scholarly journals Genome-Wide Association Analyses Identify QTL Hotspots for Yield and Component Traits in Durum Wheat Grown under Yield Potential, Drought, and Heat Stress Environments

2018 ◽  
Vol 9 ◽  
Author(s):  
Sivakumar Sukumaran ◽  
Matthew P. Reynolds ◽  
Carolina Sansaloni
Keyword(s):  
Heat Stress ◽  
Durum Wheat ◽  
Genome Wide Association ◽  
Yield Potential ◽  
Association Analyses ◽  
Genome Wide ◽  
Component Traits ◽  
Stress Environments ◽  
Drought And Heat Stress

scholarly journals Genome-wide association study and Mendelian randomization analysis provide insights for improving rice yield potential

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jing Su ◽  
Kai Xu ◽  
Zirong Li ◽  
Yuan Hu ◽  
Zhongli Hu ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Rice Yield ◽  
Genome Wide Association ◽  
Yield Potential ◽  
Genome Wide ◽  
Component Traits ◽  
Effect On Yield

AbstractRice yield per plant has a complex genetic architecture, which is mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW), and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. To understand the genetic basis of the relationship between rice yield and component traits, we investigated the four traits of two rice hybrid populations (575 + 1495 F1) in different environments and conducted meta-analyses of genome-wide association study (meta-GWAS). In total, 3589 significant loci for three components traits were detected, while only 3 loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus/gene affected component traits to further enhance yield is recommended. Mendelian randomization design is adopted to investigate the genetic effects of loci on yield through component traits and estimate the genetic relationship between rice yield and its component traits by these loci. The loci for GPP or TP mainly had a positive genetic effect on yield, but the loci for KGW with different direction effects (positive effect or negative effect). Additionally, TP (Beta = 1.865) has a greater effect on yield than KGW (Beta = 1.016) and GPP (Beta = 0.086). Five significant loci for component traits that had an indirect effect on yield were identified. Pyramiding superior alleles of the five loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice. Our findings provided a rationale for using component traits as indirect indices to enhanced rice yield, which will be helpful for further understanding the genetic basis of yield and provide valuable information for improving rice yield potential.

scholarly journals Genome-Wide Association Analyses of Biological Responses to Heat Stress in Pigs

2015 ◽  
Author(s):  
Kwan-Suk Kim ◽  
Eui-Soo Kim ◽  
Jacob T. Seibert ◽  
Aileen F. Keating ◽  
Lance H. Baumgard ◽  
...  
Keyword(s):  
Heat Stress ◽  
Genome Wide Association ◽  
Association Analyses ◽  
Biological Responses ◽  
Genome Wide

scholarly journals Genetic Basis of Relationship Between Yield and its Component Traits in Rice Revealed by Genome-Wide Association and Mendelian Randomization Study

2020 ◽  
Author(s):  
Jing Su ◽  
Kai Xu ◽  
Chao Wu ◽  
Zirong Li ◽  
Zhongli Hu ◽  
...  
Keyword(s):  
Genetic Basis ◽  
Mendelian Randomization ◽  
Rice Yield ◽  
Genome Wide Association ◽  
Yield Potential ◽  
Genome Wide ◽  
Component Traits ◽  
Selection For ◽  
Ideotype Breeding ◽  
Effect On Yield

Abstract BackgroundRice yield has a complex genetic architecture, which mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW) and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. Thus, it is important that studying the genetic basis of relationship between rice yield and component traits and clarifying the effects of each component trait on yield. Main textIn this study, we carried out meta-analyses of genome-wide association study (Meta-GWAS) with two population (575 + 1495 F1) in different environment for yield and its three component traits in rice. Totally, 3589 significant loci for three components traits were detected, while only 3 significant loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus (QTL)/gene affected component traits to further enhance yield is recommended. A Mendelian randomization (MR) design was adopted to further estimate the causal relationship between rice yield and its component traits. Both GPP (Beta=0.086, 95% CI: 0.030~0.141, P=0.003) and TP (Beta=1.865, 95% CI: 1.035~2.694, P<0.0001) has a positive causal relationship with yield, but no significant relationship between KGW and yield (Beta=0.456, 95% CI: -0.119~1.031, P=0.120) was observed. Additionally, TP (Beta=1.865) has a greater effect on yield than GPP (Beta=0.086). Four significant loci for TP and GPP with indirect effect on yield were identified. Pyramiding superior alleles of the four loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice.ConclusionsOur results suggested rice production would improve by ideotype breeding based on selection for GPP and TP. By studying the nature and strength of the relationship between yield and its components, provide genetic insights for further improving rice yield potential.

