Search bioRxiv⌕ Search

Biology subjects

Boughorbel, S.

Publications and source records attributed to Boughorbel, S..

6 recordsLinked to original sources

Coordinated periodic expression of the imprinted network genes in the hair follicle growth cycle.

1.Imprinted genes help mediate embryonic cell proliferation and differentiation, but their roles after birth are far less well understood. A subset of 16 imprinted gene network (IGN) genes is expressed at higher levels in stem cell progenitor cells of adult skeletal muscle and epidermis compared to their differentiated counterparts. While these genes function in muscle regeneration, their role in the skin is poorly understood. We assessed the expression profiles of these 16 IGN genes in publicly available datasets and revealed elevated expression of IGN genes in the telogen and early anagen phases in mouse skin. We also identified IGN genes among a list of previously identified hair cycle-associated genes. Furthermore, our results suggest that IGN genes form part of a larger network and function predominantly as upstream regulators of hair cycle-regulated genes. Based on these in silico data, we propose a potential novel role of these 16 IGN genes as upstream regulators of hair cycle-associated genes. We speculate that IGN gene dysregulation participates in syndromes characterized by an impaired hair cycle. Thus, IGN gene expression might serve as a point of therapeutic intervention for patients suffering from cutaneous pathologies such as common hair-loss disorders.

genetics↗

A curated transcriptome dataset collection to investigate inborn errors of immunity.

Primary immunodeficiencies (PIDs) are a heterogeneous group of inherited disorders, frequently caused by loss-of-function and less commonly by gain-of-function mutations, which can result in susceptibility to a broad or a very narrow range of infections but also in inflammatory, allergic or malignant diseases. Owing to the wide range in clinical manifestations and variability in penetrance and expressivity, there is an urgent need to better understand the underlying molecular, cellular and immunological phenotypes in PID patients in order to improve clinical diagnosis and management. Here we have compiled a manually curated collection of public transcriptome datasets mainly obtained from human whole blood, peripheral blood mononuclear cells (PBMCs) or fibroblasts of patients with PIDs and of control subjects for subsequent meta-analysis, query and interpretation. A total of nineteen (19) datasets derived from studies of PID patients were identified and retrieved from the NCBI Gene Expression Omnibus (GEO) database and loaded in GXB, a custom web application designed for interactive query and visualization of integrated large-scale data. The dataset collection includes samples from well characterized PID patients that were stimulated ex vivo under a variety of conditions to assess the molecular consequences of the underlying, naturally occurring gene defects on a genome-wide scale. Multiple sample groupings and rank lists were generated to facilitate comparisons of the transcriptional responses between different PID patients and control subjects. The GXB tool enables browsing of a single transcript across studies, thereby providing new perspectives on the role of a given molecule across biological systems and PID patients. This dataset collection is available at: http://pid.gxbsidra.org/dm3/geneBrowser/list.

immunology↗

A curated collection of transcriptome datasets to investigate the molecular mechanisms of immunoglobulin E-mediated atopic diseases

Prevalence of allergies has reached ~50% of industrialized populations and with children under ten being the most susceptible. However, the combination of the complexity of atopic allergy susceptibility/development and environmental factors has made identification of gene biomarkers challenging. The amount of publicly accessible transcriptomic data presents an unprecedented opportunity for mechanistic discoveries and validation of complex disease signatures across studies. However, this necessitates structured methodologies and visual tools for the interpretation of results. Here, we present a curated collection of transcriptomic datasets relevant to immunoglobin E (IgE)-mediated atopic diseases (ranging from allergies to primary immunodeficiencies). 30 datasets from the Gene Expression Omnibus (GEO), encompassing 1761 transcriptome profiles, were made available on the Gene Expression Browser (GXB), an online and open-source web application that allows for the query, visualization, and annotation of metadata. The thematic compositions, disease categories, sample number, and platforms of the collection are described. Ranked gene lists and sample grouping are used to facilitate data visualization/interpretation and are available online via GXB (http://ige.gxbsidra.org/dm3/geneBrowser/list). Dataset validation using associated publications showed good concordance in GXB gene expression trend and fold-change.\n\nDatabase URL: http://ige.gxbsidra.org/dm3/geneBrowser/list

immunology↗

The abundance of Nudix hydrolase 16 transcripts is elevated in human sepsis: perspectives gained during a hands-on reductionist investigation workshop.

