Literature DB >> 11903901

Microarrays in ecology and evolution: a preview.

Greg Gibson1.   

Abstract

Microarray technology provides a new tool with which molecular ecologists and evolutionary biologists can survey genome-wide patterns of gene expression within and among species. New analytical approaches based on analysis of variance will allow quantification of the contributions of among individual variation, genotype, sex, microenvironment, population structure, and geography to variation in gene expression. Applications of this methodology are reviewed in relation to studies of mechanisms of adaptation and divergence; delineation of developmental and physiological pathways and networks; characterization of quantitative genetic parameters at the level of transcription ('quantitative genomics'); molecular dissection of parasitism and symbiosis; and studies of the diversification of gene content. Establishment of microarray resources is neither prohibitively expensive nor technologically demanding, and a commitment to development of gene expression profiling methods for nonmodel organisms could have a tremendous impact on molecular and genetic research at the interface of organismal and population biology.

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Mesh:

Year:  2002        PMID: 11903901     DOI: 10.1046/j.0962-1083.2001.01425.x

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  26 in total

1.  Pheromone-mediated gene expression in the honey bee brain.

Authors:  Christina M Grozinger; Noura M Sharabash; Charles W Whitfield; Gene E Robinson
Journal:  Proc Natl Acad Sci U S A       Date:  2003-10-22       Impact factor: 11.205

Review 2.  Gene expression profiling in ecotoxicology.

Authors:  Terry W Snell; Sara E Brogdon; Michael B Morgan
Journal:  Ecotoxicology       Date:  2003-12       Impact factor: 2.823

Review 3.  The genomic revolution: what does it mean for human and ecological risk assessment?

Authors:  Curtis C Travis; William E Bishop; David P Clarke
Journal:  Ecotoxicology       Date:  2003-12       Impact factor: 2.823

4.  Key considerations for measuring allelic expression on a genomic scale using high-throughput sequencing.

Authors:  Pierre Fontanillas; Christian R Landry; Patricia J Wittkopp; Carsten Russ; Jonathan D Gruber; Chad Nusbaum; Daniel L Hartl
Journal:  Mol Ecol       Date:  2010-03       Impact factor: 6.185

5.  Quantitative evolutionary genomics: differential gene expression and male reproductive success in Drosophila melanogaster.

Authors:  Jenny M Drnevich; Melissa M Reedy; Elizabeth A Ruedi; Sandra Rodriguez-Zas; Kimberly A Hughes
Journal:  Proc Biol Sci       Date:  2004-11-07       Impact factor: 5.349

6.  Microarray analysis reveals differential gene expression in hybrid sunflower species.

Authors:  Zhao Lai; Briana L Gross; Yi Zou; Justen Andrews; Loren H Rieseberg
Journal:  Mol Ecol       Date:  2006-04       Impact factor: 6.185

7.  Pervasive sex-linked effects on transcription regulation as revealed by expression quantitative trait loci mapping in lake whitefish species pairs (Coregonus sp., Salmonidae).

Authors:  N Derome; B Bougas; S M Rogers; A R Whiteley; A Labbe; J Laroche; L Bernatchez
Journal:  Genetics       Date:  2008-07-27       Impact factor: 4.562

8.  Gene-class analysis of expression patterns induced by psychoactive pharmaceutical exposure in fathead minnow (Pimephales promelas) indicates induction of neuronal systems.

Authors:  Michael A Thomas; Parag P Joshi; Rebecca D Klaper
Journal:  Comp Biochem Physiol C Toxicol Pharmacol       Date:  2011-06-06       Impact factor: 3.228

9.  Candidate gene polymorphisms associated with salt tolerance in wild sunflower hybrids: implications for the origin of Helianthus paradoxus, a diploid hybrid species.

Authors:  Christian Lexer; Zhao Lai; Loren H Rieseberg
Journal:  New Phytol       Date:  2004-01       Impact factor: 10.151

10.  Simultaneous detection of marine fish pathogens by using multiplex PCR and a DNA microarray.

Authors:  Santiago F González; Melissa J Krug; Michael E Nielsen; Ysabel Santos; Douglas R Call
Journal:  J Clin Microbiol       Date:  2004-04       Impact factor: 5.948

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