Interactive Map Research Articles

ReCRAC: A Stringent Method for Precise Mapping of Protein-RNA Interactions in Yeast.

Intricate interactions between RNA-binding proteins (RBPs) and RNA play pivotal roles in cellular homeostasis, impacting a spectrum of biological processes vital for survival. UV crosslinking methods to study protein-RNA interactions have been instrumental in elucidating their interactions but can be limited by degradation of target proteins during the process, low signal-to-noise ratios, and nonspecific interactions. Addressing these limitations, we describe reCRAC (reverse CRAC), a novel adaptation of the CRAC (crosslinking and analysis of cDNA) technique, optimized for yeast Saccharomyces cerevisiae. Like CRAC, reCRAC applies tandem affinity purification to yield highly enriched protein preparations. However, reCRAC is redesigned to work with unstable proteins. This is achieved by lysing the cells directly into highly denaturing buffer conditions, followed by stringent purification steps. The reCRAC method was successfully applied to the easily degraded yeast protein Pin4, allowing identification of precise binding sites at base-pair resolution with greatly reduced target protein degradation and improved signal-to-noise ratios.

Understanding community perspective on the heritage of locality: memory map methodology

PurposeCommunity involvement in heritage preservation requires appropriate approaches. Sanciai (in Lithuanian: Šanciai) historic district in Kaunas (Lithuania) has long-lasting military and industrial heritage, valuable urban structure and connections to the natural frame of the city. Sanciai residents’ willingness to participate in heritage preservation and urban planning prompted the aim of this research – to develop, test and present the mapping methodology, that would be applicable in the process of community involvement into heritage identification, preservation, interpretation and creation process.Design/methodology/approachThe methods of research included analysis of literature and theoretical research, development and testing of the methodology for the community involvement in heritage identification, preservation, interpretation and creation process. The workshop methodology and interactive online map are presented in this research. The memory map methodology developed and presented in this research includes the elements of mental mapping, design thinking and citizen science.FindingsThe methodology was tested in spring of 2021 in two-day online workshops with the students of pro-gymnasium located in Sanciai. Workshop participants together with workshop coordinator and moderators created different layers of the mental map, collected stories from the members of community and gathered the data for online interactive Sanciai memory map. The evaluation of the methodology and workshop results allowed concluding that memory map methodology is a functioning participant, community and research-oriented approach that can be applied in diverse heritage and community related circumstances.Originality/valueThe originality of the research is determined by the synergistic nature of developed memory map methodology which complements traditional mental mapping with creative hands-on techniques, empathy-oriented tasks and interactive online tool. Moreover, the research reveals the importance of local-global connections in urban studies as active local community became the stimulus for memory map methodology. The two-fold aim of the methodology – community cohesion and empowerment as well as research data collection – contributes to the originality of the research as well.

Exploring the therapeutic potential of marine actinomycetes: a systems biology-based approach for Alzheimer’s disease treatment

Abstract Background This study addresses the urgent need for novel Alzheimer’s Disease (AD) treatments, focusing on the therapeutic potential of marine Actinomycetes compounds. Current AD therapies provide only symptomatic relief, necessitating a paradigm shift toward more effective interventions. Methodology Ninety-one bioactive compounds were methodically identified from Actinomycetes strains in the Indian Ocean. Rigorous ADME analysis and in silico toxicological screening narrowed the selection to 19 compounds, including Helquinoline, Bonactin, Azamerone, and Arcyriaflavin A. These compounds demonstrated favorable drug-like properties and activity against crucial AD targets. Utilizing network pharmacology, a bioactive-target-disease association network was constructed to unveil intricate relationships between compounds and target proteins in the context of AD. Topological analysis highlighted influential targets such as SRC, MAPK1, EGFR, PRKCA, PRKCD, and CDK2. Protein–Protein Interaction (PPI) mapping revealed interconnected pathways influenced by these compounds. Results Focus narrowed to the top 10 pathways associated with key hub–bottleneck genes. The GnRH signaling, EGFR tyrosine kinase inhibitor resistance, and ErbB signaling pathways exhibited remarkable fold enrichment, emphasizing their central roles in AD pathogenesis. The GnRH signaling pathway aligned with endocrine dysregulation in AD, EGFR’s dual role in prion-like propagation and amyloid-β pathology, and ErbB signaling’s multifaceted contributions. Conclusion In conclusion, this study presents marine Actinomycetes compounds as potential poly-pharmacological modulators in AD. Despite promising results, cautious optimism is warranted, requiring further experimental validation. The identified compounds and pathways offer a novel perspective, laying the groundwork for targeted interventions within the intricate landscape of AD. This research contributes to advancing AD therapeutics within a systems biology framework, introducing innovative approaches to address this complex neurodegenerative disorder.

