Genetic analysis of various quantitative traits ininter-varietal crosses of Vigna mungo

2016 ◽  
Author(s):  
Shayla Bindra ◽  
R. K. Mittal ◽  
V. K. Sood ◽  
H. K. Chaudhary
Keyword(s):  
Yield Components ◽  
Quantitative Traits ◽  
Gene Action ◽  
Duplicate Gene ◽  
Vigna Mungo ◽  
Dominance Model ◽  
Early Generation ◽  
Gene Effects ◽  
Complementary Gene ◽  
Complementary Gene Action

Gene effects for 13 characters in four crosses of Vigna mungo were studied by six parameter generation mean model to determine the potential for the improvement of yield components. Scaling tests revealed inadequacy of the additive-dominance model for all the traits indicating the presence of non-allelic interactions. Duplicate gene action was observed for six characters in KUG-216 x HPBU-111, five in KUG-216 x Palampur-93, two in IPU-05-13 x Palampur-93 and one in IPU-05-13 x HPBU-111 and complementary gene action for one character each in KUG-216 x Palampur-93 and IPU-05-13 x HPBU-111 cross. Selection in later generations for duplicate gene action and early generation selection involving intermatings in F2 f or complementary gene action should be adopted for harnessing desirable recombinants.

scholarly journals Molecular-Marker-Facilitated Investigations of Quantitative-Trait Loci in Maize. I. Numbers, Genomic Distribution and Types of Gene Action

Genetics ◽  
1987 ◽  
Vol 116 (1) ◽  
pp. 113-125
Author(s):  
M D Edwards ◽  
C W Stuber ◽  
J F Wendel
Keyword(s):  
Quantitative Trait Loci ◽  
Phenotypic Variation ◽  
Quantitative Trait ◽  
Quantitative Traits ◽  
Gene Action ◽  
Individual Plant ◽  
Gene Effects ◽  
Individual Gene ◽  
Trait Loci ◽  
Marker Loci

ABSTRACT Individual genetic factors which underlie variation in quantitative traits of maize were investigated in each of two F2 populations by examining the mean trait expressions of genotypic classes at each of 17–20 segregating marker loci. It was demonstrated that the trait expression of marker locus classes could be interpreted in terms of genetic behavior at linked quantitative trait loci (QTLs). For each of 82 traits evaluated, QTLs were detected and located to genomic sites. The numbers of detected factors varied according to trait, with the average trait significantly influenced by almost two-thirds of the marked genomic sites. Most of the detected associations between marker loci and quantitative traits were highly significant, and could have been detected with fewer than the 1800–1900 plants evaluated in each population. The cumulative, simple effects of marker-linked regions of the genome explained between 8 and 40% of the phenotypic variation for a subset of 25 traits evaluated. Single marker loci accounted for between 0.3% and 16% of the phenotypic variation of traits. Individual plant heterozygosity, as measured by marker loci, was significantly associated with variation in many traits. The apparent types of gene action at the QTLs varied both among traits and between loci for given traits, although overdominance appeared frequently, especially for yield-related traits. The prevalence of apparent overdominance may reflect the effects of multiple QTLs within individual marker-linked regions, a situation which would tend to result in overestimation of dominance. Digenic epistasis did not appear to be important in determining the expression of the quantitative traits evaluated. Examination of the effects of marked regions on the expression of pairs of traits suggests that genomic regions vary in the direction and magnitudes of their effects on trait correlations, perhaps providing a means of selecting to dissociate some correlated traits. Marker-facilitated investigations appear to provide a powerful means of examining aspects of the genetic control of quantitative traits. Modifications of the methods employed herein will allow examination of the stability of individual gene effects in varying genetic backgrounds and environments.

scholarly journals Development of a Five-Parameter Model to Facilitate the Estimation of Additive, Dominance, and Epistatic Effects with a Mediating Using Bootstrapping in Advanced Generations of Wheat (Triticum aestivum L.)

Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1325
Author(s):  
Ahmed E. A. Khalaf ◽  
Mohamed A. M. Eid ◽  
Kamal H. Ghallab ◽  
Sherif R. M. El-Areed ◽  
Ahmed A. M. Yassein ◽  
...  
Keyword(s):  
Gene Action ◽  
Mathematical Proof ◽  
Triticum Aestivum L ◽  
Algebraic Solution ◽  
Analysis Method ◽  
Dominance Model ◽  
Gene Effects ◽  
Local Varieties ◽  
Variable Generation ◽  
1000 Grain Weight

As a result of two crosses among three local varieties of wheat, five populations (P1, P2, F5, F6 and F7) were used as parents and grown during two successive seasons; 2016/2017 and 2017/2018. To estimate five types of gene action (e.g., mean effects, additive, dominance, additive × additive, and dominance × dominance), five formulas were developed from with algebraic solution, algebraic proof, and mathematical proof. Besides, to test adequate of a simple additive-dominance model, three formulas A, B, and C scaling test were developed. The path analysis method by PROCESS Macro, AMOS, and Bootstrapping was employed to assess the relationships between grain yield/plant (GYP) as the dependent variable and each one of the number of spikes (NS) and 1000-grain weight (TW) as the independent variables. The results show that there are eight validated equations used to estimate the scaling test (A, B and C) and five types of gene effects (m, a, D, I and L), respectively. Confidence interval using Bootstrapping results indicate that TW was played as the partial mediator between NS as an exogenous variable and GYP as an endogenous variable. Generation means analysis is a relatively simple and statistically reliable tool suitable for the fundamental estimation of different genetic influences.

scholarly journals Assessment of Gene Action for Grain Micronutrient Content, Yield and Yield Contributing Traits in Rice (Oryza sativa L.)

2020 ◽  
pp. 56-63
Author(s):  
Ashutosh Kumar ◽  
Avinash Kumar ◽  
N. K. Singh ◽  
Rajesh Kumar ◽  
. Nilanjaya ◽  
...  
Keyword(s):  
Gene Action ◽  
Oryza Sativa L ◽  
Zinc Content ◽  
Dominance Model ◽  
Gene Effects ◽  
Gene Effect ◽  
Biotechnological Approach ◽  
Zn Content ◽  
H Gene ◽  
Iron And Zinc

Biofortification of food crops using conventional breeding or biotechnological approach is gaining momentum to alleviate micronutrient malnutrition.  Rice is a nice choice for biofortification of grain iron and zinc content as this is a cheap and chief staple food for millions of peoples world-wide particularly the poor. In present study, generation mean analysis was done to estimate the nature and magnitude of gene effects for grain iron and zinc content in rice cross Khusisoi-RI-Sareku × IR 91175-27-1-3-1-3.  Scaling test and Joint scaling test indicated the influence of epistasis on the expression of yield, its component traits and grain Fe and Zn content and inadequacy of additive-dominance model to explain the variation in different generations. Dominance [h] gene effect was of higher magnitude as compared to additive [d] gene effect for both grain iron and grain zinc content.  Additive × additive, additive × dominance and dominance × dominance component was significant for both grain Fe and Zn content, whereas dominance × dominance component was predominant for both grain Fe and Zn content. Dominance [h] gene effect and dominance × dominance interaction acted in opposite directions, indicating duplicate type of gene action controlling the expression of both grain Fe and grain Zn content which could be a bottleneck to exploit heterosis. Heterosis breeding and recombination breeding with postponement of selection till later generations, could be effective in improving both grain Fe and grain Zn content in rice.

scholarly journals Estimation of Gene Action and Interaction for Some Quantitative Characters in Rice (Oryza sativa L.) by Generation Mean Analysis

2021 ◽  
Vol 12 (6) ◽  
pp. 737-744
Author(s):  
Amrita Kumari ◽  
◽  
B. K. Senapati ◽  
Anita Roy Aich ◽  
Aditya Pratap Singh ◽  
...  
Keyword(s):  
Gene Action ◽  
Oryza Sativa L ◽  
Basic Mechanism ◽  
Generation Mean Analysis ◽  
Dominance Model ◽  
Rice Varieties ◽  
Gene Effects ◽  
Quantitative Characters ◽  
Days To Maturity ◽  
Main Gene

