Biology subjects

Yang, H.

Publications and source records attributed to Yang, H..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

MS4MS: LLMs-driven Multi-agent System for Small-molecule Identification via LC-MS/MS

Small molecule identification is central to research fields such as drug discovery, but in complex systems like Traditional Chinese Medicine (TCM), traditional mass spectrometry analysis methods remain constrained by bottlenecks including insufficient database coverage, fragmented analysis workflows, and poor result interpretability. To address these limitations, we developed MS4MS, a large language model-driven multi-agent system that enables an end-to-end automated pipeline from raw data to small molecule identification. Validation on a public benchmark demonstrates that MS4MS achieves state-of-the-art performance in molecular formula prediction. Furthermore, its innovative small molecule identification agent enables efficient and interpretable compound elucidation. Verification using herbal extracts indicates MS4MSs outstanding performance regarding analytical coverage and the discrimination of isomers. Consequently, MS4MS offers a novel, accurate, interpretable, and high-throughput end-to-end automated strategy for small molecule identification, overcoming the analytical bottlenecks of traditional mass spectrometry in natural products and complex TCM systems.

bioinformatics↗

bioRxiv2025

The Emergence of Novel Versus Known Three-Dimensional Structures from Random Sequences.

It has been hypothesized that while random sequences are unlikely to fold into proteins of the length of globular proteins, repeated random sequences are more likely to adopt stably folded structures, with implications for molecular evolution. We used structure prediction methods to determine the foldability of approximately 120-residue sequences composed of 5-to 60-residue random repeats. With repeats of less than 30-residues, sequences were frequently discovered (1-12%) that fold with high confidence. For less than 60-residue repeats, we frequently observe {beta}-solenoids, similar to those seen in natural proteins. We observe solenoids stabilized by apolar packing as well as ones stabilized by polar interactions with Ca2+ in the core of the structure as in natural RTX domains. Helical bundles were observed with high frequency when insertions or deletions (INDELs) were included between blocks of repeating sequences. We also observed a new super-secondary structure consisting of a tightly wound -helical screw, and experimentally confirmed its stability and structure by CD spectroscopy and X-ray crystallography. Thus, structure predictors can discover structures that are well out of the distribution of the data upon which they were trained. Beyond 40-residue repeat lengths very few sequences were predicted to fold. The small number of structures we observed were representative of well-established major classes of tertiary structures; greater sampling would be needed to discover novel structures from a random distribution. These studies illuminate dark matter regions of protein structure space and support previous predictions that proteins evolved through the assortment of shorter peptide sequences. Significance statementThe availability of powerful and accurate programs for predicting protein three-dimensional structures enables one to ask fundamental questions concerning the origin of folded functional proteins during evolution. We show that 120-residue proteins composed of random sequences repeated in tandem are predicted to be much more likely to fold than fully random proteins. These studies validate previous predictions that proteins evolved through the repetition and assortment of short peptide sequences. Also, some of the predicted structures represent novel conformations, which were confirmed experimentally. These findings advance our understanding of molecular evolution and have implications for design of novel proteins.

biophysics↗

bioRxiv2025

Defective insulin clearance plays a primary role in the pathogenesis of chronic kidney disease in mice with null deletion of Ceacam2 gene

Endogenous insulin clearance occurs primarily in hepatocytes and to a lower extent in kidneys proximal tubule cells (KPTCs). CEACAM1 promotes receptor-mediated insulin uptake to be degraded in hepatocytes in a phosphorylation-dependent manner. Its deletion/inactivation causes hyperinsulinemia-driven insulin resistance, steatohepatitis and liver fibrosis. CEACAM2, the dominant CEACAM protein in murine KPTCs, shares a high homology with CEACAM1. Thus, we examined whether it regulates renal insulin disposal to maintain renal homeostasis. KPTCs derived from Ceacam2 null mice (Cc2-/-) exhibited lower receptor-mediated insulin uptake. Combined with the gradual decline in CEACAM1-dependent hepatic insulin clearance, impaired renal insulin clearance contributed to chronic hyperinsulinemia and insulin resistance starting at 10 months of age in Cc2-/-males. This was followed by proteinuria and reduced glomerular filtration rate in association with glomerulosclerosis and tubulointerstitial damage. Increased collagen deposition in Cc2-/- kidneys could be mediated in part, by hyperinsulinemia-driven activation of the 5{beta}1 integrin-focal adhesion kinase (FAK) signaling pathways. Together, the data demonstrated that loss of CEACAM2 impaired renal insulin clearance that contributed to hyperinsulinemia and resultant insulin resistance, followed by kidney dysfunction and renal fibrosis. This study provided an in vivo demonstration of the regulation of kidney function by insulin clearance along the liver-kidney axis.

