Identification of novel reference genes using sika deer antler transcriptome expression data and their validation for quantitative gene expression analysis

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• 作者：Meichen Liu (1)
  Baojin Yao (1) (2)
  Hui Zhang (1)
  Huanyu Guo (1)
  Dongyang Hu (1)
  Qun Wang (1)
  Yu Zhao (1)
  
• 关键词：Deer antler ; geNorm ; NormFinder ; Reference gene ; Transcriptome
• 刊名：Genes & Genomics
• 出版年：2014
• 出版时间：October 2014
• 年：2014
• 卷：36
• 期：5
• 页码：573-582
• 全文大小：921 KB
• 参考文献：1. Andersen CL, Jensen JL, 脴rntoft 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鈥?250 CrossRef
  2. Bustin SA, Benes V, Nolan T, Pfaffl MW (2005) Quantitative real-time RT-PCR: a perspective. J Mol Endocrinol 34:597鈥?01 CrossRef
  3. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL et al (2009) The MIQE Guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611鈥?22 CrossRef
  4. Calabrese R, Zampieri M, Mechelli R, Annibali V, Guastafierro T, Ciccarone F, Coarelli G, Umeton R, Salvetti M, Caiafa P (2012) Methylation-dependent PAD2 upregulation in multiple sclerosis peripheral blood. Mult Scler 18:299鈥?04 CrossRef
  5. Cankorur-Cetinkaya A, Dereli E, Eraslan S, Karabekmez E, Dikicioglu D, Kirdar B (2012) A novel strategy for selection and validation of reference genes in dynamic multidimensional experimental design in yeast. PLoS One 7:e38351 CrossRef
  6. Coker JS, Davies E (2003) Selection of candidate housekeeping controls in tomato plants using EST data. Biotechniques 35:740鈥?42, 744, 746 passim
  7. 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鈥?7 CrossRef
  8. de Jonge HJ, Fehrmann RS, de Bont ES, Hofstra RM, Gerbens F, Kamps WA, de Vries EG, van der Zee AG, te Meerman GJ, ter Elst A (2007) Evidence based selection of housekeeping genes. PLoS One 2:e898 CrossRef
  9. de Kok JB, Roelofs RW, Giesendorf BA, Pennings JL, Waas ET, Feuth T, Swinkels DW, Span PN (2005) Normalization of gene expression measurements in tumor tissues: comparison of 13 endogenous control genes. Lab Invest 85:154鈥?59 CrossRef
  10. Foldager CB, Munir S, Ulrik-Vinther M, S酶balle K, B眉nger C, Lind M (2009) Validation of suitable housekeeping genes for hypoxia-cultured human chondrocytes. BMC Mol Biol 10:94 CrossRef
  11. Goidin D, Mamessier A, Staquet MJ, Schmitt D, Berthier-Vergnes O (2001) Ribosomal 18S RNA prevails over glyceraldehyde-3-phosphate dehydrogenase and beta-actin genes as internal standard for quantitative comparison of mRNA levels in invasive and noninvasive human melanoma cell subpopulations. Anal Biochem 295:17鈥?1 CrossRef
  12. Hamalainen HK, Tubman JC, Vikman S, Kyr枚l盲 T, Ylikoski E, Warrington JA, Lahesmaa R (2001) Identification and validation of endogenous reference genes for expression profiling of T helper cell differentiation by quantitative real-time RT-PCR. Anal Biochem 299:63鈥?0 CrossRef
  13. Huggett J, Dheda K, Bustin S, Zumla A (2005) Real-time RT-PCR normalisation; strategies and considerations. Genes Immun 6:279鈥?84 CrossRef
  14. Infante C, Matsuoka MP, Asensio E, Ca帽avate 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 CrossRef
  15. Kierdorf U, Kierdorf H (2011) Deer antlers: a model of mammalian appendage regeneration: an extensive review. Gerontology 57:53鈥?5 CrossRef
  16. Ku啪mov谩 E, Barto拧 L, Kotrba R, Bubenik GA (2011) Effect of different factors on proliferation of antler cells, cultured in vitro. PLoS One 6:e18053 CrossRef
  17. Lee Y, Tsai J, Sunkara S, Karamycheva S, Pertea G, Sultana R, Antonescu V, Chan A, Cheung F, Quackenbush J (2005) The TIGR gene indices: clustering and assembling EST and known genes and integration with eukaryotic genomes. Nucleic Acids Res 33:D71鈥揇74 CrossRef
  18. Li C, Stanton JA, Robertson TM, Suttie JM, Sheard PW, Harris AJ, Clark DE (2007) Nerve growth factor mRNA expression in the regenerating antler tip of red deer (Cervus elaphus). PLoS One 2:e148 CrossRef
  19. Macrae T, Sargeant T, Lemieux S, H茅bert J, Deneault E, Sauvageau G (2013) RNA-Seq reveals spliceosome and proteasome genes as most consistent transcripts in human cancer cells. PLoS One 17:e72884 CrossRef
  20. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B (2008) Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 5:621鈥?28 CrossRef
  21. Neville MJ, Collins JM, Gloyn AL, McCarthy MI, Karpe F (2011) Comprehensive human adipose tissue mRNA and MicroRNA endogenous control selection for quantitative real-time-pcr normalization. Obesity (Silver Spring) 19:888鈥?92 CrossRef
  22. Peltier HJ, Latham GJ (2008) Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA 14:844鈥?52 CrossRef
  23. Pita-Thomas W, Fern谩ndez-Martos C, Yunta M, Maza RM, Navarro-Ruiz R, Lopez-Rodr铆guez MJ, Reigada D, Nieto-Sampedro M, Nieto-Diaz M (2010) Gene expression of axon growth promoting factors in the deer antler. PLoS One 5:e15706 CrossRef
  24. Price J, Allen S (2004) Exploring the mechanisms regulating regeneration of deer antlers. Philos Trans R Soc Lond B Biol Sci 359:809鈥?22 CrossRef
  25. Price JS, Allen S, Faucheux C, Althnaian T, Mount JG (2005) Deer antlers: a zoological curiosity or the key to understanding organ regeneration in mammals? J Anat 207:603鈥?18 CrossRef
  26. Selvey S, Thompson EW, Matthaei K, Lea RA, Irving MG, Griffiths LR (2001) Beta-actin: an unsuitable internal control for RT-PCR. Mol Cell Probes 15:307鈥?11 CrossRef
  27. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3:RESEARCH0034
  28. Warner JR, McIntosh KB (2009) How common are extraribosomal functions of ribosomal proteins? Mol Cell 34:3鈥?1 CrossRef
  29. 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鈥?47
  30. Zhou YH, Zhang YJ, Luo ZB, Fan YH, Tang GR, Liu LJ, Pei Y (2012) Selection of optimal reference genes for expression analysis in the entomopathogenic fungus / Beauveria bassiana during development, under changing nutrient conditions, and after exposure to abiotic stresses. Appl Microbiol Biotechnol 93:679鈥?85 CrossRef
  
