New York Genome Characterization Center: Somatic Mosaicism across Human Tissues

项目摘要/摘要-纽约基因组表征中心 在过去的二十年里，大规模的测序工作一直集中在产生DNA序列上 来自血液或唾液等容易获得的组织的数据集，以识别与 疾病表型。然而，在描述健康人的体细胞变异方面取得的进展有限。 组织及其在人类一生中对健康和疾病的贡献。体细胞变异有 历史上是在肿瘤生物学的背景下研究的；然而，越来越多的证据表明，体细胞 变异在衰老过程中起着重要作用，在心血管、神经退行性、 免疫学和神经发育疾病。因此，迫切需要描述体细胞的特征。 在人的一生中，不同种族和民族的人的健康人体组织中的不同景观。 人体组织中的体细胞嵌合体(SMAHT)计划将通过建立一个 凝聚网络将共同努力创建高质量的体细胞变异目录；一个广泛的目录 可在科学界共享，并使研究能够调查 跨细胞群体和组织的体细胞嵌合体，这可以阐明克隆的机制 发展、进化和扩展，使研究体细胞突变在疾病中的作用成为可能 发病机制和进展。纽约基因组鉴定中心(NYGCC)将工作 与其他SMAHTT网络中心合作，使用三个 核心高深度测序分析：双链全基因组测序(WGS)、信使核糖核酸测序和长链DNA测序。 阅读牛津纳米孔WGS。这三项核心分析将提供前所未有的全面视角 各种健康组织中的体细胞突变。来自Deep WGS的数据将使我们能够发现 体细胞SNV、INDELs、移动元件、拷贝数变化和结构变体。核糖核酸测序 数据将被用来确认那些落入表达基因中的变异的存在，并进一步评估 它们对拼接的影响。长读WGS测序将被用作短读WGS的推论以确认 并加强对移动元件、拷贝数变化和结构变体的发现。对这些核心分析 我们建议增加使用直接文库准备(DLP)的单细胞WGS测序和基因分型 转录本(GOT)。DLP是一种无扩增的单细胞WGS检测方法，允许高灵敏度检测 拷贝数变化、杂合性丧失和结构变异。它进一步促进了对复制的研究 计时、克隆扩展和适合度，并与池化伪体分析兼容，以进行比较 深层散装WGS。转录本分析的基因分型将使我们能够探索表达的体细胞变异， 它们出现的细胞类型或谱系，并通过与单个细胞表达数据(和细胞表面)配对 标记检测和长读转录本测序)这些突变的功能影响。

PROJECT SUMMARY/ABSTRACT - NEW YORK GENOME CHARACTERIZATION CENTER Large-scale sequencing efforts over the last two decades have been focused on generating DNA sequence datasets from readily available tissues such as blood or saliva to identify germline variants associated with disease phenotypes. However, limited progress has been made in characterizing somatic variants in healthy tissues and their contribution to health and disease over the course of the human lifespan. Somatic variation has historically been studied in the context of tumor biology; however, there is mounting evidence that somatic variation plays an important role in the aging process, as well as in cardiovascular, neurodegenerative, immunologic, and neurodevelopmental diseases. There is therefore a critical need to characterize the somatic variant landscape in healthy human tissues in individuals of diverse race and ethnicity across the human lifespan. The Somatic Mosaicism across Human Tissues (SMaHT) program will address this gap by establishing a cohesive Network that will work together to create high-quality somatic variant catalog; a catalog that is broadly shareable across the scientific community and that enables studies investigating the rates and patterns of somatic mosaicism across cell populations and tissues, that can elucidate the mechanisms underlying clonal development, evolution, and expansion, and that enables studies of the role of somatic mutation in disease pathogenesis and progression. The New York Genome Characterization Center (NYGCC) will work collaboratively with other SMaHT Network Centers to generate a high-quality somatic variant catalog using three core high-depth sequencing assays: duplex whole genome sequencing (WGS), mRNA sequencing, and long- read Oxford Nanopore WGS. These three core assays will provide an unprecedented and comprehensive view of somatic mutations across a variety of healthy tissues. The data from deep WGS will enable discovery of somatic SNVs, indels, mobile elements, copy number changes, and structural variants. The RNA sequencing data will be used to confirm the presence of those variants that fall in expressed genes, and further evaluate their effect on splicing. The long read WGS sequencing will be used as a corollary to short read WGS to confirm and enhance discovery of mobile elements, copy number changes and structural variants. To these core assays we propose adding single cell WGS sequencing using Direct Library Preparation Plus (DLP+) and genotyping of transcriptomes (GoT). DLP+ is an amplification-free single cell WGS assay that allows high sensitivity detection of copy number changes, loss of heterozygosity, and structural variation. It further enables the study of replication timing, clonal expansion and fitness and is compatible with pooled pseudo-bulk analysis to compare against deep bulk WGS. The genotyping of transcriptomes assay will allow us to explore, for expressed somatic variants, the cell type or lineage in which they occurred and by pairing with single cell expression data (and cell surface marker detection and long read transcript sequencing) the functional effects of these mutations.