Diverse Tissues Research Articles

Multivariate analysis of metabolic state vulnerabilities across diverse cancer contexts reveals synthetically lethal associations.

Targeting the distinct metabolic needs of tumor cells has recently emerged as a promising strategy for cancer therapy. The heterogeneous, context-dependent nature of cancer cell metabolism, however, poses challenges in identifying effective therapeutic interventions. Here, we utilize various unsupervised and supervised multivariate modeling approaches to systematically pinpoint recurrent metabolic states within hundreds of cancer cell lines, elucidate their association with tumor lineage and growth environments, and uncover vulnerabilities linked to their metabolic states across diverse genetic and tissue contexts. We validate key findings via analysis of data from patient-derived tumors and pharmacological screens, and by performing new genetic and pharmacological experiments. Our analysis uncovers new synthetically lethal associations between the tumor metabolic state (e.g., oxidative phosphorylation), driver mutations (e.g., loss of tumor suppressor PTEN), and actionable biological targets (e.g., mitochondrial electron transport chain). Investigating the mechanisms underlying these relationships can inform the development of more precise and context-specific, metabolism-targeted cancer therapies.

Digital light processing printed hydrogel scaffolds with adjustable modulus

Hydrogels are extensively explored as biomaterials for tissue scaffolds, and their controlled fabrication has been the subject of wide investigation. However, the tedious mechanical property adjusting process through formula control hindered their application for diverse tissue scaffolds. To overcome this limitation, we proposed a two-step process to realize simple adjustment of mechanical modulus over a broad range, by combining digital light processing (DLP) and post-processing steps. UV-curable hydrogels (polyacrylamide-alginate) are 3D printed via DLP, with the ability to create complex 3D patterns. Subsequent post-processing with Fe3+ ions bath induces secondary crosslinking of hydrogel scaffolds, tuning the modulus as required through soaking in solutions with different Fe3+ concentrations. This innovative two-step process offers high-precision (10 μm) and broad modulus adjusting capability (15.8–345 kPa), covering a broad range of tissues in the human body. As a practical demonstration, hydrogel scaffolds with tissue-mimicking patterns were printed for cultivating cardiac tissue and vascular scaffolds, which can effectively support tissue growth and induce tissue morphologies.

Bioinspired Printable Tough Adhesives with In Situ Benignly Triggered Mechanical Enhancements

AbstractAdhesives can intimately connect humans to machines, seamlessly bond diverse tissues in the human body, and manage various diseases. However, the precise spatial control of wet and tough adhesion of biocompatible hydrogels on biological tissues remains a major challenge. Inspired by the bioglue secreted by sandcastle worms, the design of printable tough adhesives (PTAs) is proposed, a supramolecular hydrogel that can be printed into defined structures, in situ mechanically reinforced into a tough matrix with physiologically relevant benign triggers, and strongly adhere to diverse substrates. With carefully selected polymer components and ratios, it is discovered that the 3D printed PTAs can achieve a marked increase in toughness, tensile strength, and stiffness after being immersed in water/saline solution or attached to biological tissues. To assess the robust toughening mechanism triggered by the supramolecular interactions, the effects of polymer content and pH on the mechanical performance of PTAs and the kinetics of their triggered reinforcement are thoroughly investigated. The potential of PTAs is further demonstrated for manufacturing tough connective tissue mimetics, controlling patterned bioadhesion, and designing programmable 4D soft robotics. The bioinspired, printable, benignly triggerable, and adhesive supramolecular PTAs are expected to find broad applications in engineering and medicine.

