Biology subjects

Chen, J.-F.

Publications and source records attributed to Chen, J.-F..

12 recordsLinked to original sources

bioRxiv2026

Periosteal and periarticular compartments house lymphatic vessels in bone

The anatomical localization of lymphatic vessels in bone remains controversial and has led to conflicting interpretations of skeletal lymphatic function. Here we assessed lymphatic identity and localization in bone using mouse genetic labeling, tissue clearance, and three-dimensional imaging. We analyzed long bones after extensive periosteum removal and identified Vegfr3+ blood vessels lacking Lyve1 expression within bone marrow, whereas Vegfr3+Lyve1+ lymphatic vessels were confined to residual periosteal regions. Genetic lineage tracing using Prox1-Cre/ER;mScarlet further confirmed that lymphatic vessels are absent from long bone marrow and restricted to periosteal compartments, particularly in fibrous but not cambial layers. Extending these analyses to the mandible, we observed Vegfr3+Lyve1+ lymphatic vessels localized to periarticular soft tissues surrounding the temporomandibular joint (TMJ), while mandibular bone marrow contained only Vegfr3+Lyve1- blood vessels and lacked Prox1 lineage-traced lymphatic vessels. Together, these findings establish that lymphatic vessels in bone are confined to periosteal and periarticular compartments and absent from bone marrow, providing a framework for interpreting lymphatic contributions to skeletal physiology and disease.

cell biology↗

bioRxiv2026

Distinct Biological and Biomechanical Features in TMJ and Knee Cartilages

The temporomandibular joint (TMJ) and the knee joint are two of the most frequently used joints in the body, with the mandibular condylar cartilage (MCC) and the articular cartilage (AC) covering the joint bone surfaces, respectively. Compromised MCC functions lead to various temporomandibular disorders (TMD), including TMJ osteoarthritis (TMJ OA); however, the mechanisms governing MCC homeostasis and its biomechanical properties are still poorly understood. In this study, we comprehensively compared the biological and biomechanical features of the MCC and AC in mice. Histological analysis on P1, P21, 3-month, and 10-month mice revealed the most drastic structural differences between MCC and AC at occlusion establishment (P21), with MCC found to be more susceptible to age-associated cartilage degeneration. Immunostaining revealed differentially distributed cartilage extracellular matrix components in MCC and AC, including collagen type I, II, and X, and highly enriched expression of several key transcriptional factors at the posterior region of the MCC, including sex determining region Y-box 9 (SOX9), runt-related transcription factor 2 (RUNX2), and scleraxis (SCX). The posterior MCC also houses a group of long-lasting, slow-proliferative cells, as evidenced by the BrdU/EdU incorporation assay, suggesting the presence of a potential stem/progenitor cell niche at the posterior TMJ. Unbiased nanoindentation analysis revealed distinct biomechanical features between these joint cartilages. MCC exhibits a significantly lower elastic modulus (EIT) than AC, with the highest EIT observed at the anterior TMJ, which is oppositely associated with the fibrous layer thickness, but positively correlated with the ratio of the collagen type X-positive matrix in the cartilaginous layer. Altogether, this study provides a basic understanding of the biological and biomechanical features of the cartilaginous tissues in two important joints, which may facilitate our understanding of the physiology in the TMJ and knee joint, and support the applications of mouse models to study TMJ dysfunctions.

developmental biology↗

bioRxiv2025

Integrated histopathologic modeling of detailed tumor subtypes and actionable biomarkers

Accurate cancer subtyping with accompanying molecular characterization is critical for precision oncology. While machine learning approaches have been applied to both digital pathology and cancer genomics, previous work has been limited in sample size and has typically aggregated granular cancer subtypes into coarse groupings, likely obfuscating informative molecular and prognostic associations and phenotypic variation of more detailed tumor subtypes. Accordingly, we collated 378,123 hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) with matched targeted DNA clinical sequencing results and OncoTree detailed cancer subtypes from a real-world cohort of 71,142 patients. Using this scaled, granular dataset and a cancer subtype knowledge graph, we developed Mosaic: a family of calibrated machine learning models using H&E WSI embeddings to classify tumors and identify molecular phenotypes across 163 detailed subtypes. The cancer subtyping module (Aeon) achieved an area under the receiver operating characteristic curve (AUROC) of 0.992 overall, with 161/163 subtypes reaching an AUROC [≥] 0.90 and improved performance over a state-of-the-art genomics-based classifier. The genomic inference module (Paladin) achieved an AUROC [≥] 0.80 for 167 pairs of detailed subtypes and genomic targets. We further used the learned histopathologic representations to i) identify key associations of the histopathologic embeddings with clinical biomarkers; ii) identify unsupervised sub-clusters of tumors with genomic determinants of tumor phenotype; iii) specify granular diagnoses for cancers of unknown primary, evaluated by genomic associations and expected clinical outcome distributions; iv) annotate functional significance for variants of uncertain significance (VUS); and v) identify cases that mimic the phenotypic effect of known DNA variants on H&E in the absence of detectable DNA alterations. Taken together, this work advances our understanding of phenotypic variation of granular tumor subtypes, their relevance to enhanced diagnostics, and their potential utility in risk stratification with multimodal machine learning in cancer.

