The genetic relationship between popping expansion volume and two yield components in popcorn using unconditional and conditional QTL analysis

Abstract

Popping expansion volume (PEV) is the most important quality trait in popcorn, while its germplasm is inferior to normal dent/Xint corn in yield. In this study, 259 F 2:3 families, developed from the cross between a dent corn inbred Dan232 and a popcorn inbred N04, were evaluated for their PEV, grain weight per plant (GWP) and 100-grain weight (100 GW) in two environments. The genetic relationship between PEV and GWP, and 100 GW on individual gene loci were evaluated using unconditional and conditional QTL mapping methods. In total, Wve, one and three unconditional QTL were identiWed for PEV, GWP, and 100 GW, respectively. The positive alleles of all QTL for PEV were from N04, while positive alleles of all QTL for GWP and 100 GW were from Dan232. In conditional mapping, one and two QTL failed to be detected, and all four additional QTL were detected. Nevertheless, three QTL were identiWed, which controlled PEV independently from GWP/100 GW. They seemed to be potential candidates in popcorn breeding to increase PEV without decreasing GWP/100 GW. The results suggested that for signiWcantly correlated traits, the conditional QTL mapping method could be used to dissect the genetic interrelationship between traits at the level of individual QTL, as well as reveal additional QTL that were undetectable by unconditional mapping.

Genetic relationship between lodging and lodging components in barley (Hordeum vulgare) based on unconditional and conditional quantitative trait locus analyses

“…The present study demonstrated that conditional QTL mapping could identify a greater number of QTL, as well as evaluate the genetic relationships among different significantly correlated traits at the molecular level. Such information could be used in marker-assisted selection for simultaneously improving objective traits (Li et al, 2008). Excluding the influences of CSFIN, CSSN, CSTN, CSFN, CSFON, DFIN, and DFON on LD resulted in the identification of a large number of new QTL that accounted for a high proportion of the phenotypic variation.…”

“…Recently, a method called multivariable conditional QTL analysis was proposed for analyzing the contributions of component traits to a complex trait and for investigating the genetic relationship between two traits at the QTL level (Wen and Zhu, 2005). This method could be used to determine genetic interrelationships between traits at the level of individual QTL, and to find additional QTL that are undetectable with unconditional mapping (Li et al, 2008). This method has been successfully used to analyze QTL by Guo et al (2005), Zhao et al (2006), Liu et al (2008), andCui et al (2011).…”

Genetic Relationships Among Panicle Characteristics of Rice (Oryza sativa L.) Using Unconditional and Conditional QTL Analyses

“…A protocol for conditional genetics analysis proposed by Zhu (1995) has been further developed to study closely related traits and to investigate the contribution of each trait to other related traits at the QTL level (Cao 2000;Guo et al 2005;Zhao et al 2006). For significantly correlated traits, a conditional QTL mapping method could be used to dissect the genetic interrelationship between traits at the level of individual QTLs, as well as reveal additional QTLs that are undetectable by unconditional mapping (Li et al 2008).…”

Identification of QTL underlying the oil filling rate at different developmental stages of soybean seed

“…Loci of small effects were also reported in rice (Xu et al 2004;Li et al 2006), wheat (Kirigwi et al 2007;Wang et al 2009) and maize (Lu et al 2003;Li et al 2007Li et al , 2008. Thus, more attention should be paid to the stable, major QTL detected across different growth stages and with positive pleiotropic effects on other traits.…”