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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

Differential Transcript Usage Reveals Isoform-Level Remodeling of Tumor Biology in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is characterized by transcriptional reprogramming driven by hypoxia signaling, metabolic rewiring, and immune modulation. While gene-level analyses have defined key features of ccRCC biology, they do not capture isoform-level variation arising from alternative splicing. Differential transcript usage (DTU) represents an additional regulatory layer that may influence protein function, pathway activity, and clinical outcomes, yet its role in ccRCC biology and prognosis remains incompletely understood. We assessed differential expression in 127 ccRCC tumors and 33 normal-adjacent tissues from the Dartmouth Cancer Center cohort, with external validation in 94 CPTAC tumors, adjusting for cell-type proportions. DTU was identified using DRIMSeq/stageR, followed by limmavoom modeling with clinical and tumor microenvironment covariates. Transcript-based consensus clustering defined tumor subgroups, and Cox proportional hazards modeling integrated transcript-level features with clinical variables. In tumor versus normal comparisons, 1,170 transcripts exhibited significant differential usage, mapping to canonical ccRCC pathways with distinct patterns across functional and non-functional transcript classes. Consensus clustering based on transcript us-age identified two subgroups with distinct angiogenic profiles and significant survival differences. Cluster-level analysis revealed DTU in genes involved in cytoskeletal organization (ACTB), immune processes (B2M), extracellular matrix organization (FN1, APLP2), and iron metabolism (FTH1) with protein domain alterations, including the loss of actin-associated domains in ACTB and immunoglobulin-like domains in B2M. Prognostic modeling identified twelve transcripts consistently retained across bootstraps, improving risk stratification over clinical variables alone. External validation confirmed overlapping prognostic transcripts, including FGFR1 and NUCB1. Isoform-level features may serve as biomarkers and therapeutic targets in ccRCC. Statement of significanceTranscript-level analysis uncovers potential regulatory pathways in ccRCC missed by gene-level approaches, revealing isoform-specific alterations that define survival sub-groups and offer potential biomarkers and therapeutic targets.

cancer biology↗

bioRxiv2022

Topological transitions, turbulent-like motion and long-time-tails driven by cell division in biological tissues

The complex spatiotemporal flow patterns in living tissues, driven by active forces, have many of the characteristics associated with inertial turbulence even though the Reynolds number is extremely low. Analyses of experimental data from two-dimensional epithelial monolayers in combination with agent-based simulations show that cell division and apoptosis lead to directed cell motion for hours, resulting in rapid topological transitions in neighboring cells. These transitions in turn generate both long ranged and long lived clockwise and anticlockwise vortices, which gives rise to turbulent-like flows. Both experiments and simulations show that at long wavelengths the wave vector (k) dependent energy spectrum E(k) {approx} k-5/3, coinciding with the Kolmogorov scaling in fully developed inertial turbulence. Using theoretical arguments and simulations, we show that long-lived vortices lead to long-time tails in the velocity auto-correlation function, Cv(t) [~] t-1/2, which has the same structure as in classical 2D fluids but with a different scaling exponent.

biophysics↗

bioRxiv2025

Design of peptide-based PAC1 antagonists combining molecular dynamics simulations and a biologically relevant cell-based assay

The PACAP receptor PAC1 is a Gs-coupled family B1 GPCR for which the highest-affinity endogenous peptide ligands are the pituitary adenylate cyclase-activating peptides PACAP38 and PACAP27, and whose most abundant endogenous ligand is PACAP38. PACAP action at PAC1 is implicated in neuropsychiatric disorders, atherosclerosis, pain chronification, and protection from neurodegeneration and ischemia. As PACAP also interacts with two related receptors, VPAC1 and VPAC2, highly selective ligands, both agonists and antagonists, for PAC1 have been sought. To date, the peptide PACAP(6-38) and polypeptide M65, which is related to maxadilan, a sandfly vasodilator peptide, have been identified as selective for PAC1. Several non-peptide small molecule compounds (SMOLs) have been reported to be specific antagonists at PAC1, albeit their specificities have not been rigorously documented. Here, we present a platform of cellular assays for the screening of biologically relevant antagonists at PAC1 and show that some currently proposed SMOL antagonists do not have activity in this cell reporter assay, while we confirm that PACAP(6-38) and M65 are competitive antagonists. We have used this assay system to explore other peptide antagonists at PAC1, guided by molecular dynamics analysis of the PACAP-PAC1 interaction based on cryo-EM structural models of PAC1 complexed with a number of biologically active ligands. The affinity-trap model for the PAC1-ligand interaction successfully predicts the engagement behavior of PACAP27 and PACAP38 peptide-based PAC1 inhibitors. In particular, C-terminal deletants of PACAP(6-38) that maintain equipotency to PACAP(6-38) allow the shorter sequence to function as a scaffold for further peptide-based antagonist exploration.

