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Unification of Gene Expression Data for Comparable Analyses Under Stress Conditions

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Microbial Stress Tolerance for Biofuels

Part of the book series: Microbiology Monographs ((MICROMONO,volume 22))

Abstract

Gene expression is a fundamental biological process in which genotypes rise to phenotypes. As a quantitative measurement, expression of a gene is commonly examined by mRNA abundance that varies in response to different conditions and environmental stimuli. High throughput quantitative measurements of gene expression data have difficulties of reproducibility and comparability due to a lack of standard mRNA quantification references. Efforts have been made to safeguard data fidelity, yet generating quality expression data of inherent value remains a challenge. This not only affects unbiased data assessment and clinical applications but also damages establishing invaluable database resources for the larger scientific community. Unification of multi-source gene expression data is necessary for comparable and comprehensive analyses to gain insight into complex gene interactions and regulatory networks of life events using more integrated approaches of bioinformatics, computational biology and systems biology. Development and application of commonly accepted quantification references to generate comparable expression data are urgently needed. This chapter provides basics and application aspects for comparative gene expression analyses using microbial examples under stress conditions.

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References

  • Applied Biosystems (2004) Absolute quantification: Getting started guide for the 7300/7500 System, Part Number 4347825 Revison A. Foster City

    Google Scholar 

  • Applied Biosystems (2006) Amplification efficiency of Taqman gene expression assays, Application Note 5 pp Publication 127AP05-03. Foster City

    Google Scholar 

  • Baeber RD, Harmer DW, Coleman RA, Clark BJ (2005) GAPDH as a housekeeping gene: analysis of GAPDH mRNA expression in a panel of 72 human tissues. Physiol Genomics 21:389–395

    Article  Google Scholar 

  • Bammler T, Beyer RP, Bhattacharya S, Boorman GA, Boyles A, Bradford BU, Bumgarner RE, Bushel PR, Chaturvedi K, Choi D, Cunningham ML, Deng S, Dressman HK, Fannin RD, Farin FM, Freedman JH, Fry RC, Harper A, Humble MC, Hurban P, Kavanagh TJ, Kaufmann WK, Kerr KF, Jing L, Lapidus JA, Lasarev MR, Li J, Li Y-J, Lobenhofer EK, Lu X, Malek RL, Milton S, Nagalla SR, O’Malley JP, Palmer VS, Pattee P, Paules RS, Perou CM, Phillips K, Qin L-X, Qiu Y, Quigley SD, Rodland M, Rusyn I, Samson LD, Schwartz DA, Shi Y, Shin J-L, Sieber SO, Slifer S, Speer MC, Spencer PS, Sproles DI, Swenberg JA, Suk WA, Sullivan RC, Tian R, Tennant RW, Todd SA, Tucker CJ, Van Houten B, Weis BK, Xuan S, Zarbl H (2005) Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods 2:351–356

    Article  PubMed  Google Scholar 

  • Bower NI, Moser RJ, Hill JR, Lehnert SA (2007) Universal reference method for real-time PCR gene expression analysis of preimplantation embryos. Biotechniques 42:199–206

    Article  PubMed  CAS  Google Scholar 

  • Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach J, Ansorge W, Ball CA, Causton HC, Gaasterland T, Glenisson P, Holstege FCP, Kim IF, Markowitz V, Matese JC, Parkinson H, Robinson A, Sarkans U, Schulze-Kremer S, Stewart J, Taylor R, Vilo J, Vingron M (2001) Minimum information about a microarray experiment (MIAME)–toward standards for microarray data. Nat Genet 29:365–371

    Article  PubMed  CAS  Google Scholar 

  • Bustin SA, Benes VJ, Garson A, Hellemants J, HuggettJ KM, Mueller R, Nolan TM, Pfaffl W, Shipley GL, Vandesompele JC, Wittwer T (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:4

    Article  Google Scholar 

  • Choi J-C, Tiedje JM (2002) Quantitative detection of microbial genes by using DNA microarrays. Appl Environ Microbiol 68:1425–1430

    Article  Google Scholar 

  • Collins ML, Zayati C, DetmerJJ DB, Kolberg JA, Cha T-A, Irvine BD, Tucker J, Urdea MS (1995) Preperation and characterization of RNA standard for use in quantitative branched DNA hybridization assays. Anal Biochem 226:120–129

    Article  PubMed  CAS  Google Scholar 

  • Collins C, Rommens JM, Kowbel D, Godfrey T, Tabnner M, Hwang SI, Polikoff D, Nonet G, Cochran J, Maymbo K, Jay KE, Frooula J, Cloutier T, Kuo WL, Yaswen P, Dairkee S, Giovanola J, Hutchinson GB, Isola J, Kallioniemi OP, Palazzolo M, Martin C, Erricson C, Pinkel D, Albertson D, Li WB, Gray JW (1998) Positional cloning of ZNF217 and NABC1: genes amplified at 20q13.2 and over expressed in breast carcinoma. Proc Natl Acad Sci USA 95:8703–8708

