SBIR Phase I: Low-Cost and Scalable Creation of Genomic Databases with Long-Read Next-Generation Sequencing

SBIR 第一阶段：利用长读长下一代测序低成本、可扩展地创建基因组数据库

• 批准号: 2110980
• 负责人: Dario Dilernia
• 金额: $ 25.11万
• 依托单位: SEQUEGENICS LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2110980&HistoricalAwards=false
• 关键词: SBIR; Phase; Low; Cost; Scalable

The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be the development and validation of a new approach to facilitate population-level access to genetic information contained in the human genome currently inaccessible. Importantly, it can drive a significant reduction in time and cost needed to scan the genome of patients who suffer from a specific disease, from years to months, accelerating discovery cycles and producing data with higher resolution to develop better diagnostic tools or treatments. The proposed project describes a novel approach for high-resolution human genome sequencing using unique computational algorithms that facilitate detection of diverse types of genetic variation using a pangenomics approach, implemented directly on raw sequencing data. Genetic variation inadequately captured by short-read Next Generation Sequencing, such as large chromosomal rearrangements, long tandem repeats, or long-range haplotype configurations, represent a significant gap in knowledge. In the last few years, maturation of long-read Next Generation Sequencing (NGS) technologies have begun uncovering the role of Structural Variants (SVs) and haplotypes in disease. However, the main limitation to expand implementation of long-read NGS is the cost of generating sufficient sequencing coverage to compensate for the relatively high natural error rate. The proposed technology can address this issue directly and facilitate cost-effective long-read sequencing of human genomes at scale.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I阶段项目的更广泛影响将是开发和验证一种新方法，以促进人口级别访问当前无法访问的人类基因组中所包含的遗传信息。重要的是，它可以大大减少时间和成本来扫描患有特定疾病的患者的基因组，从几年到几个月，加速发现周期并产生具有更高分辨率的数据以开发更好的诊断工具或治疗方法。拟议的项目描述了一种使用独特的计算算法进行高分辨率人基因组测序的新方法，该算法促进了使用Pangenomics方法直接在原始测序数据上实现的，促进了使用Pangenomics方法来检测各种类型的遗传变异。遗传变异因短读下一代测序而被捕获不足，例如大染色体重排，长串联重复序列或远距离单倍型构型，代表了知识的显着差距。在过去的几年中，长阅读下一代测序（NGS）技术的成熟已经开始揭示结构变异（SVS）和单倍型在疾病中的作用。但是，扩大长阅读NGS实施的主要限制是产生足够的测序覆盖范围以补偿相对较高的自然错误率的成本。拟议的技术可以直接解决此问题，并促进了人类基因组对人类基因组的长期长期读取测序。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来获得支持。