Biology subjects

Orvis, J.

Publications and source records attributed to Orvis, J..

10 recordsLinked to original sources

bioRxiv2026

SENgEAR: an interactive visualization platform for comparative analysis of senescence signatures and cellular communication

Single-cell and spatial transcriptomic datasets provide tremendous potential to identify the cellular states and communication networks associated with senescence. Annotating senescent cells in these datasets is hindered by the lack of universal markers for senescent cells and their context-dependent variability. To overcome this, several groups have developed gene signatures to annotate cells with distinct senotypes. However, comparing these signatures and their biological contexts to determine the specificity of senescence signatures remains complicated by the separate data platforms for signatures and datasets. We present SENgEAR, a no-code web platform for senescent cell annotation, visualization of cell-cell communication networks, and comparison of senescence signatures across studies, tissues, species, and data modalities. SENgEAR provides a unified framework to explore contextual signature specificity, cellular communication pathways, and senotype heterogeneity. We demonstrate the use of SENgEAR for applications spanning aging, fibrosis, and wound healing and its ability to interrelate these states.

bioinformatics↗

bioRxiv2026

A comparative single-cell transcriptomic atlas for diverse populations of vertebrate hair cells

Mechanosensitive hair cells vary widely in morphology and regenerative capacity across vertebrate organs and species. To investigate their underlying transcriptomic diversity, we integrated human, mouse, chicken, and zebrafish single-cell and single-nucleus RNA sequencing datasets and assembled a cross-species atlas of hair cells spanning organs, developmental stages, and species. Analysis of 29 hair cell populations, encompassing the major cochlear, vestibular, and lateral-line hair cell types, identified approximately 5,000 genes enriched in at least one hair cell population compared to supporting cells from the same organs. Unsupervised clustering of these hair cell-enriched (HCE) genes defined species-, organ-, and hair cell state-associated cohorts as well as broadly conserved hair cell-enriched programs. Using an AUC-based scoring framework, we further defined 884 pan hair cell-enriched (pan-HCE) genes with elevated expression in most developing and/or mature hair cell populations, including genes implicated in deafness, mechanotransduction, and synaptic transmission, along with genes not previously linked to hair cell function. Independent analysis of developing hair cells using the same metrics stratified pan-HCE genes based on when they are first enriched and identified an additional 97 genes that are transiently enriched. We used the pan- and developing HCE gene sets to assess transcriptional similarity between baseline hair cell states and hair cells produced during avian hair cell regeneration and in mouse cochlear organoids, as well as hair cell-like populations produced by fibroblast reprogramming. HCE gene sets with different developmental dynamics identified young vs. more mature hair cells when projected onto independent single-cell RNA sequencing datasets from developing zebrafish, mouse, and human. We provide a web-based resource of all HCE metrics and expression profiles, enabling future exploration of vertebrate hair cell gene expression across organs, species, and experimental contexts.

neuroscience↗

bioRxiv2026

Distinct fibroblast and perivascular senotypes define spatial niches that regulate fibrosis

Fibrotic conditions contribute to significant global morbidity and mortality. Yet the underlying processes that orchestrate fibrosis remain poorly understood due to the cellular and spatial complexity of the stromal, immune, and vascular compartments that regulate fibrotic disease progression. Senescent cells (SnCs) have been implicated in fibrosis, but their roles are unclear, as evidence indicates that they serve both pathogenic and reparative functions. Here, we show that fibrosis-associated SnCs contain functionally divergent senotypes that are organized into distinct spatial niches. Using integrated single-cell and spatial transcriptomics analyses and hierarchical factorization in a murine fibrosis model, we identify fibroblast and perivascular SnC subpopulations that upregulate diverse programs related to extracellular matrix (ECM) production, immune signaling, and vascular remodeling. Fibroblast senotypes localize to discrete microenvironments with distinct tissue architectures, including niches associated with fibrotic signaling, immune activity, and cartilage development. Perivascular SnCs occupy interfaces between fibrotic signaling and immune-active niches and upregulate vascular and fibrotic remodeling pathways. Depletion of pericyte-lineage SnCs increases vascular maturation and fibrotic ECM deposition, providing mechanistic validation of the beneficial role these SnCs play in vascular remodeling and fibrosis modulation. In addition, using a new web-based infrastructure to query our senotype gene signatures in public datasets, we demonstrate that these senotypes are conserved across different murine and human fibrotic conditions. These findings establish senescence as a spatially organized regulator of fibrosis and identify perivascular senescence as a link between vascular remodeling and fibrotic outcomes.

