Analysis on additive effects and additive-by-additive epistatic effects of QTLs for yield traits in a recombinant inbred line population of rice

Abstract

A linkage map consisting of 158 DNA markers were constructed by using a recombinant inbred line (RIL) population derived from the indica-indica rice cross Zhenshan 97B x Milyang 46. Quantitative trait loci (QTLs) conditioning grain yield and five yield component traits were determined at the one-locus and two-locus levels, and genotype-by-environment (GE) interactions were analyzed. Thirty-one QTLs were detected to have significant additive effects for yield traits, of which 12 also exhibited significant epistatic effects. Sixteen significant additive-by-additive (AA) interactions were detected, of which nine occurred between QTLs with own additive effects (M(ep)QTLs), four occurred between QTLs showing epistatic effects only (epQTLs), and three occurred between M(ep)QTLs and epQTLs. Significant GE interactions were found for six QTLs with additive effects and one AA interaction. Generally, the contributions to the phenotypic variation were higher due to QTL main effects than to epistatic effects. The detection of additive effects and AA effects of a QTL interfered with each other, indicating that the detection of QTLs with main effects, as well as the magnitude and directions of the additive effects, might vary depending on their interactions with other loci.

Association between molecular markers and blast resistance in an advanced backcross population of rice

“…Since there is a diversity of pathogen strains in the field, it is likely that epistasis could play an important role in resistance to blast under natural conditions. The importance of epistasis has been reported in complex traits such as grain yield and its components Yu et al 1997;Zhuang et al 2002b).…”

Validating a segment on the short arm of chromosome 6 responsible for genetic variation in the hull silicon content and yield traits of rice

“…QTLs qHUS-1-1, qHUS-1-2, qHUS-6 and qHUS-11 were detected, among which qHUS-6 on the short arm of chromosome 6 had the largest eVect and explained 17.4% of the phenotypic variance (Dai et al 2005b). The interval in the vicinity of qHUS-6 had also displayed signiWcant eVects on yield traits in the same population (Zhuang et al 2002). In this study, the same RIL population and 169 RILs having identical genotypes at QTLs qHUS-1-1 and qHUS-11 were grown in 2004 for mapping QTLs for HUS, and 15 F 2:3 lines that diVered only in a 2.15-Mb segment extending from RM587 to RM6119 on the short arm of chromosome 6 were selected and tested on HUS and yield traits.…”

Response of a new IR50/Moroberekan recombinant inbred population of rice (Oryza sativa L.) from an indica × japonica cross for growth and yield traits under aerobic conditions

“…Grain yield showed significant positive association with plant height, number of tillers, panicle exsertion, number of panicles plant -1 , single panicle weight, test weight, number of fertile spikelets panicle -1 , straw weight, biomass plant -1 and harvest index at both phenotypic and genotypic levels (Table 3). Zhuang et al (2002) and Thompson et al (2003) have reported a significant and high positive association of grain yield with number of panicles, number of fertile spikelets panicle -1 and test weight. While Chakraborty et al 2001 observed a significant and high association of grain yield with plant height, panicles plant -1 , panicle length, number of fertile grains panicle -1 and harvest index under normal well-watered condition, Yogameenakshi et al (2004) observed similar results under drought stress.…”