Summary Copy number variation (CNV) is increasingly recognized as an important contributor to phenotypic variation in health and disease. Most methods for determining CNV rely on admixtures of cells, where information regarding genetic heterogeneity is lost. Here, we present a protocol that allows for the genome wide copy number analysis of single nuclei isolated from mixed populations of cells. Single nucleus sequencing (SNS), combines flow sorting of single nuclei based on DNA content, whole genome amplification (WGA), followed by next generation sequencing to quantize genomic intervals in a genome wide manner. Multiplexing of single cells is discussed. Additionally, we outline informatic approaches that correct for biases inherent in the WGA procedure and allow for accurate determination of copy number profiles. All together, the protocol takes ~3 days from flow cytometry to sequence-ready DNA libraries.

We used Drosophila olfactory memory in order to understand in vivo the molecular basis of cognitive defect in Fragile X syndrome. We observed that Fragile X protein (FMRP) was required acutely and interacted with argonaute1 and staufen in long-term memory (LTM). Occlusion of long-term memory formation in Fragile X mutants could be rescued by protein synthesis inhibitors, suggesting that excess baseline protein synthesis could impact negatively on cognition.

A substantial proportion of tumors consist of genotypically distinct subpopulations of cancer cells. This intra-tumor genetic heterogeneity poses a significant challenge for the implementation of precision medicine. Single-cell genomics constitutes a powerful approach to resolve complex mixtures of cancer cells by tracing cell lineages and discovering cryptic genetic variations that would otherwise be obscured in tumor bulk analyses. Given the chemical alterations that result from formalin fixation, single-cell genomic approaches have largely remained limited to fresh/frozen specimens. Here we describe the development and validation of a robust and accurate methodology to perform whole-genome copy-number profiling of single nuclei obtained from formalin-fixed paraffin-embedded clinical tumor samples. We applied the single-cell sequencing approach described here to study the progression from in situ to invasive breast cancer, which revealed that ductal carcinomas in situ display intra-tumor genetic heterogeneity at diagnosis and that these lesions may progress to invasive breast cancer through a variety of evolutionary processes.

Genome-wide analysis at the level of single cells has recently emerged as a powerful tool to dissect genome heterogeneity in cancer, neurobiology, and development. To be truly transformative, single-cell approaches must affordably accommodate large numbers of single cells. This is feasible in the case of copy number variation (CNV), because CNV determination requires only sparse sequence coverage. We have used a combination of bioinformatic and molecular approaches to optimize single-cell DNA amplification and library preparation for highly multiplexed sequencing, yielding a method that can produce genome-wide CNV profiles of up to a hundred individual cells on a single lane of an Illumina HiSeq instrument. We apply the method to human cancer cell lines and biopsied cancer tissue, thereby illustrating its efficiency, reproducibility, and power to reveal underlying genetic heterogeneity and clonal phylogeny. The capacity of the method to facilitate the rapid profiling of hundreds to thousands of single-cell genomes represents a key step in making single-cell profiling an easily accessible tool for studying cell lineage.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, and new therapies are needed. Altered metabolism is a cancer vulnerability, and several metabolic pathways have been shown to promote PDAC. However, the changes in cholesterol metabolism and their role during PDAC progression remain largely unknown. Here we used organoid and mouse models to determine the drivers of altered cholesterol metabolism in PDAC and the consequences of its disruption on tumor progression. We identified sterol O-acyltransferase 1 (SOAT1) as a key player in sustaining the mevalonate pathway by converting cholesterol to inert cholesterol esters, thereby preventing the negative feedback elicited by unesterified cholesterol. Genetic targeting of Soat1 impairs cell proliferation in vitro and tumor progression in vivo and reveals a mevalonate pathway dependency in p53 mutant PDAC cells that have undergone p53 loss of heterozygosity (LOH). In contrast, pancreatic organoids lacking p53 mutation and p53 LOH are insensitive to SOAT1 loss, indicating a potential therapeutic window for inhibiting SOAT1 in PDAC.