Hostname: page-component-cd9895bd7-dzt6s Total loading time: 0 Render date: 2024-12-26T16:57:19.519Z Has data issue: false hasContentIssue false
  • English
  • Français

Microsatellite marker-based genetic diversity of tropical-adapted shrunken-2 maize inbred lines and its relationship with normal endosperm inbred lines of known heterotic classification

Published online by Cambridge University Press:  07 January 2021

J. E. Iboyi ,
A. Abe  and
V. O. Adetimirin Open the ORCID record for V. O. Adetimirin [Opens in a new window]
J. E. Iboyi
Affiliation:
Plant Breeding Laboratory, Department of Crop and Horticultural Sciences, University of Ibadan, Ibadan, Nigeria Department of Agronomy, University of Florida, West Florida Research and Education Center, Jay, FL32565, USA
A. Abe
Affiliation:
Plant Breeding Laboratory, Department of Crop and Horticultural Sciences, University of Ibadan, Ibadan, Nigeria
V. O. Adetimirin*
Affiliation:
Plant Breeding Laboratory, Department of Crop and Horticultural Sciences, University of Ibadan, Ibadan, Nigeria
*
*Corresponding author. E-mail: [email protected], [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Knowledge of the genetic diversity and relationships among maize inbred lines can facilitate germplasm management and plant breeding programmes. The study investigated the level of genetic diversity among S6 lines developed from a tropical-adapted shrunken-2 (sh-2) maize population and their relationship with normal endosperm tropical inbred lines of known heterotic groups. Ninety-one sh-2 maize inbred lines (UI1-UI91) developed in the University of Ibadan super-sweet Maize Breeding Programme were genotyped at 30 simple sequence repeat (SSR) loci, alongside five normal endosperm maize inbred lines viz. TZi3, TZi4, TZi10, TZi12 and TZi15, four of which belong to two heterotic groups. Twenty-three SSR markers were polymorphic and detected a total of 61 alleles, with a range of 2–7 and an average of 2.65 alleles per locus. The polymorphic information content ranged from 0.12 in bnlg1937 to 0.77 in phi126, with an average of 0.36. The gene diversity (He) averaged 0.43. Cluster analysis resulted in five groups consisting of 16, 36, 17, 23 and 3 inbred lines, with one sh-2 line ungrouped. TZi 12 and TZi 15, both of which are of the same heterotic group, clustered with TZi 3 of another heterotic group. Considerable genetic diversity exists among the 96 inbred lines. Only two of the five normal endosperm lines shared clusters with the sh-2 lines. The clustering of the normal endosperm inbred lines is not related to their established heterotic patterns. Inbred lines in two clusters offer the possibility of guiding the exploitation of heterosis among the sh-2 lines.

Keywords

genetic diversityshrunken-2 maize inbred linessimple sequence repeats (SSR)
Type
Research Article
Information
Plant Genetic Resources , Volume 18 , Issue 6 , December 2020 , pp. 454 - 461
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of NIAB

