Skip to main content
SpringerLink
Log in

Reference gene selection for real-time quantitative PCR normalization in Hemarthria compressa and Hemarthria altissima leaf tissue

  • Original Article
  • Published:
Molecular Biology Reports Aims and scope Submit manuscript

Abstract

Hemarthria compressa and Hemarthria altissima are widely used as livestock forage and play important roles in tropical and subtropical grassland agricultural systems promoting healthy ecological environment and the development of animal husbandry. Leaf tissue of “Yaan” limpograss (H. compressa) and “H255” whip grass (H. altissima) were used to test the mRNA expression levels of 12 reference genes using RT-qPCR. The Delta-Ct method, BestKeeper (ver. 1.0), Genorm (ver. 3.5), Normfinder (ver. 0.953) and RefFinder were used to analyze the expression stability of the 12 reference genes under drought, salt, acid-aluminum and cold stresses to provide significant technical support for the study of gene expression under various abiotic stresses in Hemarthria. The results showed that the candidate reference genes showed divergent expression levels under various abiotic stresses. Among the genes that were selected, CL18892 showed the highest expression stability under salt stress in the leaf tissue. eEF-1α was the most stable gene under cold and acid-aluminum stresses and CL16384 was comparatively the most suitable genes under drought stress. As a whole, according to RefFinder analysis, CYP5, BMK.74327 and CL21527 were the most suitable reference genes for studying the effects of abiotic stress in Hemarthria. In general, CL16812 and CL18038 were not suitable reference genes under abiotic stress conditions that were examined in this study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Laloum T, Martín G, Duque P (2018) Alternative splicing control of abiotic stress responses. Trends Plant Sci 23(2):140

    Article  CAS  PubMed  Google Scholar 

  2. Willis CG, Brad R, Primack RB, Miller-Rushing AJ, Davis CC (2008) Phylogenetic patterns of species loss in Thoreau’s woods are driven by climate change. Proc Natl Acad Sci USA 105(44):17029–17033

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Rytz TC, Miller MJ, Mcloughlin F, Augustine RC, Marshall RS, Juan YT, Charng YY, Scalf M, Smith LM, Vierstra RD (2018) SUMOylome profiling reveals a diverse array of nuclear targets modified by the SUMO ligase SIZ1 during heat stress. Plant Cell 30(5):1077–1099

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Yan H, Zhang A, Chen J, He X, Xu B, Xie G, Miao Z, Zhang X, Huang L (2017) Genome-wide analysis of the PvHsp20 family in switchgrass: motif, genomic organization, and identification of stress or developmental-related Hsp20s. Front Plant Sci 8:1024

    Article  PubMed  PubMed Central  Google Scholar 

  5. Yang Y, Qi M, Mei C (2010) Endogenous salicylic acid protects rice plants from oxidative damage caused by aging as well as biotic and abiotic stress. Plant J 40(6):909–919

    Article  CAS  Google Scholar 

  6. Xin M, Wang Y, Yao Y, Xie C, Peng H, Ni Z, Sun Q (2010) Diverse set of microRNAs are responsive to powdery mildew infection and heat stress in wheat (Triticum aestivum L.). BMC Plant Biol 10(1):123

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Yang L, Li W, Xin X, Liping S, Jiaowen P, Xiangpei K, Maoying Z, Dequan L (2013) ZmLEA3, a multifunctional group 3 LEA protein from maize (Zea mays L.), is involved in biotic and abiotic stresses. Plant Cell Physiol 54(6):944–959

    Article  CAS  Google Scholar 

  8. Gachon C, Mingam A, Charrier B (2004) Real-time PCR: what relevance to plant studies? J Exp Bot 55(402):1445–1454

    Article  CAS  PubMed  Google Scholar 

  9. Tania N, Hands RE, Bustin SA (2006) Quantification of mRNA using real-time RT-PCR. Nat Protoc 1(3):1559

    Article  CAS  Google Scholar 

  10. Sugden D, Winter PD (2008) Quantification of mRNA using real time RT-PCR. Humana Press, New York

    Book  Google Scholar 

  11. Udvardi MK, Czechowski T, Scheible WR (2008) Eleven golden rules of quantitative RT-PCR. Plant Cell 20(7):1736–1737

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Radonić A, Thulke S, Mackay IM, Landt O, Siegert W, Nitsche A (2004) Guideline to reference gene selection for quantitative real-time PCR. Biochem Biophys Res Commun 313(4):856–862