bioengineering↗

bioRxiv2024

in silico transcriptome dissection of neocortical excitatory neurogenesis via joint matrix decomposition and transfer learning

Vast quantities of multi-omic data have been produced to characterize the development and diversity of cell types in the cerebral cortex of humans and other mammals. To more fully harness the collective discovery potential of these data, we have assembled gene-level transcriptomic data from 188 published studies of neocortical development, including the transcriptomes of [~]30 million single-cells, extensive spatial transcriptomic experiments and RNA sequencing of sorted cells and bulk tissues: nemoanalytics.org/landing/neocortex. Applying joint matrix decomposition (SJD) to mouse, macaque and human data in this collection, we defined transcriptome dynamics that are conserved across mammalian neurogenesis and which elucidate the evolution of outer, or basal, radial glial cells. Decomposition of adult human neocortical data identified layer-specific signatures in mature neurons and, in combination with transfer learning methods in NeMO Analytics, enabled the charting of their early developmental emergence and protracted maturation across years of postnatal life. Interrogation of data from cerebral organoids demonstrated that while broad molecular elements of in vivo development are recapitulated in vitro, many layer-specific transcriptomic programs in neuronal maturation are absent. We invite computational biologists and cell biologists without coding expertise to use NeMO Analytics in their research and to fuel it with emerging data (carlocolantuoni.org).

neuroscience↗

bioRxiv2022

The Neuroscience Multi-Omic Archive: A BRAIN Initiative resource for single-cell transcriptomic and epigenomic data from the mammalian brain

Scalable technologies to sequence the transcriptomes and epigenomes of single cells are transforming our understanding of cell types and cell states. The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative Cell Census Network (BICCN) is applying these technologies at unprecedented scale to map the cell types in the mammalian brain. In an effort to increase data FAIRness (Findable, Accessible, Interoperable, Reusable), the NIH has established repositories to make data generated by the BICCN and related BRAIN Initiative projects accessible to the broader research community. Here, we describe the Neuroscience Multi-Omic Archive (NeMO Archive; nemoarchive.org), which serves as the primary repository for genomics data from the BRAIN Initiative. Working closely with other BRAIN Initiative researchers, we have organized these data into a continually expanding, curated repository, which contains transcriptomic and epigenomic data from over 50 million brain cells, including single-cell genomic data from all of the major regions of the adult and prenatal human and mouse brains, as well as substantial single-cell genomic data from non-human primates. We make available several tools for accessing these data, including a searchable web portal, a cloud-computing interface for large-scale data processing (implemented on Terra, terra.bio), and a visualization and analysis platform, NeMO Analytics (nemoanalytics.org). KEY POINTSO_LIThe Neuroscience Multi-Omic Archive serves as the genomics data repository for the BRAIN Initiative. C_LIO_LIGenomic data from >50 million cells span all the major regions of the brains of humans and mice. C_LIO_LIWe provide a searchable web portal, a cloud-computing interface, and a data visualization platform. C_LI

genomics↗

bioRxiv2020

gEAR: gene Expression Analysis Resource portal for community-driven, multi-omic data exploration

The gEAR portal (gene Expression Analysis Resource, umgear.org) is an open access community-driven tool for multi-omic and multi-species data visualization, analysis and sharing. The gEAR supports visualization of multiple RNA-seq data types (bulk, sorted, single cell/nucleus) and epigenomics data, from multiple species, time points and tissues in a single-page, user-friendly browsable format. An integrated scRNA-seq workbench provides access to raw data of scRNA-seq datasets for de novo analysis, as well as marker-gene and cluster comparisons of pre-assigned clusters. Users can upload, view, analyze and privately share their own data in the context of previously published datasets. Short, permanent URLs can be generated for dissemination of individual or collections of datasets in published manuscripts. While the gEAR is currently curated for auditory research with over 90 high-value datasets organized in thematic profiles, the gEAR also supports the BRAIN initiative (via nemoanalytics.org) and is easily adaptable for other research domains.

bioinformatics↗

bioRxiv2020

Capture-based enrichment of Theileria parva DNA enables full genome assembly of first buffalo- derived strain and reveals exceptional intra-specific genetic diversity

