Biology subjects

Davila-Velderrain, J.

Publications and source records attributed to Davila-Velderrain, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Dispersal behavior in a cold-water coral is orchestrated via stage and species-specific physiology.

Corals form important ecosystems that serve as habitat for numerous marine species. Being sessile, adult corals are exposed to changing environments without the means to relocate. Species dispersal is therefore restricted to the motile larval lifestage. How do microscopic larvae achieve reliable dispersal and conquest of novel habitats under time pressure and unpredictable environmental conditions? Here we show an unexpected diversity of behaviors in the cold-water coral Lophelia pertusa. Anatomical and behavioral changes of coral planula promote a change from neutral, passive buoyancy in the dispersal phase, to active swimming and search behavior during competency. As lipids are metabolized and sensory abilities develop, the coral larvae drastically change their motility patterns. Comparative analysis with a poorly dispersing, lecithotrophic anthozoan larvae reveals that developmentally timed sensory integration is conserved between species, but the behavioral modes and sensory responses are adapted to their particular ecology.

developmental biology↗

bioRxiv2026

In situ structures of the ciliary tip show the multi-step mechanism of axoneme assembly

Motile cilia are highly complex, ordered organelles which extend from the cell surface to generate fluid flow. During motile cilia assembly, components rapidly self-organize at the ciliary tip. Here, over two hundred different components bind microtubules to form an intricate, repeating structure called the axoneme. Despite in-depth structural characterization of axonemal complexes, we have limited understanding of how these structures are generated. Here, we directly visualize the steps of axonemal assembly in situ by performing cryo-electron tomography of Chlamydomonas reinhardtii cilia tips. Using subtomogram averaging and classification, we identified conserved microtubule luminal proteins that establish periodicity and show that controlled microtubule lattice perforation can facilitate incorporation of late-binding components. By uncovering unexpected assembly intermediates, we explain how structural integrity and the emergence of motility are coordinated within the axoneme. Overall, we demonstrate that self-assembly proceeds through regulated, sequential construction steps and provide a molecular framework for understanding axoneme biogenesis.

molecular biology↗

bioRxiv2025

NeuRoDev resolves lifelong temporal and cellular variation in human cortical gene expression

Understanding how the human brain develops and functions requires direct analysis of human cells. Single-cell atlases open unprecedented opportunities to survey cell physiological molecular states as the brain develops. However, technical challenges limit their potential. We present NeuRoDev, a computational resource with highly curated transcriptomic data and novel analytical tools to investigate neuronal and glial development in the human cortex. NeuRoDev compresses [~]1M single-cell transcriptomes into integrative summary networks of reproducible cell clusters that capture temporal and cellular variation across all stages of human brain development. It provides a reference framework to directly interrogate cellular maturation dynamics, contextualize gene function, and interpret experimental organoid models. We use NeuRoDev to investigate developmental variation in cell physiology, reconstruct genesis and maturation dynamics in neuronal and glial cells, and interpret time-series data from organoid models. NeuRoDev is provided as a freely available software package and as web applications for interactive data analysis.

neuroscience↗

bioRxiv2025

WWOX deficiency uncovers a cell-autonomous mechanism impairing myelin repair

Remyelination is essential for neuronal function and plasticity, and its failure contributes to multiple sclerosis (MS) and other neurodegenerative disorders. Yet, the molecular programs governing oligodendrocyte precursor cell (OPC) differentiation and remyelination remain incompletely defined. Here, we identify the WW domain-containing oxidoreductase (WWOX) as a critical cell-autonomous regulator of oligodendrocyte differentiation and myelin repair. Reanalysis of single-nucleus RNA sequencing from MS lesions revealed WWOX as one of the most significantly dysregulated oligodendroglial genes. Conditional deletion of Wwox in oligodendroglia impaired OPC differentiation, favouring aberrant proliferation and blocking myelin regeneration after cuprizone-induced demyelination. Single-nucleus transcriptomics confirmed profound transcriptional reprogramming in WWOX-deficient oligodendroglia during remyelination, with enrichment of WNT and TGF{beta} signalling and cell cycle programs. Mechanistically, WWOX physically interacts with the master transcription factor SOX10 via its WW1 domain, stabilising SOX10 protein and sustaining its downstream myelin gene network. Loss of WWOX reduced SOX10 stability and activity, providing a direct mechanistic link to defective OPC differentiation. Together, our findings uncover WWOX as an essential orchestrator of remyelination and position the WWOX-SOX10 axis as a promising therapeutic target for enhancing myelin repair in MS and related demyelinating disorders.

