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

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.

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

10.21203/rs.3.rs-28492/v2 ◽

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.

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

10.21203/rs.3.rs-28492/v1 ◽

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.

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Genome-Wide Association Study for Adaptation to Agronomic Plant Density: A Component of High Yield Potential in Spring Wheat

Crop Science ◽

10.2135/cropsci2015.03.0139 ◽

2015 ◽

Vol 55 (6) ◽

pp. 2609-2619 ◽

Cited By ~ 25

Author(s):

Sivakumar Sukumaran ◽

Matthew P. Reynolds ◽

Marta S. Lopes ◽

José Crossa

Keyword(s):

Association Study ◽

Spring Wheat ◽

Genome Wide Association Study ◽

Plant Density ◽

Genome Wide Association ◽

Yield Potential ◽

High Yield ◽

Genome Wide ◽

High Yield Potential

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Genome-Wide Association Study (GWAS) For Cold Tolerance at The Bud Burst Stage in Rice Using SNP Markers

10.21203/rs.3.rs-311085/v1 ◽

2021 ◽

Author(s):

Caijing Li ◽

Jindong Liu ◽

Jianxin Bian ◽

Tao Jin ◽

Baoli Zou ◽

...

Keyword(s):

Low Temperature ◽

Association Study ◽

Cold Tolerance ◽

Genetic Basis ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Bud Burst ◽

Rice Varieties ◽

Rice Landraces ◽

Genome Wide

Abstract Background: Rice is a crop that is very sensitive to low temperature, and its morphological development and production are greatly affected by low temperature. Therefore, understanding the genetic basis of cold tolerance in rice is of great significance for mining favorable genes and cultivating excellent rice varieties. However, there were limited studies focusing on cold tolerance at the bud burst stage, therefore, considerable attention should be paid to the genetic basis of cold tolerance at the bud burst stage (CTBB).Results: In this study, a natural population consisting of 211 rice landraces collected from 15 provinces of China and other countries were firstly used to evaluate the cold tolerance at the bud burst stage. Population structure analysis showed that this population divided into three groups and was rich in genetic diversity. Our evaluation results confered that the japonica rice was more tolerance to cold at the bud burst stage than indica rice. Genome-wide association study (GWAS) were performed through the phenotypic data of 211 rice landraces and 36,727 SNPs dataset under a mixed linear model, and 12 QTLs (P < 0.0001) were identified according to the seedling survival rate (SSR) treated at 4 ℃, in which there are five QTLs (qSSR2-2, qSSR3-1, qSSR3-2, qSSR3-3 and qSSR9) which were co-located with previous studies, and seven QTLs (qSSR2-1, qSSR3-4, qSSR3-5, qSSR3-6, qSSR3-7, qSSR4 and qSSR7) which were reported for the first time. Among these QTLs, qSSR9, harboring the highest-peak SNP, explained biggest phenotypic variation. Through bioinformatics analysis, five genes (LOC_Os09g12440, LOC_Os09g12470, LOC_Os09g12520, LOC_Os09g12580 and LOC_Os09g12720) were nominated as candidates for qSSR9. Conclusion: This natural population consisting of 211 rice landraces with high density SNPs will serve as a better choice for identifying rice QTLs/genes in future, and the detected QTLs associated with cold tolerance in rice bud burst stage will be conducive to further mining favorable genes and breeding of rice varieties under cold stress.

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Common Susceptibility Loci for Male Breast Cancer

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djaa101 ◽

2020 ◽

Author(s):

Sarah Maguire ◽

Eleni Perraki ◽

Katarzyna Tomczyk ◽

Michael E Jones ◽

Olivia Fletcher ◽

...

Keyword(s):

Breast Cancer ◽

Association Study ◽

Genetic Correlation ◽

Male Breast Cancer ◽

Genetic Basis ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Susceptibility Loci ◽

Single Nucleotide ◽

Genome Wide

Abstract Background The etiology of male breast cancer (MBC) is poorly understood. In particular, the extent to which the genetic basis of MBC differs from female breast cancer (FBC) is unknown. A previous genome-wide association study of MBC identified 2 predisposition loci for the disease, both of which were also associated with risk of FBC. Methods We performed genome-wide single nucleotide polymorphism genotyping of European ancestry MBC case subjects and controls in 3 stages. Associations between directly genotyped and imputed single nucleotide polymorphisms with MBC were assessed using fixed-effects meta-analysis of 1380 cases and 3620 controls. Replication genotyping of 810 cases and 1026 controls was used to validate variants with P values less than 1 × 10–06. Genetic correlation with FBC was evaluated using linkage disequilibrium score regression, by comprehensively examining the associations of published FBC risk loci with risk of MBC and by assessing associations between a FBC polygenic risk score and MBC. All statistical tests were 2-sided. Results The genome-wide association study identified 3 novel MBC susceptibility loci that attained genome-wide statistical significance (P < 5 × 10–08). Genetic correlation analysis revealed a strong shared genetic basis with estrogen receptor–positive FBC. Men in the top quintile of genetic risk had a fourfold increased risk of breast cancer relative to those in the bottom quintile (odds ratio = 3.86, 95% confidence interval = 3.07 to 4.87, P = 2.08 × 10–30). Conclusions These findings advance our understanding of the genetic basis of MBC, providing support for an overlapping genetic etiology with FBC and identifying a fourfold high-risk group of susceptible men.

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