Genomic insights into bamboo witches’ broom disease: pathogenicity and phytohormone biosynthesis in Aciculosporium take

Bamboo witches’ broom disease (WBD), caused by Aciculosporium take Miyake, devastates bamboo forests. Understanding the genome and pathogenic factors of pathogen is crucial for disease control. We employed single-molecule real-time sequencing, Illumina paired-end sequencing, and chromatin interaction mapping techniques to assemble the genome of A. take CCTCC-M2023413, analyze pathogenicity- and phytohormone-biosynthesis-related genes, and compare it to 12 other WBD pathogens. The genome of A. take is 59.24 Mb in size, with 54.32% repeats, 7 chromosomes, 7,105 protein-coding genes, 84 ribosomal RNAs, and 115 transfer RNAs. Predictive analysis of pathogenicity genes found 237 carbohydrate-active enzymes, 1,069 membrane transport proteins, 1,040 pathogen-host interaction genes, 315 virulence factors, and 70 effectors. Most of pathogenicity genes overlapped with repeat-rich regions. Additionally, 172 genes were linked to auxin biosynthesis, 53 to brassinosteroid biosynthesis, and 2 to cis-zeatin biosynthesis. Comparative genomic analysis identified 77 core orthogroups shared by 13 WBD pathogens, played roles in metabolites, genetic information processing, pathogenesis, cis-zeatin biosynthesis, lifespan, and quorum sensing. The miaA gene, crucial for cis-zeatin biosynthesis, is structurally conserved and sequence-diverse among 13 WBD pathogens, with upregulated expression during bamboo WBD pathogenesis. This highlights that cis-zeatin is significant contributor to host pathogenesis, and miaA is a new potential target for controlling WBD. This study provides important insights on preventing and controlling bamboo WBD.

Geosocial Tools for Community Diagnosis and Health Promotion.

Growing research highlights the role of local community contexts in health and well-being. Communities function as central arenas for health promotion as individuals and community spaces interact in daily life. To better communicate the linkages between community and health, we demonstrate the use of a set of geosocial tools for community diagnosis and health promotion, conceptually grounded in the framework of geosocial embeddedness, using data from community surveys and participatory research conducted with local inhabitants to engage their competency. Through a web-based interactive map generated using a geographic information system, we identified public territories in the municipality where greater policy attention is needed to enhance health. Through an intersectional matrix produced using multilevel analysis, we identified precise social groups by intersectional categories that are most at risk of loneliness for targeted intervention. A health radar chart on multidomain indicators illustrated information on group dynamics and longitudinal comparisons for health promotion. Overall, these tools offered not only diagnoses of the most vulnerable social groups for tailored interventions but also insight for policymakers to improve infrastructure and material resources to promote health. We conclude that geosocial tools offer a promising approach toward sharpening health communication and improving health in the community.

Robust Collaborative Visual-Inertial SLAM for Mobile Augmented Reality.