physiology↗

bioRxiv2025

Nuclear factor kappa B subunits and IkappaB family are modulated in the ovine endometrium during early pregnancy

Pregnancy modulates the endometrial immune responses to establish maternal immune tolerance, and nuclear factor kappa B (NF-{kappa}B) subunits and I{kappa}B family are involved in the maternal innate and adaptive immune responses. It, nevertheless, is unclear if early pregnancy regulates the expression of NF-{kappa}B subunits and inhibitor of NF-{kappa}B (I{kappa}B) family in the ovine endometrium. In this study, ovine endometria were sampled at day 16 of the estrous cycle (N16), and at days 13, 16, and 25 of pregnancy (P13, P16, and P25), and mRNA and protein expression of NF-{kappa}B subunits and I{kappa}B family was analyzed by RT-qPCR, western blot, and immunohistochemistry. The results revealed that the expression of all NF-{kappa}B subunits was decreased at P25 compared with N16 both in mRNA and protein expression, but the expression of B cell leukemia-3, I{kappa}B, I{kappa}B kinase {gamma}, and I{kappa}B{delta} was increased at P25 compared with N16 both in mRNA and protein expression. I{kappa}B{beta}, however, was downregulated during early pregnancy, and the expression of I{kappa}B{varepsilon} and I{kappa}B{zeta} was decreased at P13 and P16 compared with N16 and P25 both in mRNA and protein expression. In summary, early pregnancy changed the expression of NF-{kappa}B subunits and I{kappa}B family in the ovine endometrium both in mRNA and protein expression, which may be essential for maternal immune tolerance and embryo implantation.

immunology↗

bioRxiv2025

Developmental deviations of structural connectivity in youths with ADHD predict symptom and treatment outcomes

Attention-deficit/hyperactivity disorder (ADHD) lacks validated biomarkers to track symptom development or guide treatment selection in youth. We quantified individual deviations from normative age-related trajectories of white-matter structural connectivity (SC) across two independent cohorts: 6,687 typically developing and 1,114 ADHD scans from the ABCD study, and 292 typically developing and 482 ADHD participants from a Chinese cohort. Youth with ADHD showed pronounced SC deviations, especially in higher-order association pathways. A subset of connections showed ADHD-specific developmental reductions in deviations beyond typical developmental patterns, and these changes mediated the age-related decline in ADHD symptoms. Longitudinal within-individual analyses demonstrated that decreases in deviation over two years tracked symptom improvement. Baseline deviations also predicted 12-week treatment response to atomoxetine, but not methylphenidate, and follow-up imaging revealed treatment-related reductions in deviation. Together, these findings identify SC deviation as a robust developmental biomarker with prognostic and theragnostic relevance for ADHD, supporting precision care through risk stratification, individualized pharmacotherapy selection, and objective monitoring of treatment effects.

neuroscience↗

bioRxiv2025

OSM-11 modulates salinity-stress tolerance in Caenorhabditis elegans

Most terrestrial animals exhibit narrow salinity tolerance compared to their marine counterparts. Previous studies identified osm-11 (which encodes a Notch co-ligand) mutations as a driver of hyper-saline tolerance in Caenorhabditis elegans, but mechanistic insights remained unclear. This study employs RNA sequencing and CRISPR/Cas-9 genome editing to demonstrate that osm-11 mutations enhance salinity stress resistance through up-regulation of fatty acid metabolism (acdh-12, acs-17) and cytochrome P450 pathways (ugt-15), while suppressing calcium signaling. Furthermore, we demonstrated that acdh-12 mutation impairs salinity-stress tolerance by activating ferroptosis and mitophagy, accompanied by down-regulated oxidative phosphorylation and up-regulated autophagic pathways. Morphological observations show that mitochondrial fragmentation contributes to wild-type nematode mortality under high salinity, while enlarged lipid droplets in wild-types correlate with reduced {beta}-oxidation gene expression (dhs-28, daf-22), whose knockout disrupts tolerance in mutants. These findings unravel the multi-pathway regulatory network of osm-11-mediated salinity tolerance, providing mechanistic insights for developing protective strategies against environmental salinity stressors impacting animal survival.

