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Current Protein & Peptide Science

Editor-in-Chief

ISSN (Print): 1389-2037
ISSN (Online): 1875-5550

Review Article

Efficient High-throughput Techniques for the Analysis of Disease- Resistant Plant Varieties and Detection of Food Adulteration

Author(s): Romesh Kumar Salgotra* and Javaid Akhter Bhat*

Volume 23, Issue 1, 2022

Published on: 23 December, 2021

Page: [20 - 32] Pages: 13

DOI: 10.2174/1389203723666211223111238

Price: $65

Abstract

Over the past two decades, the advances in the next generation sequencing (NGS) platforms have led to the identification of numerous genes/QTLs at high-resolution for their potential use in crop improvement. The genomic resources generated through these high-throughput sequencing techniques have been efficiently used in screening of particular gene of interest particularly for numerous types of plant stresses and quality traits. Subsequently, the identified-markers linked to particular trait have been used in Marker-Assisted Backcross Breeding (MABB) activities. Besides, these markers are also being used to catalogue the food crops for detection of adulteration to improve the quality of food. With the advancement of technologies, the genomic resources are originating with new markers; however, to use these markers efficiently in crop breeding, High-Throughput Techniques (HTT) such as multiplex PCR and Capillary Electrophoresis (CE) can be exploited. Robustness, ease of operation, good reproducibility and low cost are the main advantages of multiplex PCR and CE. The CE is capable of separating and characterizing proteins with simplicity, speed and small sample requirements. Keeping in view the availability of vast data generated through NGS techniques and development of numerous markers, there is a need to use these resources efficiently in crop improvement programmes. In summary, this review describes the use of molecular markers in the screening of resistance genes in breeding programme and detection of adulterations in food crops using high-throughput techniques.

Keywords: Biotic stress, genomic approach, NGS technique, varietal mixture, quality, security.