neuroscience↗

bioRxiv2025

Developmentally timed sensory integration enables efficient larval dispersal

Animals integrate internal and external sensory information to adjust movement gait according to the physical constraints imposed by body-environment interactions. Efficient locomotion is especially important in small organisms where the motile phase is ontogenetically restricted. Motile larvae of otherwise sessile cnidarians must disperse and identify a suitable habitat in a restricted timeframe. Here we show that dispersal in Nematostella vectensis larvae is accomplished by a constant ciliary sensory-motor system that produces stimulus-induced movement. In contrast, neuro-muscular and sensory systems gradually increase in complexity during development, enabling movement-associated gait control through reafferent matching of external and internal information. Together with ciliary propulsion, the developmentally timed appearance of sensory and neuronal structures endows the animal with the ability to integrate information to shape swimming behavior and achieve dispersal in a timely manner, appropriate to the physical challenges of its specific ecological niche.

neuroscience↗

bioRxiv2025

Gene specificity landscapes for comparative transcriptomic analysis across tissues, cell types, and species

Gene expression specificity is a biological parameter relevant for understanding the molecular basis of evolutionary constraints and tissue-selective pathogenesis. Many efforts have tried to quantify the degree of tissue specificity of individual genes. The growing availability of single-cell transcriptomic data greatly expands the context in which expression specificity can be assessed. We present a computational strategy to globally analyse and compare the specificity of genes and groups of related genes across different contexts. By representing expression profiles in terms of expression level-breadth (L-B) relationships, we are able to quantify and construct 2D landscapes that provide a globally consistent coordinate system to map specificity patterns. We characterize these landscapes at different levels of resolution and across species to demonstrate simple strategies for comparative transcriptomics. We use this approach to investigate the tissue, cell type, and neuronal specificity of human genes and generate reference specificity landscapes. Finally, by comparing the specificity of brain cell subtypes across 4 primate species we find that their degree of conservation mirrors evolutionary divergence times. Our analysis framework and data resources are available in the R package GeneSLand.

bioinformatics↗

bioRxiv2024

WWOX deficiency impairs neurogenesis and neuronal function in human organoids

WOREE and SCAR12 syndromes are rare neurodevelopmental disorders caused by WWOX mutations, severely impairing brain development. The pleiotropic nature of WWOX complicates identifying specific mechanisms. Using neural organoids and single-cell transcriptomics, we identified radial glial cells (RGs) as preferentially affected, with disrupted cell cycle dynamics leading to an accumulation of cells in the G2/M and S phases, overexpression of the proto-oncogene MYC, and concomitant reduction in neuronal generation. Patient-derived organoids exhibited milder phenotypes compared to knockout organoids, showing functional neuronal impairments like hyperexcitability and delayed differentiation rather than RG dysfunction. Remarkably, gene therapy restored neuronal function, normalizing hyperexcitability and promoting maturation, without disturbing RG populations. We propose a model in which WWOX mutations impair neurogenesis via RG through cell-type specific dysregulation of the MYC and Wnt signaling pathways. These insights highlight potential therapeutic strategies for WWOX-related disorders and open avenues for interventions targeting these key molecular pathways. TeaserWWOX mutations disrupt radial glial function and neurogenesis via MYC dysregulation, with gene therapy offering targeted restoration.

neuroscience↗

bioRxiv2023

Dissecting the neurotropism and neurovirulence of MPXV using human stem cell-based models

