Application of Microarray Technology in Environmental and Comparative Physiology

Abstract

DNA microarray technology is revolutionizing many aspects of biological research, allowing the expression of many thousands of gene transcripts to be monitored simultaneously. This provides powerful tools for the genome-wide correlation of gene transcript levels with physiological responses and alterations in physiological states. To date, microarray analyses have been applied almost exclusively to a few model species for which the abundant gene sequence data permit the fabrication of whole-genome microarrays. However, many interesting physiological traits and responses are poorly expressed or absent in model species and may be better illustrated in nonmodel organisms. Comparative approaches to understanding function traditionally focus on species that by virtue of their unusual adaptations, lifestyles, and phylogeny are particularly suited to address a specific biological process or problem. In this review, we show that microarray technology can be successfully applied to these nonmodel species and used to generate new insights of comparative and evolutionary significance into animal function.

Identification and characterization of hypoxia-induced genes in Carassius auratus blastulae embryonic cells using suppression subtractive hybridization

“…A range of physiological adaptations on transcriptional levels have received considerable attention in fish. cDNA microarray has been used to identify hypoxiainduced genes in tissues from several fish species (Gracey et al, 2001;Gracey and Cossins, 2003;Ton et al, 2003;David et al, 2005;Ju et al;2007). Suppression subtractive hybridization is a powerful approach to identify differentially expressed gene that involved in physiological and pathological processes without bias of the prerequisite knowledge of a specific gene.…”

Upregulation of intracellular antioxidant enzymes in brain and heart during estivation in the African lungfish Protopterus dolloi

“…total SOD activity versus individual MnSOD and CuZnSOD quantiWcation), the duration of estivation (which varies from »15 days to 180 days), or they may simply reXect diVerences in how particular species adapt to the metabolic stress of estivation. Antioxidant enzymes represent only one facet of the cellular adaptive response that can be recruited in the adaptation to environmental stress (Gracey and Cossins 2003;Kültz 2003).…”

Insights into the role of differential gene expression on the ecological adaptation of the snail Littorina saxatilis

“…Sorting or clustering genes into groups according to their expression patterns can provide a broad and interpretable overview of gene regulation [7]. Here, we carried out a cluster analysis in order to identify sets of genes with common expression between ecotypes.…”

“…In fact, a very similar result was found in the same population at the proteome level [54], where enzymes related with the energetic metabolism (arginine kinase and fructose bisphosphate aldolase) were also up-regulated in the SU ecotype. Consequently, the provision of ATP and the control of its metabolism seem to be critical components of the general environmental stress response in all organisms, allowing them to respond with adaptive physiological changes while, at the same time, buffering the changing energy demands [7]. The SU individuals have to develop higher muscular effort than the other ecotype to be able to hold on the rocks while suffering the strong swell of their habitat [54].…”

“…However, its utility has been restricted to organisms with extensive cDNA or genomic DNA sequence data available and, of course, any key question in ecology and evolutionary biology cannot be solely addressed using model organisms [7]. A useful alternative technique for transcriptome profiling is cDNA-amplified fragment length polymorphism analysis (cDNA-AFLP), a modification of the original genomic DNA-AFLP [8,9], by means of which accurate gene expression profiles can be determined by quantitative analysis of the peak (transcript) intensities generated [10,11].…”