Biology subjects

Hertzano, R.

Publications and source records attributed to Hertzano, R..

11 recordsLinked to original sources

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

Epithelial-Mesenchymal Wnt Crosstalk Directs Planar Cell Polarity in the Developing Cochlea

Cochlear hair cells are crucial for sound transduction and are precisely oriented by planar cell polarity (PCP). Wnt proteins direct PCP in vertebrates, but their roles in regulating cochlear PCP remain unclear. Here, we inhibited Wnt secretion by ablating Wntless in the cochlear epithelium and found shortened cochlea, mild hair cell misorientation and mislocalization of PCP proteins, Fzd6 and Dvl2, representing defects less severe than classic PCP mutants. Computational cell-communication analysis predicted that candidate Wnts from the cochlear epithelium (Wnt5a, Wnt7a, Wnt7b) and surrounding periotic mesenchyme (Wnt5a) act on developing hair cells. Deletion of Wnt5a, Wnt7a, and Wnt7b additively shortened the cochlea without causing hair cell misorientation or mislocalization of PCP proteins. Moreover, deletion of Wnt5a alone in the periotic mesenchyme failed to cause PCP defects. However, ablating both epithelial and mesenchymal Wnts caused a severely shortened cochlea with apically malrotated hair cells devoid of polarized core PCP proteins. Thus, Wnts serve as global instructive cues directing cochlear outgrowth and hair cell polarization, with remarkable redundancy of distinct Wnts across epithelial and mesenchymal compartments to ensure a fail-safe developmental program.

developmental biology↗

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 BRAIN Initiative Cell Census Data Ecosystem: A User's Guide

Characterizing cellular diversity at different levels of biological organization across data modalities is a prerequisite to understanding the function of cell types in the brain. Classification of neurons is also required to manipulate cell types in controlled ways, and to understand their variation and vulnerability in brain disorders. The BRAIN Initiative Cell Census Network (BICCN) is an integrated network of data generating centers, data archives and data standards developers, with the goal of systematic multimodal brain cell type profiling and characterization. Emphasis of the BICCN is on the whole mouse brain and demonstration of prototypes for human and non-human primate (NHP) brains. Here, we provide a guide to the cellular and spatial approaches employed, and to accessing and using the BICCN data and its extensive resources, including the BRAIN Cell Data Center (BCDC) which serves to manage and integrate data across the ecosystem. We illustrate the power of the BICCN data ecosystem through vignettes highlighting several BICCN analysis and visualization tools. Finally, we present emerging standards that have been developed or adopted by the BICCN toward FAIR (Wilkinson et al. 2016a) neuroscience. The combined BICCN ecosystem provides a comprehensive resource for the exploration and analysis of cell types in the brain.

bioinformatics↗

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

Spectrum of genes for inherited hearing loss in the Israeli Jewish population, including the novel human deafness gene ATOH1

Mutations in more than 150 genes are responsible for inherited hearing loss, with thousands of different, severe causal alleles that vary among populations. The Israeli Jewish population includes communities of diverse geographic origins, revealing a wide range of deafness-associated variants and enabling clinical characterization of the associated phenotypes. Our goal was to identify the genetic causes of inherited hearing loss in this population, and to determine relationships among genotype, phenotype, and ethnicity. Genomic DNA samples from informative relatives of 88 multiplex families, all of self-identified Jewish ancestry, with either non-syndromic or syndromic hearing loss, were sequenced for known and candidate deafness genes using the HEar-Seq gene panel. The genetic causes of hearing loss were identified for 60% of the families. One gene was encountered for the first time in human hearing loss: ATOH1 (Atonal), a basic helix-loop-helix transcription factor responsible for autosomal dominant progressive hearing loss in a five-generation family. Our results demonstrate that genomic sequencing with a gene panel dedicated to hearing loss is effective for genetic diagnoses in a diverse population. Comprehensive sequencing enables well-informed genetic counseling and clinical management by medical geneticists, otolaryngologists, audiologists, and speech therapists and can be integrated into newborn screening for deafness.

genetics↗

bioRxiv2020

An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

neuroscience↗

bioRxiv2019

Individual differences in stereotypy and neuron subtype translatome with TrkB deletion

