five

An ultra high-throughput, massively multiplexable, single-cell RNA-seq platform in yeasts

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP479790
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Yeasts are naturally diverse, genetically tractable, and easy to grow such that researchers can investigate any number of genotypes, environments, or interactions thereof. However, studies of yeast transcriptomes have been limited by the processing capabilities of traditional RNA sequencing techniques. Here we optimize a powerful, high-throughput single-cell RNA sequencing (scRNAseq) platform, SPLiT-seq (Split Pool Ligation-based Transcriptome sequencing), for yeasts and apply it to 43,388 cells of multiple species and ploidies. This platform utilizes a combinatorial barcoding strategy to enable massively parallel RNA sequencing of hundreds of yeast genotypes or growth conditions at once. This method can be applied to most species or strains of yeast for a fraction of the cost of traditional scRNAseq approaches. Thus, our technology permits researchers to leverage “the awesome power of yeast” by allowing us to survey the transcriptome of hundreds of strains and environments in a short period of time, and with no specialized equipment. The key to this method is that sequential barcodes are probabilistically appended to cDNA copies of RNA while the molecules remain trapped inside of each cell. Thus, the transcriptome of each cell is labeled with a unique combination of barcodes. Since SPLiT-seq uses the cell membrane as a container for this reaction, many cells can be processed together without the need to physically isolate them from one another in separate wells or droplets. Further, the first barcode in the sequence can be chosen intentionally to identify samples from different environments or genetic backgrounds, enabling multiplexing of hundreds of unique perturbations in a single experiment. In addition to greater multiplexing capabilities, our method also facilitates a deeper investigation of biological heterogeneity given its single-cell nature. For example, in the data presented here we detect transcriptionally distinct cell states related to cell cycle, ploidy, metabolic strategies, etc. all within clonal yeast populations grown in the same environment. Hence, our technology has two obvious and impactful applications for yeast research: the first is the general study of transcriptional phenotypes across many strains and environments, and the second is investigating cell-to-cell heterogeneity across the entire transcriptome. Overall design: Diploid s288c, genetically naive haploid BY4741, MATa ura3A0 his3?1 met17?0 P ACT1-GAL3::SpHIS5 gall1?gal10?::LEU2 leu2?0::P PGK1 -mCherry-KanMX6 ybr209w?::B103-HphMX6, and MATa ura3A0 his3?1 met17?0 P ACT1-GAL3::SpHIS5 gall1?gal10?::LEU2 leu2?0::P GAL1 -YFP-KanMX6 ybr209w?::BC3-HphMX6, and ATCC 3147 C. albicans strains were used. Cells were streaked on YP plus 2% dextrose agar plates from frozen -80C glycerol stocks and grown at 30C for 48 hours. In experiments 1 and 2, single colonies of s288c and ATCC 3147 were picked into YP plus 2% dextrose liquid media (YPD). The YFP and mCherry engineered cells were picked into Synthetic Complete minus glucose (Sunrise) plus 2.5% sucrose, 1.25% raffinose, and 0.625% galactose media to induce YFP expression in experiment 2. In experiment 3, diploid s288c cells and haploid BY4741 cells were picked into Synthetic Complete (Sunrise) plus 2% glucose media (SCD). All cultures were grown with shaking at 30C for 24 hours. For experiments 1 and 2, cells were then transferred into fresh YPD media at a 1:250 dilution and grown until cultures reached approximately 2-4*10^7 cells/mL, or early mid log phase. For experiment 3, approximately 15,000 total cells were transferred into 50 mL of fresh SCD and sampled at 17, 19, 21, and 23 hours after inoculation which correspond to approximately 0.9*10^7, 2.7*10^7, 5.7*10^7, and 8.6*10^7 cells/mL.
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2024-07-03
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