Biology subjects

Su, H.

Publications and source records attributed to Su, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Aptamer-Enabled Discovery and Clinical Analysis of Exosomal Surface Biomarkers in Hepatocellular Carcinoma

Exosomal membrane proteins hold promise as cancer biomarkers but face detection challenges due to low abundance and conformational sensitivity. We developed AptEx-ID, a microbead-displayed aptamer platform enabling high- throughput screening of hepatocellular carcinoma (HCC)-specific exosomal surface proteins. Aptamers, selected via competitive binding to tumor-derived versus healthy exosomes, demonstrated high affinity and specificity. Clinical validation using 50 HCC and 30 control plasma samples identified a 7-aptamer panel via machine learning, achieving 93.75% accuracy and 0.95 ROC-AUC. These aptamers further revealed HCC-associated biomarkers (e.g., IMPDH1, ASCC3, GTSE1), validated by siRNA knockdown and biophysical assays. Post-treatment monitoring showed aptamer signal reduction in responsive patients, highlighting their prognostic utility. This platform integrates biomarker discovery, diagnostics, and therapeutic monitoring, offering a robust approach for HCC management through exosomal surface proteome profiling.

molecular biology↗

bioRxiv2025

Neurophysiological Markers of Cancer-Related Fatigue Derived from High-Density EEG

Cancer-related fatigue (CRF) significantly diminishes the quality of life of cancer survivors; however, objective diagnostic markers and the underlying neurophysiological mechanisms remain unclear. This study aimed to identify noninvasive EEG-based biomarkers of CRF by examining cortical activity and functional connectivity. We recorded resting-state and task-related [repetitive submaximal elbow flexions (EFs) until self-perceived exhaustion] high-density electroencephalography (EEG) from 10 cancer survivors with CRF and 14 healthy controls (HC). In our analysis, task-induced fatigue was categorized as mild, moderate, and severe, corresponding to the level of fatigue perceived at the beginning, middle, and end of the task period. Our study revealed the following significant findings: (1) Linear mixed-effects modeling of event-related desynchronization (ERD) EEG analysis during the EF task demonstrated significant effects of group and fatigue levels in the alpha band (8-12 Hz). (2) EF task-specific functional connectivity was estimated using the debiased weighted phase-lag index (dwPLI), which demonstrated reduced inter-regional connectivity in the M1 and prefrontal regions in the CRF group compared with the HC group. (3) The dwPLI analysis identified significantly reduced alpha-band connectivity strength in the CRF group, particularly between the right supramarginal gyrus and other brain regions during mild fatigue. (4) Additionally, resting-state EEG exhibited globally elevated deltaband (1-4 Hz) activity in CRF survivors than HC, potentially reflecting chronic fatigue. These observations emphasize the clinical relevance of resting-state EEG, motor activity-related ERD and functional brain connectivity as potential CRF biomarkers. Future research should validate these findings in larger cohorts and provide insights into more objective CRF diagnosis and the development of personalized interventions for alleviating CRF.