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adetimirin, VO (2008) Stand establishment and early field vigour variation in a tropicalized shrunken-2 maize population. Field Crops Research 108: 143–149.CrossRefGoogle Scholar
Adetimirin, VO, Kim, SK and Aken'Ova, ME (2000) Expression of mature plant resistance to Striga hermonthica in maize. Euphytica 115: 149–158.CrossRefGoogle Scholar
Adetimirin, VO, Vroh-Bi, I, Thé, C, Menkir, A, Mitchell, SE and Kresovich, S (2008) Diversity analysis of elite maize inbred lines adapted to West and Central Africa using SSR markers. Maydica 53: 143–149.Google Scholar
Akaogu, IC, Badu-Apraku, B, Adetimirin, VO, Vroh-Bi, I, Oyekunle, M and Akinwale, RO (2013) Genetic diversity assessment of extra-early maturing yellow maize inbreds and hybrid performance in Striga-infested and Striga-free environments. Journal of Agricultural Science 151: 519–537.CrossRefGoogle Scholar
Akintunde, EO (2017) Combining ability of tropical-adapted shrunken-2 maize inbred lines for yield and other agronomic traits. MSc thesis, Pan-African University/University of Ibadan, Ibadan, Nigeria.Google Scholar
Allard, RW (1999) Principles of Plant Breeding, 2nd edn. New York: Wiley, pp. 264.Google Scholar
Bantte, K and Prasanna, BM (2003) Simple sequences repeat polymorphism in quality protein maize (QTL) lines. Euphytica 129: 337–344.CrossRefGoogle Scholar
Choukan, R, Hossainzadeh, A, Ghannadha, MR, Talei, AR, Mohammadi, SA and Warburton, ML (2006) Use of SSR data to determine relationships and potential heterotic groupings within medium to late maturing Iranian maize inbred lines. Field Crop Research 95: 221–222.CrossRefGoogle Scholar
Gasura, E, Setimela, P, Mabasa, S, Rwafa, R, Kageler, S and Nyakurwa, C (2019) Response of IITA maize inbred lines bred for Striga hermonthica resistance to Striga asiatica and associated resistance mechanisms in Southern Africa. Euphytica 215: 151.CrossRefGoogle Scholar
Gerdes, JT and Tracy, WF (1994) Diversity of historically important sweet corn inbreds as estimated by RFLPs, morphology, isozymes and pedigree. Crop Science 34: 26–33.CrossRefGoogle Scholar
Heckenberger, M, Bohn, M, Ziegle, JS, Joe, LK, Hauser, JD, Hutton, M and Melchinger, AE (2002) Variation of DNA fingerprints among accessions within maize inbred lines and implications for identification of essentially derived varieties. I. Genetic and technical sources of variation in SSR data. Molecular Breeding 10: 181–191.CrossRefGoogle Scholar
Kim, SK, Efron, Y, Khadr, F, Fajemisin, J and Lee, MH (1987) Registration of 16 maize streak resistant tropical maize parental inbred lines. Crop Science 27: 824–825.CrossRefGoogle Scholar
Kim, SK, The, C, Adetimirin, VO, Kling, J, Makinde, A, Bamidele, T, Ogaji, A, Solademi, O and Adekunle, D (2000) Development of Striga hermonthica tolerant and resistant tropical maize germplasm lines and synthetics. Korean Journal of International Agriculture 12: 161–165.Google Scholar
Krishna, MSR, Reddy, SS and Naik, CB (2012) Assessment of genetic diversity in quality protein maize (QPM) lines using simple sequence repeat (SSR) markers. African Journal of Biotechnology 11: 16427–16433.Google Scholar
Legesse, BW, Myburg, AA, Pixley, KV and Botha, AM (2007) Genetic diversity of African maize inbred lines revealed by SSR markers. Hereditas 144: 10–17.CrossRefGoogle ScholarPubMed
Liu, K and Muse, SV (2005) Powermarker: integrated analysis environment for genetic marker data. Bioinformatics (Oxford, England) 21: 2128–2129.CrossRefGoogle Scholar
Lopes, AD, Scapim, CA, Machado, MF, Siva, TA, Cantagali, LB, Teixeira, FF and Mora, F (2015) Genetic diversity assessed by microsatellite markers in sweet corn cultivars. Scientia Agricola 72: 513–519.CrossRefGoogle Scholar
Matsuoka, Y, Mitchell, SE and Kresovich, S (2002) Microsatellites in Zea: variability, patterns of mutations and use for evolutionary studies. Theoretical and Applied Genetics 104: 436–450.CrossRefGoogle ScholarPubMed
Mehta, B, Hossain, F, Muthusamy, V, Baveja, A, Zunjare, R, Jha, S and Gupta, HS (2017) Microsatellite-based genetic diversity analyses of sugary1-, shrunken2- and double mutant-sweet corn inbreds for their utilization in breeding programme. Physiology and Molecular Biology of Plants 23: 411–420.CrossRefGoogle ScholarPubMed