Simplifying Stem Cell Therapy for IRs: Exploring New Horizons in Interventional Radiology and Cell Therapy

AbstractThe effective treatment of various diseases requires not only medications but also precise delivery methods to the body and specific organs. In this regard, radiology plays a crucial role, acting as the eyes of physicians. In contrast, interventional radiology serves as its hands, acting as one of the most effective drug delivery systems. Among interventional radiology disciplines, arterial drug delivery through arteries holds paramount importance as organs primarily receive nourishment directly from them. Furthermore, regenerative medicine is a burgeoning field dedicated to repairing diverse body tissues without relying on pharmaceutical drugs. Stem cells, inherent in various parts of our bodies, are vital for tissue regeneration and reconstruction. Depending on the treatment approach, stem cells can be sourced from the patient's body (autologous) or another individual (allogeneic). There exist various types of stem cells across species, with regenerative properties observed in animals and even plants. However, targeted cell therapy is preferred over systematic injections throughout the body for better efficacy. This article aims to familiarize interventionalists with stem cells and provide them with a clear and helpful explanation of their functions, mechanisms of action, different sources, and other relevant aspects. This will help them select the most appropriate cells for their therapeutic purposes. By comprehensively understanding the significance of stem cells in interventional radiology, we can implement optimal methodologies to address diverse medical conditions efficiently.

Incorporation of decellularized-ECM in graphene-based scaffolds enhances axonal outgrowth and branching in neuro-muscular co-cultures.

Peripheral nerve and large-scale muscle injuries result in significant disability, necessitating the development of biomaterials that can restore functional deficits by promoting tissue regrowth in an electroactive environment. Among these materials, graphene is favored for its high conductivity, but its low bioactivity requires enhancement through biomimetic components. In this study, we extrusion printed graphene-poly(lactide-co-glycolide) (graphene) lattice scaffolds, aiming to increase bioactivity by incorporating decellularized extracellular matrix (dECM) derived from mouse pup skeletal muscle. We first evaluated these scaffolds using human-induced pluripotent stem cell (hiPSC)-derived motor neurons co-cultured with supportive glia, observing significant improvements in axon outgrowth. Next, we tested the scaffolds with C2C12 mouse and human primary myoblasts, finding no significant differences in myotube formation between dECM-graphene and graphene scaffolds. Finally, using a more complex hiPSC-derived 3D motor neuron spheroid model co-cultured with human myoblasts, we demonstrated that dECM-graphene scaffolds significantly improved axonal expansion towards peripheral myoblasts and increased axonal network density compared to graphene-only scaffolds. Features of early neuromuscular junction formation were identified near neuromuscular interfaces in both scaffold types. These findings suggest that dECM-graphene scaffolds are promising candidates for enhancing neuromuscular regeneration, offering robust support for the growth and development of diverse neuromuscular tissues.

Cellular Pathophysiology in Zoonotic Transmission of Orthopoxviruses (OPXVs) from Animal Host to Human

Orthopoxviruses (OPXVs), belonging to the Poxviridae family, are large, double-stranded DNA viruses known for their zoonotic potential and impact on human and animal health. This review explores the transmission dynamics of OPXVs from animal hosts to humans and the underlying cellular pathophysiological mechanisms. Animal hosts such as rodents, primates, and livestock are central in the ecology of OPXVs, with transmission typically occurring through direct contact or exposure to contaminated materials. Clinical manifestations in animals range from skin lesions and fever to respiratory and gastrointestinal symptoms, reflecting the diverse tissue tropism of these viruses. Humans primarily acquire OPXVs through contact with infected animals or their products, highlighting the zoonotic risk posed by these viruses. At the cellular level, OPXV infections involve complex interactions between viral proteins and host cell receptors, triggering robust immune responses characterized by cytokine release and inflammation. The viruses replicate within the cytoplasm without accessing the host cell nucleus, evading detection by nuclear sensors and exploiting cellular machinery for viral assembly. A comprehensive grasp of OPXV transmission dynamics and cellular pathophysiology is requisite to devise effective prevention and control strategies. Insights into host immune responses and viral replication mechanisms provide a foundation for antiviral drug development and vaccine strategies. This review synthesizes current knowledge on OPXV ecology, transmission, and cellular interactions, emphasizing their significance in veterinary, medical, and public health contexts.

