Biology subjects

Dang, K.

Publications and source records attributed to Dang, K..

15 recordsLinked to original sources

bioRxiv2026

Promoter-targeted duplex RNAs activate TCF4 expression

Pitt-Hopkins syndrome (PTHS) is a severe neurodevelopmental disorder caused by haploinsufficient expression of transcription factor 4 (TCF4). Increasing expression from the remaining functional TCF4 allele could provide a mutation-independent strategy for patients with diverse pathogenic variants. We integrated genomic datasets with strand-specific RNA analysis to identify transcribed regions of the TCF4 promoter suitable for targeting by activating double-stranded RNAs (dsRNAs). Screening of overlapping promoter-targeted dsRNAs identified a hotspot for increased TCF4 expression. Activation was retained by a lead dsRNA containing extensive 2'-fluoro, 2'-O-methyl, and phosphorothioate modifications used in therapeutic oligonucleotides. Anti-AGO2 immunoprecipitation showed association with RNA transcribed from the targeted promoter region. dsRNA-mediated activation was associated with increased RNA polymerase II occupancy. These findings establish promoter-targeted dsRNAs as chemically tractable starting points for increasing TCF4 expression and support their investigation as a mutation-independent strategy for haploinsufficient disease.

molecular biology↗

bioRxiv2026

SETD5 dysfunction in human astrocytes drives IL-6-mediated neuronal impairments via the JAK/STAT signaling pathway

Intellectual disability (ID) and autism spectrum disorder (ASD) are neurodevelopmental conditions marked by lifelong impairments in cognitive, motor, and social functions. Hundreds of genetic variants have been linked to these disorders, including mutations in chromatin regulators such as the SET-domain-containing protein 5 (SETD5) gene. Most studies linking SETD5 loss-of-function to ASD/ID have focused primarily on neurons. However, while SETD5 is highly expressed in astrocytes, its role in glia cells remains poorly understood. Here, we examine how dysfunction of SETD5 in human-induced pluripotent stem cell (hiPSC)-derived astrocytes affects neuronal physiology. We show that SETD5-deficient astrocytes have increased levels of extracellular reactive oxygen species (ROS), glutamate, and interleukins-6 and 8 (IL-6 and IL-8). Elevated astrocytic IL-6 exerts a non-cell autonomous harmful effect on healthy neurons. Using SETD5-deficient astrocytes as a screening platform, we identify the JAK/STAT pathway as an upstream regulator of abnormal IL-6 accumulation associated with SETD5 dysfunction. Accordingly, pharmacological inhibition of JAK-STAT signaling restores extracellular IL-6 to basal levels and partially rescues astrocyte morphology and neuronal deficits. Collectively, these findings highlight the JAK/STAT pathway as a key regulator of SETD5-mediated astrocytic function and suggest its potential as a therapeutic target for astrocytic-driven neuronal impairments in ASD and ID.

neuroscience↗

bioRxiv2026

Unbiased Single-Cell Transcriptome-Proteome Co-Profiling Reveals Malignant Dormancy and Post-Transcriptional Buffering of CTCs

Leptomeningeal metastasis is driven by rare cerebrospinal fluid circulating tumor cells (CSF-CTCs). However, the mechanisms underlying their adaptation to chemotherapeutic stress remain elusive, primarily because transcriptomics alone poorly predicts functional protein states. Here, we present scMAPS, a single-cell multi-omics method that employs magnetic-assisted partitioning cell lysates to enable unbiased transcriptome-proteome co-profiling without loss-prone physical splitting and precision device. By coupling scMAPS with our custom CLEAP (CTC Label-free Enrichment and Accurate Picking) system, we performed the first deep multi-omics profiling of rare clinical CSF-CTCs before and after localized chemotherapy, detecting an average of 2,547 proteins and 7,821 genes per cell. The integrated CLEAP-scMAPS pipeline reveals a coordinated prioritizing survival over proliferation malignant dormancy phenotype and identified post-transcriptional buffering as the primary driver of treatment resistance. Our platform enables the comprehensive molecular phenotyping of rare clinical specimens, providing a highly versatile framework for decoding complex post-transcriptional regulatory networks.

