Identification of the most suitable reference gene for gene expression studies with development and abiotic stress response in Bromus sterilis
Language English Country Great Britain, England Media electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
PubMed
34183710
PubMed Central
PMC8238991
DOI
10.1038/s41598-021-92780-1
PII: 10.1038/s41598-021-92780-1
Knihovny.cz E-resources
- MeSH
- Bromus genetics MeSH
- Gene Expression genetics MeSH
- Stress, Physiological genetics MeSH
- Genetic Techniques MeSH
- Real-Time Polymerase Chain Reaction methods MeSH
- Reference Standards MeSH
- Herbicide Resistance genetics MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Bromus sterilis is an annual weedy grass, causing high yield losses in winter cereals. Frequent use of herbicides had led to the evolution of herbicide resistance in this species. Mechanisms underlying herbicide resistance in B. sterilis must be uncovered because this problem is becoming a global threat. qRT-PCR and the next-generation sequencing technologies can elucidate the resistance mechanisms. Although qRT-PCR can calculate precise fold changes, its preciseness depends on the expression of reference genes. Regardless of stable expression in any given condition, no gene can act as a universal reference gene. Hence, it is necessary to identify the suitable reference gene for each species. To our knowledge, there are no reports on the suitable reference gene in any brome species so far. Thus, in this paper, the stability of eight genes was evaluated using qRT-PCR experiments followed by expression stability ranking via five most commonly used software for reference gene selection. Our findings suggest using a combination of 18S rRNA and ACCase to normalise the qRT-PCR data in B. sterilis. Besides, reference genes are also recommended for different experimental conditions. The present study outcomes will facilitate future molecular work in B. sterilis and other related grass species.
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Žd’árková V, Hamouzová K, Holec J, Janků J, Soukup J. Seed ecology of Bromus sterilis L. Julius-Kühn-Arch. 2014;443:156–164.
Jursík M, Kolářová M, Soukup J, Žďárková V. Effects of adjuvants and carriers on propoxycarbazone and pyroxsulam efficacy on Bromus sterilis in winter wheat. Plant Soil Environ. 2016;62:447–452. doi: 10.17221/273/2016-PSE. DOI
Žďárková V, Hamouzová K, Kolářová M, Soukup J. Germination responses to water potential in Bromus sterilis L. under different temperatures and light regimes. Plant Soil Environ. 2017;63:368–374. doi: 10.17221/406/2017-PSE. DOI
Davies LR, Hull R, Moss S, Neve P. The first cases of evolving glyphosate resistance in UK poverty brome (Bromus sterilis) populations. Weed Sci. 2019;67:41–47. doi: 10.1017/wsc.2018.61. DOI
Gaines TA, et al. Gene amplification confers glyphosate resistance in Amaranthus palmeri. PNAS. 2010;107:1029–1034. doi: 10.1073/pnas.0906649107. PubMed DOI PMC
Salas RA, Scott RC, Dayan FE, Burgos NR. EPSPS gene amplification in glyphosate-resistant Italian ryegrass (Lolium perenne ssp. multiflorum) populations from arkansas (United States) J. Agric. Food Chem. 2015;63:5885–5893. doi: 10.1021/acs.jafc.5b00018. PubMed DOI
Gaines TA, et al. RNA-Seq transcriptome analysis to identify genes involved in metabolism-based diclofop resistance in Lolium rigidum. Plant J. 2014;78:865–876. doi: 10.1111/tpj.12514. PubMed DOI
Chen J, et al. Selection of relatively exact reference genes for gene expression studies in goosegrass (Eleusine indica) under herbicide stress. Sci. Rep. 2017;7:46494. doi: 10.1038/srep46494. PubMed DOI PMC
Joseph JT, Poolakkalody NJ, Shah JM. Plant reference genes for development and stress response studies. J. Biosci. 2018;43:173–187. doi: 10.1007/s12038-017-9728-z. PubMed DOI
Nolan T, Hands RE, Bustin SA. Quantification of mRNA using real-time RT-PCR. Nat. Protoc. 2006;1:1559–1582. doi: 10.1038/nprot.2006.236. PubMed DOI
Ginzinger DG. Gene quantification using real-time quantitative PCR: An emerging technology hits the mainstream. Exp. Hematol. 2002;30:503–512. doi: 10.1016/S0301-472X(02)00806-8. PubMed DOI
Huggett J, Dheda K, Bustin S, Zumla A. Real-time RT-PCR normalisation; strategies and considerations. Genes Immun. 2005;6:279–284. doi: 10.1038/sj.gene.6364190. PubMed DOI
Guénin S, et al. Normalisation of qRT-PCR data: The necessity of adopting a systematic, experimental conditions-specific, validation of references. J. Exp. Bot. 2009;60:487–493. doi: 10.1093/jxb/ern305. PubMed DOI
Bustin S. Quantification of mRNA using real-time reverse transcription PCR (RT-PCR): Trends and problems. J. Mol. Endocrinol. 2002;29:23–39. doi: 10.1677/jme.0.0290023. PubMed DOI
Rocha AJ, Monteiro-Júnior JE, Freire JEC, Sousa AJS, Fonteles CSR. Real time PCR: The use of reference genes and essential rules required to obtain normalisation data reliable to quantitative gene expression. J. Mol. Biol. Res. 2015;5:45. doi: 10.5539/jmbr.v5n1p45. DOI
