Literature DB >> 21317363

Human transcriptome array for high-throughput clinical studies.

Weihong Xu1, Junhee Seok, Michael N Mindrinos, Anthony C Schweitzer, Hui Jiang, Julie Wilhelmy, Tyson A Clark, Karen Kapur, Yi Xing, Malek Faham, John D Storey, Lyle L Moldawer, Ronald V Maier, Ronald G Tompkins, Wing Hung Wong, Ronald W Davis, Wenzhong Xiao.   

Abstract

A 6.9 million-feature oligonucleotide array of the human transcriptome [Glue Grant human transcriptome (GG-H array)] has been developed for high-throughput and cost-effective analyses in clinical studies. This array allows comprehensive examination of gene expression and genome-wide identification of alternative splicing as well as detection of coding SNPs and noncoding transcripts. The performance of the array was examined and compared with mRNA sequencing (RNA-Seq) results over multiple independent replicates of liver and muscle samples. Compared with RNA-Seq of 46 million uniquely mappable reads per replicate, the GG-H array is highly reproducible in estimating gene and exon abundance. Although both platforms detect similar expression changes at the gene level, the GG-H array is more sensitive at the exon level. Deeper sequencing is required to adequately cover low-abundance transcripts. The array has been implemented in a multicenter clinical program and has generated high-quality, reproducible data. Considering the clinical trial requirements of cost, sample availability, and throughput, the GG-H array has a wide range of applications. An emerging approach for large-scale clinical genomic studies is to first use RNA-Seq to the sufficient depth for the discovery of transcriptome elements relevant to the disease process followed by high-throughput and reliable screening of these elements on thousands of patient samples using custom-designed arrays.

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Year:  2011        PMID: 21317363      PMCID: PMC3048146          DOI: 10.1073/pnas.1019753108

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


  33 in total

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Authors:  V G Tusher; R Tibshirani; G Chu
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-17       Impact factor: 11.205

Review 2.  Protein diversity from alternative splicing: a challenge for bioinformatics and post-genome biology.

Authors:  D L Black
Journal:  Cell       Date:  2000-10-27       Impact factor: 41.582

3.  Genomewide analysis of mRNA processing in yeast using splicing-specific microarrays.

Authors:  Tyson A Clark; Charles W Sugnet; Manuel Ares
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4.  Summaries of Affymetrix GeneChip probe level data.

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Review 5.  Pre-mRNA splicing and human disease.

Authors:  Nuno André Faustino; Thomas A Cooper
Journal:  Genes Dev       Date:  2003-02-15       Impact factor: 11.361

6.  Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays.

Authors:  Jason M Johnson; John Castle; Philip Garrett-Engele; Zhengyan Kan; Patrick M Loerch; Christopher D Armour; Ralph Santos; Eric E Schadt; Roland Stoughton; Daniel D Shoemaker
Journal:  Science       Date:  2003-12-19       Impact factor: 47.728

Review 7.  Expression profiling--best practices for data generation and interpretation in clinical trials.

Authors: 
Journal:  Nat Rev Genet       Date:  2004-03       Impact factor: 53.242

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Journal:  Nature       Date:  2000-02-03       Impact factor: 49.962

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Journal:  Nature       Date:  2000-08-17       Impact factor: 49.962

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  66 in total

1.  Coding SNPs as intrinsic markers for sample tracking in large-scale transcriptome studies.

Authors:  Weihong Xu; Hong Gao; Junhee Seok; Julie Wilhelmy; Michael N Mindrinos; Ronald W Davis; Wenzhong Xiao
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2.  JETTA: junction and exon toolkits for transcriptome analysis.

Authors:  Junhee Seok; Weihong Xu; Hong Gao; Ronald W Davis; Wenzhong Xiao
Journal:  Bioinformatics       Date:  2012-03-19       Impact factor: 6.937

3.  The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance.

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Journal:  Nat Biotechnol       Date:  2014-08-24       Impact factor: 54.908

4.  Transcriptome profiling of peripheral blood immune cell populations in multiple sclerosis patients before and during treatment with a sphingosine-1-phosphate receptor modulator.

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5.  High-Resolution Expression Profiling of Peripheral Blood CD8+ Cells in Patients with Multiple Sclerosis Displays Fingolimod-Induced Immune Cell Redistribution.

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Journal:  Mol Neurobiol       Date:  2016-09-08       Impact factor: 5.590

6.  Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder.

Authors:  Marquis Philip Vawter; Robert Philibert; Brandi Rollins; Patricia L Ruppel; Terry W Osborn
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7.  A comprehensive time-course-based multicohort analysis of sepsis and sterile inflammation reveals a robust diagnostic gene set.

Authors:  Timothy E Sweeney; Aaditya Shidham; Hector R Wong; Purvesh Khatri
Journal:  Sci Transl Med       Date:  2015-05-13       Impact factor: 17.956

Review 8.  Next-generation sequencing in the clinic: promises and challenges.

Authors:  Jiekun Xuan; Ying Yu; Tao Qing; Lei Guo; Leming Shi
Journal:  Cancer Lett       Date:  2012-11-19       Impact factor: 8.679

9.  The spliceosome factor SART1 exerts its anti-HCV action through mRNA splicing.

Authors:  Wenyu Lin; Chuanlong Zhu; Jian Hong; Lei Zhao; Nikolaus Jilg; Dahlene N Fusco; Esperance A Schaefer; Cynthia Brisac; Xiao Liu; Lee F Peng; Qikai Xu; Raymond T Chung
Journal:  J Hepatol       Date:  2014-12-03       Impact factor: 25.083

10.  Trauma-associated human neutrophil alterations revealed by comparative proteomics profiling.

Authors:  Jian-Ying Zhou; Ravi K Krovvidi; Yuqian Gao; Hong Gao; Brianne O Petritis; Asit K De; Carol L Miller-Graziano; Paul E Bankey; Vladislav A Petyuk; Carrie D Nicora; Therese R Clauss; Ronald J Moore; Tujin Shi; Joseph N Brown; Amit Kaushal; Wenzhong Xiao; Ronald W Davis; Ronald V Maier; Ronald G Tompkins; Wei-Jun Qian; David G Camp; Richard D Smith
Journal:  Proteomics Clin Appl       Date:  2013-05-22       Impact factor: 3.494

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