Biology subjects

Jiao, S.

Publications and source records attributed to Jiao, S..

16 recordsLinked to original sources

bioRxiv2026

Virtual spatial transcriptomics from histopathology enables prognostic and therapeutic response prediction in cancer

Spatial transcriptomics reveals cellular heterogeneity, intercellular communication, and tissue organization, but its cost and limited accessibility restrict clinical use. Here, we present VISTA, a model that integrates multi-scale histological features and spatial context to infer spatial gene expression from H&E-stained tissue images. Across leave-one-section-out cross-validation and independent validation, VISTA robustly predicted thousands of genes and outperformed state-of-the-art methods. Beyond expression reconstruction, VISTA enabled clinically relevant downstream analyses. In TCGA breast cancer samples, it identified survival-associated genes, stratified prognostic risk groups, and revealed adverse tumor-associated spatial subtypes. In our in-house intrahepatic cholangiocarcinoma cohort, it preserved tumor-normal organization and identified CLDN4 and CYP3A4 as complementary spatial biomarkers. In HER2+ breast cancer, it predicted pathological response to neoadjuvant trastuzumab-based therapy and linked response-associated regions to immune and cytokine-related programs. These results support virtual spatial transcriptomics from routine histopathology for oncology applications.

genomics↗

bioRxiv2026

Designing AAV Capsid Protein with viability-guided Diffusion Model

Adeno-associated virus (AAV) capsids have shown great promise as delivery vectors for gene therapy. However, the natural properties of AAV capsids impose significant limitations on their efficacy. While capsid library screening and directed evolution have facilitated the development of improved vectors, current methods for generating AAV libraries frequently yield nonviable variants that fail to assemble or package DNA. Here, we propose a viability-guided diffusion model AAVDiffusion for de novo viable AAV capsid design. AAVDiffusion iteratively denoises Gaussian vectors into vectors of AAV capsid protein sequences, yielding intermediate latent variables. By leveraging the continuous nature of these latent variables, AAVDiffusion integrates an additional viability classifier that applies gradient updates to enhance the generation of viable AAV sequences. Through extensive computational tests, AAVDiffusion exhibits superior performance in generating viable AAV sequences. Furthermore, 196 AAV candidates were identified through a selection workflow, with the potential to cross the blood-brain barrier, thereby offering safer and more effective gene therapies for brain diseases. AAVDiffusion offers a powerful and efficient computational method for designing viable AAV capsids, advancing the development of AAV vectors for gene therapy.

bioinformatics↗

bioRxiv2025

Migration patterns and hybridization within the Asian stonechat complex in response to a major geographical barrier

Long-distance avian migration is thought to be under strong natural selection. Facing geographical barriers, migrants display various patterns considered to be adaptive. For example, they may detour along either side around the barrier or cross it, requiring specialized behavioral adaptations. Variations within closely related taxa are excellent sources for understanding the evolutionary background of migration and how barriers are shaping migration routes. In Asia, some species are assumed to have a migratory divide in response to the major geographical barrier, the Qinghai-Tibet Plateau (QTP), including the stonechat taxa (Siberian Stonechat Saxicola maurus maurus and Amur Stonechat S. stejnegeri). As they detour along either side of the QTP, these taxa are believed to disfavor a crossing over the highland. However, the more southernly distributed Tibetan Stonechat (S. m. przewalskii) breeds on the QTP, suggesting adaptation to high elevation. To investigate migration patterns and the potentially associated genetic differences, we studied migration routes and population genetics of four populations around the assumed migratory divide in Russia and Mongolia, and of one from the QTP in China. Our results confirmed the existence of a migratory divide between maurus and stejnegeri, albeit with extensive hybridization. We observed both the hypothesized western and eastern routes, but also found individuals employing intermediate routes crossing the QTP, of which two-thirds were clear hybrids. Meanwhile, przewalskii followed a highland-crossing route and was genetically differentiated from maurus and stejnegeri. The diverse migration routes among Asian stonechats show differential responses towards the geographical barrier. The intermediate route may be associated with hybridization, and its conditional viability may facilitate gene flow between maurus and stejnegeri. The Asian stonechat complex thus offers great opportunities for novel research of the genetics and evolution of migration. The specific evolutionary background associated with inhabiting and crossing the QTP can offer new perspectives in this field. Teaser textMigratory divides can arise in birds because alternative routes around migratory barriers would select for behaviors to restrict hybridization. Hybrids of parental types that employ alternative routes are hypothesized to embark on intermediate routes that would expose them to suboptimal conditions, resulting in post-zygotic reproductive isolation. However, this hypothesis is challenged when a sister taxon actually breeds on the geographical barrier. This is the case in the Asian stonechat complex that breeds near or on the Qinghai-Tibet Plateau (QTP), the roof of the world. We demonstrated a migratory divide in central Siberia to Mongolia for race maurus and stejnegeri, yet showed also evidence for extensive hybridization. Hybrids migrated along a newly discovered intermediate route, seemingly viable and overlaps with the migration trajectory of race przewalskii over the eastern part of the QTP. The Asian migratory divide relative to the QTP thus provided new insights to the evolution of landbird migration.