    Article  PubMed  CAS  Google Scholar 

  13. Suzuki T, Higgins PJ, Crawford DR (2000) Control selection for RNA quantitation. Biotechniques 29(2):332–337

    Article  CAS  PubMed  Google Scholar 

  14. Tunbridge EM, Eastwood SL, Harrison PJ (2011) Changed relative to what? Housekeeping genes and normalization strategies in human brain gene expression studies. Biol Psychiatry 69(2):173–179

    Article  CAS  PubMed  Google Scholar 

  15. Cappelli K, Felicetti M, Capomaccio S, Spinsanti G, Silvestrelli M, Supplizi AV (2008) Exercise induced stress in horses: selection of the most stable reference genes for quantitative RT-PCR normalization. BMC Mol Biol 9(1):1–8

    Article  CAS  Google Scholar 

  16. Brunner AM, Yakovlev IA, Strauss SH (2004) Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol 4(1):14

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Czechowski T, Bari RP, Stitt M, Scheible WR, Udvardi MK (2010) Real-time RT-PCR profiling of over 1400 Arabidopsis transcription factors: unprecedented sensitivity reveals novel root- and shoot-specific genes. Plant J 38(2):366–379

    Article  CAS  Google Scholar 

  18. Mukesh J, Aashima N, 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(2):646–651

    Article  CAS  Google Scholar 

  19. Bas A, Forsberg G, Hammarström S, Hammarström M-L (2010) Utility of the housekeeping genes 18S rRNA, beta-actin and glyceraldehyde-3-phosphate-dehydrogenase for normalization in real-time quantitative reverse transcriptase-polymerase chain reaction analysis of gene expression in human T lymphocytes. Scand J Immunol 59(6):566–573

    Article  Google Scholar 

  20. De Oliveira LA, Breton MC, Bastolla FM, Camargo SDS, Margis R, Frazzon J, Pasquali G (2012) Reference genes for the normalization of gene expression in Eucalyptus species. Plant Cell Physiol 53(2):405

    Article  PubMed  CAS  Google Scholar 

  21. Hong SM, Bahn SC, Lyu A, Jung HS, Ahn JH (2010) Identification and testing of superior reference genes for a starting pool of transcript normalization in Arabidopsis. Plant Cell Physiol 51(10):1694

    Article  CAS  PubMed  Google Scholar 

  22. Schmidt GW, Delaney SK (2010) Stable internal reference genes for normalization of real-time RT-PCR in tobacco (Nicotiana tabacum) during development and abiotic stress. Mol Genet Genomics 283(3):233–241

    Article  CAS  PubMed  Google Scholar 

  23. 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(2–3):291–295

    Article  CAS  PubMed  Google Scholar 

  24. Carvalho DDD, Goncalez DA, Ghisi OMAA (1996) Agronomic evaluation of seven accessions of Hemarthria altissima (Poir.) Stapf et C.E. Hubb in Pindamonhangaba, Sao Paulo. Rev Soc Bras Zootec

  25. Rumball PJ, Lambert JP (1981) Plant introduction trials. N Z J Exp Agric 9(1):5

    Google Scholar 

  26. Woods PW, Couchman JN, Barlow HA (1996) Variation and adaptation in limpograss (Hemarthria altissima). Proc N Z Grassl Assoc 57:49–53

    Google Scholar 

  27. Huang LK, Zhang XQ, Xie WG, Zhang J, Cheng L, Yan HD (2012) Molecular diversity and population structure of the forage grass Hemarthria compressa (Poaceae) in south China based on SRAP markers. Genet Mol Res 11(3):2441–2450

    Article  PubMed  Google Scholar 

  28. Zhang J, Huang X, Huang D, Zhang Y, Huang L, Lu L, Yan H (2016) Studies on genetic diversity and phylogenetic relationships of limpograss (Hemarthria altissima) and related species based on combined chloroplast DNA intergenic spacer data. Biochem Syst Ecol 69:91–100

    Article  CAS  Google Scholar 

  29. Migocka M, Papierniak A (2011) Identification of suitable reference genes for studying gene expression in cucumber plants subjected to abiotic stress and growth regulators. Mol Breed 28(3):343–357

