Biology subjects

Xiang, J.

Publications and source records attributed to Xiang, J..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Exploring Population Differences in the Human Gut Microbiome: from Microbial Abundance to Single Nucleotide Polymorphisms

The human gut microbiota exhibits significant diversity across populations, influenced by factors such as geography, diet, and lifestyle, particularly between the Han Chinese and non-Chinese populations. While previous studies have predominantly focused on the taxonomic abundance of the gut microbiome, the impact of single nucleotide polymorphisms (SNPs) in driving population-specific differences remains largely underexplored. In this study, we systematically investigated gut microbial differences between the Han Chinese and non-Chinese populations using the Human Gut Microbiome Reference Genome Catalog (HGMRGC). HGMRGC includes 271,480 non-redundant genomes from 5,785 prokaryotic species, which was generated by metagenomic sequencing data from 9,320 publicly available samples across 22 countries and 3,584 newly sequenced samples from Han Chinese individuals across 29 provinces and regions in China. We observed geography was the primary driver of microbial variation of abundance and SNPs. We identified 625 novel population-specific genome clusters from HGMRGC with functional differences in carbohydrate utilization and 126 species exhibiting distinct prevalence related to vitamin biosynthesis, antibiotic resistance, and carbohydrate metabolism. Beta diversity analysis highlighted significant inter-population differences in both microbial abundance and SNPs, while alpha diversity analysis revealed that non-Chinese populations exhibited higher diversity in microbial abundance, and Han Chinese populations displayed greater diversity in SNPs. These results provide valuable insights into population-specific microbial diversity, laying the groundwork for future research on its functional and health implications.

microbiology↗

bioRxiv2025

Non-invasive skin topical delivery of hyaluronan

Hyaluronic acid (HA), a key glycosaminoglycan in the skin extracellular matrix, diminishes with aging, leading to dryness, wrinkles, and loss of elasticity. While subcutaneous HA injection remains the standard treatment, it is invasive and associated with complications. Here, we developed a zwitterionic polymer-based nanogel system (HA/OP) for noninvasive transdermal HA delivery. The nanogels, formed by complexing HA with poly[2-(N-oxide-N,N-diethylamino)ethyl methacrylate] (OP), exhibited pH-responsive behavior, remaining stable at weakly acidic skin surface pH ([~]5) but dissociating in neutral dermal environments. HA/OP nanogels efficiently permeated the stratum corneum via sebum-assisted enrichment and para-corneocyte transport, followed by transcytosis and enhanced paracellular penetration mediated by myosin light-chain kinase (MLCK) upregulation. This enabled deep HA deposition in the dermis and subcutaneous tissue, significantly improving skin hydration and reducing wrinkles in hairless mice without irritation. Our findings present a safe, needle-free strategy for topical HA delivery, addressing a major unmet need in cosmetic and dermatological applications.

bioengineering↗

bioRxiv2025

scWGBS-GPT: A Foundation Model for Capturing Long-Range CpG Dependencies in Single-Cell Whole-Genome Bisulfite Sequencing to Enhance Epigenetic Analysis

Single-cell DNA methylomes are challenging to interpret because of sparse CpG coverage and the complexity of genome-wide sequences. We present scDNAm-GPT, a universal foundation model that uses context-aware CpG tokenization, a Mamba backbone, and cross-attention to capture both local and global DNA methylation patterns. Trained on over one million single cells from 35 human and mouse tissues, scDNAm-GPT enables accurate cell clustering, zero-shot prediction of CpG effects on gene expression, improved trajectory inference, and reference-free deconvolution of cell types from cell-free DNA. The model hierarchically learns regulatory features, and its attention maps highlight functionally relevant regions, demonstrating high biological interpretability. These results establish scDNAm-GPT as a scalable and generalizable framework for single-cell epigenomic analysis, offering new opportunities to dissect epigenetic regulation in health and disease. Code is available at GitHub (https://github.com/ChaoqiLiang/scDNAm-GPT).

bioinformatics↗

bioRxiv2024

The comprehensive detection of hemoglobinopathy variants via long-read sequencing