evolutionary biology↗

bioRxiv2025

Single-cell and spatial transcriptomics reveal the pathogenesis of chronic granulomatous disease in a natural model

Genetic defects in NOX2 can cause chronic granulomatous disease (CGD), characterized by increased susceptibility to infections and pronounced inflammatory responses that lead to granuloma formation. We developed a CGD model using Ncf2-/- mice through controlled environmental exposure. Unlike in specific pathogen-free environment, these mice spontaneously developed pulmonary granulomas under clean-grade conditions. Employing single-cell RNA sequencing, we observed an expansion of neutrophils and monocyte-derived macrophages (MDMs) within the lung tissue, identifying pro-inflammatory NOS2high-neutrophils and a distinct MDMs subset marked by NOS2 and ARG1. Spatial transcriptomics demonstrated that NOS2high-neutrophils were located at the core area, while the MDMs subset was positioned at the periphery, facilitating extracellular matrix remodeling. Pharmacological targeting of MIF, deletion of the pro-survival gene Morrbid, and elimination of Il1r1 all suppressed granuloma formation by mitigating inflammation. This study underscores how environmental control can establish a natural CGD model, elucidates the mechanisms of granuloma formation, and develops potent therapeutic interventions. HighlightsO_LIThrough installing a mutation in a NOX2 subunit gene Ncf2 and changing the husbandry environment, we generated a natural CGD mouse model with progressive pulmonary granuloma formation. C_LIO_LINOS2high neutrophils located in the core region of CGD lung granulomas, exhibit a pro-inflammatory transcriptional profile. C_LIO_LIMonocyte-derived macrophages marked by Nos2 and Arg1 are located at the periphery of granulomas and exhibit a profibrotic transcriptional profile. C_LIO_LIThe transcriptomic studies assist the development of three effective perturbations for treating the rare disease CGD via targeting Il1r1, Morrbid, and Mif respectively. C_LI

immunology↗

bioRxiv2025

LCORL and STC2 variants increase body size and growth rate in cattle and other animals

Using ancestral recombination graphs, we investigated recent selection signatures in European beef cattle breeds, pinpointing sweep-driving variants in the LCORL and STC2 loci with notable effects on body size and growth rate. The ACT-to-A frameshift mutation in LCORL occurs mainly in central-European cattle, and stimulates growth. Remarkably, convergent truncating mutations were also found in commercial breeds of sheep, goats, pigs, horses, dogs, rabbits, and chickens. In the STC2 gene, we identified a missense mutation (A60P) located within the conserved region across vertebrates. We validated the two natural mutations in gene-edited mouse models, where both variants in homozygous carriers increase the average weight by 11%. Our findings provide insights into a seemingly recurring gene target of body size enhancing truncating mutations across domesticated species, and offer valuable targets for gene editing-based breeding in animals.

genetics↗

bioRxiv2024

A Multi-Property Optimizing Generative Adversarial Network for de novo Antimicrobial Peptide Design

Antimicrobial peptides (AMPs) play a crucial role in developing novel antiinfective drugs due to their broad-spectrum antimicrobial activity and lower likelihood of causing bacterial resistance. However, laboratory synthesis of AMPs is tedious and time-consuming. Existing computational methods have limited capability in optimizing multiple desired properties simultaneously. Here, we propose a Multi-Property Optimizing Generative Adversarial Network (MPOGAN), a feedback-loop framework that iteratively learns from data with multiple desired properties. This approach enables de novo design of AMPs with potent antimicrobial activity, reduced cytotoxicity, and diversity. Through extensive computational tests, MPOGAN exhibits superior performance in optimizing multiple desired properties of generated AMPs. Ten of the most promising candidates are chemically synthesized, with nine showing potent antimicrobial activity against three bacterial strains and low cytotoxicity against eukaryotic cells. MPOGAN offers a powerful computational approach for effective multi-property optimization of AMPs, thereby advancing the field of AI-aided drug discovery.