Mpox is a zoonotic illness of international concern that can lead to severe disease including neurological sequelae. However, the neurotropism of monkeypox virus (MPXV) and the mechanisms regulating cell-intrinsic antiviral immunity within the central nervous system (CNS) remain poorly understood. Here, we investigated the neurotropism of MPXV using astrocytes, cortical neurons, and microglia derived from human pluripotent stem cells (hPSCs) and ex vivo human brain tissue to demonstrate that MPXV infects and replicates more efficiently in astrocytes and microglia compared to cortical neurons. Upon MPXV exposure, glial cells, in contrast to cortical neurons, inhibit type I IFN antiviral programs potentially conferring differential susceptibility to MPXV. Furthermore, we demonstrate that treatment using either IFN-beta or tecovirimat inhibits MPXV infection. Together, our results suggest that MPXV has a broad tropism within the CNS and that differential type I IFN signaling underpins cell type-specific susceptibility to MPXV infection.

microbiology↗

bioRxiv2023

Uncovering the role that specific genes play in reachability properties of complex biological Gene Regulatory Networks (GRNs): The Arabidopsis thaliana flower development case

The dynamic processes of multicellular organism development are regulated and coordinated by Gene Regulatory Networks (GRNs). Therefore, a sustained effort to understand the dynamical properties of these modularly structured networks has shown the great utility of experimentally grounded and dynamically characterized discrete Boolean models, as an ideal formalism based on dynamical systems modeling tool for its qualitative description. Up to now, several low-dimensional Boolean GRNs have been proposed to recover gene activation configurations observed for specific cell types, and they have been validated via robustness and mutant analyses. Nevertheless, systematic studies that elucidate the role of individual genes implicated on transitions between given attractors in the context of morphogenetic patterns of development, are still very scarce. Such sort of studies is in fact quite relevant because genes belonging to a given GRN do not work in isolation. Indeed, they could interact with others GRNs and/or with micro-environmental cues. Consequently, the structural specificities of the involved genes at the network level should be assessed in order to uncover the functional nature of the larger network involved. This is particularly meaningful when considering the role played by specific genes on transient dynamics related to cell fate specification. Following this idea, we propose here a computer-based analytical procedure intended to elucidate the role that specific genes play on the reachability properties of GRNs. As a structural property of a given dynamical network, reachability characterizes the attainability of specified attractors from given initial attractors as a consequence of the action of specific driving exogenous stimuli. Our proposal is based on algebraic systems approaches built around the Semi-Tensor Product (STP). We illustrate here our proposed procedure through the exploration of the reachability properties of the well-known Floral Organ Specification GRN of Arabidopsis thaliana (FOS-GRN), that recovers ten fixed-point attractors. Our findings suggest that there exist 79 inducible transitions among all possible pairs of attractors, with a suitable external Boolean control input over different well-characterized nodes of the network. Additionally, we found that such potentiality of these genes to produce attractor transitions is maintained by the continuous approximation model of the FOS-GRN, recovering not only qualitative but also useful quantitative information. Finally, we discussed the biological significance of our results and, even if we do not establish the specific molecular nature of the characterized exogenous control input, we concluded that reachability analysis can give us some important insights on the network level role that individual genes acquire by their collaboration with the GRN, becoming then targets in cell-fate decisions during development. Author summaryBringing to light the specific role that given genes play in gene regulatory networks is of particular importance, especially when it is necessary to quantify the influence of the environment on their dynamics. However, this becomes difficult by the fact that the genes in the network interact both nonlinearly and in the presence of feedback-based interactions. This requires then the development of methods of analysis that take into account such complex interdependencies. In this regard, Control Theory offers tools that allow characterizing the changes in the transition patterns between stable configurations (that is, cellular phenotypes) of the networks as a result of the presence of exogenous stimuli. In this work we propose a method based on the algebraic representation of small size gene regulatory networks, we first described in discrete Boolean terms, focused on delimiting the influence that specific nodes of the network play in the enhancement of transitions that define trajectories in the space of stable configurations of the state of expression of the genes involved. The proposed method uses the key control-oriented concept of reachability and is illustrated by the characterization of some induced morphogenetic trajectories that explain the development stages of Arabidopsis thaliana flower organs. Our proposal allows us to confirm that, in biological terms, the reachability analysis offers powerful tools to deepen the understanding of the interplay between the structure of specific gene regulatory networks involving both their own constitutive elements and including the networks with which they interact. This contributes to the understanding of biological development, which opens an access route to the exploration of the basic principles that associate the structure of gene regulatory processes not only with cell reprogramming and cell dedifferentiation, but also with dynamic processes underlying phenotypic plasticity and its evolutionary consequences. This is because the explanation of phenotypic change responses to environmental variability requires specifying how the constraints that govern developmental trajectories, potentially elucidated through reachability analysis, modulate the balance between phenotypic robustness and evolvability.

