Adapting the 10x Genomics Platform for single-cell RNA-seq in yeast reveals the importance of stochastic gene expression during the lag phase
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ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE144820 | GEO | 2020/02/06
REPOSITORIES: GEO
Similar Datasets
Project description:Adapting the 10x Genomics Platform for single-cell RNA-seq in yeast reveals the importance of stochastic gene expression during the lag phase
| PRJNA605000 | ENA
Project description:Single-cell RNA sequencing (scRNA-seq) is generally used for profiling transcriptome of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data generated by these two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analyses. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data more. For 10X-based data, we observed higher noise for mRNAs with low expression levels. Approximately 10%-30% of all detected transcripts by both platforms were from non-coding genes, with long non-coding RNAs (lncRNAs) accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected distinct groups of differentially expressed genes between cell clusters, indicating the different characteristics of these technologies. Our study promotes better understanding of these two platforms and offers the basis for an informed choice of these widely used technologies.
| S-EPMC8602399 | biostudies-literature
Project description:The time that elapsed between the initial introduction and the proliferation of an invasive species is referred to as the lag phase. The identification of the lag phase is critical for generating plans for pest management and for the prevention of biosecurity failure. However, lag phases have been identified mostly through retrospective searches of historical records. The agricultural pest fall armyworm (FAW; Spodoptera frugiperda) is native to the New World. FAW invasion was first reported from West Africa in 2016, then it spread quickly through Africa, Asia, and Oceania. Here, using population genomics approaches, we demonstrate that the FAW invasion involved an undocumented lag phase. Invasive FAW populations have negative signs of genomic Tajima's D, and invasive population-specific genetic variations have particularly decreased Tajima's D, supporting a substantial amount of time for the generation of new mutations in introduced FAW populations. Model-based diffusion approximations support the existence of a period with a cessation of gene flow between native and invasive FAW populations. Taken together, these results provide strong support for the presence of a lag phase during the FAW invasion. These results show the usefulness of using population genomics analyses to identify lag phases in biological invasions.
| S-EPMC11310199 | biostudies-literature
Project description:T cell receptor (TCR) signaling in Jurkat cells was investigated using the CROP-seq method for CRISPR single-cell sequencing. In CROP-seq, genetic perturbations are introduced into single cells in a pooled fashion, and single-cell RNA-seq is used to determine the transcriptional response to the CRISPR-induced perturbation in a large number of single cells in parallel. Importantly, the CROP-seq vector makes individual guide-RNAs detectable using standard single-cell RNA-seq technology. The dataset presented here is based on CROP-seq in combination with single-cell RNA-seq using the 10x Genomics v2 chemistry. It recapitulates a previously published CROP-seq dataset (Datlinger et al. 2017 Nature Methods; GEO: GSE92872) that used the Drop-seq protocol as the single-cell RNA-seq readout. Additional information on CROP-seq are available from the following website: http://crop-seq.computational-epigenetics.org/ .
2019-10-08 | GSE137554 | GEO
Project description:BackgroundSingle-cell RNA sequencing experiments commonly use 10x Genomics (10x) kits due to their high-throughput capacity and standardized protocols. Recently, Parse Biosciences (Parse) introduced an alternative technology that uses multiple in-situ barcoding rounds within standard 96-well plates. Parse enables the analysis of more cells from multiple samples in a single run without the need for additional reagents or specialized microfluidics equipment. To evaluate the performance of both platforms, we conducted a benchmark study using biological and technical replicates of mouse thymus as a complex immune tissue.ResultsWe found that Parse detected nearly twice the number of genes compared to 10x, with each platform detecting a distinct set of genes. The comparison of multiplexed samples generated from 10x and Parse techniques showed 10x data to have lower technical variability and more precise annotation of biological states in the thymus compared to Parse.ConclusionOur results provide a comprehensive comparison of the suitability of both single-cell platforms for immunological studies.
| S-EPMC11552371 | biostudies-literature
Project description:The linked read sequencing library preparation platform by 10X Genomics produces barcoded sequencing libraries, which are subsequently sequenced using the Illumina short read sequencing technology. In this new approach, long fragments of DNA are partitioned into separate micro-reactions, where the same index sequence is incorporated into each of the sequencing fragment inserts derived from a given long fragment. In this study, we exploited this property by using reads from index sequences associated with a large number of reads, to assemble the chloroplast genome of the Sitka spruce tree (Picea sitchensis). Here we report on the first Sitka spruce chloroplast genome assembled exclusively from P. sitchensis genomic libraries prepared using the 10X Genomics protocol. We show that the resulting 124,049 base pair long genome shares high sequence similarity with the related white spruce and Norway spruce chloroplast genomes, but diverges substantially from a previously published P. sitchensis- P. thunbergii chimeric genome. The use of reads from high-frequency indices enabled separation of the nuclear genome reads from that of the chloroplast, which resulted in the simplification of the de Bruijn graphs used at the various stages of assembly.
