Literature DB >> 21045080

Gene expression profiling of human breast tissue samples using SAGE-Seq.

Zhenhua Jeremy Wu1, Clifford A Meyer, Sibgat Choudhury, Michail Shipitsin, Reo Maruyama, Marina Bessarabova, Tatiana Nikolskaya, Saraswati Sukumar, Armin Schwartzman, Jun S Liu, Kornelia Polyak, X Shirley Liu.   

Abstract

We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein-coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.

Entities:  

Mesh:

Year:  2010        PMID: 21045080      PMCID: PMC2989999          DOI: 10.1101/gr.108217.110

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  31 in total

1.  Differential expression in SAGE: accounting for normal between-library variation.

Authors:  Keith A Baggerly; Li Deng; Jeffrey S Morris; C Marcelo Aldaz
Journal:  Bioinformatics       Date:  2003-08-12       Impact factor: 6.937

Review 2.  Design issues for cDNA microarray experiments.

Authors:  Yee Hwa Yang; Terry Speed
Journal:  Nat Rev Genet       Date:  2002-08       Impact factor: 53.242

Review 3.  Overexpression of G protein-coupled receptors in cancer cells: involvement in tumor progression.

Authors:  Shuyu Li; Shuguang Huang; Sheng-Bin Peng
Journal:  Int J Oncol       Date:  2005-11       Impact factor: 5.650

4.  Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

Authors:  M Schena; D Shalon; R W Davis; P O Brown
Journal:  Science       Date:  1995-10-20       Impact factor: 47.728

Review 5.  Gene discovery using the serial analysis of gene expression technique: implications for cancer research.

Authors:  K Polyak; G J Riggins
Journal:  J Clin Oncol       Date:  2001-06-01       Impact factor: 44.544

6.  Next-generation tag sequencing for cancer gene expression profiling.

Authors:  A Sorana Morrissy; Ryan D Morin; Allen Delaney; Thomas Zeng; Helen McDonald; Steven Jones; Yongjun Zhao; Martin Hirst; Marco A Marra
Journal:  Genome Res       Date:  2009-06-18       Impact factor: 9.043

7.  Genome-wide mapping of in vivo protein-DNA interactions.

Authors:  David S Johnson; Ali Mortazavi; Richard M Myers; Barbara Wold
Journal:  Science       Date:  2007-05-31       Impact factor: 47.728

8.  Identifying differential expression in multiple SAGE libraries: an overdispersed log-linear model approach.

Authors:  Jun Lu; John K Tomfohr; Thomas B Kepler
Journal:  BMC Bioinformatics       Date:  2005-06-29       Impact factor: 3.169

9.  Overdispersed logistic regression for SAGE: modelling multiple groups and covariates.

Authors:  Keith A Baggerly; Li Deng; Jeffrey S Morris; C Marcelo Aldaz
Journal:  BMC Bioinformatics       Date:  2004-10-06       Impact factor: 3.169

10.  Design and analysis of ChIP-seq experiments for DNA-binding proteins.

Authors:  Peter V Kharchenko; Michael Y Tolstorukov; Peter J Park
Journal:  Nat Biotechnol       Date:  2008-11-16       Impact factor: 54.908

View more
  25 in total

1.  Altered antisense-to-sense transcript ratios in breast cancer.

Authors:  Reo Maruyama; Michail Shipitsin; Sibgat Choudhury; Zhenhua Wu; Alexei Protopopov; Jun Yao; Pang-Kuo Lo; Marina Bessarabova; Alex Ishkin; Yuri Nikolsky; X Shirley Liu; Saraswati Sukumar; Kornelia Polyak
Journal:  Proc Natl Acad Sci U S A       Date:  2010-11-22       Impact factor: 11.205

2.  Deconvoluting complex tissues for expression quantitative trait locus-based analyses.

Authors:  Ji-Heui Seo; Qiyuan Li; Aquila Fatima; Aron Eklund; Zoltan Szallasi; Kornelia Polyak; Andrea L Richardson; Matthew L Freedman
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-05-06       Impact factor: 6.237

Review 3.  Minireview: applications of next-generation sequencing on studies of nuclear receptor regulation and function.