Motor stereotypies occurring in early-onset neuropsychiatric diseases are associated with dysregulated basal ganglia direct-pathway activity. Disruptions in network connectivity through impaired neuronal structure have been implicated in both rodents and humans. However, the neurobiological mechanisms leading to direct-pathway neuron disconnectivity in stereotypy remain poorly understood. We have a mouse line with Tropomyosin receptor kinase B (TrkB) receptor deletion from D1-expressing cells (D1-Cre-flTrkB) in which a subset of animals shows repetitive rotations and head tics with juvenile onset. Here we demonstrate these behaviors may be associated with abnormal direct-pathway activity by reducing rotations using chemogenetic inhibition of dorsal striatum D1-medium spiny neurons (D1-MSNs) in both juvenile and young adult mice. Taking advantage of phenotypical differences in animals with similar genotype, we then interrogated the D1-MSN specific translatome associated with repetitive behavior by using RNA-sequencing of ribosome-associated mRNA. Detailed translatome analysis followed by multiplexed gene expression assessment revealed profound alterations in neuronal projection and synaptic structure related genes in stereotypy mice. Examination of neuronal morphology demonstrated dendritic atrophy and dendritic spine loss in dorsal striatum D1-MSNs from mice with repetitive behavior. Together, our results uncover phenotype-specific molecular alterations in D1-MSNs that relate to morphological adaptations in mice displaying stereotypy behavior.

neuroscience↗

bioRxiv2019

Biological insights from multi-omic analysis of 31 genomic risk loci for adult hearing difficulty

Age-related hearing impairment (ARHI), one of the most common medical conditions, is strongly heritable, yet its genetic causes remain largely unknown. We conducted a meta-analysis of GWAS summary statistics from multiple hearing-related traits in the UK Biobank (n = up to 323,978) and identified 31 genome-wide significant risk loci for self-reported hearing difficulty (p < 5e-8), of which 30 have not been reported previously in the peer-reviewed literature at genome-wide significance. We investigated the regulatory and cell specific expression for these loci by generating mRNA-seq, ATAC-seq, and single-cell RNA-seq from cells in the mouse cochlea. Risk-associated genes were most strongly enriched for expression in cochlear epithelial cells, as well as for genes related to sensory perception and known Mendelian deafness genes, supporting their relevance to auditory function. Regions of the human genome homologous to open chromatin in sensory epithelial cells from the mouse were strongly enriched for heritable risk for hearing difficulty, even after adjusting for baseline effects of evolutionary conservation and cell-type nonspecific regulatory regions. Epigenomic and statistical fine-mapping most strongly supported 50 putative risk genes. Of these, at least 39 were expressed robustly in mouse cochlea and 16 were enriched specifically in sensory hair cells. These results reveal new risk loci and risk genes for hearing difficulty and suggest an important role for altered gene regulation in the cochlear sensory epithelium.

genetics↗

bioRxiv2018

Genomic knockout of alms1 in zebrafish recapitulates Alstrom syndrome and provides insight into metabolic phenotypes

SCIENTIFIC ABSTRACTAlstrom syndrome is an autosomal recessive obesity ciliopathy caused by loss-of-function mutations in the ALMS1 gene. In addition to multi-organ dysfunction, such as cardiomyopathy, retinal degeneration, and renal dysfunction, the disorder is characterized by high rates of obesity, insulin resistance and early onset type 2 diabetes mellitus (T2DM). To investigate mechanisms linking disease phenotypes we generated a loss-of-function deletion of alms1 in the zebrafish using CRISPR/Cas9. We demonstrate conserved phenotypic effects including cardiac defects, retinal degeneration, and metabolic deficits that included propensity for obesity and fatty livers in addition to hyperinsulinemia and glucose response defects. Gene expression changes in {beta}-cells isolated from alms1-/- mutants revealed changes consistent with insulin hyper-secretion and glucose sensing failure, which were also identified in cultured murine {beta}-cells lacking Alms1. These data present a zebrafish model to assess etiology and new secretory pathway defects underlying Alstrom syndrome-associated metabolic phenotypes. Given the hyperinsulinemia and reduced glucose sensitivity in these animals we also propose the alms1 loss-of-function mutant as a monogenic model for studying T2DM phenotypes.\n\nAUTHOR SUMMARYThese data comprise a thorough characterization of a zebrafish model of Alstrom syndrome, a human obesity syndrome caused by loss-of-function deletions in a single gene, ALMS1. The high rates of obesity and insulin resistance found in these patients suggest this disorder as a single-gene model for Type 2 Diabetes Mellitus (T2DM), a disorder caused by a variety of environmental and genetic factors in the general population. We identify a propensity for obesity, excess lipid storage, loss of {beta}-cells in islets, and hyperinsulinemia in larval and adult stages of zebrafish alms1 mutants. We isolated {beta}-cells from the alms1 mutants and compared the gene expression profiles from RNASeq datasets to identify molecular pathways that may contribute to the loss of {beta}-cells and hyperinsulinemia. The increase in genes implicated in generalized pancreatic secretion, insulin secretion, and glucose transport suggest potential {beta}-cell exhaustion as a source of {beta}-cell loss and excess larval insulin. We propose this mutant as a new genetic tool for understanding the metabolic failures found in Type 2 Diabetes Mellitus.

genetics↗