Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology

Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in the post-genomic era. Also, complex diseases present highly heterogeneous genotype, which difficult biological marker identification. Machine learning methods are widely used to identify these markers, but their performance is highly dependent upon the size and quality of available data. In this study, we demonstrated that machine learning classifiers trained on gene functional similarities, using Gene Ontology (GO), can improve the identification of genes involved in complex diseases. For this purpose, we developed a supervised machine learning methodology to predict complex disease genes. The proposed pipeline was assessed using Autism Spectrum Disorder (ASD) candidate genes. A quantitative measure of gene functional similarities was obtained by employing different semantic similarity measures. To infer the hidden functional similarities between ASD genes, various types of machine learning classifiers were built on quantitative semantic similarity matrices of ASD and non-ASD genes. The classifiers trained and tested on ASD and non-ASD gene functional similarities outperformed previously reported ASD classifiers. For example, a Random Forest (RF) classifier achieved an AUC of 0. 80 for predicting new ASD genes, which was higher than the reported classifier (0.73). Additionally, this classifier was able to predict 73 novel ASD candidate genes that were enriched for core ASD phenotypes, such as autism and obsessive-compulsive behavior. In addition, predicted genes were also enriched for ASD co-occurring conditions, including Attention Deficit Hyperactivity Disorder (ADHD). We also developed a KNIME workflow with the proposed methodology which allows users to configure and execute it without requiring machine learning and programming skills. Machine learning is an effective and reliable technique to decipher ASD mechanism by identifying novel disease genes, but this study further demonstrated that their performance can be improved by incorporating a quantitative measure of gene functional similarities. Source code and the workflow of the proposed methodology are available at https://github.com/Muh-Asif/ASD-genes-prediction.This work was supported by the Portuguese Fundação para a Ciência e Tecnologia (SFRH/BD/52485/2014 to MA and DeST: Deep Semantic Tagger PTDC/CCI-BIO/28685/2017).info:eu-repo/semantics/publishedVersio

Catching the therapeutic window of opportunity in early initial-onset Vogt�Koyanagi�Harada uveitis can cure the disease

Purpose: Vogt�Koyanagi�Harada (VKH) disease is a primary autoimmune granulomatous choroiditis that begins in the choroidal stroma. The aim of this review was to gather a body of evidence for the concept of a window of therapeutic opportunity, defined as a time interval following initial-onset disease during which adequate treatment will substantially modify the disease outcome and possibly even lead to cure, similar to what has been described for rheumatoid arthritis. Methods: We reviewed the literature and consulted leading experts in VKH disease to determine the consensus for the notion of a therapeutic window of opportunity in VKH disease. Results: We found a substantial body of evidence in the literature that a therapeutic window of opportunity exists for initial-onset acute uveitis associated with VKH disease. The disease outcome can be substantially improved if dual systemic steroidal and non-steroidal immunosuppressants are given within 2�3 weeks of the onset of initial VKH disease, avoiding evolution to chronic disease and development of �sunset glow fundus.� Several studies additionally report series in which the disease could be cured, using such an approach. Conclusions: There is substantial evidence for a therapeutic window of opportunity in initial-onset acute VKH disease. Timely and adequate treatment led to substantial improvement of disease outcome and prevented chronic evolution and �sunset glow fundus,� and very early treatment led to the cure after discontinuation of therapy in several series, likely due to the fact that the choroid is the sole origin of inflammation in VKH disease. © 2018 The Author(s

Constraints on Dark Matter Annihilation in Clusters of Galaxies with the Fermi Large Area Telescope

Nearby clusters and groups of galaxies are potentially bright sources of high-energy gamma-ray emission resulting from the pair-annihilation of dark matter particles. However, no significant gamma-ray emission has been detected so far from clusters in the first 11 months of observations with the Fermi Large Area Telescope. We interpret this non-detection in terms of constraints on dark matter particle properties. In particular for leptonic annihilation final states and particle masses greater than ~200 GeV, gamma-ray emission from inverse Compton scattering of CMB photons is expected to dominate the dark matter annihilation signal from clusters, and our gamma-ray limits exclude large regions of the parameter space that would give a good fit to the recent anomalous Pamela and Fermi-LAT electron-positron measurements. We also present constraints on the annihilation of more standard dark matter candidates, such as the lightest neutralino of supersymmetric models. The constraints are particularly strong when including the fact that clusters are known to contain substructure at least on galaxy scales, increasing the expected gamma-ray flux by a factor of ~5 over a smooth-halo assumption. We also explore the effect of uncertainties in cluster dark matter density profiles, finding a systematic uncertainty in the constraints of roughly a factor of two, but similar overall conclusions. In this work, we focus on deriving limits on dark matter models; a more general consideration of the Fermi-LAT data on clusters and clusters as gamma-ray sources is forthcoming.Comment: accepted to JCAP, Corresponding authors: T.E. Jeltema and S. Profumo, minor revisions to be consistent with accepted versio