cell biology↗

bioRxiv2025

Loss of tight junction protein claudin 18 uncovers alveolar epithelial stem cell plasticity and emergence of non-fibrogenic transitional progenitors

Persistence of senescent alveolar transitional progenitors following lung injury is implicated in the pathogenesis of fibrosis. We identified transitional cells in uninjured Cldn18 knockout (KO) mouse lungs distinct from previously reported damage-associated transitional progenitors (DATPs) with a less fibrogenic transcriptomic profile. Cldn18 KO mice are protected from bleomycin-induced fibrosis, with early restoration of cellular homeostasis. Lineage tracing implicates accelerated differentiation as a mechanism for protection from fibrosis, leading us to name these cells regeneration-associated transitional progenitors (RATPs). Multiome confirms that RATPs and DATPs are epigenetically distinct, with RATPs comprised of RATP2s and RATP1s based on epigenomic proximity to AT2s and AT1s, respectively, and suggests dynamic regulatory remodeling during AT2-to-AT1 differentiation, with NKX2.1 and AP-1 active in early transitions and TEAD factors in later stages. These results reveal an unexpected role for Cldn18 in regulation of AEC plasticity, while identification of RATPs challenges the notion that persistence of transitional alveolar cells is invariably pathologic.

cell biology↗

bioRxiv2025

Multi-omic analysis of photoreceptor alterations during early-onset retinal degeneration in Mfrp-/- mice

Loss-of-function mutations in the membrane frizzled-related protein (MFRP) gene are associated with autosomal recessive ocular disorders such as nanophthalmos, posterior microphthalmia, and retinitis pigmentosa, yet the molecular mechanisms underlying MFRP-related retinal degeneration remain poorly defined. To investigate these mechanisms, we generated and characterized Mfrp-/- mice and conducted an integrated multi-omic analysis to map the onset and progression of transcriptional changes during retinal degeneration. Using longitudinal in vivo imaging, histological and immunohistochemical analysis, qRT-PCR, single-nucleus RNA sequencing (snRNA-seq), snATAC seq (single-nucleus Assay for Transposase-Accessible Chromatin using sequencing) and spatial transcriptomics (GeoMx DSP), we identified early and progressive photoreceptor loss in Mfrp-/- mice, beginning by 28d. Retinal thinning and autofluorescent deposits in Mfrp-/- mice were accompanied by decreased expression of rod and cone opsins. Transcriptomic profiling by snRNA-seq revealed distinct, photoreceptor-specific gene expression changes, including early upregulation of inflammatory and stress-related genes and later downregulation of genes involved in chromatin remodeling, synaptic function, and neurodevelopment. Spatial transcriptomic analysis of the outer nuclear layer (ONL) revealed disruptions in mitochondrial function, mTORC1 signaling, and G protein-coupled receptor pathways. These findings define a temporally and spatially coordinated program of degeneration triggered by Mfrp loss and demonstrate that Mfrp is required for the maintenance of photoreceptor integrity and gene regulatory homeostasis during retinal development. Our work establishes Mfrp-/- mice as a robust model for dissecting photoreceptor vulnerability and provides a transcriptomic atlas of disease progression with potential relevance for therapeutic development in MFRP-associated retinal dystrophies.

genomics↗

bioRxiv2025

AquIRE reveals multiple mechanisms of clinically induced RNA damage and the conservation and dynamics of glycoRNAs

RNA is subject to many modifications, from small chemical changes such as methylation through to conjugation of biomolecules such as glycans. As well as these endogenously written modifications, RNA is also exposed to damage induced by its environment. Certain clinical compounds are known to drive covalent modifications of RNA with a growing appreciation for how these affect function. To understand the regulation of these modifications we need a reliable, sensitive and rapid methodology for their quantification. Thus, we developed AquIRE and applied it to the analysis of drug-induced RNA damage, showing this to be widespread with intricate temporal dynamics. Using the same methodology we identify RNA:protein crosslinking and the rewriting of the epitranscriptome as a consequence of clinical RNA damage. We also demonstrate how liquid-liquid phase separation increases RNA damage and expand the horizons of the glycoRNA world across the kingdoms of life and into cell-free glycoRNA.