The present investigation was conducted to understand the genetic action for controlling the inheritance of some quantitative characters. The experimental materials consisted of three rice varieties, i.e., Mahsuri, Bhutmuri, IR36 and F1, F2, and F3 populations of Mahsuri×Bhutmuri (Cross I) and IR36×Bhutmuri (Cross II). To conduct the generation mean analysis, the parents and their F1, F2, and F3 populations were evaluated during June to October month of Kharif 2016 and Kharif 2017. Generation mean analysis was done for eighteen quantitative characters following the five parameter model. The Analysis of Variance revealed significant differences among the five generations for all the characters studied. The results of the scaling tests and joint scaling test revealed that the Simple additive-dominance model was inadequate for days to 50% flowering, days to maturity, number of panicles plant-1, number of primary branches panicle-1, number of secondary branches panicle-1 in Cross I, while it was for plant height, number of tillers plant-1, number of panicles plant-1, number of grains panicle-1, number of filled grains panicle–1 and fertility % in Cross II. Hence, the present studies have revealed that epistasis as a basic mechanism that cannot be ignored. Thus, formulating breeding policies on only main gene effects i.e. additive and dominance could be misleading.

scholarly journals Prescreening Slash Pine and Cronartium Pedigrees for Evaluation of Complementary Gene Action in Fusiform Rust Disease

Plant Disease ◽  
1999 ◽  
Vol 83 (4) ◽  
pp. 385-389 ◽  
Author(s):  
H. E. Stelzer ◽  
R. L. Doudrick ◽  
T. L. Kubisiak ◽  
C. D. Nelson
Keyword(s):  
Gene Action ◽  
Rust Fungus ◽  
Slash Pine ◽  
Rust Disease ◽  
Fusiform Rust ◽  
Interaction Studies ◽  
Complementary Gene ◽  
Sib Families ◽  
Host Families ◽  
Complementary Gene Action

Single-urediniospore cultures of the fusiform rust fungus were used to inoculate seedlings from 10 full-sib families of a five-parent slash pine diallel at two different times in 1994. The presence or absence of fusiform rust galls was recorded for each inoculated seedling at 9 months postinoculation, and percent infection levels for each family-inoculum-time combination were used for detecting differences among host families and fungal cultures and for identifying differential interactions. The existence of differential interactions between two or more fungal cultures and two or more host families verifies that complementary gene action does exist in this pathosystem. Some host families may be excluded from more detailed interaction studies on the basis of their redundancy and lack of participation in differential interactions.

scholarly journals Genetic Variance Components in Cotton by Generation Mean Analysis

2021 ◽  
Vol 3 (2) ◽  
pp. 72-85
Author(s):  
A. Isong ◽  
A. Balu ◽  
A. Ahmed ◽  
J. O. Mbe ◽  
I. G. Mohammed ◽  
...  
Keyword(s):  
Variance Components ◽  
Quantitative Traits ◽  
Genetic Variance ◽  
Gene Action ◽  
Dominance Effect ◽  
Generation Mean Analysis ◽  
Seed Cotton ◽  
Gene Effects ◽  
Main Effect ◽  
Additive Gene

The mode of gene action for the expression of quantitative traits is decided by the predominance of variances due to additive, dominance and epistasis gene effects. In this experiment, involving four F1 crosses (TCH1716 x TCB37, TCH1705-101 x TCB209, KC2 x TCB26 and TSH0250 x DB3) of upland cotton, inheritance of major yield components by Generation Mean Analysis was investigated. The investigation revealed that both additive and dominance gene effects were involved in the expression of most of the yield contributing traits. One or more types of epistatic interaction effects were prevalent for all the characters and thus played a major role in the control of the characters. The inheritance of the traits was found to be complex in lieu of the low heritability estimates and genetic advance over mean. For seed cotton yield per plant, the dominance x dominance interaction effect was positively significant for all the crosses, the additive x dominance effect was positively significant only in cross 1 and the dominance main effect showed negative significant in all crosses. The dominance (h) and dominance x dominance (l) effects were of opposite signs in all the crosses indicating the presence of duplicate epistasis in all the crosses. To harness additive gene effects for improvement of some of the traits, breeding methods with postponement of selection to later generation should be adopted.