| S-EPMC5025161 | biostudies-literature
Project description:Current methods for single-cell RNA sequencing (scRNA-seq) of yeast cells do not match the throughput and relative simplicity of the state-of-the-art techniques that are available for mammalian cells. In this study, we report how 10x Genomics' droplet-based single-cell RNA sequencing technology can be modified to allow analysis of yeast cells. The protocol, which is based on in-droplet spheroplasting of the cells, yields an order-of-magnitude higher throughput in comparison to existing methods. After extensive validation of the method, we demonstrate its use by studying the dynamics of the response of isogenic yeast populations to a shift in carbon source, revealing the heterogeneity and underlying molecular processes during this shift. The method we describe opens new avenues for studies focusing on yeast cells, as well as other cells with a degradable cell wall.
| S-EPMC7259953 | biostudies-literature
Project description:Background: The commercially available 10x Genomics protocol to generate droplet-based single cell RNA-seq (scRNA-seq) data is enjoying growing popularity among researchers. Fundamental to the analysis of such scRNA-seq data is the ability to cluster similar or same cells into non-overlapping groups. Many competing methods have been proposed for this task, but there is currently little guidance with regards to which method to use. Methods: Here we use one gold standard 10x Genomics dataset, generated from the mixture of three cell lines, as well as multiple silver standard 10x Genomics datasets generated from peripheral blood mononuclear cells to examine not only the accuracy but also running time and robustness of a dozen methods. Results: We found that Seurat outperformed other methods, although performance seems to be dependent on many factors, including the complexity of the studied system. Furthermore, we found that solutions produced by different methods have little in common with each other. Conclusions: In light of this we conclude that the choice of clustering tool crucially determines interpretation of scRNA-seq data generated by 10x Genomics. Hence practitioners and consumers should remain vigilant about the outcome of 10x Genomics scRNA-seq analysis.
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Project description:The European hazelnut (Corylus avellana L.; 2n = 2x = 22) is a worldwide economically important tree nut that is cross-pollinated due to sporophytic incompatibility. Therefore, any individual plant is highly heterozygous. Cultivars are clonally propagated using mound layering, rooted suckers, and micropropagation. In recent years, the interest in this crop has increased, due to a growing demand related to the recognized health benefits of nut consumption. C. avellana cv "Tonda Gentile delle Langhe" ("TGdL") is well-known for its high kernel quality, and the premium price paid for this cultivar is an economic benefit for producers in northern Italy. Assembly of a high-quality genome is a difficult task in many plant species because of the high level of heterozygosity. We assembled a chromosome-level genome sequence of "TGdL" with a two-step approach. First, 10X Genomics Chromium Technology was used to create a high-quality sequence, which was then assembled into scaffolds with cv "Tombul" genome as the reference. Eleven pseudomolecules were obtained, corresponding to 11 chromosomes. A total of 11,046 scaffolds remained unplaced, representing 11% of the genome (46,504,161 bp). Gene prediction, performed with Maker-P software, identified 27,791 genes (AED ≤0.4 and 92% of BUSCO completeness), whose function was analyzed with BlastP and InterProScan software. To characterize "TGdL" specific genetic mechanisms, Orthofinder was used to detect orthologs between hazelnut and closely related species. The "TGdL" genome sequence is expected to be a powerful tool to understand hazelnut genetics and allow detection of markers/genes for important traits to be used in targeted breeding programs.
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Project description:Lysosomes are the terminal degradative compartment of autophagy, endocytosis and phagocytosis. What once was viewed as a simple acidic organelle in charge of macromolecular digestion has emerged as a dynamic organelle capable of integrating cellular signals and producing signal outputs. In this review, we focus on the concept that the lysosome surface serves as a platform to assemble major signaling hubs like mTORC1, AMPK, GSK3 and the inflammasome. These molecular assemblies integrate and facilitate cross-talk between signals such as amino acid and energy levels, membrane damage and infection, and ultimately enable responses such as autophagy, cell growth, membrane repair and microbe clearance. In particular, we review how molecular machinery like the vacuolar-ATPase proton pump, sestrins, the GATOR complexes, and the Ragulator, modulate mTORC1, AMPK, GSK3 and inflammation. We then elaborate how these signals control autophagy initiation and resolution, TFEB-mediated lysosome adaptation, lysosome remodeling, antigen presentation, inflammation, membrane damage repair and clearance. Overall, by being at the cross-roads for several membrane pathways, lysosomes have emerged as the ideal surveillance compartment to sense, integrate and elicit cellular behavior and adaptation in response to changing environmental and cellular conditions.
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