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Nat Commun. 2019 Jan 9;10(1):95. doi: 10.1038/s41467-018-07981-6.

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

Wang N1,2,3, Zheng J2,3,4, Chen Z1,2,3, Liu Y2,3, Dura B1, Kwak M1, Xavier-Ferrucio J3,5, Lu YC3,5, Zhang M2,4,6, Roden C2,3, Cheng J2,3, Krause DS3,5, Ding Y7, Fan R8,9, Lu J10,11,12,13.

Author information

1
Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA.
2
Department of Genetics, Yale University School of Medicine, New Haven, CT, 06510, USA.
3
Yale Stem Cell Center, Yale Cancer Center, New Haven, CT, 06520, USA.
4
Department of Urology, Southwest Hospital, Third Military Medical University, 400038, Chongqing, China.
5
Department of Laboratory Medicine, Yale University School of Medicine, New Haven, CT, 06510, USA.
6
School of Medicine, Jiangsu University, 212013, Zhenjiang, Jiangsu, China.
7
Wadworth Center, New York State Department of Health, Albany, NY, 12208, USA.
8
Department of Biomedical Engineering, Yale University, New Haven, CT, 06520, USA. rong.fan@yale.edu.
9
Yale Stem Cell Center, Yale Cancer Center, New Haven, CT, 06520, USA. rong.fan@yale.edu.
10
Department of Genetics, Yale University School of Medicine, New Haven, CT, 06510, USA. jun.lu@yale.edu.
11
Yale Stem Cell Center, Yale Cancer Center, New Haven, CT, 06520, USA. jun.lu@yale.edu.
12
Yale Center for RNA Science and Medicine, New Haven, CT, 06520, USA. jun.lu@yale.edu.
13
Yale Cooperative Center of Excellence in Hematology, New Haven, CT, 06520, USA. jun.lu@yale.edu.

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 (R2 = 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.

PMID:
30626865
PMCID:
PMC6327095
DOI:
10.1038/s41467-018-07981-6
[Indexed for MEDLINE]
Free PMC Article

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