Synthetic Genitourinary Image Synthesis via Generative Adversarial Networks: Enhancing Artificial Intelligence Diagnostic Precision.

In the realm of computational pathology, the scarcity and restricted diversity of genitourinary (GU) tissue datasets pose significant challenges for training robust diagnostic models. This study explores the potential of Generative Adversarial Networks (GANs) to mitigate these limitations by generating high-quality synthetic images of rare or underrepresented GU tissues. We hypothesized that augmenting the training data of computational pathology models with these GAN-generated images, validated through pathologist evaluation and quantitative similarity measures, would significantly enhance model performance in tasks such as tissue classification, segmentation, and disease detection. To test this hypothesis, we employed a GAN model to produce synthetic images of eight different GU tissues. The quality of these images was rigorously assessed using a Relative Inception Score (RIS) of 1.27 ± 0.15 and a Fréchet Inception Distance (FID) that stabilized at 120, metrics that reflect the visual and statistical fidelity of the generated images to real histopathological images. Additionally, the synthetic images received an 80% approval rating from board-certified pathologists, further validating their realism and diagnostic utility. We used an alternative Spatial Heterogeneous Recurrence Quantification Analysis (SHRQA) to assess the quality of prostate tissue. This allowed us to make a comparison between original and synthetic data in the context of features, which were further validated by the pathologist's evaluation. Future work will focus on implementing a deep learning model to evaluate the performance of the augmented datasets in tasks such as tissue classification, segmentation, and disease detection. This will provide a more comprehensive understanding of the utility of GAN-generated synthetic images in enhancing computational pathology workflows. This study not only confirms the feasibility of using GANs for data augmentation in medical image analysis but also highlights the critical role of synthetic data in addressing the challenges of dataset scarcity and imbalance. Future work will focus on refining the generative models to produce even more diverse and complex tissue representations, potentially transforming the landscape of medical diagnostics with AI-driven solutions.

Emerging clinical role of proprotein convertase subtilisin/kexin type 9 inhibition-Part one: Pleiotropic pro-atherosclerotic effects of PCSK9.

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is primarily recognized for its role in lipid metabolism, but recent evidence suggests that it may have broader implications due to its diverse tissue expression. This review aims to explore the multifaceted functions of PCSK9, highlighting its pro-atherosclerotic effects, including its impact on circulating lipoprotein variables, non-low-density lipoprotein receptors, and various cell types involved in atherosclerotic plaque development. PCSK9 exhibits diverse roles beyond lipid metabolism, potentially contributing to atherosclerosis through multiple pathways. Understanding these mechanisms could offer new insights into therapeutic strategies targeting PCSK9 for cardiovascular disease management.

A systematic review of the role of TREM2 in Alzheimer's disease.

Given the established genetic linkage between triggering receptors expressed on myeloid cells 2 (TREM2) and Alzheimer's disease (AD), an expanding research body has delved into the intricate role of TREM2 within the AD context. However, a conflicting landscape of outcomes has emerged from both in vivo and in vitro investigations. This study aimed to elucidate the multifaceted nuances and gain a clearer comprehension of the role of TREM2. PubMed database was searched spanning from its inception to January 2022. The search criteria took the form of ("Alzheimer's disease" OR "AD") AND ("transgenic mice model" OR "transgenic mouse model") AND ("Triggering receptor expressed on myeloid cells" OR "TREM2"). Inclusion criteria consisted of the following: (1) publication of original studies in English; (2) utilization of transgenic mouse models for AD research; and (3) reports addressing the subject of TREM2. A total of 43 eligible articles were identified. Our analysis addresses four pivotal queries concerning the interrelation of TREM2 with microglial function, Aβ accumulation, tau pathology, and inflammatory processes. However, the diverse inquiries posed yielded inconsistent responses. Nevertheless, the inconsistent roles of TREM2 within these AD mouse models potentially hinge upon factors such as age, sex, brain region, model type, and detection methodologies. This review substantiates the evolving understanding of TREM2's disease progression-dependent impacts. Furthermore, it reviews the interplay between TREM2 and its effects across diverse tissues and temporal stages.