neuroscience↗

bioRxiv2025

Boosting Cellular Longevity Through Intracellular ATP Modulation

Mitochondrial dysfunction and declining ATP production are common features of aging, yet whether ATP availability itself directly regulates cellular lifespan. However, the causal relationship between cellular ATP homeostasis and aging has not been established. Here, we developed a synthetic system to manipulate intracellular ATP independently of endogenous energy production by expressing a plasma membrane-targeted nucleotide transporter, NTT1, from the intracellular parasite Encephalitozoon cuniculi in Saccharomyces cerevisiae. NTT1 expression depleted intracellular ATP in the absence of extracellular ATP, whereas ATP supplementation produced robust NTT1-dependent ATP uptake and increased intracellular ATP abundance. ATP availability strongly influenced replicative lifespan: ATP depletion shortened lifespan, whereas ATP supplementation restored and extended lifespan in NTT1-expressing cells. Unexpectedly, extracellular ATP also extended lifespan in wild-type cells that lack ATP import, revealing an NTT1-independent response to extracellular ATP. Transcriptomic analyses showed that NTT1- mediated ATP import suppresses glucose uptake, carbohydrate catabolism, mitochondrial respiration, and autophagy, whereas extracellular ATP elicits a distinct transcriptional response in wild-type cells involving metabolic, mitochondrial, and signaling pathways. Single-cell aging analyses further showed that ATP supplementation extends lifespan across distinct aging trajectories and shifts cells away from the mitochondrial dysfunction-associated aging state. Finally, experiments in cells lacking mitochondrial DNA separated these effects mechanistically: NTT1-associated lifespan phenotypes and high-ATP toxicity required functional mitochondria, whereas extracellular ATP extended lifespan in wild-type cells independently of mitochondrial respiration. Together, these findings demonstrate that ATP availability is a direct regulator of cellular aging and reveal distinct metabolic and extracellular ATP-responsive routes through which cellular energy state influences longevity. SignificanceCellular energy homeostasis is a crucial factor in determining the health and longevity of organisms. While intracellular ATP levels are tightly regulated, the idea that cells can directly take in extracellular ATP to influence metabolism has not been thoroughly explored. In this study, we engineered yeast cells to import external ATP and demonstrated that this approach significantly alters mitochondrial function, metabolic flow, and aging processes. Our findings show that ATP uptake inhibits catabolic pathways and modulates mitochondrial bioenergetics function, thereby extending cellular lifespan through a novel and non-traditional mechanism. This research reveals an unexpected degree of metabolic flexibility and introduces a synthetic biology-based method to reprogram energy metabolism and longevity. The principles established in this study provide a new framework for understanding the role of cellular bioenergetics in aging, highlighting how the modulation of ATP availability can impact metabolic states and lifespan regulation.

molecular biology↗

bioRxiv2025

BioMaster: Multi-agent System for Automated Bioinformatics Analysis Workflow

MotivationThe rapid expansion of biological data has significantly increased the complexity of bioinformatics workflows, which often involve intricate, multi-step processes. These tasks demand considerable manual effort from bioinformaticians, creating inefficiencies and limiting scalability. Recent advancements in large language model (LLM)-powered agents offer promising solutions to streamline and automate these workflows. However, existing automated systems, while effective for short, well-defined tasks, often struggle with long, multi-step workflows due to challenges such as error propagation, limited adaptability to emerging tools, and the inability of LLMs to generalize to niche bioinformatics tasks. Achieving effective workflow automation requires robust task coordination, dynamic knowledge retrieval, and mechanisms to ensure errors are identified and resolved before they impact downstream processes. ResultsWe present BioMaster, a multi-agent framework designed to automate and streamline complex bioinformatics workflows. BioMaster incorporates specialized agents with role-based responsibilities, enabling precise task decomposition, execution, and validation. It leverages Retrieval-Augmented Generation (RAG) to dynamically retrieve domain-specific knowledge, improving adaptability to new tools and niche analyses. BioMaster also introduces enhanced control over input and output validation to ensure pipeline consistency and employs a memory management strategy optimized for handling long workflows. Experiments across diverse bioinformatics tasks, including RNA-seq, ChIP-seq, single-cell analysis, and Hi-C processing, demonstrate that BioMaster significantly outperforms existing methods in accuracy, efficiency, and scalability. By addressing key limitations in workflow automation, BioMaster offers a robust solution for modern bioinformatics challenges. Availabilityhttps://github.com/ai4nucleome/BioMaster Contactyanlinzhang@hkust-gz.edu.cn

bioinformatics↗

bioRxiv2025

MutBERT: Probabilistic Genome Representation Improves Genomics Foundation Models

MotivationUnderstanding the genomic foundation of human diversity and disease requires models that effectively capture sequence variation, such as single nucleotide polymorphisms (SNPs). While recent genomic foundation models have scaled to larger datasets and multi-species inputs, they often fail to account for the sparsity and redundancy inherent in human population data, such as those in the 1000 Genomes Project. SNPs are rare in humans, and current masked language models (MLMs) trained directly on whole-genome sequences may struggle to efficiently learn these variations. Additionally, training on the entire dataset without prioritizing regions of genetic variation results in inefficiencies and negligible gains in performance. ResultsWe present MutBERT, a probabilistic genome-based masked language model that efficiently utilizes SNP information from population-scale genomic data. By representing the entire genome as a probabilistic distribution over observed allele frequencies, MutBERT focuses on informative genomic variations while maintaining computational efficiency. We evaluated MutBERT against DNABERT-2, various versions of Nucleotide Transformer, and modified versions of MutBERT across multiple downstream prediction tasks. MutBERT consistently ranked as one of the top-performing models, demonstrating that this novel representation strategy enables better utilization of biobank-scale genomic data in building pretrained genomic foundation models. Availabilityhttps://github.com/ai4nucleome/mutBERT Contactyanlinzhang@hkust-gz.edu.cn

bioinformatics↗

bioRxiv2025

Biosynthesis and Bioactivity of Anti-Inflammatory Triterpenoids in Calendula officinalis (pot marigold)

