AI/ML Ready appraoches for integrative RNA processing, splicing and spatial genomics

用于整合 RNA 处理、剪接和空间基因组学的 AI/ML Ready 方法

基本信息

批准号：
10407768
负责人：
Julia Salzman
金额：
$ 15.75万
依托单位：
STANFORD UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-01-01 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10407768
关键词：
Address Algorithms Alternative Splicing Base Sequence Biological Biological Markers Biology Cells Code Communities Complex Computer software DNA DNA Sequence Data Development Diagnostic Disease Disease Marker Docking Drug Targeting Engineering Eukaryota Eukaryotic Cell Evolution Foundations Future Generations Genes Genetic Genetic Transcription Genome Genomics Goals Individual Knowledge Life Methods Minority Modality Nucleic Acids Nucleotides Organism Output Pathogenicity Polyadenylation Process Processed Genes Protein Isoforms Proteins Public Domains RNA RNA Processing RNA Splicing Readiness Regulation Reproducibility Research Research Personnel Resolution Role Statistical Algorithm Transcript Untranslated RNA Untranslated Regions Variant cell type digital experimental study genetic variant insight nervous system disorder novel parent grant programs public health relevance public repository single cell sequencing single-cell RNA sequencing tool transcriptomics

项目摘要

Project Summary/Abstract From parent grant: Cells and organisms, from simple to complex, carry the same genetic DNA sequence organized into genes. Multicellular eukaryotes transcribe and process genes into RNA isoforms through a process called alternative splicing. Alternative splicing is developmentally, and cell-type specifically regulated. It is foundational to how higher organisms’ genomes are decoded. Yet, critical, and fundamental questions regarding its regulation and the function of its output remain unanswered. For example, circRNA being a ubiquitous product of alternative splicing was only discovered in 2012, and its regulation and function remains enigmatic. circRNAs’ discovery revealed a larger critical knowledge gap in the field for “what, how and why” genes are alternatively spliced. What RNA splice variants are expressed, how splicing is regulated, and which spliced RNAs have essential functions? Answering these questions is critical for predicting which of myriad genetic variants cause disease and why they do so. Answers will also enable a new generation of digital nucleic acid biomarkers and diagnostics for disease, drug targets for correcting dysregulated splicing and identification of pathogenic protein- or non-coding products (respectively) as well as fundamental basic scientific insight into evolution and function of eukaryotic genomes.. Despite the great promise for discovering how splicing is regulated in massive single cell RNAseq experiments, the field is still lacking unbiased precise methods to address statistical and computational challenges of splicing analysis in scRNA-Seq. State-of-the-art, reproducible, statistical algorithms to achieve precise splice variant calls, detecting how they are regulated in cell types and subcellularly lag far behind the rate at which single cell RNA- seq (scRNA-seq) data is generated, limiting ML/AI readiness. Here, we will open the possibility of analyzing novel RNA regulatory biology through ML/AI-ready software and processed data to a huge community of biomedical researchers enabling new basic and translational discoveries.

来自父母赠款的项目摘要/摘要：从简单到复杂的细胞和生物，带有相同的遗传DNA序列组织成基因。多细胞真核生物转录和处理基因通过称为替代剪接的过程。开发了替代剪接和细胞类型特别监管。这是如何解码较高的生物基因组的基础。然而，批评和有关其监管及其产出功能的基本问题仍未得到答复。例如， Circrna是替代剪接的普遍产物，仅在2012年才发现，其调节和调节和功能保持神秘。 Circrnas的发现揭示了该领域的较大批判知识差距，“什么， “如何和原因”基因或者是剪接的。表达了什么RNA剪接变体，剪接的方式受监管，哪些剪接RNA具有重要功能？回答这些问题对于预测多种遗传变异的哪种会导致疾病以及为什么会导致疾病。答案还将启用新的生成数字核酸生物标志物和疾病诊断，校正药物靶标病原蛋白或非编码产物的剪接和鉴定以及鉴定（分别）基本的基本科学见解对真核基因组的进化和功能。尽管很棒发现在大规模单细胞RNASEQ实验中发现剪接如何调节剪接的承诺，该领域仍在缺乏无公正的精确方法来解决剪接分析的统计和计算挑战 scrna-seq。最先进的，可重现的统计算法，以实现精确的剪接变体，检测它们在细胞类型中的调节，并落后于远远落后于单个细胞RNA-的速率生成SEQ（SCRNA-SEQ）数据，限制了ML/AI准备就绪。在这里，我们将开放分析的可能性通过ML/AI-Ready软件和处理数据的新型RNA调节生物学生物医学研究人员可以实现新的基本和翻译发现。