Quantitative trait loci mapping for biomass yield traits in a Lolium inbred line derived F2 population
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Lolium perenne L. (perennial ryegrass) is the principle forage grass species in temperate agriculture. Improving biomass yield still remains one of the most important aims of current forage breeding programmes. A quantitative trait locus (QTL) study investigating biomass yield traits in perennial ryegrass was carried out in greenhouse and field environments. The study is based on an F2 population consisting of 360 individuals derived from two inbred grandparents where the F1 has a large biomass yield phenotype. For both experimental environments co-localized QTL for biomass yield traits including fresh and dry weight and dry matter were identified on linkage groups 2, 3 and 7. A major QTL for fresh and dry weight was identified on LG 3 which explained around 30% of the phenotypic variance in the field experiment. The findings of this study are discussed with regard for their potential in research and breeding.
KeywordsLolium perenne Perennial ryegrass Biomass QTL Fresh weight Dry weight
UCMA was financed by a Teagasc PhD Walsh Fellowship. The project was financed in part by the National Development Plan and by Teagasc core funding. We are grateful to several summer students, to the forage breeding group and the farm staff in Oak Park for help with field maintenance.
- Armstead IP, Turner LB, Marshall AH, Humphreys MO, King IP, Thorogood D (2008) Identifying genetic components controlling fertility in the outcrossing grass species perennial ryegrass (Lolium perenne) by quantitative genetics. New Phytol 178(3):559–571. doi: 10.1111/j.1469-8137.2008.02413.x PubMedCrossRefGoogle Scholar
- Becker H (1993) Pflanzenzüchtung. Eugen Ulmer Verlag, Stuttgart, 150 ppGoogle Scholar
- Hannaway D, Fransen S, Cropper J, Teel M, Chaney M, Griggs T, Halse R, Hart J, Cheeke P, Hansen D, Klinger R, Lane W (1999) Perennial ryegrass (Lolium perenne L.). A Pacific Northwest Extension Publication, vol. PNW 502. Oregon State University, Washington State University, University of IdahoGoogle Scholar
- Lisec J, Meyer RC, Steinfath M, Redestig H, Becher M, Witucka-Wall H, Fiehn O, Törjék O, Selbig J, Altmann T, Willmitzer L (2008) Identification of metabolic and biomass QTL in Arabidopsis thaliana in a parallel analysis of RIL and IL population. Plant J 53:960–972. doi: 10.1111/j.1365-313X.2007.03383.x PubMedCrossRefGoogle Scholar
- Liu HL (1998) Statistical genomics: linkage, mapping, and QTL analysis. CRC Press, Boca RatonGoogle Scholar
- Piepho HP, Williams ER, Fleck M (2006) A note on the analysis of designed experiments with complex treatment structure. HortScience 41:446–452Google Scholar
- Uchimiya H, Takahashi N (1973) Kinetics of heterosis in growth of the leaf blade in Zea mays L. Ann Bot (Lond) 37:147–152Google Scholar
- Van Ooijen JW, Boer MP, Jansen RC, Maliepaard C (2002) Map QTL 4.0: software for the calculation of QTL positions on genetic maps. Plant Research International, WageningenGoogle Scholar
- Yamada T, Jones ES, Cogan NOI, Vecchies AC, Nomura T, Hisano H, Shimamoto Y, Smith KF, Hayward MD, Forster JW (2004) QTL analysis of morphological, developmental, and winter hardiness-associated traits in perennial ryegrass. Crop Sci 44:925–935Google Scholar