Graphical Abstract
[1]
D’Argenio, V. The high-throughput analyses era: are we ready for the data struggle? High Throughput, 2018, 7(1), 8.
[http://dx.doi.org/10.3390/ht7010008] [PMID: 29498666]
[2]
Bhat, J.A.; Ali, S.; Salgotra, R.K.; Mir, Z.A.; Dutta, S.; Jadon, V.; Tyagi, A.; Mushtaq, M.; Jain, N.; Singh, P.K.; Singh, G.P.; Prabhu, K.V. Genomic selection in the Era of next generation sequencing for complex traits in plant breeding. Front. Genet., 2016, 7, 221.
[http://dx.doi.org/10.3389/fgene.2016.00221] [PMID: 28083016]
[3]
Bhat, J.A.; Deshmukh, R.; Zhao, T.; Patil, G.; Deokar, A.; Shinde, S.; Chaudhary, J. Harnessing high-throughput phenotyping and genotyping for enhanced drought tolerance in crop plants. J. Biotechnol., 2020, 324, 248-260.
[http://dx.doi.org/10.1016/j.jbiotec.2020.11.010] [PMID: 33186658]
[4]
Sanger, F.; Nicklen, S.; Coulson, A.R. DNA sequencing with chain-terminating inhibitors. Proc. Natl. Acad. Sci. USA, 1977, 74(12), 5463-5467.
[http://dx.doi.org/10.1073/pnas.74.12.5463] [PMID: 271968]
[5]
D’Argenio, V.; Petrillo, M.; Pasanisi, D.; Pagliarulo, C.; Colicchio, R.; Talà, A.; de Biase, M.S.; Zanfardino, M.; Scolamiero, E.; Pagliuca, C.; Gaballo, A.; Cicatiello, A.G.; Cantiello, P.; Postiglione, I.; Naso, B.; Boccia, A.; Durante, M.; Cozzuto, L.; Salvatore, P.; Paolella, G.; Salvatore, F.; Alifano, P. The complete 12 Mb genome and transcriptome of Nonomuraea gerenzanensis with new insights into its duplicated “magic” RNA polymerase. Sci. Rep., 2016, 6(1), 18.
[http://dx.doi.org/10.1038/s41598-016-0025-0] [PMID: 28442708]
[6]
Horai, M.; Mishima, H.; Hayashida, C.; Kinoshita, A.; Nakane, Y.; Matsuo, T.; Tsuruda, K.; Yanagihara, K.; Sato, S.; Imanishi, D.; Imaizumi, Y.; Hata, T.; Miyazaki, Y.; Yoshiura, K.I. Detection of de novo single nucleotide variants in offspring of atomic-bomb survivors close to the hypocenter by whole-genome sequencing. J. Hum. Genet., 2018, 63(3), 357-363.
[http://dx.doi.org/10.1038/s10038-017-0392-9] [PMID: 29279608]
[7]
Calhoun, J.D.; Vanoye, C.G.; Kok, F.; George, A.L., Jr; Kearney, J.A. Characterization of a KCNB1 variant associated with autism, intellectual disability, and epilepsy. Neurol. Genet., 2017, 3(6), e198.
[http://dx.doi.org/10.1212/NXG.0000000000000198] [PMID: 29264390]
[8]
Miller, E.M.; Patterson, N.E.; Zechmeister, J.M.; Bejerano-Sagie, M.; Delio, M.; Patel, K.; Ravi, N.; Quispe-Tintaya, W.; Maslov, A.; Simmons, N.; Castaldi, M.; Vijg, J.; Karabakhtsian, R.G.; Greally, J.M.; Kuo, D.Y.S.; Montagna, C. Development and validation of a targeted next generation DNA sequencing panel outperforming whole exome sequencing for the identification of clinically relevant genetic variants. Oncotarget, 2017, 8(60), 102033-102045.
[http://dx.doi.org/10.18632/oncotarget.22116] [PMID: 29254223]
[9]
Nunziato, M.; Starnone, F.; Lombardo, B.; Pensabene, M.; Condello, C.; Verdesca, F.; Carlomagno, C.; De Placido, S.; Pastore, L.; Salvatore, F.; D’Argenio, V. Fast detection of a BRCA2 large genomic duplication by next generation sequencing as a single procedure: a case report. Int. J. Mol. Sci., 2017, 18(11), 2487.
[http://dx.doi.org/10.3390/ijms18112487] [PMID: 29165356]
[10]
D’Argenio, V.; Precone, V.; Casaburi, G.; Miele, E.; Martinelli, M.; Staiano, A.; Salvatore, F.; Sacchetti, L. An altered gut microbiome profile in a child affected by Crohn’s disease normalized after nutritional therapy. Am. J. Gastroenterol., 2013, 108(5), 851-852.
[http://dx.doi.org/10.1038/ajg.2013.46] [PMID: 23644964]
[11]
Widschwendter, M.; Evans, I.; Jones, A.; Ghazali, S.; Reisel, D.; Ryan, A.; Gentry-Maharaj, A.; Zikan, M.; Cibula, D.; Eichner, J.; Alunni-Fabbroni, M.; Koch, J.; Janni, W.J.; Paprotka, T.; Wittenberger, T.; Menon, U.; Wahl, B.; Rack, B.; Lempiäinen, H. Methylation patterns in serum DNA for early identification of disseminated breast cancer. Genome Med., 2017, 9(1), 115.
[http://dx.doi.org/10.1186/s13073-017-0499-9] [PMID: 29268762]
[12]
Nardelli, C.; Granata, I.; Iaffaldano, L.; D’Argenio, V.; Del Monaco, V.; Maruotti, G.M.; Omodei, D.; Del Vecchio, L.; Martinelli, P.; Salvatore, F.; Guarracino, M.R.; Sacchetti, L.; Pastore, L. miR-138/miR-222 overexpression characterizes the miRNome of amniotic mesenchymal stem cells in obesity. Stem Cells Dev., 2017, 26(1), 4-14.