    Article  PubMed  CAS  Google Scholar 

  • Cronin M, Ghosh K, Sistare F, Quackenbush J, Vilker V, O’Connell C (2004) Universal RNA reference materials for gene expression. Clin Chem 50:1464–1471

    Article  PubMed  CAS  Google Scholar 

  • Czechowski T, Bri RP, Stitt M, Scheible W, Udvardi MK (2004) Real-time RT-PCR profiling of over 1400 Arabidopsis transcription factors: unprecedented sensitivity reveals novel root-and shoot-specific genes. Plant J 38:366–379

    Article  PubMed  CAS  Google Scholar 

  • Dallas PB, Gottardo NG, Firth MJ, Beesley AH, Hoffmann K, Terry PA, Freitas JR, Boag JM, Cummings AJ, Kees UR (2005) Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR – how well do they correlate? BMC Genomics 6:59

    Article  PubMed  Google Scholar 

  • Ellefsen S, Stenslokken K-O, Sandvik GK, Kristensen TA, Nilsson GE (2008) Improved normalization of real-time reverse transcriptase polymerase chain reaction data using an external RNA control. Anal Biochem 376:83–93

    Article  PubMed  CAS  Google Scholar 

  • ERCC (2005a) The external RNA controls consortium: a progress report. Nat Methods 2:731–734

    Article  Google Scholar 

  • ERCC (2005b) Proposed methods for testing and selecting ERCC external RNA controls. BMC Genomics 6:150

    Article  Google Scholar 

  • Etienne W, Meyer MH, Peppers J, Meyer RA Jr (2004) Comparison of mRNA gene expression by RT-PCR and DNA microarray. Biotechniques 36:618–626

    PubMed  CAS  Google Scholar 

  • Fisk DG, Ball CA, Dolinski K, Engel SR, Hong EL, Issel-Tarver L, Schwartz K, Sethuraman A, Botstein D, Cherry JM (2006) Saccharomyces cerevisiae S288C genome annotation: a working hypothesis. Yeast 23:857–865

    Article  PubMed  CAS  Google Scholar 

  • Goldsworthy SM, Goldsworthy TL, Sprankle CS, Butterworth BE (1993) Variation in expression of genes used for normalization of Northern blots after induction of cell proliferation. Cell Prolif 26:511–518

    Article  PubMed  CAS  Google Scholar 

  • Huggett J, Dheda K, Bustin S, Zumla A (2005) Real-time RT-PCR normalization: strategies and considerations. Genes Immun 6:279–284

    Article  PubMed  CAS  Google Scholar 

  • Irizarry RA, Warren D, Spencer F, Kim IF, Biswal S, Frank BC, Gabrielson EJ, Garcia GN, Geoghegan J, Germino G, Griffin C, Hilmer SC, Hoffman E, Jedlicka AE, Kawasaki Martínez-Murillo EF, Morsberger L, Lee H, Petersen D, Quackenbush J, Scott A, Wilson M, Yang Y, Qing Ye S, Yu W (2005) Multiple-laboratory comparison of microarray platforms. Nat Methods 2:345–350

    Article  PubMed  CAS  Google Scholar 

  • Kakuhata R, Watanabe M, Yamamoto T, Akamine R, Yamazaki N, Kataoka S, Fukuoka S, Ishikawa M, Ooie T, Baba Y, Hori T, Shinohara Y (2007) Possible utilization of in vitro synthesized mRNA s specifically expressed in certain tissues as standard for quantitative evaluation of the results of microarray analysis. J Biochem Biophys Methods 70:755–760

    Article  PubMed  CAS  Google Scholar 

  • Kanno J, Aisaki K, Igarashi K, Nakatsu N, Ono A, Kodma Y, Nagao T (2006) “Per cell” normalization method for mRNA measurement by quantitative PCR and microarrays. BMC Genomics 7:64

    Article  PubMed  Google Scholar 

  • Kapushesky M, Emam I, Holloway E, Kurnosov P, Zorin A, Malone J, Rustici G, Williams E, Parkinson H, Brazma A (2010) Gene expression atlas at the European Bioinformatics Institute. Nucleic Acids Res 38:D690–D698, Database issue

    Article  PubMed  CAS  Google Scholar 

  • Klein D (2002) Quantification using real-time PCR technology: applications and limitations. Trends Mol Med 8:257–260

    Article  PubMed  CAS  Google Scholar 

  • Lage JM, Hamann S, Gribanov O, Leamon JH, Pejovic T, Lizardi PM (2002) Microgel assessment of nucleic acid integrity and labeling quality in microarray experiments. Biotechniques 32:312–314

    PubMed  CAS  Google Scholar 

  • Larinov A, Krause A, Miller W (2005) A standard curve based method for relative real time PCR data processing. BMC Bioinformatics 6:62

    Article  Google Scholar 

  • Larkin JE, Frank BC, Gavras H, Sultana R, Quackenbush J (2005) Independence and reproducibility across microarray platforms. Nat Methods 2:337–344

    Article  PubMed  CAS  Google Scholar 

  • Liu W, Saint DA (2002) A new quantitative method of real time reverse transcription polymerase chain reaction assay based on simulation of polymerase chain reaction kinetics. Anal Biochem 302:52–59

    Article  PubMed  CAS  Google Scholar 

  • Liu ZL (2010) Unification of gene expression data applying standard mRNA quantification reference for comparable analyses. J Microbial Biochem Technol 12:124–126

    Article  CAS  Google Scholar 

  • Liu ZL, Slininger PJ (2007) Universal external RNA quality controls for mRNA expression analysis using microbial DNA oligo microarray and real time quantitative RT-PCR. J Microbiol Methods 68:486–496

    Article  PubMed  CAS  Google Scholar 

  • Liu ZL, Palmquist DE, Ma M, Liu J, Alexander NJ (2009a) Application of a master equation for absolute mRNA quantification using qRT-PCR. J Biotechnol 143:10–16

    Article  PubMed  CAS  Google Scholar 

  • Liu ZL, Ma M, Song M (2009b) Evolutionarily engineered ethanologenic yeast detoxifies lignocellulosic biomass conversion inhibitors by reprogrammed pathways. Mol Genet Genomics 282:233–244

    Article  PubMed  Google Scholar 

  • Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2-ΔΔCT method. Methods 25:402–408

    Article  PubMed  CAS  Google Scholar 

  • Ma M, Liu ZL (2010) Quantitative transcription dynamic analysis reveales candidate genes and key regulators for ethanol tolerance in Saccharomyces cerevisiae. BMC Genomics 10:169

    Google Scholar 

  • Mohsenzadeh M, Saupe-Thies W, Sterier G, Schroeder T, Francella F, Ruoff P, Rensing L (1998) Temperature adaptation of house keeping and heat shock gene expression in Neurospora crassa. Fungal Genet Biol 25:31–43

    Article  PubMed  CAS  Google Scholar 

  • Novoradovskaya N, Whitfield ML, Basehore L, Novoradovsky SA, Pesich RJ, Usary J, Karaca M, Wong WK, Aprelikova O, Fero M, Perou CM, Botstein D, Braman J (2004) Universal reference RNA as a standard for microarray experiments. BMC Genomics 5:20

    Article  PubMed  Google Scholar 

  • PE Applied Biosystems (1997) User Bulletin #2 Norwalk. Perkin-Elmer Corp, CT, p 36

    Google Scholar 

  • Pfaffl MW (2001) A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res 29:e45

    Article  PubMed  CAS  Google Scholar 

  • Smith RD, Brown B, Ikonomi P, Schechter AN (2003) Exogenous reference RNA for normalization of real-time quantitative PCR. Biotechniques 34:88–91

    PubMed  CAS  Google Scholar 

  • Staroscik A (2004) Availible at http://www.uri.edu/research/gsc/resources/cndna.html

  • Suslov O, Steindler DA (2005) PCR inhibition by reverse transcriptase leads to an overestimation of amplification efficiency. Nucleic Acids Res 33:e181

    Article  PubMed  Google Scholar 

  • Tichopad A, Dilger M, Schward G, Pfaffl MW (2003) Standardized determination of real-time PCR efficiency from a single reaction set-up. Nucleic Acids Res 31:e122

    Article  PubMed  Google Scholar 

  • Tricarico C, Pinzani P, Bianchi S, Paglierani M, Distante V, Pazzagli M, Bustin SA, Orlando C (2002) Quantitative real-time reverse transcription polymerase chain reaction: normalization to rRNA or single housekeeping genes is inappropriate for human tissue biopsies. Anal Biochem 309:293–300

    Article  PubMed  CAS  Google Scholar 

  • VanGuilder HD, Vrana KE, Freeman WM (2008) Twenty-five years of quantitative PCR for gene expression analysis. Biotechniques 44:619–626

    Article  PubMed  CAS  Google Scholar 

  • Wong ML, Medrano JF (2005) Real-time PCR for mRNA quantitation. Biotechniques 39:1–11

    Article  Google Scholar 

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Acknowledgment

The author is grateful to Michael A. Cotta and Marsha Ebener for proofreading of the manuscript. This work was supported in part by NIFA National Research Initiative Award 2006-35504-17359. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. USDA is an equal opportunity provider and employer.

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  1. National Center for Agricultural Utilization Research, USDA-ARS, 1815 N. University Street, Peoria, IL, 61604, USA

    Z. Lewis Liu

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  1. Z. Lewis Liu
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Correspondence to Z. Lewis Liu .

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  1. USDA-ARS, National Center for Agricultural Utiliza USDA-ARS, PEORIA, Illinois, USA

    Zonglin Lewis Liu

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Liu, Z.L. (2012). Unification of Gene Expression Data for Comparable Analyses Under Stress Conditions. In: Liu, Z. (eds) Microbial Stress Tolerance for Biofuels. Microbiology Monographs, vol 22. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21467-7_12

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