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QTL detection in maize testcross progenies as affected by related and unrelated testers

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Abstract

The evaluation of recombinant inbred lines (RILs) per se can be biased by inbreeding depression in case of allogamous species. To overcome this drawback, RILs can be evaluated in combination with testers; however, testers can carry dominant alleles at the quantitative trait loci (QTL), thus hampering their detection. This study was conducted on the maize (Zea mays L.) population of 142 RILs derived from the single cross B73 × H99 to evaluate the role of different testers in affecting: (1) QTL detection, (2) the estimates of their effects, and (3) the consistency of such estimates across testers. Testcrosses (TCs) were produced by crossing RILs with inbred testers B73 [TC(B)], H99 [TC(H)], and Mo17 [TC(M)]. TCs were field tested in three environments. TC(B) mean was higher than TC(H) mean for all traits, while TC(M) mean was the highest for plant vigor traits and grain yield. As to the number of detected QTL, tester Mo17 was superior to H99 and B73 for traits with prevailing additive effects. Several overlaps among the QTL were detected in two or all the three TC populations with QTL effects being almost always consistent (same sign). For traits with prevailing dominance–overdominance effects, as grain yield, the poor performing tester H99 was clearly the most effective; fewer overlaps were found and some of them were inconsistent (different sign). Epistatic interactions were of minor importance. In conclusion, the three testers proved to affect QTL detection and estimation of their effects, especially for traits showing high dominance levels.

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References

  • Ajmone Marsan P, Gorni C, Chittò A, Redaelli R, van Vijk R, Stam P, Motto M (2001) Identification of QTLs for grain yield and grain-related traits of maize (Zea mays L.) using an AFLP map, different testers, and cofactor analysis. Theor Appl Genet 102:230–243

    Article  Google Scholar 

  • Austin DF, Lee M, Veldboom LR, Hallauer AR (2000) Genetic mapping in maize with hybrid progeny across testers and generations: grain yield and grain moisture. Crop Sci 40:30–39

    Google Scholar 

  • Austin DF, Lee M, Veldboom LR (2001) Genetic mapping in maize with hybrid progeny across testers and generations: plant height and flowering. Theor Appl Genet 102:163–176

    Article  CAS  Google Scholar 

  • Beavis WD, Smith OS, Grant D, Fincher R (1994) Identification of quantitative trait loci using a small sample of topcrossed and F4 progeny from maize. Crop Sci 34:882–896

    Google Scholar 

  • Blanc G, Charcosset A, Mangin B, Gallais A, Moreau L (2006) Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize. Theor Appl Genet 113:206–224

    Article  PubMed  CAS  Google Scholar 

  • Burr B, Burr FA (1991) Recombinant inbreds for molecular mapping in maize: theoretical and practical considerations. Trends Genet 7:55–60

    PubMed  CAS  Google Scholar 

  • Churchill GA, Doerge RW (1994) Empirical threshold values for quantitative trait mapping. Genetics 138:963–971

    PubMed  CAS  Google Scholar 

  • Cockerham CC, Zeng ZB (1996) Design III with marker loci. Genetics 143:1437–1456

    PubMed  CAS  Google Scholar 

  • Crow JF (2000) The rise and fall of overdominance. Plant Breed Rev 17:225–257

    Google Scholar 

  • Frascaroli E, Canè MA, Landi P, Pea G, Gianfranceschi L, Villa M, Morgante M, Pè ME (2007) Classical genetic and quantitative trait loci analyses of heterosis in a maize hybrid between two elite inbred lines. Genetics 176:625–644

    Article  PubMed  CAS  Google Scholar 

  • Frova C, Krajewski P, Di Fonzo N, Villa M, Sari-Gorla M (1999) Genetic analysis of drought tolerance in maize by molecular markers. I. Yield components. Theor Appl Genet 99:280–288

    Article  Google Scholar 

  • Groh S, González-de-León D, Khairallah MM, Jiang C, Bergvinson D, Bohn M, Hoisington DA, Melchinger AE (1998) QTL mapping in tropical maize: III. Genomic regions for resistance to Diatraea spp. and associated traits in two RIL populations. Crop Sci 38:1062–1072

