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Revealing the genetic diversity of maize (Zea mays L.) populations by phenotypic traits and DArTseq markers for variable resistance to fall armyworm

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The fall armyworm (FAW) is a gregarious insect pest causing substantial yield losses and crop failures in maize and related cereal crops in sub-Saharan Africa due to a lack of resistant varieties and integrated control options. Genetic variation for economic traits including resistance to the FAW damage is a prerequisite in maize improvement programs. The objective of this study was to determine the genetic diversity of 59 maize genotypes of diverse genetic background with variable resistance to fall armyworm, using phenotypic traits and SNP-based DArT markers. The test genotypes were profiled using agro-morphological traits, FAW damage parameters, and Diversity Array Technology Sequencing-derived single nucleotide polymorphism (SNP) markers. Significant (p < 0.001) differences were observed among the genotypes for 13 phenotypic traits with phenotypic coefficient of variation ranging from 2.19 to 51.79%. Notable phenotypic variation was observed for ear position, grain yield, FAW induced leaf and cob damage. The mean gene diversity and polymorphic information content were 0.29 and 0.23, respectively, reflecting a moderate level of genetic variation among the test genotypes when assessed using SNP markers. Analysis of the molecular variance revealed greater genetic variance within a population rather than between populations. Population structure and cluster analysis grouped the test populations into two main clusters. The following genetically divergent open pollinated varieties were selected with favourable agronomic performance and FAW resistance for population improvement or hybrid breeding: Pool 16, ZM 4236 and ZM 7114. The genetic diversity detected within and among the tested populations will facilitate the breeding of maize varieties incorporating farmer-preferred agronomic traits and FAW resistance in Zambia and related agro-ecologies.

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  • Abrahams P, Beale T, Cock M, Corniani N, Day R, Godwin J, Gomez J, Moreno PG, Murphy ST, Opon-Mensah B, Phiri N, Richards G, Pratt C, Silvestri S, Witt A (2017) Fall armyworm status- impacts and control options in Africa: Preliminary Evidence Note. UK: CABI.

  • Aci MM, Lupini A, Mauceri A, Morsli A, Khelifi L, Sunseri F (2018) Genetic variation and structure of maize populations form Saoura and Gourara oasis in Algerain Sahara. BMC Genet 19:51

    Article  PubMed  PubMed Central  Google Scholar 

  • Acquaah G (2009) Principles of plant genetics and breeding. Hoboken N. J Wiley & Sons, USA

    Google Scholar 

  • Adu GB, Badu-Apraku B, Akromah R, Garcia-Oliveira AL, Awuku FJ, Gedil M (2019) Genetic diversity and population structure of early-maturing tropical maize inbred lines using SNP markers. PLoS ONE 14(4):e0214810

    Article  CAS  Google Scholar 

  • Akbari M, Wenzl P, Caig V, Carling J, Xia L, Yang S, Uszynski G, Mohler V, Lehmensiek A, Kuchel H, Hayden MJ, Howes N, Sharp P, Vaughan P, Rathmell B, Huttner E, Kilian A (2006) Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome. Theor Appl Genet 113:1409–1420

    Article  CAS  PubMed  Google Scholar 

  • Balloux F, Moulin NL (2002) The estimation of population differentiation with microsatellite markers. Mol Ecol 11:155–165

    Article  PubMed  Google Scholar 

  • Baloch FS, Alsaleh A, Shahid MQ, Çiftçi V, de Miera LES, Aasim M, Nadeem MA, Aktas H, Ozkan H, Hatipoglu R (2017) A whole genome DArTseq and SNP analysis for genetic diversity assessment in durum wheat from central fertile crescent. PLoS ONE 12:e0167821

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Banerjee R, Hasler J, Meagher R, Nagoshi R, Hietala L, Huang F, Narva K, Jurat-Fuentes JL (2017) Mechanism and DNA-based detection of field-evolved resistance to transgenic Bt corn in fall armyworm (Spodoptera frugiperda). Sci Rep 7:10877

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Barkley NA, Dean RE, Pittman RN, Wang ML, Holbrook CC, Pederson GA (2007) Genetic diversity of cultivated and wild-type peanuts evaluated with M13-tailed SSR markers and sequencing. Genet Res 89:93–106

