Biology subjects

Miao, Y.

Publications and source records attributed to Miao, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2023

Alzheimer mutations stabilize synaptotoxic γ-secretase-substrate complexes

Alzheimers disease is characterized pathologically by cerebral deposition of 42-residue amyloid {beta}-peptide (A{beta}42), proteolytically produced from amyloid precursor protein (APP) by {beta}- and {gamma}-secretases.1 Although mutations in APP and presenilin, the catalytic component of {gamma}-secretase, cause familial Alzheimers disease (FAD), a role for A{beta}42 as the primary disease driver has not been clearly established and remains controversial.2,3 Here we show through comprehensive analysis of the multi-step proteolysis of APP substrate C99 by {gamma}-secretase that FAD mutations are consistently deficient in early proteolytic events, not later events that produce secreted A{beta} peptides. Cryo-electron microscopy revealed that a substrate mimetic traps {gamma}-secretase at the transition state for intramembrane proteolysis, and this structure closely aligns with activated enzyme-substrate complex captured by molecular dynamics simulations. In silico simulations and fluorescence lifetime imaging microscopy in cultured cells support stabilization by FAD mutations of enzyme-substrate and/or enzyme-intermediate complexes. Neuronal expression of C99 and/or presenilin-1 in Caenorabditis elegans led to age-dependent synaptic loss only when one of the transgenes carried an FAD mutation. Designed mutations that stabilize the enzyme-substrate complex and block proteolysis likewise led to synaptic loss. Collectively, these findings implicate the stalled process--not the released products--of {gamma}-secretase cleavage of substrates in FAD pathogenesis.

neuroscience↗

bioRxiv2023

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution

Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 159 samples, 652,160 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, this package also integrated a module to process the seq-based spatial transcriptomic data and analyze the spatial features of TME. Software availability: http://lifeome.net/software/sccancer2/.

bioinformatics↗

bioRxiv2023

Local interneurons in the murine visual thalamus have diverse receptive fields and can provide feature selective inhibition to relay cells.

By influencing the type and quality of information that relay cells transmit, local interneurons in thalamus have a powerful impact on cortex. To define the sensory features that these inhibitory neurons encode, we mapped receptive fields of optogenetically identified cells in the murine dorsolateral geniculate nucleus. Although few in number, local interneurons had diverse types of receptive fields, like their counterpart relay cells. This result differs markedly from visual cortex, where inhibitory cells are typically less selective than excitatory cells. To explore how thalamic interneurons might converge on relay cells, we took a computational approach. Using an evolutionary algorithm to search through a library of interneuron models generated from our results, we show that aggregated output from different groups of local interneurons can simulate the inhibitory component of the relay cells receptive field. Thus, our work provides proof-of-concept that groups of diverse interneurons can supply feature-specific inhibition to relay cells.

neuroscience↗

bioRxiv2023

Collective dynamics of formin and microtubule and its crosstalk mediated by FHDC1

The coordination between actin and microtubule network is crucial, yet our understanding of the underlying mechanisms remains limited. In this study, we used travelling waves in the cell cortex to characterize the collective dynamics of cytoskeletal networks. Our findings show that Cdc42 and F-BAR-dependent actin waves in mast cells are mainly driven by formin-mediated actin polymerization, with the microtubule-binding formin FH2 domain-containing protein 1 (FHDC1) identified as an early regulator. The depolymerization of microtubules coincides with the nucleation of actin waves, and the concurrent release of FHDC1 from microtubule is required for actin waves. Lastly, we show the importance of the actin-microtubule linkage mediated by FHDC1 in crucial cellular processes such as cell division and migration. Our data provided molecular insights into the nucleation mechanisms of actin waves and uncover an antagonistic interplay between microtubule and actin polymerization in their collective dynamics.

cell biology↗

bioRxiv2023

HCCDB v2.0: Decompose the Expression Variations by Single-cell RNA-seq and Spatial Transcriptomics in HCC