genetics↗

bioRxiv2025

Multimodal AI Decodes Extreme Environment Functional Dark Matter Beyond Homology

Functional annotation of proteins from extreme environments represents a major bottleneck for bioresource discovery, as a vast reservoir of functional dark matter defies existing homology-based methods. We demonstrate that environmental pressures impart conserved physicochemical energy signatures that co-determine protein function with sequence and structure. Here we developed ACCESS, a multimodal graph neural network employing hierarchical contrastive learning with a tailored label-sample co-embedding to fuse energy, sequence, and structural information and overcome homology scarcity. ACCESS surpasses state-of-the-art methods including BLASTp and CLEAN in annotating low-identity enzymes. Applied to extreme environmental metagenomics, we constructed a function map of extremophile enzymes to expand the biocatalyst library, pinpointed functionally critical residues to guide rational design, and enabled large-scale, function-based macro-evolutionary analyses. This paradigm transcends the limitations of homology, illuminating protein dark matter and accelerating the exploration of the biospheres functional diversity for applications in biotechnology and therapeutic development.

bioinformatics↗

bioRxiv2025

Sensory neuronal mTORC1 signaling establishes neuroimmune memory that initiates allergic immunity

Environmental allergens are enriched in protease activity, a feature that directly activates cutaneous sensory neurons, triggering itch and Substance P release, which promotes Th2-skewing CD301b+ dendritic cell migration and initiates allergic immunity. However, allergens are typically encountered as repeated, subthreshold exposures, and how these cumulatively induce sensitization is unknown. We identify a sensory neuron-intrinsic mechanism of neuroimmune memory that enables this process. Initial activation by protease allergens induces sustained mTORC1 signaling and PGC-1-associated mitochondrial remodeling, establishing a metabolically primed state that amplifies neuroimmune responses upon allergen re-exposure. This heightened state, independent of adaptive immunity, drives enhanced itch, increased CD301b+ dendritic cell migration, and augmented Th2 differentiation. Disrupting neuronal mTORC1 signaling or mitochondrial stability abrogates this amplification while leaving primary responses intact. Importantly, this mechanism generalizes across distinct protease allergens, revealing mTORC1-driven metabolic reprogramming in sensory neurons as a form of innate neuroimmune memory underlying allergen cross-sensitization and polysensitization.

immunology↗

bioRxiv2025

A BCG toxic effector induces mitochondrial DNA compaction to refrain protective immunity

Innate immune memory typically emphasizes nuclear chromatin remodeling that determines transcriptional memory in monocytes and macrophages. Here, we show that compaction of mitochondrial DNA (mtDNA), governed by mitochondrial transcription factor A (TFAM) abundance and mtATP-dependent remodeling, defines the transcriptional and functional state of trained macrophages. While typical pathogen-associated molecular pattern (PAMPs) triggered mtDNA accessibility, Bacillus Calmette-Guerin (BCG) effector PE18 directly interacted with and activated SLC25A5 to reduce mtATP levels, thereby inhibiting TFAM degradation by AFG3L2. Accumulated TFAM restricts mtDNA accessibility, suppressing the transcription of the mtNd1 and thereby reducing mtNd1-mediated mtROS production, which diminishes the trained capacity of macrophages against secondary infections. Notably, BCG{Delta}pe18 maintains macrophages cytokine transcriptional capacity independent of classical nuclear histone modifications. Moreover, BCG{Delta}pe18 provides robust and lifelong protective immunity against Mycobacterium tuberculosis (Mtb) infection. These findings reveal mitochondrial genome as a regulatory entity in trained immunity, and suggest a potential strategy for improving vaccine performance.

immunology↗

bioRxiv2025

A multi-tissue atlas of genetic regulatory effects in sheep

Characterizing the impact of genomic variants on genome function and ultimately complex traits in livestock is essential for the development of sustainable precision agriculture and comparative genomics. Here, as part of the Farm animal Genotype-Tissue Expression (FarmGTEx) project, we present the pilot phase of the SheepGTEx resource through analyzing 6,761 RNA-sequencing samples of 51 primary tissues in a multi-breed population of sheep. We identify millions of regulatory variants associated with seven types of molecular phenotypes, and fine-map 322,468 primary and 114,017 non-primary effects, revealing a high degree of regulatory allelic heterogeneity. We systematically characterize the pleiotropic effects of these variants on molecular phenotypes, assess their context-specific regulatory patterns across tissues, breeds, sexes, and developmental stages, as well as explore their evolutionary constraints across mammals. Finally, we demonstrate the substantial potential of the SheepGTEx resource (https://sheepgtex.farmgtex.org), by providing examples of regulatory mechanisms underpinning 34 complex traits, population divergence between European and Asian breeds, and adaptive evolution in sheep over the past ten millennia.