[http://dx.doi.org/10.1089/scd.2016.0127] [PMID: 27762728]
[13]
Panagopoulos, I.; Gorunova, L.; Spetalen, S.; Bassarova, A.; Beiske, K.; Micci, F.; Heim, S. Fusion of the genes ataxin 2 like, ATXN2L, and Janus kinase 2, JAK2, in cutaneous CD4 positive T-cell lymphoma. Oncotarget, 2017, 8(61), 103775-103784.
[http://dx.doi.org/10.18632/oncotarget.21790] [PMID: 29262599]
[14]
Precone, V.; Del Monaco, V.; Esposito, M.V.; De Palma, F.D.; Ruocco, A.; Salvatore, F.; D’Argenio, V. Cracking the code of human diseases using next-generation sequencing: applications, challenges, and perspectives. BioMed Res. Int., 2015, 2015, 161648.
[http://dx.doi.org/10.1155/2015/161648] [PMID: 26665001]
[15]
Tyson, J.R.; O’Neil, N.J.; Jain, M.; Olsen, H.E.; Hieter, P.; Snutch, T.P. MinION-based long-read sequencing and assembly extends the Caenorhabditis elegans reference genome. Genome Res., 2017, 28, 266-274.
[16]
Tomkowiak, A.; Bocianowski, J.; Radzikowska, D.; Kowalczewski, P.Ł. Selection of parental material to maximize heterosis using SNP and SilicoDarT markers in maize. Plants, 2019, 8(9), 349.
[http://dx.doi.org/10.3390/plants8090349] [PMID: 31540117]
[17]
Sandhu, C.; Qureshi, A.; Emili, A. Panomics for precision medicine. Trends Mol. Med., 2018, 24(1), 85-101.
[http://dx.doi.org/10.1016/j.molmed.2017.11.001] [PMID: 29217119]
[18]
Wrigley, C.W.; Bekes, F. Grain protein composition as a document of wheat quality type: new approaches to varietal identification. In: Wheat Quality Elucidation: The Bushuk Legacy; Ng, P.K.W.; Wrigley, W., Eds.; American Assoc. Cereal Chemists: St Paul, MN, USA, 2002; pp. 65-86.
[19]
Raina, M.; Salgotra, R.K. Multiplex PCR assay for detection of major bacterial blight resistance genes Xa21 and xa13 in Basmati (Oryza sativa L.). Res. J. Biotechnol., 2020, 15(2), 40-46.
[20]
Sint, D.; Raso, L.; Traugott, M. Advances in multiplex PCR: balancing primer efficiencies and improving detection success. Methods Ecol. Evol., 2012, 3(5), 898-905.
[http://dx.doi.org/10.1111/j.2041-210X.2012.00215.x] [PMID: 23549328]
[21]
Umesha, S.; Avinash, P. ultiplex PCR for simultaneous identification of Ralstonia solanacearum and Xanthomonas perforans. 3 Biotech, 2015, 5, 245-252.
[22]
Liu, B.; Zhou, X.; Zhang, L.; Liu, W.; Dan, X.; Shi, C.; Shi, X. Development of a novel multiplex PCR assay for the identification of Salmonella enterica, Typhimurium and Enteritidis. Food Control, 2012, 27, , 87e93..
[23]
Laney, A.G.; Acosta-Leal, R.; Rotenberg, D. Optimized yellow dwarf virus multiplex PCR assay reveals a common occurrence of barley yellow dwarf virus-PAS in kansas winter wheat. Plant Health Prog., 2018, 19, 37-43.
[http://dx.doi.org/10.1094/PHP-09-17-0056-RS]
[24]
Das, A.K.; Nerkar, S.; Gawande, N.; Thakre, N.; Kumar, A. SCAR marker for Phytophthora nicotianae and a multiplex PCR assay for simultaneous detection of P. nicotianae and Candidatus Liberibacter asiaticus in citrus. J. Appl. Microbiol., 2019, 127(4), 1172-1183.
[http://dx.doi.org/10.1111/jam.14392] [PMID: 31329353]
[25]
Bangratz, M.; Wonni, I.; Kini, K.; Sondo, M.; Brugidou, C.; Béna, G.; Gnacko, F.; Barro, M.; Koebnik, R.; Silué, D.; Tollenaere, C. Design of a new multiplex PCR assay for rice pathogenic bacteria detection and its application to infer disease incidence and detect co-infection in rice fields in Burkina Faso. PLoS One, 2020, 15(4), e0232115.
[http://dx.doi.org/10.1371/journal.pone.0232115] [PMID: 32339192]
[26]
Coburn, J.R.; Temnykh, S.V.; Paul, E.M.; McCouch, S.R. A set of multiplex panels of microsatellite markers for rapid molecular characterization of rice accessions. Crop Sci., 2002, 42, 2092-2099.
[http://dx.doi.org/10.2135/cropsci2002.2092]
[27]
Bellagamba, F.; Comincini, S.; Ferretti, L.; Valfrè, F.; Moretti, V.M. Application of quantitative real-time PCR in the detection of prion-protein gene species-specific DNA sequences in animal meals and feedstuffs. J. Food Prot., 2006, 69(4), 891-896.
[http://dx.doi.org/10.4315/0362-028X-69.4.891] [PMID: 16629035]
[28]
