Developing a whole-genome sequencing method for single human cells

开发单个人类细胞的全基因组测序方法

基本信息

批准号：
8413756
负责人：
Nicholas Navin
金额：
$ 19.75万
依托单位：
UNIVERSITY OF TX MD ANDERSON CAN CTR
依托单位国家：
美国
项目类别：
财政年份：
2012
资助国家：
美国
起止时间：
2012-09-24 至 2014-08-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8413756
关键词：
Address Base Pairing Biological Phenomena Breast Cancer Cell Cancer Patient Cancer cell line Cell Culture System Cell Culture Techniques Cell Line Cell Lineage Cells Cleaved cell Clinical Cluster Analysis Communicable Diseases Complex DNA DNA Library DNA Sequence Data Defect Development Developmental Biology Diagnosis Early Diagnosis Evolution Fertilization in Vitro Fibroblasts Genetic Heterogeneity Genome Genomics Genotype Goals Grant Heterogeneity Human Immune System Diseases Immunology Investigation Knowledge Malignant Neoplasms Mammalian Cell Mammary Neoplasms Methodology Methods Microbiology Mission Modality Modeling Morbidity - disease rate Mutation Nature Neoplasm Metastasis Neurobiology Patients Point Mutation Polymerase Population Primary Neoplasm Public Health Reading Reagent Reporting Research Resistance Resolution Sampling Seeds Signal Transduction Solid Neoplasm Somatic Mutation Technology Testing Tissues Tn5 transposase United States National Institutes of Health Validation Variant Work base cancer cell cancer genome chemotherapy cost effective developmental disease genome sequencing genome-wide human disease improved innovation interest malignant breast neoplasm mortality neoplastic cell nervous system disorder new technology next generation novel programs research study response single cell analysis tool tumor tumor progression

项目摘要

DESCRIPTION (provided by applicant): Current genomic methods are limited to reporting an average signal from a complex population of cells because they require a large amount of input material. In complex tissues such as tumors, where genetic heterogeneity is common, important information may be lost. To address this problem, we propose to develop a whole-genome sequencing method that can obtain high-coverage (>80%) sequencing data from the genome of a single human cell. From this data we will identify the full spectrum of somatic mutations, including point mutations, indels, structural variants and copy number aberration that are present in the genome of a single cell. By comparing the genomes of multiple cells we can delineate clonal diversity and infer how tumor genomes evolve complex somatic mutations. To do this, we propose to develop an innovative method called Cell-Seq which combines minimal isothermal amplification with a Phi29 polymerase and a Tn5 transposase that can simultaneously cleave DNA fragments and add adapters for next-generation sequencing, starting with only a single cell. In aim 1 we will develop and optimize the Cell-Seq method. In aim 2 we will validate the method in two clonal cell cultures by comparing the genomes of single cells to million cell samples, to determine error rates and identify potential biases associated with the method. In aim 3 we will apply Cell-Seq to a human breast tumor sample and sequence the genomes of 10 single cells to investigate clonal diversity and genome evolution. We hypothesize that breast tumors are organized into one or more major clonal subpopulations that stably expand to form the tumor mass, not millions of diverse clones, as the prevailing model for tumor progression assumes. We expect that clustering analysis will show evidence for a few major groups, and that within each group genomic mutations will be highly similar. The proposed single-cell sequencing approach is innovative because it can fully resolve heterogeneity in complex populations of cells, whereas standard bulk genomic methods are limited to reporting an average signal. This research is significant because achieving these aims will improve our fundamental understanding of clonal diversity in human breast cancers, and our knowledge of how tumor genomes evolve complex somatic mutations. Our long-term goal is to use single-cell sequencing to study how single cells from human tumors seed metastases and evolve resistance to chemotherapy. Our work is directly aligned with the mission of the NIH to reduce mortality rates in breast cancer through the development of new modalities for early detection and diagnosing heterogeneity in tumors. Our work is also aligned with the goal of the SCAP to cure human diseases through the development of new single-cell genomic technologies. In addition to benefiting the study of cancer, we expect that our tools will have a broad positive impact on many other human diseases, including neurological disorders, immunological diseases, developmental defects and infectious disease. PUBLIC HEALTH RELEVANCE: We propose to develop a whole-genome sequencing method for single human cells and apply it to study clonal diversity in a breast tumor sample. This study is directly aligned with the interests of the Single Cell Analysis Program (SCAP) to develop new technologies to study genomics in single cells and with the mission of NIH to decreased morbidity in breast cancer through the development of new methods to diagnosing and detecting tumor cells. The single-cell sequencing tools developed in this grant are also highly relevant to public health because they will have a broad positive impact on many other human diseases, including neurological disorders, infectious disease, immunological diseases and developmental disorders.

