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Genome-wide identification of internal reference genes for normalization of gene expression values during endosperm development in wheat

  • Junyi Mu
  • Lin Chen
  • Yunsong Gu
  • Luning Duan
  • Shichen Han
  • Yaxuan Li
  • Yueming Yan
  • Xiaohui LiEmail author
Plant Genetics • Original Paper
  • 3 Downloads

Abstract

Internal reference genes that are stably expressed are essential for normalization in comparative expression analyses. However, gene expression varies significantly among species, organisms, tissues, developmental stages, stresses, and treatments. Therefore, identification of stably expressed reference genes in developmental endosperm of bread wheat is important for expression analysis of endosperm genes. As the first study to systematically screen for reference genes across different developmental stages of wheat endosperm, nine genes were selected from among 76 relatively stable genes based on high-throughput RNA sequencing data. The expression stability of these candidate genes and five traditional reference genes was assessed by real-time quantitative PCR combined with three independent algorithms: geNorm, NormFinder, and BestKeeper. The results showed that ATG8d was the most stable gene during wheat endosperm development, followed by Ta54227, while the housekeeping gene GAPDH, commonly used as an internal reference, was the least stable. ATG8d and Ta54227 together formed the optimal combination of reference genes. Comparative expression analysis of glutenin genes indicated that credible quantification could be achieved by normalization against ATG8d in developmental endosperm. The stably expressed gene characterized here can act as a proper internal reference for expression analysis of wheat endosperm genes, especially nutrient- and nutrient synthesis–related genes.

Keywords

Wheat Endosperm Internal reference gene RNA-Seq RT-qPCR Glutenin 

Notes

Author contributions

XHL conceived and designed the experiment. JYM, LC, YSG, LND, and SCH performed the experiment. JYM and LC analyzed the data. YXL and YMY provided technical assistance and scientific discussion. JYM and XHL wrote the paper.

Funding

This research was supported by grants from National Key R&D Program of China (2016ZX08009003-004), National Natural Science Foundation of China (31571652), the Natural Science Foundation of Beijing (6162002, 6122002), and the Youth Innovative Research Team of Capital Normal University.

Compliance with ethical standards

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.

Supplementary material

13353_2019_503_MOESM1_ESM.docx (1.9 mb)
ESM 1 (DOCX 1992 kb)