A hands-on training workshop was devised with omics data used as source material to emulate reductionist investigation approaches. NUDT16, a member of the Nudix hydrolase family was selected as a candidate gene on the basis of: 1) it being upregulated in neutrophils exposed in vitro to serum of patients with sepsis, AND 2) the absence of overlap between the NUDT16 and sepsis, inflammation or neutrophil literature. We next sought to corroborate the initial finding in five public transcriptome sepsis datasets in which NUDT16 transcript levels were measured. In each of these dataset NUDT16 transcript abundance was found to be significantly increased in septic patients in vivo in comparison to uninfected controls. Next, biological concepts were extracted from the NUDT16 literature. The main concepts to emerge from profiling this literature were RNA decapping, inosine triphosphate, and inosine diphosphate. Through these concepts, indirect links could be established between NUDT16 and the sepsis/inflammation/neutrophil literature. A potential role for NUDT16 could, in turn, be inferred in the degradation of mRNAs in activated neutrophils. Follow on experiments that would be necessary in order to further explore such inference are discussed.

immunology↗

On the Depth of Deep Learning Models for Splice Site Identification

The success of deep learning has been shown in various fields including computer vision, speech recognition, natural language processing and bioinformatics. The advance of Deep Learning in Computer Vision has been an important source of inspiration for other research fields. The objective of this work is to adapt known deep learning models borrowed from computer vision such as VGGNet, Resnet and AlexNet for the classification of biological sequences. In particular, we are interested by the task of splice site identification based on raw DNA sequences. We focus on the role of model architecture depth on model training and classification performance.\n\nWe show that deep learning models outperform traditional classification methods (SVM, Random Forests, and Logistic Regression) for large training sets of raw DNA sequences. Three model families are analyzed in this work namely VGGNet, AlexNet and ResNet. Three depth levels are defined for each model family. The models are benchmarked using the following metrics: Area Under ROC curve (AUC), Number of model parameters, number of floating operations. Our extensive experimental evaluation show that shallow architectures have an overall better performance than deep models. We introduced a shallow version of ResNet, named S-ResNet. We show that it gives a good trade-off between model complexity and classification performance.\n\nAuthor summaryDeep Learning has been widely applied to various fields in research and industry. It has been also succesfully applied to genomics and in particular to splice site identification. We are interested in the use of advanced neural networks borrowed from computer vision. We explored well-known models and their usability for the problem of splice site identification from raw sequences. Our extensive experimental analysis shows that shallow models outperform deep models. We introduce a new model called S-ResNet, which gives a good trade-off between computational complexity and classification accuracy.

bioinformatics↗

IRF4 haploinsufficiency in a family with Whipples disease

The pathogenesis of Whipples disease (WD) remains largely unknown, as WD strikes only a very small minority of the individuals infected with Tropheryma whipplei (Tw). Asymptomatic carriage of Tw is less rare. We studied a large multiplex French kindred, containing four otherwise healthy WD patients (mean age: 76.7 years) and five healthy carriers of Tw (mean age: 55 years). We used a strategy combining genome-wide linkage analysis and whole-exome sequencing to test the hypothesis that WD is inherited in an autosomal dominant (AD) manner, with age-dependent incomplete penetrance. WD was linked to 12 genomic regions covering 27 megabases in the four patients. These regions contained only one very rare non-synonymous variation: the R98W variant of IRF4. The five Tw carriers were heterozygous for R98W. Interferon regulatory factor 4 (IRF4) is a transcription factor with pleiotropic roles in immunity. We showed that R98W was a loss-of-function allele, like only five other exceedingly rare IRF4 alleles of a total of 39 rare and common non-synonymous alleles tested. Furthermore, heterozygosity for R98W led to a distinctive pattern of transcription in leukocytes following stimulation with BCG or Tw. Finally, we found that IRF4 had evolved under purifying selection and that R98W was not dominant-negative, suggesting that the IRF4 deficiency in this kindred was due to haploinsufficiency. Overall, haploinsufficiency at the IRF4 locus selectively underlies WD in this multiplex kindred. This deficiency displays AD inheritance with incomplete penetrance, and chronic carriage probably precedes WD by several decades in Tw-infected heterozygotes.

immunology↗