DNA microarray technology and its application in fish biology and aquaculture

Abstract

Fishery is an important industry in China as well as in the rest of the world, and it provides a human food resource containing high-quality protein. Best practice in aquaculture requires a full understanding of the genomic controls and transcriptional profiles of cultured fish species. Improvements in aquaculture can be made by regulation of the expression of functional genes. Microarray technology is a powerful tool for rapid screening of genes or transcriptional profiles in a particular fish or for a particular economic character; for example, genes that are related to growth and disease control in the fish. This review provides a brief introduction to microarray technology and its methods and applications, together with a discussion of the achievements in fish biology that have resulted from this technology.

Keywords

complementary DNA (cDNA) microarray / bioinformatics / transcription profiles / teleost fish / aquaculture

References

[1] Adams A, Thompson K D (2006). Biotechnology offers revolution to fish health management. Trends Biotechnol, 24(5): 201–-205

[2] Arcand S L, Mes-Masson A M, Provencher D, Hudson T J, Tonin P N (2004). Gene expression microarray analysis and genome databases facilitate the characterization of a chromosome 22 derived homogeneously staining region. Mol Carcinog, 41(1): 17-38

[3] Benninghoff A D, Williams D E (2008). Identification of a transcriptional fingerprint of estrogen exposure in rainbow trout liver. Toxicol Sci, 101(1): 65-80

[4] Berger J A, Hautaniemi S, Jarvinen A K, Edgren H, Mitra S K, Astola J (2004). Optimized LOWESS normalization parameter selection for DNA microarray data. BMC Bioinformatics, 5: 194

[5] Bolstad B M, Irizarry R A, Astrand M, Speed T P (2003). A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics, 19(2): 185-193

[6] Brown M M, Williams T D, Kevin Chipman J, Katsiadaki I, Sanders M, Craft J A (2008). Construction of subtracted EST and normalised cDNA libraries from liver of chemical-exposed three-spined stickleback (Gasterosteus aculeatus) containing pollutant-responsive genes as a resource for transcriptome analysis. Mar Environ Res, 66(1): 127-130

[7] Byon J Y, Ohira T, Hirono I, Aoki T (2005). Use of a cDNA microarray to study immunity against viral hemorrhagic septicemia (VHS) in Japanese flounder (Paralichthys olivaceus) following DNA vaccination. Fish Shellfish Immunol, 18(2): 135-147

[8] Byon J Y, Ohira T, Hirono I, Aoki T (2006). Comparative immune responses in Japanese flounder, Paralichthys olivaceus after vaccination with viral hemorrhagic septicemia virus (VHSV) recombinant glycoprotein and DNA vaccine using a microarray analysis. Vaccine, 24(7): 921-930

[9] Cohen R, Chalifa-Caspi V, Williams T D, Auslander M, George S G, Chipman J K, Tom M (2007). Estimating the efficiency of fish cross-species cDNA microarray hybridization. Mar Biotechnol (NY), 9(4): 491-499

[10] Colantuoni C, Henry G, Zeger S, Pevsner J (2002). Local mean normalization of microarray element signal intensities across an array surface: quality control and correction of spatially systematic artifacts. Biotechniques, 32(6): 1316-1320

[11] Corredor-Adamez M, Welten M C, Spaink H P, Jeffery J E, Schoon R T, de Bakker M A, Bagowski C P, Meijer A H, Verbeek F J, Richardson M K (2005). Genomic annotation and transcriptome analysis of the zebrafish (Danio rerio) hox complex with description of a novel member, hoxb13a. Evolution & Development, 7(5): 362-375

[12] Darias M J, Zambonino-Infante J L, Hugot K, Cahu C L, Mazurais D (2008). Gene expression patterns during the larval development of European sea bass (dicentrarchus labrax) by microarray analysis. Mar Biotechnol (NY), 10(4): 416-428

[13] Douglas S E (2006). Microarray studies of gene expression in fish. Omics, 10(4): 474-489