References

  1. Anders S, Pyl PT, Huber W (2015) HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31(2):166–169CrossRefGoogle Scholar
  2. 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):5245–5250CrossRefGoogle Scholar
  3. Brunner AM, Yakovlev IA, Strauss SH (2004) Validating internal controls for quantitative plant gene expression studies. BMC Plant Biol 4:14CrossRefGoogle Scholar
  4. 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(1):5–17CrossRefGoogle Scholar
  5. D’Ovidio R, Masci S (2004) The low-molecular-weight glutenin subunits of wheat gluten. J Cereal Sci 39:321–339CrossRefGoogle Scholar
  6. Dekkers BJW, Willems L, Bassel GW, van Bolderen-Veldkamp RP, Ligterink W, Hilhorst HWM, Bentsink L (2012) Identification of reference genes for RT-qPCR expression analysis in Arabidopsis and tomato seeds. Plant Cell Physiol 53:28–37CrossRefGoogle Scholar
  7. Dheda K, Huggett JF, Bustin SA, Johnson MA, Rook G, Zumla A (2004) Validation of housekeeping genes for normalizing RNA expression in real-time PCR. Biotechniques 37:112–119CrossRefGoogle Scholar
  8. Dong GQ, Ni ZF, Yao YY, Nie XL, Sun QX (2007) Wheat Dof transcription factor WPBF interacts with TaQM and activates transcription of an alpha-gliadin gene during wheat seed development. Plant Mol Biol 63:73–84CrossRefGoogle Scholar
  9. Evers T, Millar S (2002) Cereal grain structure and development: some implications for quality. J Cereal Sci 36:261–284CrossRefGoogle Scholar
  10. Fernández-Aparicio M, Huang K, Wafula EK, Honaas LA, Wickett NJ, Timko MP, Depamphilis CW, Yoder JI, Westwood JH (2013) Application of qRT-PCR and RNA-Seq analysis for the identification of housekeeping genes useful for normalization of gene expression values during Striga hermonthica development. Mol Biol Rep 40(4):3395–3407CrossRefGoogle Scholar
  11. Guo WW, Yang H, Liu YQ, Gao YJ, Ni ZF, Peng HR, Xin MM, Hu ZR, Sun QX, Yao YY (2015) The wheat transcription factor TaGAMyb recruits histone acetyltransferase and activates the expression of a high-molecular-weight glutenin subunit gene. Plant J 84:347–359CrossRefGoogle Scholar
  12. Guzmán C, Alvarez JB (2016) Wheat waxy proteins: polymorphism, molecular characterization and effects on starch properties. Theor Appl Genet 129(1):1–16CrossRefGoogle Scholar
  13. Hu LX, Li HY, Chen L, Lou YH, Amombo E, Fu JM (2015) RNA-seq for gene identification and transcript profiling in relation to root growth of bermudagrass (Cynodon dactylon) under salinity stress. BMC Genomics 16:575CrossRefGoogle Scholar
  14. Hurkman WJ, Tanaka CK, Vensel WH, Thilmony R, Altenbach SB (2013) Comparative proteomic analysis of the effect of temperature and fertilizer on gliadin and glutenin accumulation in the developing endosperm and flour from Triticum aestivum L. cv. Butte 86. Proteome Sci 11(1):8CrossRefGoogle Scholar
  15. Joseph JT, Poolakkalody NJ, Shah JM (2018) Plant reference genes for development and stress response studies. J Biosci 43(1):173–187CrossRefGoogle Scholar
  16. Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12(4):357–360CrossRefGoogle Scholar
  17. Li XH, Wang K, Wang SL, Gao LY, Xie XX, Hsam SLK, Zeller FJ, Yan YM (2010) Molecular characterization and comparative transcriptional analysis of LMW-m-type genes from wheat (Triticum aestivum L.) and Aegilops species. Theor Appl Genet 121(5):845–856CrossRefGoogle Scholar
  18. Lin F, Jiang L, Liu YH, Lv YD, Dai HX, Zhao H (2014) Genome-wide identification of housekeeping genes in maize. Plant Mol Biol 86:543CrossRefGoogle Scholar
  19. Liu W, Zhang YZ, Gao X, Wang K, Wang SL, Zhang Y, He ZH, Ma WJ, Yan YM (2012) Comparative proteome analysis of glutenin synthesis and accumulation in developing grains between superior and poor quality bread wheat cultivars. J Sci Food Agric 92(1):106–115CrossRefGoogle Scholar
  20. Liu J, Huang S, Niu X, Chen D, Chen Q, Tian L, Xiao FM, Liu YS (2018) Genome-wide identification and validation of new reference genes for transcript normalization in developmental and post-harvested fruits of Actinidia chinensis. Gene 645:1–6CrossRefGoogle Scholar
  21. Nakatogawa H, Ichimura Y, Ohsumi Y (2007) Atg8, a ubiquitin-like protein required for autophagosome formation, mediates membrane tethering and hemifusion. Cell 130(1):165–178CrossRefGoogle Scholar
  22. 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 10:11CrossRefGoogle Scholar
  23. 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(6):509–515CrossRefGoogle Scholar
  24. Seo E, Woo J, Park E, Bertolani SJ, Siegel JB, Choi D, Dinesh-Kumar SP (2016) Comparative analyses of ubiquitin-like ATG8 and cysteine protease ATG4 autophagy genes in the plant lineage and cross-kingdom processing of ATG8 by ATG4. Autophagy 12(11):2054–2068CrossRefGoogle Scholar
  25. Shewry PR, Halford NG (2002) Cereal seed storage proteins: structures, properties and role in grain utilization. J Exp Bot 53:947–958CrossRefGoogle Scholar
  26. Stanton KA, Edger PP, Puzey JR, Kinser T, Cheng P, Vernon DM, Forsthoefel NR, Cooley AM (2017) A whole-transcriptome approach to evaluating reference genes for quantitative gene expression studies: a case study in Mimulus. G3-Genes Genom Genet 7(4):1085–1095Google Scholar
  27. Suzuki T, Higgins PJ, Crawford DR (2000) Control selection for RNA quantitation. Biotechniques 29:332–337CrossRefGoogle Scholar
  28. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van BMJ, 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(5):511–515CrossRefGoogle Scholar
  29. 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):1–12CrossRefGoogle Scholar
  30. Vasil IK (2007) Molecular genetic improvement of cereals: transgenic wheat (Triticum aestivum L.). Plant Cell Rep 26:1133–1154CrossRefGoogle Scholar
  31. Wu D, Dong J, Yao YJ, Zhao WC, Gao X (2015) Identification and evaluation of endogenous control genes for use in quantitative RT-PCR during wheat (Triticum aestivum L.) grain filling. Genet Mol Res 14(3):10530–10542CrossRefGoogle Scholar
  32. Xie ZP, Nair U, Klionsky DJ (2008) Atg8 controls phagophore expansion during autophagosome formation. Mol Biol Cell 19(8):3290–3298CrossRefGoogle Scholar
  33. Xu H, Bao JD, Dai JS, Li YQ, Zhu Y (2015) Genome-wide identification of new reference genes for qRT-PCR normalization under high temperature stress in rice endosperm. PLoS One 10(11):e0142015CrossRefGoogle Scholar
  34. Yorimitsu T, Klionsky DJ (2005) Autophagy: molecular machinery for self-eating. Cell Death Differ 12(S2):1542CrossRefGoogle Scholar
  35. Yue WJ, Nie XJ, Cui LC, Zhi YQ, Zhang T, Du XH, Song WN (2018) Genome-wide sequence and expressional analysis of autophagy gene family in bread wheat (Triticum aestivum L.). J Plant Physiol 229:7–21CrossRefGoogle Scholar

Copyright information

© Institute of Plant Genetics, Polish Academy of Sciences, Poznan 2019

Authors and Affiliations

  1. 1.Key Laboratory of Genetics and Biotechnology, College of Life ScienceCapital Normal UniversityBeijingChina

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