Plants have been central to traditional medicine for millennia, yet the precise metabolites responsible for their therapeutic properties often remain unidentified. Moreover, the low natural abundance and structural complexity of bioactive molecules can hinder their accessibility and chemical synthesis. Here, we investigate the widely reported anti-inflammatory properties of Calendula officinalis (pot marigold), an ancient medicinal herb. We confirm C16-hydroxylated triterpenoids as key contributors to the anti-inflammatory activity of C. officinalis floral extracts and uncover a novel mechanism by which they act in modulating interleukin 6 release. Through biosynthetic pathway elucidation, we demonstrate that the oxidosqualene synthase catalysing the first committed step emerged early in Asteraceae evolution and identify residues governing product specificity. Further, we functionally characterise cytochrome P450s and acyltransferases responsible for downstream modifications. By reconstructing the complete biosynthetic pathway in the heterologous plant chassis Nicotiana benthamiana, we provide a platform for production of the anti-inflammatory components. Our work highlights how integrated studies of bioactivity and biosynthesis can unlock the therapeutic potential of medicinal plants.

plant biology↗

bioRxiv2024

PRMT1-Mediated Metabolic Reprogramming Promotes Leukemogenesis

Copious expression of protein arginine methyltransferase 1 (PRMT1) is associated with poor survival in many types of cancers, including acute myeloid leukemia. We observed that a specific acute megakaryocytic leukemia (AMKL) cell line (6133) derived from RBM15-MKL1 knock-in mice exhibited heterogeneity in Prmt1 expression levels. Interestingly, only a subpopulation of 6133 cells expressing high levels of Prmt1 caused leukemia when transplanted into congenic mice. The PRMT1 inhibitor, MS023, effectively cured this PRMT1-driven leukemia. Seahorse analysis revealed that PRMT1 increased the extracellular acidification rate (ECAR) and decreased the oxygen consumption rate (OCR). Consistently, PRMT1 accelerated glucose consumption and led to the accumulation of lactic acid in the leukemia cells. The metabolomic analysis supported that PRMT1 stimulated the intracellular accumulation of lipids, which was further validated by FACS analysis with BODIPY 493/503. In line with fatty acid accumulation, PRMT1 downregulated the protein level of CPT1A, which is involved in the rate-limiting step of fatty acid oxidation. Furthermore, administering the glucose analogue 2-deoxy-glucose (2-DG) delayed AMKL progression and promoted cell differentiation. Ectopic expression of Cpt1a rescued the proliferation of 6133 cells ectopically expressing PRMT1 in the glucose-minus medium. In conclusion, PRMT1 upregulates glycolysis and downregulates fatty acid oxidation to enhance the proliferation capability of AMKL cells. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC="FIGDIR/small/628174v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1ae96borg.highwire.dtl.DTLVardef@d27916org.highwire.dtl.DTLVardef@ba63corg.highwire.dtl.DTLVardef@cee9af_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Hormone-induced thrombosis is mediated through non-canonical fibrin(ogen) aggregation and a novel estrogen target in zebrafish

Venous thrombosis is a well-known complication of estrogen exposure, with nearly every woman at risk across her lifetime through contraception, pregnancy, or hormone therapy. Although estrogens alter expression of coagulation factors, the mechanisms that mediate estrogen-induced thrombosis are poorly understood, partially due to the absence of an animal model. Identification of these mediators is central to understanding of hormone-induced pathophysiology, could ascertain patients at higher risk for thrombosis, and pinpoint future therapeutic targets. The zebrafish is characterized by external development, high fecundity, optical transparency, and hemostasis is highly conserved with humans. Through a transgenic line that generates GFP-tagged fibrinogen, we show rapid onset of thrombosis after exposure to various estrogens, but not progestins or testosterone. Thrombi are localized to the venous system with evidence for clot contraction. Thrombosis is only partially impeded by anticoagulants, occurs in the absence of factor VII, factor X, and prothrombin, but is dependent on tissue factor and fibrin(ogen). Finally, targeting of all known estrogen receptors does not eliminate thrombosis. The inability to completely inhibit thrombosis through genetic/pharmacologic anticoagulation or estrogen receptor disruption suggests mechanisms different from canonical coagulation/thrombosis. These studies suggest that estrogen-induced thrombosis is a unique entity distinct from other forms of venous thrombosis.

pathology↗

bioRxiv2024

UniOP: a universal operon prediction for high-throughput prokaryotic (meta-)genomic data using intergenic distance

The study of the deluge of metagenomic and genomic sequences is challenging due to the severe lack of function information. Predicting operons, groups of functionally related genes in prokaryotic genomes, is critical for bridging this gap. However, existing methods for operon prediction heavily rely on experimental data, functional annotations, or extensive characterization of homologous genes, making it difficult to accurately predict operons in newly sequenced or poorly characterized genomes. Here, we introduce UniOP, an unsupervised approach that uses a statistical model to predict operons from intergenic distances directly derived from the target genomic sequence. UniOP not only outperforms alternative approaches on ten complete genomes but also shows superior results on 3269 metagenome-assembled genomes across 13 bacterial and 2 archaeal phyla. Furthermore, we explored enhancing UniOP by incorporating the conservation of gene neighborhood and strandedness in respective genomes and examined the influence of Pfam annotations and motif searching on its performance.

bioinformatics↗

bioRxiv2024

Tardigrade Dsup: Interactions with DNA and protection of cells from oxidative stress

The remarkable capability of Tardigrade to survive under extreme conditions has been partially attributed to Dsup, an intrinsically disordered, highly positively charged protein. Dsup has been shown to bind to DNA in vitro, a property that has been associated with the capability of Dsup to exhibit stress-protective effects when expressed in mammalian cells. However, DNA binding of Dsup has not been visualized in living cells and expression of Dsup in different cell types was associated with either protective or detrimental effects. In addition, the effect of Dsup expression has not been clearly demonstrated at the organism level. Here we combined molecular dynamics (MD) simulations and fluorescence lifetime imaging microscopy (FLIM)-Forster resonance energy transfer (FRET) to interrogate Dsup-DNA interactions and demonstrated Dsup binding to DNA in living mammalian cells. Furthermore, Dsup expression in both HEK293T cells and yeast enhanced cell survival in the presence of hydrogen peroxide, suggesting that the presence of Dsup allows both mammalian and yeast cells to better cope with oxidative stress conditions. This study provides a better understanding of the property and functional role of Dsup and lays a foundation to explore new approaches to enhance stress resistance.

biophysics↗

bioRxiv2024

Comparative spatiotemporal single cell transcriptomes reveal rewiring of pre-existing regulations during emergence of Kranz anatomy in C4 grasses

Many of the worlds most productive food and bioenergy crops use C4 photosynthesis, which have high photosynthetic efficiency due to a Kranz anatomy-based CO2 concentrating mechanism. Here, we took a comparative transcriptomics approach using single cell spatial transcriptomes of leaf primordia for maize (Zea mays) and single cell RNA-seq (scRNA-seq) atlases of corresponding leaf tissues for three C4 species (Zea mays, Sorghum bicolor, Setaria viridis) and one C3 rice (Oryza sativa) to study regulatory networks involved in the development and evolution of Kranz anatomy. We show that the formation of Kranz anatomy involves extensive recruitment and modification of pre-existing regulatory modules, especially the SHR-SCR module and the auxin signaling pathway. Members of the INDETERMINATE DOMAIN (IDD) family transcription factors, including IDD7 and IDDP1, contribute to the modification of the involved modules. These extensive recruitment and modification of existing genetic regulatory programs underlie the repeated emergence of C4 photosynthesis during evolution.

plant biology↗

bioRxiv2024

Alternative transcripts recode human genes to express overlapping, frameshifted microproteins