Achieving precise real-time localization and ensuring robustness are critical challenges in multi-user mobile AR applications. Leveraging collaborative information to augment tracking accuracy on lightweight devices and fortify overall system robustness emerges as a crucial necessity. In this paper, we propose a robust centralized collaborative rnulti-agent VI-SLAM system for mobile AR interaction and server-side efficient consistent mapping. The system deploys a lightweight VIO frontend on mobile devices for real-time tracking, and a backend running on a remote server to update multiple submaps. When overlapping areas between submaps across agents are detected, the system performs submap fusion to establish a globally consistent map. Additionally, we propose a map registration and fusion strategy based on covisibility areas for online registration and fusion in multi-agent scenarios. To improve the tracking accuracy of the frontend on agent, we introduce a strategy for updating the global map to the local map at a moderate frequency between the camera-rate pose estimation of the frontend VIO and the low-frequency global map optimization, using a tightly coupled strategy to achieve consistency of the multi-agent frontend poses estimation in the global map. The effectiveness of the proposed method is further confirmed by executing backend mapping on the server and deploying VIO frontends on multiple mobile devices for AR demostration. Additionally, we discuss the scalability of the proposed system by analyzing network traffic, synchronization frequency, and other factors at both the agent and server ends.

High-throughput ecological interaction mapping of dairy microorganisms

To engineer efficient microbial management strategies in the food industry, a comprehensive understanding of microbial interactions is crucial. Microorganisms live in communities where they influence each other in several ways. Although much attention has been paid to the production of antagonistic metabolites in lactic acid bacteria (LAB), research that accounts for the complexity of their ecological interactions and their dynamics remains limited. This study explores binary interactions within a mock community of 94 strains, including 23 LAB from culture collections and 71 isolated from dairy products. Using a colony-picking robot and image analysis, bidirectional interactions were measured at high throughput on solid media, where one test strain was challenged against other mock community members as the target strains. Assays of 15 test strains (14 LAB and one yeast) yielded 1,142 bidirectionally mapped interactions, classified by ecological type over seven days. The results showed variation in the strength, directionality, and type of interactions depending on the origin of the target strains. Cooperation rates increased for strains isolated from raw milk to pasteurized milk and cheese, while exploitation was more common in raw milk strains. Cooperating strains also exhibited more similar ecological behaviors than competing strains, suggesting the presence of microbial cliques. Interestingly, Lactococcus cremoris ATCC 19257 developed pink-red pigmentation when co-cultured with Pseudomonas aeruginosa. Overall, these findings present an unprecedented exploratory data set that significantly improves our understanding of microbial interactions at the system level, with potential applications in strain selection for food processes such as fermentation, bioprotection, and probiotics.

Rhythmic qualities of jazz improvisation predict performer identity and style in source-separated audio recordings.

Great musicians have a unique style and, with training, humans can learn to distinguish between these styles. What differences between performers enable us to make such judgements? We investigate this question by building a machine learning model that predicts performer identity from data extracted automatically from an audio recording. Such a model could be trained on all kinds of musical features, but here we focus specifically on rhythm, which (unlike harmony, melody and timbre) is relevant for any musical instrument. We demonstrate that a supervised learning model trained solely on rhythmic features extracted from 300 recordings of 10 jazz pianists correctly identified the performer in 59% of cases, six times better than chance. The most important features related to a performer's 'feel' (ensemble synchronization) and 'complexity' (information density). Further analysis revealed two clusters of performers, with those in the same cluster sharing similar rhythmic traits, and that the rhythmic style of each musician changed relatively little over the duration of their career. Our findings highlight the possibility that artificial intelligence can perform performer identification tasks normally reserved for experts. Links to each recording and the corresponding predictions are available on an interactive map to support future work in stylometry.

