Understanding rice adaptation to varying agro-ecosystems: trait interactions and quantitative trait loci

• DOI: 10.1186/s12863-015-0249-1
• Publication Date: 2015-07-18T00:04:35Z
• Authors: Shalabh Dixit; Alexandre Grondin; Cheng-Ruei Lee; Amelia Henry; Thomas-Mitchell Olds; Arvind Kumar
• Keywords: Trait

Interaction and genetic control for traits influencing the adaptation of rice crop to varying environments was studied in a mapping population derived from parents (Moroberekan Swarna) contrasting drought tolerance, yield potential, lodging resistance, dry direct seeding. A BC2F3-derived related these four trait groups phenotyped understand interactions among map align QTLs using composite interval (CIM). The study also aimed identify as multivariate least square (MLSIM) further traits. Significant correlations between drought- yield-related at seedling reproductive stages respectively with direct-seeded conditions were observed. CIM MLSIM methods applied univariate QTL clusters showing alignment several within across detected chromosomes 3, 4, 7 through CIM. largest number belonging all identified on chromosome 3 close qDTY 3.2 locus. These included such bleeding rate, shoot biomass, stem strength, spikelet fertility. Multivariate loci supported by 4 well distinctly different 8 which undetected Rice requires better wide range cultivation practices adjust climate change. Understanding genetics trade-offs each thus becomes highly important develop varieties stability them. This provides wider picture physiology environments. With complete understanding processes relationships groups, marker-assisted breeding can be used more efficiently plant types that combine or most beneficial show high environments, ecosystems, practices.