Overlapping genes were thought to be essentially absent from the human genome until the discovery of hundreds of translated, frameshifted internal open reading frames (iORFs) within annotated protein coding sequences (CDS). This would suggest that some human genes encode two completely different proteins; however, it is unclear how iORF-encoded proteins are translated, and whether they are broadly functional. We demonstrate that "non-coding" alternative transcripts lacking a complete protein coding sequence (CDS) are required for iORF translation. We also demonstrate that iORFs such as the conserved and antiapoptotic DEDD2 iORF encode proteins with functions distinct from the annotated proteins they overlap. This work thus provides a molecular and functional basis for dual coding of overlapping ORFs in human genes.

biochemistry↗

bioRxiv2024

Integration of the DD-genome reshapes gene transcription, chromatin architecture and metabolome of allohexaploid wheat leading to enhanced adaptability

The integration, through hybridization, of the DD genome into domesticated tetraploid wheat gave rise to allohexaploid wheat, the most cultivated wheat globally growing across diverse environmental conditions. However, the regulatory basis of this integration on increased environmental adaptability in allohexaploid remains largely unexplored. Here, we investigated the change of transcriptome, epigenome as well as the chromatin interactome, and metabolome in three independent polyploidization events representing DD genome integration. Our findings reveal that polyploidization events induce the activation of defense-related genes through comprehensive reorganization of epigenome and chromatin architecture. DD integration not only brings an additional gene copy but also activates the homoeologs existing in the A and B subgenomes through chromatin interactions. Furthermore, secondary metabolites represented by alkaloids and flavonoids that are crucial for environmental adaptation, are significantly enriched following polyploidization. Thus, hexaploid wheat exhibits enhanced tolerance to alkalinity, UV-B light stress and high salt conditions was observed. These results highlight the indispensable role of DD genome integration in the adaptability of allohexaploid wheat during its evolution.

plant biology↗

bioRxiv2024

Neural dynamics of spontaneous memory recall and future thinking in the continuous flow of thoughts

The human brain constantly recalls past experiences and anticipates future events, generating a continuous flow of thoughts. However, the neural mechanisms underlying the natural transitions and trajectories of thoughts during spontaneous memory recall and future thinking remain underexplored. To address this gap, we conducted a functional magnetic resonance imaging study using a think-aloud paradigm, where participants verbalize their uninterrupted stream of thoughts during rest. We found that transitions between thoughts, particularly those involving significant shifts in semantic content, activate the brains default and control networks. These neural responses to internally generated thought boundaries produce activation patterns resembling those triggered by external event boundaries. Moreover, interactions within and between these networks shape the overall semantic structure of thought trajectories: stronger functional connectivity within the medial temporal subsystem of the default network predicts greater variability in thoughts, while stronger connectivity between the control and core default networks is associated with reduced variability. Together, our findings highlight how the default and control networks guide the dynamic transitions and structure of naturally arising memory and future thinking.

neuroscience↗

bioRxiv2024

STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics

A significant challenge in analyzing spatial transcriptomics data is the effective and efficient detection of spatially variable genes (SVGs), whose expression exhibits non-random spatial patterns in tissues. Many SVGs show spatial variation in expression that is highly correlated with cell type categories or compositions, leading to the concept of cell type-specific spatially variable genes (ctSVGs). Existing statistical methods for detecting ctSVGs treat cell type-specific spatial effects as fixed effects when modeling, resulting in a critical issue: the testing results are not invariant to the rotation of spatial coordinates. Additionally, an SVG may display random spatial patterns within a cell type, and a ctSVG may exhibit random spatial patterns from a general perspective, indicating that an SVG does not necessarily have to be a ctSVG, and vice versa. This poses challenges in real analysis when detecting SVGs or ctSVGs. To address these problems, we propose STANCE, a unified statistical model developed to detect both SVG and ctSVGs in spatial transcriptomics. By integrating gene expression, spatial location, and cell type composition through a linear mixed-effect model, STANCE enables the identification of both SVGs and ctSVGs in an initial stage, followed by a second stage test dedicated to ctSVG detection. Its design ensures robustness in complex scenarios and the results are spatial rotation invariant. We demonstrated the performance of STANCE through comprehensive simulations and analyses of three public datasets. The downstream analyses based on ctSVGs detected by STANCE suggest promising future applications of the model in spatial transcriptomics and various areas of genome biology. A software implementation of STANCE is available at https://github.com/Cui-STT-Lab/STANCE.

bioinformatics↗

bioRxiv2024

Decoding Specificity of Cyanobacterial MysDs in Mycosporine-Like Amino Acid Biosynthesis through Heterologous Expression in Saccharomyces cerevisiae

