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Literature DB >> 22871714

Transcriptome sequencing of single cells with Smart-Seq.

Jillian J Goetz, Jeffrey M Trimarchi.

Abstract

Mesh：

Substances：
RNA, Messenger

Year: 2012 PMID： 22871714 DOI： 10.1038/nbt.2325

Source DB: PubMed Journal: Nat Biotechnol ISSN： 1087-0156 Impact factor: 54.908

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10 in total

1. Single-cell transcriptional analysis of neuronal progenitors.

Authors: Ian Tietjen; Jason M Rihel; Yanxiang Cao; Georgy Koentges; Lisa Zakhary; Catherine Dulac
Journal: Neuron Date: 2003-04-24 Impact factor: 17.173

2. Single-cell transcript analysis of pancreas development.

Authors: Ming-Ko Chiang; Douglas A Melton
Journal: Dev Cell Date: 2003-03 Impact factor: 12.270

3. Analysis of gene expression in single live neurons.

Authors: J Eberwine; H Yeh; K Miyashiro; Y Cao; S Nair; R Finnell; M Zettel; P Coleman
Journal: Proc Natl Acad Sci U S A Date: 1992-04-01 Impact factor: 11.205

4. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.

Authors: Saiful Islam; Una Kjällquist; Annalena Moliner; Pawel Zajac; Jian-Bing Fan; Peter Lönnerberg; Sten Linnarsson
Journal: Genome Res Date: 2011-05-04 Impact factor: 9.043

5. mRNA-Seq whole-transcriptome analysis of a single cell.

Authors: Fuchou Tang; Catalin Barbacioru; Yangzhou Wang; Ellen Nordman; Clarence Lee; Nanlan Xu; Xiaohui Wang; John Bodeau; Brian B Tuch; Asim Siddiqui; Kaiqin Lao; M Azim Surani
Journal: Nat Methods Date: 2009-04-06 Impact factor: 28.547

Review 6. RNA-Seq: a revolutionary tool for transcriptomics.

Authors: Zhong Wang; Mark Gerstein; Michael Snyder
Journal: Nat Rev Genet Date: 2009-01 Impact factor: 53.242

7. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.

Authors: Daniel Ramsköld; Shujun Luo; Yu-Chieh Wang; Robin Li; Qiaolin Deng; Omid R Faridani; Gregory A Daniels; Irina Khrebtukova; Jeanne F Loring; Louise C Laurent; Gary P Schroth; Rickard Sandberg
Journal: Nat Biotechnol Date: 2012-08 Impact factor: 54.908

8. Single-cell dissection of transcriptional heterogeneity in human colon tumors.

Authors: Piero Dalerba; Tomer Kalisky; Debashis Sahoo; Pradeep S Rajendran; Michael E Rothenberg; Anne A Leyrat; Sopheak Sim; Jennifer Okamoto; Darius M Johnston; Dalong Qian; Maider Zabala; Janet Bueno; Norma F Neff; Jianbin Wang; Andrew A Shelton; Brendan Visser; Shigeo Hisamori; Yohei Shimono; Marc van de Wetering; Hans Clevers; Michael F Clarke; Stephen R Quake
Journal: Nat Biotechnol Date: 2011-11-13 Impact factor: 54.908

9. Evidence for diversity in transcriptional profiles of single hematopoietic stem cells.

Authors: Carlos A Ramos; Teresa A Bowman; Nathan C Boles; Akil A Merchant; Yayun Zheng; Irma Parra; Suzanne A W Fuqua; Chad A Shaw; Margaret A Goodell
Journal: PLoS Genet Date: 2006-08-09 Impact factor: 5.917

10. Individual retinal progenitor cells display extensive heterogeneity of gene expression.

Authors: Jeffrey M Trimarchi; Michael B Stadler; Constance L Cepko
Journal: PLoS One Date: 2008-02-13 Impact factor: 3.240

10 in total

25 in total

Transcriptome sequencing of single cells with Smart-Seq.

1. Single-cell transcriptional analysis of neuronal progenitors.

2. Single-cell transcript analysis of pancreas development.

3. Analysis of gene expression in single live neurons.

4. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq.

5. mRNA-Seq whole-transcriptome analysis of a single cell.

Review 6. RNA-Seq: a revolutionary tool for transcriptomics.

7. Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells.

8. Single-cell dissection of transcriptional heterogeneity in human colon tumors.

9. Evidence for diversity in transcriptional profiles of single hematopoietic stem cells.

10. Individual retinal progenitor cells display extensive heterogeneity of gene expression.

1. Image-based transcriptomics in thousands of single human cells at single-molecule resolution.

Review 2. Functional genomics of stromal cells in chronic inflammatory diseases.

3. Single-cell transcriptome analysis of endometrial tissue.

4. Suppression of artifacts and barcode bias in high-throughput transcriptome analyses utilizing template switching.

5. Combined ultra-low input mRNA and whole-genome sequencing of human embryonic stem cells.

Review 6. DNA sequencing methods in human genetics and disease research.

Review 7. Seeing is believing: new methods for in situ single-cell transcriptomics.

Review 8. Single-Cell Sequencing Technology in Oncology: Applications for Clinical Therapies and Research.

9. Genome sequencing of a single tardigrade Hypsibius dujardini individual.

Review 10. Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level.