bioinformatics↗

bioRxiv2024

Small DNA elements that act as both insulators and silencers in plants

Insulators are cis-regulatory elements that separate transcriptional units, whereas silencers are elements that repress transcription regardless of their position. In plants, these elements remain largely uncharacterized. Here, we use the massively parallel reporter assay Plant STARR-seq with short fragments of eight large insulators to identify more than 100 fragments that block enhancer activity. The short fragments can be combined to generate more powerful insulators that abolish the capacity of the strong viral 35S enhancer to activate the 35S minimal promoter. Unexpectedly, when tested upstream of weak enhancers, these fragments act as silencers and repress transcription. Thus, these elements are capable of both insulating or repressing transcription dependent upon regulatory context. We validate our findings in stable transgenic Arabidopsis, maize, and rice plants. The short elements identified here should be useful building blocks for plant biotechnology efforts.

plant biology↗

bioRxiv2024

Identifying potential risk genes for clear cell renal cell carcinoma with deep reinforcement learning

Clear cell renal cell carcinoma (ccRCC) is the most prevalent type of renal cell carcinoma. However, our understanding of ccRCC risk genes remains limited. This gap in knowledge poses significant challenges to the effective diagnosis and treatment of ccRCC. To address this problem, we propose a deep reinforcement learning-based computational approach named RL-GenRisk to identify ccRCC risk genes. Distinct from traditional supervised models, RL-GenRisk frames the identification of ccRCC risk genes as a Markov decision process, combining the graph convolutional network and Deep Q-Network for risk gene identification. Moreover, a well-designed data-driven reward is proposed for mitigating the lim-itation of scant known risk genes. The evaluation demonstrates that RL-GenRisk outperforms existing methods in ccRCC risk gene identification. Additionally, RL-GenRisk identifies ten novel ccRCC risk genes. We successfully validated epidermal growth factor receptor (EGFR), corroborated through independent datasets and biological experimentation. This approach may also be used for other diseases in the future.

bioinformatics↗

bioRxiv2024

DiffuST: a latent diffusion model for spatial transcriptomics denoising

Spatial transcriptomics technologies have enabled comprehensive measurements of gene expression profiles while retaining spatial information and matched pathology images. However, noise resulting from low RNA capture efficiency and experimental steps needed to keep spatial information may corrupt the biological signals and obstruct analyses. Here, we develop a latent diffusion model DiffuST to denoise spatial transcriptomics. DiffuST employs a graph autoencoder and a pre-trained model to extract different scale features from spatial information and pathology images. Then, a latent diffusion model is leveraged to map different scales of features to the same space for denoising. The evaluation based on various spatial transcriptomics datasets showed the superiority of DiffuST over existing denoising methods. Furthermore, the results demonstrated that DiffuST can enhance downstream analysis of spatial transcriptomics and yield significant biological insights.

genomics↗

bioRxiv2023

High throughput detection of variation in single-cell whole transcriptome through streamlined scFAST-seq

High-throughput single-cell full-length RNA sequencing is a powerful tool to explore the entire transcriptome, including non-polyadenylated transcripts. We developed a single cell Full-length RNA Sequence Transcriptome sequencing method (scFAST-seq), which combines semi-random primers with high reverse transcription efficiency, template switching and convenient rRNA removal methods, allowing the construction of full-length RNA libraries of up to 12,000 cells within 8 hours. Compared to regular 3 scRNA-seq, scFAST-seq has similar sensitivity to mRNA detection, sequencing cost and experimental workflow. Moreover, scFAST-seq has clear advantages in detecting non-polyadenylated transcripts, covering longer transcript length, and identifying more splice junctions. In addition, scFAST-seq can more accurately predict the direction of cell differentiation by calculating RNA velocity. Furthermore, we demonstrated that scFAST-seq combined with target region enrichment can simultaneously identify somatic mutations and cellular status of individual tumor cells, which is valuable information for precision medicine.

genomics↗

bioRxiv2022

Translation control by maternal Nanog promotes oocyte maturation and early embryonic development