Evaluation of bacteriophages for the alleviation of potential bacterial contamination risks in developmental engineering.

This research aimed to address the potential bacterial contamination risks in developmental engineering (DE) using bacteriophages. To compare and contrast the exemplar Escherichia coli T4 and M13 bacteriophages, human dermal fibroblasts cultivated on culture plates, natural cellulosic scaffolds, and poly(methyl methacrylate) (PMMA) particles were utilized as two-dimensional (2D) cell, three-dimensional (3D) tissue, and modular tissue culture models, respectively. When directly introduced into these distinct culture systems, both phages survived, exhibited no significant effects on the cultured cells or tissues, yet displayed their potentials to alleviate the infections caused by corresponding bacterial host cells. Apart from direct addition into the culture medium, both phages were also coated on PMMA, polystyrene, poly(lactic acid) particles with different diameters (5, 10, 30, and 100 µm) and cellulosic scaffolds. The coated phages endured the coating processes and demonstrated their viabilities in plaque assays. Further testing indicated that the phages coated on the PMMA particles tolerated multiple deliberate rinses and centrifugations, but not thermal treatment at 60-80°C. In summary, T4 and M13 bacteriophages not only manifested their antibacterial functions in diverse 2D cell, 3D tissue, and modular tissue culture systems, but also demonstrated their potentials of coating modular scaffolds to alleviate the bacterial contamination risks in DE.

VascuConNet: an enhanced connectivity network for vascular segmentation.

Medical image segmentation commonly involves diverse tissue types and structures, including tasks such as blood vessel segmentation and nerve fiber bundle segmentation. Enhancing the continuity of segmentation outcomes represents a pivotal challenge in medical image segmentation, driven by the demands of clinical applications, focusing on disease localization and quantification. In this study, a novel segmentation model is specifically designed for retinal vessel segmentation, leveraging vessel orientation information, boundary constraints, and continuity constraints to improve segmentation accuracy. To achieve this, we cascade U-Net with a long-short-term memory network (LSTM). U-Net is characterized by a small number of parameters and high segmentation efficiency, while LSTM offers a parameter-sharing capability. Additionally, we introduce an orientation information enhancement module inserted into the model's bottom layer to obtain feature maps containing orientation information through an orientation convolution operator. Furthermore, we design a new hybrid loss function that consists of connectivity loss, boundary loss, and cross-entropy loss. Experimental results demonstrate that the model achieves excellent segmentation outcomes across three widely recognized retinal vessel segmentation datasets, CHASE_DB1, DRIVE, and ARIA.

ETMR-26. MIR-34/449 FAMILY PLAYS A CRUCIAL ROLE IN CHOROID PLEXUS MULTICILIATION AND TUMORIGENESIS

Abstract BACKGROUND Choroid plexus (CP), an epithelial structure within the brain ventricles, produces cerebrospinal fluid and serves barrier functions in the brain. Primary CP neoplasms are rare intracranial tumors that predominantly occurs in childhood. Recent studies revealed multiciliated cells in the CP in humans and mice. In contrast, benign CP papilloma, and malignant CP carcinoma (CPC) in humans are characterized by solitary cilia, and disturbances to multiciliation program directed by transcription factor GMNC. Additionally, most CPC in humans carry mutations in TP53 tumor suppressor. Consistently, Trp53-deficient CPC in mice display singular cilia consequent to defects in GMNC multiciliation program. Thus, the impairment of multiciliation enables tumor cell proliferation. MicroRNAs (miRNAs) are non-coding small RNAs with gene regulatory functions. Specifically, the mir-34/449 family comprises of six miRNAs collaborate to influence multiciliation in diverse tissues but role of mir-34/449 family in the brain is poorly understood. Knowledge of multiciliation program regulation may provide crucial insights into tumor suppression mechanisms in CPC. METHODS To investigate the role of mir-34/449 family in the CP, human CP organoid and mir-34/449 mutant animals were used. RNAscope, In situ hybridization as well as immunofluorescence staining was utilized to identify gene expression in tissues. RESULTS Preliminary studies revealed GMNC program activity and multiciliated cells in CP organoid derived from human induced pluripotent stem cells. Disruption of the mir-34/449 family led to supernumerary cilia and ectopic multiciliation program activity in the CP. Importantly, Trp53-deficient CPC exhibited distinct expression of the mir-34/449 family. Further, sequencing studies revealed an overlap of differentially expressed miRNAs in CP tumors in humans and mice, with an enrichment of the mir-34/449 family. CONCLUSIONS Together, these findings indicate that the mir-34/449 family regulates multiciliation in the CP, whereas the study of its interactions with the multiciliation program holds the key to understanding multiciliation as a tumor suppression pathway in CPC.

