Biology subjects

Germain, P.-L.

Publications and source records attributed to Germain, P.-L..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

The vascular gene Apold1 is dispensable for normal development but controls angiogenesis under pathological conditions

The molecular mechanisms of angiogenesis have been intensely studied, but many genes that control endothelial behavior and fate still need to be described. Here, we characterize the role of Apold1 (Apolipoprotein L domain containing 1) in angiogenesis in vivo and in vitro. Single-cell analyses reveal that - across tissues - the expression of Apold1 is restricted to the vasculature, and that Apold1 expression in endothelial cells (ECs) is highly sensitive to environmental factors. Using Apold1-/- mice, we find that Apold1 is dispensable for development and does not affect postnatal retinal angiogenesis nor alters the vascular network in adult brain and muscle. However, when exposed to ischemic conditions following photothrombotic stroke as well as femoral artery ligation, Apold1-/- mice display dramatic impairments in recovery and revascularization. We also find that human tumor endothelial cells express strikingly higher levels of Apold1, and that Apold1 deletion in mice stunts the growth of subcutaneous B16 melanoma tumors, which have smaller and poorly perfused vessels. Mechanistically, Apold1 is activated in ECs upon growth factor stimulation as well as in hypoxia, and Apold1 intrinsically controls EC proliferation but not migration. Our data demonstrate that Apold1 is a key regulator of angiogenesis in pathological settings, whereas it does not affect developmental angiogenesis, thus making it a promising candidate for clinical investigation.

cell biology↗

bioRxiv2022

7q11.23 CNV alters protein synthesis and REST-mediated neuronal intrinsic excitability

Copy number variations (CNVs) at 7q11.23 cause Williams-Beuren (WBS) and 7q microduplication syndromes (7Dup), two neurodevelopmental disorders with shared and opposite cognitive-behavioral phenotypes. Using patient-derived and isogenic neurons, we integrated transcriptomics, translatomics and proteomics to elucidate the molecular underpinnings of this dosage effect. We found that 7q11.23 CNVs cause opposite alterations in neuronal differentiation and excitability. Genes related to neuronal transmission chiefly followed 7q11.23 dosage and appeared transcriptionally controlled, while translation and ribosomal protein genes followed the opposite trend and were post-transcriptionally buffered. Mechanistically, we uncovered REST regulon as a key mediator of observed phenotypes and rescued transcriptional and excitability alterations through REST inhibition. We identified downregulation of global protein synthesis, mGLUR5 and ERK-mTOR pathways activity in steady-state in both WBS and 7Dup, whereas BDNF stimulation rescued them specifically in 7Dup. Overall, we show that 7q11.23 CNVs alter protein synthesis and neuronal firing-established molecular and cellular phenotypes of neurodevelopmental disorders. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/511483v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1b0fa99org.highwire.dtl.DTLVardef@146624org.highwire.dtl.DTLVardef@13dc89aorg.highwire.dtl.DTLVardef@13d098f_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Meta-analysis of (single-cell method) benchmarks reveals the need for extensibility and interoperability

Computational methods represent the lifeblood of modern molecular biology. Benchmarking is important for all methods, but with a focus here on computational methods, benchmarking is critical to dissect important steps of analysis pipelines, formally assess performance across common situations as well as edge cases, and ultimately guide users on what tools to use. Benchmarking can also be important for community building and advancing methods in a principled way. We conducted a meta-analysis of recent single-cell benchmarks to summarize the scope, extensibility, neutrality, as well as technical features and whether best practices in open data and reproducible research were followed. The results highlight that while benchmarks often make code available and are in principle reproducible, they remain difficult to extend, for example, as new methods and new ways to assess methods emerge. In addition, embracing containerization and workflow systems would enhance reusability of intermediate benchmarking results, thus also driving wider adoption.

bioinformatics↗

bioRxiv2021

Pathological LSD1 mutations cause HDAC-mediated aberrant gene repression during early cell differentiation

