Genome-wide Association Study of Biological Shape Based on Elliptic Fourier Analysis: A Case Study in Rice Grain Shape Variation

Abstract Background Grain weight and grain shape are important agronomic traits that affect the grain yield potential and grain quality of rice. Both grain weight and grain shape are controlled by multiple genes. The 3,000 Rice Genomes Project (3 K RGP) greatly facilitates the discovery of agriculturally important genetic variants and germplasm resources for grain weight and grain shape. Results Abundant natural variations and distinct phenotic differentiation among the subgroups in grain weight and grain shape were observed in a large population of 2,453 accessions from the 3 K RGP. A total of 21 stable quantitative trait nucleotides (QTNs) for the four traits were consistently identified in at least two of 3-year trials by genome-wide association study (GWAS), including six new QTNs (qTGW3.1, qTGW9, qTGW11, qGL4/qRLW4, qGL10, and qRLW1) for grain weight and grain shape. We further predicted seven candidate genes (Os03g0186600, Os09g0544400, Os11g0163600, Os04g0580700, Os10g0399700, Os10g0400100 and Os01g0171000) for the six new QTNs by high-density association and gene-based haplotype analyses. The favorable haplotypes of the seven candidate genes and five previously cloned genes in elite accessions with high TGW and RLW are also provided. Conclusions Our results deepen the understanding of the genetic basis of grain weight and grain shape in rice and provide valuable information for improving rice grain yield and grain quality through molecular breeding.

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Combined Linkage Mapping and Genome-Wide Association Study Identified QTLs Associated with Grain Shape and Weight in Rice (Oryza sativa L.)

Agronomy ◽

10.3390/agronomy10101532 ◽

2020 ◽

Vol 10 (10) ◽

pp. 1532

Author(s):

Ju-Won Kang ◽

Nkulu Rolly Kabange ◽

Zarchi Phyo ◽

So-Yeon Park ◽

So-Myeong Lee ◽

...

Keyword(s):

Linkage Mapping ◽

Genome Wide Association Study ◽

Grain Shape ◽

Genome Wide Association ◽

Width Ratio ◽

Rice Grain ◽

Grain Length ◽

Transplanted Rice ◽

Genome Wide ◽

Length Width

In the current study, we used a linkage mapping–Genome-Wide Association Study (GWAS) joint strategy to investigate quantitative trait loci (QTLs) governing rice grain shape and weight in a doubled haploid (DH) population, using Kompetitive Allele-Specific PCR (KASP) markers. Results revealed the co-detection of the QTLs, qGLE-12-1 and qGLE-12-2 (Chromosome 12), qGTE-3-1 (Chromosome 3), and qGWL-5-1 and qLWRL-5-1 (Chromosome 5), associated with grain length, width, and length–width ratio, by both linkage mapping and GWAS. In addition, qGLL-7-1 (logarithm of the odds (LOD): 18.0, late-transplanted rice) and qGLE-3-1 (LOD: 8.1, early-transplanted rice), and qLWRL-7-1 (LOD: 34.5), detected only by linkage mapping, recorded a high phenotypic variation explained (PVE) of 32.5%, 19.3%, and 37.7% for grain length, and grain length–width ratio, respectively, contributed by the allele from 93-11. Meanwhile, qGWL-5-1 (LOD: 17.2) recorded a high PVE (31.7%) for grain width, and the allele from Milyang352 contributed to the observed phenotypic variation. Furthermore, qGTL-5-1 (LOD: 21.9) had a high PVE (23.3%) for grain thickness. Similarly, qTGWE-5-1 (LOD: 8.6) showed a high contribution to the PVE for grain weight (23.4%). Moreover, QTLs, qGW-5-1, qGT-5-1, qLWR-5-1, and qTGW-5-1 coincided on chromosome 5, flanked with KJ05_17 and KJ05_13 markers. Therefore, these QTLs are suggested to govern rice grain shape and weight. Additionally, the identified candidate genes could play active roles in the regulation of rice grain shape and weight, regarding their predicted functions, and similarity with previously reported genes. Downstream breeding and functional studies are required to elucidate the roles of these candidate genes in the regulation of grain shape and weight in rice.

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A novel rice grain size gene OsSNB was identified by genome-wide association study in natural population

PLoS Genetics ◽

10.1371/journal.pgen.1008191 ◽

2019 ◽

Vol 15 (5) ◽

pp. e1008191 ◽

Cited By ~ 14

Author(s):

Xiaosong Ma ◽

Fangjun Feng ◽

Yu Zhang ◽

Ibrahim Eid Elesawi ◽

Kai Xu ◽

...

Keyword(s):

Grain Size ◽

Association Study ◽

Natural Population ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Rice Grain ◽

Genome Wide

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Genomic Prediction of Biological Shape: Elliptic Fourier Analysis and Kernel Partial Least Squares (PLS) Regression Applied to Grain Shape Prediction in Rice (Oryza sativa L.)

