Bermudagrass ( (L.)) is the most important warm-season grass grown for forage or turf. It shows extensive variation in morphological characteristics and growth attributes, but the genetic basis of this variation is little understood. Detection and tagging of quantitative trait loci (QTL) affecting above-ground morphology with diagnostic DNA markers would provide a foundation for genetic and molecular breeding applications in bermudagrass. Here, we report early findings regarding genetic architecture of foliage (canopy height, HT), stolon (stolon internode length, ILEN and length of the longest stolon LLS), and leaf traits (leaf blade length, LLEN and leaf blade width, LW) in 110 F individuals derived from a cross between (T89) and (T574). Separate and joint environment analyses were performed on trait data collected across two to five environments (locations, and/or years, or time), finding significant differences ( < 0.001) among the hybrid progeny for all traits. Analysis of marker-trait associations detected 74 QTL and 135 epistatic interactions. Composite interval mapping (CIM) and mixed-model CIM (MCIM) identified 32 main effect QTL (M-QTL) and 13 interacting QTL (int-QTL). Colocalization of QTL for plant morphology partially explained significant correlations among traits. M-QTL qILEN-3-2 (for ILEN; = 11-19%), qLLS-7-1 (for LLS; = 13-27%), qLEN-1-1 (for LLEN; = 10-11%), and qLW-3-2 (for LW; = 10-12%) were 'stable' across multiple environments, representing candidates for fine mapping and applied breeding applications. QTL correspondence between bermudagrass and divergent grass lineages suggests opportunities to accelerate progress by predictive breeding of bermudagrass.
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http://dx.doi.org/10.1534/g3.119.400061 | DOI Listing |
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State Key Laboratory of Swine and Poultry Breeding Industry, Key Laboratory of Agricultural Bioinformatics, Ministry of Education, Key Laboratory of Livestock and Poultry Multi-omics, Ministry of Agriculture and Rural Affairs, College of Animal and Technology, Sichuan Agricultural University, Chengdu, China.
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Institute of Biotechnology, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China. Electronic address:
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Department of Agronomy, Kansas State University, Manhattan, KS, 66506, USA.
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Key Laboratory of New Technology in Agricultural Application, College of Plant Science and Technology, Beijing University of Agriculture, Beijing, 102206 China.
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