EAGER: Assembling the Immunoglobulin Loci Across Mammalian Species and Across the Human Population

正在进行的新冠肺炎大流行提出了开发新的计算技术以了解对新出现病原体的免疫反应的挑战。该项目将开发一种新的计算机程序，用于分析负责对病原体的免疫反应的基因组部分。这将通过表征对免疫反应至关重要的突变来分析人类群体对病毒的免疫力的发展。这项研究还将加强对蝙蝠和大羊驼免疫反应的了解，蝙蝠是大量冠状病毒的宿主，大羊驼可能是针对该病毒的强大疫苗的重要来源。该项目还将开发一个大型在线公开课“SARS-COV-2的生物信息学”，该课程将涵盖对新出现的病原体进行计算分析的各个方面，以及分析人类基因组这些复杂和动态部分的挑战。关于基因组中免疫球蛋白编码区的信息对于分析对新型SARS-CoV-2冠状病毒的免疫反应、开发针对SARS-COV-2的抗体药物以及测试未来针对SARS-CoV-2的疫苗至关重要。然而，仍然没有算法来推断高度复杂和快速进化的免疫球蛋白(IG)基因座的序列。此外，尽管免疫球蛋白基因座内的免疫球蛋白基因构成了抗体的积木，但仍然没有软件工具来准确识别这些基因。这个项目将开发一种新的算法来组装和注释IG基因座。这些方法将应用于多个哺乳动物基因组，重点是组装蝙蝠异常复杂的IG基因座，以表征它们对冠状病毒的免疫反应。第二个重点将是组装骆驼免疫球蛋白基因座，以帮助开发针对SARS-COV-2的疫苗，利用这一组中存在的更简单和更稳定的抗体。该项目还将专注于在多个新冠肺炎患者中组装高度可变的免疫球蛋白基因座，目的是揭示这些基因座在功能上的重要突变。该项目有很大的风险，因为免疫球蛋白基因座对之前所有的组装尝试都是顽固的，但加强对哺乳动物免疫球蛋白基因的理解将极大地增强社会预测和应对当前和未来大流行的能力。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The ongoing COVID-19 pandemic raised the challenge of developing new computational techniques for understanding the immune response to emerging pathogens. This project will develop a new computer program for analyzing the parts of the genome that are responsible for immune responses to pathogens. This will enable analyses of the development of immunity to the virus in human populations by characterizing the mutations that are essential to the immune response. This research will also enhance understanding of the immune responses in bats, which are hosts to large numbers of coronaviruses, and in llamas, which are potentially an important source for a robust vaccine against the virus. The project will also develop a Massive Online Open Course “Bioinformatics of SARS-COV-2” that will cover various aspects of computational analysis of emerging pathogens, and the challenges of analyzing these complex and dynamic parts of the human genome. Information about the immunoglobulin-encoding regions in the genome is critically important for analyzing the immune response to the novel SARS-CoV-2 coronavirus, developing antibody drugs against SARS-COV-2, and testing future vaccines against SARS-CoV-2. However, there are still no algorithms for inferring the sequences of the highly complex and rapidly evolving immunoglobulin (IG) loci. Moreover, although the immunoglobulin genes within the IG loci form the building blocks of antibodies, there are still no software tools for accurate identification of these genes. This project will develop a new algorithm for assembling and annotating the IG loci. These methods will be applied to multiple mammalian genomes with a focus on assembling the unusually complex IG loci in bats to characterize their immune response to coronaviruses. A second focus will be assembly of camelid IG loci to aid in developing vaccines against SARS-COV-2, taking advantage of the simpler and more stable antibodies present in this group. The project will also focus on assembling the highly variable immunoglobulin loci in multiple COVID-19 patients with the goal of revealing functionally important mutations in these loci. The project entails substantial risk, because the IG loci have been recalcitrant to all previous assembly attempts, but enhanced understanding of mammalian immunoglobin genes would greatly enhance the ability of society to predict and respond to current and future pandemics.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.