Saini, N.; Jain, N.; Jain, S.; Jain, R.K. Assessment of genetic diversity within and among Basmati and non-Basmati rice varieties using AFLP, ISSR and SSR markers. Euphytica, 2004, 140, 133-146.
[http://dx.doi.org/10.1007/s10681-004-2510-y]
[29]
Hittalmani, S.; Parco, A.; Mew, T.V.; Zeigler, R.S.; Huang, N. Fine mapping and DNA marker assisted pyramiding of three major genes for blast resistance of rice. Theor. Appl. Genet., 2000, 100, 1121-1128.
[http://dx.doi.org/10.1007/s001220051395]
[30]
Salgotra, R.K.; Millwood, R.J.; Agarwal, S.; Stewart, C.N. Jr High-throughput functional marker assay for detection of Xa/xa and fgr genes in rice (Oryza sativa L.). Electrophoresis, 2011, 32(16), 2216-2222.
[http://dx.doi.org/10.1002/elps.201100196] [PMID: 21793000]
[31]
Findlay, I.; Taylor, A.; Quirke, P.; Frazier, R.; Urquhart, A. DNA fingerprinting from single cells. Nature, 1997, 389(6651), 555-556.
[http://dx.doi.org/10.1038/39225] [PMID: 9335493]
[32]
Vallone, P.M.; Hill, C.R.; Butler, J.M. Demonstration of rapid multiplex PCR amplification involving 16 genetic loci. Forensic Sci. Int. Genet., 2008, 3(1), 42-45.
[http://dx.doi.org/10.1016/j.fsigen.2008.09.005] [PMID: 19083866]
[33]
Archak, S.; Lakshminarayanareddy, V.; Nagaraju, J. High-throughput multiplex microsatellite marker assay for detection and quantification of adulteration in Basmati rice (Oryza sativa). Electrophoresis, 2007, 28(14), 2396-2405.
[http://dx.doi.org/10.1002/elps.200600646] [PMID: 17577195]
[34]
Wang, Y.; Wang, Y.; Ma, A.J.; Li, D.X.; Luo, L.J.; Liu, D.X.; Jin, D.; Liu, K.; Ye, C.Y. Rapid and sensitive isothermal detection of nucleic-acid sequence by multiple cross displacement amplification. Sci. Rep., 2015, 5, 11902.
[http://dx.doi.org/10.1038/srep11902] [PMID: 26154567]
[35]
Gibson-Daw, G.; Crenshaw, K.; McCord, B. Optimization of ultrahigh-speed multiplex PCR for forensic analysis. Anal. Bioanal. Chem., 2018, 410(1), 235-245.
[http://dx.doi.org/10.1007/s00216-017-0715-x] [PMID: 29188309]
[36]
Lookhart, G.L.; Bean, S. A fast method for wheat cultivar differentiation using capillary zone electrophoresis. Cereal Chem., 1995, 72, 312-316.
[37]
Frazier, R. Capillary electrophoresis in food analysis; Labtech: Business Briefing, 2004, 42-45.
[38]
Kaisoon, O.; Siriamornpun, S.; Meeso, N. Distinction between cereal genotypes based on the protein and DNA composition of the grain by capillary electrophoresis. World Appl. Sci. J., 2008, 4, 384-395.
[39]
Hjerten, S. High-performance electrophoresis: the electrophoretic counterpart of high-performance liquid chromatography. J. Chromatogr. A, 1983, 270, 1-6.
[http://dx.doi.org/10.1016/S0021-9673(01)96347-2]
[40]
Cottet, H.; Gareil, P.; Viovy, J.L. The effect of blob size and network dynamics on the size-based separation of polystyrenesulfonates by capillary electrophoresis in the presence of entangled polymer solutions. Electrophoresis, 1998, 19(12), 2151-2162.
[http://dx.doi.org/10.1002/elps.1150191219] [PMID: 9761197]
[41]
Sunada, W.M.; Blanch, H.W. Polymeric separation media for capillary electrophoresis of nucleic acids. Electrophoresis, 1997, 18(12-13), 2243-2254.
[http://dx.doi.org/10.1002/elps.1150181215] [PMID: 9456039]
[42]
Hieter, P.; Boguski, M. Functional genomics: it’s all how you read it. Science, 1997, 278(5338), 601-602.
[http://dx.doi.org/10.1126/science.278.5338.601] [PMID: 9381168]
[43]
Temnykh, S.; DeClerck, G.; Lukashova, A.; Lipovich, L.; Cartinhour, S.; McCouch, S. Computational and experimental analysis of microsatellites in rice (Oryza sativa L.): frequency, length variation, transposon associations, and genetic marker potential. Genome Res., 2001, 11(8), 1441-1452.
[http://dx.doi.org/10.1101/gr.184001] [PMID: 11483586]
[44]
Doley, J.J.; Doley, J.L. A rapid total DNA preparation procedure for fresh plant tissue. Focus, 1990, 12, 13-15.
[45]
Perumalsamy, S.; Bharani, M.; Sudha, M.; Nagarajan, P.; Arul, L.; Sarawathi, R.; Balasubramanian, R.J. Functional marker-assisted selection for bacterial leaf blight resistance genes in rice (Oryza sativa L.). Plant Breed., 2010, 129, 400-406.
[46]
Bassam, B.J.; Caetano-Anolles, G. A new electrophoresis technique to separate microsatellite alleles. Appl. Biochem. Biotechnol., 1983, 42, 181-188.