molecular biology↗

bioRxiv2024

Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina

Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.

genomics↗

bioRxiv2024

Artificial intelligence networks combining histopathology and machine learning can extract axon pathology in autism spectrum disorder

Axon features that underlie the structural and functional organization of cortical pathways have distinct patterns in the brains of neurotypical controls (CTR) compared to individuals with Autism Spectrum Disorder (ASD). However, detailed axon study demands labor-intensive surveys and time-consuming analysis of microscopic sections from post-mortem human brain tissue, making it challenging to systematically examine large regions of the brain. To address these challenges, we developed an approach that uses machine learning to automatically classify microscopic sections from ASD and CTR brains, while also considering different white matter regions: superficial white matter (SWM), which contains a majority of axons that connect nearby cortical areas, and deep white matter (DWM), which is comprised exclusively by axons that participate in long-range pathways. The result was a deep neural network that can successfully classify the white matter below the anterior cingulate cortex (ACC) of ASD and CTR groups with 98% accuracy, while also distinguishing between DWM and SWM pathway composition with high average accuracy, up to 80%. Multidimensional scaling analysis and sensitivity maps further underscored the reliability of ASD vs CTR classification, based on the consistency of axon pathology, while highlighting the important role of white matter location that constrains pathway dysfunction, based on several shared anatomical markers. Large datasets that can be used to expand training, validation, and testing of this network have the potential to automate high-resolution microscopic analysis of post-mortem brain tissue, so that it can be used to systematically study white matter across brain regions in health and disease. One Sentence StatementHistopathology-trained AI can identify ASD network disruptions and guide development of diagnostics and targeted therapeutics.

neuroscience↗

bioRxiv2023

Ribosome Quality Control Mechanism Mitigates the Cytotoxic Impacts of Ribosome Collisions Induced by 5-Fluorouracil

Translation of aberrant or damaged mRNAs results in ribosome stalling and collisions. The Ribosome Quality Control (RQC) mechanism detects collided ribosomes and removes aberrant mRNAs and nascent peptides, thus preventing their cytotoxic effects. Conversely, excessive or unresolved ribosome collisions can induce apoptosis. 5-Fluorouracil (5FU) forms the backbone of standard-of-care chemotherapeutic regimens for several types of cancer. Although best known for its incorporation into DNA and inhibition of thymidylate synthase, a major determinant of 5FUs anticancer activity is its incorporation into RNAs. Nevertheless, the mechanism(s) underlying RNA-dependent 5FU cytotoxicity and the cellular response to its impact on RNA metabolism remain unclear. Here, we report a key role for RQC in mitigating the cytotoxic effects of 5FU-induced dysregulation of mRNA translation. We show that acute 5FU treatment results in the rapid induction of the mTOR signalling pathway, an enhanced rate of mRNA translation initiation, and increased ribosome collisions that trigger RQC. We also found that RQC deficiency, caused by the depletion of ZNF598, results in increased 5FU-induced cell death, a phenotype that is reversed by inhibition of mTOR or repression of mRNA translation initiation. Importantly, 5FU treatment enhances the expression of key RQC factors, including ZNF598 and GIGYF2, via an mTOR-dependent post-translational regulation mechanism. This acute adaptation likely mitigates the cytotoxic consequences of increased ribosome collisions upon 5FU treatment. Overall, our data indicate a heretofore unknown mTOR-dependent mechanism that augments the RQC process, mitigating the cytotoxicity of 5FU and undermining its anticancer efficacy.