pharmacology and toxicology↗

bioRxiv2021

NFIC regulates ribosomal biology and ER stress in pancreatic acinar cells and suppresses PDAC initiation

Tissue-specific differentiation is driven by specialized transcriptional networks. Pancreatic acinar cells crucially rely on the PTF1 complex, and on additional transcription factors, to deploy their transcriptional program. Here, we identify NFIC as a novel regulator of acinar differentiation using a variety of methodological strategies. NFIC binding sites are found at very short distances from NR5A2-bound genomic regions and both proteins co-occur in the same complex. Nfic knockout mice show reduced expression of acinar genes and, in ChIP-seq experiments, NFIC binds the promoters of acinar genes. In addition, NFIC binds to the promoter of, and regulates, genes involved in RNA and protein metabolism; in Nfic knockout mice, p-RS6K1 and p-IEF4E are down-regulated indicating reduced activity of the mTOR pathway. In 266-6 acinar cells, NFIC dampens the ER stress program through its binding to ER stress gene promoters and is required for complete resolution of Tunicamycin-mediated ER stress. Normal human pancreata from subjects with low NFIC mRNA levels display reduced epxression of genes down-regulated in Nfic knockout mice. Consistently, NFIC displays reduced expression upon induced acute pancreatitis and is required for proper recovery after damage. Finally, expression of NFIC is lower in samples of mouse and human pancreatic ductal adenocarcinoma and Nfic knockout mice develop an increased number of mutant Kras-driven pre-neoplastic lesions.

cell biology↗

bioRxiv2024

Correlative Imaging for Comprehensive Molecular Mapping of Individual Cell Types in Biological Tissues

Mass spectrometry imaging (MSI) is a powerful technique for label-free spatial mapping of multiple classes of biomolecules in tissue sections. However, differences in desorption and ionization efficiency of different classes of molecules make it challenging to simultaneously map biomolecules at each omics layer in the same tissue sample. Herein, we present a correlative imaging method using nanospray desorption electrospray ionization (nano-DESI) MSI, which enables the spatial mapping of lipids, metabolites, peptides, and proteins with cellular-level spatial resolution in a single tissue section. We demonstrate the molecular profiling of specific cell types and identify truncated peptides in mouse pancreatic tissue. Distinct chemical gradients of peptides and lipids extending from endocrine cells to exocrine cells indicate their different roles in endocrine-exocrine crosstalk and intracellular signaling. The results underscore the power of the developed imaging approach for spatial multi-omics analysis that provides deep insights into cellular diversity and the intricate molecular interactions that occur within heterogenous biological tissues.

biochemistry↗

bioRxiv2024

Biologically-informed Killer cell immunoglobulin-like receptor (KIR) gene annotation tool

Natural killer (NK) cells are essential components of the innate immune system, with their activity significantly regulated by Killer cell Immunoglobulin-like Receptors (KIRs). The diversity and structural complexity of KIR genes present significant challenges for accurate genotyping, essential for understanding NK cell functions and their implications in health and disease. Traditional genotyping methods struggle with the variable nature of KIR genes, leading to inaccuracies that can impede immunogenetic research. These challenges extend to high-quality phased assemblies, which have been recently popularized by the Human Pangenome Consortium. This paper introduces BAKIR (Biologically-informed Annotator for KIR locus), a tailored computational tool designed to overcome the challenges of KIR genotyping and annotation on high-quality, phased genome assemblies. BAKIR aims to enhance the accuracy of KIR gene annotations by structuring its annotation pipeline around identifying key functional mutations, thereby improving the identification and subsequent relevance of gene and allele calls. It uses a multi-stage mapping, alignment, and variant calling process to ensure high-precision gene and allele identification, while also maintaining high recall for sequences that are significantly mutated or truncated relative to the known allele database. BAKIR has been evaluated on a subset of the HPRC assemblies, where BAKIR was able to improve many of the associated annotations and call novel variants. BAKIR is freely available on GitHub, offering ease of access and use through multiple installation methods, including pip, conda, and singularity container, and is equipped with a user-friendly command-line interface, thereby promoting its adoption in the scientific community.