Many maternal mRNAs are translationally repressed during oocyte maturation and spatio-temporally activated during early embryogenesis, which is critical for oocyte and early embryo development. By analyzing maternal mutants of nanog (Mnanog) in zebrafish, we demonstrated that Nanog tightly controls translation of maternal mRNA during oocyte maturation via transcriptional repression of eukaryotic translation elongation factor 1 alpha 1, like 2 (eef1a1l2). Loss of maternal Nanog led to defects of egg maturation, increased endoplasmic reticulum (ER) stress, and an activated unfold protein response (UPR), which was caused by elevated translational activity. We further demonstrated that Nanog, as a transcriptional repressor, represses the transcription of eefl1a1l2 by directly binding to the eef1a1l2 promoter during oocyte maturation. More importantly, depletion of eef1a1l2 in nanog mutant females effectively rescued the elevated translational activity in oocytes, egg quality defects, and embryonic defects of Mnanog embryos. Thus, our study demonstrates that maternal Nanog regulates oocyte maturation and early embryogenesis though translational control of maternal mRNA via a novel mechanism, in which Nanog acts as a transcriptional repressor to suppress transcription of eef1a1l2.

developmental biology↗

bioRxiv2021

PCBP1 Deficient Pigs Hold the Potential to Inhibit CSFV Infection

Classical swine fever virus (CSFV), pathogen of classic swine fever, has caused severe economic losses worldwide. Poly (rC)-binding protein 1 (PCBP1), interacting with Npro of CSFV, plays a vital role in CSFV growth. Here, our research is the first report to generate PCBP1 knockout pigs via gene editing technology. The PCBP1 knockout pigs exhibited normal birth weight, reproductive-performance traits, and developed normally. Viral challenge results indicated that primary cells isolated from F0 and F1 generation pigs could significantly reduce CSFV infection. Additional mechanism exploration further confirmed that PCBP1 KO mediated antiviral effect is related with the activation of type I interferon. Beyond showing that gene editing strategy can be used to generate PCBP1 KO pigs, our study introduces a valuable animal model for further investigating infection mechanisms of CSFV that help to develop better antiviral solution. ImportanceAs a negative regulator in immune modulation, the effects of PCBP1 on viral replication have been found to be valuable. Here, this study was the first report to generate PCBP1 knockout pigs with normal pregnancy rate and viability. Primary cells isolated from F0 and F1 generation PCBP1 knockout pigs could significantly reduce CSFV infection. The PCBP1 knockout pigs could be used as a natural host models for investigating the effects of PCBP1-mediating critical interactions on viral replication and helping to develop better antiviral solution.

molecular biology↗

bioRxiv2021

An oligosaccharide analog exhibited antifungal activity by misleading cell wall organization via targeting PHR transglucosidases

The fungal cell wall is an ideal target for the design of antifungal drugs. In this study we used an analog of cell wall polymer, a highly deacetylated long-chain chitosan oligosaccharide (HCOS), to test its effect against pathogenic Candida strains. Results showed that HCOS was successfully incorporated into the dynamic cell wall organization process and exhibited an apparent antifungal activity against both plankton and mature fungal biofilm, by impairing the cell wall integrity. Unexpectedly, mechanistic studies suggested that HCOS exerts its activity by interfering with family members of PHR {beta}-(1,3)-glucanosyl transferases and affecting the connection and assembly of cell wall polysaccharides. Furthermore, HCOS showed great synergistic activity with different fungicides against Candida cells, especially those in biofilm. These findings indicated HCOS has a great potential as an antifungal drug or drug synergist and proposed a novel antifungal strategy with structure-specific oligosaccharides mimicking cell wall polysaccharide fragments. IMPORTANCEFungal infections have always been a puzzle in clinical medicine. Only a few antifungal drugs are available for medical usage and the widespread use of antifungal drugs increased the incidence of drug resistance. It is an urgent need for the development of novel treatment strategies against fungal infections. In this study, we proposed a novel strategy targeting to fungal cell wall against C. albicans. To our knowledge, it is the first study to show a cell wall polysaccharide fragment analog integrate into and interfere with the fungal cell wall, indicating a novel antifungal strategy using structure-specific oligosaccharides mimicking cell wall polysaccharide fragments.

microbiology↗

bioRxiv2019

Nanog safeguards early embryogenesis against global activation of maternal β-catenin activity by interfering with TCF factors