cell biology↗

bioRxiv2023

Transcriptomic profiling of nuclei from PFA-fixed and FFPE brain tissues

Formalin-fixed and paraffin-embedded (FFPE) tissue archives are the largest repository of clinically annotated specimens, and FFPE-compatible single cell gene expression workflow had been developed and applied recently. However, for tissues where cells are hard to dissociate or brains with complex neuronal cells, nuclear transcriptomic profiling are desirable. Moreover, the effects of standard pathological practice on the transcriptome of samples obtained from such archived specimens was also largely anecdotal. Here, we performed RNA-seq of nuclei from hippocampal of mice that underwent freezing, paraformaldehyde (PFA) fixation, and paraffin embedding. Then, we comprehensively evaluated the parameters affecting mRNA quality, transcription patterns, functional level and cell states of nuclei, including PFA fixation time and storage time of FFPE tissues. The results showed that the transcriptome signatures of nuclei isolated from fresh PFA-fixed and fresh FFPE tissues were more similar to matched frozen samples. By contrast, the brain fixed for more than 3 days had prominent impacts on the sequencing data, such as the numbers and biotypes of gene, GC content and ratio of reads interval. Commensurately, prolonged fixation time will result in more differentially expressed genes, especially those enriched in spliceosome and synaptic related pathways, affecting the analysis of gene splicing and neuron cells. MuSiC deconvolution results revealed that PFA infiltrating brains for 3 days will destroy the real cell states, and the proportion of neuron, endothelial and oligodendrocytes diminished while that of microglia was reversed. Yet the effect of storage time on cell composition was more neglectable for FFPE samples. In addition, oligodendrocyte precursor cells were most affected in all fixed samples, and their destruction was independent of fixation time and preservation time. The comprehensive results highlighted that fixation time had much more influences on the nuclear transcriptomic profiles than FFPE retention time, and the cliff-like effects appeared to occur over a fixed period of 1-3 days, with no more differences from additional fixation durations.

molecular biology↗

bioRxiv2022

Stromal Hippo-YAP signaling in stem cell niche controls intestinal homeostasis

Intestinal homeostasis is tightly regulated by the reciprocal interaction between gut epithelium and adjacent mesenchyme. The mammalian Hippo-YAP pathway is intimately associated with intestinal epithelial homeostasis and re-generation; however, its role in postnatal gut mesenchyme remains poorly defined. We find that, although removal of the core Hippo kinases Lats1/2 or activation of YAP in adult intestinal smooth muscle has largely no effect; Hippo-YAP signaling in Gli1/PDGFR-expressing intestinal stromal cells is critical to maintain the stem cell niche. We show that YAP/TAZ activation drives over-proliferation and suppresses smooth muscle actin expression in the niche-forming Gli1+ mesenchymal progenitors. In addition, mesenchymal YAP/TAZ activation disrupts the epithelial-mesenchymal crosstalk by promoting Wnt ligand production, leading to epithelial Wnt pathway activation. Our data also reveal that YAP/TAZ are upregulated in the stroma during DSS-induced injury and stromal YAP activation promotes intestinal epithelial regeneration. Altogether, our data identify an essential requirement for stromal Hippo-YAP signaling in the stem cell niche during intestinal homeostasis. HIGHTLIGHTSO_LILats1/2 control proliferation and differentiation of adult gut mesenchymal progenitors. C_LIO_LIMesenchymal YAP/TAZ promotes Wnt ligand production in intestinal stem cell niche. C_LIO_LIYAP/TAZ is up-regulated in the mesenchyme during intestinal injury. C_LIO_LIStromal YAP activation promotes intestinal epithelial regeneration. C_LI

developmental biology↗

bioRxiv2020

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular targets, there are currently small-molecules available only for a small proportion of the human proteome. Effective approaches are therefore required to map the massive space of unexplored compound-target interactions for novel and potent activities. Here, we carried out a crowdsourced benchmarking of predictive models for kinase inhibitor potencies across multiple kinase families using unpublished bioactivity data. The top-performing predictions were based on kernel learning, gradient boosting and deep learning, and their ensemble resulted in predictive accuracy exceeding that of kinase activity assays. We then made new experiments based on the model predictions, which further improved the accuracy of experimental mapping efforts and identified unexpected potencies even for under-studied kinases. The open-source algorithms together with the novel bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking new prediction algorithms and for extending the druggable kinome.

