Literature DB >> 18629150

A comparison of global gene expression measurement technologies in Arabidopsis thaliana.

Sean J Coughlan1, Vikas Agrawal, Blake Meyers.   

Abstract

Microarrays and tag-based transcriptional profiling technologies represent diverse but complementary data types. We are currently conducting a comparison of high-density in situ synthesized microarrays and massively-parallel signature sequencing (MPSS) data in the model plant, Arabidopsis thaliana. The MPSS data (available at http://mpss.udel.edu/at) and the microarray data have been compiled using the same RNA source material. In this review, we outline the experimental strategy that we are using, and present preliminary data and interpretations from the transcriptional profiles of Arabidopsis leaves and roots. The preliminary data indicate that the log ratio differences of transcripts between leaves and roots measured by microarray data are in better agreement with the MPSS data than the absolute intensities measured for individual microarrays hybridized to only one of the cRNA populations. The correlation was substantially improved by focusing on a subset of genes excluding those with very low expression levels; this selection may have removed noisy data. Future reports will incorporate more than 10 tissues that have been sampled by MPSS.

Entities:  

Year:  2004        PMID: 18629150      PMCID: PMC2447440          DOI: 10.1002/cfg.397

Source DB:  PubMed          Journal:  Comp Funct Genomics        ISSN: 1531-6912


  17 in total

1.  Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays.

Authors:  S Brenner; M Johnson; J Bridgham; G Golda; D H Lloyd; D Johnson; S Luo; S McCurdy; M Foy; M Ewan; R Roth; D George; S Eletr; G Albrecht; E Vermaas; S R Williams; K Moon; T Burcham; M Pallas; R B DuBridge; J Kirchner; K Fearon; J Mao; K Corcoran
Journal:  Nat Biotechnol       Date:  2000-06       Impact factor: 54.908

2.  Experimental annotation of the human genome using microarray technology.

Authors:  D D Shoemaker; E E Schadt; C D Armour; Y D He; P Garrett-Engele; P D McDonagh; P M Loerch; A Leonardson; P Y Lum; G Cavet; L F Wu; S J Altschuler; S Edwards; J King; J S Tsang; G Schimmack; J M Schelter; J Koch; M Ziman; M J Marton; B Li; P Cundiff; T Ward; J Castle; M Krolewski; M R Meyer; M Mao; J Burchard; M J Kidd; H Dai; J W Phillips; P S Linsley; R Stoughton; S Scherer; M S Boguski
Journal:  Nature       Date:  2001-02-15       Impact factor: 49.962

3.  Arabidopsis microarray service facilities.

Authors:  E Wisman; J Ohlrogge
Journal:  Plant Physiol       Date:  2000-12       Impact factor: 8.340

4.  Large-scale profiling of the Arabidopsis transcriptome.

Authors:  T Zhu; X Wang
Journal:  Plant Physiol       Date:  2000-12       Impact factor: 8.340

5.  Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations.

Authors:  M L Lee; F C Kuo; G A Whitmore; J Sklar
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-29       Impact factor: 11.205

6.  The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster.

Authors:  W Jin; R M Riley; R D Wolfinger; K P White; G Passador-Gurgel; G Gibson
Journal:  Nat Genet       Date:  2001-12       Impact factor: 38.330

7.  Analysis of the genome sequence of the flowering plant Arabidopsis thaliana.

Authors: 
Journal:  Nature       Date:  2000-12-14       Impact factor: 49.962

8.  Direct comparison of GeneChip and SAGE on the quantitative accuracy in transcript profiling analysis.

Authors:  M Ishii; S Hashimoto; S Tsutsumi; Y Wada; K Matsushima; T Kodama; H Aburatani
Journal:  Genomics       Date:  2000-09-01       Impact factor: 5.736

9.  Analysis of matched mRNA measurements from two different microarray technologies.

Authors:  Winston Patrick Kuo; Tor-Kristian Jenssen; Atul J Butte; Lucila Ohno-Machado; Isaac S Kohane
Journal:  Bioinformatics       Date:  2002-03       Impact factor: 6.937

