Brain transcriptomic profiling reveals common alterations across neurodegenerative and psychiatric disorders

Neurodegenerative and neuropsychiatric disorders (ND-NPs) are multifactorial, polygenic and complex behavioral phenotypes caused by brain abnormalities. Large-scale collaborative efforts have tried to identify the genetic architecture of these conditions. However, the specific and shared underlying molecular pathobiology of brain illnesses is not clear. Here, we examine transcriptome-wide characterization of eight conditions, using a total of 2,633 post-mortem brain samples from patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), Progressive Supranuclear Palsy (PSP), Pathological Aging (PA), Autism Spectrum Disorder (ASD), Schizophrenia (Scz), Major Depressive Disorder (MDD), and Bipolar Disorder (BP)–in comparison with 2,078 brain samples from matched control subjects. Similar transcriptome alterations were observed between NDs and NPs with the top correlations obtained between Scz-BP, ASD-PD, AD-PD, and Scz-ASD. Region-specific comparisons also revealed shared transcriptome alterations in frontal and temporal lobes across NPs and NDs. Co-expression network analysis identified coordinated dysregulations of cell-type-specific modules across NDs and NPs. This study provides a transcriptomic framework to understand the molecular alterations of NPs and NDs through their shared- and specific gene expression in the brain

FEELnc : a tool for long non-coding RNA annotation and its application to the dog transcriptome

Whole transcriptome sequencing (RNA-seq) has become a standard for cataloguing and monitoring RNA populations. One of the main bottlenecks, however, is to correctly identify the different classes of RNAs among the plethora of reconstructed transcripts, particularly those that will be translated (mRNAs) from the class of long non-coding RNAs (lncRNAs). Here, we present FEELnc (FlExible Extraction of LncRNAs), an alignment-free program that accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames. Benchmarking versus five state-of-the-art tools shows that FEELnc achieves similar or better classification performance on GENCODE and NONCODE data sets. The program also provides specific modules that enable the user to fine-tune classification accuracy, to formalize the annotation of lncRNA classes and to identify lncRNAs even in the absence of a training set of non-coding RNAs. We used FEELnc on a real data set comprising 20 canine RNA-seq samples produced by the European LUPA consortium to substantially expand the canine genome annotation to include 10 374 novel lncRNAs and 58 640 mRNA transcripts. FEELnc moves beyond conventional coding potential classifiers by providing a standardized and complete solution for annotating lncRNAs and is freely available at https://github.com/tderrien/FEELnc.Peer reviewe

Immune and Genetic Signatures of Breast Carcinomas Triggering Anti-Yo–Associated Paraneoplastic Cerebellar Degeneration

International audienceBackground and Objectives Paraneoplastic cerebellar degeneration (PCD) with anti-Yo antibodies is a cancer-related autoimmune disease directed against neural antigens expressed by tumor cells. A putative trigger of the immune tolerance breakdown is genetic alteration of Yo antigens. We aimed to identify the tumors' genetic and immune specificities involved in Yo-PCD pathogenesis. Methods Using clinicopathologic data, immunofluorescence (IF) imaging, and whole-transcriptome analysis, 22 breast cancers (BCs) associated with Yo-PCD were characterized in terms of oncologic characteristics, genetic alteration of Yo antigens, differential gene expression profiles, and morphofunctional specificities of their in situ antitumor immunity by comparing them with matched control BCs. Results Yo-PCD BCs were invasive carcinoma of no special type, which early metastasized to lymph nodes. They overexpressed human epidermal growth factor receptor 2 (HER2) but were hormone receptor negative. All Yo-PCD BCs carried at least 1 genetic alteration (variation or gain in copy number) on CDR2L, encoding the main Yo antigen that was found aberrantly overexpressed in Yo-PCD BCs. Analysis of the differentially expressed genes found 615 upregulated and 54 downregulated genes in Yo-PCD BCs compared with HER2-driven control BCs without PCD. Ontology enrichment analysis found significantly upregulated adaptive immune response pathways in Yo-PCD BCs. IF imaging confirmed an intense immune infiltration with an overwhelming predominance of immunoglobulin G-plasma cells. Discussion These data confirm the role of genetic alterations of Yo antigens in triggering the immune tolerance breakdown but also outline a specific biomolecular profile in Yo-PCD BCs, suggesting a cancer-specific pathogenesis