[14] Eisen M B, Spellman P T, Brown P O, Botstein D (1998). Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci USA, 95(25): 14863-14868

[15] Ewart K V, Belanger J C, Williams J, Karakach T, Penny S, Tsoi S C, Richards R C, Douglas S E (2005). Identification of genes differentially expressed in Atlantic salmon (Salmo salar) in response to infection by Aeromonas salmonicida using cDNA microarray technology. Dev Comp Immunol, 29(4): 333-347

[16] Fiehn O (2001). Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp Funct Genomics, 2(3): 155-168

[17] Finne E F, Cooper G A, Koop B F, Hylland K, Tollefsen K E (2007). Toxicogenomic responses in rainbow trout (Oncorhynchus mykiss) hepatocytes exposed to model chemicals and a synthetic mixture. Aquat Toxicol, 81(3): 293-303

[18] Fujimoto T, Koyanagi M, Baba I, Nakabayashi K, Kato N, Sasazuki T, Shirasawa S (2007). Analysis of KRAP expression and localization, and genes regulated by KRAP in a human colon cancer cell line. J Hum Genet, 52(12): 978-984

[19] Gonzalez S F, Krug M J, Nielsen M E, Santos Y, Call D R (2004). Simultaneous detection of marine fish pathogens by using multiplex PCR and a DNA microarray. J Clin Microbiol, 42(4): 1414-1419

[20] Gracey A Y (2007). Interpreting physiological responses to environmental change through gene expression profiling. J Exp Biol, 210(Pt 9): 1584-1592

[21] Hirayama M, Ahsan M N, Mitani H, Watabe S (2008). CYR61 is a novel gene associated with temperature-dependent changes in fish metabolism as revealed by cDNA microarray analysis on a medaka Oryzias latipes cell line. J Cell Biochem, 104(4): 1297-1310

[22] Ju Z, Dunham R A, Liu Z (2002). Differential gene expression in the brain of channel catfish (Ictalurus punctatus) in response to cold acclimation. Mol Genet Genomics, 268(1): 87-95

[23] Ju Z, Wells M C, Heater S J, Walter R B (2007a). Multiple tissue gene expression analyses in Japanese medaka (Oryzias latipes) exposed to hypoxia. Comp Biochem Physiol C Toxicol Pharmacol, 145(1): 134-144

[24] Ju Z, Wells M C, Walter R B (2007b). DNA microarray technology in toxicogenomics of aquatic models: methods and applications. Comp Biochem Physiol C Toxicol Pharmacol, 145(1): 5-14

[25] Kassahn K S, Caley M J, Ward A C, Connolly A R, Stone G, Crozier R H (2007). Heterologous microarray experiments used to identify the early gene response to heat stress in a coral reef fish. Mol Ecol, 16(8): 1749-1763

[26] Katogi R, Nakatani Y, Shini T, Kohara Y, Inohaya K, Kudo A (2004). Large-scale analysis of the genes involved in fin regeneration and blastema formation in the medaka, Oryzias latipes. Mech Dev, 121(7—8): 861-872

[27] Kochzius M, Nolte M, Weber H, Silkenbeumer N, Hjorleifsdottir S, Hreggvidsson G O, Marteinsson V, Kappel K, Planes S, Tinti F, Magoulas A, Garcia Vazquez E, Turan C, Hervet C, Campo Falgueras D, Antoniou A, Landi M, Blohm D (2008). DNA microarrays for identifying fishes. Mar Biotechnol (NY), 10(2): 207-217

[28] Koskinen H, Pehkonen P, Vehniainen E, Krasnov A, Rexroad C, Afanasyev S, Molsa H, Oikari A (2004). Response of rainbow trout transcriptome to model chemical contaminants. Biochem Biophys Res Commun, 320(3): 745-753

