Literature DB >> 23267071

Two methods for full-length RNA sequencing for low quantities of cells and single cells.

Xinghua Pan1, Russell E Durrett, Haiying Zhu, Yoshiaki Tanaka, Yumei Li, Xiaoyuan Zi, Sadie L Marjani, Ghia Euskirchen, Chao Ma, Robert H Lamotte, In-Hyun Park, Michael P Snyder, Christopher E Mason, Sherman M Weissman.   

Abstract

The ability to determine the gene expression pattern in low quantities of cells or single cells is important for resolving a variety of problems in many biological disciplines. A robust description of the expression signature of a single cell requires determination of the full-length sequence of the expressed mRNAs in the cell, yet existing methods have either 3' biased or variable transcript representation. Here, we report our protocols for the amplification and high-throughput sequencing of very small amounts of RNA for sequencing using procedures of either semirandom primed PCR or phi29 DNA polymerase-based DNA amplification, for the cDNA generated with oligo-dT and/or random oligonucleotide primers. Unlike existing methods, these protocols produce relatively uniformly distributed sequences covering the full length of almost all transcripts independent of their sizes, from 1,000 to 10 cells, and even with single cells. Both protocols produced satisfactory detection/coverage of the abundant mRNAs from a single K562 erythroleukemic cell or a single dorsal root ganglion neuron. The phi29-based method produces long products with less noise, uses an isothermal reaction, and is simple to practice. The semirandom primed PCR procedure is more sensitive and reproducible at low transcript levels or with low quantities of cells. These methods provide tools for mRNA sequencing or RNA sequencing when only low quantities of cells, a single cell, or even degraded RNA are available for profiling.

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Year:  2012        PMID: 23267071      PMCID: PMC3545756          DOI: 10.1073/pnas.1217322109

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  46 in total

1.  Preparation and analysis of cDNA from a small number of hematopoietic cells.

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Journal:  Methods Enzymol       Date:  1999       Impact factor: 1.600

2.  A procedure for highly specific, sensitive, and unbiased whole-genome amplification.

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Journal:  Proc Natl Acad Sci U S A       Date:  2008-10-01       Impact factor: 11.205

3.  Increasing cDNA yields from single-cell quantities of mRNA in standard laboratory reverse transcriptase reactions using acoustic microstreaming.

Authors:  Wah Chin Boon; Karolina Petkovic-Duran; Yonggang Zhu; Richard Manasseh; Malcolm K Horne; Tim D Aumann
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4.  Unamplified cap analysis of gene expression on a single-molecule sequencer.

Authors:  Mutsumi Kanamori-Katayama; Masayoshi Itoh; Hideya Kawaji; Timo Lassmann; Shintaro Katayama; Miki Kojima; Nicolas Bertin; Ai Kaiho; Noriko Ninomiya; Carsten O Daub; Piero Carninci; Alistair R R Forrest; Yoshihide Hayashizaki
Journal:  Genome Res       Date:  2011-05-19       Impact factor: 9.043

5.  CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification.

Authors:  Tamar Hashimshony; Florian Wagner; Noa Sher; Itai Yanai
Journal:  Cell Rep       Date:  2012-08-30       Impact factor: 9.423

6.  Tumour evolution inferred by single-cell sequencing.

Authors:  Nicholas Navin; Jude Kendall; Jennifer Troge; Peter Andrews; Linda Rodgers; Jeanne McIndoo; Kerry Cook; Asya Stepansky; Dan Levy; Diane Esposito; Lakshmi Muthuswamy; Alex Krasnitz; W Richard McCombie; James Hicks; Michael Wigler
Journal:  Nature       Date:  2011-03-13       Impact factor: 49.962

7.  Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals.

Authors:  Mitchell Guttman; Ido Amit; Manuel Garber; Courtney French; Michael F Lin; David Feldser; Maite Huarte; Or Zuk; Bryce W Carey; John P Cassady; Moran N Cabili; Rudolf Jaenisch; Tarjei S Mikkelsen; Tyler Jacks; Nir Hacohen; Bradley E Bernstein; Manolis Kellis; Aviv Regev; John L Rinn; Eric S Lander
Journal:  Nature       Date:  2009-02-01       Impact factor: 49.962

Review 8.  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

9.  Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling.