• 作者单位：Meichen Liu (1)
  Baojin Yao (1) (2)
  Hui Zhang (1)
  Huanyu Guo (1)
  Dongyang Hu (1)
  Qun Wang (1)
  Yu Zhao (1)
  
  1. Center for New Medicine Research, Changchun University of Chinese Medicine, Changchun, 130117, China
  2. Department of Cellular and Molecular Medicine, Cleveland Clinic Lerner Research Institute, Cleveland, OH, 44195, USA
  
• ISSN：2092-9293

文摘

The most commonly used normalization strategy for quantitative real-time reverse transcription-polymerase chain reaction (RT-qPCR) is to select a stable reference gene. However, to date, no suitable reference genes have been identified in sika deer antler tissues. Thus, the aim of this study was to identify the most stable gene or a set of genes to be used as reference genes for RT-qPCR analysis in sika deer antler tissues. We first selected candidate reference genes using sika deer antler gene expression data from an Illumina sequencing platform (Hiseq 2000); twenty-one reference genes from the antler tips of Chinese sika deer were selected to test for the normalization of expression levels during different growth stages. These genes were tested by RT-qPCR and ranked according to the stability of their expression using two different methods (implemented in geNorm and NormFinder). Based on different algorithms and analytical procedures, our results clearly indicate RPL40 and Gpx as the most stable reference genes of our pool.