genomics↗

bioRxiv2022

Effect of rectified gap junctional electrical coupling and spatial distribution of biologically engineered pacemaking cells on ventricular excitation

AimBiologically engineered pacemaker, or bio-pacemaker, is a promising replacement for electronic pacemakers for treating cardiac dysfunction. Previous animal experimental studies, however, have not been able to accurately demonstrate the stability and efficiency of the bio-pacemaker yet. This study aimed to elucidate the underlying factors that affect bio-pacemakers performance and to discover possible optimising solutions to enable the potential use of bio-pacemaker therapy. Methods and resultsThe human ventricular myocytes model in this study followed the ten Tussuchers model in 2006, and the bio-pacemaker single cell model was modified based on it as what has been expatiated in our previous work. In tissue model, two factors were primarily evaluated for their effects on bio-pacemakers to pace and drive surrounding cardiac tissue: gap junction between bio-pacemaker cells (PMs) and adjacent ventricular myocytes (VMs) and the spatial distribution of bio-pacemakers. A suppressed gap junctional electrical coupling between and heterotypic gap junctions were simulated and a combination of them led to the best performance of the bio-pacemaker. Then, the pacemaking behaviours of three kinds of idealised PM-VM slices were simulated, in which an electrically isolated distribution of bio-pacemaker showed optimal drive capacities. Finally, a real human ventricular slice model was used to verified the conclusions in idealized tissues. ConclusionThis study develops a theory that weak-rectified electrical coupling and electrically isolated distribution can enhance the pacemaking efficiency of bio-pacemakers, which lays the groundwork for future research into therapeutic applications of bio-pacemakers. Author summaryBiologically engineered pacemakers are expected to be a substitute for electronic pacemakers because of their physiological superiority, but how to transform them for practical application remains challenging. In this paper, we presented a theoretical perspective on optimising biological pacemaking capability based on a computational simulation approach. By manipulating the gap junctional electrical coupling among bio-pacemaking cells and between the pacemaker and their surrounding cells, and controlling spatial distribution of bio-pacemaker, we demonstrated that an enhanced capacity of a bio-pacemaker can be achieved. The results of this study may provide a theoretical basis for the further clinical development of bio-pacemakers.

biophysics↗

bioRxiv2023

At-home, cell-free synthetic biology education modules for transcriptional regulation and environmental water quality monitoring

As the field of synthetic biology expands, the need to grow and train science, technology, engineering, and math (STEM) practitioners is essential. However, the lack of access to hands-on demonstrations has led to inequalities of opportunity and practice. In addition, there is a gap in providing content that enables students to make their own bioengineered systems. To address these challenges, we develop four shelf-stable cell-free biosensing educational modules that work by just-adding-water and DNA to freeze-dried crude extracts of Escherichia coli. We introduce activities and supporting curricula to teach the structure and function of the lac operon, dose-responsive behavior, considerations for biosensor outputs, and a build-your-own activity for monitoring environmental contaminants in water. We piloted these modules with K-12 teachers and 130 high school students in their classrooms - and at home - without professional laboratory equipment or researcher oversight. This work promises to catalyze access to interactive synthetic biology education opportunities.

synthetic biology↗

bioRxiv2018

Protein Structural Biology Using Cell-Free Platform from Wheat Germ

One of the biggest bottlenecks for structural analysis of proteins remains the creation of high yield and high purity samples of the target protein. Cell-free protein synthesis technologies are powerful and customizable platforms for obtaining functional proteins of interest in short timeframes while avoiding potential toxicity issues and permitting high-throughput screening. These methods have benefited many areas of genomic and proteomics research, therapeutics, vaccine development and protein chip constructions. In this work, we demonstrate a versatile and multistage eukaryotic wheat-germ cell-free protein expression pipeline to generate functional proteins of different sizes from multiple host organism and DNA source origins. We also developed a robust purification procedure, which can produce highly-pure (>98%) proteins with no specialized equipment required and minimal time invested. This pipeline successfully produced and analyzed proteins in all three major geometry formats used for structural biology including single particle analysis, and both two-dimensional and three-dimensional protein crystallography. The flexibility of the wheat germ system in combination with the multiscale pipeline described here provides a new workflow for rapid generation of samples for structural characterization that may not be amenable to other recombinant approaches.

