Generation mean analysis for quantitative traits in sesame (Sesamum indicum L.) crosses

Abstract

To study the nature and magnitude of gene effects for yield and its components in sesame (Sesamum indicum L.) we carried out generation mean analysis using the following four crosses of different sesame cultivars: VS 9510 x Co1; NIC 7907 x TMV 3; Cianno 13/10x VRI 1; and Si 1115/1 x TMV 3. The P 1 , P 2 , F 1 , F 2 , BC 1 and BC 2 of these generations were studied for seven quantitative traits. The analysis showed the presence of additive, dominance and epistatic gene interactions. The additive dominance model was adequate for plant height in the NIC 7907 x TMV3 and Si 1115/1x TMV 3 crosses and for capsule length in the VS 9510 x Co1, NIC 7907 x TMV 3 and Si 1115/1 x TMV 3 crosses. An epistatic digenic model was assumed for the remaining crosses. Duplicate-type epistasis played a greater role than complementary epistasis. The study revealed the importance of both additive and non-additive types of gene action for all the traits studied.

Generation mean analysis of phosphorus‐use efficiency in freely nodulating soybean crosses grown in low‐phosphorus soil

“…Similarly, a significant negative additive × dominance gene effect for P‐incorporation efficiency was observed in the E × IF cross, indicating duplicate epistasis between additive‐ and dominance‐increasing alleles (Sharmila et al. ). At least two of the five gene effects were as significant for both PUE and P‐incorporation efficiency for the other crosses, except for E × ME, in which none of the gene effects were significant for PUE.…”

“…The negative significant additive × dominance gene effect that was observed for root P in E × ME indicated that there was duplicate epistasis between additive‐ and dominance‐increasing alleles (Sharmila et al. ). Epistatic gene effects may be considered either complementary or duplicate depending on whether the additive × additive and dominance × dominance interactions are all significant and positive/negative or all significant with one negative and the other positive.…”

“…, Sharmila et al. ). Generation mean analysis produces a genotypic value for each individual such that mean genotypic values can be calculated for families and generations (Pooni and Treharne ).…”

“…Generation mean analysis is a tool for designing the most appropriate breeding approaches to develop crop varieties with desired traits and is commonly used in studies on the inheritance of quantitative traits. This type of analysis provides information on the relative importance of the average effects of the genes (additive effects, dominance deviations and effects due to nonallelic gene interactions) (Pooni and Treharne 1994, Iqbal and Nadeem 2003, Checa et al 2006, Sharmila et al 2007). Generation mean analysis produces a genotypic value for each individual such that mean genotypic values can be calculated for families and generations (Pooni and Treharne 1994).…”

Genetic Statistical Model to Estimate Epistasis, Additive and Dominance Genetic Effects Using Advanced Populations

“…parent 1 ( ), parent 2 ( ), first filial ( ), second generation ( ), first filial of the backcross with recurrent parent 1 ( ) and first filial of the backcross with recurrent parent 2 ( ). Generation mean analysis is a useful technique that provides the estimation of the average effects of the genes (additive, dominance and epistasis) involved in the expression of quantitative traits such as yield and yield components which benefits breeders in designing the most appropriate breeding approaches for developing a new varieties (Pooni & Treharne, 1994;Iqbal & Nadeem, 2003;Checa et al, 2006 andSharmila et al,2007). Genome scans for quantitative trait loci (QTL) have proved to be a successful strategy for identifying genetic effects and interactions (Carlborg et al, 2004).…”