10.  Expression profiling using microarrays fabricated by an ink-jet oligonucleotide synthesizer.

Authors:  T R Hughes; M Mao; A R Jones; J Burchard; M J Marton; K W Shannon; S M Lefkowitz; M Ziman; J M Schelter; M R Meyer; S Kobayashi; C Davis; H Dai; Y D He; S B Stephaniants; G Cavet; W L Walker; A West; E Coffey; D D Shoemaker; R Stoughton; A P Blanchard; S H Friend; P S Linsley
Journal:  Nat Biotechnol       Date:  2001-04       Impact factor: 54.908

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  11 in total

1.  Comparison of transcript profiling on Arabidopsis microarray platform technologies.

Authors:  Jeffrey D Pylatuik; Pierre R Fobert
Journal:  Plant Mol Biol       Date:  2005-07       Impact factor: 4.076

2.  A comparative analysis of transcript abundance using SAGE and Affymetrix arrays.

Authors:  Adel F M Ibrahim; Peter E Hedley; Linda Cardle; Warren Kruger; David F Marshall; Gary J Muehlbauer; Robbie Waugh
Journal:  Funct Integr Genomics       Date:  2005-02-16       Impact factor: 3.410

3.  Quantitative miRNA expression analysis: comparing microarrays with next-generation sequencing.

Authors:  Hanni Willenbrock; Jesper Salomon; Rolf Søkilde; Kim Bundvig Barken; Thomas Nøhr Hansen; Finn Cilius Nielsen; Søren Møller; Thomas Litman
Journal:  RNA       Date:  2009-09-10       Impact factor: 4.942

4.  Experimental design, preprocessing, normalization and differential expression analysis of small RNA sequencing experiments.

Authors:  Kevin P McCormick; Matthew R Willmann; Blake C Meyers
Journal:  Silence       Date:  2011-02-28

5.  RL-SAGE and microarray analysis of the rice transcriptome after Rhizoctonia solani infection.

Authors:  R C Venu; Yulin Jia; Malali Gowda; Melissa H Jia; Chatchawan Jantasuriyarat; Eric Stahlberg; Huameng Li; Andrew Rhineheart; Prashanth Boddhireddy; Pratibha Singh; Neil Rutger; David Kudrna; Rod Wing; James C Nelson; Guo-Liang Wang
Journal:  Mol Genet Genomics       Date:  2007-06-20       Impact factor: 3.291

6.  In silico evaluation of predicted regulatory interactions in Arabidopsis thaliana.

Authors:  Damion Nero; Manpreet S Katari; Jonathan Kelfer; Daniel Tranchina; Gloria M Coruzzi
Journal:  BMC Bioinformatics       Date:  2009-12-21       Impact factor: 3.169

7.  Deep and comparative analysis of the mycelium and appressorium transcriptomes of Magnaporthe grisea using MPSS, RL-SAGE, and oligoarray methods.

Authors:  Malali Gowda; R C Venu; Mohan B Raghupathy; Kan Nobuta; Huameng Li; Rod Wing; Eric Stahlberg; Sean Couglan; Christian D Haudenschild; Ralph Dean; Baek-Hie Nahm; Blake C Meyers; Guo-Liang Wang
Journal:  BMC Genomics       Date:  2006-12-08       Impact factor: 3.969

8.  A comparison of microarray and MPSS technology platforms for expression analysis of Arabidopsis.

Authors:  Junfeng Chen; Vikas Agrawal; Magnus Rattray; Marilyn A L West; Dina A St Clair; Richard W Michelmore; Sean J Coughlan; Blake C Meyers
Journal:  BMC Genomics       Date:  2007-11-12       Impact factor: 3.969

9.  Mechanical stress induces biotic and abiotic stress responses via a novel cis-element.

Authors:  Justin W Walley; Sean Coughlan; Matthew E Hudson; Michael F Covington; Roy Kaspi; Gopalan Banu; Stacey L Harmer; Katayoon Dehesh
Journal:  PLoS Genet       Date:  2007-08-24       Impact factor: 5.917

10.  A spatial dissection of the Arabidopsis floral transcriptome by MPSS.

Authors:  Jason A Peiffer; Shail Kaushik; Hajime Sakai; Mario Arteaga-Vazquez; Nidia Sanchez-Leon; Hassan Ghazal; Jean-Philippe Vielle-Calzada; Blake C Meyers
Journal:  BMC Plant Biol       Date:  2008-04-21       Impact factor: 4.215

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