Core B - Technical Services

项目摘要 生殖医学中心（CRM）代表了一个多学科的计划，以探索遗传 不孕症的结构。本文所述的CRM基因组学核心（GC）设想提供集中式和分布式的基因组学分析。 基因组变异、统计关联和所有组件的功能扰动的催化资源 这一总体CRM计划。这个基因组学中心将通过提供专业知识， 这些数据和方法将被用来更深入地了解罕见和常见的不孕症形式， 项目1和2分别。理事会还将作为数据、分析、 和整个程序的功能建模。在过去的几年里，我们制定了一个纲要， 计算工具，统计方法和功能基因组学方法来询问突变 人类疾病的变异谱。我们的方法结合了短变异（SNV，插入缺失）的联合分析 和结构变体（SV），包括典型平衡SV和拷贝数变体（CNV），以及 复杂SV的多样性目录，其惊人地丰富并与一系列人类疾病相关。 这些研究需要统一生成、处理和严格分析基因组数据集的方法 协会的研究。在GC中，我们将发现和注释变异，解释关联， 从我们的相关研究中获得超过1，000，000个基因组的人口规模数据集，并执行可扩展的 工程化以在与罕见和常见形式的遗传病相关的基因中产生等位基因系列扰动， 使用人诱导多能干细胞（hiPSC）衍生的GnRH模型的不孕症。总的来说，我们将支持 CRM通过完成与提供数据集，方法和功能资源相关的三个目标。 目标1：从外显子组、基因组和长片段等方面开发一个综合性的基因组学资源 排序和CRM队列的统一数据处理。目标2将执行整合的罕见变异 通过联合分析CRM队列与人群规模， 我们的基因组聚合数据库（gnomAD）项目和复杂疾病联盟生成的数据集 问题研究目的3然后将在GnRH神经元中进行不育基因的可扩展CRISPR扰动。 通过设计功能丧失突变和选择不育基因的等位基因系列来建立模型。 基因组学核心中的转录谱分析将识别与这些干扰相关的特征， 不育基因，并将寻求这些签名在少数不育相关途径上的收敛。 所有CRISPR工程模型将分发给相关项目进行进一步的功能测定，所有数据 并将模型公开分发给社区。基因组学的这些目标 因此，CRM的中心将提供数据集、基因发现和CRISPR工程化的同基因模型， 促进CRM和更广泛的研究社区内对不孕症的新见解。

PROJECT ABSTRACT The Center for Reproductive Medicine (CRM) represents a multi-disciplinary program to explore the genetic architecture of infertility. The CRM Genomics Core (GC) described herein envisages providing a centralized and catalytic resource for genomic variation, statistical association, and functional perturbations for all components of this overarching CRM program. This genomics hub will specifically catalyze discoveries by providing expertise in the data and methods that will be leveraged for deeper insights into rare and common forms of infertility in Projects 1 and 2, respectively. The GC will also serve as the focal point for cross-fertilization of data, analyses, and functional modeling across the program. Over the last several years, we have developed a compendium of computational tools, statistical approaches, and functional genomics methods to interrogate the mutational spectrum of variation in human diseases. Our methods incorporate joint analyses of short variants (SNVs, indels) and structural variants (SVs), including canonical balanced SVs and copy number variants (CNVs), as well as a diverse catalog of complex SVs that are surprisingly abundant and associated with an array of human disease. These studies have required methods to uniformly generate, process, and rigorously analyze genomics datasets for association studies. In the GC, we will discover and annotate variation, interpret association against population-scale datasets in excess of 1,000,000 genomes from our related studies, and perform scalable engineering to generate an allelic series of perturbations in genes associated with rare and common forms of infertility using human induced pluripotent stem cell (hiPSC) derived GnRH models. Overall, we will support the CRM by completing three objectives related to providing datasets, methods, and functional resources. Objective 1 will develop a comprehensive genomics resource from exome, genome and long-read sequencing, and uniform data processing of the CRM cohorts. Objective 2 will perform integrated rare variant association and interpretation of these datasets by jointly analyzing CRM cohorts with population-scale datasets generated in our genome aggregation database (gnomAD) project and complex disease consortia studies. Objective 3 will then perform scalable CRISPR perturbation of infertility genes in GnRH neuronal models by engineering loss-of-function mutations and an allelic series for select infertility genes. Transcriptional profiling in the genomics core will identify signatures associated with perturbation of these infertility genes, and will seek convergence of these signatures on a small number of infertility relevant pathways. All CRISPR-engineered models will be distributed relevant projects for further functional assays, and all data and models will be made openly available for distribution to the community. These objectives in the genomics hub of the CRM will thus provide datasets, gene discoveries, and CRISPR-engineered isogenic models to facilitate new insights into infertility within the CRM and the broader research community.