Genetic structure of Photosystem II functionality in rice unraveled by GWAS analysis

AbstractRice production is a particularly important crop for the half-world population. Therefore, knowledge about which genes are implicated in the functionality of the Photosystem II, that are still poorly explored could collaborate in the assisted selection of rice improving. In the present study, we applied Genome wide Association Studies of PSII chlorophyll fluorescence under two contrasting environmental conditions in 283 rice accessions highly diverse. A total of 110 significant association SNP-phenotype were observed, and 69 quantitative trait loci identified with a total of 157 genes, of which 38 were highly significant, mapped spread out through rice genome. These underlying regions are enriched in genes related to biotic and abiotic stresses, transcription factors, Calvin cycle, senescence, and grain characters. The correlations analyses PSII chlorophyll fluorescence parameters and some panicle characteristics found here suggest the possibility of developing molecular markers to assist the breeding programs that improve photosynthesis and yield in rice.HighlightThe genetic structure of the Photosystem II functionality in rice was studied by using genome-wide association through chlorophyll fluorescence.

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Prediction of Continuous Phenotypes in Mouse, Fly, and Rice Genome Wide Association Studies with Support Vector Regression SNPs and Ridge Regression Classifier

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) ◽

10.1109/icmla.2015.224 ◽

2015 ◽

Cited By ~ 1

Author(s):

Abdulrhman Aljouie ◽

Usman Roshan

Keyword(s):

Support Vector Regression ◽

Ridge Regression ◽

Association Studies ◽

Rice Genome ◽

Genome Wide Association ◽

Support Vector ◽

Genome Wide Association Studies ◽

Genome Wide

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Domesticated species form a treasure-trove for molecular characterization of Mendelian traits by exploiting the specific genetic structure of these species in across-breed genome wide association studies

Heredity ◽

10.1038/hdy.2011.128 ◽

2012 ◽

Vol 109 (1) ◽

pp. 1-3 ◽

Cited By ~ 7

Author(s):

H-J Megens ◽

M A M Groenen

Keyword(s):

Genetic Structure ◽

Molecular Characterization ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Treasure Trove ◽

Genome Wide

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Genome-wide Association Study-based Identification Genes Influencing Agronomic Traits in Rice (Oryza Sativa L.)

10.21203/rs.3.rs-74749/v1 ◽

2020 ◽

Author(s):

aijun wang ◽

Xinyue Shu ◽

yuqi Jiang ◽

Li Ma ◽

xiaomei jia ◽

...

Keyword(s):

Oryza Sativa ◽

Candidate Genes ◽

Human Population ◽

Agronomic Traits ◽

Association Studies ◽

Rice Genome ◽

Genome Wide Association ◽

High Yield ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract BackgroundRice (Oryza sativa L.) is one of the most important cereal crops, providing the daily dietary intake for approximately 50% of the global human population. To needs of the rapidly increasing human population worldwide, cultivation of rice varieties with high yield and quality, more genes or QTLs association with yield traits are required.ResultsCurrently, correlations among different traits and gene interactions both affect the rice breeding. Here, we re-sequenced 259 rice accessions, generating 1, 371.65 Gb of raw data. Furthermore, we performed genome-wide association studies (GWAS) on 13 agronomic traits using 2.8 million single nucleotide polymorphisms (SNPs) characterized in 259 rice accessions. Phenotypic data and best linear unbiased prediction (BLUP) values of each of the 13 traits over two years of each trait were used for GWAS. The result showed that 816 SNP signals were significantly associated (−log10P≥5) with the 13 agronomic traits. We detected candidate genes related to target traits within 200 kb upstream and downstream of the associated SNP loci, based on linkage disequilibrium (LD) blocks in the whole rice genome. These candidate genes were further identified though haplotype block construction. ConclusionsThis study provides an important genomic resource and valuable new information for breeding high yielding breeding rice cultivars through genomic selection.

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