Single-Cell Multi-omics to Link Clonal Mosaicism (CM) Genotypes with Chromatin, Epigenomic, Transcriptomic and Protein Phenotypes

总结 在广泛的正常人体组织中观察到克隆生长。克隆港体细胞 已知癌症和其他驱动基因的突变，并显示出积极选择的证据。而如何 这些驱动突变改变了细胞的细胞状态，使克隆能够胜过野生型对应物 仍然知之甚少。迄今为止，在正常组织中绘制克隆生长的努力主要是 仅限于基因分型。这是因为克隆通常会影响样本中的少数细胞， 区分细胞表面标记或形态学特征。 为了应对这一挑战，我们开发了一系列多组学单细胞技术， 捕获多层信息（例如，基因型、转录组、甲基化组、蛋白质表达）， 相同的单细胞。此外，我们解决了scRNA-seq中基因分型的特定挑战， 通过开发转录组的基因分型，以高通量的方式对细胞进行分析。重要的是，这项技术将 突变体和野生型细胞的混合物从限制变为优势，使得能够直接比较 在同一个体内的突变体（“赢家”）和野生型（“失败者”）细胞。 利用我们在单细胞技术开发方面的经验，我们的目标是扩展多组学 单细胞GoT（目标基因座的基因分型）工具包，允许询问体细胞突变如何导致 克隆生长优势首先，我们将开发和加强我们的目标单细胞基因分型的背景下， 染色质可及性（GoT-ChA）。这项技术直接从DNA中严格执行基因分型， 避免了对突变基因座基因表达的有限依赖性。因此，它可以应用于提取的核， 对SMaHT计划至关重要。我们将在GoT-ChA的基础上使用纳米抗体栓系转座酶， 在单个细胞核中分析体细胞突变和组蛋白修饰（GoT-EpiM）。为了捕获转录 变化连同体细胞突变基因分型和染色质可及性，我们将进一步使用 mRNA：cDNA杂合体在GoT-ChA-RNA中的转座。最后，我们将利用最新的进展， 用寡核苷酸标记的抗体，以捕获突变的基因座、染色质和核内蛋白， 转录因子（GoT-ChA-Pro）。在aim 2中，我们将与基因组表征中心合作， 将这些技术应用于原始人类样本，以确定正常组织中的克隆突变如何改变 染色质、组蛋白修饰、转录组和蛋白质丰度谱以产生克隆生长。 我们的首要目标是在单细胞水平上在野生型和突变型之间进行多组学比较 细胞，以全面确定克隆生长的健身优势的基础。拟议 全面的GoT工具包将能够在高通量单细胞基因型与转录之间建立联系， 蛋白质和表观遗传，在克隆嵌合体作为癌症预兆的研究中具有重要意义， 以及其他人类健康结果。

SUMMARY Clonal outgrowths are observed across a wide range of normal human tissues. Clones harbor somatic mutations in known cancer and other driver genes, and show evidence of positive selection. Nevertheless, how these driver mutations alter the cellular states of cells to allow clones to outcompete wildtype counterparts remains poorly understood. To date, efforts to chart clonal outgrowths in normal tissues have been largely limited to genotyping. This is due to the fact that clones often affect a minority of cells in a sample, without distinguishing cell surface markers or morphological features. To address this challenge, we developed an array of multi-omic single-cell technologies that are capable of capturing multiple layers of information (e.g., genotypes, transcriptomes, methylomes, protein expression) from the same single cells. Moreover, we addressed the specific challenge of genotyping in scRNA-seq in single cells at high throughput by developing genotyping of transcriptomes. Importantly, this technology turns the admixture of mutant and wildtype cell from a limitation to an advantage, enabling the direct comparison of mutant (“winner”) and wildtype (“loser”) cells within the same individual. Capitalizing on our experience with single-cell technology development, we aim to extend the multi-omics single-cell GoT (Genotyping of Targeted loci) toolkit to allow to interrogate how somatic mutations lead to clonal growth advantage. First, we will develop and enhance our targeted single-cell genotyping in the context of chromatin accessibility (GoT-ChA). This technology critically performs genotyping from DNA directly, obviating limiting dependencies on mutated loci gene expression. Thus, it can be applied to extracted nuclei, critical for the SMaHT initiative. We will build on GoT-ChA using nanobody tethered transposases to jointly profile somatic mutations and histone modifications in single nuclei (GoT-EpiM). To capture transcriptional changes together with somatic mutation genotyping and chromatin accessibility, we will further use transposition of mRNA:cDNA hybrid in GoT-ChA-RNA. Finally, we will leverage recent advances that use antibodies tagged with oligonucleotides to capture mutated loci, chromatin and intra-nuclear proteins such as transcription factors (GoT-ChA-Pro). In aim 2, we will collaborate with genomic characterization centers to apply these technologies to primary human samples to define how clonal mutations in normal tissues alter chromatin, histone modifications, transcriptomes and protein abundance profiles to yield clonal outgrowth. Our overarching goal is to invoke multi-omic comparisons at the single-cell level between wildtype and mutant cells to comprehensively identify the underpinnings of fitness advantage in clonal outgrowth. The proposed comprehensive GoT toolkit will enable to link, at high throughout single-cell genotypes with transcriptional, protein, and epigenetic, with important implication in the study of clonal mosaicism as a harbinger of cancer, as well as other human health outcomes.