Single-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation

Nayi Wang; Ji Zheng; Zhuo Chen; Yang Liu; Burak Dura; Minsuk Kwak; Juliana Xavier-Ferrucio; Yi Chien Lu; Miaomiao Zhang; Christine Roden; Jijun Cheng; Diane S. Krause; Ye Ding; Rong Fan; Jun Lu

doi:10.1038/s41467-018-07981-6

Single-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation

Nayi Wang, Ji Zheng, Zhuo Chen, Yang Liu, Burak Dura, Minsuk Kwak, Juliana Xavier-Ferrucio, Yi Chien Lu, Miaomiao Zhang, Christine Roden, Jijun Cheng, Diane S. Krause, Ye Ding, Rong Fan, Jun Lu

Yonsei Advanced Science Institute

Research output: Contribution to journal › Article › peer-review

98 Citations (Scopus)

Abstract

Measuring multiple omics profiles from the same single cell opens up the opportunity to decode molecular regulation that underlies intercellular heterogeneity in development and disease. Here, we present co-sequencing of microRNAs and mRNAs in the same single cell using a half-cell genomics approach. This method demonstrates good robustness (~95% success rate) and reproducibility (R ² = 0.93 for both microRNAs and mRNAs), yielding paired half-cell microRNA and mRNA profiles, which we can independently validate. By linking the level of microRNAs to the expression of predicted target mRNAs across 19 single cells that are phenotypically identical, we observe that the predicted targets are significantly anti-correlated with the variation of abundantly expressed microRNAs. This suggests that microRNA expression variability alone may lead to non-genetic cell-to-cell heterogeneity. Genome-scale analysis of paired microRNA-mRNA co-profiles further allows us to derive and validate regulatory relationships of cellular pathways controlling microRNA expression and intercellular variability.

Original language	English
Article number	95
Journal	Nature communications
Volume	10
Issue number	1
DOIs	https://doi.org/10.1038/s41467-018-07981-6
Publication status	Published - 2019 Dec 1

Bibliographical note

Funding Information:
This work was supported in part by NIH grants R01CA149109 (to J.L.), R01GM116855 (to Y.D. and J.L.), R21CA177393 (to R.F.), U54CA193461 (to R.F.), U54CA209992 (SubProject ID: 7297 to R.F.), Yale Cancer Center Pilot Grant (to R.F.), Sackler Institute Seed Grant (to R.F.), Connecticut RMRF grant 15-RMB-YALE-06 (to J.L.), and National Science Foundation CAREER Award CBET-1351443 (to R.F.). Services provided by the NIDDK-supported Yale Cooperative Center of Excellence in Hematology (U54DK106857) assisted this study.

Publisher Copyright:
© 2019, The Author(s).

All Science Journal Classification (ASJC) codes

Chemistry(all)
Biochemistry, Genetics and Molecular Biology(all)
General
Physics and Astronomy(all)

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10.1038/s41467-018-07981-6

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title = "Single-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation",

abstract = " Measuring multiple omics profiles from the same single cell opens up the opportunity to decode molecular regulation that underlies intercellular heterogeneity in development and disease. Here, we present co-sequencing of microRNAs and mRNAs in the same single cell using a half-cell genomics approach. This method demonstrates good robustness (~95% success rate) and reproducibility (R 2 = 0.93 for both microRNAs and mRNAs), yielding paired half-cell microRNA and mRNA profiles, which we can independently validate. By linking the level of microRNAs to the expression of predicted target mRNAs across 19 single cells that are phenotypically identical, we observe that the predicted targets are significantly anti-correlated with the variation of abundantly expressed microRNAs. This suggests that microRNA expression variability alone may lead to non-genetic cell-to-cell heterogeneity. Genome-scale analysis of paired microRNA-mRNA co-profiles further allows us to derive and validate regulatory relationships of cellular pathways controlling microRNA expression and intercellular variability.",

author = "Nayi Wang and Ji Zheng and Zhuo Chen and Yang Liu and Burak Dura and Minsuk Kwak and Juliana Xavier-Ferrucio and Lu, {Yi Chien} and Miaomiao Zhang and Christine Roden and Jijun Cheng and Krause, {Diane S.} and Ye Ding and Rong Fan and Jun Lu",

note = "Funding Information: This work was supported in part by NIH grants R01CA149109 (to J.L.), R01GM116855 (to Y.D. and J.L.), R21CA177393 (to R.F.), U54CA193461 (to R.F.), U54CA209992 (SubProject ID: 7297 to R.F.), Yale Cancer Center Pilot Grant (to R.F.), Sackler Institute Seed Grant (to R.F.), Connecticut RMRF grant 15-RMB-YALE-06 (to J.L.), and National Science Foundation CAREER Award CBET-1351443 (to R.F.). Services provided by the NIDDK-supported Yale Cooperative Center of Excellence in Hematology (U54DK106857) assisted this study. Publisher Copyright: {\textcopyright} 2019, The Author(s).",

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AU - Wang, Nayi

AU - Zheng, Ji

AU - Chen, Zhuo

AU - Liu, Yang

AU - Dura, Burak

AU - Kwak, Minsuk

AU - Xavier-Ferrucio, Juliana

AU - Lu, Yi Chien

AU - Zhang, Miaomiao

AU - Roden, Christine

AU - Cheng, Jijun

AU - Krause, Diane S.

AU - Ding, Ye

AU - Fan, Rong

AU - Lu, Jun

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PY - 2019/12/1

Y1 - 2019/12/1

N2 - Measuring multiple omics profiles from the same single cell opens up the opportunity to decode molecular regulation that underlies intercellular heterogeneity in development and disease. Here, we present co-sequencing of microRNAs and mRNAs in the same single cell using a half-cell genomics approach. This method demonstrates good robustness (~95% success rate) and reproducibility (R 2 = 0.93 for both microRNAs and mRNAs), yielding paired half-cell microRNA and mRNA profiles, which we can independently validate. By linking the level of microRNAs to the expression of predicted target mRNAs across 19 single cells that are phenotypically identical, we observe that the predicted targets are significantly anti-correlated with the variation of abundantly expressed microRNAs. This suggests that microRNA expression variability alone may lead to non-genetic cell-to-cell heterogeneity. Genome-scale analysis of paired microRNA-mRNA co-profiles further allows us to derive and validate regulatory relationships of cellular pathways controlling microRNA expression and intercellular variability.

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Single-cell microRNA-mRNA co-sequencing reveals non-genetic heterogeneity and mechanisms of microRNA regulation

Abstract

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