Breast organoid suspension cultures maintain long-term estrogen receptor expression and responsiveness.

Organoid cultures offer a powerful technology to investigate many different aspects of development, physiology, and pathology of diverse tissues. Unlike standard tissue culture of primary breast epithelial cells, breast organoids preserve the epithelial lineages and architecture of the normal tissue. However, existing organoid culture methods are tedious, difficult to scale, and do not robustly retain estrogen receptor (ER) expression and responsiveness in long-term culture. Here, we describe a modified culture method to generate and maintain organoids as suspension cultures in reconstituted basement membrane (™Matrigel). This method improves organoid growth and uniformity compared to the conventional Matrigel dome embedding method, while maintaining the fidelity of the three major epithelial lineages. Using this adopted method, we are able to culture and passage purified hormone sensing (HS) cells that retain ER responsiveness upon estrogen stimulation in long-term culture. This culture system presents a valuable platform to study the events involved in initiation and evolution of ER-positive breast cancer.

Fine-mapping causal tissues and genes at disease-associated loci.

Heritable diseases often manifest in a highly tissue-specific manner, with different disease loci mediated by genes in distinct tissues or cell types. We propose Tissue-Gene Fine-Mapping (TGFM), a fine-mapping method that infers the posterior probability (PIP) for each gene-tissue pair to mediate a disease locus by analyzing GWAS summary statistics (and in-sample LD) and leveraging eQTL data from diverse tissues to build cis-predicted expression models; TGFM also assigns PIPs to causal variants that are not mediated by gene expression in assayed genes and tissues. TGFM accounts for both co-regulation across genes and tissues and LD between SNPs (generalizing existing fine-mapping methods), and incorporates genome-wide estimates of each tissue's contribution to disease as tissue-level priors. TGFM was well-calibrated and moderately well-powered in simulations; unlike previous methods, TGFM was able to attain correct calibration by modeling uncertainty in cis-predicted expression models. We applied TGFM to 45 UK Biobank diseases/traits (average N = 316K) using eQTL data from 38 GTEx tissues. TGFM identified an average of 147 PIP > 0.5 causal genetic elements per disease/trait, of which 11% were gene-tissue pairs. Implicated gene-tissue pairs were concentrated in known disease-critical tissues, and causal genes were strongly enriched in disease-relevant gene sets. Causal gene-tissue pairs identified by TGFM recapitulated known biology (e.g., TPO-thyroid for Hypothyroidism), but also included biologically plausible novel findings (e.g., SLC20A2-artery aorta for Diastolic blood pressure). Further application of TGFM to single-cell eQTL data from 9 cell types in peripheral blood mononuclear cells (PBMC), analyzed jointly with GTEx tissues, identified 30 additional causal gene-PBMC cell type pairs at PIP > 0.5-primarily for autoimmune disease and blood cell traits, including the biologically plausible example of CD52 in classical monocyte cells for Monocyte count. In conclusion, TGFM is a robust and powerful method for fine-mapping causal tissues and genes at disease-associated loci.

