Project description:The cell cycle is known to regulate cell proliferation and cell fate decisions, the underlying mechanism of which is well-studied and conserved across species and cell types. To date, the cell cycle is receiving a renewed importance due to the rapid advancement of single-cell genomics technology. Especially in the analysis of single-cell gene expression, the cell cycle plays a key role in understanding the expression variation across cell states and cell types. The current study was designed to develop effective tools for assessing and predicting the cell cycle in single-cell gene expression data analysis. We collected both Fluorescent Ubiquitination-based Cell Cycle Indicator (FUCCI) – for determining the cell cycle – and single-cell RNA-seq (scRNA-seq) data from each individual using STRT-seq on the Fluidigm C1 platform. The cells were collected from iPSCs derived from 6 genotyped Yoruba cell lines. The experimental design controlled for C1 processing batch effects, as well as individual and gender effects. Using these data, we developed a supervised approach for predicting the cyclical ordering of single cells in the cell cycle using single-cell gene expression data. We used the FUCCI fluorescent intensities to determine a cyclical ordering of the individual cells, and to assign cell time labels for individual cells representing each cell's position in one complete cell cycle. We estimated the cyclical trend of expression levels for each gene based on the FUCCI-derived cell times, and identified candidate sets of cyclical genes for model training. We trained our model in in 5-fold cross-validation and evaluate the trained model in held-out validation samples and external datasets. We compared the prediction results with existing approaches for estimating the cell cycle using single-cell gene expression data: including unsupervised approaches to construct the cyclical ordering of single cells and approaches to categorically assign the cell cycle to individual cells. These results provide a benchmark for assessing the cell cycle in scRNA-seq data analysis and insights into the effects of the cell cycle on gene expression variation in stem cells.
Project description:Cell proliferation and division are fundamental processes of plant development and homeostasis. With the feature of high homogeneity, tobacco Bright Yellow-2 (BY-2) cells, a so-called “HeLa” cell line in plants, provide a useful system for study the cell cycle of plants, particularly when in combination with the latest high-throughput single-cell RNA sequencing (scRNA-seq) technology. Here, we generated both scRNA-seq and bulk RNA-seq data from the BY-2 cells and found that the enzymatic hydrolysis during protoplasting was the major factor contributing to cell clustering noise. We introduced the ppScoring concept to filter out confounding cells due to protoplasting and clustered the remaining cells into clusters corresponding to G0-G1, S, and G2-M phases as well as clusters with phase transition arrested or cell cycle exit cells. The clustering results were supported by cell cycle phase specific marker genes and reconstruction of the continuous full cell cycle phases, i.e., from G0-G1 to S to G2-M, based on pseudotime trajectory analysis. The clustering results also identified a set of 896 cell cycle marker genes. This work demonstrated cell cycle-dependent transcriptional heterogeneity of the BY-2 cell population, provided marker genes for study of the cell cycle of plants and new insights into the progression of cell division.
Project description:To analyze the effect of Exportin-5 expression on the MEF cells in cell cycle re-entry phase, we have employed whole genome microarray expression profiling on the MEF cells in cell cycle re-entry phase with and without down regulation of Exportin-5 gene.
Project description:To identify the component(s) involved in cell cycle control in the protozoan Giardia lamblia, cells arrested at the G1- or G2-phase by treatment with nocodazole and aphidicolin were prepared from the synchronized cell cultures. RNA-sequencing analysis of the two stages of Giardia cell cycle identified several cell cycle genes that were up-regulated at the G2-phase. This result indicates that the cell cycle machinery operates in this protozoan, one of the earliest diverging eukaryotic lineages.
Project description:Gene expression must be reconfigured rapidly during the subsequent phases of the cell cycle to execute the cellular functions specific of each phase. Post-transcriptional regulation has a predominant role in modulating gene expression during the mitotic cell cycle, including among other mechanisms, protein phosphorylation and ubiquitination, differential protein stability and mRNA localization and translatability. Regulation at the transcriptional level is also important, as studies conducted in synchronized plant cell suspension cultures have identified hundreds of genes with periodic patterns of genes expression across the phases of the cell cycle. We describe here an alternative strategy to cell suspension cultures to profile the transcriptome of Arabidopsis root cells in the G2/M phase of the cell cycle. Through fluorescence activated cell sorting we first isolated cells in G2/M using CYCB1;1-GFP, a reporter of a mitotic cyclin. The analysis of the transcriptome of these cells allowed us to identify hundreds of genes whose expression is depleted or enriched in G2/M cells.
Project description:We compared the poly(A) tail length status of mRNAs of HeLa cells between two phases of the mitotic cell cycle: S and G2/M phases. Hundreds of mRNAs were found to be regulated by changes in their poly(A) tail length during mitotic cell cycle in a phase specific manner. Many of these differentially polyadenylated mRNAs encode proteins related to cell death, cell cycle and cellular growth and proliferation. HeLa cells were synchronized with double thymidine blockade (12 hours with 2 mM thymidine, 12 hours release, and 12 hours with 2 mM thymidine), and samples were taken after 2 hours release (S phase) and 8 hours release (G2/M phase). For each condition total RNA was purified by two different procedures: poly(U) chromatography and oligo(dT)-chromatography. Poly(U)-chromatography (Jacobson, 1987): 100 μg of total RNA were bound to poly(U)-sepharose (Sigma) and eluted at 35ºC to isolate mRNAs with short poly(A) tail (<30As, SHORT fraction). Oligo(dT) chromatography: mRNAs were purified independently of their poly(A) tail length with Ambion Poly(A)Purist kit from 20 μg total RNA (ALL fraction). Jacobson, A. Purification and fractionation of poly(A)+ RNA. Methods in Enzymology (1987) 152: 254-261. Keywords: time course
Project description:We performed ATAC seq of inducible FOXD3 KO cells after cell cycle phase sorting to determine impact of FOXD3 loss on chromatin accessibility.