BACKGROUNDThe genetic complexity of hemoglobin genes, characterized by high GC content and homologous sequences, poses significant challenges for detecting hemoglobin variants in clinical settings. METHODSA long-read indexed PCR method utilizing the novel CycloneSEQ nanopore sequencing platform was developed to detect all variant types, including single nucleotide variants (SNVs), deletions, structural variants (SVs) in HBA, HBB, HBD, and HBG genes. The method was validated using 507 clinical samples to assess its performance. RESULTSThe long-read indexed PCR system employed 13 primers targeting the hemoglobin gene clusters. This design enabled the detection of 37 types of HBA deletions, 5 SV (3 multicopies (, anti3.7, anti4.2) and 2 fusion allele (HK and anti-HK)), 37 HBB deletions, and all SNVs in the targeted regions. Validation across 507 samples (84 with HBA variants, 60 with HBB variants, 256 with both HBA and HBB variants, and 107 with no known variants) demonstrated 100.0% sensitivity and specificity. Additionally, the long-read sequencing enabled phasing of variants within hemoglobin genes, providing insights critical for clinical interpretation. CONCLUSIONSThe long-read indexed PCR method, combined with the CycloneSEQ nanopore sequencing platform, proved to be a robust and efficient solution for detecting hemoglobinopathy variants. The integration of indexed primers and barcoding enhances scalability, making this method ideal for large-scale population screening programs in the future.

genomics↗

bioRxiv2024

DyNDG: Identifying Leukemia-Related Genes based on the Time-Series Dynamical Network by Integrating Differential Genes

Leukemia is a malignant disease of progressive accumulation characterized by high morbidity and mortality rates, and investigating its disease genes is crucial for understanding its etiology and pathogenesis. Network propagation methods have emerged and been widely employed in disease gene prediction, but most of them focus on static biological networks, which hinders their applicability and effectiveness in the study of progressive diseases. Moreover, there is currently a lack of special algorithms for the identification of leukemia disease genes. Here, we proposed DyNDG, a novel Dynamic Network-based model, which integrates Differentially Expressed Genes to identify leukemia-related genes. Initially, we constructed a time-series dynamic network to model the development trajectory of leukemia. Then, we built a background-temporal multilayer network by integrating both the dynamic network and the static background network, which was initialized with differentially expressed genes at each stage. To quantify the associations between genes and leukemia, we extended a random walk process to the background-temporal multilayer network. The experimental results demonstrate that DyNDG achieves superior accuracy compared to several state-of-the-art methods. Moreover, after excluding housekeeping genes, DyNDG yields a set of promising candidate genes associated with leukemia progression or potential biomarkers, indicating the value of dynamic network information in identifying leukemia-related genes. The implementation of DyNDG is available at https://github.com/CSUBioGroup/DyNDG.

bioinformatics↗

bioRxiv2024

Functionally important binding site for a volatile anesthetic in a voltage-gated sodium channel identified by X-ray crystallography

Voltage-gated sodium channels (VGSCs), key mediators of excitability and synaptic transmission, are established and functionally relevant targets for volatile anaesthetic (VA) action. Using the structurally homologous prokaryotic VGSCs NavMs and NaChBac as models, we present a structure-function analysis of VGSC-VA interactions. We report that multiple VAs compete for binding sites on NavMs, and that these direct interactions mediate functional effects of sevoflurane on NavMs that mirror those attributed to VA effects in eukaryotic VGSCs, including human isoforms. Using X-ray crystallography, we determined the first atomic-resolution structure of a VA bound to a VGSC, showing sevoflurane displacing lipids to bind in an intramembranous hydrophobic pocket of NavMs. A conserved tyrosine residue within this binding site is critical for channel gating, and its substitution with alanine abolishes sevoflurane binding and selectively eliminates the characteristic anaesthetic-induced hyperpolarising shift of steady-state inactivation that reduces neuronal excitability at physiological membrane potentials. Finally, we provide evidence supporting VA action at the conserved sites in human VGSC isoforms. These findings define the first VA binding site in a VGSC. A membrane-mediated access pathway to the binding site leads to negative modulation of channel function that reduces neuronal activity and excitatory synaptic transmission in general anaesthesia.

biophysics↗

bioRxiv2024

Association analysis of PAEP, KRT10 and BMP7 Genes SNPs with reproductive traits in Kele pigs