cancer biology↗

bioRxiv2025

StCEL-based platform enables detection and sequencing of native sialoglycoRNA

Glycosylated RNAs (glycoRNAs) are an emerging class of biomolecules characterized by glycans attached to RNA molecules. Currently, glycoRNA detection remains largely confined to cellular models, substantially impeding its functional characterization and clinical translation. Here, we developed sialyltransferase-mediated chemical enzymatic labeling (StCEL), in which azido-modified sialic acid was transferred to the natural sialic acid on sialoglycoRNA, enabling the detection of native sialoglycoRNA across diverse biological samples with high specificity and sensitivity. Using StCEL, we found that sialoglycoRNA was significantly upregulated in multiple cancer types. StCEL combined with a microplate reader was applied to detect sialoglycoRNA in large-scale samples, revealing that elevated sialoglycoRNA levels correlate positively with tumor malignancy and poor patient prognosis. Furthermore, StCEL-based sialoglycoRNA enrichment and sequencing identified dysregulated sialoglycoRNAs in tumor tissues. Collectively, StCEL establishes a multifunctional platform that enables sensitive and specific detection of sialoglycoRNA, alongside sequencing analysis, demonstrating significant potential for clinical translation.

molecular biology↗

bioRxiv2024

Tcf12 controls dynamic calvarial bone growth and motor learning in mice

Heterozygous loss-of-function mutations of TCF12 and TWIST1 can each cause craniosynostosis and neurodevelopmental delay in humans. Twist1-Tcf12 interaction plays an important role in regulating suture development. Although the molecular and cellular mechanisms underlying craniosynostosis and neurocognitive dysfunctions in Twist1+/- mice have been studied, less information on the role of Tcf12 in these defects is available. To investigate the functional mechanism of Tcf12 in regulating skull and brain development, we analyzed the skull shape of Wnt1-Cre;Mesp1-Cre;Tcf12fl/fl mice and found that, despite mild coronal synostosis, their skull shape appears to be similar to that of controls. We also found evidence of impaired motor learning ability in Tcf12 mutant mice. Furthermore, loss of Tcf12 in neural crest lineage leads to upregulated Runx2 expression in the calvarial mesenchyme and posterior expansion of the frontal bone in Wnt1-Cre;Tcf12fl/fl mice. Mechanistically, we show that Lmx1b is a direct downstream target of Tcf12 for the regulation of osteogenic differentiation in the calvarial mesenchyme during embryonic development. Importantly, overexpression of Lmx1b inhibits osteogenic differentiation in the calvarial mesenchyme of Wnt1-Cre;Tcf12fl/fl mice, indicating Tcf12s regulation of Lmx1b expression is crucial for controlling osteogenesis during calvarial bone development. Our study suggests that Tcf12 expression in the brain is crucial for motor learning. Moreover, this study establishes a new molecular mechanism underlying regulation of calvarial bone formation. Author SummaryCraniosynostosis is characterized by premature fusion of cranial sutures and associated with abnormal skull growth, delayed brain development, and often impaired brain functions. Loss-of-function mutation of TCF12 can cause coronal synostosis and neurodevelopmental delay in humans. In developing mouse sutures, Tcf12 is essential for maintaining the boundary between sutural and osteogenic cells. However, roles of Tcf12 in skull formation and brain development have not been fully investigated. In this study, we show that loss of Tcf12 leads to brain abnormalities even in the absence of coronal synostosis and that frontal bone expansion results from upregulated osteogenic differentiation in the calvarial mesenchyme in mice. Furthermore, we identify Lmx1b as a downstream target of Tcf12 for the regulation of osteogenic differentiation in the calvarial mesenchyme during frontal bone development. Our findings highlight the role of Tcf12 in the development of calvarial bones and provide new insight into molecular mechanisms for regulation of calvarial bone formation.

developmental biology↗

bioRxiv2022

Forces driving transposable element load variation during Arabidopsis range expansion

