DOI QR코드

DOI QR Code

Assessment of Suitable Reference Genes for RT-qPCR Normalization with Developmental Samples in Pacific Abalone Haliotis discus hannai

  • Lee, Sang Yoon (Department of Marine Bio-Materials and Aquaculture, Pukyong National University) ;
  • Park, Choul-Ji (Genetics and Breeding Research Center, National Institute of Fisheries Science) ;
  • Nam, Yoon Kwon (Department of Marine Bio-Materials and Aquaculture, Pukyong National University)
  • Received : 2019.09.28
  • Accepted : 2019.10.28
  • Published : 2019.12.31

Abstract

Potential utility of 14 candidate housekeeping genes as normalization reference for RT-qPCR analysis with developmental samples (fertilized eggs to late veliger larvae) in Pacific abalone Haliotis discus hannai was evaluated using four different statistical algorithms (geNorm, NormFinder, BestKeeper and comparative ΔCT method). Different algorithms identified different genes as the best candidates, and geometric mean-based final ranking from the most to the least stable expression was as follow: RPL5, RPL4, RPS18, RPL8, RPL7, UBE2, RPL7A, GAPDH, RPL36, PPIB, EF1A, ACTB and B-TU. The findings were further validated via relative quantification of metallothionein (MT) transcripts using the stable and unstable reference genes, and expression levels of MT were greatly influenced according to the choice of reference genes. In overall, our data suggest that RPL5 and RPS18, either singly or in combination, are appropriate for normalizing gene expression in developmental samples of this abalone species, whereas ACTB, B-TU and EF1A are less stable and not recommended. In addition, our findings propose that standard deviations in geometric ranking as well as geometric mean itself should also be taken into account for the final selection of reference gene(s). This study could be a useful basis to facilitate the generation of accurate and reliable RT-qPCR data with developmental samples in this abalone species.

