subjective dawn and dusk. At this time, the evolutionary history of genes with rhythmic expression is still poorly known and the role of length-of-day changes due to Earth's rotation speed decrease over the last four billion years is totally ignored. We hypothesized that ultradian and stress anticipatory genes would be more evolutionarily conserved than circadian genes and background non-oscillating genes. To investigate this issue, we performed broad computational analyses of genes/proteins oscillating at different frequency ranges across several species and showed that ultradian genes/proteins, especially those oscillating with a 12-h periodicity, are more likely to be of ancient origin and essential in mice. In summary, our results show that genes with ultradian transcriptional patterns are more likely to be phylogenetically conserved and associated with the primeval and inevitable dawn/dusk transitions.

Molecular dynamics recipes for genome research.

Molecular dynamics (MD) simulation allows one to predict the time evolution of a system of interacting particles. It is widely used in physics, chemistry and biology to address specific questions about the structural properties and dynamical mechanisms of model systems. MD earned a great success in genome research, as it proved to be beneficial in sorting pathogenic from neutral genomic mutations. Considering their computational requirements, simulations are commonly performed on HPC computing devices, which are generally expensive and hard to administer. However, variables like the software tool used for modeling and simulation or the size of the molecule under investigation might make one hardware type or configuration more advantageous than another or even make the commodity hardware definitely suitable for MD studies. This work aims to shed lights on this aspect.

Insights From Molecular Characterization of Adult Patients of Families With Multigenerational Diabetes.

Multigenerational diabetes of adulthood is a mostly overlooked entity, simplistically lumped into the large pool of type 2 diabetes. The general aim of our research in the past few years is to unravel the genetic causes of this form of diabetes. Identifying among families with multigenerational diabetes those who carry mutations in known monogenic diabetes genes is the first step to then allow us to concentrate on remaining pedigrees in which to unravel new diabetes genes. Targeted next-generation sequencing of 27 monogenic diabetes genes was carried out in 55 family probands and identified mutations verified among their relatives by Sanger sequencing. Nine variants (in eight probands) survived our filtering/prioritization strategy. After likelihood of causality assessment by established guidelines, six variants were classified as "pathogenetic/likely pathogenetic" and two as "of uncertain significance." Combining present results with our previous data on the six genes causing the most common forms of maturity-onset diabetes of the young allows us to infer that 23.6% of families with multigenerational diabetes of adulthood carry mutations in known monogenic diabetes genes. Our findings indicate that the genetic background of hyperglycemia is unrecognized in the vast majority of families with multigenerational diabetes of adulthood. These families now become the object of further research aimed at unraveling new diabetes genes.

A primary tumor gene expression signature identifies a crucial role played by tumor stroma myofibroblasts in lymph node involvement in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common oral and pharyngeal cancer, and is responsible of approximately 3% of cancers in men and 2% in women in the Western World, with increasing incidence rates in developing countries. Early detection by screening is necessary to prevent fatal disease because early, curable lesions are rarely symptomatic. The overall 5-yr survival rate is approximately 50% when surgery, radiation, or both are employed as treatment options, but lymph node involvement greatly influences this estimate, by decreasing the survival rate by about 50%. Here, we aimed at finding genetic signatures associated with lymph node metastasis in OSCC patients. We addressed this issue by whole transcriptome analysis through microarray expression profiling of a set of OSSC specimens of patients without lymph node involvement (10 patients, mean age ± SD 61.2±13.8, male 7, female 3) and with lymph node involvement (11 patients, mean age ± SD 62.1±15.1, male 8, female 3). We evidenced a gene expression signature associated to muscle contraction-related genes in specimens obtained from OSCC patients with lymph node involvement. This gene signature suggests the presence of myofibroblasts in tumor stoma of patients with lymph node involvement and emphasizes the decisive role played by myofibroblasts probably through their secretome in determining OSCC invasiveness.

MicroRNA co-expression networks exhibit increased complexity in pancreatic ductal compared to Vater's papilla adenocarcinoma.

