scholarly journals Genetic basis of phenotypic plasticity and genotype x environment interaction in a multi-parental population

2020 ◽  
Author(s):  
Isidore Diouf ◽  
Laurent Derivot ◽  
Shai Koussevitzky ◽  
Yolande Carretero ◽  
Frédérique Bitton ◽  
...  
Keyword(s):  
Phenotypic Plasticity ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
Linear Models ◽  
Global Climate ◽  
Functional Characterization ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Multiple Traits ◽  
Genotype X Environment

AbstractDeciphering the genetic basis of phenotypic plasticity and genotype x environment interaction (GxE) is of primary importance for plant breeding in the context of global climate change. Tomato is a widely cultivated crop that can grow in different geographical habitats and which evinces a great capacity of expressing phenotypic plasticity. We used a multi-parental advanced generation intercross (MAGIC) tomato population to explore GxE and plasticity for multiple traits measured in a multi-environment trial (MET) design comprising optimal cultural conditions and water deficit, salinity and heat stress over 12 environments. Substantial GxE was observed for all the traits measured. Different plasticity parameters were estimated through the Finlay-Wilkinson and factorial regression models and used together with the genotypic means for quantitative trait loci (QTL) mapping analyses. Mixed linear models were further used to investigate the presence of interactive QTLs (QEI). The results highlighted a complex genetic architecture of tomato plasticity and GxE. Candidate genes that might be involved in the occurrence of GxE were proposed, paving the way for functional characterization of stress response genes in tomato and breeding for climate-adapted crop.HighlightThe genetic architecture of tomato response to several abiotic stresses is deciphered. QTL for plasticity and QTL x Environment were identified in a highly recombinant MAGIC population.

scholarly journals Genetic basis of phenotypic plasticity and genotype × environment interactions in a multi-parental tomato population

2020 ◽  
Vol 71 (18) ◽  
pp. 5365-5376 ◽  
Author(s):  
Isidore Diouf ◽  
Laurent Derivot ◽  
Shai Koussevitzky ◽  
Yolande Carretero ◽  
Frédérique Bitton ◽  
...  
Keyword(s):  
Phenotypic Plasticity ◽  
Genetic Basis ◽  
Linear Models ◽  
Global Climate ◽  
Functional Characterization ◽  
Mixed Linear Models ◽  
Multiple Traits ◽  
Great Capacity ◽  
Cultural Conditions

Abstract Deciphering the genetic basis of phenotypic plasticity and genotype × environment interactions (G×E) is of primary importance for plant breeding in the context of global climate change. Tomato (Solanum lycopersicum) is a widely cultivated crop that can grow in different geographical habitats and that displays a great capacity for expressing phenotypic plasticity. We used a multi-parental advanced generation intercross (MAGIC) tomato population to explore G×E and plasticity for multiple traits measured in a multi-environment trial (MET) comprising optimal cultural conditions together with water deficit, salinity, and heat stress over 12 environments. Substantial G×E was observed for all the traits measured. Different plasticity parameters were estimated by employing Finlay–Wilkinson and factorial regression models and these were used together with genotypic means for quantitative trait loci (QTL) mapping analyses. In addition, mixed linear models were also used to investigate the presence of QTL × environment interactions. The results highlighted a complex genetic architecture of tomato plasticity and G×E. Candidate genes that might be involved in the occurrence of G×E are proposed, paving the way for functional characterization of stress response genes in tomato and for breeding climate-adapted cultivars.

scholarly journals Genotype X Environment Interaction of Food Barley

2015 ◽  
Vol 21 ◽  
pp. 41-48
Author(s):  
Gebremedhin Welu
Keyword(s):  
Grain Yield ◽  
Block Design ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Genotype X Environment ◽  
Genotype Effect ◽  
Environment Effects ◽  
Randomized Complete Block Design ◽  
Barley Genotypes