[http://dx.doi.org/10.1007/BF02788051]
[47]
Kelly, J.D.; Afanador, L.; Haley, S.D. Pyramiding genes for resistance to bean common mosaic virus. Euphytica, 1995, 82, 207-212.
[http://dx.doi.org/10.1007/BF00029562]
[48]
Caranta, C.; Palloix, A.; Gebre-Selassie, K.; Lefebvre, V.; Moury, B.; Daubèze, A.M. A complementation of 2 genes originating from susceptible capsicum-annuum lines confers a new and complete resistance to pepper venous mottle virus. Phytopathology, 1996, 86, 739-743.
[http://dx.doi.org/10.1094/Phyto-86-739]
[49]
Singh, M.; Mallick, N.; Chand, S.; Kumari, P.; Sharma, J.B.; Sivasamy, M.; Jayaprakash, P.; Prabhu, K.V.; Jha, S.K. Vinod, Marker-assisted pyramiding of Thinopyrum-derived leaf rust resistance genes Lr19 and Lr24 in bread wheat variety HD2733. J. Genet., 2017, 96(6), 951-957.
[http://dx.doi.org/10.1007/s12041-017-0859-7] [PMID: 29321354]
[50]
Shasidhara, Y.; Variatha, M.T.; Vishwakarma, M.K.; Manohar, S.S.; Gangurdea, S.S.; Sriswathia, M.; Sudinia, H.K.; Dobariyac, K.L.; Berad, S.K.; Thankappan Radhakrishnand, T.; Pandeya, M.K.; Janilaa, P.; Varshney, R.K. Improvement of three popular Indian groundnutvarieties for foliar disease resistance and high oleicacid using SSR markers and SNP array in marker-assisted backcrossing. Crop J., 2020, 8, 1-15.
[http://dx.doi.org/10.1016/j.cj.2019.07.001]
[51]
Mannur, D.M.; Babbar, A.; Thudi, M.; Sabbavarapu, M.M.; Roorkiwal, M.; Yeri, S.B.; Bansal, V.P.; Jayalakshmi, S.K.; Singh Yadav, S.; Rathore, A.; Chamarthi, S.K.; Mallikarjuna, B.P.; Gaur, P.M.; Varshney, R.K. Super Annigeri 1 and improved JG 74: two Fusarium wilt-resistant introgression lines developed using marker-assisted backcrossing approach in chickpea (Cicer arietinum L.). Mol. Breed., 2019, 39(1), 2.
[http://dx.doi.org/10.1007/s11032-018-0908-9] [PMID: 30631246]
[52]
Saxena, R.K.; Hake, A.; Bohra, A.; Khan, A.W.; Hingane, A.; Sultana, R.; Singh, I.P.; Naik, S.J.S.; Varshney, R.K. A diagnostic marker kit for Fusarium wilt and sterility mosaic diseases resistance in pigeonpea. Theor. Appl. Genet., 2021, 134(1), 367-379.
[http://dx.doi.org/10.1007/s00122-020-03702-0] [PMID: 33079215]
[53]
Saghai Maroof, M.A.; Jeong, S.C.; Gunduz, I.; Tucker, D.M.; Buss, G.R.; Tolin, S.A. Pyramiding of soybean mosaic virus resistance genes by marker‐assisted selection. Crop Sci., 2008, 48, 517-526.
[http://dx.doi.org/10.2135/cropsci2007.08.0479]
[54]
Mori, K.; Sakamoto, Y.; Mukojima, N.; Tamiya, S.; Nakao, T.; Ishii, T.; Hosaka, K. Development of a multiplex PCR method for simultaneous detection of diagnostic DNA markers of five disease and pest resistance genes in potato. Euphytica, 2011, 180, 347-355.
[http://dx.doi.org/10.1007/s10681-011-0381-6]
[55]
Liu, S.; Hall, M.D.; Griffey, C.A.; McKendry, A.L. Meta-Analysis of QTL associated with fusarium head blight resistance in wheat. Crop Sci., 2009, 49(6), 1955.
[http://dx.doi.org/10.2135/cropsci2009.03.0115]
[56]
Hanzalová, T. Multiplex PCR assay to detect rust resistance genes Lr26 and Lr37 in Wheat. Czech J. Genet. Plant Breed., 2010, 46, 85-89.
[http://dx.doi.org/10.17221/32/2010-CJGPB]
[57]
Aloyce, R.C.; Tairo, F.; Sseruwagi, P.; Rey, M.E.; Ndunguru, J. A single-tube duplex and multiplex PCR for simultaneous detection of four cassava mosaic begomovirus species in cassava plants. J. Virol. Methods, 2013, 189(1), 148-156.
[http://dx.doi.org/10.1016/j.jviromet.2012.10.007] [PMID: 23174160]
[58]
Rogozina, E.; Terentjeva, E.V.; Potokina, E.; Yurkina, E.N.; Nikulin, A.; Alekseev, Y. Llc Syntol. “Multiplex PCR-Based identification of potato genotypes as donors in breeding for resistance to diseases and pests. Agric. Biol., (Basel), 2019, 54(1), 19-30.
[http://dx.doi.org/10.15389/agrobiology.2019.1.19eng]
[59]
Yap, R.; Hsu, Y.C.; Wu, Y.P.; Lin, Y.R.; Kuo, C.W. Multiplex PCR genotyping for five bacterial blight resistance genes applied to marker-assisted selection in rice (Oryza sativa). Plant Breed., 2016, 35(3), 309-317.
[http://dx.doi.org/10.1111/pbr.12368]
[60]