genomics↗

bioRxiv2025

Evolutionary landscape of oral microbiome over 100,000 years

The human oral microbiome represents an intimate and enduring partnership between host and microbial communities, yet its evolutionary trajectory across deep time remains largely uncovered. Here we reconstruct the global history of the oral microbiome over 102,400 years using a global collection of 1854 oral samples spanning 61 countries. We reveal that major cultural transitions of the Neolithic Revolution, industrialization, and recent medical advances have driven a directional, globally coordinated co-evolution of oral microbial ecology, function, and population structure. Network analysis identifies two universal microbial modules of dental calculus modules: the commensal-enriched DCM1 module and the pathogen-enriched DCM2, both exhibiting progressive ecological polarization. DCM2 surged around 4,000 years ago with agricultural intensification but subsequently declined in modern European populations while persisting at high levels in African and some American groups, a geographic divide mirroring socioeconomic inequities. Species-level analyses demonstrate widespread directional changes, with obligate anaerobes declining as aerotolerant taxa expand, reflecting a carbohydrate-associated functional remodeling toward starch metabolism. Phylogenomic reconstruction reveals contrasting evolutionary trajectories. Pauljensenia mediterranea experienced near-extinction following a severe bottleneck, while Actinomyces israelii underwent a selective sweep with rapid population expansion 1,000 years ago. Critically, the oral resistome has accelerated in the antibiotic era, resulting in [~]33-50-fold surge of highly mobile, clinically relevant antimicrobial resistance genes in the last century, with Streptococcus acting as a central hub of dissemination. Collectively, these results position the oral microbiome as an active participant that has co-evolved with human subsistence, urbanization and medical practice, with direct implications for global oral health, antimicrobial resistance and interventions aimed at restoring resilient microbial states.

microbiology↗

bioRxiv2025

Development and validation of an ultra-low-cost, open source normothermic ex vivo organ perfusion platform

BackgroundNormothermic ex vivo organ perfusion (NEVOP) promises to catalyze organ preservation, therapeutic discovery, and organ-specific disease modeling. Existing technology platforms remain inaccessible for research due to restricted access to commercial organ perfusion devices, high costs of both devices and proprietary consumables, and steep technical learning curves. Additionally, the available technology is not optimized to perfuse smaller organs such as the kidney. MethodsTo overcome these barriers, a custom NEVOP circuit was developed using recycled, repurposed, and low-cost components. Porcine kidneys and autologous blood were used to iteratively optimize circuit design. A porcine kidney autotransplantation protocol was adapted to evaluate in vivo kidney function after ex vivo perfusion. To pilot the flexibility of this system as a multi-organ platform for ex vivo human biology, non-transplantable human donor kidney, spleen, and pancreas specimens were stably perfused using human blood products and analyzed. ResultsAn ultra low-cost NEVOP system engineered to perfuse porcine kidneys and diverse human organs (kidney, pancreas, and spleen) sustained viable organs for up to 24 hours with evidence of both function and viability. Key innovations included a parallel flow resistor to facilitate low-flow perfusion in non-heparinized organs and a containment bag with adjustable magnets to provide vascular stability and recycling of venous overflow. The circuit costs less than 1,500USD to construct, and porcine kidneys perfused for 24 hours on this platform demonstrated healthy in vivo function upon autotransplantation. ConclusionsCustom NEVOP platforms constitute novel and potentially transformative research platforms which use low-cost and readily available materials. Paired with access to non-transplantable research organs from altruistic donors, this model provides a road map for investigators to advance biomedical discovery and human ex vivo biology.

bioengineering↗

bioRxiv2025

Histology-informed spatial domain identification through multi-view graph convolutional networks

Identifying spatial domains is crucial in spatial transcriptomics, yet effectively integrating gene expression, spatial location, and histology remains challenging. We present STESH, a Spatial Transcriptomics clustering method that combines Expression, Spatial information and Histology. STESH extracts histological features using a convolutional neural network and generates expression, histology, spatial, and collaborative convolution modules for a multi-view graph convolutional network with a decoder and attention mechanism. We evaluated STESH on multiple tissue types and technology platforms. STESH consistently outperformed ten state-of-the-art methods, achieving superior clustering accuracy with the highest scores in adjusted Rand index, normalized mutual information, and Fowlkes-Mallows index.