scholarly journals Estimation of Gene Action for Seed Yield and Component Traits using Generation Mean Analysis in Pigeonpea [Cajanus cajan (L.) Millspaugh]

2022 ◽  
Author(s):  
Tuntun Naing ◽  
S.K. Verma ◽  
R.K. Panwar ◽  
A.K. Gaur ◽  
Charupriya Chauhan ◽  
...  
Keyword(s):  
Quantitative Traits ◽  
Gene Action ◽  
Morphological Characters ◽  
Generation Mean Analysis ◽  
Dominance Model ◽  
Additive Gene Action ◽  
High Magnitude ◽  
Component Traits ◽  
Additive Gene ◽  
Number Of Seeds

Background: For improvement of quantitative traits the information on nature of gene action is an important asset for plant breeders. However, the information on gene action for yield and its attributes is scanty in pigeonpea crop. Methods: The present experiment was carried out during kharif 2018-2020 at GBPUAT, Pantnagar, Uttarakhand. The experimental material consisted of six generations of three crosses viz., PADT-16 × PUSA 992, PADT-16 × UPAS 120 and PADT-16 × PAU 881. The observations were recorded on nine morphological characters. The gene action was estimated by three parameters model of Jinks and Jones if scaling tests were non significant and six parameters model of Hayman if scaling tests were significant. Result: For majority of traits in all three crosses, epistatic gene action was present as scaling tests were found to be significant. However, for traits number of primary branches, number of secondary branches and number of seeds per pod in cross PADT-16 × UPAS 120 a simple additive/dominance model was found to be adequate. In general, magnitude of dominance was found to be higher as compared to corresponding additive gene action. The high magnitude of dominance indicated that heterosis breeding is rewarding in these characters.

Epistasis and complementary gene action adequately account for the genetic bases of transgressive segregation of kilo-grain weight in rice

Euphytica ◽  
2011 ◽  
Vol 180 (2) ◽  
pp. 261-271 ◽  
Author(s):  
Donghai Mao ◽  
Touming Liu ◽  
Caiguo Xu ◽  
Xianghua Li ◽  
Yongzhong Xing
Keyword(s):  
Gene Action ◽  
Transgressive Segregation ◽  
Grain Weight ◽  
Complementary Gene ◽  
Complementary Gene Action ◽  
Genetic Bases

Combining ability analysis for yield and contributing traits in short duration rice (Oryza sativa L.)

2020 ◽  
Vol 57 (4) ◽  
pp. 271-276
Author(s):  
Vineeta Singh ◽  
DK Dwivedi ◽  
NA Khan ◽  
RL Verma ◽  
Manish Kumar ◽  
...  
Keyword(s):  
Short Duration ◽  
Yield Components ◽  
Gene Action ◽  
Oryza Sativa L ◽  
Genetic Parameter ◽  
Breeding Value ◽  
Parental Genotype ◽  
Additive Gene Action ◽  
Gene Effects ◽  
Additive Gene

The breeding value is an important genetic parameter determines utility of lines/genotypes to be used as parent in breeding program. This study was aimed at dissecting the breeding values (combining abilities) in 8 short duration rice lines for yield and 15 attributing traits. Altogether, 28 F1s developed under half-diallel fashion along with eight parents were evaluated. The study revealed importance of both additive and non-additive gene effects in governing yield and yield components with preponderance of non-additive gene action for most of the yield components. Additive gene action was found important for 1000-grain weight. The parental genotype (NUD3) and (NDR 359) were found to be good general combiners. The hybrids namely NDR359/Sarjoo-52, NDR359/NUD2, NDR359/NDRK5088, NDR359/NDR1, NDR359/Nagina22, NDR359/NUD3, NDR359/CSR10, Sarjoo52/NDRK5088, Sarjoo52 X NDR 1, NUD 2/NDR1, NUD 2/NUD3, NDRK5088/Nagina22, NDRK5088/NUD3, NDRK5088/CSR10, NUD 3/Nagina 22, Nagina 22/NUD3, NUD3/CSR 10 have shown significant favourable sca effect for yield and different yield components.

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