scholarly journals Genome-wide association study and Mendelian randomization analysis provide insights for improving rice yield potential

2020 ◽  
Author(s):  
Jing Su ◽  
Kai Xu ◽  
Chao Wu ◽  
Zirong Li ◽  
Zhongli Hu ◽  
...  
Keyword(s):  
Association Study ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Rice Yield ◽  
Genome Wide Association ◽  
Yield Potential ◽  
Genome Wide ◽  
Component Traits ◽  
Effect On Yield

Abstract Background: Rice yield has a complex genetic architecture, which mainly determined by its three component traits: the number of grains per panicle (GPP), kilo-grain weight (KGW) and tillers per plant (TP). Exploring ideotype breeding based on selection for genetically less complex component traits is an alternative route for further improving rice production. Thus, it is important that studying the genetic basis of relationship between rice yield and component traits and selecting the component traits to improve the rice production. Main text: In this study, we carried out meta-analyses of genome-wide association study (Meta-GWAS) with two populations (575 + 1495 F1) in different environments for yield and its three component traits in rice. 3589 significant loci for three components traits were detected, while only 3 significant loci for yield were detected. It indicated that rice yield is mainly controlled by minor-effect loci and hardly to be identified. Selecting quantitative trait locus (QTL)/gene affected component traits to further enhance yield is recommended. Mendelian randomization (MR) design was adopted to investigate the genetic effects of loci on yield through component traits and estimate the genetic relationship between rice yield and its component traits by these loci. The loci for GPP or TP mainly had a positive genetic effect on yield, but the loci for KGW with different direction of effects (positive effect or negative effect). Additionally, TP (Beta=1.865) has a greater effect on yield than KGW (Beta=1.016) and GPP (Beta=0.086). Five significant loci for component traits with indirect effect on yield were identified. Pyramiding superior alleles of the five loci revealed improved yield. A combination of direct and indirect effects may better contribute to the yield potential of rice.Conclusions: Our findings provided a rationale for using component traits as indirect indices to enhanced rice yield, which will be helpful for further understanding the genetic basis of yield, and provide valuable information for improving rice yield potential.

scholarly journals 250 Genome wide Association analyses for meat quality traits in multibreed and crossbred beef cattle.

2018 ◽  
Vol 96 (suppl_3) ◽  
pp. 84-84
Author(s):  
M Abo-Ismail ◽  
J Crowley ◽  
E Akanno ◽  
C Li ◽  
P Stothard ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Meat Quality ◽  
Genome Wide Association ◽  
Quality Traits ◽  
Association Analyses ◽  
Meat Quality Traits ◽  
Genome Wide

scholarly journals Solvent Retention Capacity and Gluten Protein Composition of Durum Wheat Flour as Influenced by Drought and Heat Stress

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1000
Author(s):  
Maryke Labuschagne ◽  
Carlos Guzmán ◽  
Keneuoe Phakela ◽  
Barend Wentzel ◽  
Angeline van Biljon
Keyword(s):  
Lactic Acid ◽  
Heat Stress ◽  
Durum Wheat ◽  
Stress Conditions ◽  
Severe Drought ◽  
Gluten Protein ◽  
Retention Capacity ◽  
Solvent Retention ◽  
Drought And Heat Stress ◽  
Solvent Retention Capacity

Drought and temperature stress can cause considerable gluten protein accumulation changes during grain-filling, resulting in variations in wheat quality. The contribution of functional polymeric components of flour to its overall functionality and quality can be measured using solvent retention capacity (SRC). The aim of this study was to determine the effect of moderate and severe drought and heat stress on SRC and swelling index of glutenin (SIG) in six durum wheat cultivars with the same glutenin subunit composition and its relation with gluten protein fractions from size exclusion high performance liquid chromatography. Distilled water, sodium carbonate and sucrose SRC reacted similarly to stress conditions, with moderate heat causing the lowest values. Lactic acid SRC and SIG reacted similarly, where severe heat stress highly significantly increased the values. SIG was significantly correlated with sodium dodecyl sulphate sedimentation (SDSS) and flour protein content (FPC) under all conditions. Lactic acid SRC was highly correlated with FPC under optimal and moderate heat stress and with SDSS under moderate drought and severe heat. SIG was negatively correlated with low molecular weight glutenins under optimal and drought conditions, and combined for all treatments. The relationship between SRC and gluten proteins was inconsistent under different stress conditions.

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