Identification of condition-specific reference genes from microarray data for locusts exposed to hypobaric hypoxia

FEBS Open Bio

Volumn 2, Issue , 2012, Pages 235-240

  Zhao, De Jian ^a   Guo, Kun ^a,b   Kang, Le ^a  

^a INSTITUTE OF ZOOLOGY   (China)

^b INSTITUTE OF MEDICINAL PLANT DEVELOPMENT   (China)

Author keywords

Hypobaric hypoxia; Locusta migratoria; Microarray; Real time quantitative PCR; Reference gene

Indexed keywords

ACETYL COENZYME A HYDROLASE; BETA ACTIN; CHITINASE; GLYCERALDEHYDE 3 PHOSPHATE DEHYDROGENASE; PHOSPHATASE; PHOSPHOGLYCOLATE PHOSPHATASE LIKE; PROTEIN; RECOMBINATION REPAIR PROTEIN 1; RNA 18S; UNCLASSIFIED DRUG;

ACRIDIDAE; ALGORITHM; ANIMAL TISSUE; ARTICLE; CONTROLLED STUDY; FEMALE; GENE EXPRESSION; GENE IDENTIFICATION; GENETIC ANALYSIS; GENETIC TRANSCRIPTION; HOUSEKEEPING GENE; HYPOBARIC HYPOXIA; HYPOBARISM; MOLECULAR STABILITY; NONHUMAN; NUCLEOTIDE SEQUENCE; PRIORITY JOURNAL; REAL TIME POLYMERASE CHAIN REACTION;

EID: 84867306190     PISSN: 22115463     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fob.2012.08.001     Document Type: Article

References (41)