    Google Scholar 

  • Hallauer AR (1990) Methods used in developing maize inbreds. Maydica 35:1–16

    Google Scholar 

  • Hallauer AR, Miranda JB (1988) Quantitative genetics in maize breeding. Iowa State University Press, Ames

    Google Scholar 

  • Knapp SJ, Stroup WW, Ross WM (1985) Exact confidence intervals for heritability on a progeny mean basis. Crop Sci 25:192–194

    Google Scholar 

  • Lande R, Thompson R (1990) Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743–756

    PubMed  CAS  Google Scholar 

  • Li ZK, Luo LJ, Mei HW, Wang DL, Shu QY, Tabien R, Zhong DB, Ying CS, Stansel JW, Khush GS, Paterson AH (2001) Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice. I. Biomass and grain yield. Genetics 158:1737–1753

    PubMed  CAS  Google Scholar 

  • Livini C, Ajmone-Marsan P, Messmer MM, Melchinger AE, Motto M (1992) Genetic diversity of maize inbred lines within and among heterotic groups revealed by RFLP. Theor Appl Genet 84:17–25

    Article  Google Scholar 

  • Lu H, Bernardo R (2001) Molecular marker diversity among current and historical maize inbreds. Theor Appl Genet 103:613–617

    Article  CAS  Google Scholar 

  • Lübberstedt T, Melchinger AE, Klein D, Degenhardt H, Paul C (1997) QTL mapping in test crosses of European flint lines of maize 2. Comparisons of different testers for forage quality traits. Crop Sci 37:1913–1922

    Google Scholar 

  • Melchinger AE, Utz HF, Schön CC (1998) Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects. Genetics 149:383–403

    PubMed  CAS  Google Scholar 

  • Mihaljevic R, Utz HF, Melchinger AE (2005) No evidence for epistasis in hybrid and per se performance of elite european flint maize inbreds from generation means and QTL analyses. Crop Sci 45:2605–2613

    Article  Google Scholar 

  • SAS INSTITUTE (1996) SAS users guide: statistic. SAS Institute, Cary

    Google Scholar 

  • Schön CC, Melchinger AE, Boppenmaier J, Brunklaus-Jung E, Herrmann RG, Seitzer JF (1994) RFLP mapping in maize: quantitative trait loci affecting testcross performances of elite european flint lines. Crop Sci 34:378–389

    Google Scholar 

  • Stuber CW, Lincoln SE, Wolff DW, Helentjaris T, Lander ES (1992) Identification of genetic factors contributing to heterosis in a hybrid from two elite maize inbred lines using molecular markers. Genetics 132:823–839

    PubMed  CAS  Google Scholar 

  • Utz HF, Melchinger AE (1996) PLABQTL: a program for composite interval mapping of QTL. J Quant Trait Loci 2:1–5

    Google Scholar 

  • Wang DL, Zhu J, Li ZK, Paterson AH (1999) Mapping QTL with epistatic effects and QTL × environment interactions by mixed model approaches. Theor Appl Genet 99:1255–1264

    Article  Google Scholar 

  • Wolf DP, Hallauer AR (1997) Triple testcross analysis to detect epistasis in maize. Crop Sci 37:763–770

    Article  Google Scholar 

  • Zeng ZB (1994) Precision mapping of quantitative trait loci. Genetics 136:1457–1468

    PubMed  CAS  Google Scholar 

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Acknowledgments

The study was conducted with the financial support of the Italian Ministry of University and Research, PRIN (Progetti di Ricerca di Interesse Nazionale) Project: “Modern approaches of quantitative genetics for the analysis of agronomic traits in maize”.

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Correspondence to Elisabetta Frascaroli.

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Communicated by C.-C. Schön.

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Frascaroli, E., Canè, M.A., Pè, M.E. et al. QTL detection in maize testcross progenies as affected by related and unrelated testers. Theor Appl Genet 118, 993–1004 (2009). https://doi.org/10.1007/s00122-008-0956-3

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  • DOI: https://doi.org/10.1007/s00122-008-0956-3

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