    Article  CAS  PubMed  Google Scholar 

  • Cantelmo NF, Pinho RGV, Balestre M (2017) Genomic analysis of maize lines introduced in the early stages of a breeding programme. Plant Breed 2017:1–16

    Google Scholar 

  • Chao S, Zhang W, Akhunov E, Sherman J, Ma Y, Luo MC, Dubcovsky J (2009) Analysis of gene-derived SNP marker polymorphism in US wheat (Triticum aestivum L.) cultivars. Mol Breed 23:23–33

    Article  CAS  Google Scholar 

  • Chen J, Zavala C, Ortega N, Petroli C, Franco J, Burgueon J, Costich DE, Hearne SJ (2016) The development of quality control genotyping approaches: a case study using elite maize lines. PLoS ONE 11(6):e0157236

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Chhetri LB, Acharya B (2019) Fall armyworm (Spodoptera frugiperda): a threat to food security for south Asian country: control and management options: a review. Farm Manag 4:38–44

    Article  Google Scholar 

  • Cooper JS, Rice BR, Shenstone EM, Lipka AE, Jamann TM (2019) Genome wide analysis and prediction of resistance to Goss’s wilt in maize. Plant Gen 12:180045

    Article  Google Scholar 

  • Cornwin JA, Kliebenstein DJ (2013) Quantitative resistance: more than just perception of a pathogen. Plant Cell 29:655–665

    Article  CAS  Google Scholar 

  • Dávila-Flores AM, DeWitt TJ, Bernal JS (2013) Facilitated by nature and agriculture: performance of a specialist herbivore improves with host-plant life history evolution, domestication, and breeding. Oecologia 173:1425–1437

    Article  PubMed  Google Scholar 

  • Davis FM, Williams WP, Wiseman BR (1989) Methods used to screen maize for and to determine mechanisms of resistance to the southwestern corn borer and fall armyworm. Paper presented at the international symposium on methodologies for developing host plant resistance to maize insects. Mexico, DF (Mexico). 9–14 Mar 1987

  • Earl DA, von Holdt BM (2012) Structure harvester: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Cons Gen Res 4 (2):359–361

    Article  Google Scholar 

  • Desjardins P, Conklin D (2010) Nanodrop microvolume quantitation of nucleic acids. J Vis Exp 45(e2565):1–5

    Google Scholar 

  • Elston RC (2005) Genetic markers. Encyclopedia of Biostatistics, John Wiley and Sons Ltd

  • Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software structure: a simulation study. Mol Ecol 14(8):2611–2620

    Article  CAS  PubMed  Google Scholar 

  • FAO (2018) Integrated management of the fall armyworm on maize: a guide for farmer field schools in Africa. Food and Agriculture Organization (FAO) of the United Nations. Retrieved on 23rd November 2018 from:

  • FAOSTAT (2017) Agricultural organization of the United Nations. Retrieved on 29th October, 2019 from

  • Fatoretto JC, Michel AP, Filho MCS, Silva N (2017) Adaptive potential of fall armyworm (Lepidoptera: Noctuidae) limits Bt trait durability in Brazil. Int J Pest Manag 8:1–10

    Article  Google Scholar 

  • Gaikpa DS, Miedaner T (2019) Genomics-assisted breeding for ear rot resistances and reduced mycotoxin contamination in maize: methods, advances and prospects. Theor Appl Genet 132:2721–2739

    Article  CAS  PubMed  Google Scholar 

  • Garcia AA, Benchimol LL, Barbosa AM, Geraldi IO, Souza CL, Souza APD (2004) Comparison of RAPD, RFLP, AFLP and SSR markers for diversity studies in tropical maize inbred lines. Genet Mol Biol 27:579–588

    Article  CAS  Google Scholar 

  • Geleta N, Labuschagne MT (2005) Qualitative traits variation in sorghum (Sorghum bicolor (L.) Moench) germplasm from eastern highlands of Ethiopia. Biodivers Conserv 14:3055–3064