Keywords

References

  1. Alves RN, Gomes SA, Stueber K, Tine M, Thorne MAS, Smaradottir H, Reinhard R, Clark MS, Ronnestad I, Power DM. 2016. The transcriptome of metamorphosing flatfish. BMC Genomics 17:413. https://doi.org/10.1186/s12864-016-2699-x
  2. Andersen CL, Jensen JL, Orntoft 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. https://doi.org/10.1158/0008-5472.CAN-04-0496
  3. 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. https://doi.org/10.1152/physiolgenomics.00025.2005
  4. Blaxter M. 2013. Development: the maternal-zygotic transition revisited. Curr. Biol. 24:R72-75. https://doi.org/10.1016/j.cub.2013.11.051
  5. Breuss MW, Leca I, Gstrein T, Hansen AH, Keays DA. 2017. Tubulins and brain development - the origin of functional specification. Mol. Cell. Neuro. 84:58-67. https://doi.org/10.1016/j.mcn.2017.03.002
  6. Bunnell TM, Burbach BJ, Shimizu Y, Ervasti JM. 2011. ${\beta}$-Actin specifically controls cell growth, migration, and the G-actin pool. Mol. Biol. Cell 22:4047-4058. https://doi.org/10.1091/mbc.E11-06-0582
  7. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT. 2009. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 55:611-622. https://doi.org/10.1373/clinchem.2008.112797
  8. Cho YS, Lee SY, Kim KH, Nam YK. 2008. Differential modulations of two glyceraldehyde 3-phosphate dehydrogenase mRNAs in response to bacterial and viral challenges in a marine teleost Oplegnathus fasciatus (Perciformes). Fish Shellfish Immunol. 25:472-476. https://doi.org/10.1016/j.fsi.2008.07.007
  9. Das B, Cai L, Carter MG, Piao YL, Sharov AA, Ko MSH, Brown DD. 2006. Gene expression changes at metamorphosis induced by thyroid hormone in Xenopus laevis tadpoles. Dev. Biol. 291:342-355. https://doi.org/10.1016/j.ydbio.2005.12.032
  10. De Santis C, Smith-Keune C, Jerry DR. 2011. Normalizing RTqPCR data: are we getting the right answers? An appraisal of normalization approaches and internal reference genes from a case study in the finfish Lates calcarifer. Mar Biotechnol. 13:170-180. https://doi.org/10.1007/s10126-010-9277-z
  11. Deschamps J, Duboule D. 2017. Embryonic timing, axial stem cells, chromatin dynamics, and the Hox clock. Genes Dev. 31:1406-1416. https://doi.org/10.1101/gad.303123.117
  12. Doak SH, Zair Z. 2012. Real-time reverse-transcription polymerase chain reaction: technical considerations for gene expression analysis. In: Parry JM, Parry EM (Eds), Genetic Toxicology: Principles and Methods, Methods in Molecular Biology. Vol. 817. Springer, NY, pp 251-270.
  13. Du Y, Zhang L, Xu F, Huang B, Zhang G, Li L. 2013. Validation of housekeeping genes as internal controls for studying gene expression during Pacific oyster (Crassostrea gigas) development by quantitative real-time PCR. Fish Shellfish Immunol. 34:939-945. https://doi.org/10.1016/j.fsi.2012.12.007
  14. Glare EM, Divjak M, Bailey MJ Walters EH. 2002. ${\beta}$-Actin and GAPDH housekeeping gene expression in asthmatic airways is variable and not suitable for normalising mRNA levels. Thorax 57:765-770. https://doi.org/10.1136/thorax.57.9.765
  15. Guenin S, Mauriat M, Pelloux J, Van Wuytswinkel O, Bellini C, Gutierrez L. 2009. Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditionsspecific, validation of references. J. Exp. Bot. 60:487-493. https://doi.org/10.1093/jxb/ern305
  16. Harvey SA, Sealy I, Kettleborough R, Fenyes F, White R, Stemple D, Smith JC. 2013. Identification of the zebrafish maternal and paternal transcriptomes. Development 140:2703-2710. https://doi.org/10.1242/dev.095091
  17. Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J. 2007. qBase relative quantification framework and software for management and automated analysis of realtime quantitative PCR data. Genome Biol. 8:R19. https://doi.org/10.1186/gb-2007-8-2-r19
  18. Lee SY, Nam YK. 2016a. Evaluation of reference genes for RTqPCR study in abalone Haliotis discus hannai during heavy metal overload stress. Fish. Aquat. Sci. 19:21. https://doi.org/10.1186/s41240-016-0022-z
  19. Lee SY, Nam YK. 2016b. Transcriptional responses of metallothionein gene to different stress factors in Pacific abalone (Haliotis discus hannai ). Fish Shellfish Immunol. 58:530-541. https://doi.org/10.1016/j.fsi.2016.09.030
  20. Li R, Shen Y. 2013. An old method facing a new challenge: revisiting housekeeping proteins as internal reference control for neuroscience research. Life Sci. 92:747-751. https://doi.org/10.1016/j.lfs.2013.02.014
  21. Liu MM, Davey JW, Jackson DJ, Blaxter ML, Davison A. 2014. A conserved set of maternal genes? Insight from a molluscan transcriptome. Int. J. Dev. Biol. 58:501-511. https://doi.org/10.1387/ijdb.140121ad
