Identification of Quantitative Trait Loci in Rice for Yield, Yield Components, and Agronomic Traits across Years and Locations

Abstract

RESEARCHI dentifying quantitative trait loci (QTLs) associated with economically valuable phenotypes is of particular interest as the basis for developing effi cient strategies for genomics-based approaches to plant improvement. Identifi cation of QTLs is also a valuable starting point for positional cloning of genes underlying quantitative phenotypes and for interpreting the molecular and biochemical mechanisms that condition plant growth and development.The QTL studies that are conducted over several years and locations provide information about which regions of the genome ABSTRACT A population of 164 recombinant inbred lines (RILs) of rice (Oryza sativa L.) derived from a cross between Milyang23 and Gihobyeo was evaluated for nine phenotypic characters over three years and two regions in Korea. The population had been previously mapped using 414 molecular markers. Genotype × environment (G × E) interaction was analyzed for six grain yieldrelated traits and three agronomic traits across years and locations using the AMMI model. The quantitative trait loci (QTLs) were detected by interval mapping and composite interval mapping. A total of 75 QTLs were identifi ed for the nine traits across fi ve environments and they were categorized as (i) 29 QTLs with main effect, (ii) 18 QTLs with minor effect, (iii) 13 QTLs with G × E interaction effect, (iv) six QTLs with both main effect and G × E interaction effect, and (v) nine potential QTLs with low log of the odds (LOD) scores. The AMMI model explained from 68.6% to 84.7% of the interaction effect and 19 QTLs were signifi cantly associated with G × E interaction. Culm length had the least G × E, while the maximum G × E interaction was exhibited for spikelets per panicle (39.7%) and percent ripened grain (35.3%). Markers closely linked to main effect QTLs will be most useful for marker-assisted breeding.

Fine mapping of consistent quantitative trait loci for yield under drought stress using rice (Oryza sativa) recombinant inbred lines adapted to rainfed environment

“…Consistent large-effect QTL (qDTY6.1) was observed for grain yield under stress conditions in TPE on chromosome 6 near marker RM2434 with phenotypic variation of 31.3%, 37.9% and 3.6% in DS01, DS02 and FC01 respectively, in these RI lines. The same region was reported to be linked to grain yield 38 , biomass, number of panicles 12 and thousand grain weight 39 in rice. QTL for seedling drought tolerance was reported near RM217 region, and the same region harbours genes expressed early under drought stress 40 and Khowaja et al 41 also reported QTLs for drought avoidance in rice in this region.…”

Análise de associação quanto à produtividade e seus caracteres componentes em linhagens e cultivares de arroz de terras altas

“…Não houve correlação fenotípica entre esses caracteres, ao contrário do que foi observado por Cho et al (2007), que relataram correlação negativa e significativa. Ranawake & Amarasinghe (2014) também relataram correlação negativa, mas não significativa quanto a esses caracteres.…”

Overexpression of rice premnaspirodiene oxygenase reduces the infection rate ofXanthomonas oryzaepv.oryzae

“…Genomic DNA was extracted as described in Cho et al (2007) with some modifications. The relative purity and concentration of extracted DNA was estimated using NanoDrop-One (Thermo Scientific).…”