[29] Kurobe T, Yasuike M, Kimura T, Hirono I, Aoki T (2005). Expression profiling of immune-related genes from Japanese flounder Paralichthys olivaceus kidney cells using cDNA microarrays. Dev Comp Immunol, 29(6): 515-523

[30] Lam S H, Gong Z (2006). Modeling liver cancer using zebrafish: a comparative oncogenomics approach. Cell Cycle, 5(6): 573-577

[31] Lam S H, Winata C L, Tong Y, Korzh S, Lim W S, Korzh V, Spitsbergen J, Mathavan S, Miller L D, Liu E T, Gong Z (2006). Transcriptome kinetics of arsenic-induced adaptive response in zebrafish liver. Physiol Genomics, 27(3): 351-361

[32] Larkin P, Villeneuve D L, Knoebl I, Miracle A L, Carter B J, Liu L, Denslow N D, Ankley G T (2007). Development and validation of a 2,000-gene microarray for the fathead minnow (Pimephales promelas). Environ Toxicol Chem, 26(7): 1497-1506

[33] Leung Y F, Ma P, Dowling J E (2007). Gene expression profiling of zebrafish embryonic retinal pigment epithelium in vivo. Invest Ophthalmol Vis Sci, 48(2): 881-890

[34] Lien C L, Schebesta M, Makino S, Weber G J, Keating M T (2006). Gene expression analysis of zebrafish heart regeneration. PLoS Biol, 4(8): e260

[35] Linney E, Dobbs-McAuliffe B, Sajadi H, Malek R L (2004a). Microarray gene expression profiling during the segmentation phase of zebrafish development. Comp Biochem Physiol C Toxicol Pharmacol, 138(3): 351-362

[36] Linney E, Upchurch L, Donerly S (2004b). Zebrafish as a neurotoxicological model. Neurotoxicol Teratol, 26(6): 709-718

[37] Lo J, Lee S, Xu M, Liu F, Ruan H, Eun A, He Y, Ma W, Wang W, Wen Z, Peng J (2003). 15000 unique zebrafish EST clusters and their future use in microarray for profiling gene expression patterns during embryogenesis. Genome Res, 13(3): 455-466

[38] Lua D T, Yasuike M, Hirono I, Aoki T (2005). Transcription program of red sea bream iridovirus as revealed by DNA microarrays. J Virol, 79(24): 15151-15164

[39] Martin S A, Blaney S C, Houlihan D F, Secombes C J (2006). Transcriptome response following administration of a live bacterial vaccine in Atlantic salmon (Salmo salar). Mol Immunol, 43(11): 1900-1911

[40] Martyniuk C J, Gerrie E R, Popesku J T, Ekker M, Trudeau V L (2007). Microarray analysis in the zebrafish (Danio rerio) liver and telencephalon after exposure to low concentration of 17alpha-ethinylestradiol. Aquat Toxicol, 84(1): 38-49

[41] Meijer A H, Verbeek F J, Salas-Vidal E, Corredor-Adamez M, Bussman J, van der Sar A M, Otto G W, Geisler R, Spaink H P (2005). Transcriptome profiling of adult zebrafish at the late stage of chronic tuberculosis due to Mycobacterium marinum infection. Mol Immunol, 42(10): 1185-1203

[42] Moens L N, Smolders R, van der Ven K, van Remortel P, Del-Favero J, De Coen W M (2007). Effluent impact assessment using microarray-based analysis in common carp: a systems toxicology approach. Chemosphere, 67(11): 2293-2304

[43] Moens L N, van der Ven K, Van Remortel P, Del-Favero J, De Coen W M (2007). Gene expression analysis of estrogenic compounds in the liver of common carp (Cyprinus carpio) using a custom cDNA microarray. J Biochem Mol Toxicol, 21(5): 299-311

[44] Nishidate M, Nakatani Y, Kudo A, Kawakami A (2007). Identification of novel markers expressed during fin regeneration by microarray analysis in medaka fish. Dev Dyn, 236(9): 2685-2693