Genetic load refers to the accumulated and potentially life-threatening deleterious mutations in populations. Understanding the mechanisms underlying genetic load variation of transposable elements (TEs), one major large-effect mutations, during range expansion is an intriguing question in biology. Here, we used 1,115 globally natural accessions of Arabidopsis thaliana, to study the driving forces of TE load variation during its range expansion. The TE load increased with range expansion, especially in the recently established Yangtze River basin population. The effective population size explained 62.0% of the variance in TE load, and high transposition rate and positive selection or hitch-hiking effect contributed to the accumulation of TEs in the expanded populations. We genetically mapped the candidate causal genes or TEs and revealed the genetic architecture of TE load. Overall, this study reveals the variation in the genetic load of TEs during Arabidopsis expansion and highlights the causes of TE load variation.

evolutionary biology↗

bioRxiv2021

Classification and clustering of RNA crosslink-ligation data reveal complex structures and homodimers

The recent development and application of methods based on the general principle of "crosslinking and proximity ligation" (crosslink-ligation) are revolutionizing RNA structure studies in living cells. However, extracting structure information from such data presents unique challenges. Here we introduce a set of computational tools for the systematic analysis of data from a wide variety of cross-link-ligation methods, specifically focusing on read mapping, alignment classification and clustering. We design a new strategy to map short reads with irregular gaps at high sensitivity and specificity. Analysis of previously published data reveals distinct properties and bias caused by the crosslinking reactions. We perform rigorous and exhaustive classification of alignments and discover 8 types of arrangements that provide distinct information on RNA structures and interactions. To deconvolve the dense and inter-twined gapped alignments, we develop a network/graph-based tool CRSSANT (Crosslinked RNA Secondary Structure Analysis using Network Techniques), which enables clustering of gapped alignments and discovery of new alternative and dynamic conformations. We discover that multiple crosslinking and ligation events can occur on the same RNA, generating multi-segment alignments to report complex high level RNA structures and multi-RNA interactions. We find that alignments with overlapped segments are produced from potential homodimers and develop a new method for their de novo identification. Analysis of overlapping alignments revealed potential new homodimers in cellular noncoding RNAs and RNA virus genomes in the Picornaviridae family. Together, this suite of computational tools enables rapid and efficient analysis of RNA structure and interaction data in living cells.

bioinformatics↗

bioRxiv2021

Atp13a5 Marker Reveals Pericytes of The Central Nervous System in Mice

Perivascular mural cells including vascular smooth cells (VSMCs) and pericytes are integral components of the vascular system. In the central nervous system (CNS), pericytes are also known as the guardian of the blood-brain barrier, blood-spinal cord barrier and blood-retinal barrier, and play key roles in maintaining cerebrovascular and neuronal functions. However, the functional difference between CNS and peripheral pericytes has not been resolved at the genetic and molecular levels. Hence, the generation of reliable CNS pericyte-specific models and genetic tools remains very challenging. Here, we report a new CNS pericyte marker in mice. This cation-transporting ATPase 13A5 (Atp13a5) marker is highly specific to the pericytes in brain, spinal cord and retina. We generated a transgenic model with a knock-in tdTomato reporter and Cre recombinase. The tdTomato reporter reliably labels the CNS pericytes, but not found in any other CNS cell types including closely related VSMCs, or in peripheral organs. More importantly, Atp13a5 is turned on at embryonic day E15, suggesting brain pericytes are shaped by the developing neural environment. We hope that the new tools will allow us to further explore the heterogeneity of pericytes and achieve a better understanding of CNS pericytes in health and diseases.

neuroscience↗

bioRxiv2020

Optimized photochemistry and enzymology enable efficient analysis of RNA structures and interactions in cells and virus infections

Direct determination of RNA structures and interactions in living cells is critical for understanding their functions. Current crosslinking and proximity-ligation approaches are fundamentally limited due to inefficient RNA crosslinking, purification and high-level photochemical damages. Here we present PARIS2 (psoralen analysis of RNA interactions and structures, second generation), a re-invented method for capturing RNA duplexes in cells with three orders of magnitude improved efficiency. PARIS2 captures ribosome small subunit (SSU) binding sites on mRNAs, reporting translation status on a transcriptome wide scale, and captures spliceosomal snRNP binding sites on various RNA targets. We determine the RNA genome structure of enterovirus D68, a re-emerging viral pathogen associated with severe neurological symptoms, and discover alternative conformations in the internal ribosome entry site (IRES) that controls translation initiation. Together, these results reveal new aspects of RNA photochemistry and enzymology, and enable highly efficient interrogation of the RNA structurome and interactome in cells.

genomics↗

bioRxiv2020

Microvascular Injury in Mild Traumatic Brain Injury Accelerates Alzheimer-like Pathogenesis in Mice