Mycosporine-like amino acids (MAAs) are potent natural UV-protectants, but their industrial production is hindered by efficiency and sustainability issues of large-scale extraction of their native hosts. Heterologous expression of MAA biosynthesis pathway genes in chassis organisms provides a promising alternative route, though the substrate promiscuity of the ATP-grasp ligase MysD complicates the biosynthesis of specific MAAs. In this study, we developed a Saccharomyces cerevisiae strain with enhanced capacity of producing mycosporine-glycine (MG), through genomic expression of biosynthesis pathway genes and knockout of competing pathway genes. This strain serves as an efficient MysD expression platform, which converts MG into shinorine and porphyra-334. Through structural modelling, site-directed mutagenesis and mutant characterization, we identified two residues on the omega-loop of MysD involved in determining product specificity. We further characterized the product specificity of 20 MysDs from diverse cyanobacterial lineages and confirmed the residue pattern-product specificity correlation. Our findings provide guidance for screening, selecting, and designing novel MysDs for industrial-scale MAA production through heterologous expression.

synthetic biology↗

bioRxiv2024

Deletion of Setd7 protects against cardiac hypertrophy via inhibiting lipid oxidation

Setd7, a catalytic enzyme responsible for histone H3K4 methylation, is implicated in various cardiac diseases. However, the role of Setd7 in pathological cardiac hypertrophy remains unclear. In this study, we observed that Setd7 is significantly elevated in pathological hypertrophy stimuli cardiomyocytes and mouse failing hearts. Subsequently, we found that mice lacking Setd7 remarkably preserved cardiac function after transverse aortic constriction, as demonstrated by improving myocardial hypertrophy and fibrosis, whereas Setd7 overexpression in cardiomyocytes deteriorated hypertrophy phenotype. Further in vitro analyses revealed that Setd7 mediated-E2F1 activation induces E3 ubiquitin protein ligases WWP2 expression to catalyze the lipid-peroxide-reducing enzyme GPx4 ubiquitination degradation, ultimately causing widespread lipid peroxidation and boosting pathological cardiac hypertrophy. Remarkably, loss of activity of GPx4 blunted the Setd7 knockdown exerts antihypertrophic effect in pathological cardiomyocytes hypertrophy, further confirming an important role of lipid peroxidation in Setd7-mediated failing hearts. In summary, the role of Setd7 in pressure overload-induced cardiac hypertrophy is regulated by the Setd7-E2F1-WWP2-GPx4 signaling pathway, suggesting that targeting Setd7 is a promising therapeutic strategy to attenuate pathological cardiac hypertrophy and heart failure.

molecular biology↗

bioRxiv2024

New integrative vectors increase Agrobacterium rhizogenes transformation and help characterise roles for soybean GmTML gene family members

Hairy-root transformation is widely used to generate transgenic plant roots for genetic functional characterisation studies. However, transformation efficiency can be limited, largely due to the use of binary vectors. Here, we report on the development of novel integrative vectors that significantly increase the transformation efficiency of hairy roots. This includes pHGUS7, for promoter::reporter visualisation studies, and pHOG13, for genetic insertion and overexpression studies. These vectors have been designed to simplify cloning workflows, enhance the selection of positively transformed Agrobacterium colonies, and increase the transformation efficiency and ease of selection of genetically modified hairy roots. To demonstrate the efficacy of the new vectors, Too Much Love (TML) encoding genes acting in the Autoregulation Of Nodulation (AON) pathway of soybean were investigated. Both constructs provided significantly higher transformation rates than the binary vector control, often resulting in >70% of the roots being transformed. Overexpression of each individual TML encoding gene (GmTML1a, GmTML1b and GmTML2) using pHOG13 resulted in a significant reduction in nodule number, demonstrating the role of all three in inhibiting nodule organogenesis. Moreover, reporter-fusions with the promoter of each TML encoding gene using pHGUS7 revealed that each exhibits a unique pattern of expression in nodules, with GmTML1b displaying considerably stronger expression than GmTML1a or GmTML2. Taken together, these results demonstrate the utility and efficiency of the new pHOG13 and pHGUS7 integrative vectors in hairy-root transformation, and improve our understanding of the critical TML-encoding genes in soybean nodulation control.

plant biology↗