The aims of this study were to investigate the effects of single nucleotide polymorphisms (SNPs) in progestogen-associated endometrial protein (PAEP), keratin 10 (KRT10), and bone morphogenetic protein 7 (BMP7) genes on reproductive traits (total number of piglets born, number of piglets born alive, litter birth weight, number of piglets weaned and litter weight weaned) in Kele pigs. We used a total of 255 multiparous Kele sow (2-4 parities) as research materials. SNPs were identified by PCR amplification instrument and sequence alignment software DANMAN. The population genetic characteristics of SNPs were analyzed using the SHEsis online software. Bioinformatics analysis of SNPs were conducted using RNAfold, SOPMA, SWISS-MODEL, and Swiss-PdbViewer programs. The associations between the SNPs and reproductive traits in Kele pigs were analyzed through SPSS 22.0 software. In this study, nine SNPs were identified in the three genes: g.1884992 T>C (exon 4), g.1885152 G>C (intron 4) and g.1887834 G>A (intron 4) in PAEP, g.21643703 C>T (intron 4), g.21643714 G>A (intron 4) and g.21643741 G>A (exon 5) in KRT10, and g.57647887 G>A (intron 3), g.57647990 C>T (intron 3) and g.57648145 C>G (intron 3) in BMP7. In SNPs g.1884992 T>C of PAEP, missense mutation eventuated structural changes in mRNA and proteins secondary structure. In SNPs g.21643741 G>A of KRT10, synonymous mutation led to alteration in mRNA secondary structure. For PAEP, the CC genotype in SNPs g.1885152 G>C and the AA genotype in SNPs g.1887834 G>A showed significantly higher values than other genotypes in all reproduction traits except for litter birth weight, preliminarily identified as favorable genotypes. For KRT10, the GG genotype in SNPs g.21648641 G>A showed significant superiority than AA genotype (P<0.05) in all aspects except for litter birth weight, and notably surpassed the GA genotype in total number of piglets born (P<0.05), preliminarily recognized as a favorable genotype. Regarding BMP7, the GA genotype in SNPs g.57647887 G>A and the CT genotype in SNPs g.57647990 C>T exhibited significantly higher number of piglets born alive and number of piglets born alive compared to other genotypes (P<0.05). And the GG genotype in SNPs g.57648145 C>G was significantly associated with higher litter birth weight (P<0.05). The result of diplotype analyses indicated that the H3H3 (CCGGGG) of PAEP and H3H3 (CCGGAA) of KRT10 had a significant effect on the five traits. For BMP7, the H4H4 (AATTGG) diplotype showed a significant influence on all genotypes except litter birth weight.

genetics↗

bioRxiv2024

A 15-Gene prognostic signature with TFAP2B functioning in Platinum Resistance of Ovarian Carcinoma

Resistance to platinum is the main challenge in the chemotherapy of ovarian cancer (OV). Therefore, developing a response signature to platinum is essential for the precision therapy of OV. Existing quantitative signatures of platinum are susceptible to batch effects and sequencing platform variations. To address this, we developed a transcriptome-based platinum signature, named PRSM, consisting of 15 genes, based on within-sample prognostic and relative expression ordering of genes, to predict individual responses to platinum in OV. The PRSM model demonstrated superior classification accuracy compared to previous quantitative signatures. Resistant samples classified by PRSM exhibited poorer overall survival, lower SNV neoantigen load, tumor mutational burden, and distinct methylation patterns compared to sensitive samples. Pathway analysis revealed the activation of MYC targets V2 and oxidative phosphorylation in resistant tumors. Single-cell analysis highlighted the roles of NK and epithelial cells in resistance. Among the 15 core genes, five (TFAP2B, KRT81, PAGE1, CRNN, UGT2B17) were linked to poor prognosis, with TFAP2B having the highest contribution to PRSM. Overexpression of TFAP2B in A2780 cells enhanced cisplatin sensitivity, while in A2780cis cells, it inhibited growth. In brief, our findings provide a multi-dimensional view of platinum resistance in ovarian cancer, introducing a robust predictive model and identifying potential therapeutic targets.

pharmacology and toxicology↗

bioRxiv2024

Nuclear Translocation of SIRT4 Mediates Deacetylation of U2AF2 to Modulate Renal Fibrosis Through Alternative Splicing-mediated Upregulation of CCN2