描述（由申请人提供）：当前的基因组方法仅限于报告复杂细胞群的平均信号，因为它们需要大量的输入材料。在遗传异质性的复杂组织（例如肿瘤）中，可能会丢失重要信息。为了解决这个问题，我们建议开发一种全基因组测序方法，该方法可以从单个人类细胞的基因组中获得高覆盖（> 80％）的测序数据。从这些数据中，我们将确定单个细胞基因组中存在的整个体细胞突变，包括点突变，indels，结构变异和拷贝数畸变。通过比较多个细胞的基因组，我们可以描述克隆多样性，并推断肿瘤基因组如何发展复杂的体细胞突变。为此，我们建议开发一种称为Cell-seq的创新方法，该方法将最小的等温扩增与PHI29聚合酶和TN5转座酶结合在一起，该方法可以同时切割DNA片段，并为下一代测序添加衔接子，仅从单个细胞开始。在AIM 1中，我们将开发和优化单元格方法。在AIM 2中，我们将通过比较单个细胞的基因组与百万个细胞样品的基因组来验证该方法，以确定错误率并确定与该方法相关的潜在偏见。在AIM 3中，我们将对人类乳腺肿瘤样品应用细胞序列，并为10个单个细胞的基因组序列，以研究克隆多样性和基因组进化。我们假设将乳腺肿瘤组织成一个或多个主要的克隆亚群，这些亚群稳定地扩展以形成肿瘤质量，而不是数百万种不同的克隆，正如肿瘤进展的主要模型一样。我们预计聚类分析将显示一些主要群体的证据，并且在每个组中，基因组突变将高度相似。提出的单细胞测序方法具有创新性，因为它可以在复杂的细胞中完全解决异质性，而标准的大量基因组方法仅限于报告平均信号。这项研究很重要，因为实现这些目标将改善我们对人乳腺癌克隆多样性的基本理解，以及我们对肿瘤基因组如何发展复杂体细胞突变的了解。我们的长期目标是使用单细胞测序来研究人类肿瘤种子转移的单个细胞如何发展对化学疗法的耐药性。我们的工作与NIH的任务直接与降低乳腺癌死亡率的使命保持一致，这是通过开发新的方式来提早检测和诊断肿瘤异质性。我们的工作还与SCAP通过开发新的单细胞基因组技术来治愈人类疾病的目标保持一致。除了受益于癌症研究外，我们还希望我们的工具对许多其他人类疾病（包括神经系统疾病，免疫学疾病，发育缺陷和传染病）产生广泛的积极影响。公共卫生相关性：我们建议为单个人类细胞开发一种全基因组测序方法，并将其应用于乳腺肿瘤样品中的克隆多样性。这项研究与单细胞分析程序（SCAP）的利益直接一致，以开发新技术来研究单细胞中的基因组学，以及NIH通过开发诊断和检测肿瘤细胞的新方法来降低乳腺癌的发病率。该赠款中开发的单细胞测序工具也与公共卫生高度相关，因为它们将对许多其他人类疾病产生广泛的积极影响，包括神经系统疾病，传染病，免疫疾病和发育疾病。