Theileria parva is an economically important, intracellular, tick-transmitted parasite of cattle. A live vaccine against the parasite is effective against challenge from cattle-transmissible T. parva but not against genotypes originating from the African Cape buffalo, a major wildlife reservoir, prompting the need to characterize genome-wide variation within and between cattle- and buffalo-associated T. parva populations. Here, we describe a capture-based target enrichment approach that enables, for the first time, de novo assembly of nearly complete T. parva genomes derived from infected host cell lines. This approach has exceptionally high specificity and sensitivity and is successful for both cattle- and buffalo-derived T. parva parasites. De novo genome assemblies generated for cattle genotypes differ from the reference by [~]54K single nucleotide polymorphisms (SNPs) throughout the 8.31 Mb genome, an average of 6.5 SNPs/kb. We report the first buffalo-derived T. parva genome, which is larger than the genome from the reference, cattle-derived, Muguga strain. The average non-synonymous nucleotide diversity ({pi}N) per gene, between buffalo-derived T. parva and the Muguga strain, was 1.3%. This remarkably high level of genetic divergence is supported by an average FST, genome-wide, of 0.44, reflecting a degree of genetic differentiation between cattle- and buffalo-derived T. parva parasites more commonly seen between, rather than within, species, with clear implications for vaccine development. The DNA capture approach used provides clear advantages over alternative T. parva DNA enrichment methods used previously and enables in-depth comparative genomics in this apicomplexan parasite.

genomics↗

bioRxiv2020

Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse

The primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup of this region, whose similarity mirrors evolutionary distance and is consistent between the transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal types allowed the generation of a cross-species consensus cell type classification and inference of conserved cell type properties across species. Despite overall conservation, many species specializations were apparent, including differences in cell type proportions, gene expression, DNA methylation, and chromatin state. Few cell type marker genes were conserved across species, providing a short list of candidate genes and regulatory mechanisms responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human primate and human and characterization of their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

neuroscience↗

bioRxiv2019

Re-annotation of the Theileria parva genome refines 53% of the proteome and uncovers essential components of N-glycosylation, a conserved pathway in many organisms

BackgroundThe apicomplexan parasite Theileria parva causes a livestock disease called East coast fever (ECF), with millions of animals are at risk in sub-Saharan East and Southern Africa, the geographic distribution of T. parva. Over a million bovines die each year of ECF, with a tremendous economic burden to pastoralists in endemic countries. Comprehensive, accurate parasite genome annotation can facilitate the discovery of novel chemotherapeutic targets for disease treatment, as well as elucidate the biology of the parasite. However, genome annotation remains a significant challenge because of limitations in the quality and quantity of the data being used to inform the location and function of protein-coding genes and, when RNA data are used, the underlying biological complexity of the processes involved in gene expression. Here, we apply our recently published RNAseq dataset derived from the schizont life-cycle stage of T. parva to update structural and functional gene annotations across the entire nuclear genome. ResultsThe re-annotation effort lead to evidence-supported updates in over half of all protein-coding sequence (CDS) predictions, including exon changes, gene merges and gene splitting, an increase in average CDS length of approximately 50 base pairs, and the identification of 128 new genes. Among the new genes identified were those involved in N-glycosylation, a process previously thought not to exist in this organism and a potentially new chemotherapeutic target pathway for treating ECF. Alternatively-spliced genes were identified, and antisense and multi-gene family transcription were extensively characterized. ConclusionsThe process of re-annotation led to novel insights into the organization and expression profiles of protein-coding sequences in this parasite, and uncovered a minimal N-glycosylation pathway that changes our current understanding of the evolution of this post-translation modification in apicomplexan parasites.

genomics↗

bioRxiv2019

Neuron subtype-specific effector gene expression in the Motor Ganglion of Ciona

The central nervous system of the Ciona larva contains only 177 neurons. The precise regulation of neuron subtype-specific morphogenesis and differentiation observed in during the formation of this minimal connectome offers a unique opportunity to dissect gene regulatory networks underlying chordate neurodevelopment. Here we compare the transcriptomes of two very distinct neuron types in the hindbrain/spinal cord homolog of Ciona, the Motor Ganglion (MG): the Descending decussating neuron (ddN, proposed homolog of Mauthner Cells in vertebrates) and the MG Interneuron 2 (MGIN2). Both types are invariantly represented by a single bilaterally symmetric left/right pair of cells in every larva. Supernumerary ddNs and MGIN2s were generated in synchronized embryos and isolated by fluorescence-activated cell sorting for transcriptome profiling. Differential gene expression analysis revealed ddN- and MGIN2-specific enrichment of a wide range of genes, including many encoding potential \"effectors\" of subtype-specific morphological and functional traits. More specifically, we identified the upregulation of centrosome-associated, microtubule-stabilizing/bundling proteins and extracellular matrix proteins and axon guidance cues as part of a single intrinsic regulatory program that might underlie the unique polarization of the ddNs, the only descending MG neurons that cross the midline.

developmental biology↗