Genetic analysis for grain filling duration in wheat using joint segregation analysis

Abstract

Mixed inheritance analysis using joint segregation analysis was investigated in 6 basic populations (P 1 , F 1 , P 2 , BC 1 , BC 2 , and F 2 ) of 4 wheat crosses, i.e. Hashim-08 × LU-26, Farid-06 × Shafaq, Parula × Blue Silver, and TD-1 × D-97603, for grain filling duration during the crop season of 2011/2012. In cross Hashim-08 × LU-26, the duration of grain filling was controlled by 1 major gene and the additive-dominance-epistasis of polygenes (model D). In cross Farid-06 × Shafaq, the duration was controlled by additive-dominanceepistasis of 2 major genes (model B-1). However, in crosses Parula × Blue Silver and TD-1 × D-97603, the period of grain filling was under the control of 2 mixed groups of genes including additive-dominant-epistatic major genes plus the additive-dominant-epistasis of polygenes (model E and model E-1, respectively). In cross Hashim-08 × LU-26, the variation and heritability of the polygenes were greater than those of the major gene, whereas these components were low in cross Parula × Blue Silver. In crosses Farid-06 × Shafaq and TD-1 × D-97603, no polygenes were involved and the duration of grain filling was mainly under the influence of major genes. For the duration of grain filling, the maximum environmental variation revealed the influence of environment. Results suggested that due to its maximum heritability, early selection would be feasible in cross Hashim-08 × LU-26, while due to low heritability and variation in cross Parula × Blue Silver, delayed selection will be effective. Yield improvement based on duration of grain filling could be done through selection in later generations until the accumulation of the maximum favorable additive genes is achieved.

<b>Genetic effects for controlling stripe rust (<i>Puccinia striiformis</i> f. sp. <i>tritici</i>) resistance in wheat through joint segregation analysis

“…Suitable genetic models for each cross combination were determined by using maximum log of likelihood estimates (Wang & Gai, 1997) and Akaike's information criterion (Akaike, 1977 ) and Kolmogorove's statistics (Dn) were used as goodness of fit tests to determine whether the selected model sufficiently explains the data (Table 5 and 6). However, if for a particular genetic model, none of these five statistics were found significant, then the data were adequately fit to the model (Gai & Wang, 1998;Ullah et al, 2014a). The data were analyzed by using sin.exe software and the major gene-polygene mixed inheritance model to a joint analysis of multi-generations .…”