A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA
Abstract Significant heterogeneities in gene expression among individual cells are typically interrogated using single whole cell approaches. However, tissues that have highly interconnected processes, such as in the brain, present unique challenges. Single-nucleus RNA sequencing (SNS) has emerged a...
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Nature Portfolio
2017
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oai:doaj.org-article:decb1c554c2c448c9346ed00418f18852021-12-02T15:05:15ZA comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA10.1038/s41598-017-04426-w2045-2322https://doaj.org/article/decb1c554c2c448c9346ed00418f18852017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-04426-whttps://doaj.org/toc/2045-2322Abstract Significant heterogeneities in gene expression among individual cells are typically interrogated using single whole cell approaches. However, tissues that have highly interconnected processes, such as in the brain, present unique challenges. Single-nucleus RNA sequencing (SNS) has emerged as an alternative method of assessing a cell’s transcriptome through the use of isolated nuclei. However, studies directly comparing expression data between nuclei and whole cells are lacking. Here, we have characterized nuclear and whole cell transcriptomes in mouse single neurons and provided a normalization strategy to reduce method-specific differences related to the length of genic regions. We confirmed a high concordance between nuclear and whole cell transcriptomes in the expression of cell type and metabolic modeling markers, but less so for a subset of genes associated with mitochondrial respiration. Therefore, our results indicate that single-nucleus transcriptome sequencing provides an effective means to profile cell type expression dynamics in previously inaccessible tissues.Blue B. LakeSimone CodeluppiYun C. YungDerek GaoJerold ChunPeter V. KharchenkoSten LinnarssonKun ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-8 (2017) |
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Medicine R Science Q |
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Medicine R Science Q Blue B. Lake Simone Codeluppi Yun C. Yung Derek Gao Jerold Chun Peter V. Kharchenko Sten Linnarsson Kun Zhang A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA |
| description |
Abstract Significant heterogeneities in gene expression among individual cells are typically interrogated using single whole cell approaches. However, tissues that have highly interconnected processes, such as in the brain, present unique challenges. Single-nucleus RNA sequencing (SNS) has emerged as an alternative method of assessing a cell’s transcriptome through the use of isolated nuclei. However, studies directly comparing expression data between nuclei and whole cells are lacking. Here, we have characterized nuclear and whole cell transcriptomes in mouse single neurons and provided a normalization strategy to reduce method-specific differences related to the length of genic regions. We confirmed a high concordance between nuclear and whole cell transcriptomes in the expression of cell type and metabolic modeling markers, but less so for a subset of genes associated with mitochondrial respiration. Therefore, our results indicate that single-nucleus transcriptome sequencing provides an effective means to profile cell type expression dynamics in previously inaccessible tissues. |
| format |
article |
| author |
Blue B. Lake Simone Codeluppi Yun C. Yung Derek Gao Jerold Chun Peter V. Kharchenko Sten Linnarsson Kun Zhang |
| author_facet |
Blue B. Lake Simone Codeluppi Yun C. Yung Derek Gao Jerold Chun Peter V. Kharchenko Sten Linnarsson Kun Zhang |
| author_sort |
Blue B. Lake |
| title |
A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA |
| title_short |
A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA |
| title_full |
A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA |
| title_fullStr |
A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA |
| title_full_unstemmed |
A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA |
| title_sort |
comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear rna |
| publisher |
Nature Portfolio |
| publishDate |
2017 |
| url |
https://doaj.org/article/decb1c554c2c448c9346ed00418f1885 |
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