Chapman JR, Waldenström J. With reference to reference genes: A systematic review of endogenous controls in gene expression studies. PLoS ONE. 2015;10:e0141853. doi: 10.1371/journal.pone.0141853. PubMed DOI PMC
Nestorov J, Matić G, Elaković I, Tanić N. Gene expression studies: How to obtain accurate and reliable data by quantitative real-time RT PCR/izučavanje ekspresije gena: kako dobiti tačne i pouzdane podatke kvantitativnim rt pcr-om u realnom vremenu. J. Med. Biochem. 2013;32:325–338. doi: 10.2478/jomb-2014-0001. DOI
Kozera B, Rapacz M. Reference genes in real-time PCR. J. Appl. Genet. 2013;54:391–406. doi: 10.1007/s13353-013-0173-x. PubMed DOI PMC
Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible W-R. Genome-wide identification and testing of superior reference genes for transcript normalization in arabidopsis. Plant Physiol. 2005;139:5–17. doi: 10.1104/pp.105.063743. PubMed DOI PMC
Xu H, et al. Identification of reference genes for studying herbicide resistance mechanisms in Japanese foxtail (Alopecurus japonicus) Weed Sci. 2017;65:557–566. doi: 10.1017/wsc.2017.19. DOI
Hong S-Y, Seo PJ, Yang M-S, Xiang F, Park C-M. Exploring valid reference genes for gene expression studies in Brachypodium distachyon by real-time PCR. BMC Plant Biol. 2008;8:112. doi: 10.1186/1471-2229-8-112. PubMed DOI PMC
Gutierrez L, et al. 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. 2008;6:609–618. doi: 10.1111/j.1467-7652.2008.00346.x. PubMed DOI
Tong Z, Gao Z, Wang F, Zhou J, Zhang Z. Selection of reliable reference genes for gene expression studies in peach using real-time PCR. BMC Mol. Biol. 2009;10:71. doi: 10.1186/1471-2199-10-71. PubMed DOI PMC
Ramesh K, Matloob A, Aslam F, Florentine SK, Chauhan BS. Weeds in a changing climate: Vulnerabilities, consequences, and implications for future weed management. Front. Plant Sci. 2017;8:95. doi: 10.3389/fpls.2017.00095. PubMed DOI PMC
Sen MK, et al. Enhanced metabolism and target gene overexpression confer resistance against acetolactate synthase-inhibiting herbicides in Bromus sterilis. Pest Manag. Sci. 2021;77(4):2122–2128. doi: 10.1002/ps.6241. PubMed DOI
Davies LR, Onkokesung N, Brazier-Hicks M, Edwards R, Moss S. Detection and characterisation of resistance to acetolactate synthase inhibiting herbicides in Anisantha and Bromus species in the United Kingdom. Pest Manag. Sci. 2020;76:2473–2482. doi: 10.1002/ps.5788. PubMed DOI
Anthimidou E, Ntoanidou S, Madesis P, Eleftherohorinos I. Mechanisms of Lolium rigidum multiple resistance to ALS- and ACCase-inhibiting herbicides and their impact on plant fitness. Pestic. Biochem. Physiol. 2020;164:65–72. doi: 10.1016/j.pestbp.2019.12.010. PubMed DOI
Gaines TA, et al. Mechanisms of evolved herbicide resistance. J. Biol. Chem. 2020;295:10307–10330. doi: 10.1074/jbc.REV120.013572. PubMed DOI PMC
Pan L, Gao H, Xia W, Zhang T, Dong L. Establishing a herbicide-metabolising enzyme library in Beckmannia syzigachne to identify genes associated with metabolic resistance. J. Exp. Bot. 2016;67:1745–1757. doi: 10.1093/jxb/erv565. PubMed DOI
Jugulam M, Shyam C. Non-target-site resistance to herbicides: Recent developments. Plants. 2019;8:417. doi: 10.3390/plants8100417. PubMed DOI PMC
Akbarabadi A, Ismaili A, Kahrizi D, Firouzabadi FN. Validation of expression stability of reference genes in response to herbicide stress in wild oat (Avena ludoviciana) Cell Mol. Biol. (Noisy-le-grand) 2018;64:113–118. doi: 10.14715/cmb/2018.64.4.19. PubMed DOI
Ruduś I, Kępczyński J. Reference gene selection for molecular studies of dormancy in wild oat (Avena fatua L.) caryopses by RT-qPCR method. PLoS ONE. 2018;13:e0192343. doi: 10.1371/journal.pone.0192343. PubMed DOI PMC
Wrzesińska B, Kierzek R, Obrępalska-Stęplowska A. Evaluation of six commonly used reference genes for gene expression studies in herbicide-resistant Avena fatua biotypes. Weed Res. 2016;56:284–292. doi: 10.1111/wre.12209. DOI
Xu X, et al. Selection of relatively exact reference genes for gene expression studies in flixweed (Descurainia sophia) by quantitative real-time polymerase chain reaction. Pestic. Biochem. Physiol. 2016;127:59–66. doi: 10.1016/j.pestbp.2015.09.007. PubMed DOI
Jain M, Nijhawan A, Tyagi AK, Khurana JP. Validation of housekeeping genes as internal control for studying gene expression in rice by quantitative real-time PCR. Biochem. Biophys. Res. Commun. 2006;345:646–651. doi: 10.1016/j.bbrc.2006.04.140. PubMed DOI
Petit C, Pernin F, Heydel J-M, Délye C. Validation of a set of reference genes to study response to herbicide stress in grasses. BMC Res. Notes. 2012;5:18. doi: 10.1186/1756-0500-5-18. PubMed DOI PMC
Liu J, et al. Selection and evaluation of potential reference genes for gene expression analysis in Avena fatua Linn. Plant Protect. Sci. 2018;55:61–71. doi: 10.17221/20/2018-PPS. DOI
Roy A, Palli SR. Epigenetic modifications acetylation and deacetylation play important roles in juvenile hormone action. BMC Genomics. 2018;19:934. doi: 10.1186/s12864-018-5323-4. PubMed DOI PMC
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods. 2001;25:402–408. doi: 10.1006/meth.2001.1262. PubMed DOI