systems biology↗

bioRxiv2021

Neurons burdened by DNA double strand breaks incite microglia activation through antiviral-like signaling in neurodegeneration.

DNA double strand breaks (DSBs) are linked to aging, neurodegeneration, and senescence1,2. However, the role played by neurons burdened with DSBs in disease-associated neuroinflammation is not well understood. Here, we isolate neurons harboring DSBs from the CK-p25 mouse model of neurodegeneration through fluorescence-activated nuclei sorting (FANS), and characterize their transcriptomes using single-nucleus, bulk, and spatial sequencing techniques. We find that neurons harboring DSBs enter a late-stage DNA damage response marked by the activation of senescent and antiviral-like immune pathways. We identify the NFkB transcription factor as a master regulator of immune gene expression in DSB-bearing neurons, and find that the expression of cytokines like Cxcl10 and Ccl2 develop in DSB-bearing neurons before glial cell types. Alzheimers Disease pathology is significantly associated with immune activation in excitatory neurons, and direct purification of DSB-bearing neurons from Alzheimers Disease brain tissue further validates immune gene upregulation. Spatial transcriptomics reveal that regions of brain tissue dense with DSB-bearing neurons also harbor signatures of inflammatory microglia, which is ameliorated by NFkB knock down in neurons. Inhibition of NFkB or depletion of Ccl2 and Cxcl10 in DSB-bearing neurons also reduces microglial activation in organotypic brain slice culture. In conclusion, we find that in the context of age-associated neurodegenerative disease, DSBs activate immune pathways in neurons, which in turn adopt a senescence associated secretory phenotype to elicit microglia activation. These findings highlight a novel role for neurons in the mechanism of age-associated neuroinflammation. SummaryIt is unclear how age-associated DNA double strand break (DSB) accumulation in neurons influences the progression of cellular senescence and neurodegenerative disease. Here, we leverage mouse models of neurodegeneration, single-nucleus, bulk, and spatial transcriptomics from Alzheimers disease patients, mouse models, and primary neuron cultures to dissect the immune signaling pathways initiated by DSB-bearing neurons that trigger neuroinflammation.

neuroscience↗

bioRxiv2021

Single-cell anatomical analysis of human hippocampus and entorhinal cortex uncovers early-stage molecular pathology in Alzheimer's disease

The human hippocampal formation plays a central role in Alzheimers disease (AD) progression, cognitive traits, and the onset of dementia; yet its molecular states in AD remain uncharacterized. Here, we report a comprehensive single-cell transcriptomic dissection of the human hippocampus and entorhinal cortex across 489,558 cells from 65 individuals with varying stages of AD pathology. We transcriptionally characterize major brain cell types and neuronal classes, including 17 glutamatergic and 8 GABAergic neuron subpopulations. Combining evidence from human and mouse tissue-microdissection, neuronal cell isolation and spatial transcriptomics, we show that single-cell expression patterns capture fine-resolution neuronal anatomical topography. By stratifying subjects into early and late pathology groups, we uncover stage-dependent and cell-type specific transcriptional modules altered during AD progression. These include early-stage cell-type specific dysregulation of cellular and cholesterol metabolism, late-stage neuron-glia alterations in neurotransmission, and late-stage signatures of cellular stress, apoptosis, and DNA damage broadly shared across cell types. Late-stage signatures show signs of convergence in hippocampal and cortical cells, while early changes diverge; highlighting the relevance of characterizing molecular pathology across brain regions and AD progression. Finally, we characterize neuron subregion-specific responses to AD pathology and show that CA1 pyramidal neurons are the most transcriptionally altered while CA3 and dentate gyrus granule neurons the least. Our study provides a valuable resource to extend cell type-specific studies of AD to clinically relevant brain regions affected early by pathology in disease progression.