1. Magalhães J., Ascensão A., Soares J.M.C., et al. Acute and severe hypobaric hypoxia increases oxidative stress and impairs mitochondrial function in mouse skeletal muscle. J. Appl. Physiol. 2005, 99:1247-1253.
2. Liao W., Cai M., Chen J., et al. Hypobaric hypoxia causes deleterious effects on spermatogenesis in rats. Reproduction 2010, 139:1031-1038.
3. Gelfi C., De Palma S., Ripamonti M., et al. New aspects of altitude adaptation in Tibetans: a proteomic approach. FASEB J. 2004, 18:612-614.
4. Lippl F.J., Neubauer S., Schipfer S., et al. Hypobaric hypoxia causes body weight reduction in obese subjects. Obesity 2010, 18:675-681.
5. Ekman D.R., Lorenz W.W., Przybyla A.E., et al. SAGE analysis of transcriptome responses in arabidopsis roots exposed to 2,4,6-trinitrotoluene. Plant Physiol. 2003, 133:1397-1406.
6. Kang L., Chen X., Zhou Y., et al. The analysis of large-scale gene expression correlated to the phase changes of the migratory locust. Proc. Natl. Acad. Sci. U.S.A. 2004, 101:17611-17615.
7. Guo W., Wang X., Ma Z., et al. CSP and Takeout genes modulate the switch between attraction and repulsion during behavioral phase change in the migratory locust. PLoS Genet. 2011, 7:e1001291.
8. Ma Z., Guo W., Guo X., et al. Modulation of behavioral phase changes of the migratory locust by the catecholamine metabolic pathway. Proc. Natl. Acad. Sci. U.S.A. 2011, 108:3882-3887.
9. Wang H., Ma Z., Cui F., et al. Parental phase status affects the cold hardiness of progeny eggs in locusts. Funct. Ecol. 2012, 26:379-389.
10. Chen S., Yang P., Jiang F., et al. De novo analysis of transcriptome dynamics in the migratory locust during the development of phase traits. PLoS ONE 2010, 5:e15633.
11. Kosir R., Acimovic J., Golicnik M., et al. Determination of reference genes for circadian studies in different tissues and mouse strains. BMC Mol. Biol. 2010, 11:60.
12. Kidd M., Nadler B., Mane S., et al. GeneChip, geNorm, and gastrointestinal tumors: novel reference genes for real-time PCR. Physiol. Genomics 2007, 30:363-370.
13. Spanakis E. Problems related to the interpretation of autoradiographic data on gene expression using common constitutive transcripts as controls. Nucleic Acids Res. 1993, 21:3809-3819.
14. Piana C., Wirth M., Gerbes S., et al. Validation of reference genes for qPCR studies on Caco-2 cell differentiation. Eur. J. Pharm. Biopharm. 2008, 69:1187-1192.
15. Watson S., Mercier S., Bye C., et al. Determination of suitable housekeeping genes for normalisation of quantitative real time PCR analysis of cells infected with human immunodeficiency virus and herpes viruses. Virol. J. 2007, 4:130.
16. Udvardi M.K., Czechowski T., Scheible W.R. Eleven golden rules of quantitative RT-PCR. Plant Cell 2008, 20:1736-1737.
17. Cicinnati V., Shen Q., Sotiropoulos G., et al. Validation of putative reference genes for gene expression studies in human hepatocellular carcinoma using real-time quantitative RT-PCR. BMC Cancer 2008, 8:350.
18. Majerowicz D., Alves-Bezerra M., Logullo R., et al. Looking for reference genes for real-time quantitative PCR experiments in Rhodnius prolixus (Hemiptera: Reduviidae). Insect Mol. Biol. 2011, 20:713-722.
19. Jain M., Nijhawan A., Tyagi A.K., et al. Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem. Biophys. Res. Commun. 2006, 345:646-651.
20. Radonić A., Thulke S., Mackay I.M., et al. Guideline to reference gene selection for quantitative real-time PCR. Biochem. Biophys. Res. Commun. 2004, 313:856-862.
21. An Y., Reimers K., Allmeling C., et al. Validation of differential gene expression in muscle engineered from rat groin adipose tissue by quantitative real-time PCR. Biochem. Biophys. Res. Commun. 2012, 421:736-742.
22. Popovici V., Goldstein D., Antonov J., et al. Selecting control genes for RT-QPCR using public microarray data. BMC Bioinformatics 2009, 10:42.
23. de Jonge H.J.M., Fehrmann R.S.N., de Bont E.S.J.M., et al. Evidence based selection of housekeeping genes. PLoS ONE 2007, 2:e898.
24. Andersen C.L., Jensen J.L., Orntoft T.F. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 2004, 64:5245-5250.
25. Guénin S., Mauriat M., Pelloux J., et al. Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references. J. Exp. Bot. 2009, 60:487-493.
26. Winnebeck E.C., Millar C.D., Warman G.R. Why does insect RNA look degraded. J. Insect. Sci. 2010, 10:159.
27. Ritchie M.E., Silver J., Oshlack A., et al. A comparison of background correction methods for two-colour microarrays. Bioinformatics 2007, 23:2700-2707.
28. Smyth G.K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 2004, 3. Article3.
29. Benjamini Y., Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Statist. Soc. Ser. B 1995, 57:289-300.
30. Pickett S., Carriedo S., Wang C., Determining the signal-to-noise ratio and optimal photomultiplier gain setting in the GenePix 4000B (Application Note), (2001).
31. Guo W., Wang X.H., Zhao D.J., et al. Molecular cloning and temporal-spatial expression of I element in gregarious and solitary locusts. J. Insect Physiol. 2010, 56:943-948.
32. Vandesompele J., De Preter K., Pattyn F., et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002, 3. RESEARCH0034.
33. Bustin S.A., Benes V., Garson J.A., et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 2009, 55:611-622.
34. Foldager C.B., Munir S., Ulrik-Vinther M., et al. Validation of suitable house keeping genes for hypoxia-cultured human chondrocytes. BMC Mol. Biol. 2009, 10:94.
35. McCurley A.T., Callard G.V. Characterization of housekeeping genes in zebrafish: male-female differences and effects of tissue type, developmental stage and chemical treatment. BMC Mol. Biol. 2008, 9:102.
36. Nicot N., Hausman J.-F., Hoffmann L., et al. Housekeeping gene selection for real-time RT-PCR normalization in potato during biotic and abiotic stress. J. Exp. Bot. 2005, 56:2907-2914.
37. Silver N., Best S., Jiang J., et al. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol. Biol. 2006, 7:33.
38. Lee F.J., Lin L.W., Smith J.A. Acetyl-CoA hydrolase involved in acetate utilization in Saccharomyces cerevisiae. Biochim. Biophys. Acta 1996, 1297:105-109.
39. Suematsu N., Okamoto K., Isohashi F. Mouse cytosolic acetyl-CoA hydrolase, a novel candidate for a key enzyme involved in fat metabolism: cDNA cloning, sequencing and functional expression. Acta Biochim. Pol. 2002, 49:937-945.
40. Teresa Pellicer M., Felisa Nunez M., Aguilar J., et al. Role of 2-phosphoglycolate phosphatase of Escherichia coli in metabolism of the 2-phosphoglycolate formed in DNA repair. J. Bacteriol. 2003, 185:5815-5821.
41. Zhong H., Simons J.W. Direct comparison of GAPDH, beta-actin, cyclophilin, and 28S rRNA as internal standards for quantifying RNA levels under hypoxia. Biochem. Biophys. Res. Commun. 1999, 259:523-526.