TGF-{beta} stimulates CCN2 expression which in turn amplifies TGF-{beta} signaling. This process promotes extracellular matrix production and accelerates the pathological progression of fibrotic diseases. Alternative splicing plays an important role in multiple disease development, while U2 small nuclear RNA auxiliary factor 2 (U2AF2) is an essential factor in the early steps of pre-mRNA splicing. However, the molecular mechanism underlying abnormal CCN2 expression upon TGF-{beta} stimulation remains unclear. This study elucidates that SIRT4 acts as a master regulator for CCN2 expression in response to TGF-{beta} by modulating U2AF2-mediated alternative splicing. Analyses of renal biopsy specimens from patients with CKD and mouse fibrotic kidney tissues revealed marked nuclear accumulation of SIRT4. The tubulointerstitial fibrosis was alleviated by global deletion or tubular epithelial cell (TEC)-specific knockout of Sirt4, and aggravated by adeno-associated virus-mediated SIRT4 overexpression in TECs. Furthermore, SIRT4 was found to translocate from the mitochondria to the cytoplasm through the BAX/BAK pore under TGF-{beta} stimulation. In the cytoplasm, TGF-{beta} activated the ERK pathway and induced the phosphorylation of SIRT4 at Ser36, which further promoted its interaction with importin 1 and subsequent nuclear translocation. In the nucleus, SIRT4 was found to deacetylate U2AF2 at K413, facilitating the splicing of CCN2 pre-mRNA to promote CCN2 protein expression. Importantly, exosomes containing anti-SIRT4 antibodies were found to effectively mitigate the UUO-induced kidney fibrosis in mice. Collectively, these findings indicated that SIRT4 plays a role in kidney fibrosis by regulating CCN2 expression via the pre-mRNA splicing.

molecular biology↗

bioRxiv2024

Functional overlap between the mammalian SAR1A and SAR1B paralogs in vivo

Proteins carrying a signal peptide and/or a transmembrane domain enter the intracellular secretory pathway at the endoplasmic reticulum (ER) and are transported to the Golgi apparatus via COPII vesicles or tubules. SAR1 initiates COPII coat assembly by recruiting other coat proteins to the ER membrane. Mammalian genomes encode two SAR1 paralogs, SAR1A and SAR1B. While these paralogs exhibit [~]90% amino acid sequence identity, it is unknown whether they perform distinct or overlapping functions in vivo. We now report that genetic inactivation of Sar1a in mice results in lethality during mid-embryogenesis. We also confirm previous reports that complete deficiency of murine Sar1b results in perinatal lethality. In contrast, we demonstrate that deletion of Sar1b restricted to hepatocytes is compatible with survival, though resulting in hypocholesterolemia that can be rescued by adenovirus-mediated overexpression of either SAR1A or SAR1B. To further examine the in vivo function of these 2 paralogs, we genetically engineered mice with the Sar1a coding sequence replacing that of Sar1b at the endogenous Sar1b locus. Mice homozygous for this allele survive to adulthood and are phenotypically normal, demonstrating complete or near-complete overlap in function between the two SAR1 protein paralogs in mice. These data also suggest upregulation of SAR1A gene expression as a potential approach for the treatment of SAR1B deficiency (chylomicron retention disease) in humans.

genetics↗

bioRxiv2024

Genetic polymorphisms of Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3) gene in African American kidney transplant recipients are associated with post-transplant graft failure

BackgroundAfrican American (AA) kidney transplant recipients exhibit a higher rate of graft loss compared to other racial and ethnic populations, highlighting the need to identify causative factors underlying this disparity. MethodWe analyzed RNA sequences of pretransplant whole blood from subjects followed in three kidney transplant cohorts to identify single nucleotide polymorphisms (SNPs) associated with death censored graft loss (DCGL). We employed a meta-analysis to uncover key transcriptional signatures and pathways associated with the identified SNPs and used single cell RNA to define cellular specificity. We characterized SNP functions using in vitro immunological and survival assays and tested for associations between the identified SNPs and other immune-related diseases using a [~]30,100 subject, electronic health record (EHR)-linked database. ResultsWe uncovered a cluster of four consecutive missense SNPs in the Leukocyte Immunoglobulin-Like Receptor B3 (LILRB3, a negative immune response regulator) gene that strongly associated with DCGL. This LILRB3-4SNPs cluster encodes missense mutations at amino acids 617-618 proximal to a SHP-1/2 phosphatase-binding ITIM motif. LILRB3-4SNPs is specifically enriched within subjects of AA ancestry (8.6% prevalence vs 2.3% in Hispanic and 0.1% in European populations), is not linked to APOL1 G1/G2 alleles, and exhibited a strong association with DCGL. Analysis of PBMC and transplant biopsies from recipients with LILRB3-4SNPs showed evidence of enhanced adaptive immune responsiveness and ferroptosis-associated death in monocytes. Overexpression of the variant allele in THP-1 cells (macrophage line) induced augmented inflammation and ferroptosis, which were attenuated by a ferroptosis inhibitor, verifying a causal link. The LILRB3-4SNPs also associated with multiple systemic and organ-specific immune-related diseases in AAs, consistent with conferring a broadly relevant immune function. Conclusionthe LILRB3-4SNPs represent a functionally important, distinct genetic risk factor for kidney transplant outcome and development/severity of other immune-related diseases in patients of AA ancestry. Pharmacological targeting of ferroptosis should be tested to prevent or treat these disease processes in AA recipients carrying LILRB3-4SNPs.

genetics↗

bioRxiv2024

Translational response to mitochondrial stresses is orchestrated by tRNA modifications.