Participatory Digital Mapping, Dynamic Data, and Children’s Emergent Science Argumentation About Local Socio-Ecological Systems

Abstract Over the last two decades, there has been an increasing focus on spatial technologies in teaching and learning, revealing the potential to support new forms of youth sensemaking across varied settings and modalities. Recent scholarship has shown the possibilities of participatory digital mapping technologies, enabling young people to collect data within community settings and create interactive data-rich maps about complex phenomena and processes that build from their local expertise and inquiries. Yet to date, these technologies and related pedagogies remain less researched within K-5 educational contexts. In this article, we examine the most recent iteration from a multi-year design research project that centered 5th grade students’ learning about socio-ecological systems by engaging in participatory digital mapping to study their schoolyard soil ecosystems underfoot. We examine the possibilities of centering digital participatory map making as a basis for modeling and argumentation in elementary science. Analyzing whole class discussion video within the 10-week curriculum, we show how children authored their collective maps in numerous ways, making visible their social and ecological knowledge of the schoolyard, as well as their experiences defining, producing and visualizing qualitative and quantitative data. As part of this broader design-based research project, we find that children were able to reason about complex socio-ecological systems across spatial, temporal, and relational dimensions in inventive ways, often considered out of reach for elementary aged students, while also expanding what could count as data and what ways of knowing were valued within the science classroom. Implications for science education, place-based education, and emerging geospatial technologies are discussed.

The Application of an Augmented Reality Offline System for Rural Tourism Development at Pa’ Lungan, Bario

The development of rural tourism is one of the Malaysian government’s primary priorities for improving the socioeconomic and living conditions of the local community. Therefore, new ideas for assisting the rural population’s growth and economy through tourism must be explored. This article examines the application of augmented reality (AR) offline systems in improving this issue. It aims to review the planning, implementation, and effectiveness of the Interactive Digital Map (ID-MAP) as part of a rural tourism project in Pa’ Lungan, Bario, Sarawak. The study is carried out through a practical visual approach and analysed through observational, experiential and reflection approaches. The analysis elaborates on one of the main themes contained in the ID-MAP, which is linked to the famous tourist attraction of Pa’ Lungan – a megalithic rock called Batuh Ritung. The outcome was initially presented through an exhibition that applied digital information delivery using AR applications. As a result, an offline system was developed to assist locals in efficiently promoting tourism sites. This serves as an alternative platform that can verify the eligibility of tourist spots based on the existing digital and interactive multimedia systems, which are vital components in developing the smart village concept with Bario as a case study. Thus, this research has opened new interdisciplinary research opportunities and can be considered an alternative method to visual-based research, especially to stimulate the tourism industry and inform stakeholders and academics on the future of rural tourism.

Multi-layer graph attention neural networks for accurate drug-target interaction mapping

In the crucial process of drug discovery and repurposing, precise prediction of drug-target interactions (DTIs) is paramount. This study introduces a novel DTI prediction approach—Multi-Layer Graph Attention Neural Network (MLGANN), through a groundbreaking computational framework that effectively harnesses multi-source information to enhance prediction accuracy. MLGANN not only strides forward in constructing a multi-layer DTI network by capturing both direct interactions between drugs and targets as well as their multi-level information but also amalgamates Graph Convolutional Networks (GCN) with a self-attention mechanism to comprehensively integrate diverse data sources. This method exhibited significant performance surpassing existing approaches in comparative experiments, underscoring its immense potential in elevating the efficiency and accuracy of DTI predictions. More importantly, this study accentuates the significance of considering multi-source data information and network heterogeneity in the drug discovery process, offering new perspectives and tools for future pharmaceutical research.

A Network Pharmacological Study of Qianjin Sanhuang Decoction in the Treatment of Osteoarthritic Knee Disease