Authors:  Clifford A Meyer; Qianzi Tang; X Shirley Liu
Journal:  Mol Endocrinol       Date:  2012-08-28

4.  KDM5 Histone Demethylase Activity Links Cellular Transcriptomic Heterogeneity to Therapeutic Resistance.

Authors:  Kunihiko Hinohara; Hua-Jun Wu; Sébastien Vigneau; Thomas O McDonald; Kyomi J Igarashi; Kimiyo N Yamamoto; Thomas Madsen; Anne Fassl; Shawn B Egri; Malvina Papanastasiou; Lina Ding; Guillermo Peluffo; Ofir Cohen; Stephen C Kales; Madhu Lal-Nag; Ganesha Rai; David J Maloney; Ajit Jadhav; Anton Simeonov; Nikhil Wagle; Myles Brown; Alexander Meissner; Piotr Sicinski; Jacob D Jaffe; Rinath Jeselsohn; Alexander A Gimelbrant; Franziska Michor; Kornelia Polyak
Journal:  Cancer Cell       Date:  2018-11-21       Impact factor: 31.743

5.  Digital gene expression for non-model organisms.

Authors:  Lewis Z Hong; Jun Li; Anne Schmidt-Küntzel; Wesley C Warren; Gregory S Barsh
Journal:  Genome Res       Date:  2011-08-15       Impact factor: 9.043

6.  Analysis of HIV-1 expression level and sense of transcription by high-throughput sequencing of the infected cell.

Authors:  Gregory Lefebvre; Sébastien Desfarges; Frédéric Uyttebroeck; Miguel Muñoz; Niko Beerenwinkel; Jacques Rougemont; Amalio Telenti; Angela Ciuffi
Journal:  J Virol       Date:  2011-04-20       Impact factor: 5.103

7.  Molecular profiling of human mammary gland links breast cancer risk to a p27(+) cell population with progenitor characteristics.

Authors:  Sibgat Choudhury; Vanessa Almendro; Vanessa F Merino; Zhenhua Wu; Reo Maruyama; Ying Su; Filipe C Martins; Mary Jo Fackler; Marina Bessarabova; Adam Kowalczyk; Thomas Conway; Bryan Beresford-Smith; Geoff Macintyre; Yu-Kang Cheng; Zoila Lopez-Bujanda; Antony Kaspi; Rong Hu; Judith Robens; Tatiana Nikolskaya; Vilde D Haakensen; Stuart J Schnitt; Pedram Argani; Gabrielle Ethington; Laura Panos; Michael Grant; Jason Clark; William Herlihy; S Joyce Lin; Grace Chew; Erik W Thompson; April Greene-Colozzi; Andrea L Richardson; Gedge D Rosson; Malcolm Pike; Judy E Garber; Yuri Nikolsky; Joanne L Blum; Alfred Au; E Shelley Hwang; Rulla M Tamimi; Franziska Michor; Izhak Haviv; X Shirley Liu; Saraswati Sukumar; Kornelia Polyak
Journal:  Cell Stem Cell       Date:  2013-06-13       Impact factor: 24.633

8.  Spatial Proximity to Fibroblasts Impacts Molecular Features and Therapeutic Sensitivity of Breast Cancer Cells Influencing Clinical Outcomes.

Authors:  Andriy Marusyk; Doris P Tabassum; Michalina Janiszewska; Andrew E Place; Anne Trinh; Andrii I Rozhok; Saumyadipta Pyne; Jennifer L Guerriero; Shaokun Shu; Muhammad Ekram; Alexander Ishkin; Daniel P Cahill; Yuri Nikolsky; Timothy A Chan; Mothaffar F Rimawi; Susan Hilsenbeck; Rachel Schiff; Kent C Osborne; Antony Letai; Kornelia Polyak
Journal:  Cancer Res       Date:  2016-09-26       Impact factor: 12.701

9.  Transcriptome analysis of the Bombyx mori fat body after constant high temperature treatment shows differences between the sexes.

Authors:  Hua Wang; Yan Fang; Lipeng Wang; Wenjuan Zhu; Haipeng Ji; Haiying Wang; Shiqing Xu; Yanghu Sima
Journal:  Mol Biol Rep       Date:  2014-06-28       Impact factor: 2.316

10.  CRISPRcloud: a secure cloud-based pipeline for CRISPR pooled screen deconvolution.

Authors:  Hyun-Hwan Jeong; Seon Young Kim; Maxime W C Rousseaux; Huda Y Zoghbi; Zhandong Liu
Journal:  Bioinformatics       Date:  2017-09-15       Impact factor: 6.937

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.