Cell type-specific genetic regulation of gene expression across human tissues

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type-interaction QTLs for seven cell types and show that cell type-interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type-interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue

The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation

The impact of sex on gene expression across human tissues

Many complex human phenotypes exhibit sex-differentiated characteristics, however the underlying molecular mechanisms of these differences remain largely unknown. Here, we present an extensive catalog of both sex differences in gene expression and its genetic regulation across 44 human tissue sources surveyed by GTEx (v8 release). We demonstrate that sex strongly influences gene expression levels and cellular composition of tissue samples across the human body. The effect of sex on gene expression is widespread, with a total of 37% of all genes exhibiting sex-biased expression in at least one tissue. This suggests that many if not most biological processes, and thus complex traits and diseases, are impacted by sex effects on the transciptome. We expand the identification of cis-eQTLs with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation in a single sex, including novel associations not detected with sex-agnostic approaches. Altogether we provide the most comprehensive characterization of sex differences in the human transcriptome and its regulation to date.Peer ReviewedPreprin

Modélisation d'un réseau de régulation d'ARN pour prédire des fonctions de gènes impliqués dans le mode de reproduction du puceron du pois

This thesis aims to discriminate between embryos development towards either sexual or asexual reproduction types in pea aphids, Acyrthosiphon pisum, at the genomic level. This discrimination involves the creation of a post-transcriptional regulation network between microRNAs and mRNAs whose kinetic expressions change depending on the embryogenesis. It also involves a study of this network's interaction modules using formal concept analysis. To do so, a three-step strategy was set up. First the creation of an interaction network between the pea aphid's microRNAs and mRNAs. The network is then reduced by keeping only microRNAs and mRNAs which possess differential kinetics between the two embryogeneses, these are obtained using high-throughput sequencing data. Finally the remaining network is analysed using formal concept analysis. Analysing the network allowed for the identification of several functions of potential interest such as oogenesis, transcriptional regulation or even neuroendocrine system. In addition to network analysis, formal concept analysis was used to create a new method to repair a bipartite graph based on its topology and a method to visualise a bipartite graph using its formal concepts.Cette thèse cherche à discriminer au niveau génomique entre le développement d'embryons vers un mode de reproduction sexué et le développement vers un mode asexué chez le puceron du pois, Acyrthosiphon pisum. Cette discrimination passe par la création du réseau de régulation post-transcriptionnelle des microARN et des ARNm qui possèdent des cinétiques d'expression différentes entre ces deux embryogenèses ainsi que par l'analyse des modules d'interactions de ce réseau par l'utilisation de l'analyse de concepts formels. Pour ce faire, une stratégie en plusieurs étapes a été mise en place : la création d'un réseau d'interactions entre les microARN et les ARNm du puceron du pois ; l'extraction et la réduction du réseau aux microARN et ARNm qui possèdent des cinétiques différentes entre les deux embryogenèses à partir des données d'expression tirées du séquençage haut-débit ; l'analyse du réseau d'interactions réduit aux éléments d’intérêt par l'analyse de concepts formels. L'analyse du réseau a permis l'identification de différentes fonctions potentiellement importantes comme l'ovogenèse, la régulation transcriptionnelle ou encore le système neuroendocrinien. En plus de l'analyse du réseau, l'analyse de concepts formels a été utilisée pour définir une méthode de réparation de graphe biparti basée sur une topologie en "concepts" ainsi qu'une méthode de visualisation de graphes bipartis par ses concepts

Modeling of a gene network between mRNAs and miRNAs to predict gene functions involved in phenotypic plasticity in the pea aphid

