Genomics Core

基因组学核心

• 批准号: 10595632
• 负责人: Robert Sebra
• 金额: $ 30.01万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-03-22 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10595632
• 关键词: 2019-nCoV; Address; COVID-19 vaccine; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Clinical; Collaborations; Coupling; Custom; Data; Data Analyses; Data Set; Databases; Dengue Vaccine; Dengue Virus; Development; Flow Cytometry; Fostering; Gene Expression Profile; Generations; Genes; Genetic Transcription; Genomics; Human; Immune; Immune response; Immunity; Immunization Programs; Immunology; Immunophenotyping; Individual; Infection; Inflammatory Response; Influenza A virus; Influenza B Virus; Informatics; Lymphoid Tissue; Metadata; Methods; Modeling; Molecular; Multiomic Data; Natural Immunity; Outcome; Participant; Pattern; Peripheral Blood Mononuclear Cell; Phenotype; Population; Proteins; Quality Control; Resolution; Resources; Serology; System; Technology; Time; Tissue-Specific Gene Expression; Tissues; Tonsil; Vaccinated; Vaccination; Vaccinee; Vaccines; Variant; Viral; Viral Genome; Virus Diseases; analysis pipeline; breakthrough infection; chemokine; cohort; cytokine; data analysis pipeline; data integration; data management; differential expression; genetic signature; genomic data; influenza virus vaccine; multiple omics; multiscale data; pathogen; protein expression; seasonal influenza; transcription regulatory network; transcriptome sequencing; transcriptomics; vaccination outcome; vaccine immunogenicity; vaccine response; viral genomics

GENOMICS CORE D PI: Dr. Sebra PROJECT SUMMARY Recent advances in genomics technology and associated data analysis methods have provided a framework to interrogate the human host response to vaccination and the dynamic interplay between host and pathogen during viral infection at an unprecedented resolution. The integration of molecular and cellular data alongside clinical metadata and serologic data nucleates the potential to identify signatures of viral immunity outcomes by characterizing changes in innate immunity before and after vaccination. However, no single technology is sufficient to address the multitude of open questions raised by deep molecular immune profiling, necessitating an integrated approach for profiling immunity and vaccine response. Analysis of PBMCs and histocultures across VIVA projects with a variety of cutting-edge and custom high throughput, molecular and high-resolution multi-omics technologies will provide the best database for vaccine immune responses across these systems. The VIVA Genomics Core D aims to leverage a data generation technology suite inclusive of bulk RNAseq, serologic data, single cell CITEseq, CyTOF, spatial transcriptomics, viral genomics and multi-scale computational approaches for the comprehensive characterization of immune response to predict vaccine outcomes. Using the integration of these data, Core D will deliver multi-omics data generation and quality control for seamless analysis, integration and annotation with the Genomics Data Analysis and Management Core E across VIVA projects including the Immune/Clinical Core, Project 1 (SARS-CoV-2), Project 2 (seasonal influenza), Project 3 (tetravalent DENV). Core D will serve as an invaluable resource for the VIVA HIPC team coupling molecular data generation and Core E data driven approaches to foster technology refinement and development and promote collaboration between VIVA projects.

基因组学核心D PI：Sebra医生 项目摘要 基因组学技术和相关数据分析方法的最新进展提供了 询问人类宿主对疫苗接种的反应和动态相互作用的框架 在病毒感染过程中宿主和病原体之间以前所未有的分辨率连接。整合 分子和细胞数据以及临床元数据和血清学数据的核心， 通过表征先天免疫应答的变化来识别病毒免疫结果特征的潜力 接种疫苗前后的免疫力然而，没有一种技术足以解决 深度分子免疫分析提出了许多悬而未决的问题，需要 免疫和疫苗反应分析的综合方法。PBMC分析和 VIVA项目的历史文化，具有各种尖端和定制的高通量， 分子和高分辨率多组学技术将为疫苗提供最佳数据库 免疫系统的反应。VIVA Genomics Core D旨在利用数据 生成技术套件，包括批量RNAseq、血清学数据、单细胞CITEseq， 空间转录组学、病毒基因组学和多尺度计算方法 免疫应答的综合表征，以预测疫苗结果。使用 通过整合这些数据，Core D将提供多组学数据生成和质量控制， 与基因组学数据分析和管理无缝分析、集成和注释 VIVA项目的核心E，包括免疫/临床核心项目1（SARS-CoV-2）， 项目2（季节性流感），项目3（四价DENV）。核心D将作为一个宝贵的 VIVA HIPC团队的资源，将分子数据生成和Core E数据驱动结合起来 促进技术完善和开发以及促进 VIVA项目。