Objective: To predict the action targets of Qianjin Sanhuang decoction in the treatment of knee osteoarthritis through network pharmacology, to explore its potential multi component, multi target, multi, pathway mechanism of action, and to elaborate the relationship between the pharmacological effects of the drug and the disease from the perspective of molecular mechanism. Methods: The Chinese herbal composition of Qianjin Sanhuang decoction was determined by reading ancient texts and reviewing data, and the chemical components of Qianjin Sanhuang decoction were collected through the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP), and the active ingredients of the drug were obtained after oral utilization (OB) and drug-like properties (DL) screening, and the active ingredient target prediction was performed, while the active ingredient targets were retrieved from GeneCards, OMIM, and DisGeNet database to retrieve knee osteoarthritis-related targets. After taking the intersecting targets, a software called cytoscape 3.9.0 was used for mapping, with the goal of constructing a component-target network map, followed by a string database for mapping, with the goal of making a network map of target protein-target protein interactions, and finally, a gene ontology (GO) enrichment analysis and a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, this analysis process was performed in the metascape database. Results: A total of 1272 targets related to osteoarthritis of the knee were collected in this study, 89 active ingredients of Qianjin Sanhuang decoction, involving 267 targets, and 121 therapeutic targets involving osteoarthritis of the knee, and the results of GO enrichment analysis showed that it involved the response to inorganic substances, positive regulation of cell migration, response to oxygen content, response to lipopolysaccharide, response to peptides, regulation of cell adhesion, response to extracellular stimuli, negative regulation of cell differentiation, positive regulation of cell death, glandular development, regulation of apoptotic signaling pathways, development of reproductive structures, response to trauma, response to growth factors, regulation of inflammatory response, cellular response to organic recycling compounds, regulation of proteolysis, etc. After KEGG analysis, the results showed that signaling pathways such as AGE-RAGE pathway and HIF-1 pathway were involved. Conclusion: Qianjin Sanhuang decoction can improve the inflammatory response of knee osteoarthritis through potential multi-pathways, multi-targets and multi-pathways, and can have potential therapeutic effects on osteoarthritis.

Geographic variation in kidney failure and transplantation in Aotearoa New Zealand: A population-based data linkage study.

This study aimed to describe the epidemiology of kidney replacement therapy (KRT) in Aotearoa New Zealand and assess the impact of residential location on access to kidney transplantation. AcceSS and Equity in Transplantation (ASSET), a health-linked data platform, was used to identify people commencing KRT in New Zealand from 2006 to 2019 and analyse regional epidemiology. Health services were classified as 'transplanting', 'intermediate' or 'remote' depending on their degree of separation from a transplant centre. Multiple logistic regression modelling was used to assess the predictors of deceased donor waitlisting or living donor transplantation within 6 months after starting KRT. Web-based mapping software was used to develop interactive geospatial maps. The cohort was 7704 people newly starting KRT. Living in an intermediate [odds ratio (OR): 0.73 (95% confidence interval (CI): 0.61-0.88)] or remote [OR: 0.38 (95% CI: 0.27-0.54)) region and Māori (OR: 0.35 (95% CI: 0.28-0.44)], Pacific [OR: 0.32 (95% CI: 0.24-0.42)) and Asian (OR: 0.66 (95% CI: 0.50-0.87)] ethnicity were associated with a decreased likelihood of timely waitlisting or transplantation. Regional maps can be explored here. There is marked geospatial and ethnic variation in the epidemiology of kidney failure and access to kidney transplantation across New Zealand. Geospatial mapping of kidney failure epidemiology and transplantation outcomes can provide opportunities to direct resources towards populations at greatest need.

‘Freeze the measles’: how to improve backward tracing with a new digital tool

Abstract Background A measles outbreak occurred in Tuscany, between January and April 2024. There were 37 cases (Incidence: 40,5 per million) with 32 cases (24 confirmed) in the Health District of Pisa. Even if bidirectional tracing showed a better effectiveness in pandemics, there aren’t ready-to-use standardized tools for backward tracing. Methods Pisa Public Health Unit created a digital tool based on a spreadsheet and called “Freeze the measles” which records measles cases and the locations where they passed through (hotspots). These were uploaded on a cloud shared with all the tracers. Hotspots have an expiry date of 21 days. Hotspots and home address case were plotted on a digital map. In a new investigation, tracers could find out if the case visited some hotspots before getting sick and check the distance between home address and hotspots, reducing recall bias. Every case was interviewed about 21 days before rash onset (backward) and plus or minus 4 days of rash onset (forward). The tool matched data to identify contacts and exposure. Results Since the index case wasn’t found, the first 5 unrelated cases were considered index cases for this outbreak. Second and third wave involved 17 cases. The tool allows to find an epidemiological link for 16 of them, while 1 case remained unrelated. A super-spreader was identified with 12 secondary cases occurred at hospital emergency room (7), at a near home minimarket (4) and in a large furniture store (1). In second and third waves, tool was able to link 94% of cases. 2 additional cases were imported. When the last hotspot became frozen without new cases occurring, the outbreak was considered ended. The outbreak lasted 33 days. Conclusions The “Freeze the measles” tool allows to identify transmission chains through an interactive map built on cases and their mobility. Key messages • Contact tracing needs an appropriate backward investigation to be more effective. • New digital tools as ‘Freeze the measles’ could improve preparedness and management of outbreaks.