Large-scale transcriptomic data are crucial for understanding the molecular features of hepatocellular carcinoma (HCC). By integrating 15 transcriptomic datasets of HCC clinical samples, the first version of HCCDB was released in 2018. The meta-analysis of differentially expressed genes and prognosis-related genes across multiple datasets provides a systematic view of the altered biological processes and the inter-patient heterogeneities of HCC with high reproducibility and robustness. After four years, the database needs to integrate recently published datasets. Furthermore, the latest single-cell and spatial transcriptomics provided a great opportunity to decipher the complex gene expression variations at the cellular level with spatial architecture. Here, we present HCCDB v2.0, an updated version that combines bulk, single-cell, and spatial transcriptomic data of HCC clinical samples. It dramatically expands the bulk sample size, adding 1656 new samples of 11 datasets to the existing 3917 samples, thereby enhancing the reliability of transcriptomic meta-analysis. A total of 182,832 cells and 69,352 spatial spots are added to the single-cell and spatial transcriptomics sections, respectively. A novel single-cell level and 2-dimension (sc-2D) metric was proposed to summarize the cell type-specific and dysregulated gene expression patterns. Results are all graphically visualized in our online portal, allowing users to easily retrieve data through a user-friendly interface and navigate between different views. With extensive clinical phenotypes and transcriptomic data in the database, we show two applications for identifying prognosis-associated cells and tumor microenvironment. HCCDB v2.0 is available at http://lifeome.net/database/hccdb2.

cancer biology↗

bioRxiv2023

APOE-NOTCH Axis Governs Elastogenesis During Human Cardiac Valve Remodeling

BackgroundValve remodeling is a complex process involving extracellular matrix organization, development of trilaminar structures, and physical elongation of valve leaflets. However, the cellular and molecular mechanisms regulating valve remodeling and their roles in congenital valve disorders remain poorly understood. MethodsSemilunar valves and atrioventricular valves from healthy and age-matched human fetal hearts with pulmonary stenosis (PS) were collected. Single-Cell RNA-sequencing (scRNA-seq) was performed to determine the transcriptomic landscape of multiple valvular cell subtypes in valve remodeling and disease. Spatial localization of newly-identified cell subtypes was determined via immunofluorescence and RNA in situ hybridization. The molecular mechanisms mediating valve development was investigated utilizing primary human fetal heart valve interstitial cells (VICs) and endothelial cells (VECs). ResultsscRNA-seq analysis of healthy human fetal valves identified a novel APOE+ elastin-producing VIC subtype (Elastin-VICs) spatially located underneath VECs sensing the unidirectional flow. Knockdown of APOE in fetal VICs resulted in significant elastogenesis defects. In pulmonary valve with PS, we observed decreased expression of APOE and other genes regulating elastogenesis such as EMILIN1 and LOXL1, as well as elastin fragmentation. These findings suggested the crucial role of APOE in regulating elastogenesis during valve remodeling. Furthermore, cell-cell interaction analysis revealed that JAG1 from unidirectional VECs activates NOTCH signaling in Elastin-VICs through NOTCH3. In vitro Jag1 treatment in VICs increased elastogenesis, while similar observations were found in VICs co-cultured with VECs in the presence of unidirectional flow. Notably, we found that the JAG1-NOTCH3 signaling pair was drastically reduced in the PS valves. Lastly, we demonstrated that APOE is indispensable for JAG1-induced NOTCH activation in VICs, reinforcing the presence of a synergistic intrinsic and external regulatory network involving APOE and NOTCH signaling that is responsible for regulating elastogenesis during human valve remodeling. ConclusionscRNA-seq analysis of human fetal valves identified a novel Elastin-VIC subpopulation, and revealed mechanism of intrinsic APOE and external NOTCH signaling in regulating elastogenesis during cardiac valve remodeling. These mechanisms may contribute to deciphering the pathogenesis of elastin malformation in congenital valve diseases. Clinical Perspective What Is New?O_LIHigh-resolution single-cell transcriptome atlas generated from healthy human fetal heart valves and valves affected by pulmonary stenosis during the early phase of valve remodeling prior to birth. C_LIO_LIA unique subset of valve interstitial cells (VICs) that produce elastin (Elastin-VICs) was identified. C_LIO_LIElastin-VICs specifically located underneath the valve endothelial cells (VECs) sensing unidirectional flow, and played a crucial role in elastin maturation via the expression of APOE. C_LIO_LIElastin-VICs communicated with adjacent VECs via the JAG1-NOTCH signaling, facilitating elastin formation and valve remodeling. C_LI What Are the Clinical Implications?O_LIElastin-VICs from patient valvular tissues with Pulmonary Stenosis exhibit decreased APOE-NOTCH signaling and elastin fragmentation. C_LIO_LIDirect targeting of APOE and NOTCH signaling could be a novel approach to promote elastin fiber formation and valve remodeling in patients with valvular defects. C_LI