    Article  Google Scholar 

  • Georgen G, Kumar PL, Sankung SB, Togola A, Tamò M (2016) First report of outbreaks of the fall armyworm Spodoptera frugiperda (J.E. Smith) (Lepidoptera, Noctuidae), a new alien invasive pest in West and Central Africa. PLoS One 11:e0165632

    Article  CAS  Google Scholar 

  • Gustafson TJ, de Leon N, Kaeppler SM, Tracy WF (2018) Genetic analysis of sugarcane mosaic virus resistance in the Wisconsin diversity panel of maize. Crop Sci 58:1853–1865

    Article  CAS  Google Scholar 

  • Hartl DL, Clark AG (1997) Principles of population genetics. Sinauer Associates Inc, Sunderland

    Google Scholar 

  • Howard JA, Mungoma C (1996) Zambia’s stop-and-go revolution: The impact of policies and organizations on the development and spread of maize technology. In:. Weber CLMT (ed) International development working paper. Michigan State University, East Lansing, USA

  • Hruska A (2019) Fall armyworm (Spodoptera frugiperda) management by small holder farmers. CAB Rev 14:43

  • Hruska AJ, Gould F (1999) Fall armyworm (Lepidoptera: noctuidae)and Diatrea Lineolata (Lepidoptera: pyralidae): impact of larval population and temporal occurrence on maize in Nacaragua. Entomol Soc Am 9:611–622

    Google Scholar 

  • Ingber DA, Mason CE, Flexner L (2017) Cry1 Bt susceptibilities of fall armyworm (Lepidoptera: Noctuidae) host strains. J Econ Entomol 111:361–368

    Article  CAS  Google Scholar 

  • Ingherlandt DV, Melchinger AE, Lebreton C, Stich B (2009) Population structure and genetic diversity in a commercial maize breeding program assesed with SSR and SNP markers. Theor Appl Genet 120:1289–1299

    Article  Google Scholar 

  • Liu K, Goodman M , Muse S, Smith JS, Bucler E, Doebley J (2003) Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165:2117–2128

    CAS  PubMed  PubMed Central  Google Scholar 

  • Mackay TFC (2009) Q & A: gentic analysis of quantitative traits. Biology 8:23

    Google Scholar 

  • Markert JA, Champlin DM, Gutjahr-Gobell R, Grear JS, Kuhn A, McGreevy TJ, Roth A, Bagley MJ, Nacci DE (2010) Population genetic diversity and fitness in multiple environments. BMC Evol Biol 10:205

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Masole H, Gumbo M (1994) Performance of early to medium maturity maize genotypes during the 1991–1992 drought in Zambia. In: Maize research for stress environments. Proceedings of the Fourth Eastern and Southern African Regional Maize Conference 28th March–1st April 1994, pp 112–116

  • McCann J (2005) Maize and grace. Harvard University Press, UK

    Book  Google Scholar 

  • Mihn J (1983) Efficient mass rearing and infestation techniques to screen for resistance to Spodoptera frugiperda. CIMMYT, Mexico

    Google Scholar 

  • Mubanga BC, Mubanga KH, Alubi T (2018) Characterization of selected maize varieties for all-year-round sweet corn production in Malawi. FSQM 76:77–84

    Google Scholar 

  • Mueller D, Sisson A (2013) Corn field guide: a reference for production, intergrated pest management and identification of diseases, insects and disorders of corn. Iowa State University, USA

    Google Scholar 

  • Mulungu K, Ng’ombe, JN (2019) Climate change impacts on sustainable maize production in Sub-Saharan Africa: a review. In Maize-production and use. IntechOpen. UK

  • Ndjiondjop MN, Semagn K, Gouda AC, Kpeki SB, Dro Tia DD, Sow M, Goungoulou A, Sie M, Perrier X, Ghesquiere A, Waburton ML (2017) Genetic variation and population structure of Oryza glaberrima and development of a mini-core collection using DArTseq. Front Plant Sci 8:1748

    Article  PubMed  PubMed Central  Google Scholar 

  • OECD (2018) Crop production indicator. The Organization for Economic Cooperation and Development. Retrieved on 24th October 2018 from:

  • Payne R (2015) A guide to anova and design. In Genstat 18th Edition VSN international, 2 Amberside, Wood Lane, Hertfordshire, UK

  • Pejic I, Ajmone-Marsan P, Morgante M, Kozumplick V, Castiglioni P, Taramino G, Motto M (1998) Comparative analysis of genetic similarity among maize inbred lines detected by RFLPs, RAPDs, SSRs, and AFLPs. Theor Appl Genet 97:1248–1255

    Article  CAS  Google Scholar 

  • Prasanna B, Huesing J, Eddy R, Peschke V (2018) Fall armyworm in Africa: a guide for integrated pest management. CIMMYT and USAID, Mexico

    Google Scholar 

  • Radosavljević I, Satovic Z, Liber Z (2015) Causes and consequences of contrasting genetic structure in sympatrically growing and closely related species. AoB Plants 7:1–13

    Article  CAS  Google Scholar 

  • R Core Team (2014) R: A language and environment for statistical computing. R Foundation for statistical computing. Vienna, Austria.

  • Romay MC, Millard MJ, Glaubitz JC, Peiffer JA, Swarts KL, Casstevens TM, Elshire LJ, Acharya CB, Mitchelle SE, Flint Garcia SA, McMullen MD, Holland JB, Buckler ES, Gardner CA (2013) Comprehensive genotyping of the USA national maize inbred seed bank. Genome Biol 14:R55

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Schaefer CM, Bernardo R (2013) Population structure and single nucleotide polymorphism diversity of historical Minnesota Maize Inbreds. Crop Sci 53:1529–1536

    Article  CAS  Google Scholar 

  • Sharma K, Misra RS (2011) Molecular approaches towards analyzing the viruses infecting maize (Zea mays L.). J Gen Mol Virol 3:1–7

    Article  Google Scholar 

  • Shrestha J (2016) Cluster analysis of maize inbred lines. J Nepal Agric Res Counc 2:33–36

    Article  Google Scholar 

  • Smale M, Simpungwe E, Birol E, De Groote H, Mutale R (2013) The changing structure of the maize seed industry in Zambia: prospects for orange maize. Paper presented at the 4th international conference of the African Association of Agricultural Economists, September 22–25, 2013, Hammamet, Tunisia

  • Souza CL (2011) Cultivar development of allogamous crops. Crop Breed Appl Biotechnol 11:8–11

    Article  Google Scholar 

  • Stagnati L, Lanubile A, Samayoa LF, Bragalanti M, Giorni P, Busconi M, Holland JB, Marocco A (2019) A genome wide association study reveals markers and genes associated with resistance to Fusarium verticillioides infection of seedlings in a maize diversity panel. G3(9):571–579

    Google Scholar 

  • Wright S (1978) Evolution and the genetics of populations: genetics and biometric foundations V4. Variability within and among natural populations. Chicago University Press, USA

    Google Scholar 

  • Wu X, Li Y, Shi Y, Song Y (2014) Fine genetic characterization of elite maize germplasm using high-throughput SNP genotyping. Theorl Appl Genet 127:621–631

    Article  Google Scholar 

  • Zhang X, Zhang H, Li L, Lan H, Ren Z, Liu D, Wu L, Liu H, Jaqueth J, Li B, Pan G, Gao S (2016) Characterizing the population structure and genetic diversity of maize breeding germplasm in Southwest China using genome-wide SNP markers. BMC Genom 17:1–16

    Article  CAS  Google Scholar 

  • Ziyomo C, Bernardo R (2013) Drought tolerance in maize: indirect selection through secondary traits versus genome wide selection. Crop Sci 52:1269–1275

    Article  Google Scholar 

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We sincerely thank the Alliance for a Green Revolution (AGRA) for funding this research through the African Centre for Crop Improvement (ACCI). Gratitude to the Zambia Agricultural Research Institute (ZARI) for hosting and supporting this work.

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Correspondence to Chapwa Kasoma.

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Kasoma, C., Shimelis, H., Laing, M.D. et al. Revealing the genetic diversity of maize (Zea mays L.) populations by phenotypic traits and DArTseq markers for variable resistance to fall armyworm. Genet Resour Crop Evol 68, 243–259 (2021).

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