PLoS ONE ◽

10.1371/journal.pone.0120610 ◽

2015 ◽

Vol 10 (3) ◽

pp. e0120610 ◽

Cited By ~ 26

Author(s):

Hiroyoshi Iwata ◽

Kaworu Ebana ◽

Yusaku Uga ◽

Takeshi Hayashi

Keyword(s):

Oryza Sativa ◽

Fourier Analysis ◽

Genomic Prediction ◽

Grain Shape ◽

Oryza Sativa L ◽

Pls Regression ◽

Elliptic Fourier Analysis ◽

Kernel Partial Least Squares ◽

Shape Prediction ◽

Biological Shape

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I36. FUNCTIONAL INTERPRETATION OF GENOME-WIDE ASSOCIATION STUDY FINDINGS IN RHEUMATOID ARTHRITIS: A CASE STUDY

Rheumatology ◽

10.1093/rheumatology/kex060.036 ◽

2017 ◽

Vol 56 (suppl_2) ◽

Author(s):

Gisela Orozco

Keyword(s):

Rheumatoid Arthritis ◽

Association Study ◽

Genome Wide Association Study ◽

Genome Wide Association ◽

Functional Interpretation ◽

Genome Wide

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A high-resolution genome-wide association study of the grain ionome and agronomic traits in rice Oryza sativa subsp. indica

Scientific Reports ◽

10.1038/s41598-021-98573-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Suong T. Cu ◽

Nicholas I. Warnock ◽

Julie Pasuquin ◽

Michael Dingkuhn ◽

James Stangoulis

Keyword(s):

Genome Wide Association Study ◽

Agronomic Traits ◽

Association Studies ◽

Starch Synthesis ◽

Grain Filling ◽

Genome Wide Association ◽

Rice Grain ◽

Genome Wide Association Studies ◽

Potential Candidate ◽

Genome Wide

AbstractThis study presents a comprehensive study of the genetic bases controlling variation in the rice ionome employing genome-wide association studies (GWAS) with a diverse panel of indica accessions, each genotyped with 5.2 million markers. GWAS was performed for twelve elements including B, Ca, Co, Cu, Fe, K, Mg, Mn, Mo, Na, P, and Zn and four agronomic traits including days to 50% flowering, grain yield, plant height and thousand grain weight. GWAS identified 128 loci associated with the grain elements and 57 associated with the agronomic traits. There were sixteen co-localization regions containing QTL for two or more traits. Fourteen grain element quantitative trait loci were stable across growing environments, which can be strong candidates to be used in marker-assisted selection to improve the concentrations of nutritive elements in rice grain. Potential candidate genes were revealed including OsNAS3 linked to the locus that controls the variation of Zn and Co concentrations. The effects of starch synthesis and grain filling on multiple grain elements were elucidated through the likely involvement of OsSUS1 and OsGSSB1 genes. Overall, our study provides crucial insights into the genetic basis of ionomic variations in rice and will facilitate improvement in breeding for trace mineral content.

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Genome-wide association study of rice grain width variation

Genome ◽

10.1139/gen-2017-0106 ◽

2018 ◽

Vol 61 (4) ◽

pp. 233-240 ◽

Cited By ~ 5

Author(s):

Xiao-Ming Zheng ◽

Tingting Gong ◽

Hong-Ling Ou ◽

Dayuan Xue ◽

Weihua Qiao ◽

...

Keyword(s):

Association Study ◽

Seed Size ◽

Large Scale ◽

Genome Wide Association Study ◽

Rice Variety ◽

Genome Wide Association ◽

Grass Species ◽

Rice Grain ◽

Genome Wide ◽

Grain Width

Seed size is variable within many plant species, and understanding the underlying genetic factors can provide insights into mechanisms of local environmental adaptation. Here we make use of the abundant genomic and germplasm resources available for rice (Oryza sativa) to perform a large-scale genome-wide association study (GWAS) of grain width. Grain width varies widely within the crop and is also known to show climate-associated variation across populations of its wild progenitor. Using a filtered dataset of >1.9 million genome-wide SNPs in a sample of 570 cultivated and wild rice accessions, we performed GWAS with two complementary models, GLM and MLM. The models yielded 10 and 33 significant associations, respectively, and jointly yielded seven candidate locus regions, two of which have been previously identified. Analyses of nucleotide diversity and haplotype distributions at these loci revealed signatures of selection and patterns consistent with adaptive introgression of grain width alleles across rice variety groups. The results provide a 50% increase in the total number of rice grain width loci mapped to date and support a polygenic model whereby grain width is shaped by gene-by-environment interactions. These loci can potentially serve as candidates for studies of adaptive seed size variation in wild grass species.

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