Lysine-specific demethylase 1 (LSD1/KDM1A) demethylates both histone and non-histone substrates, recruits repressive chromatin complexes, and is increased in cancers. De novo LSD1 mutations impairing protein function lead to a rare developmental disorder, but the molecular details of the pathology remains unclear. Using patient-derived fibroblasts, reprogrammed pluripotent stem cells, and differentiated cells, we found over 4000 differentially expressed genes and 68 transcription factors (TFs) whose motif accessibilities changed upon LSD1 mutation. An enhancer-mediated gene regulatory network approach identified transcriptional repressors with impaired activity in fibroblast and stem cells, leading to erroneous activation of their target genes. We also revealed overall decreases in TF target gene expression during early lineage differentiation of LSD1 mutant stem cells, likely caused by increased activity of repressive histone deacetylases (HDACs), co-factors of LSD1. Indeed, an HDACs inhibitor restored changes in gene expression including downregulation phenotype. Our findings characterize the molecular pathogenesis of LSD1 mutations and suggest potential therapeutic strategies for the developmental disorder and cancers caused by LSD1 dysregulations.

genomics↗

bioRxiv2021

scanMiR: a biochemically-based toolkit for versatile and efficient microRNA target prediction

microRNAs are important post-transcriptional regulators of gene expression, but the identification of functionally relevant targets is still challenging. Recent research has shown improved prediction of microRNA-mediated repression using a biochemical model combined with empirically-derived k-mer affinity predictions. Here, we translate this approach into a flexible and user-friendly bioconductor package, scanMiR, also available through a web interface. Using lightweight linear models, scanMiR efficiently scans for binding sites, estimates their affinity, and predicts aggregated transcript repression. Moreover, flexible 3-supplementary alignment enables the prediction of unconventional interactions, such as bindings potentially leading to target-directed microRNA degradation (TDMD) or slicing. We showcase scanMiR through a systematic scan for such unconventional sites on neuronal transcripts, including lncRNAs and circRNAs.

bioinformatics↗

bioRxiv2021

microRNA-138 controls hippocampal interneuron function and short-term memory

The proper development and function of neuronal circuits relies on a tightly regulated balance between excitatory and inhibitory (E/I) synaptic transmission, and disrupting this balance can cause neurodevelopmental disorders, e.g. schizophrenia. microRNA-dependent gene regulation in pyramidal neurons is important for excitatory synaptic function and cognition, but its role in inhibitory interneurons is poorly understood. Here, we identify miR-138-5p as a regulator of short-term memory and inhibitory synaptic transmission in the hippocampus. Sponge-mediated miR-138-5p inactivation specifically in parvalbumin (PV)-expressing interneurons impairs spatial recognition memory and enhances GABAergic synaptic input onto pyramidal neurons. Cellular and behavioural phenotypes associated with miR-138-5p inactivation are paralleled by an upregulation of the schizophrenia-associated Erbb4, which we validated as a direct miR-138-5p target gene. Our findings suggest that miR-138-5p is a critical regulator of PV interneuron function, with implications for cognition and schizophrenia. More generally, they provide evidence that microRNAs orchestrate neural circuit development by fine-tuning both excitatory and inhibitory synaptic transmission.

neuroscience↗

bioRxiv2021

KMT2D haploinsufficiency in Kabuki Syndrome disrupts neuronal function through transcriptional and chromatin rewiring independent of H3K4-monomethylation

Kabuki syndrome (KS) is a rare multisystem disorder, characterized by intellectual disability, growth delay, and distinctive craniofacial features. It is mostly caused by de novo mutations of KMT2D, which is responsible for histone H3lysine 4 mono-methylation (H3K4me1) that marks active and poised enhancers. We assessed the impact of KMT2D mutations on chromatin and transcriptional regulation in a cohort of multiple KS1 tissues, including primary patient samples and disease-relevant lineages, namely cortical neurons (iN), neural crest stem cells (NCSC), and mesenchymal cells (MC). In parallel, we generated an isogenic line derived from human embryonic stem cells (hESC) for the stepwise characterization of neural precursors and mature neurons. We found that transcriptional dysregulation was particularly pronounced in cortical neurons and widely affected synapse activity pathways. This was consistent with highly specific alterations of spontaneous network-bursts patterns evidenced by Micro-electrode-array (MEA)-based neural network. Profiling of H3K4me1 unveiled the almost complete uncoupling between this chromatin mark and the effects on transcription, which is instead reflected by defects in H3K27ac. Finally, we identified the direct targets of KMT2D in mature cortical neurons, uncovering TEAD2 as the main mediator of KMT2D haploinsufficiency. Our results uncover the multi-tissue architecture of KS1 dysregulation and define a unique electrical phenotype and its molecular underpinnings for the cortical neuronal lineage.

