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Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations

文献类型：期刊论文

作者Nadal-Ribelles, Mariona1,2,3,6; Islam, Saiful1,2; Wei, Wu1,2; Nguyen, Michelle1,2; Steinmetz, Lars M.1,2; Latorre, Pablo3,6; de Nadal, Eulalia3,6; Posas, Francesc3,6; Wei, Wu4; Steinmetz, Lars M.5
刊名NATURE MICROBIOLOGY
出版日期2019
卷号4期号:4页码:683-692
ISSN号2058-5276
DOI10.1038/s41564-018-0346-9
文献子类Article
英文摘要Single-cell RNA sequencing has revealed extensive cellular heterogeneity within many organisms, but few methods have been developed for microbial clonal populations. The yeast genome displays unusually dense transcript spacing, with interleaved and overlapping transcription from both strands, resulting in a minuscule but complex pool of RNA that is protected by a resilient cell wall. Here, we have developed a sensitive, scalable and inexpensive yeast single-cell RNA-seq (yscRNA-seq) method that digitally counts transcript start sites in a strand- and isoform-specific manner. YscRNA-seq detects the expression of low-abundance, noncoding RNAs and at least half of the protein-coding genome in each cell. In clonal cells, we observed a negative correlation for the expression of sense-antisense pairs, whereas paralogs and divergent transcripts co-expressed. By combining yscRNA-seq with index sorting, we uncovered a linear relationship between cell size and RNA content. Although we detected an average of -3.5 molecules per gene, the number of expressed isoforms is restricted at the single-cell level. Remarkably, the expression of metabolic genes is highly variable, whereas their stochastic expression primes cells for increased fitness towards the corresponding environmental challenge. These findings suggest that functional transcript diversity acts as a mechanism that provides a selective advantage to individual cells within otherwise transcriptionally heterogeneous populations.
学科主题Microbiology
WOS关键词SACCHAROMYCES-CEREVISIAE ; GENES ; CYCLE ; PCR ; QUANTIFICATION ; IDENTIFICATION ; VALIDATION ; NOISE ; START
语种英语
出版者NATURE PUBLISHING GROUP
WOS记录号WOS:000461999200021
版本出版稿
源URL[http://202.127.25.144/handle/331004/483]  
专题中国科学院上海生命科学研究院营养科学研究所
作者单位1.Stanford Univ, Stanford Genome Technol Ctr, Stanford, CA 94305 USA;
2.Stanford Univ, Dept Genet, Sch Med, Stanford, CA 94305 USA;
3.Barcelona Inst Sci & Technol, Cell Signaling, Inst Res Biomed, Barcelona, Spain;
4.Univ Chinese Acad Sci, Chinese Acad Sci, CAS Key Lab Computat Biol,Shanghai Inst Biol Sci, CAS MPG Partner Inst Computat Biol,Shanghai Inst, Shanghai, Peoples R China;
5.Genome Biol Unit, European Mol Biol Lab, Heidelberg, Germany,
6.Univ Pompeu Fabra, Cell Signaling Res Grp, Dept Ciencies Expt & Salut, Barcelona, Spain;
推荐引用方式
GB/T 7714		 Nadal-Ribelles, Mariona,Islam, Saiful,Wei, Wu,et al. Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations[J]. NATURE MICROBIOLOGY,2019,4(4):683-692.
APA Nadal-Ribelles, Mariona.,Islam, Saiful.,Wei, Wu.,Nguyen, Michelle.,Steinmetz, Lars M..,...&Steinmetz, Lars M..(2019).Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations.NATURE MICROBIOLOGY,4(4),683-692.
MLA Nadal-Ribelles, Mariona,et al."Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations".NATURE MICROBIOLOGY 4.4(2019):683-692.

入库方式： OAI收割

来源：上海营养与健康研究所

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