[45] Oostlander A E, Meijer G A, Ylstra B (2004). Microarray-based comparative genomic hybridization and its applications in human genetics. Clin Genet, 66(6): 488-495

[46] Pollack J R, Perou C M, Alizadeh A A, Eisen M B, Pergamenschikov A, Williams C F, Jeffrey S S, Botstein D, Brown P O (1999). Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat Genet, 23(1): 41-46

[47] Ranheim T, Mattingsdal M, Lindvall J M, Holla O L, Berge K E, Kulseth M A, Leren T P (2008). Genome-wide expression analysis of cells expressing gain of function mutant D374Y-PCSK9. J Cell Physiol, 217(2): 459-467

[48] Renn S C, Aubin-Horth N, Hofmann H A (2004). Biologically meaningful expression profiling across species using heterologous hybridization to a cDNA microarray. BMC Genomics, 5(1): 42

[49] Rise M L, Jones S R, Brown G D, von Schalburg K R, Davidson W S, Koop B F (2004). Microarray analyses identify molecular biomarkers of Atlantic salmon macrophage and hematopoietic kidney response to Piscirickettsia salmonis infection. Physiol Genomics, 20(1): 21-35

[50] Salem M, Kenney P B, Rexroad C E3rd, Yao J (2006). Microarray gene expression analysis in atrophying rainbow trout muscle: a unique nonmammalian muscle degradation model. Physiol Genomics, 28(1): 33-45

[51] Schebesta M, Lien C L, Engel F B, Keating M T (2006). Transcriptional profiling of caudal fin regeneration in zebrafish. Sci World J, 6: 38-54

[52] Ton C, Stamatiou D, Dzau V J, Liew C C (2002). Construction of a zebrafish cDNA microarray: gene expression profiling of the zebrafish during development. Biochem Biophys Res Commun, 296(5): 1134-1142

[53] Ton C, Stamatiou D, Liew C C (2003). Gene expression profile of zebrafish exposed to hypoxia during development. Physiol Genomics, 13(2): 97-106

[54] Tsoi S C, Cale J M, Bird I M, Ewart V, Brown L L, Douglas S (2003). Use of human cDNA microarrays for identification of differentially expressed genes in Atlantic salmon liver during Aeromonas salmonicida infection. Mar Biotechnol (NY), 5(6): 545-554

[55] van der Meer D L, van den Thillart G E, Witte F, de Bakker M A, Besser J, Richardson M K, Spaink H P, Leito J T, Bagowski C P (2005). Gene expression profiling of the long-term adaptive response to hypoxia in the gills of adult zebrafish. Am J Physiol Regul Integr Comp Physiol, 289(5): R1512-1519

[56] van der Ven K, De Wit M, Keil D, Moens L, van Leemput K, Naudts B, De Coen W (2005). Development and application of a brain-specific cDNA microarray for effect evaluation of neuro-active pharmaceuticals in zebrafish (Danio rerio). Comp Biochem Physiol B Biochem Mol Biol, 141(4): 408-417

[57] Williams T D, Gensberg K, Minchin S D, Chipman J K (2003). A DNA expression array to detect toxic stress response in European flounder (Platichthys flesus). Aquat Toxicol, 65(2): 141-157

[58] Wu W, Liu X, Xu M, Peng J R, Setiono R (2005). A hybrid SOM-SVM approach for the zebrafish gene expression analysis. Genomics Proteomics Bioinformatics, 3(2): 84-93

[59] Xiang C C, Chen Y (2000). cDNA microarray technology and its applications. Biotechnol Adv, 18(1): 35-46

[60] Yang Y H, Buckley M J, Speed T P (2001). Analysis of cDNA microarray images. Brief Bioinform, 2(4): 341-349

[61] Zhang D, Wells M T, Smart C D, Fry W E (2005). Bayesian normalization and identification for differential gene expression data. J Comput Biol, 12(4): 391-406

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