genetics↗

bioRxiv2021

Molecular roadmap of the healthy stress response in the mouse hippocampus

The acute stress response mobilizes energy to meet situational demands and re-establish homeostasis. However, little is known about the nature and dynamics of the underlying molecular cascades. We used a brief forced swim exposure to trigger a strong stress response in mice, which transiently increases anxiety, but does not lead to lasting maladaptive behavioral changes. Using multiomic profiling we characterize the stress-induced molecular events in the hippocampus over time, across molecular scales, and down to the level of cell types and single cells. Our results unveil the complexity and specificity of the healthy stress response, with widespread changes in protein phosphorylation and gene transcription, but tightly regulated protein translation. All observed molecular events resolve efficiently within 4 hours after initiation of stress. The data are accessible through an interactive web portal, creating an extensive molecular resource that will help understand how stress impacts brain function in health and disease.

neuroscience↗

bioRxiv2021

Streamlining differential exon and 3 UTR usage with diffUTR

BackgroundDespite the importance of alternative poly-adenylation and 3 UTR length for a variety of biological phenomena, there are limited means of detecting UTR changes from standard transcriptomic data. ResultsWe present the diffUTR Bioconductor package which streamlines and improves upon differential exon usage (DEU) analyses, and leverages existing DEU tools and alternative polyadenylation site databases to enable differential 3 UTR usage analysis. We demonstrate the diffUTR features and show that it is more flexible and more accurate than state-of-the-art alternatives, both in simulations and in real data. ConclusionsdiffUTR enables differential 3 UTR analysis and more generally facilitates DEU and the exploration of their results.

bioinformatics↗

bioRxiv2020

Translatomic profiling of the acute stress response: It's a TRAP

The impact of stress on gene expression in different cell types of the brain remains poorly characterized. Three pioneering studies have recently used translating ribosome affinity purification followed by RNA sequencing (TRAP-seq) to assess the response to stress in CA3 pyramidal neurons of the hippocampus. The results suggest that acute stress alters the translation of thousands of genes in CA3 pyramidal neurons, and that this response is strongly modulated by factors such as sex, genotype and a history of early life stress. However, our reanalysis of these datasets leads to different conclusions. We confirm that acute stress induces robust translational changes in a small set of genes. However, we found no evidence that either early life stress or sex have an effect on gene translation induced by acute stress. Our findings highlight the need for additional studies with adequate sample sizes and proper methods of analysis to assess the impact of stress across cell types in the brain.

neuroscience↗

bioRxiv2020

Pervasive compartment-specific regulation of gene expression during homeostatic synaptic scaling

Synaptic scaling is a form of homeostatic plasticity which allows neurons to adjust their action potential firing rate in response to chronic alterations in neural activity. Synaptic scaling requires profound changes in gene expression, but the relative contribution of local and cell-wide mechanisms is controversial. Here we performed a comprehensive multi-omics characterization of the somatic and process compartments of primary rat hippocampal neurons during synaptic scaling. Thereby, we uncovered both highly compartment-specific and correlated changes in the neuronal transcriptome and proteome. Whereas downregulation of crucial regulators of neuronal excitability occurred primarily in the somatic compartment, structural components of excitatory postsynapses were mostly downregulated in processes. Motif analysis further suggests an important role for trans-acting post-transcriptional regulators, including RNA-binding proteins and microRNAs, in the local regulation of the corresponding mRNAs. Altogether, our study indicates that compartmentalized gene expression changes are widespread in synaptic scaling and might co-exist with neuron-wide mechanisms to allow synaptic computation and homeostasis.

neuroscience↗

bioRxiv2020

Transcriptome and epigenome characterization of mouse spermatogonial cells reveals distinct chromatin regulatory landscapes in postnatal and adult testis

