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

项目摘要 该提案的统一主题是使用最先进的技术来调查基本的 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， 旨在展示如何利用强大的技术可以告知许多疾病。重要的是这 这项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;特别是，在诊断和 了解人类先天畸形综合征和哺乳动物发育生物学， 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- 携带与人类结构性出生缺陷相关突变的小鼠妊娠胚胎。本质上，我们是 提出利用sci-RNA-seq作为表型，人们可以用它来注释表达和细胞的变化， 在异常器官发生过程中的类型表征。理想情况下，这些配置文件将相互比较， 并且可以潜在地提供对基本生物学途径的洞察， 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的最新进展， 小鼠突变体的形态学表征更加准确、定量、可重复和易获得。 将在E15.5收获来自项目1中研究的相同品系的子代，并使用microCT进行成像 扫描。然后，我们将采用几种不同的数据分析技术，以确定组织中的差异 突变小鼠的体积和形状与从“正常”小鼠库构建的合成图像相比， 样品 项目3的目标是将新技术用于结构性出生缺陷儿童的前瞻性队列 以识别目前方法无法确定的遗传变异。这些“隐藏”的变体包括结构性的 重排，以及合子后出现的DNA突变，而不是在血液来源的 DNA.我们将使用基于长读段的DNA和RNA测序方法，或基于深度短读段的DNA 多个非血液来源的组织的测序，对具有结构性出生缺陷的患者， 检查结果为非诊断性。

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.