Cette thèse cherche à discriminer au niveau génomique entre le développement d'embryons vers un mode de reproduction sexué et le développement vers un mode asexué chez le puceron du pois, Acyrthosiphon pisum. Cette discrimination passe par la création du réseau de régulation post-transcriptionnelle des microARN et des ARNm qui possèdent des cinétiques d'expression différentes entre ces deux embryogenèses ainsi que par l'analyse des modules d'interactions de ce réseau par l'utilisation de l'analyse de concepts formels. Pour ce faire, une stratégie en plusieurs étapes a été mise en place : la création d'un réseau d'interactions entre les microARN et les ARNm du puceron du pois ; l'extraction et la réduction du réseau aux microARN et ARNm qui possèdent des cinétiques différentes entre les deux embryogenèses à partir des données d'expression tirées du séquençage haut-débit ; l'analyse du réseau d'interactions réduit aux éléments d’intérêt par l'analyse de concepts formels. L'analyse du réseau a permis l'identification de différentes fonctions potentiellement importantes comme l'ovogenèse, la régulation transcriptionnelle ou encore le système neuroendocrinien. En plus de l'analyse du réseau, l'analyse de concepts formels a été utilisée pour définir une méthode de réparation de graphe biparti basée sur une topologie en "concepts" ainsi qu'une méthode de visualisation de graphes bipartis par ses concepts.This thesis aims to discriminate between embryos development towards either sexual or asexual reproduction types in pea aphids, Acyrthosiphon pisum, at the genomic level. This discrimination involves the creation of a post-transcriptional regulation network between microRNAs and mRNAs whose kinetic expressions change depending on the embryogenesis. It also involves a study of this network's interaction modules using formal concept analysis. To do so, a three-step strategy was set up. First the creation of an interaction network between the pea aphid's microRNAs and mRNAs. The network is then reduced by keeping only microRNAs and mRNAs which possess differential kinetics between the two embryogeneses, these are obtained using high-throughput sequencing data. Finally the remaining network is analysed using formal concept analysis. Analysing the network allowed for the identification of several functions of potential interest such as oogenesis, transcriptional regulation or even neuroendocrine system. In addition to network analysis, formal concept analysis was used to create a new method to repair a bipartite graph based on its topology and a method to visualise a bipartite graph using its formal concepts

Edge Selection in a Noisy Graph by Concept Analysis – Application to a Genomic Network

International audienceMicroRNAs (miRNAs) are small RNA molecules that bind messengerRNAs (mRNAs) to silence their expression. Understanding this regulation mech-anism requires the study of the miRNA/mRNA interaction network. State of theart methods for predicting interactions lead to a high level of false positive: theinteraction score distribution may be roughly described as a mixture of two over-lapping Gaussian laws that need to be discriminated with a threshold. In order tofurther improve the discrimination between true and false interactions, we presenta method that considers the structure of the underlying graph. We assume that thegraph is formed on a relatively simple structure of formal concepts (associated toregulation modules in the regulation mechanism). Specifically, the formal contexttopology of true edges is assumed to be less complex than in the case of a noisygraph including spurious interactions or missing interactions. Our approach consiststhus in selecting edges below an edge score threshold and applying a repair processon the graph, adding or deleting edges to decrease the global concept complexity.To validate our hypothesis and method, we have extracted parameters from a realbiological miRNA/mRNA network and used them to build random networks withfixed concept topology and true/false interaction ratio. Each repaired network canbe evaluated with a score balancing the number of edge changes and the conceptualadequacy in the spirit of the minimum description length principle

Genome expression control during the photoperiodic response of aphids

International audienceAphids are major crop pests and show a high level of phenotypic plasticity. They display a seasonal, photoperiodically-controlled polyphenism during their life cycle. In spring and summer, they reproduce efficiently by parthenogenesis. At the end of summer, parthenogenetic individuals detect the transition from short nights to long nights, which initiates the production of males and oviparous females within their offspring. These are the morphs associated with the autumn season. Deciphering the physiological and molecular events associated with this switch in reproductive mode in response to photoperiodic conditions is thus of key interest for understanding and explaining the remarkable capacity of aphids to adapt to fluctuations in their environment. The present review aims to compile earlier physiological studies, focussing on the neuroendocrine control of seasonal photoperiodism, as well as a series of large-scale transcriptomic approaches made possible by the recent development of genomic resources for the model aphid species: the pea aphid Acyrthosiphon pisum. These analyses identify genetic programmes putatively involved in the control of the initial steps of detection and transduction of the photoperiodic signal, as well as in the regulation of the switch between asexual and sexual oogenesis within embryonic ovaries. The contribution of small RNAs pathways (and especially microRNAs) in the post-transcriptional control of gene expression, as well as the role of epigenetic mechanisms in the regulation of genome expression associated with the photoperiodic response, is also summarized