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Molecular Dissection Of Quantitative Variation In Bermudagrass Hybrids (Cynodon Dactylon X Transvaalensis): Morphological Traits

S. Khanal, Jeffrey C. Dunne, B. Schwartz, Changsoo Kim, S. Milla-Lewis, P. Raymer, W. W. Hanna, Jeevan Adhikari, Susan A. Auckland, Lisa K. Rainville, A. Paterson
Published 2019 · Biology, Medicine

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Bermudagrass (Cynodon (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 F1 individuals derived from a cross between Cynodon dactylon (T89) and C. transvaalensis (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 (P < 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; R2 = 11–19%), qLLS-7-1 (for LLS; R2 = 13–27%), qLEN-1-1 (for LLEN; R2 = 10–11%), and qLW-3-2 (for LW; R2 = 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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