Authors:  Nicholas T Ingolia; Sina Ghaemmaghami; John R S Newman; Jonathan S Weissman
Journal:  Science       Date:  2009-02-12       Impact factor: 47.728

10.  An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis.

Authors:  Kazuki Kurimoto; Yukihiro Yabuta; Yasuhide Ohinata; Yukiko Ono; Kenichiro D Uno; Rikuhiro G Yamada; Hiroki R Ueda; Mitinori Saitou
Journal:  Nucleic Acids Res       Date:  2006-03-17       Impact factor: 16.971

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  64 in total

Review 1.  Single-cell analysis of the transcriptome and its application in the characterization of stem cells and early embryos.

Authors:  Na Liu; Lin Liu; Xinghua Pan
Journal:  Cell Mol Life Sci       Date:  2014-03-21       Impact factor: 9.261

2.  Template-dependent multiple displacement amplification for profiling human circulating RNA.

Authors:  Weihua Wang; Yi Ren; Yang Lu; Yuan Xu; Seth D Crosby; Adrian M Di Bisceglie; Xiaofeng Fan
Journal:  Biotechniques       Date:  2017-07-01       Impact factor: 1.993

3.  Single-Cell Sequencing and Organoids: A Powerful Combination for Modelling Organ Development and Diseases.

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Journal:  Rev Physiol Biochem Pharmacol       Date:  2021       Impact factor: 5.545

4.  Immune Escape in Breast Cancer During In Situ to Invasive Carcinoma Transition.

Authors:  Carlos R Gil Del Alcazar; Sung Jin Huh; Muhammad B Ekram; Anne Trinh; Lin L Liu; Francisco Beca; Xiaoyuan Zi; Minsuk Kwak; Helga Bergholtz; Ying Su; Lina Ding; Hege G Russnes; Andrea L Richardson; Kirsten Babski; Elizabeth Min Hui Kim; Charles H McDonnell; Jon Wagner; Ron Rowberry; Gordon J Freeman; Deborah Dillon; Therese Sorlie; Lisa M Coussens; Judy E Garber; Rong Fan; Kristie Bobolis; D Craig Allred; Joon Jeong; So Yeon Park; Franziska Michor; Kornelia Polyak
Journal:  Cancer Discov       Date:  2017-06-26       Impact factor: 39.397

Review 5.  Understanding development and stem cells using single cell-based analyses of gene expression.

Authors:  Pavithra Kumar; Yuqi Tan; Patrick Cahan
Journal:  Development       Date:  2017-01-01       Impact factor: 6.868

Review 6.  Emergent Properties of Microbial Activity in Heterogeneous Soil Microenvironments: Different Research Approaches Are Slowly Converging, Yet Major Challenges Remain.

Authors:  Philippe C Baveye; Wilfred Otten; Alexandra Kravchenko; María Balseiro-Romero; Éléonore Beckers; Maha Chalhoub; Christophe Darnault; Thilo Eickhorst; Patricia Garnier; Simona Hapca; Serkan Kiranyaz; Olivier Monga; Carsten W Mueller; Naoise Nunan; Valérie Pot; Steffen Schlüter; Hannes Schmidt; Hans-Jörg Vogel
Journal:  Front Microbiol       Date:  2018-08-27       Impact factor: 5.640

7.  Geostatistical visualization of ecological interactions in tumors.

Authors:  Hunter Bryan Boyce; Parag Mallick
Journal:  Proceedings (IEEE Int Conf Bioinformatics Biomed)       Date:  2020-02-06

Review 8.  Library construction for next-generation sequencing: overviews and challenges.

Authors:  Steven R Head; H Kiyomi Komori; Sarah A LaMere; Thomas Whisenant; Filip Van Nieuwerburgh; Daniel R Salomon; Phillip Ordoukhanian
Journal:  Biotechniques       Date:  2014-02-01       Impact factor: 1.993

9.  Profiling individual human embryonic stem cells by quantitative rt-PCR.

Authors:  HoTae Lim; In Young Choi; Gabsang Lee
Journal:  J Vis Exp       Date:  2014-05-29       Impact factor: 1.355

10.  Microfluidic single-cell whole-transcriptome sequencing.

Authors:  Aaron M Streets; Xiannian Zhang; Chen Cao; Yuhong Pang; Xinglong Wu; Liang Xiong; Lu Yang; Yusi Fu; Liang Zhao; Fuchou Tang; Yanyi Huang
Journal:  Proc Natl Acad Sci U S A       Date:  2014-04-29       Impact factor: 11.205

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