Human trophoblast invasion and migration are mediated by the YAP1-CCN1 pathway: defective signaling in trophoblasts during early-onset severe preeclampsia†.

The transcription coactivator YAP1 mediates the major effects of the Hippo signaling pathway. The CCN family is a small group of glycoproteins known to be downstream effectors of YAP1 in diverse tissues. However, whether CCN family members mediate the effects of YAP1 in human trophoblasts is unknown. In this study, placental expression of both YAP1 and CCN1 was found to be impaired in pregnancies complicated by early-onset severe preeclampsia. CCN1 was expressed not only in cytotrophoblasts, trophoblast columns, and mesenchymal cells, similar to active YAP1, but also in syncytiotrophoblasts of normal first-trimester placental villi; moreover, decidual staining of active YAP1 and CCN1 was found in both interstitial and endovascular extravillous trophoblasts. In cultured immortalized human trophoblastic HTR-8/SVneo cells, knockdown of YAP1 decreased CCN1 mRNA and protein expression and led to impaired cell invasion and migration. Also, CCN1 knockdown negatively affected HTR-8/SVneo cell invasion and migration but not viability. YAP1 knockdown was further found to impair HTR-8/SVneo cell viability via G0/G1 cell cycle arrest and apoptosis, while CCN1 knockdown had minimal effect on cell cycle arrest and no effect on apoptosis. Accordingly, treatment with recombinant CCN1 partially reversed the YAP1 knockdown-induced impairment in trophoblast invasion and migration but not in viability. Thus, CCN1 mediates the effects of YAP1 on human trophoblast invasion and migration but not apoptosis, and decreased placental expression of YAP1 and CCN1 in pregnancies complicated by early-onset severe preeclampsia might contribute to the pathogenesis of this disease.

DNA mismatch and damage patterns revealed by single-molecule sequencing.

Mutations accumulate in the genome of every cell of the body throughout life, causing cancer and other diseases1,2. Most mutations begin as nucleotide mismatches or damage in one of the two strands of the DNA before becoming double-strand mutations if unrepaired or misrepaired3,4. However, current DNA-sequencing technologies cannot accurately resolve these initial single-strand events. Here we develop a single-molecule, long-read sequencing method (Hairpin Duplex Enhanced Fidelity sequencing (HiDEF-seq)) that achieves single-molecule fidelity for base substitutions when present in either one or both DNA strands. HiDEF-seq also detects cytosine deamination-a common type of DNA damage-with single-molecule fidelity. We profiled 134 samples from diverse tissues, including from individuals with cancerpredisposition syndromes, and derive from them single-strand mismatch and damage signatures. We find correspondences between these single-strand signatures and known double-strand mutational signatures, which resolves the identity of the initiating lesions. Tumours deficient in both mismatch repair and replicative polymerase proofreading show distinct single-strand mismatch patterns compared to samples that are deficient in only polymerase proofreading. We also define a single-strand damage signature for APOBEC3A. In the mitochondrial genome, our findings support a mutagenic mechanism occurring primarily during replication. As double-strand DNA mutations are only the end point of the mutation process, our approach to detect the initiating single-strand events at single-molecule resolution will enable studies of how mutations arise in a variety of contexts, especially in cancer and ageing.

A multimodal generative AI copilot for human pathology

Computational pathology1,2 has witnessed considerable progress in the development of both task-specific predictive models and task-agnostic self-supervised vision encoders3,4. However, despite the explosive growth of generative artificial intelligence (AI), there have been few studies on building general-purpose multimodal AI assistants and copilots5 tailored to pathology. Here we present PathChat, a vision-language generalist AI assistant for human pathology. We built PathChat by adapting a foundational vision encoder for pathology, combining it with a pretrained large language model and fine-tuning the whole system on over 456,000 diverse visual-language instructions consisting of 999,202 question and answer turns. We compare PathChat with several multimodal vision-language AI assistants and GPT-4V, which powers the commercially available multimodal general-purpose AI assistant ChatGPT-4 (ref. 6). PathChat achieved state-of-the-art performance on multiple-choice diagnostic questions from cases with diverse tissue origins and disease models. Furthermore, using open-ended questions and human expert evaluation, we found that overall PathChat produced more accurate and pathologist-preferable responses to diverse queries related to pathology. As an interactive vision-language AI copilot that can flexibly handle both visual and natural language inputs, PathChat may potentially find impactful applications in pathology education, research and human-in-the-loop clinical decision-making.

