Dataset Information

Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors.

ABSTRACT: Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we combined Luria and Delbrück's fluctuation analysis with population-based RNA sequencing (MemorySeq) for identifying genes transcriptome-wide whose fluctuations persist for several divisions. MemorySeq revealed multiple gene modules that expressed together in rare cells within otherwise homogeneous clonal populations. These rare cell subpopulations were associated with biologically distinct behaviors like proliferation in the face of anti-cancer therapeutics. The identification of non-genetic, multigenerational fluctuations can reveal new forms of biological memory in single cells and suggests that non-genetic heritability of cellular state may be a quantitative property.

SUBMITTER: Shaffer SM

PROVIDER: S-EPMC7496637 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors.

Shaffer Sydney M SM Emert Benjamin L BL Reyes Hueros Raúl A RA Cote Christopher C Harmange Guillaume G Schaff Dylan L DL Sizemore Ann E AE Gupte Rohit R Torre Eduardo E Singh Abhyudai A Bassett Danielle S DS Raj Arjun A

Cell 20200730 4

Non-genetic factors can cause individual cells to fluctuate substantially in gene expression levels over time. It remains unclear whether these fluctuations can persist for much longer than the time of one cell division. Current methods for measuring gene expression in single cells mostly rely on single time point measurements, making the duration of gene expression fluctuations or cellular memory difficult to measure. Here, we combined Luria and Delbrück's fluctuation analysis with population-b ...[more]

PMID: 32735851

Similar Datasets

Project description:Study questionWhat are the cellular composition and single-cell transcriptomic differences between myometrium and leiomyomas as defined by single-cell RNA sequencing?Summary answerWe discovered cellular heterogeneity in smooth muscle cells (SMCs), fibroblast and endothelial cell populations in both myometrium and leiomyoma tissues.What is known alreadyPrevious studies have shown the presence of SMCs, fibroblasts, endothelial cells and immune cells in myometrium and leiomyomas. However, there is no information on the cellular heterogeneity in these tissues and the transcriptomic differences at the single-cell level between these tissues.Study design, size, durationWe collected five leiomyoma and five myometrium samples from a total of eight patients undergoing hysterectomy. We then performed single-cell RNA sequencing to generate a cell atlas for both tissues. We utilized our single-cell sequencing data to define cell types, compare cell types by tissue type (leiomyoma versus myometrium) and determine the transcriptional changes at a single-cell resolution between leiomyomas and myometrium. Additionally, we performed MED12-variant analysis at the single-cell level to determine the genotype heterogeneity within leiomyomas.Participants/materials, setting, methodsWe collected five MED12-variant positive leiomyomas and five myometrium samples from a total of eight patients. We then performed single-cell RNA sequencing on freshly isolated single-cell preparations. Histopathological assessment confirmed the identity of the samples. Sanger sequencing was performed to confirm the presence of the MED12 variant in leiomyomas.Main results and role of chanceOur data revealed previously unknown heterogeneity in the SMC, fibroblast cell and endothelial cell populations of myometrium and leiomyomas. We discovered the presence of two different lymphatic endothelial cell populations specific to uterine leiomyomas. We showed that both myometrium and MED12-variant leiomyomas are relatively similar in cellular composition but differ in cellular transcriptomic profiles. We found that fibroblasts influence the leiomyoma microenvironment through their interactions with endothelial cells, immune cells and SMCs. Variant analysis at the single-cell level revealed the presence of both MED12 variants as well as the wild-type MED12 allele in SMCs of leiomyomatous tissue. These results indicate genotype heterogeneity of cellular composition within leiomyomas.Large scale dataThe datasets are available in the NCBI Gene Expression Omnibus (GEO) using GSE162122.Limitations, reasons for cautionOur study focused on MED12-variant positive leiomyomas for single-cell RNA sequencing analyses. Leiomyomas carrying other genetic rearrangements may differ in their cellular composition and transcriptomic profiles.Wider implications for the findingsOur study provides a cellular atlas for myometrium and MED12-variant positive leiomyomas as defined by single-cell RNA sequencing. Our analysis provides significant insight into the differences between myometrium and leiomyomas at the single-cell level and reveals hitherto unknown genetic heterogeneity in multiple cell types within human leiomyomas. Our results will be important for future studies into the origin and growth of human leiomyomas.Study funding/competing interest(s)This work was supported by funding from the National Institute of Child Health and Human Development (HD098580 and HD088629). The authors declare no competing interests.

Dataset Information

Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors.

Publications

Memory Sequencing Reveals Heritable Single-Cell Gene Expression Programs Associated with Distinct Cellular Behaviors.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets