Abstract
In the wake of recent progress of high throughput transcriptome profiling technologies, extensive housekeeping gene mining has been conducted in humans. However, very few studies have been reported in maize (Zea mays L.), an important crop plant, and none were conducted on a genome -wide level. In this study, we surveyed housekeeping genes throughout the maize transcriptome using RNA-seq and microarray techniques, and validated the housekeeping profile with quantitative polymerase chain reaction (qPCR) under a series of conditions including different genotypes and nitrogen supplies. Seven microarray datasets and two RNA-seq libraries representing 40 genotypes at more than 20 developmental stages were selected to screen for commonly expressed genes. A total of 1,661 genes showed constitutive expression in both microarray and RNA-seq datasets, serving as our starting housekeeping gene candidates. To determine for stably expressed housekeeping genes, NormFinder was used to select the top 20 % invariable genes to be the more likely candidates, which resulted in 48 and 489 entries from microarray and RNA-seq data, respectively. Among them, nine genes (2OG-Fe, CDK, DPP9, DUF, NAC, RPN, SGT1, UPF1 and a hypothetical protein coding gene) were expressed in all 40 maize diverse genotypes tested covering 16 tissues at more than 20 developmental stages under normal and stress conditions, implying these as being the most reliable reference genes. qPCR analysis confirmed the stable expression of selected reference gene candidates compared to two widely used housekeeping genes. All the reference gene candidates showed higher invariability than ACT and GAPDH. The hypothetical protein coding gene exhibited the most stable expression across 26 maize lines with different nitrogen treatments with qPCR, followed by CDK encoding the cyclin-dependent kinase. As the first study to systematically screen for housekeeping genes in maize, we identified candidates by examining the transcriptome atlas generated from RNA-seq and microarray technologies. The nine top-ranked qPCR-validated novel housekeeping genes provide a valuable resource of reference genes for maize gene expression analysis.
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References
Andersen CL, Jensen JK, Ørntoft TF (2004) 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 64:5245–5250
Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, Davis AP, Dolinski K, Dwight SS, Eppig JT et al (2000) Gene ontology: tool for the unification of biology. Nat Genet 25:25–29
Barber 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
Bremnera JM (1960) Determination of nitrogen in soil by the Kjeldahl method. J Agric Sci 55:11–33
Brunner AM, Yakovlev IA, Strauss SH (2004) Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol 4:14
Butte AJ, Dzau VJ, Glueck SB (2001) Further defining housekeeping, or “maintenance”, genes focus on “A compendium of gene expression in normal human tissues”. Physiol Genomics 7:95–96
Chen K, Fessehaie A, Arora R (2012) Selection of reference genes for normalizing gene expression during seed priming and germination using qPCR in Zea mays and Spinacia oleracea. Plant Mol Biol Rep 30:478–487
Coker JS, Davies E (2003) Selection of candidate housekeeping controls in tomato plants using EST data. Biotechniques 35:740–748
Conesa A, Götz S, García-Gómez JM, Terol J, Talón M, Robles M (2005) Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics 21:3674–3676
Cox MP, Peterson DA, Biggs PJ (2010) SolexaQA: At-a-glance quality assessment of Illumina second-generation sequencing data. BMC Bioinformatics 11:485
Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible WR (2005) Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiol 139:5–17
Danilevskaya ON, Meng X, Hou Z, Ananiev EV, Simmons CR (2008) A genomic and expression compendium of the expanded PEBP gene family from maize. Plant Physiol 146:250–264
Davidson RM, Hansey CN, Gowda M, Childs KL, Lin H, Vaillancourt B, Sekhon RS, de Leon N, Kaeppler SM, Jiang N, Buell CR (2011) Utility of RNA sequencing for analysis of maize reproductive transcriptomes. Plant Genome 4:191–203
Ding D, Zhang L, Wang H, Liu Z, Zhang Z, Zheng Y (2009) Differential expression of miRNAs in response to salt stress in maize roots. Ann Bot 103:29–38
Eisenberg E, Levanon EY (2003) Human housekeeping genes are compact. Trends Genet 19:362–365
Eisenberg E, Levanon EY (2013) Human housekeeping genes, revisited. Trends Genet 29:569–574
Galli V, Messias RS, Anjos e Silva SD, Rombaldi CV (2013) Selection of reliable reference genes for quantitative real-time polymerase chain reaction studies in maize grains. Plant Cell Rep 32:1869–1877
Goidin D, Mamessier A, Staquet MJ, Schmitt D, Berthier-Vergnes O (2001) Ribosomal 18S RNA prevails over glyceraldehyde-3-phosphate dehydrogenase and ß-Actin genes as internal standard for quantitative comparison of mRNA levels in invasive and noninvasive human melanoma cell subpopulations. Anal Biochem 295:17–21
Gutierrez L, Mauriat M, Guénin S, Pelloux J, Lefebvre JF, Louvet R, Rusterucci C, Moritz T, Guerineau F, Bellini C, Wuytswinkel OV (2008) The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription polymerase chain reaction (RT-PCR) analysis in plants. Plant Biotechnol J 6:609–618
Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, Rinn JL, Lander ES, Regev A (2010) Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol 28:503–510
Hong SY, Seo PJ, Yang MS, Xiang F, Park CM (2008) Exploring valid reference genes for gene expression studies in Brachypodium distachyon by real-time PCR. BMC Plant Biol 8:112
Infante C, Matsuoka MP, Asensio E, Cañavate JP, Reith M, Manchado M (2008) Selection of housekeeping genes for gene expression studies in larvae from flatfish using real-time PCR. BMC Mol Biol 9:28
Jain M, Nijhawan A, Tyagi AK, Khurana JP (2006) Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem Biophys Res Commun 345:646–651
Kim BR, Nam HY, Kim SU, Kim SI, Chang YJ (2003) Normalization of reverse transcription quantitative-PCR with housekeeping genes in rice. Biotechnol Lett 25:1869–1872
Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25
Lee PD, Sladek R, Greenwood CMT, Hudson TJ (2002) Control genes and variability: absence of ubiquitous reference transcripts in diverse mammalian expression studies. Genome Res 12:292–297
Li H, Ruan J, Durbin R (2008) Mapping short DNA sequencing reads and calling variants using mapping quality scores. Genome Res 18:1851–1858
Lister R, O’Malley RC, Tonti-Filippini J, Gregory BD, Berry CC, Millar AH, Ecker JR (2008) Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell 133:523–536
Liu S, Cai P, Hou N, Piao X, Wang H, Hung T, Chen Q (2012) Genome-wide identification and characterization of a panel of house-keeping genes in Schistosoma japonicum. Mol Biochem Parasit 182:75–82
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
Lunter G, Goodson M (2010) Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res 21:936–939
Makarevitch I, Phillips RL, Springer NM (2008) Profiling expression changes caused by a segmental aneuploid in maize. BMC Genom 9:7
Manoli A, Sturaroa A, Trevisana S, Quaggiotti S, Nonis A (2012) Evaluation of candidate reference genes for qPCR in maize. J Plant Physiol 169:807–815
Marioni JC, Mason CE, Mane SM, Stephens M, Gilad Y (2008) RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Res 18:1509–1517
Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat Methods 5:621–628
Murphy D (2002) Gene expression studies using microarrays: principles, problems, and prospects. Adv Physiol Educ 26:256–270
Murphy SP, Simmons CR, Bass HW (2010) Structure and expression of the maize (Zea mays L) SUN-domain protein gene family: evidence for the existence of two divergent classes of SUN proteins in plants. BMC Plant Biol 10:269
Nagalakshmi U, Wang Z, Waern K, Shou C, Raha D, Gerstein M, Snyder M (2008) The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320:1344–1349
Nebreda AR (2006) CDK activation by non-cyclin proteins. Curr Opin Cell Biol 18:192–198
Paolacci AR, Tanzarella OA, Porceddu E, Ciaffi M (2009) Identification and validation of reference genes for quantitative RT-PCR normalization in wheat. BMC Mol Biol 10:11
Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper–Excel-based tool using pair-wise correlations. Biotechnol Lett 26:509–515
Ramsköld D, Wang ET, Burge CB, Sandberg R (2009) An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS Comput Biol 5:e1000598
Remans T, Smeets K, Opdenakker K, Mathijsen D, Vangronsveld J, Cuypers A (2008) Normalization of real-time RT-PCR gene expression measurements in Arabidopsis thaliana exposed to increased metal concentrations. Planta 227:1343–1349
Robertson G, Schein J, Chiu R, Corbett R, Field M, Jackman SD, Mungall K, Lee S, Okada HM, Qian JQ et al (2010) De novo assembly and analysis of RNA-seq data. Nat Methods 7:909–912
Schnable PS, Ware D, Fulton RS, Stein JC, Wei F, Pasternak S, Liang C, Zhang J, Fulton L, Graves TA et al (2009) The B73 maize genome: complexity, diversity, and dynamics. Science 326:1112–1115
Scholtz JJ, Visser B (2013) Reference gene selection for qPCR gene expression analysis of rust-infected wheat. Physiol Mol Plant P 81:22–25
Sekhon RS, Lin H, Childs KL, Hansey CN, Buell CR, de Leon N, Kaeppler SM (2011) Genome-wide atlas of transcription during maize development. Plant J 66:553–563
Selvey S, Thompson EW, Matthaei K, Lea RA, Irving MG, Griffiths LR (2001) β-Actin—an unsuitable internal control for RT-PCR. Mol Cell Probes 15:307–311
Teste MA, Duquenne M, François JM, Parrou JL (2009) Validation of reference genes for quantitative expression analysis by real-time RT-PCR in Saccharomyces cerevisiae. BMC Mol Biol 10:99
Thellin O, Zorzi W, Lakaye B, Borman BD, Coumans B, Hennen G, Grisar T, Igout A, Heinen E (1999) Housekeeping genes as internal standards: use and limits. J Biotechnol 75:291–295
Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L (2010) Transcript assembly and quantification by RNA-seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 28:511–515
Vandesompele J, Preter KD, Pattyn F, Poppe B, Roy NV, Raepe AD, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:1–11
Velculescu VE, Madden SL, Zhang L, Lash AE, Yu J, Rago C, Lal A, Wang CJ, Beaudry GA, Ciriello KM et al (1999) Analysis of human transcriptomes. Nat Genet 23:387–388
Wang Z, Gerstein M, Snyder M (2009) RNA-seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10:57–63
Wang L, Wang Y, Zhou P (2013) Validation of reference genes for quantitative real-time PCR during Chinese wolfberry fruit development. Plant Physiol Biochem 70:304–310
Warrington JA, Nair A, Mahadevappa M, Tsyganskaya M (2000) Comparison of human adult and fetal expression and identification of 535 housekeeping/maintenance genes. Physiol Genomics 2:143–147
Yang XS, Wu J, Ziegler TE, Yang X, Zayed A, Rajani MS, Zhou D, Basra AS, Schachtman DP, Peng M et al (2011) Gene expression biomarkers provide sensitive indicators of in planta nitrogen status in maize. Plant Physiol 157:1841–1852
Zhong H, Simons JW (1999) Direct comparison of GAPDH, β-Actin, cyclophilin, and 28S rRNA as internal standards for quantifying RNA levels under hypoxia. Biochem Biophys Res Commun 259:523–526
Zhu J, He F, Song S, Wang J, Yu J (2008) How many human genes can be defined as housekeeping with current expression data? BMC Genom 9:172
Acknowledgments
This work was supported by Grant from the Natural Science Foundation of China (No. 31271728) and Jiangsu Agriculture Science and Technology Innovation Fund [cx(12)2032].
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The authors declare that they have no conflict of interest.
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Feng Lin and Lu Jiang contributed equally to this work.
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Lin, F., Jiang, L., Liu, Y. et al. Genome-wide identification of housekeeping genes in maize. Plant Mol Biol 86, 543–554 (2014). https://doi.org/10.1007/s11103-014-0246-1
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DOI: https://doi.org/10.1007/s11103-014-0246-1