Hajira, S.K.; Sundaram, R.M.; Laha, G.S.; Yugander, A.; Balachandran, S.M.; Viraktamath, B.C.; Sujatha, K.; Balachiranjeevi, C.H.; Pranathi, K.; Anila, M.; Bhaskar, S.; Abhilash, V.; Mahadevaswamy, V.K.; Kousik, M. Dilip kumar, T.; Harika, G.; Rekha, G. Single-tube, functional marker-based multiplex PCR assay for simultaneous detection of major bacterial blight resistance genes Xa21, xa13 and xa5 in rice. Rice Sci., 2016, 23(3), 144-151.
[http://dx.doi.org/10.1016/j.rsci.2015.11.004]
[61]
Ndayihanzamaso, P.; Karangwa, P.; Mostert, D.; Mahuku, G.; Blomme, G.; Beed, F.; Viljoen, A. The development of a multiplex PCR assay for the detection of Fusarium oxysporum F. sp. cubense lineage VI strains in east and central Africa; Eur. J. Plant Path, 2020.
[http://dx.doi.org/10.1007/s10658-020-02092-9]
[62]
Ellison, E.E.; Nagalakshmi, U.; Gamo, M.E.; Huang, P.J.; Dinesh-Kumar, S.; Voytas, D.F. Multiplexed heritable gene editing using RNA viruses and mobile single guide RNAs. Nat. Plants, 2020, 6(6), 620-624.
[http://dx.doi.org/10.1038/s41477-020-0670-y] [PMID: 32483329]
[63]
Hsu, Y.C.; Chiu, C.H.; Yap, R.; Tseng, Y.C.; Wu, Y.P. Pyramiding bacterial blight resistance genes in Tainung82 for broad-spectrum resistance using marker-assisted selection. Int. J. Mol. Sci., 2020, 21(4), 1281.
[http://dx.doi.org/10.3390/ijms21041281] [PMID: 32074964]
[64]
Ramkumar, G.; Prahalada, G.D.; Hechanova, S.L.; Vinarao, R.; Jena, K.K. Development and validation of SNP-based functional codominant markers for two major disease resistance genes in rice (O. sativa L.) Mol. Breed., 2015, 35, 129-2015.
[http://dx.doi.org/10.1007/s11032-015-0323-4]
[65]
Fjellstrom, R.; Conaway-Bormans, C.A.; McClung, A.; Marchetti, M.A.; Shank, A.A.; Park, W. Development of DNA markers suitable for marker assisted selection of three pi genes conferring resistance to multiple Pyricularia grisea pathotypes. Crop Sci., 2004, 44, 1790-1798.
[http://dx.doi.org/10.2135/cropsci2004.1790]
[66]
Sinha, D.K.; Smith, C.M. Selection of reference genes for expression analysis in Diuraphis noxia (Hemiptera: Aphididae) fed on resistant and susceptible wheat plants. Sci. Rep., 2014, 4(1), 5059.
[http://dx.doi.org/10.1038/srep05059] [PMID: 24862828]
[67]
Ilnitskaya, E.T.; Makarkina, M.V.; Tokmakov, S.V.; Naumova, L.G. DNA-marker based identification of the RPV3 gene determining downy mildew resistance in grapevines. Vavilovskii Zhurnal Genet. Selektsii, 2018, 22, 703-707.
[http://dx.doi.org/10.18699/VJ18.413]
[68]
Thakur, H.; Jindal, S.K.; Sharma, A.; Dhaliwal, M.S. Chilli leaf curl virus disease: a serious threat for chilli cultivation. J. Plant Dis. Prot., 2018, 2018(125), 239-249.
[http://dx.doi.org/10.1007/s41348-018-0146-8]
[69]
Rojas, E.C.; Jensen, B.; Jørgensen, H.J.L.; Latz, M.; Esteban, P.; Ding, Y.; Collinge, D.B. Selection of fungal endophytes with biocontrol potential against Fusarium head blight in wheat. Biol. Control, 2020, 2020, 104222.
[http://dx.doi.org/10.1016/j.biocontrol.2020.104222]
[70]
Gupta, V.; Dorsey, G.; Hubbard, A.E.; Rosenthal, P.J.; Greenhouse, B. Gel versus capillary electrophoresis genotyping for categorizing treatment outcomes in two anti-malarial trials in Uganda. Malar. J., 2010, 9, 19.
[http://dx.doi.org/10.1186/1475-2875-9-19] [PMID: 20074380]
[71]
McCudden, C.R.; Mathews, S.P.; Hainsworth, S.A.; Chapman, J.F.; Hammett-Stabler, C.A.; Willis, M.S.; Grenache, D.G. Performance comparison of capillary and agarose gel electrophoresis for the identification and characterization of monoclonal immunoglobulins. Am. J. Clin. Pathol., 2008, 129(3), 451-458.
[http://dx.doi.org/10.1309/6KT8N49BRNVVVBT1] [PMID: 18285269]
[72]
Nagaraju, J.; Kathirvel, M.; Kumar, R.R.; Siddiq, E.A.; Hasnain, S.E. Genetic analysis of traditional and evolved Basmati and non-Basmati rice varieties by using fluorescence-based ISSR-PCR and SSR markers. Proc. Natl. Acad. Sci. USA, 2002, 99(9), 5836-5841.
[http://dx.doi.org/10.1073/pnas.042099099] [PMID: 11959900]
[73]
Mahajan, S.; Kaur, S. Quality analysis of indian basmati rice grains using top-hat transformation. Int. J. Comput. Appl., 2014, 94, 42-48.
[74]
Salgotra, R.K.; Bhat, J.; Binita Gupta, B.B.; Sharma, S. Determination of genetic relationship among basmati and non-basmati rice (Oryza sativa L.) genotypes from North-West Himalayas using microsatellite markers. Int. J. Biotechnol., 2017, 16(1), 68-75.