    Article  Google Scholar 

  30. Huang L, Yan H, Jiang X, Zhang X, Zhang Y, Huang X, Zhang Y, Miao J, Xu B, Frazier T (2014) Evaluation of candidate reference genes for normalization of quantitative RT-PCR in switchgrass under various abiotic stress conditions. Bioenergy Res 7(4):1201–1211

    Article  CAS  Google Scholar 

  31. Xiao-Hui C, Ai-Qing Z, Xin-Hui D et al (2017) Effects of aluminum stress on growth and physiological of five cultivars of Lolium multiflorum. Grassl Turf

  32. Huang X, Yan HD, Zhang XQ, Zhang J, Frazier TP, Huang DJ, Lu L, Huang LK, Liu W, Peng Y (2016) De novo transcriptome analysis and molecular marker development of two Hemarthria species. Front Plant Sci 7(610):496

    PubMed  PubMed Central  Google Scholar 

  33. Jacinta G, Nicholas E, Allen VD, Eduardo B (2014) Selection and validation of reference genes for gene expression analysis in switchgrass (Panicum virgatum) using quantitative real-time RT-PCR. PLoS ONE 9(3):e91474

    Article  CAS  Google Scholar 

  34. Chen YX (2016) Clone actin gene and establishment of quantitative real-time PCR from Hemarthria compressa. Guangdong Agric Sci 16

  35. 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(7):research0034.1

    Article  Google Scholar 

  36. Andersen CL, Jensen JL, 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(15):5245–5250

    Article  CAS  PubMed  Google Scholar 

  37. 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. Biotech Lett 26(6):509–515

    Article  CAS  Google Scholar 

  38. Silver N, Jiang BJ (2006) Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol Biol 7(1):33

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Zhu X, Li X, Chen W, Chen J, Lu W, Chen L, Fu D (2012) Evaluation of new reference genes in papaya for accurate transcript normalization under different experimental conditions. PLoS ONE 7(8):e44405

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Chen Y, Huang L, Yan H et al (2016) Cloning and characterization of an ABA-independent DREB transcription factor gene, HcDREB2, in Hemarthria compressa. Hereditas 153(1):3

    Article  PubMed  PubMed Central  Google Scholar 

  41. 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(1):112

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Jian B, Liu B, Bi Y, Hou W, Wu C, Han T (2008) Validation of internal control for gene expression study in soybean by quantitative real-time PCR. BMC Mol Biol 9(1):59

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  43. Jiang XM, Zhang XQ, Yan HD, Zhang Y, Yang ST, Huang LK (2014) Reference gene selection for real-time quantitative PCR normalization in switchgrass (Panicum virgatum L.) root tissue. J Agric Biotechnol 22(1):55–63

    CAS  Google Scholar 

  44. An YQ, Mcdowell JM, Huang S, Mckinney EC, Chambliss S, Meagher RB (2010) Strong, constitutive expression of the Arabidopsis ACT2/ACT8 actin subclass in vegetative tissues. Plant J 10(1):107–121

    Article  Google Scholar 

  45. Yan HD, Jiang XM, Zhang XQ, Huang LK (2014) Reference genes for qRT-PCR in perennial ryegrass (Lolium perenne L.) under various abiotic stresses. J Agric Biotechnol 22:1494–1501

    CAS  Google Scholar 

Download references

Acknowledgements

This study was funded by the Modern Agro-industry Technology Research System (CARS-34) and the Sichuan Province Breeding Research Grant (2016NYZ0039) and Modern Agricultural Industry System Sichuan Forage Innovation Team.

Author information

Author notes

  1. Yao Lin, Ailing Zhang, and Shengting Yang have contributed equally to this work.

Authors and Affiliations

  1. Department of Grassland Science, Faculty of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China

    Yao Lin, Ailing Zhang, Shengting Yang & Linkai Huang

Authors
  1. Yao Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ailing Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shengting Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Linkai Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Linkai Huang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 688 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, Y., Zhang, A., Yang, S. et al. Reference gene selection for real-time quantitative PCR normalization in Hemarthria compressa and Hemarthria altissima leaf tissue. Mol Biol Rep 46, 4763–4769 (2019). https://doi.org/10.1007/s11033-019-04922-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11033-019-04922-4

Keywords

Search

Navigation