bioinformatics↗

bioRxiv2023

An single oscillating proto-hypothalamic neuron gates taxis behavior in the primitive chordate Ciona

Ciona larvae display a number of behaviors, including negative phototaxis. In negative phototaxis, the larvae first perform short spontaneous rhythmic casting swims. As larvae cast in a light field, their photoreceptors are directionally shaded by an associated pigment cell, providing a phototactic cue. This then evokes an extended negative taxis swim. We report here that the larval forebrain of Ciona has a previously uncharacterized single slow-oscillating inhibitory neuron (neuron cor-assBVIN78) that projects to the midbrain, where it targets key interneurons of the phototaxis circuit known as the photoreceptor relay neurons. The anatomical location, gene expression and oscillation of cor-assBVIN78 suggest homology to oscillating neurons of the vertebrate hypothalamus. Ablation of cor-assBVIN78 results in larvae showing extended phototaxis-like swims, but which occur in the absence of phototactic cues. These results indicate that cor-assBVIN78 has a gating activity on phototaxis by projecting temporally-oscillating inhibition to the photoreceptor relay neurons. However, in intact larvae the frequency of cor-assBVIN78 oscillation does not match that of the rhythmic spontaneous swims, indicating that the troughs in oscillations do not themselves initiate swims, but rather that cor-assBVIN78 may modulate the phototaxis circuit by filtering out low level inputs while restricting them temporally to the troughs in inhibition.

neuroscience↗

bioRxiv2023

A whole nervous system atlas of glutamate receptors reveals distinct receptor roles in sensorimotor circuits

A goal of connectomics is to reveal the links between neural circuits and behavior. Larvae of the primitive chordate Ciona are well-suited to make contributions in this area. The small size of the Ciona larval nervous system ([~]180 neurons) has facilitated the full characterization of a connectome. In addition, the larvae display a range of behaviors that are readily quantified in both normal and manipulated larvae. Moreover, the small number of neurons allows for a neuron-by-neuron characterization of attributes such as neurotransmitter use. We present here a nervous system-wide atlas of glutamate receptor expression. Included in the atlas are both ionotropic receptors (AMPA, NMDA, and Kainate), and metabotropic receptors. The expression of these receptors is presented in the context of known circuits driving behaviors such as phototaxis, mechanosensation, and looming shadow response. The expression of AMPA and NMDA receptors, in particular, helps to resolve the apparently paradoxical coproduction of GABA and glutamate by some photoreceptors. We find that the targets of these photoreceptors, midbrain relay neurons, primarily express NMDA receptors in the absence of AMPA receptors. This is in agreement with previous results indicating that GABA is the primary neurotransmitter from the photoreceptors evoking a behavioral response (swimming) through a disinhibition mechanism. We hypothesize that NMDA receptors have a modulatory effect in the relay neurons. Other findings reported here are more unexpected. For example, the targets of glutamatergic epidermal sensory neurons (ESNs) do not express any of the ionotropic receptors, yet the ESNs themselves express metabotropic receptors. Thus, we speculate that their production of glutamate may be for communication with neighboring ESNs, rather than to their interneuron targets.

neuroscience↗

bioRxiv2023

SFyNCS detects oncogenic fusions involving non-coding sequences in cancer

Fusion genes are well-known cancer drivers. However, very few known oncogenic fusions involve non-coding sequences. We develop SFyNCS with superior performance to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. We validate fusions using somatic structural variations detected from the genomes. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We detect 165,139 fusions in 9,565 tumor samples across 33 tumor types in the Cancer Genome Atlas cohort. Among them, 72% of the fusions involve non-coding sequences and many are recurrent. We discover two long non-coding RNAs recurrently fused with various partner genes in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.