In mammals, spermatogonial cells (SPGs) are undifferentiated male germ cells in testis that are quiescent until birth and then self-renew and differentiate to produce spermatogenic cells and functional sperm from early postnatal life throughout adulthood. The transcriptome of SPGs is highly dynamic and timely regulated during postnatal development. We examined if such dynamics involves changes in chromatin organization by profiling the transcriptome and chromatin accessibility of SPGs from early postnatal stages to adulthood in mice using deep RNA-seq, ATAC-seq and computational deconvolution analyses. By integrating transcriptomic and epigenomic features, we show that SPGs undergo massive chromatin remodeling during postnatal development that partially correlates with distinct gene expression profiles and transcription factors (TF) motif enrichment. We identify genomic regions with significantly different chromatin accessibility in adult SPGs that are marked by histone modifications associated with enhancers and promoters. Some of the regions with increased accessibility correspond to transposable element subtypes enriched in multiple TFs motifs and close to differentially expressed genes. Our results underscore the dynamics of chromatin organization in developing germ cells and complement existing datasets on SPGs by providing maps of the regulatory genome at high resolution from the same cell populations at early postnatal, late postnatal and adult stages collected from single individuals.

developmental biology↗

bioRxiv2020

treeclimbR pinpoints the data-dependent resolution of hierarchical hypotheses

The arrangement of hypotheses in a hierarchical structure (e.g., phylogenies, cell types) appears in many research fields and indicates different resolutions at which data can be interpreted. A common goal is to find a representative resolution that gives high sensitivity to identify relevant entities (e.g., microbial taxa or cell subpopulations) that are related to a phenotypic outcome (e.g. disease status) while controlling false detections, therefore providing a more compact view of detected entities and summarizing characteristics shared among them. Current methods, either performing hypothesis tests at an arbitrary resolution or testing hypotheses at all possible resolutions leading to nested results, are suboptimal. Moreover, they are not flexible enough to work in situations where each entity has multiple features to consider and different resolutions might be required for different features. For example, in single cell RNA-seq data, an increasing focus is to find differential state genes that change expression within a cell subpopulation in response to an external stimulus. Such differential expression might occur at different resolutions (e.g., all cells or a small set of cells) for different genes. Our new algorithm treeclimbR is designed to fill this gap by exploiting a hierarchical tree of entities, proposing multiple candidates that capture the latent signal and pinpointing branches or leaves that contain features of interest, in a data-driven way. It outperforms currently available methods on synthetic data, and we highlight the approach on various applications, including microbiome and microRNA surveys as well as single cell cytometry and RNA-seq datasets. With the emergence of various multi-resolution genomic datasets, treeclimbR provides a thorough inspection on entities across resolutions and gives additional flexibility to uncover biological associations.

bioinformatics↗

bioRxiv2020

pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single-cell RNA-seq preprocessing tools

The massive growth of single-cell RNA-sequencing (scRNAseq) and the methods for its analysis still lack sufficient and up-to-date benchmarks that could guide analytical choices. Numerous benchmark studies already exist and cover most of scRNAseq processing and analytical methods but only a few give advice on a comprehensive pipeline. Moreover, current studies often focused on isolated steps of the process and do not address the impact of a tool on both the intermediate and the final steps of the analysis. Here, we present a flexible R framework for pipeline comparison with multi-level evaluation metrics. We apply it to the benchmark of scRNAseq analysis pipelines using simulated and real datasets with known cell identities, covering common methods of filtering, doublet detection, normalization, feature selection, denoising, dimensionality reduction and clustering. We evaluate the choice of these tools with multi-purpose metrics to assess their ability to reveal cell population structure and lead to efficient clustering. On the basis of our systematic evaluations of analysis pipelines, we make a number of practical recommendations about current analysis choices and for a comprehensive pipeline. The evaluation framework that we developed, pipeComp (https://github.com/plger/pipeComp), has been implemented so as to easily integrate any other step, tool, or evaluation metric allowing extensible benchmarks and easy applications to other fields of research in Bioinformatics, as we demonstrate through a study of the impact of removal of unwanted variation on differential expression analysis.