bioinformatics↗

bioRxiv2025

SAMHD1 promotes SARS-CoV-2 infection by enhancing HNF1-dependent ACE2 expression in lung epithelial cells

Sterile alpha motif and HD domain-containing protein 1 (SAMHD1) restricts a board spectrum of viruses through multifaceted mechanisms. It also limits spontaneous- and virus-induced innate immune responses by suppressing proinflammatory cytokine and type-I interferon (IFN-I) production. Some viruses escape SAMHD1 restriction by utilizing SAMHD1-mediated innate immune suppression to establish effective infection through viral antagonism. Our previous studies showed that SAMHD1 is a proviral factor facilitating replication of severe acute respiratory syndrome coronavirus (SARS-CoV-2) in human macrophages, monocytic THP-1 and epithelial-like HEK293T cell lines by suppressing IFN responses. However, it is unclear about the function of SAMHD1 in lung epithelial cells during SARS-CoV-2 infection. Here, we report that SAMHD1 facilitates SARS-CoV-2 replication in lung epithelial Calu-3 cells by enhancing endogenous expression of the viral receptor angiotensin-converting enzyme 2 (ACE2) via hepatocyte nuclear factor 1-alpha (HNF1) and HNF1{beta}. Using pseudotyped SARS-CoV-2 and lentiviral vectors, we found that SARS-CoV-2 spike protein-mediated viral entry was suppressed in Calu-3 cells with SAMHD1 knockout (KO). SAMHD1 KO repressed ACE2 expression in Calu-3 cells at mRNA and protein levels. Functional analyses revealed that HNF1 and HNF1{beta} were crucial for the endogenous ACE2 expression in Calu-3 cells. Additionally, SAMHD1 KO led to a reduction in the expression levels and ACE2-promoting function of HNF1 and HNF1{beta}. Inhibition of IFN antiviral response by baricitinib, a Janus kinase 1 and 2 (JAK 1/2) inhibitor, did not revert the suppression of SARS-CoV-2 in SAMHD1 KO Calu-3 cells. Our findings demonstrate that SAMHD1 facilitates HNF1-mediated ACE2 expression and SARS-CoV-2 replication in Calu-3 cells via a novel mechanism beyond its IFN-suppressive function. Author SummaryDuring viral infection, SAMHD1 acts as a viral restriction factor and a suppressor of the innate immune system, controlling viral replication while also ensuring immune homeostasis. The innate immune suppressive function of SAMHD1 can be proviral for some viruses. SAMHD1 has been shown to facilitate SARS-CoV-2 infection in human macrophages, THP-1 and HEK293T cell lines by promoting IFN antagonism, but its role in lung epithelial cells is unclear. Here, we demonstrated that SAMHD1 promotes SARS-CoV-2 replication in human lung epithelial Calu-3 cells by enhancing expression of the major viral receptor ACE2. We found that SAMHD1 facilitated HNF1-medaited ACE2 expression that was required for spike protein-mediated SARS-CoV-2 entry. However, inhibiting IFN signaling in SAMHD1 KO Calu-3 cells was not sufficient to revert SARS-CoV-2 replication. Our findings shed light on the differential proviral function of SAMHD1 in ACE2 expressing cells and suggest that SAMHD1 can facilitate SARS-CoV-2 infection beyond enhancing IFN antagonism.

microbiology↗

bioRxiv2025

Pan-cancer analysis reveals that tumor microbiomes generate specific epitopes through transcriptional reprogramming