bioinformatics↗

bioRxiv2023

Artificial Intelligence Boosted Molecular Dynamics

We have developed a new Deep Boosted Molecular Dynamics (DBMD) method. Probabilistic Bayesian neural network models were implemented to construct boost potentials that exhibit Gaussian distribution with minimized anharmonicity, thereby allowing for accurate energetic reweighting and enhanced sampling of molecular simulations. DBMD was demonstrated on model systems of alanine dipeptide and the fast-folding protein and RNA structures. For alanine dipeptide, 30ns DMBD simulations captured up to 83-125 times more backbone dihedral transitions than 1{micro}s conventional molecular dynamics (cMD) simulations and were able to accurately reproduce the original free energy profiles. Moreover, DBMD sampled multiple folding and unfolding events within 300ns simulations of the chignolin model protein and identified low-energy conformational states comparable to previous simulation findings. Finally, DBMD captured a general folding pathway of three hairpin RNAs with the GCAA, GAAA, and UUCG tetraloops. Based on Deep Learning neural network, DBMD provides a powerful and generally applicable approach to boosting biomolecular simulations. DBMD is available with open source in OpenMM at https://github.com/MiaoLab20/DBMD/.

bioinformatics↗

bioRxiv2023

Chromosome-level genome assembly of tree sparrow reveals a burst of new genes driven by segmental duplications

The creation of new genes is a major force of evolution. Despite as an important mechanism that generated new genes, segmental duplication (SD) has yet to be accurately identified and fully characterized in birds because the repetitive complexity leads to misassignment and misassembly of sequence. In addition, SD may lead to new gene copies, which makes it possible to test the "out of testis" hypothesis which suggests genes are frequently born with testis-specific expression. Using a high-quality chromosome-level assembly, we performed a systematic analysis and presented a comprehensive landscape of SDs in tree sparrow (Passer montanus). We detected co-localization of newly expanded genes and long terminal repeat retrotransposons (LTR-RTs), both of which are derived from SDs and enriched in microchromosomes. The newly expanded genes are mostly found in eight families including C2H2ZNF, OR, PIM, PAK, MROH, HYDIN, HSF and ITPRIPL. The large majority of new members of these eight families have evolved to pseudogenes, whereas there still some new copies preserved transcriptional activity. Among the transcriptionally active new members, new genes from different families with diverse structures and functions shared a similar testis-biased expression pattern, which is consistent with the "out of testis" hypothesis. Through a case analysis of the high-quality genome assembly of tree sparrow, we reveal that the SDs contribute to the formation of new genes. Our study provides a comprehensive understanding of the emergence, expression and fate of duplicated genes and how the SDs might participate in these processes and shape genome evolution.

genomics↗

bioRxiv2023

Deep Learning Dynamic Allostery of G-Protein-Coupled Receptors

G-protein-coupled receptors (GPCRs) are the largest superfamily of human membrane proteins and represent primary targets of [~]1/3 of currently marketed drugs. Allosteric modulators have emerged as more selective drug candidates compared with orthosteric agonists and antagonists. However, many X-ray and cryo-EM structures of GPCRs resolved so far exhibit negligible differences upon binding of positive and negative allosteric modulators (PAMs and NAMs). Mechanism of dynamic allosteric modulation in GPCRs remains unclear. In this work, we have systematically mapped dynamic changes in free energy landscapes of GPCRs upon binding of allosteric modulators using the Gaussian accelerated molecular dynamics (GaMD), Deep Learning (DL) and free energy prOfiling Workflow (GLOW). A total of 18 available high-resolution experimental structures of allosteric modulator-bound class A and B GPCRs were collected for simulations. A number of 8 computational models were generated to examine selectivity of the modulators by changing their target receptors to different subtypes. All-atom GaMD simulations were performed for a total of 66 {micro}s on 44 GPCR systems in the presence/absence of the modulator. DL and free energy calculations revealed significantly reduced conformational space of GPCRs upon modulator binding. While the modulator-free GPCRs often sampled multiple low-energy conformational states, the NAMs and PAMs confined the inactive and active agonist-G protein-bound GPCRs, respectively, to mostly only one specific conformation for signaling. Such cooperative effects were significantly reduced for binding of the selective modulators to "non-cognate" receptor subtypes in the computational models. Therefore, comprehensive DL of extensive GaMD simulations has revealed a general dynamic mechanism of GPCR allostery, which will greatly facilitate rational design of selective allosteric drugs of GPCRs.