A Measurement of Coherent Neutral Pion Production in Neutrino Neutral Current Interactions in NOMAD

We present a study of exclusive neutral pion production in neutrino-nucleus Neutral Current interactions using data from the NOMAD experiment at the CERN SPS. The data correspond to $1.44 \times 10^6$ muon-neutrino Charged Current interactions in the energy range $2.5 \leq E_{\nu} \leq 300$ GeV. Neutrino events with only one visible $\pi^0$ in the final state are expected to result from two Neutral Current processes: coherent $\pi^0$ production, {\boldmath $\nu + {\cal A} \to \nu + {\cal A} + \pi^0$} and single $\pi^0$ production in neutrino-nucleon scattering. The signature of coherent $\pi^0$ production is an emergent $\pi^0$ almost collinear with the incident neutrino while $\pi^0$'s produced in neutrino-nucleon deep inelastic scattering have larger transverse momenta. In this analysis all relevant backgrounds to the coherent $\pi^0$ production signal are measured using data themselves. Having determined the backgrounds, and using the Rein-Sehgal model for the coherent $\pi^0$ production to compute the detection efficiency, we obtain {\boldmath $4630 \pm 522 (stat) \pm 426 (syst)$} corrected coherent-$\pi^0$ events with $E_{\pi^0} \geq 0.5$ GeV. We measure {\boldmath $\sigma (\nu {\cal A} \to \nu {\cal A} \pi^0) = [ 72.6 \pm 8.1(stat) \pm 6.9(syst) ] \times 10^{-40} cm^2/nucleus$}. This is the most precise measurement of the coherent $\pi^0$ production to date.Comment: 23 pages, 9 figures, accepted for publication in Phys. Lett.

“Out of the Can”: A Draft Genome Assembly, Liver Transcriptome, and Nutrigenomics of the European Sardine, Sardina pilchardus

Clupeiformes, such as sardines and herrings, represent an important share of worldwide fisheries. Among those, the European sardine (Sardina pilchardus, Walbaum 1792) exhibits significant commercial relevance. While the last decade showed a steady and sharp decline in capture levels, recent advances in culture husbandry represent promising research avenues. Yet, the complete absence of genomic resources from sardine imposes a severe bottleneck to understand its physiological and ecological requirements. We generated 69 Gbp of paired-end reads using Illumina HiSeq X Ten and assembled a draft genome assembly with an N50 scaffold length of 25,579 bp and BUSCO completeness of 82.1% (Actinopterygii). The estimated size of the genome ranges between 655 and 850 Mb. Additionally, we generated a relatively high-level liver transcriptome. To deliver a proof of principle of the value of this dataset, we established the presence and function of enzymes (Elovl2, Elovl5, and Fads2) that have pivotal roles in the biosynthesis of long chain polyunsaturated fatty acids, essential nutrients particularly abundant in oily fish such as sardines. Our study provides the first sustainableomics datasetexploitation.from a valuable economic marine teleost species, the European sardine, representing an essential resource for their effective conservation, management, and sustainable exploitation. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.Funding: We acknowledge the North Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) that supported this research through the Coral—Sustainable Ocean Exploitation (reference NORTE-01-0145-FEDER-000036). R.R.d.F. thanks the Danish National Research Foundation for its support of the Center for Macroecology, Evolution, and Climate (grant DNRF96). Acknowledgments: Some computational work was performed on the Abel Supercomputing Cluster (Norwegian metacenter for High Performance Computing (NOTUR) and the University of Oslo) operated by the Research Computing Services group at USIT, the University of Oslo IT-department (http://www.hpc.uio.no/). We would like to thank Jette Bornholdt, Amal Al-Chaer and George Pacheco for help with laboratory procedures, and the Bioinformatics Center of the University of Copenhagen for providing laboratory space. This work is part of the CIIMAR-lead initiative Portugal-Fishomics

Internal representations of smell in the Drosophila brain

Recent advances in sensory neuroscience using Drosophila olfaction as a model system have revealed brain maps representing the external world. Once we understand how the brain's built-in capability generates the internal olfactory maps, we can then elaborate how the brain computes and makes decision to elicit complex behaviors. Here, we review current progress in mapping Drosophila olfactory circuits and discuss their relationships with innate olfactory behaviors