Nei, M and Li, W (1979) Mathematical model for studying genetic variation in terms of restriction endonucleases. Proceedings of the National Academy of Sciences of the USA 76: 5269–5273.CrossRefGoogle ScholarPubMed
Nyaligwa, L, Hussein, S, Amelework, B and Ghebrehiwot, H (2015) Genetic diversity analysis of elite maize inbred lines of diverse sources using SSR markers. Maydica 60: 1–8.Google Scholar
Oppong, A, Bedoya, C, Ewool, M, Asante, M, Thompson, R, Adu-Dapaah, H, Lamptey, J, Ofori, K, Offeil, S and Warburton, ML (2014) Bulk genetic characterization of Ghanaian maize landraces using microsatellite markers. Maydica 59: 1–8.Google Scholar
Rohlf, FJ (2000) NTSYSpc: Numerical Taxonomy and Multivariate Analysis System Version 2.1 User Guide. New York: Applied Biostatistics Incorporation.Google Scholar
Rosenbloom, JI, Kalusk, DN and Berry, EM (2008) A global nutritional index. Food and Nutrition Bulletin 29: 266–277.CrossRefGoogle ScholarPubMed
Salazar, E, Gonzalez, M, Araya, C, Mejia, N and Carrasco, B (2017) Genetic diversity and inter-racial structure in Chilean Chocolero corn (Zea mays L.) germplasm revealed by simple sequence repeat markers (SSRs). Scientia Horticulturae 225: 620–629.CrossRefGoogle Scholar
Senior, ML, Chin, ECL, Lee, M, Smith, JSC and Stuber, CW (1996) Simple sequences repeat markers developed from maize sequences found in the GENEBANK database: map construction. Crop Science 36: 1676–1683.CrossRefGoogle Scholar
Senior, ML, Murphy, JP, Goodman, MM and Stuber, CW (1998) Utility of SSRs for determining genetic similarities and relationships in maize using an agarose gel system. Crop Science 38: 1088–1098.CrossRefGoogle Scholar
Smith, JSC, Chin, ECL, Shu, H, Smith, OS, Wall, SJ, Senior, ML, Mitchell, SE, Kresovich, S and Ziegle, J (1997) An evaluation of the utility of SSR loci as molecular markers in maize (Zea mays L): comparisons with data from RFLPs and pedigree. Theoretical and Applied Genetics 95: 163–173.CrossRefGoogle Scholar
Sserumaga, JP, Makumbi, D, Ji, H, Njoroge, K, Muthomi, JW, Chemining'wa, GN, Si-myung, L, Asea, G and Kim, H (2014) Molecular characterization of tropical maize inbred lines using microsatellite DNA markers. Maydica 59: 267–274.Google Scholar
Tracy, WF (1997) History, genetics and breeding of supersweet (shrunken-2) corn. Plant Breeding Reviews 14: 189–236.Google Scholar
Tracy, WF (2001) Sweet corn. In: Hallauer AR (eds.) Specialty Corn. Boca Raton, FL: CRC, pp. 162–164.Google Scholar
United Nations Department of Economic and Social Affairs (UNDESA) (2020) World Population Prospects, 2019: Highlights (ST/ESA/SER.A/423). New York: United Nations, pp. 46.Google Scholar
Vigouroux, Y, Mitchell, S, Matsuoka, Y, Hamblin, M, Kresovich, S, Stephen, CJ, Jennifer, J, Oscar, SS and John, D (2005) An analysis of genetic diversity across the maize genome using microsatellites. Genetics 169: 1617–1630.CrossRefGoogle ScholarPubMed
Warburton, ML, Xia, XC, Crossa, J, Franco, J, Melchinger, AE, Frisch, M, Bohn, M and Hoisington, D (2002) Genetic characterization of CIMMYT inbred maize lines and open pollinated populations using large scale fingerprinting methods. Crop Science 42: 1832–1840.CrossRefGoogle Scholar
Weber, JL (1990) Informativeness of human (dC-dA)n.(dG-dT)n polymorphisms. Genomics 7: 524–530.CrossRefGoogle ScholarPubMed
Whatman FTA Protocol BD05 (2002) Applying and Preparing Plant Samples on FTA Cards for DNA Analysis. United Kingdom: Whatman, pp. 2.Google Scholar
Wietholter, P, Cruz, MJ, de-Freitas, T, Delmar, S and Barbosa, JF (2008) Genetic variability in corn landraces from Southern Brazil. Maydica 53: 151–159.Google Scholar
Wilson, DO, Mohan, SK and Knott, E (1993) Evaluation of fungicide and seed treatments for shrunken-2 (‘supersweet’) sweet corn. Plant Diseases 77: 384–351.CrossRefGoogle Scholar
Yousef, GG and Juvik, JA (2002) Enhancement of seedling emergence in sweet corn by marker-assisted backcrossing of beneficial QTL. Crop Science 42: 96–104.Google ScholarPubMed
Yuan, LX, Fu, JH, Warburton, ML, Li, XH, Zhang, SH, Khairallah, M, Liu, XZ, Peng, ZB and Li, LC (2000) Comparison of genetic diversity among maize inbred lines based on RFLPs, SSRs, AFLPs and RAPDs. Acta Genetica Sinica 27: 725–733.Google ScholarPubMed