[75]
Jain, S.; Jain, R.K.; McCouch, S.R. Genetic analysis of Indian aromatic and quality rice (Oryza sativa L.) germplasm using panels of fluorescently-labeled microsatellite markers. Theor. Appl. Genet., 2004, 109(5), 965-977.
[http://dx.doi.org/10.1007/s00122-004-1700-2] [PMID: 15309297]
[76]
Zhou, P.P.; Zhang, J.Z.; You, Y.H.; Wu, Y.N. Detection of genetically modified crops by combination of multiplex PCR and low-density DNA microarray. Biomed. Environ. Sci., 2008, 21(1), 53-62.
[http://dx.doi.org/10.1016/S0895-3988(08)60007-0] [PMID: 18478979]
[77]
Demeke, T.; Giroux, R.W.; Reitmeier, S.; Simon, S.L. Development of a polymerase chain reaction assay for detection of three canola transgenes. J. Am. Oil Chem. Soc., 2002, 79(10), 1015-1019.
[http://dx.doi.org/10.1007/s11746-002-0595-2]
[78]
Lu, B.R.; Yang, X.; Ellstrand, N.C. Fitness correlates of crop transgene flow into weedy populations: a case study of weedy rice in China and other examples. Evol. Appl., 2016, 9(7), 857-870.
[http://dx.doi.org/10.1111/eva.12377] [PMID: 27468304]
[79]
Babaei, A.; Arshami, J.; Haghparast, A.; Danesh Mesgaran, M. Effects of saffron (Crocus sativus) petal ethanolic extract on hematology, antibody response, and spleen histology in rats. Avicenna J. Phytomed., 2014, 4(2), 103-109.
[PMID: 25050307]
[80]
Moon, Y.S.; Choi, W.S.; Park, E.S.; Bae, I.K.; Choi, S.D.; Paek, O.; Kim, S.H.; Chun, H.S.; Lee, S.E. Antifungal and antiaflatoxigenic methylenedioxy-containing compounds and piperine-like synthetic compounds. Toxins (Basel), 2016, 8(8), 240.
[http://dx.doi.org/10.3390/toxins8080240] [PMID: 27537912]
[81]
Soffritti, G.; Busconi, M.; Sánchez, R.A.; Thiercelin, J.M.; Polissiou, M.; Roldán, M.; Fernández, J.A. Genetic and epigenetic approaches for the possible detection of adulteration and auto-adulteration in saffron (Crocus sativus L.) spice. Molecules, 2016, 21(3), 343.
[http://dx.doi.org/10.3390/molecules21030343] [PMID: 26978342]
[82]
Li, F.; Dong, C.; Yang, T.; Ma, J.; Zhang, S.; Wei, C.; Wan, X.; Zhang, Z. Seasonal theanine accumulation and related gene expression in the roots and leaf buds of tea plants (Camellia sinensis L.). Front. Plant Sci., 2019, 10, 1397.
[http://dx.doi.org/10.3389/fpls.2019.01397] [PMID: 31749819]
[83]
Han, E.H.; Cho, K.; Goo, Y.; Kim, M.; Shin, Y.W.; Kim, Y.H.; Lee, S.W. Development of molecular markers, based on chloroplast and ribosomal DNA regions, to discriminate three popular medicinal plant species, Cynanchum wilfordii, Cynanchum auriculatum, and Polygonum multiflorum. Mol. Biol. Rep., 2016, 43(4), 323-332.
[http://dx.doi.org/10.1007/s11033-016-3959-1] [PMID: 26902862]
[84]
Abid, S.; Mohanan, P.; Kaliraj, L.; Park, J.K.; Ahn, J.C.; Yang, D.C. Development of species-specific chloroplast markers for the authentication of Gynostemma pentaphyllum and their distribution in the Korean peninsula. Fitoterapia, 2019, 138, 104295.
[http://dx.doi.org/10.1016/j.fitote.2019.104295] [PMID: 31400481]
[85]
Bazakos, C.; Dulger, A.O.; Uncu, A.T.; Spaniolas, S.; Spano, T.; Kalaitzis, P. A SNP-based PCR-RFLP capillary electrophoresis analysis for the identification of the varietal origin of olive oils. Food Chem., 2012, 134(4), 2411-2418.
[http://dx.doi.org/10.1016/j.foodchem.2012.04.031] [PMID: 23442703]
[86]
Uncu, A.T.; Uncu, A.O. Plastid trnH-psbA intergenic spacer serves as a PCR-based marker to detect common grain adulterants of coffee (Coffea arabica L.). Food Control, 2018, 91, 32-39.
[http://dx.doi.org/10.1016/j.foodcont.2018.03.029]
[87]
Vemireddy, L.R.; Archak, S.; Nagaraju, J. Capillary electrophoresis is essential for microsatellite marker based detection and quantification of adulteration of Basmati rice (Oryza sativa). J. Agric. Food Chem., 2007, 55(20), 8112-8117.
[http://dx.doi.org/10.1021/jf0714517] [PMID: 17867634]
[88]
Anupama, K.; Pranathi, K.; Meenakshi Sundaram, R. Assessment of genetic purity of bulked-seed of rice CMS lines using capillary electrophoresis. Electrophoresis, 2020, 41(20), 1749-1751.
[http://dx.doi.org/10.1002/elps.201900429] [PMID: 32357250]