neuroscience↗

bioRxiv2021

Single-cell deconvolution of 3,000 post-mortem brain samples for eQTL and GWAS dissection in mental disorders

Thousands of genetic variants acting in multiple cell types underlie complex disorders, yet most gene expression studies profile only bulk tissues, making it hard to resolve where genetic and non-genetic contributors act. This is particularly important for psychiatric and neurodegenerative disorders that impact multiple brain cell types with highly-distinct gene expression patterns and proportions. To address this challenge, we develop a new framework, SPLITR, that integrates single-nucleus and bulk RNA-seq data, enabling phenotype-aware deconvolution and correcting for systematic discrepancies between bulk and single-cell data. We deconvolved 3,387 post-mortem brain samples across 1,127 individuals and in multiple brain regions. We find that cell proportion varies across brain regions, individuals, disease status, and genotype, including genetic variants in TMEM106B that impact inhibitory neuron fraction and 4,757 cell-type-specific eQTLs. Our results demonstrate the power of jointly analyzing bulk and single-cell RNA-seq to provide insights into cell-type-specific mechanisms for complex brain disorders.

genomics↗

bioRxiv2019

In vivo and in vitro human gene essentiality estimations capture contrasting functional constraints

Gene essentiality estimation is a popular empirical approach to link genotypes to phenotypes. In humans, essentiality is estimated based on loss-of-function (LoF) mutation intolerance, either from population exome sequencing (in vivo) data or CRISPR-based in vitro perturbation experiments. Both approaches identify genes presumed to have strong detrimental consequences on the organism upon mutation. Are these genes functionally distinct and constrained by having key roles? Do in vivo and in vitro estimations equally recover these constraints? To address these questions, here we integrated disparate genome-scale datasets and compared structural, functional, and evolutionary features of essential genes versus genes with extremely high mutational tolerance and proteome expectation. We found that essentiality estimates do recover functional constraints. However, the organismal or cellular context of estimation leads to functionally contrasting properties underlying the constraint. Our results suggest that depletion of LoF mutations in human populations effectively captures developmental, organismal-level functional constraints not experimentally accessible through CRISPR-based screens. Finally, we identify a new set of genes (OrgEssential), which are intolerant of LoF mutation in vivo but highly tolerant in vitro. These genes drive observed functional constraint differences and have an unexpected preference for nervous system expression.

systems biology↗

bioRxiv2019

Multi-resolution single-cell state characterization via joint archetypal/network analysis

Dissecting the cellular heterogeneity embedded in single-cell transcriptomic data is challenging. Although a large number of methods and approaches exist, robustly identifying underlying cell states and their associations is still a major challenge; given the nonexclusive and dynamic influence of multiple unknown sources of variability, the existence of state continuum at the time-scale of observation, and the inevitable snapshot nature of experiments. As a way to address some of these challenges, here we introduce ACTIONet, a comprehensive framework that combines archetypal analysis and network theory to provide a ready-to-use analytical approach for multiresolution single-cell state characterization. ACTIONet uses multilevel matrix decomposition and network reconstruction to simultaneously learn cell state patterns, quantify single-cell states, and reconstruct a reproducible structural representation of the transcriptional state space that is geometrically mapped to a color space. A color-enhanced quantitative view of cell states enables novel visualization, prediction, and annotation approaches. Using data from multiple tissues, organisms, and developmental conditions, we illustrate how ACTIONet facilitates the reconstruction and exploration of single-cell state landscapes.

genomics↗

bioRxiv2019

Single-cell interactomes of the human brain reveal cell-type specific convergence of brain disorders