bioinformatics↗

bioRxiv2023

A dynamic partitioning mechanism polarizes membrane protein distribution

The plasma membrane is widely regarded as the hub of the signal transduction network activities that drives numerous physiological responses, including cell polarity and migration. Yet, the symmetry breaking process in the membrane, that leads to dynamic compartmentalization of different proteins, remains poorly understood. Using multimodal live-cell imaging, here we first show that multiple endogenous and synthetic lipid-anchored proteins, despite maintaining stable tight association with the inner leaflet of the plasma membrane, were unexpectedly depleted from the membrane domains where the signaling network was spontaneously activated such as in the new protrusions as well as within the propagating ventral waves. Although their asymmetric patterns resembled those of standard peripheral "back" proteins such as PTEN, unlike the latter, these lipidated proteins did not dissociate from the membrane upon global receptor activation. Our experiments not only discounted the possibility of recurrent reversible translocation from membrane to cytosol as it occurs for weakly bound peripheral membrane proteins, but also ruled out the necessity of directed vesicular trafficking and cytoskeletal supramolecular structure-based restrictions in driving these dynamic symmetry breaking events. Selective photoconversion-based protein tracking assays suggested that these asymmetric patterns instead originate from the inherent ability of these membrane proteins to "dynamically partition" into distinct domains within the plane of the membrane. Consistently, single-molecule measurements showed that these lipid-anchored molecules have substantially dissimilar diffusion profiles in different regions of the membrane. When these profiles were incorporated into an excitable network-based stochastic reaction-diffusion model of the system, simulations revealed that our proposed "dynamic partitioning" mechanism is sufficient to give rise to familiar asymmetric propagating wave patterns. Moreover, we demonstrated that normally uniform integral and lipid-anchored membrane proteins in Dictyostelium and mammalian neutrophil cells can be induced to partition spatiotemporally to form polarized patterns, by optogenetically recruiting membrane domain-specific peptides to these proteins. Together, our results indicate "dynamic partitioning" as a new mechanism of plasma membrane organization, that can account for large-scale compartmentalization of a wide array of lipid-anchored and integral membrane proteins in different physiological processes.

cell biology↗

bioRxiv2022

Ligand Gaussian accelerated molecular dynamics 2 (LiGaMD2): Improved calculations of ligand binding thermodynamics and kinetics with closed protein pocket

Ligand binding thermodynamics and kinetics are critical parameters for drug design. However, it has proven challenging to efficiently predict ligand binding thermodynamics and kinetics from molecular simulations due to limited simulation timescales. Protein dynamics especially in the ligand binding pocket often plays an important role in ligand binding. Based on our previously developed Ligand Gaussian accelerated molecular dynamics (LiGaMD), here we present LiGaMD2 in which a selective boost potential was applied to both the ligand and protein residues in the binding pocket to improve sampling of ligand binding and dissociation. To validate the performance of LiGaMD2, the T4 lysozyme (T4L) mutants with open and closed pockets bound by different ligands were chosen as model systems. LiGaMD2 could efficiently capture repetitive ligand dissociation and binding within microsecond simulations of all T4L systems. The obtained ligand binding kinetic rates and free energies agreed well with available experimental values and previous modeling results. Therefore, LiGaMD2 provides an improved approach to sample opening of closed protein pockets for ligand dissociation and binding, thereby allowing for efficient calculations of ligand binding thermodynamics and kinetics.

biophysics↗

bioRxiv2022

Structure of the Wnt-Frizzled-LRP6 initiation complex reveals the basis for co-receptor discrimination