biochemistry↗

bioRxiv2019

Exploring Contextual Interference in Implicit and Explicit Motor Learning

The classic advice given to anyone learning a new skill is \"practice makes perfect.\" While this provides a good general rule to follow, it lacks any detail on what form of practice will efficiently maximize learning. So when faced with the task of acquiring multiple skills, what is the optimal way to learn? Would it be more beneficial to master each skill separately or learn them all at once in an interleaved fashion? A concept known as contextual interference suggests that using a random practice schedule leads to better retention than a blocked one. There are some motor learning studies that are consistent with this hypothesis and some that are not. In order to explore these conflicting results, we applied contextual interference to a simple reaching task that could allow us to observe its effects to various components of motor learning. We had participants learn three different visuomotor rotations and manipulated interference by placing them in groups characterized by how training targets are ordered (blocked vs. random). Using reaction time and hand angle as our measures of performance, we found that participants who experienced a random practice schedule had significant improvements in their ability to retain information, which was manifest as higher levels of implicit adaptation and faster reaction times. However, this did not necessarily mean the information was executed accurately since hand angles did not differ between groups. These findings suggest contextual interference will be most advantageous in situations that require fast explicit recall of a motor plan to use rather than those that emphasize accuracy.

neuroscience↗

bioRxiv2017

Combining accurate tumour genome simulation with crowd sourcing to benchmark somatic structural variant detection

BackgroundThe phenotypes of cancer cells are driven in part by somatic structural variants. Structural variants can initiate tumors, enhance their aggressiveness and provide unique therapeutic opportunities. Whole-genome sequencing of tumors can allow exhaustive identification of the specific structural variants present in an individual cancer, facilitating both clinical diagnostics and the discovery of novel mutagenic mechanisms. A plethora of somatic structural variant detection algorithms have been created to enable these discoveries, however there are no systematic benchmarks of them. Rigorous performance evaluation of somatic structural variant detection methods has been challenged by the lack of gold-standards, extensive resource requirements and difficulties arising from the need to share personal genomic information.\n\nResultsTo facilitate structural variant detection algorithm evaluations, we create a robust simulation framework for somatic structural variants by extending the BAMSurgeon algorithm. We then organize and enable a crowd-sourced benchmarking within the ICGC-TCGA DREAM Somatic Mutation Calling Challenge (SMC-DNA). We report here the results of structural variant benchmarking on three different tumors, comprising 204 submissions from 15 teams. In addition to ranking methods, we identify characteristic error-profiles of individual algorithms and general trends across them. Surprisingly, we find that ensembles of analysis pipelines do not always outperform the best individual method, indicating a need for new ways to aggregate somatic structural variant detection approaches.\n\nConclusionsThe synthetic tumors and somatic structural variant detection leaderboards remain available as a community benchmarking resource, and BAMSurgeon is available at https://github.com/adamewing/bamsurgeon.

bioinformatics↗

bioRxiv2016

Experimental evolution reveals favored adaptive routes to cell aggregation in yeast

Yeast flocculation is a community-building cell aggregation trait that is an important mechanism of stress resistance and a useful phenotype for brewers; however, it is also a nuisance in many industrial processes, in clinical settings, and in the laboratory. Chemostat-based evolution experiments are impaired by inadvertent selection for aggregation, which we observe in 35% of populations. These populations provide a testing ground for understanding the breadth of genetic mechanisms Saccharomyces cerevisiae uses to flocculate, and which of those mechanisms provide the biggest adaptive advantages. In this study, we employed experimental evolution as a tool to ask whether one or many routes to flocculation are favored, and to engineer a strain with reduced flocculation potential. Using a combination of whole genome sequencing and bulk segregant analysis, we identified causal mutations in 23 independent clones that had evolved cell aggregation during hundreds of generations of chemostat growth. In 12 of those clones we identified a transposable element insertion in the promoter region of known flocculation gene FLO1, and in an additional five clones we recovered loss-of-function mutations in transcriptional repressor TUP1, which regulates FLO1 and other related genes. Other causal mutations were found in genes that have not been previously connected to flocculation. Evolving a flo1 deletion strain revealed that this single deletion reduces flocculation occurrences to 3%, and demonstrated the efficacy of using experimental evolution as a tool to identify and eliminate the primary adaptive routes for undesirable traits.

genetics↗