Mitochondrial stress and dysfunction play important roles in many pathologies. However, how cells respond to mitochondrial stress is not fully understood. Here, we examined the translational response to electron transport chain (ETC) inhibition and arsenite induced mitochondrial stresses. Our analysis revealed that during mitochondrial stress, tRNA modifications (namely f5C, hm5C, queuosine and its derivatives, and mcm5U) dynamically change to fine tune codon decoding, usage, and optimality. These changes in codon optimality drive the translation of many pathways and gene sets, such as the ATF4 pathway and selenoproteins, involved in the cellular response to mitochondrial stress. We further examined several of these modifications using targeted approaches. ALKBH1 knockout (KO) abrogated f5C and hm5C levels and led to mitochondrial dysfunction, reduced proliferation, and impacted mRNA translation rates. Our analysis revealed that tRNA queuosine (tRNA-Q) is a master regulator of the mitochondrial stress response. KO of QTRT1 or QTRT2, the enzymes responsible for tRNA-Q synthesis, led to mitochondrial dysfunction, translational dysregulation, and metabolic alterations in mitochondria-related pathways, without altering cellular proliferation. In addition, our analysis revealed that tRNA-Q loss led to a domino effect on various tRNA modifications. Some of these changes could be explained by metabolic profiling. Our analysis also revealed that utilizing serum deprivation or alteration with Queuine supplementation to study tRNA-Q or stress response can introduce various confounding factors by altering many other tRNA modifications. In summary, our data show that tRNA modifications are master regulators of the mitochondrial stress response by driving changes in codon decoding.

molecular biology↗

bioRxiv2023

Divide-and-conquer quantum algorithm for hybrid de novo genome assembly of short and long reads

Computational biology holds immense promise as a domain that can leverage quantum advantages due to its involvement in a wide range of challenging computational tasks. Researchers have recently explored the applications of quantum computing in genome assembly implementation. However, the issue of repetitive sequences remains unresolved. In this paper, we propose a hybrid assembly quantum algorithm using high-accuracy short reads and error-prone long reads to deal with sequencing errors and repetitive sequences. The proposed algorithm builds upon the variational quantum eigensolver and utilizes divide-and-conquer strategies to approximate the ground state of larger Hamiltonian while conserving quantum resources. Using simulations of 10-qubit quantum computers, we address problems as large as 140 qubits, yielding optimal assembly results. The convergence speed is significantly improved via the problem-inspired ansatz based on the known information about the assembly problem. Besides, entanglement within quantum circuits is qualitatively verified to notably accelerate the assembly path optimization.

bioinformatics↗

bioRxiv2023

Skin permeable polymer for noninvasive transdermal insulin delivery

Subcutaneous injection of insulin is the current standard medication for many diabetic patients. Convenient and painless noninvasive transdermal insulin delivery has long been pursued but yet succeeded due to no such technologies for large biomacromolecules. We find a tertiary amine oxide-based polyzwitterion, OPDMA, that can efficiently penetrate both the stratum corneum (SC) and viable epidermis into circulation. So its conjugate with insulin, OPDMA-I, applied on the skin can exhibit hypoglycemic effects as efficiently as subcutaneously injected insulin in type-1 diabetic mice and minipigs. The unique pH-dependent cationic-to-zwitterionic transition of OPDMA in the characteristic acidic-to-neutral pH gradient from the skin surface to deep SC enables fast transdermal delivery of OPDMA and its conjugate. On the skin, OPDMA binds to carboxylic acids in the acidic sebum layer, enriching OPDMA-I on the SC. As pH increases in deeper SC layers, binding between OPDMA-I and the skin weakens gradually, allowing for diffusion through inter-corneocyte gaps and penetration into viable epidermis and finally entering the systemic circulation via dermal lymphatic vessels. This process does not alter SC microstructures or cause any physiological changes in the skin. This study represents a groundbreaking example of noninvasive transdermal protein delivery.

bioengineering↗

bioRxiv2023

Spatio-temporal patterns of ovarian development and VgR gene silencing reduced fecundity of parthenogenetic Artemia