The therapeutic promise of tumor microbial peptides faces a critical safety paradox: tumors and peritumor tissues harbor compositionally similar microbiomes, yet safe immunotherapy demands tumor-specific targeting. We performed comprehensive transcriptomic analysis of microbial communities from 1,868 tumor and peritumor samples across 11 cancer types. Although 88.5% of microbial species are present in both tissue types, tumor and peritumor tissues exhibit profound transcriptional divergence: only 34.1% of microbial genes are expressed in both tissue types, and merely 18.2% of predicted HLA-binding peptides overlap. This transcriptional divergence represents microbial transcriptional reprogramming (MTR) in tumor tissues, through which microbes activate distinct genomic regions while adapting to tumor microenvironmental pressures, thereby generating tumor-specific peptide repertoires. Using Microbial Transcriptional Reprogramming Index (MiTRI) to quantify MTR, we found that higher MiTRI values correlate with expanded immunogenic peptide repertoires. Mass spectrometry-based immunopeptidomics confirmed that 25% of naturally presented microbial peptides originate from MTR regions. Crucially, in microsatellite-stable colorectal cancer, neo-adjuvant therapy responders exhibited significantly higher MiTRI values. T cell receptors (TCRs) recognized MTR-derived epitopes at 2.10-fold higher rates than genome-wide epitopes, accounting for 79.1% of clonally expanded TCRs. These findings establish MTR as the principle that ensures the tumor-specificity and safety of micorbiome-directed immunotherapy.

cancer biology↗

bioRxiv2025

Molecular and cellular dynamics of measurable residual disease progression in myelodysplastic syndromes

Cancer relapse after treatment invariably proceeds from the persistence and progression of measurable residual disease (MRD), an ultrasmall malignant population. Despite the poor prognostic impact established by increasingly sensitive MRD detection methods, the molecular pathways defining MRD remain unknown. To identify the unique features of MRD and the molecular forces shaping its progression, we performed single-cell multi-omic profiling on DNA, RNA and protein layers for a longitudinal patient cohort with relapsed myelodysplastic syndromes (MDS) after stem cell transplantation (SCT), the only curative modality for MDS. We provide a comprehensive molecular portrait of MRD cells with novel markers, shared across genetically heterogeneous patients. MDS relapse after SCT manifested universally with marked phenotypic evolution. Genotype and phenotype analyses revealed MRD progression as a dynamic, evolutionary process rather than a static expansionary one, driven by both subclonal sweeping and cell state transitions. Malignant cells adapted to infiltrating T cells by rewiring IFN-{gamma} responses to activate a key immunoevasive pathway. Our study demonstrates the power of longitudinal, single-cell multi-omic analysis for identifying, tracking, and understanding MRD cells, opening new avenues to target MRD persistence and progression.

cancer biology↗

bioRxiv2025

A spatially-resolved human brain proteome atlas for understanding function and disease

While the brain performs specialized functions across distinct regions, the spatial organization of the human brain proteome remains largely uncharted. Here we present a comprehensive spatially-resolved proteome atlas of the human brain, analyzing over two thousand MRI- guided locations across four individuals. Proteome analysis integrated with transcriptomics reveals extensive post-transcriptional regulation, with cortical regions showing markedly higher protein diversity than transcript. Unsupervised molecular clustering defines distinct brain territories that transcend anatomical boundaries, instead reflecting metabolic demands and functional specialization patterns. Application to epilepsy brain tissue uncovered disrupted astrocyte metabolism, protein homeostasis and therapeutic targets including the seizure-associated purinergic receptor P2RX7. This resource bridges molecular and systems neuroscience to accelerate neurological drug discovery.

neuroscience↗

bioRxiv2025

ctsGRN: Inferring cell type-specific gene regulatory networks in Arabidopsis

Gene regulatory networks (GRNs) govern life processes. And exploring GRNs is of great value for understanding biological functions and developing species resources. At present, studies on plant GRNs are limited, mostly focusing on the tissue level, which hinders the discovery of cell type-specific regulatory networks and mechanisms. To address this, we have proposed a GRN research framework named ctsGRN (CellTypeSpecGRN) for conducting cell-specific GRN research at the cell type resolution. In this framework, we employed three representative algorithms from statistics (e.g., correlation analysis), traditional machine learning (e.g., random forest) and deep learning (e.g., neural networks) to construct GRNs for different cell types in Arabidopsis roots. Among these, traditional machine learning methods showed the best performance. Experimental validation through yeast one-hybrid (Y1H) assays and ChIP-seq data confirmed the high reliability and predictive power of these inferred GRNs. By analyzing these networks, we mined novel cell type-specific regulatory relationships, identified core transcription factor (TF) AT5G08790 involved in root development, discovered 249 cell-type-specific hub TFs, and 136 key functional modules were found to be enriched in biological processes. Additionally, we revealed significant heterogeneity of TF-target gene interactions across various cell types. This comprehensive analysis offers a detailed overview of TF-mediated cell type-specific transcriptional regulation in Arabidopsis roots, providing new insights into the molecular mechanisms of root development and establishing a guideline framework for GRN research at the cell-type level in plants.

bioinformatics↗