molecular biology↗

bioRxiv2021

Design and modular assembly of synthetic intramembrane proteolysis receptors for custom gene regulation in therapeutic cells

Synthetic biology has established powerful tools to precisely control cell function. Engineering these systems to meet clinical requirements has enormous medical implications. Here, we adopted a clinically driven design process to build receptors for the autonomous control of therapeutic cells. We examined the function of key domains involved in regulated intramembrane proteolysis and showed that systematic modular engineering can generate a class of receptors we call SyNthetic Intramembrane Proteolysis Receptors (SNIPRs) that have tunable sensing and transcriptional response abilities. We demonstrate the potential transformative utility of the receptor platform by engineering human primary T cells for multi-antigen recognition and production of dosed, bioactive payloads relevant to the treatment of disease. Our design framework enables the development of fully humanized and customizable transcriptional receptors for the programming of therapeutic cells suitable for clinical translation.

synthetic biology↗

bioRxiv2023

The ClpX chaperone and a hypermorphic FtsA variant with impaired self-interaction are mutually compensatory for coordinating Staphylococcus aureus cell division

Bacterial cell division requires the coordinated assembly and disassembly of a large protein complex called the divisome, however, the exact role of molecular chaperones in this critical process remains unclear. In the important pathogenic bacterium Staphylococcus aureus, the ClpX chaperone is essential for growth at 30{degrees}C and microscopic analyses suggested that ClpX plays a temperature-dependent role in cell division. We here provide genetic evidence that ClpX unfoldase activity is a determinant for proper coordination of cell division by showing that a spontaneous G325V substitution in the ATP-binding domain of the essential FtsA cell division protein rescues growth and septum synthesis in a Staphylococcus aureus clpX mutant. The polymerization state of FtsA is thought to control initiation of bacterial septum synthesis and, while restoring the aberrant FtsA dynamics in clpX cells, the FtsAG325V variant displayed reduced ability to interact with itself and other cell division proteins. In wild-type cells, the ftsAG325V allele shared phenotypes with E. coli superfission ftsA mutants and accelerated the cell cycle, increased the risk of daughter cell lysis, and conferred sensitivity to heat and antibiotics inhibiting cell wall synthesis. Strikingly, lethality was mitigated by spontaneous mutations that inactivate ClpX. Taken together, our results suggest that ClpX promotes septum synthesis by antagonizing FtsA interactions and illuminates the critical role of a protein unfoldase in coordinating bacterial cell division. IMPORTANCEEssential biological processes, such as cell division, are performed by multiple proteins working together in dynamic functional complexes. In eukaryotic cells, the disassembly of such molecular machines is often assisted by molecular chaperones capable of unfolding proteins. The ClpX unfoldase is conserved from bacteria to humans, however, the roles of ClpX in bacterial cell biology remain relatively unexplored. By combining genetic methods with super-resolution microscopy techniques, we show here that ClpX and a mutant variant of the essential cell division protein FtsA mutually compensate for each other in controlling cell division of the pathogenic bacterium Staphylococcus aureus. The selected FtsAG325V variant has diminished self-interactions and restored the aberrant FtsA dynamics in clpX cells suggesting that ClpX promotes cell division by antagonizing FtsA protein interactions. This study, for the first time, illuminates the important role of protein unfoldases in the functioning of the divisome, a multienzyme complex fundamental to bacterial reproduction.

molecular biology↗

bioRxiv2026

A single-cell atlas and aging clock define biological age and risk-associated stem cell states in human hematopoiesis