IntroductionTraumatic brain injury (TBI) is considered as the most robust environmental risk factor for Alzheimers disease (AD). Besides direct neuronal injury and neuroinflammation, vascular impairment is also a hallmark event of the pathological cascade after TBI. However, the vascular connection between TBI and subsequent AD pathogenesis remains underexplored. MethodsWe established a closed-head mild TBI (mTBI) model in mice with controlled cortical impact, and examined the time courses of microvascular injury, blood-brain barrier (BBB) dysfunction, gliosis and motor function impairment in wild type C57BL/6 mice. We also determined the brain clearance of {beta}-amyloid, as well as amyloid pathology and cognitive functions after mTBI in the 5xFAD mouse model of AD. ResultsmTBI induced microvascular injury with BBB breakdown, pericyte loss and cerebral blood flow reduction in mice, which preceded gliosis. mTBI also impaired brain amyloid clearance via the vascular pathways. More importantly, mTBI accelerated amyloid pathology and cognitive impairment in the 5xFAD mice. DiscussionOur data demonstrated that microvascular injury plays a key role in the pathogenesis of AD after mTBI. Therefore, restoring vascular functions might be beneficial for patients with mTBI, and potentially reduce the risk of developing AD.

neuroscience↗

bioRxiv2018

Using the modified male osteoporosis self-assessment tool for Taiwan to predict osteoporosis onset - a sub-study of the Taiwan osteoporosis survey

PurposeTo develop a risk index by item reduction from multiple variable regression, which can identify male Taiwanese patients at risk of developing osteoporosis.\n\nMethodsTo develop the model, a risk index was identified by item reduction from multivariate regression analysis. Using receiver operating characteristic (ROC) curve analysis and their sensitivity/specificity, MOSTAi was validated in a separate cohort of Taiwanese men and its performance with compared with the National Osteoporosis Foundation recommendations (NOF 2013).\n\nResultsBetween 2008 and 2011 a total of 4,323 males were enrolled for bone mineral density (BMD) measurements. Univariate analysis identified four major risk factors for osteoporosis, including age, body weight (BW), previous fracture and body height. The ROC analysis showed the area under the curve (AUC) for the model based on the three-variable, two-variable (age and BW), and one-variable models (BW), was 0.701 (p<0.001, 95% confidence interval [CI] 0.658-0.744), 0.700 (p<0.001, 95% CI, 0.656-0.742), and 0.690 (p<0.001, 95% CI, 0.646-0.734), respectively. Using the optimal cutoff value (-2) for the OSTA, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) in the validation cohort were 64.0%, 65.7%, 26.9% and 90.2%, respectively. The ROC curves for predicting osteoporosis by MOSTAi, OSTA and NOF 2013 and the AUC for MOSTAi, OSTA and NOF 2013 was 0.706 (p<0.001, 95% CI: 0.664-0.748) and 0.697(p<0.001, 95% CI: 0.657-0.738), respectively.\n\nConclusionThe results showed that MOSTAi could be a more precise model than OSTA and NOF 2013, for identifying men in Taiwan with osteoporosis who require referrals for DXA scans. It was demonstrated that MOSTAi is a simple tool with fair sensitivity/specificity and PPV, and high NPV. MOSTAi could also be a more accurate model than OSTA for identifying men in Taiwan at risk of osteoporosis. In comparison with NOF 2013, MOSTAi is a more accurate and simpler tool for the referral of Taiwanese men for DXA scans.

immunology↗

bioRxiv2017

Forward-reverse mutation cycles between stages of cancer development

Earlier, prominent occurrences of interstitial loss-of-heterozygosities (LOHs) were found in different cancers as a type of single-nucleotide-variations (SNVs), at rates far exceeding those of the commonly investigated gain-of-heterozygosities (GOHs) type of SNVs. Herein, such co-occurrences of LOHs and GOHs were confirmed in 102 cases of four cancer types analyzed with three different next-generation sequencing platforms, comparing non-tumor, paratumor, and tumor tissues with white-blood-cell controls; and in 246 pan-cancer cases of whole-genome tumor-control pairs. Unexpectedly, large numbers of SNVs enriched with CG>TG GOHs and copy-number-variations (CNVs) proximal to these GOHs were detected in the non-tumor tissues, which were extensively reversed in paratumors showing prominent TG>CG LOHs with proximal CNVs, and less so in tumors to form forward-reverse mutation cycles. Lineage effects in the reversions, likely resulting from directional selection, supported a sequential rather than parallel mode of evolution as described in a Stage Specific Populations model of cancer development.

cancer biology↗