[89]
Bonetti, A.; Marotti, I.; Catizone, P.; Dinelli, G.; Maietti, A.; Tedeschi, P.; Brandolini, V. Compared use of HPLC and FZCE for cluster analysis of Triticum sp. and for the identification of T. durum adulteration. J. Agric. Food Chem., 2004, 52(13), 4080-4089.
[http://dx.doi.org/10.1021/jf034881f] [PMID: 15212451]
[90]
Bazakos, C.; Spaniolas, S.; Kalaitzis, P. DNA-based approaches for traceability and authentication of olive oil; Prod. Olive Tree, 2016.
[http://dx.doi.org/10.5772/64494]
[91]
García-Villalba, R.; Carrasco-Pancorbo, A.; Vázquez-Martín, A.; Oliveras-Ferraros, C.; Menéndez, J.A.; Segura-Carretero, A.; Fernández-Gutiérrez, A.A. 2-D-HPLC-CE platform coupled to ESI-TOF-MS to characterize the phenolic fraction in olive oil. Electrophoresis, 2009, 30(15), 2688-2701.
[http://dx.doi.org/10.1002/elps.200800807] [PMID: 19650044]
[92]
Kowalczyk, T.; Ciborowski, M.; Kisluk, J.; Kretowski, A.; Barbas, C. Mass spectrometry based proteomics and metabolomics in personalized oncology. Biochim. Biophys. Acta Mol. Basis Dis., 2020, 1866(5), 165690.
[http://dx.doi.org/10.1016/j.bbadis.2020.165690] [PMID: 31962175]
[93]
Yan, Y.M.; Hsam, S.L.K.; Yu, J.Z.; Jiang, Y.; Zeller, F.J. Genetic polymorphisms at Gli-Dt gliadin loci in Aegilops tauschii as revealed by acid polyacrylamide gel and capillary electrophoresis. Plant Breed., 2003, 122(2), 120-124.
[http://dx.doi.org/10.1046/j.1439-0523.2003.00824.x]
[94]
Piergiovanni, A. Minor wheat protein fractions analysis by using capillary zone electrophoresis. Separations, 2016, 3(2), 17.
[http://dx.doi.org/10.3390/separations3020017]
[95]
Shewry, P.R. Seed storage proteins of economically important cereals. In: Advances in Cereal Science and Technology; Pomeranlz, I., Ed.; American Association of Cereal Chemists: St. Paul, Minnesota, 1985; pp. 1-83.
[96]
Bean, S.R.; Lookhart, G.L. High-performance capillary electrophoresis of meat, dairy, and cereal proteins. Electrophoresis, 2001, 22(19), 4207-4215.
[http://dx.doi.org/10.1002/1522-2683(200111)22:19<4207:AID-ELPS4207>3.0.CO;2-S] [PMID: 11824638]
[97]
Sutton, K.H. Variation among high molecular weight subunits of glutenin detected by capillary electrophoresis. J. Cereal Sci., 1997, 25, 9-16.
[http://dx.doi.org/10.1006/jcrs.1996.9999]
[98]
Galindo-Luján, R.; Pont, L.; Sanz-Nebot, V.; Benavente, F. Classification of quinoa varieties based on protein fingerprinting by capillary electrophoresis with ultraviolet absorption diode array detection and advanced chemometrics. Food Chem., 2021, 341(Pt 1), 128207.
[http://dx.doi.org/10.1016/j.foodchem.2020.128207] [PMID: 33035861]
[99]
Piergiovanni, A.R.; Taranto, G. Specific differentiation in Vicia genus by means of capillary electrophoresis. J. Chromatogr. A, 2005, 1069(2), 253-260.
[http://dx.doi.org/10.1016/j.chroma.2005.01.062] [PMID: 15830952]
[100]
Huang, C.; Nie, X.; Shen, C.; You, C.; Li, W.; Zhao, W.; Zhang, X.; Lin, Z. Population structure and genetic basis of the agronomic traits of upland cotton in China revealed by a genome-wide association study using high-density SNPs. Plant Biotechnol. J., 2017, 15(11), 1374-1386.
[http://dx.doi.org/10.1111/pbi.12722] [PMID: 28301713]
[101]
Elshire, R.J.; Glaubitz, J.C.; Sun, Q.; Poland, J.A.; Kawamoto, K.; Buckler, E.S.; Mitchell, S.E. A robust, simple genotyping-by-sequencing (GBS) approach for high diversity species. PLoS One, 2011, 6(5), e19379.
[http://dx.doi.org/10.1371/journal.pone.0019379] [PMID: 21573248]
[102]
Sonah, H.; Bastien, M.; Iquira, E.; Tardivel, A.; Légaré, G.; Boyle, B.; Normandeau, É.; Laroche, J.; Larose, S.; Jean, M.; Belzile, F. An improved genotyping by sequencing (GBS) approach offering increased versatility and efficiency of SNP discovery and genotyping. PLoS One, 2013, 8(1), e54603.
[http://dx.doi.org/10.1371/journal.pone.0054603] [PMID: 23372741]
[103]
Tardivel, A.; Sonah, H.; Belzile, F.; O’Donoughue, L.S. Rapid identification of alleles at the soybean maturity gene E3 using genotyping by sequencing and a haplotype-based approach. Plant Genome, 2014, 7, 1-9.
[http://dx.doi.org/10.3835/plantgenome2013.10.0034]

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