Halophilic zooplankton brine shrimp Artemia has been used as an experimental animal in multidisciplinary research. However, the reproductive patterns and regulation mechanisms of Artemia remain a mystery. In this study, the ovarian development process of parthenogenetic Artemia (P. Artemia) was distinguished into five stages, and oogenesis or egg formation process was identified with six phases. The mode of oogenesis was assumed polytrophic. Moreover, we traced the dynamic translocation of germline stem cells (GSCs) by EdU labeling, elucidated several key cytological events in oogenesis through HE staining and florescent image. Notably, distinguished from the ovary structure of insects and crustaceans, P. Artemia germarium originated from ovariole buds and located in the base of the ovarioles. RNA-seq based on five stages of ovarian development revealed that 2657 up-regulated genes related to reproduction were obtained by pair-to-pair comparison of RNA-seq. Furthermore, Gbb, Dpp, piwi, vasa, nanos, VgA and VgR associated with GSCs recognition and reproductive development genes were screened and also verified by qPCR. Silencing of the VgR gene in P. Artemia (PA-VgR) at stage L of ovarian development led to a low level of gene expression (<10%) within five days, which resulted variations of oogenesis-related gene expression and significantly inhibited vitellogenesis, impeded oocyte maturation, and eventually decreased the offspring number. In conclusion, we illustrated the patterns of ovarian development, outlined the key spatio-temporal features of oogenesis and established a platform for gene function research using P. Artemia as an experimental animal. These results lay the foundation for studying the reproductive biology of invertebrates, may also provide a novel insight in the reproductive regulation mechanism of aquatic animals in extreme environments. SUMMARY STATEMENTArtemia is a novel experimental platform and potential "model" crustacean for studying specific process and mechanism of reproduction.

developmental biology↗

bioRxiv2023

Integrated Spatial Transcriptomic and Proteomic Analysis of Fresh Frozen Tissue Based on Stereo-seq

To simultaneously detect whole transcriptomes and protein markers on the same tissue section, we combined Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) and Stereo-seq to develop the Stereo-CITE-seq workflow. Here, we demonstrated that Stereo-CITE-seq can co-detect mRNAs and proteins in immune organs with high spatial resolution, reproducibility and accuracy.

molecular biology↗

bioRxiv2022

St2cell: Reconstruction of in situ single-cell spatial transcriptomics by integrating high-resolution histological image.

Spatially resolved transcriptomics (SRT) has greatly expanded our understanding of the spatial patterns of gene expression in histological tissue sections. However, most currently available platforms could not provide in situ single-cell spatial transcriptomics, limiting their biological applications. Here, to in silico reconstruct SRT at the single-cell resolution, we propose St2cell which combines deep learning-based frameworks with a novel convex quadratic programming (CQP)-based model. St2cell can thoroughly leverage information in high-resolution (HR) histological images, enabling the accurate segmentation of in situ single cells and identification of their transcriptomics. Applying St2cell on various SRT datasets, we demonstrated the reliability of reconstructed transcriptomics. The single-cell resolution provided by our proposed method greatly promoted the detection of elaborate spatial architectures and further facilitated the integration with single-cell RNA-sequencing data. Moreover, in a breast cancer tissue, St2cell identified general spatial structures and co-occurrence patterns of cell types in the tumor microenvironment. St2cell is also computationally efficient and easily accessible, making it a promising tool for SRT studies.

bioinformatics↗

bioRxiv2022

Integrate multiscale module kernel for disease-gene discovery in biological networks

Biomedical data mining plays a crucial role in studying diseases, with disease-gene identification being one of the most prominent areas of research in this field. Many biomolecule networks are known to have multi-scale module structures, which may be helpful for studying complex diseases, but the mining and utilization of multi-scale module structure is an open issue. Therefore, we present a kind of novel hybrid network-based method (HyMSMK) for disease-gene identification through incorporating multi-scale module kernel in biomolecule networks. We first apply exponential sampling to construct multi-scale module profile containing local to global structural information, where modules at different scales are extracted from comprehensive interactome by multi-scale modularity optimization. Then, the multi-scale module profile is preprocessed by the relative information content, and is used to generate multi-scale module kernel, which is further preprocessed by kernel sparsification. We design multiple schemes for incorporating multi-scale module kernel to discover potential disease-related genes. We investigate the performance of these schemes by experimental evaluations, show the positive effect of kernel sparsification on reducing the requirement for space and time, and confirm the superior performance of our method compared to other state-of-art network-based baselines. The study demonstrates the utility of multi-scale module kernel in discovering disease genes, which could provide insights for the research of relevant issues.

bioinformatics↗