The objective of this experiment was to estimate the magnitude of genotype X environment interaction on grain yield and yield related traits. Twelve varieties of food barley were included in the study planted in randomized complete block design with three replications. The ANOVA of combined and individual location revealed significant differences among the food barley genotypes for grain yield and other traits. The results of ANOVA for grain yield showed highly significant (p≤0.01) differences among genotypes evaluated for grain yield at Maychew and significant (p≤0.05) differences in Korem, Alage and Mugulat. The ANOVA over locations showed a highly significant (p≤0.01) variation for the genotype effect, environment effects, genotype X environment interaction (GEI) effect and significant (p≤0.05) variation for GEI effect of yield and for most of the yield related traits of food barley genotypes. Haftysene, Yidogit, Estayish and Basso were the genotypes with relatively high mean grain yield across all locations and they are highly performing genotypes to the area. Among locations, the highest mean grain yield was recorded at Korem and it was a suited environment to all the genotypes whereas Mugulat is unfavoured one. ECOPRINT 21: 41-48, 2014DOI: http://dx.doi.org/10.3126/eco.v21i0.11903

scholarly journals Genotype x Environment Interaction and Yield-Stability Analyses of Rice Grown in Tropical Inland Swamp

2011 ◽  
Vol 39 (1) ◽  
pp. 220 ◽  
Author(s):  
Adesola L. NASSIR ◽  
Omolayo J. ARIYO
Keyword(s):  
Total Variation ◽  
Yield Stability ◽  
Genotype X Environment Interaction ◽  
Environment Interaction ◽  
Rice Varieties ◽  
Environmental Indices ◽  
Genotype X Environment ◽  
Additional Information ◽  
Gxe Interaction ◽  
The Stability

Twelve rice varieties were cultivated in inland hydromorphic lowland over a four year-season period in tropical rainforest ecology to study the genotype x environment (GxE) interaction and yield stability and to determine the agronomic and environmental factors responsible for the interaction. Data on yield and agronomic characters and environmental variables were analyzed using the Additive Main Effect and Multiplicative Interaction (AMMI), Genotype and Genotype x Environment Interaction, GGE and the yield stability using the modified rank-sum statistic (YSi). AMMI analysis revealed environmental differences as accounting for 47.6% of the total variation. The genotype and GxE interaction accounted for 28.5% and 24% respectively. The first and second interaction axes captured 57% and 30% of the total variation due to GXE interaction. The analysis identified ‘TOX 3107’ as having a combination of stable and average yield. The GGE captured 85.8%of the total GxE. ‘TOX 3226-53-2-2-2’ and ‘ITA 230’ were high yielding but adjudged unstable by AMMI. These two varieties along with ‘WITA 1’ and ‘TOX 3180-32-2-1-3-5’ were identified with good inland swamp environment, which is essentially moisture based. The two varieties (‘TOX 3226-53-2-2-2’ and ‘ITA 230’), which were equally considered unstable in yield by the stability variance, ?2i, were selected by YSi in addition to ‘TOX 3107’, ‘WITA 1’, ‘IR 8’ and ‘M 55’. The statistic may positively complement AMMI and GGE in selecting varieties suited to specific locations with peculiar fluctuations in environmental indices. Correlation of PC scores with environmental and agronomic variables identified total rainfall up to the reproductive stage, variation in tillering ability and plant height as the most important factors underlying the GxE interaction. Additional information from the models can be positively utilized in varietal development for different ecologies.

scholarly journals Genotype x Environment interaction in the yield and fruit quality of passion fruit germplasm grown in the Ecuadorian Littoral

2020 ◽  
Vol 20 (sup3) ◽  
pp. S1829-S1844
Author(s):  
William Viera ◽  
Beatriz Brito ◽  
Eddie Zambrano ◽  
Lenin Ron ◽  
Jorge Merino ◽  
...  
Keyword(s):  
Fruit Quality ◽  
Genotype X Environment Interaction ◽  
Passion Fruit ◽  
Environment Interaction ◽  
Genotype X Environment
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