The reference human interactome has been instrumental in the systems-level study of the molecular inner workings of the cell, providing a framework to analyze the network context of disease associated gene perturbations. However, reference organismal interactomes do not capture the tissue- and cell type-specific context in which proteins and modules preferentially act. Emerging single-cell profiling technologies, which survey the transcriptional cell-state distribution of complex tissues, could be used to infer the single-cell context of gene interactions. Here we introduce SCINET (Single-Cell Imputation and NETwork construction), a computational framework that reconstructs an ensemble of cell type-specific interactomes by integrating a global, context-independent reference interactome with a single-cell gene expression profile. SCINET addresses technical challenges of single-cell data by robustly imputing, transforming, and normalizing the initially noisy and sparse expression data. Subsequently, cell-level gene interaction probabilities and group-level gene interaction strengths are computed, resulting in cell type specific interactomes. We use SCINET to analyze the human cortex, reconstructing interactomes for the major cell types of the adult human brain. We identify network neighborhoods composed of topologically-specific genes that are central for cell-type influence but not for global interactome connectivity. We use the reconstructed interactomes to analyze the specificity and modularity of perturbations associated with neurodegenerative, neuropsychiatric, and neoplastic brain disorders; finding high variability across diseases, yet overall consistency in patterns of cell-type convergence for diseases of the same group. We infer for each disorder group disease gene networks with preferential cell-type specific activity that can aid the design and interpretation of cell-type resolution experiments. Finally, focusing on the pleiotropy of schizophrenia and bipolar disorder, we show how cell type specific interactomes enable the identification of disease genes with preferential influence on neuronal, glial, or glial-neuronal cells. The SCINET framework is applicable to any organism, cell-type/tissue, and reference network; it is freely available at https://github.com/shmohammadi86/SCINET.

systems biology↗

bioRxiv2018

Genome-wide active enhancer identification using cell type-specific signatures of epigenomic activity

Recently enhancers have emerged as key players regulating crucial mechanisms such as cell fate determination and establishment of spatiotemporal patterns of gene expression during development. Due to their functional and structural complexity, an accurate in silico identification of active enhancers under specific conditions remain challenging. We present a novel machine learning based method that derives epigenomic patterns exclusively from experimentally characterized active enhancers contrasted with a weighted set of non-enhancer genomic regions. We demonstrate better predictive performance over previous methods, as well as wide generalizability by identifying and annotating active enhancers genome-wide across different tissues/cell types in human and mouse.

bioinformatics↗

bioRxiv2018

DECODE-ing sparsity patterns in single-cell RNA-seq

An inherent challenge in interpreting single-cell transcriptomic data is the high frequency of zero values. This phenomenon has been attributed to both biological and technical sources, although the extent of the contribution of each remains unclear. Here, we show that the underlying gene presence/absence sparsity patterns are by themselves highly informative. We develop an algorithm, called DECODE, to assess the extent of joint presence/absence of genes across different cells, and to infer a gene dependency network. We show that this network captures biologically-meaningful pathways, cell-type specific modules, and connectivity patterns characteristic of complex networks. We develop a model that uses this network to discriminate biological vs. technical zeros, by exploiting each genes local network neighborhood. For inferred non-biological zeros, we build a predictive model that imputes the missing value of each gene based on activity patterns of its most informative neighbors. We show that our framework accurately infers gene-gene functional dependencies, pinpoints technical zeros, and predicts biologically-meaningful missing values in three diverse datasets.

bioinformatics↗

bioRxiv2017

Integrative construction of regulatory region networks in 127 human reference epigenomes by matrix factorization

Despite large experimental and computational efforts aiming to dissect the mechanisms underlying disease risk, mapping cis-regulatory elements to target genes remains a challenge. Here, we introduce a matrix factorization framework to integrate physical and functional interaction data of genomic segments. The framework was used to predict a regulatory network of chromatin interaction edges linking more than 20,000 promoters and 1.8 million enhancers across 127 human reference epigenomes, including edges that are present in any of the input datasets. Our network integrates functional evidence of correlated activity patterns from epigenomic data and physical evidence of chromatin interactions. An important contribution of this work is the representation of heterogeneous data with different qualities as networks. We show that the unbiased integration of independent data sources suggestive of regulatory interactions produces meaningful associations supported by existing functional and physical evidence, correlating with expected independent biological features.

epidemiology↗