Maternal {beta}-catenin activity is essential and critical for dorsal induction and its dorsal activation has been thoroughly studied. However, how the maternal {beta}-catenin activity is suppressed in the non-dorsal cells remains poorly understood. Nanog is known to play a central role for maintenance of the pluripotency and maternal-to-zygotic transition. Here we reveal a novel role of Nanog as a strong repressor of maternal Wnt/{beta}-catenin signaling to safeguard the embryo against hyper-activation of maternal {beta}-catenin activity and hyper-dorsalization. Knockdown of nanog at different levels led to either posteriorization or dorsalization, mimicking zygotic or maternal activation of Wnt/{beta}-catenin activities, and the maternal-zygotic mutant of nanog (MZnanog) showed strong activation of maternal {beta}-catenin and hyper-dorsalization. Although a constitutive-activator-type Nanog (Vp16-Nanog, lacking the N-terminal) perfectly rescued the defects of maternal to zygotic transition in MZnanog, it did not rescue the phenotypes resulting from {beta}-catenin activation. Mechanistically, the N-terminal of Nanog directly interacts with TCF and interferes with the binding of {beta}-catenin to TCF, thereby attenuating the transcriptional activity of {beta}-catenin. Therefore, our study establishes a novel role for Nanog in repressing maternal {beta}-catenin activity and demonstrates a transcriptional switch between {beta}-catenin/TCF and Nanog/TCF complexes, which safeguards the embryo from global activation of maternal {beta}-catenin activity.

developmental biology↗

bioRxiv2018

Application of clinical genomic sequencing among Chinese advanced cancer patients to guide precision medicine decisions

PurposeA number of studies have suggested that high-throughput genomic analyses might improve the outcomes of cancer patients. However, whether integrative information about genomic sequencing and related clinical interpretation may benefit Chinese cancer patients with stage IV disease to date has not investigated.\n\nMethodsTargeted gene panel and whole exome of tumor/blood samples in > 1,000 Chinese cancer patients were sequenced. Then we provided patients and their oncologists with the sequencing results and a clinical recommendation roadmap based on evidence-based medicine, defined as CWES. Only patients with stage IV disease who failed the previous treatment upon receiving the CWES reports were included for analyzing the impact of CWES on clinical outcomes in 1-year follow-ups.\n\nResultsWe identified the mutational signatures of 953 Chinese cancer patients, with some being unique. Approximately 88.6% of patients had clinically actionable somatic genomic alterations. We successfully followed up 22 stage IV patients. Of these, 11 patients treatment followed the CWES reports defined as group A. Eleven patients received the next treatment, but did not follow the CWES suggestions, and are defined as group B. The types of therapies before CWES were similar in the two groups. The median PFS of group A was 12 months and 45% patients failed this round of therapy. The median PFS of group B was 4 months and 91% of patients failed the treatment.\n\nConclusionThe current study suggested that CWES has the potential to help explore the clinical benefits in multiple line therapies among advanced stage tumor patients.

cancer biology↗

bioRxiv2018

Comprehensive analysis of potential immunotherapy genomic biomarkers in 1,000 Chinese patients with cancer

BackgroundTumor mutation burden (TMB), DNA mismatch repair deficiency (dMMR), microsatellite instability (MSI), and PD-L1 amplification (PD-L1 AMP) may predict the efficacy of PD-1/PD-L1 blockade. In this study, we aimed to characterize the distributions of these biomarkers in over 1,000 Chinese patients with cancer.\n\nMethodsTMB, MSI, dMMR, and PD-L1 AMP were determined based on whole-exome sequencing of tumor/blood samples from > 1,000 Chinese patients with cancer.\n\nResultsIncidence rates among 953 Chinese patients with cancer showing high TMB (TMB-H), high MSI (MSI-H), dMMR and PD-L1 AMP were 35%, 4%, 0.53% and 3.79%, respectively. We found higher rates of TMB-H among hepatocellular carcinoma, breast cancer, and esophageal cancer patients than was reported for The Cancer Genome Atlas data. Lung cancer patients with EGFR mutations had significantly lower TMB values than those with wild-type EGFR, and increased TMB was significantly associated with dMMR in colorectal cancer (CRC). The frequency of tumors with MSI-H was highest in CRC (14%) and gastric cancer (4%). PD-L1 AMP occurred most frequently in lung squamous cell carcinoma (14.3%) and HER2-positive breast cancer (8.8%). Most MSI-H and dMMR cases exhibited TMB-H, but the overlap among the other biomarkers was low.\n\nConclusionWhile MSI and dMMR are associated with higher mutational loads, correlations between TMB-H and other biomarkers, between MSI-H and dMMR, and between PD-L1 AMP and other biomarkers were low, indicating different underlying causes of the four biomarkers. Thus, it is recommended that all four biomarkers be assessed for certain cancers before administration of PD-1/PD-L1 blockade treatment.

cancer biology↗