Aging of hematopoietic stem and progenitor cells (HSPCs) impairs regenerative capacity and predisposes to hematological diseases. Here, we constructed a comprehensive single-cell transcriptomic atlas comprising 186,123 CD34+ HSPCs spanning early prenatal development (6 post-conception weeks) to late adulthood (74 years). We identified two conserved core molecular programs (MPs) of inflammaging and RNA splicing / protein homeostasis. Leveraging these programs, we developed a machine learning-based stem cell aging clock from 84 donors. Applying this clock to acute myeloid leukemia (AML), we define Transcriptional Age Deviation (TAD), a novel metric of biological age divergence. We found that a biologically "younger" state (low TAD), reflecting oncofetal reprogramming, is a powerful independent predictor of poor survival in two large AML cohorts. Low TAD was associated with high-risk genetics and therapy resistance, and critically, it re-stratified patient outcomes within each ELN 2022 risk category. Our work establishes a quantitative link between stem cell aging biology and AML prognosis, offering a robust tool to refine clinical risk assessment.

bioinformatics↗

bioRxiv2024

Making Neurobots and Chimerical Ctenophores

Making living machines using biological materials (cells, tissues, and organs) is one of the challenges in developmental biology and modern biomedicine. Constraints in regeneration potential and immune self-defense mechanisms limit the progress in the field. Here, we present unanticipated features related to self-recognition and ancestral neuro-immune architectures of new emerging reference species - ctenophores or comb jellies. These are descendants of the earliest survival metazoan lineage with unique tissues, organs and independent origins of major animal traits such as neurons, muscles, mesoderm, and through-gut. Thus, ctenophores convergently evolved complex organization, compared to bilaterians. Nevertheless, their neural and immune systems are likely functionally coupled, enabling designs and experimental construction of hybrid neural systems and even entire animals. This report illustrates impressive opportunities to build both chimeric animals and neurobots using ctenophores as models for bioengineering. The obtained neurobots and chimeric animals from three ctenophore species (Bolinopsis, Mnemiopsis, and Pleurobrachia) were able to be autonomous and survive for days. In sum, the unification of biodiversity, cell biology, and neuroscience opens unprecedented opportunities for experimental synthetic biology.

developmental biology↗

bioRxiv2017

An extensible ontology for inference of emergent whole cell function from relationships between subcellular processes

Whole cell responses arise from coordinated interactions between diverse human gene products functioning within various pathways underlying sub-cellular processes (SCP). Lower level SCPs interact to form higher level SCPs, often in a context specific manner to give rise to whole cell function. We sought to determine if capturing such relationships enables us to describe the emergence of whole cell functions from interacting SCPs. We developed the \"Molecular Biology of the Cell\" ontology based on standard cell biology and biochemistry textbooks and review articles. Currently, our ontology contains 5,392 genes, 753 SCPs and 19,182 expertly curated gene-SCP associations. Our algorithm to populate the SCPs with genes enables extension of the ontology on demand and the adaption of the ontology to the continuously growing cell biological knowledge. Since whole cell responses most often arise from the coordinated activity of multiple SCPs, we developed a dynamic enrichment algorithm that flexibly predicts SCP-SCP relationships beyond the current taxonomy. This algorithm enables us to identify interactions between SCPs as a basis for higher order function in a context dependent manner, allowing us to provide a detailed description of how SCPs together can give rise to whole cell functions. We conclude that this ontology can, from omics data sets, enable the development of detailed multidimensional SCP networks for predictive modeling of emergent whole cell functions.

systems biology↗

bioRxiv2024

Using CRISPR barcoding as a molecular clock to capture dynamic processes at single-cell resolution

Biological processes are fundamentally dynamic, yet existing methods for capturing these temporal changes are limited. We present scDynaBar, a novel approach that integrates CRISPR-Cas9 dynamic barcoding with single-cell sequencing to enable the recording of temporal cellular events. In this system, genetic barcodes accumulate mutations over a 25-day period and then are sequenced together with the transcriptome of each single cell. We propose that this gradual accumulation of genetic diversity can be exploited to create an ordered record of a cellular event. We apply this approach to track the transition from a pluripotent state to a two-cell (2C)-like state in mouse embryonic stem cells (mESCs). The results provide compelling evidence for the transient nature of the 2C-like state. Additionally, our system shows consistent mutation rates across diverse cell types in a mouse gastruloid model, underscoring its robustness and versatility across various biological contexts. This technique not only improves our ability to study single-cell dynamics but also creates new opportunities for recording other temporal signals--in other words, using dynamic barcoding as a molecular clock in individual cells. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/618192v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1665361org.highwire.dtl.DTLVardef@ec3114org.highwire.dtl.DTLVardef@8a3123org.highwire.dtl.DTLVardef@a0235f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2026