Wnt morphogens are critical for embryonic development and tissue regeneration. Canonical Wnts form ternary receptor complexes composed of tissue-specific Frizzled receptors together with the shared LRP5/6 co-receptors to initiate {beta}-catenin signaling. The structure of a ternary complex of an affinity-matured XWnt8-Frizzled8-LRP6 complex elucidates the basis of co-receptor discrimination by canonical Wnts by means of their N-termini and linker domains that engage the LRP6 E1E2 domain funnels. Chimeric Wnts bearing modular linker grafts were able to transfer LRP6 domain specificity between different Wnts and enable non-canonical Wnt5a to signal through the canonical pathway. Synthetic peptides comprising the linker domain serve as Wnt-specific antagonists. The structure of the ternary complex provides a topological blueprint for the orientation and proximity of Frizzled and LRP6 within the Wnt cell surface signalosome.

biophysics↗

bioRxiv2022

Bacillus velezensis SQR9 sways the rhizosphere community and its sociality toward cooperation and plant growth promotion

According to the Lotka-Volterra competition model, intraspecific competition in plant-associated microbial communities should be stronger than interspecific competition. However, there is limited information on whether microbial communities follow this pattern and how disturbance by a newcomer affects them. Given the increasing popularity of probiotics, filling this knowledge gap could help guide future coexistence research. Here, we show that inoculation with a known probiotic, B. velezensis SQR9 shifts species co-occurrence patterns by decreasing the diversity of more distant species and promoting the growth of more closely related species, especially within the Bacillus community. By testing the sociality of Bacillus rhizosphere isolates, we then demonstrated that SQR9 increases the frequency of cooperative interactions in the Bacillus community, which may contribute to the promotion of plant growth. Finally, we provide an ecosystem framework comprising the strains genetic relatedness, metabolic niche space and social compatibility for the efficient and reliable assembly of Bacillus consortia. These findings shed new light on the ecological mechanisms underlying the beneficial effects of probiotics on host fitness.

microbiology↗

bioRxiv2022

Pharmacological hallmarks of allostery at the M4 muscarinic receptor elucidated through structure and dynamics

Allosteric modulation of G protein-coupled receptors (GPCRs) is a major paradigm in drug discovery. Despite decades of research, a molecular level understanding of the general principals that govern the myriad pharmacological effects exerted by GPCR allosteric modulators remains limited. The M4 muscarinic acetylcholine receptor (M4 mAChR) is a well-validated and clinically relevant allosteric drug target for several major psychiatric and cognitive disorders. Here, we present high-resolution cryo-electron microscopy structures of the M4 mAChR bound to a cognate Gi1 protein and the high affinity agonist, iperoxo, in the absence and presence of two different positive allosteric modulators, LY2033298 or VU0467154. We have also determined the structure of the M4 mAChR-Gi1 complex bound to its endogenous agonist, acetylcholine (ACh). Structural comparisons, together with molecular dynamics, mutagenesis, and pharmacological validations, have provided in-depth insights into the role of structure and dynamics in orthosteric and allosteric ligand binding, global mechanisms of receptor activation, cooperativity, probe-dependence, and species variability; all key hallmarks underpinning contemporary GPCR drug discovery.

pharmacology and toxicology↗

bioRxiv2022

TIST: Transcriptome and Histopathological Image Integrative Analysis for Spatial Transcriptomics

Sequencing-based spatial transcriptomics (ST) is an emerging technique to study in situ gene expression patterns at the whole-genome scale. In addition to transcriptomic data, the technique usually generates matched histopathological images for the same tissue sample. ST data analysis is complicated by severe technical noise; matched histopathological images with high spatial continuity and resolution introduce complementary cellular phenotypical information and provide a chance to mitigate the noise in ST data. Hence, we propose a novel ST data analysis method called transcriptome and histopathological image integrative analysis for spatial transcriptomics (TIST), which integrates the information from sequencing-based ST data and histopathological images. TIST uses a Markov random field (MRF) model to learn the macroscopic cellular features from histopathological images and devises a random-walk-based strategy to integrate the extracted image features, the transcriptomic features and the location information for spatial cluster (SC) identification and gene expression enhancement. We tested TIST both on simulated datasets and on 33 real datasets; we found that TIST achieved superior performance on multiple tasks, which illustrates the utility of this method in facilitating the discovery of biological insights from sequencing-based ST data.

bioinformatics↗