MiRNA expression abnormalities in adenocarcinoma arising from pancreatic ductal system (PDAC) and Vater's papilla (PVAC) could be associated with distinctive pathologic features and clinical cancer behaviours. Our previous miRNA expression profiling data on PDAC (n=9) and PVAC (n=4) were revaluated to define differences/similarities in miRNA expression patterns. Afterwards, in order to uncover target genes and core signalling pathways regulated by specific miRNAs in these two tumour entities, miRNA interaction networks were wired for each tumour entity, and experimentally validated target genes underwent pathways enrichment analysis. One hundred and one miRNAs were altered, mainly over-expressed, in PDAC samples. Twenty-six miRNAs were deregulated in PVAC samples, where more miRNAs were down-expressed in tumours compared to normal tissues. Four miRNAs were significantly altered in both subgroups of patients, while 27 miRNAs were differentially expressed between PDAC and PVAC. Although miRNA interaction networks were more complex and dense in PDAC than in PVAC, pathways enrichment analysis uncovered a functional overlapping between PDAC and PVAC. However, shared signalling events were influenced by different miRNA and/or genes in the two tumour entities. Overall, specific miRNA expression patterns were involved in the regulation of a limited core signalling pathways in the biology landscape of PDAC and PVAC.

High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE.

24,189 are all the possible non-synonymous amino acid changes potentially affecting the human mitochondrial DNA. Only a tiny subset was functionally evaluated with certainty so far, while the pathogenicity of the vast majority was only assessed in-silico by software predictors. Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. We provide a detailed description of the underlying algorithm, of the selected and manually curated training and test sets of variants, as well as of its classification ability.

Analysis of clock gene-miRNA correlation networks reveals candidate drivers in colorectal cancer.

Altered functioning of the biological clock is involved in cancer onset and progression. MicroRNAs (miRNAs) interact with the clock genes modulating the function of genetically encoded molecular clockworks. Collaborative interactions may take place within the coding-noncoding RNA regulatory networks. We aimed to evaluate the cross-talk among miRNAs and clock genes in colorectal cancer (CRC). We performed an integrative analysis of miRNA-miRNA and miRNA-mRNA interactions on high-throughput molecular profiling of matched human CRC tissue and non-tumor mucosa, pinpointing core clock genes and their targeting miRNAs. Data obtained in silico were validated in CRC patients and human colon cancer cell lines. In silico we found severe alterations of clock gene-related coding-noncoding RNA regulatory networks in tumor tissues, which were later corroborated by the analysis of human CRC specimens and experiments performed in vitro. In conclusion, specific miRNAs target and regulate the transcription/translation of clock genes and clock gene-related miRNA-miRNA as well as mRNA-miRNA interactions are altered in colorectal cancer. Exploration of the interplay between specific miRNAs and genes, which are critically involved in the functioning of the biological clock, provides a better understanding of the importance of the miRNA-clock genes axis and its derangement in colorectal cancer.

Multifaceted enrichment analysis of RNA-RNA crosstalk reveals cooperating micro-societies in human colorectal cancer.

Alterations in the balance of mRNA and microRNA (miRNA) expression profiles contribute to the onset and development of colorectal cancer. The regulatory functions of individual miRNA-gene pairs are widely acknowledged, but group effects are largely unexplored. We performed an integrative analysis of mRNA-miRNA and miRNA-miRNA interactions using high-throughput mRNA and miRNA expression profiles obtained from matched specimens of human colorectal cancer tissue and adjacent non-tumorous mucosa. This investigation resulted in a hypernetwork-based model, whose functional backbone was fulfilled by tight micro-societies of miRNAs. These proved to modulate several genes that are known to control a set of significantly enriched cancer-enhancer and cancer-protection biological processes, and that an array of upstream regulatory analyses demonstrated to be dependent on miR-145, a cell cycle and MAPK signaling cascade master regulator. In conclusion, we reveal miRNA-gene clusters and gene families with close functional relationships and highlight the role of miR-145 as potent upstream regulator of a complex RNA-RNA crosstalk, which mechanistically modulates several signaling pathways and regulatory circuits that when deranged are relevant to the changes occurring in colorectal carcinogenesis.