Human γδ T cells in diverse tissues exhibit site-specific maturation dynamics across the life span.

During ontogeny, γδ T cells emerge from the thymus and directly seed peripheral tissues for in situ immunity. However, their functional role in humans has largely been defined from blood. Here, we analyzed the phenotype, transcriptome, function, and repertoire of human γδ T cells in blood and mucosal and lymphoid tissues from 176 donors across the life span, revealing distinct profiles in children compared with adults. In early life, clonally diverse Vδ1 subsets predominate across blood and tissues, comprising naïve and differentiated effector and tissue repair functions, whereas cytolytic Vδ2 subsets populate blood, spleen, and lungs. With age, Vδ1 and Vδ2 subsets exhibit clonal expansions and elevated cytolytic signatures, which are disseminated across sites. In adults, Vδ2 cells predominate in blood, whereas Vδ1 cells are enriched across tissues and express residency profiles. Thus, antigenic exposures over childhood drive the functional evolution and tissue compartmentalization of γδ T cells, leading to age-dependent roles in immunity.

Accurate and efficient integrative reference-informed spatial domain detection for spatial transcriptomics.

Spatially resolved transcriptomics (SRT) studies are becoming increasingly common and large, offering unprecedented opportunities in mapping complex tissue structures and functions. Here we present integrative and reference-informed tissue segmentation (IRIS), a computational method designed to characterize tissue spatial organization in SRT studies through accurately and efficiently detecting spatial domains. IRIS uniquely leverages single-cell RNA sequencing data for reference-informed detection of biologically interpretable spatial domains, integrating multiple SRT slices while explicitly considering correlations both within and across slices. We demonstrate the advantages of IRIS through in-depth analysis of six SRT datasets encompassing diverse technologies, tissues, species and resolutions. In these applications, IRIS achieves substantial accuracy gains (39-1,083%) and speed improvements (4.6-666.0) in moderate-sized datasets, while representing the only method applicable for large datasets including Stereo-seq and 10x Xenium. As a result, IRIS reveals intricate brain structures, uncovers tumor microenvironment heterogeneity and detects structural changes in diabetes-affected testis, all with exceptional speed and accuracy.

De novo prediction of functional effects of genetic variants from DNA sequences based on context-specific molecular information

Deciphering the functional effects of noncoding genetic variants stands as a fundamental challenge in human genetics. Traditional approaches, such as Genome-Wide Association Studies (GWAS), Transcriptome-Wide Association Studies (TWAS), and Quantitative Trait Loci (QTL) studies, are constrained by obscured the underlying molecular-level mechanisms, making it challenging to unravel the genetic basis of complex traits. The advent of Next-Generation Sequencing (NGS) technologies has enabled context-specific genome-wide measurements, encompassing gene expression, chromatin accessibility, epigenetic marks, and transcription factor binding sites, to be obtained across diverse cell types and tissues, paving the way for decoding genetic variation effects directly from DNA sequences only. The de novo predictions of functional effects are pivotal for enhancing our comprehension of transcriptional regulation and its disruptions caused by the plethora of noncoding genetic variants linked to human diseases and traits. This review provides a systematic overview of the state-of-the-art models and algorithms for genetic variant effect predictions, including traditional sequence-based models, Deep Learning models, and the cutting-edge Foundation Models. It delves into the ongoing challenges and prospective directions, presenting an in-depth perspective on contemporary developments in this domain.