  22. Lopez-Landavery EA, Portillo-Lopez A, Gallardo-Escarate C, Rio-Portilla MAD. 2014. Selection of reference genes as internal controls for gene expression in tissues of red abalone Haliotis rufescens (Mollusca, Vetigastropoda; Swainson, 1822). Gene 549:258-265. https://doi.org/10.1016/j.gene.2014.08.002
  23. Mao H, Wang DH, Yang WX. 2012. Involvement of metallothionein in the development of aquatic invertebrate. Aquatic Toxicol. 110-111:208-2013. https://doi.org/10.1016/j.aquatox.2012.01.018
  24. Nakayama T, Okada N, Yoshikawa M, Asaka D, Kuboki A, Kojima H, Tanaka Y, Haruna S. 2018. Assessment of suitable reference genes for RT-qPCR studies in chronic rhinosinusitis. Sci. Rep. 8:1568. https://doi.org/10.1038/s41598-018-19834-9
  25. Park CJ, Kim SY. 2013. Abalone aquaculture in Korea. J Shellfish Res. 32:17-19. https://doi.org/10.2983/035.032.0104
  26. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP. 2004. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: Bestkeeper-Excelbased tool using pair-wise correlations. Biotechnol. Lett. 26:509-515. https://doi.org/10.1023/B:BILE.0000019559.84305.47
  27. Praggastis SA, Thummel CS. 2017. Right time, right place: the temporal regulation of developmental gene expression. Genes Dev. 31:847-848. https://doi.org/10.1101/gad.301002.117
  28. Qiu R, Sun B, Fang S, Sun Li, Liu X. 2013. Identification of normalization factors for quantitative real-time RT-PCR analysis of gene expression in Pacific abalone Haliotis discus hannai. Chin. J. Oceanol. Limnol. 31:421-430. https://doi.org/10.1007/s00343-013-2221-0
  29. Romney AL, Podrabsky JE. 2017. Transcriptomic analysis of maternally provisioned cues for phenotypic plasticity in the annual killifish Austrofundulus limnaeus. EvoDevo 8:6. https://doi.org/10.1186/s13227-017-0069-7
  30. Schmittgen TD, Livak KJ. 2008. Analyzing real-time PCR data by the comparative CT method. Nat. Protoc. 3:1101-1108. https://doi.org/10.1038/nprot.2008.73
  31. Searcy-Bernal R, Perez-Sanchez E, Anguiano-Beltran C, Flores-Aguilar R. 2007. Metamorphosis and postlarval growth of abalone Haliotis rufescens in a Mexican commercial hatchery. J. Shellfish Res. 26:783-787. https://doi.org/10.2983/0730-8000(2007)26[783:MAPGOA]2.0.CO;2
  32. Sikand K, Singh J, Ebron JS, Shukla GC. 2012. Housekeeping gene selection advisory: glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and ${\beta}$-actin are targets of miR-644a. PLoS One 7:e47510. https://doi.org/10.1371/journal.pone.0047510
  33. Silver N, Best S, Jiang J, Thein SL. 2006. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol. Biol. 7:33. https://doi.org/10.1186/1471-2199-7-33
  34. Song H, Dang X, He YQ, Zhang T, Wang HY. 2017. Selection of housekeeping genes as internal controls for quantitative RT-PCR analysis of the veined rapa whelk (Rapana venosa). PeerJ 5:e3398. https://doi.org/10.7717/peerj.3398
  35. Taylor DA, Thompson EL, Nair SV, Raftos DA. 2013. Differential effects of metal contamination on the transcript expression of immune- and stress-response genes in the Sydney Rock oyster, Saccostrea glomerata. Environ Pollt. 178:65-71. https://doi.org/10.1016/j.envpol.2013.02.027
  36. Udvardi MK, Czechowski T, Scheible WR. 2008. Eleven golden rules of quantitative RT-PCR. Plant Cell 20:1736-1737. https://doi.org/10.1105/tpc.108.061143
  37. 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:research0034.1-0034.11.
  38. Wan Q, Whang I, Choi CY, Lee JS, Lee J. 2011. Validation of housekeeping genes as internal controls for studying biomarkers of endocrine-disrupting chemicals in disk abalone by real-time PCR. Comp Biochem. Physiol. C 153:259-268.
  39. Yuan M, Lu Y, Zhu X, Wan H, Shakeel M, Zhan S, Jin BR, Li J. 2014. Selection and evaluation of potential reference genes for gene expression analysis in the brown planthopper, Nilaparvata lugens (Hemiptera: Delphacidae) using reversetranscription quantitative PCR. PLoS One 9:e86503. https://doi.org/10.1371/journal.pone.0086503
  40. Zainuddin A, Chua KH, Rahim NA, Makpol S. 2010. Effect of experimental treatment on GAPDH mRNA expression as a housekeeping gene in human diploid fibroblasts. BMC Mol. Biol. 11:59. https://doi.org/10.1186/1471-2199-11-59
  41. Zhao L, Liu L, Wang S, Wang H, Jiang J. 2016. Transcriptome profiles of metamorphosis in the ornamented pygmy frog Microhyla fissipes clarify the functions of thyroid hormone receptors in metamorphosis. Sci. Rep. 6:27310. https://doi.org/10.1038/srep27310