Comparative Biology at Single-Cell Resolution: Rigorous Matching of Atlases for Cross-Species Analysis

Single-cell transcriptomics has revolutionised developmental biology by providing an unprecedented, fine-grained view of cellular lineages. However, our ability to compare species and distinguish universal from species-specific developmental principles remains limited by biological and technical variability. To address this, we introduce RIMA (RIgorous Matching of Atlases), a method for quantitatively comparing transcriptomic atlases across species at near-single-cell resolution. RIMA uses a novel computational approach to identify matching cell states across atlases and leverages this to enable quantitative comparative analyses. Applied to gastrulation in mouse, rabbit, and macaque, RIMA recapitulates a developmental hourglass pattern, identifying a molecular similarity bottleneck at the onset of organogenesis. It further uncovers conserved developmental programmes, including a core set of transcription factors driving epithelial-mesenchymal transition, and highlights transcriptional boosts of erythroid differentiation genes that are conserved across species but exhibit shifted onset timing. Furthermore, RIMA enables cross-species prediction of gene expression, augmenting sparse atlases and correcting differences between model and target organisms. Beyond cross-species comparisons, RIMAs framework extends naturally to any setting where large systematic differences exist across datasets, including in vitro to in vivo comparisons, opening new avenues for improving biological models and advancing translational research.

bioinformatics↗

bioRxiv2020

In situ measurement of intracellular thermal conductivity using heater-thermometer hybrid diamond nanosensor

Understanding heat dissipation processes at nanoscale during cellular thermogenesis is essential to clarify the relationships between the heat and biological processes in cells and organisms. A key parameter determining the heat flux inside a cell is the local thermal conductivity, a factor poorly investigated both experimentally and theoretically. Here, using a nanoheater/nanothermometer hybrid based on a polydopamine shell encapsulating a fluorescent diamond nanocrystal, we measured the intracellular thermal conductivity of HeLa cell with a spatial resolution of about 200 nm. Its mean value of 0.11 Wm-1K-1 determined for the first time is significantly smaller than that of water. Bayesian analysis of the data strongly supports the existence of variation of the intracellular thermal conductivity of about 40%. These results present a major milestone towards understanding the intracellular heat transfer phenomena at nanoscale.

cell biology↗

bioRxiv2020

Single cell transcriptome analysis defines novel heterogeneity within the pancreatic ductal tree

Lineage tracing using genetically engineered mouse models is an essential tool for investigating cell-fate decisions of progenitor cells and biology of mature cell types, with relevance to physiology and disease progression. To study disease development, an inventory of an organs cell types and understanding of physiologic function is paramount. Here, we performed single-cell RNA sequencing to examine heterogeneity of murine pancreatic duct cells, pancreatobiliary cells, and intrapancreatic bile duct cells. We describe an epithelial-mesenchymal transitory axis in our three pancreatic duct subpopulations and identify SPP1 as a regulator of this fate decision as well as human duct cell de-differentiation. Our results further identify functional heterogeneity within pancreatic duct subpopulations by elucidating a role for Geminin in accumulation of DNA damage in the setting of chronic pancreatitis. Our findings implicate diverse functional roles for subpopulations of pancreatic duct cells in maintenance of duct cell identity and disease progression and establish a comprehensive road map of murine pancreatic duct cell, pancreatobiliary cell, and intrapancreatic bile duct cell homeostasis. SIGNIFICANCEMurine models are extensively used for pancreatic lineage tracing experiments and investigation of pancreatic disease progression. Here, we describe the transcriptome of murine pancreatic duct cells, intrapancreatic bile duct cells, and pancreatobiliary cells at single cell resolution. Our analysis defines novel heterogeneity within the pancreatic ductal tree and supports the paradigm that more than one population of pancreatic duct cells harbors progenitor capacity. We identify and validate unique functional properties of subpopulations of pancreatic duct cells including an epithelial-mesenchymal transcriptomic axis and roles in chronic pancreatic inflammation.

bioinformatics↗