Rainbow-Seq: Combining Cell Lineage Tracing with Single-Cell RNA Sequencing in Preimplantation Embryos
We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and rea...
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| Published in | iScience Vol. 7; pp. 16 - 29 |
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| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
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Elsevier
28.09.2018
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| Abstract | We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and read single-cell transcriptomes. We triggered lineage tracking in each blastomere at the 2-cell stage, observed microscopically inequivalent contributions of the progeny to the two embryonic poles at the blastocyst stage, and analyzed every single cell at either 4- or 8-cell stage with deep paired-end sequencing of full-length transcripts. Although lineage difference was not marked unequivocally at a single-gene level, it became clear when the transcriptome was analyzed as a whole. Moreover, several groups of novel transcript isoforms with embedded repeat sequences exhibited lineage difference, suggesting a possible link between DNA demethylation and cell fate decision. Rainbow-seq bridged a critical gap between division history and single-cell RNA-seq assays. |
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| AbstractList | We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and read single-cell transcriptomes. We triggered lineage tracking in each blastomere at the 2-cell stage, observed microscopically inequivalent contributions of the progeny to the two embryonic poles at the blastocyst stage, and analyzed every single cell at either 4- or 8-cell stage with deep paired-end sequencing of full-length transcripts. Although lineage difference was not marked unequivocally at a single-gene level, it became clear when the transcriptome was analyzed as a whole. Moreover, several groups of novel transcript isoforms with embedded repeat sequences exhibited lineage difference, suggesting a possible link between DNA demethylation and cell fate decision. Rainbow-seq bridged a critical gap between division history and single-cell RNA-seq assays.
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Rainbow-seq traces cell division history and reveals single-cell transcriptomes
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A single gene does not exhibit unequivocal lineage difference at 4- and 8-cell stages
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Lineage difference becomes clear when the transcriptome is analyzed as a whole
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Novel RNA isoforms with embedded repeat sequences exhibit lineage difference
Preimplantation, Cell fate, Single cell, Lineage tracing, Transposon We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and read single-cell transcriptomes. We triggered lineage tracking in each blastomere at the 2-cell stage, observed microscopically inequivalent contributions of the progeny to the two embryonic poles at the blastocyst stage, and analyzed every single cell at either 4- or 8-cell stage with deep paired-end sequencing of full-length transcripts. Although lineage difference was not marked unequivocally at a single-gene level, it became clear when the transcriptome was analyzed as a whole. Moreover, several groups of novel transcript isoforms with embedded repeat sequences exhibited lineage difference, suggesting a possible link between DNA demethylation and cell fate decision. Rainbow-seq bridged a critical gap between division history and single-cell RNA-seq assays. : Preimplantation, Cell fate, Single cell, Lineage tracing, Transposon Subject Areas: Preimplantation, Cell fate, Single cell, Lineage tracing, Transposon We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and read single-cell transcriptomes. We triggered lineage tracking in each blastomere at the 2-cell stage, observed microscopically inequivalent contributions of the progeny to the two embryonic poles at the blastocyst stage, and analyzed every single cell at either 4- or 8-cell stage with deep paired-end sequencing of full-length transcripts. Although lineage difference was not marked unequivocally at a single-gene level, it became clear when the transcriptome was analyzed as a whole. Moreover, several groups of novel transcript isoforms with embedded repeat sequences exhibited lineage difference, suggesting a possible link between DNA demethylation and cell fate decision. Rainbow-seq bridged a critical gap between division history and single-cell RNA-seq assays.We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and read single-cell transcriptomes. We triggered lineage tracking in each blastomere at the 2-cell stage, observed microscopically inequivalent contributions of the progeny to the two embryonic poles at the blastocyst stage, and analyzed every single cell at either 4- or 8-cell stage with deep paired-end sequencing of full-length transcripts. Although lineage difference was not marked unequivocally at a single-gene level, it became clear when the transcriptome was analyzed as a whole. Moreover, several groups of novel transcript isoforms with embedded repeat sequences exhibited lineage difference, suggesting a possible link between DNA demethylation and cell fate decision. Rainbow-seq bridged a critical gap between division history and single-cell RNA-seq assays. We developed the Rainbow-seq technology to trace cell division history and reveal single-cell transcriptomes. With distinct fluorescent protein genes as lineage markers, Rainbow-seq enables each single-cell RNA sequencing (RNA-seq) experiment to simultaneously decode the lineage marker genes and read single-cell transcriptomes. We triggered lineage tracking in each blastomere at the 2-cell stage, observed microscopically inequivalent contributions of the progeny to the two embryonic poles at the blastocyst stage, and analyzed every single cell at either 4- or 8-cell stage with deep paired-end sequencing of full-length transcripts. Although lineage difference was not marked unequivocally at a single-gene level, it became clear when the transcriptome was analyzed as a whole. Moreover, several groups of novel transcript isoforms with embedded repeat sequences exhibited lineage difference, suggesting a possible link between DNA demethylation and cell fate decision. Rainbow-seq bridged a critical gap between division history and single-cell RNA-seq assays. |
| Author | Chen, Zhen Calandrelli, Riccardo Biase, Fernando H. Rivas-Astroza, Marcelo Wu, Qiuyang Zhou, Shuigeng Zhong, Sheng |
| AuthorAffiliation | 4 Department of Diabetes Complications and Metabolism, City of Hope, Duarte, CA 91010, USA 1 Department of Bioengineering, University of California San Diego, San Diego, CA 92130, USA 3 School of Computer Science, Fudan University, Shanghai 200433, China 2 Department of Computer Science and Technology, Tongji University, Shanghai 201804, China |
| AuthorAffiliation_xml | – name: 2 Department of Computer Science and Technology, Tongji University, Shanghai 201804, China – name: 1 Department of Bioengineering, University of California San Diego, San Diego, CA 92130, USA – name: 4 Department of Diabetes Complications and Metabolism, City of Hope, Duarte, CA 91010, USA – name: 3 School of Computer Science, Fudan University, Shanghai 200433, China |
| Author_xml | – sequence: 1 givenname: Fernando H. surname: Biase fullname: Biase, Fernando H. – sequence: 2 givenname: Qiuyang surname: Wu fullname: Wu, Qiuyang – sequence: 3 givenname: Riccardo surname: Calandrelli fullname: Calandrelli, Riccardo – sequence: 4 givenname: Marcelo surname: Rivas-Astroza fullname: Rivas-Astroza, Marcelo – sequence: 5 givenname: Shuigeng surname: Zhou fullname: Zhou, Shuigeng – sequence: 6 givenname: Zhen surname: Chen fullname: Chen, Zhen – sequence: 7 givenname: Sheng orcidid: 0000-0001-6419-7453 surname: Zhong fullname: Zhong, Sheng |
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| Keywords | Single cell Preimplantation Cell fate Lineage tracing Transposon |
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