A New Corpus of Roman Coins from England and Wales. An Overview of the Evidence and Analysis of the Data

Abstract This paper considers a new corpus of 490,154 Roman coins (site finds) which have been recorded from England and Wales. The corpus provides British and regional means to aid in the preparation of coin reports in line with Historic England guidelines, along with spatial data providing new opportunities for research. The methods of data collection will be detailed and some of the possibilities this dataset can provide presented through a number of case studies. Through the consideration of applied numismatic analyses, the social distribution of the material and, crucially, the spatial distribution of Roman coinage, we can identify new trends and patterns. Case studies evaluating the fourth century will emphasise the changing importance of settlements in Roman Britain and identify those linked with the late Roman state. Furthermore, the retraction of coinage distributions in the second half of the fourth century will be explored. Building on the national and site type means explored within the paper, the full dataset has been made available in a range of forms on the Archaeology Data Service and in an interactive map developed by Maploom.

ProCogGraph: a graph-based mapping of cognate ligand domain interactions.

Mappings of domain-cognate ligand interactions can enhance our understanding of the core concepts of evolution and be used to aid docking and protein design. Since the last available cognate-ligand domain database was released, the PDB has grown significantly and new tools are available for measuring similarity and determining contacts. We present ProCogGraph, a graph database of cognate-ligand domain mappings in PDB structures. Building upon the work of the predecessor database, PROCOGNATE, we use data-driven approaches to develop thresholds and interaction modes. We explore new aspects of domain-cognate ligand interactions, including the chemical similarity of bound cognate ligands and how domain combinations influence cognate ligand binding. Finally, we use the graph to add specificity to partial EC IDs, showing that ProCogGraph can complete partial annotations systematically through assigned cognate ligands. The ProCogGraph pipeline, database and flat files are available at https://github.com/bashton-lab/ProCogGraph and https://doi.org/10.5281/zenodo.13165851.

Методологическое обоснование содержания, структуры и программной реализации базы геопространственных знаний территориальных образований

The article deals with substantiating the contents, structure and software implementation of the geospatial knowledge base. The importance and relevance of forming its infrastructure and the corresponding informational base on the territory in modern geoinformatics and cartography are noted. The requirements for the contents, formal and logical representation of the mentioned base, its structure and connections of the elements at the logical level are given. The authors consider the software implementation of the processes of searching and issuing geospatial knowledge in a visualized form at the request of untrained users in the field of geoinformatics and cartography. The requisitions and information on the special original software, which allows observing the contents of the geospatial knowledge base, are shown. The effectiveness of visualizing the geospatial knowledge base through interactive configuration of software elements is substantiated, based on the metadata principle proposed by the authors, two formalisms and an algorithm for creating corresponding services for geospatial knowledge and other related data. These formalisms of the client’s parameters and server software applications are described, a variant of the geospatial knowledge base structure is given, and the requirements for the necessary software for the effective solution of the task are formulated. The authors` solution is considered in the form of a complex of multicomponent software, used at working with geodata and creating their own interactive maps by poorly trained non-professional users

PhoXplex: Combining Phospho-enrichable Cross-Linking with Isobaric Labeling for Quantitative Proteome-Wide Mapping of Protein Interfaces.

