Utilization of Advanced Technologies for the Understanding of Human Structural Birth Defects

项目总结 这项提案的统一主题是使用最先进的技术来研究基本的 哺乳动物器官发育和人类结构性出生缺陷的生物学。我们的方法是广泛的， 旨在展示利用强大的技术如何为许多疾病提供信息。重要的是，这 该提案结合了西雅图儿童研究所和 华盛顿大学基因组科学系；具体地说，在诊断和 对人类先天畸形综合征和哺乳动物发育生物学的认识，以及 应用强大的新技术进行生物调查。 在项目1中，我们建议使用单细胞RNA测序(SCI-RNA-seq)技术来表征中期 携带与人类结构性出生缺陷相关的突变的小鼠的怀孕胚胎。本质上，我们是 建议利用SCI-RNA-seq作为表型，用它来注释表达的变化和细胞- 器官发生异常时的类型表现。理想情况下，这些配置文件应该可以相互比较， 并潜在地提供对基本生物通路的洞察，这些基本生物通路在 发育上重要的基因丢失了。 在项目2中，我们将利用3D成像、计算机视觉和机器学习方面的最新进展来制作 小鼠突变体的形态特征更加准确、定量、重复性和可达性更好。 来自项目1中研究的相同品系的后代将在E15.5收获并使用MicroCT进行成像 扫描中。然后，我们将使用几种不同的数据分析技术来识别组织中的差异 突变小鼠的体积和形状与由“正常”小鼠构建的合成图像进行了比较 样本。 项目3的目标是在结构性出生缺陷儿童的预期队列中使用新技术 以鉴定目前方法无法确定的遗传变异。这些“隐藏的”变体包括结构 重排，以及合子后出现的、在血液中不存在的DNA突变 DNA我们将使用基于长阅读的DNA和RNA测序方法，或基于深度短阅读的DNA 结构性出生缺陷患者的多个非血源性组织的测序 体检是非诊断性的。

PROJECT SUMMARY The unifying theme of this proposal is the aim to use state-of-the-art technologies to investigate the basic biology of mammalian organ development and human structural birth defects. Our approach is wide-ranging, and aims to demonstrate how utilization of powerful technologies can inform many disorders. Importantly, this proposal marries a number of strengths of investigators at Seattle Children’s Research Institute and the University of Washington Department of Genome Sciences; specifically, expertise in the diagnosis and understanding of human congenital malformation syndromes and mammalian developmental biology, and the application of powerful new techniques for biological investigation. In Project 1, we propose to use single-cell RNA sequencing (sci-RNA-seq) technology to characterize mid- gestation embryos of mice carrying mutations relevant to human structural birth defects. Essentially, we are proposing to utilize sci-RNA-seq as a phenotype, with which one can annotate changes in expression and cell- type representation during abnormal organogenesis. Ideally, these profiles will be comparable to each other, and can potentially provide insight into fundamental biological pathways that are perturbed when developmentally important genes are lost. In Project 2, we will leverage recent advances in 3D imaging, computer vision and machine-learning to make the morphological characterization of mouse mutants more accurate, quantitative, reproducible and accessible. Progeny from the same lines studied in Project 1 will be harvested at E15.5 and imaged using microCT scanning. We will then employ several different data analysis techniques to identify differences in the tissue volume and shapes in the mutant mice compared to synthetic image constructed from a pool of ‘normative’ samples. The goal of Project 3 is to use novel technologies in prospective cohorts of children with structural birth defects to identify genetic variation not ascertained by current methods. These “hidden” variants include structural rearrangements, as well as DNA mutations that arise post-zygotically and are not present in blood-derived DNA. We will use long-read based DNA and RNA sequencing methods, or deep short-read based DNA sequencing of multiple, non-blood derived tissues, on patients with structural birth defects whose clinical workup has been non-diagnostic.