bioinformatics↗

bioRxiv2019

On the discovery of population-specific state transitions from multi-sample multi-condition single-cell RNA sequencing data

Single-cell RNA sequencing (scRNA-seq) has quickly become an empowering technology to profile the transcriptomes of individual cells on a large scale. Many early analyses of differential expression have aimed at identifying differences between subpopulations, and thus are focused on finding subpopulation markers either in a single sample or across multiple samples. More generally, such methods can compare expression levels in multiple sets of cells, thus leading to cross-condition analyses. However, given the emergence of replicated multi-condition scRNA-seq datasets, an area of increasing focus is making sample-level inferences, termed here as differential state analysis. For example, one could investigate the condition-specific responses of cell subpopulations measured from patients from each condition; however, it is not clear which statistical framework best handles this situation. In this work, we surveyed the methods available to perform cross-condition differential state analyses, including cell-level mixed models and methods based on aggregated "pseudobulk" data. We developed a flexible simulation platform that mimics both single and multi-sample scRNA-seq data and provide robust tools for multi-condition analysis within the muscat R package.

bioinformatics↗

bioRxiv2019

A novel mode of communication between blood and the germline for the inheritance of paternal experiences

In many species, environmental stimuli can affect the germline and contribute to phenotypic changes in the offspring, without altering the genetic code1-5. So far, little is known about which biological signals can link exposure to germ cells. Using a mouse model of postnatal trauma with transgenerational effects, we show that exposure alters lipid-based metabolites in blood of males and their non-exposed offspring. Comparable alterations are validated in serum and saliva of orphan children exposed to trauma. Peroxisome proliferator-activated receptor (PPAR) is identified as mediating the effects of metabolites alterations. Mimicking PPAR activation with a dual PPAR/{gamma} agonist in vivo induces changes in the sperm transcriptome similarly to trauma, and reproduces metabolic phenotypes in the offspring. Injecting serum collected from adult males exposed to postnatal trauma into controls recapitulates metabolic phenotypes in the offspring. These results suggest conserved effects of early life adversity on blood metabolites, and causally involve paternal blood factors and PPAR nuclear receptor in phenotype heritability.

molecular biology↗

bioRxiv2019

7q11.23 Syndromes Reveal BAZ1B as a Master Regulator of the Modern Human Face and Validate the Self-Domestication Hypothesis

Symmetrical 7q11.23 dosage alterations cause craniofacial and cognitive/behavioral phenotypes that provide a privileged entry point into the evolution of the modern human face and (pro-) sociality. We undertook a functional dissection of chromatin remodeler BAZ1B in neural crest stem cells (NCSCs) from a uniquely informative cohort of typical and atypical patients harboring 7q11.23 Copy Number Variants (CNVs). Our results reveal a key contribution of BAZ1B to NCSC in vitro induction and migration, coupled with a crucial involvement in neural crest (NC)-specific transcriptional circuits and distal regulation. By intersecting our experimental data with new paleogenetic analyses comparing modern and archaic humans, we uncover a modern-specific enrichment for regulatory changes both in BAZ1B and its experimentally defined downstream targets, thereby providing the first empirical validation of the self-domestication hypothesis and positioning BAZ1B as a master regulator of the modern human face.\n\nOne Sentence SummaryBAZ1B dosage shapes the modern human face.

evolutionary biology↗

bioRxiv2018

Alterations in sperm long RNA contribute to the epigenetic inheritance of the effects of postnatal trauma

Psychiatric diseases have a strong heritable component known to not be restricted to DNA sequence-based genetic inheritance alone but to also involve epigenetic factors in germ cells 1,2. Initial evidence suggested that sperm RNA is causally linked 2,3 to the transmission of symptoms induced by traumatic experiences. Here we show that alterations in long RNA in sperm contribute to the inheritance of specific trauma symptoms. Injection of long RNA fraction from sperm of males exposed to postnatal trauma recapitulates the effects on food intake, glucose response to insulin and risk-taking in adulthood whereas the small RNA fraction alters body weight and behavioral despair. Alterations in long RNA are maintained after fertilization, suggesting a direct link between sperm and embryo RNA.

developmental biology↗