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Title: Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

Journal Article · · Comparative and Functional Genomics
DOI:https://doi.org/10.1155/2009/950171· OSTI ID:1197681
 [1];  [2];  [3];  [4];  [4];  [5];  [3];  [5]
  1. Department of Independent Surveillance Assessment and Statistics, Sandia National Laboratories, Albuquerque, NM 87185-0829, USA
  2. National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD 20894, USA
  3. Scripps Institution of Oceanography, University of California at San Diego, La Jolla, CA 92093-0202, USA
  4. Department of Biomolecular Analysis and Imaging, Sandia National Laboratories, Albuquerque, NM 87185-0895, USA
  5. Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW 2109, Australia
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Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.

Research Organization:
Univ. of California, San Diego, CA (United States); Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Grant/Contract Number:
DOE DE-FG03-O1ER63148; FG03-01ER63148
OSTI ID:
1197681
Alternate ID(s):
OSTI ID: 1626198
Journal Information:
Comparative and Functional Genomics, Journal Name: Comparative and Functional Genomics Vol. 2009; ISSN 1531-6912
Publisher:
Hindawi Publishing CorporationCopyright Statement
Country of Publication:
Egypt
Language:
English
Citation Metrics:
Cited by: 6 works
Citation information provided by
Web of Science

References (14)

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Analysis of variance components in gene expression data journal February 2004
Application of molecular techniques to addressing the role of P as a key effector in marine ecosystems journal January 1999
Importance of replication in microarray gene expression studies: Statistical methods and evidence from repetitive cDNA hybridizations journal August 2000
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Active mixing during hybridization improves the accuracy and reproducibility of microarray results journal January 2005
Assessing Gene Significance from cDNA Microarray Expression Data via Mixed Models journal November 2001
Computational inference and experimental validation of the nitrogen assimilation regulatory network in cyanobacterium Synechococcus sp. WH 8102 journal February 2006
Statistical design and the analysis of gene expression microarray data journal February 2001
Significance analysis of microarrays applied to the ionizing radiation response journal April 2001
Protein phosphorylation and regulation of adaptive responses in bacteria. journal January 1989
Identification of competence pheromone responsive genes in Streptococcus pneumoniae by use of DNA microarrays: Pneumococcal competence and gene expression journal December 2003
The genome of a motile marine Synechococcus journal August 2003
TM4: A Free, Open-Source System for Microarray Data Management and Analysis journal February 2003

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