Integrating cross-linking mass spectrometry (XL-MS) into structural biology workflows provides valuable information about the spatial arrangement of amino acid stretches, which can guide elucidation of protein assembly architecture. Additionally, the combination of XL-MS with peptide quantitation techniques is a powerful approach to delineate protein interface dynamics across diverse conditions. While XL-MS is increasingly effective with isolated proteins or small complexes, its application to whole-cell samples poses technical challenges related to analysis depth and throughput. The use of enrichable cross-linkers has greatly improved the detectability of protein interfaces in a proteome-wide scale, facilitating global protein-protein interaction mapping. Therefore, bringing together enrichable cross-linking and multiplexed peptide quantification is an appealing approach to enable comparative characterization of structural attributes of proteins and protein interactions. Here, we combined phospho-enrichable cross-linking with TMT labeling to develop a streamline workflow (PhoXplex) for the detection of differential structural features across a panel of cell lines in a global scale. We achieved deep coverage with quantification of over 9000 cross-links and long loop-links in total including potentially novel interactions. Overlaying AlphaFold predictions and disorder protein annotations enables exploration of the quantitative cross-linking data set, to reveal possible associations between mutations and protein structures. Lastly, we discuss current shortcomings and perspectives for deep whole-cell profiling of protein interfaces at large-scale.

Chromatin interaction maps of human arterioles reveal new mechanisms for the genetic regulation of blood pressure.

Arterioles are small blood vessels located just upstream of capillaries in nearly all tissues. The constriction and dilation of arterioles regulate tissue perfusion and are primary determinants of systemic blood pressure (BP). Abnormalities in arterioles are central to the development of major diseases such as hypertension, stroke, and microvascular complications of diabetes. Despite the broad and essential role of arterioles in physiology and disease, current knowledge of the functional genomics of arterioles is largely absent, partly because it is challenging to obtain and analyze human arteriole samples. Here, we report extensive maps of chromatin interactions, single-cell expression, and other molecular features in human arterioles and uncover new mechanisms linking human genetic variants to gene expression in vascular cells and the development of hypertension. Compared to large arteries, arterioles exhibited a higher proportion of pericytes which were strongly associated with BP traits. BP-associated single nucleotide polymorphisms (SNPs) were enriched in chromatin interaction regions in arterioles, particularly through enhancer SNP-promoter interactions, which were further linked to gene expression specificity across tissue components and cell types. Using genomic editing in animal models and human induced pluripotent stem cells, we discovered novel mechanisms linking BP-associated noncoding SNP rs1882961 to gene expression through long-range chromatin contacts and revealed remarkable effects of a 4-bp noncoding genomic segment on hypertension in vivo. We anticipate that our rich data and findings will advance the study of the numerous diseases involving arterioles. Moreover, our approach of integrating chromatin interaction mapping in trait-relevant tissues with SNP analysis and in vivo and in vitro genome editing can be applied broadly to bridge the critical gap between genetic discoveries and physiological understanding.

RNA architecture of porcine deltacoronavirus genome inside virions detected by vRIC-seq

Porcine deltacoronavirus (PDCoV) is a newly emerging and special delta coronavirus, which infect mammals such as pigs, cattle and humans, as well as chickens and birds. Exploring RNA structures in the viral genome benefits the understanding of the role of RNA in the lifecycle of viruses. In this study, vRIC-seq is employed to analyze the RNA-RNA interaction in the whole genome structure of PDCoV in virions. About 12.87 and 13.52 million paired reads are obtained in two biological replicates, respectively, with 17.9% and 14.8% of them are identified as valid chimeric reads. These are employed to predict the RNA secondary structure, which is compact and highly structured. A twisted-cyclized conformation is observed in the RNA-RNA interaction map of PDCoV for the first time. 77 multi-way junctions are evenly distributed in the PDCoV genome. Our work provides fundamental structural insights that are essential for understanding the genomic structure and function, genetic evolution, and packaging characteristics of PDCoV.