Development and application of indica–japonica SNP assays using the Fluidigm platform for rice genetic analysis and molecular breeding

Seo, Jeonghwan; Lee, Gileung; Jin, Zhuo; Kim, Backki; Chin, Joong Hyoun; Koh, Hee‐Jong

doi:10.1007/s11032-020-01123-x

Cited by 26 publications

(32 citation statements)

References 64 publications

(68 reference statements)

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“…All eight HYVs used in this study were clustered into indica group based on indica-japonica SNP sets in previous study [28]. Interestingly, some japonica-type SNPs were detected within the genomes of HYVs after resequencing analysis.…”

Section: Discussionmentioning

confidence: 93%

“…The Wx gene contain only synonymous SNP although it is located within Chr6-1, thus it was not selected in our study. However, we previously developed functional SNP marker for Wx gene [28]. The genomic region containing Wx gene is a hotspot of grain quality [38] and has been selected during and after domestication of rice [39].…”

Section: Discussionmentioning

confidence: 99%

“…Out of many SNPs in the genes, only one SNP with substitution polymorphism between indica (IR 8 and TN1) and japonica (Nipponbare and Yukara) per representative gene was selected for the genomic validation. The SNP markers for Fluidigm platform (Fluigim corp., USA) were designed using the method of Seo et al [28]. To design Fluidigm SNP genotyping assays, 60-150 bp sequences flanking the selected SNPs on either side were aligned by BLAST.…”

Section: Snp Marker Development For Fluidigm Platformmentioning

confidence: 99%

“…Five SNP markers out of total 39 SNP markers were designed in 3' or 5' UTR. In addition, 12 agronomic traits related SNP markers in indica-japonica SNP set 2 [28] and four previously developed yield related SNP markers [34] were also used for genotyping of 94 diverse germplasms. Total of 55 SNP markers were genotyped for 94 germplasms using Fluidigm system, and consequently 54 SNP showed polymorphism and clear genotype, except one monomorphic SNP marker designed in Os01g0348900 on Chr1-2 block.…”

Section: Snp Marker Development and Genotyping Using Fluidigm Platformmentioning

confidence: 99%

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Characterization of the Common japonica-Originated Genomic Regions in the High Yielding Varieties Developed from Inter-Subspecific Crosses in Rice (Oryza sativa L.)

Seo

Lee

Han

et al. 2020

Preprint

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The inter-subspecific crossing between indica and japonica subspecies in rice have been utilized to improve yield potential in temperate rice. In this study, a comparative study of the genomic regions in the eight high yielding varieties (HYVs) was conducted with those of the four non-HYV varieties. NGS mapping on the Nipponbare reference genome identified a total of 14 common genomic regions of japonica-originated alleles. Interestingly, the HYVs shared the japonica-originated genomic regions on the nine chromosomes, although they were developed from different breeding programs. A panel of 94 varieties was classified into four varietal groups with the 39 SNP markers from 39 genes residing the japonica-originated genomic regions and 16 additional trait-specific SNPs. As expected, the japonica originated genomic regions were present only in JAP and HYV groups with exceptions for Chr4-1 and Chr4-2. The Wx gene located within Chr6-1 was present in HYV and JAP variety groups, while the yield-related genes were conserved as indica alleles in HYVs. The japonica-originated genomic regions and alleles shared by HYVs can be employed in molecular breeding programs for further development of HYVs in rice.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Snp Marker Development For Fluidigm Platformmentioning

confidence: 99%

Section: Snp Marker Development and Genotyping Using Fluidigm Platformmentioning

confidence: 99%

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Characterization of the Common japonica-Originated Genomic Regions in the High Yielding Varieties Developed from Inter-Subspecific Crosses in Rice (Oryza sativa L.)

Seo

Lee

Han

et al. 2020

Preprint

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“…Genotype and the phenotype data consisting of 240 markers, including KASP markers previously reported [90] to be specific for detecting polymorphism between japonica ssp. and Fluidigm markers [91] specific for detecting polymorphism between indica and japonica subspecies, and 117 rice doubled haploid (DH) lines and the parental lines (93-11 and Milyang352) were used for detecting quantitative trait loci (QTLs) associated with rice grain length, width, thickness, grain length-width ratio, and thousand grain weight. The raw data (Genotype and phenotype) were initially formatted in RStudio (v.1.2.5042; 2009-2020; RStudio Inc., Boston, MA, USA) using fread, pheno.raw, geno.raw, and cbind functions.…”

Section: Construction Of Linkage Maps Qtl Analysis and Gwasmentioning

confidence: 99%

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

et al. 2020

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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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Genetic variation and population structure of Oryza sativa accessions in the AfricaRice collection and development of the AfricaRice O. sativa Core Collection

et al. 2023

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Genetic diversity studies provide an increased understanding of genebank collections and enhance their use for improving global food security. This study explores the genetic variation and population structure of 5738 rice (Oryza sativa L.) accessions representing 39.6% of the O. sativa collection conserved in the AfricaRice genebank of which 74.0% originated from African countries. These accessions were genotyped with 25,904 polymorphic DArTseq-based single nucleotide polymorphisms (SNPs). Genetic distances between pairs of accessions indicate high variability, with 21.0% of pairs being moderately distant and 78.2% highly distant from each other. The genotyped accessions are traditionally grown in six different agro-ecologies from 73 countries. Using neighbor-joining tree, principal component, and modelbased population structure analyses, the accessions were divided into four genotypic groups representing the two O. sativa subspecies, Japonica (787 accessions) and Indica, which were further divided into landraces (1879 accessions), and improved cultivars (3027 accessions), and a fourth small group of admixed accessions. Subclusters identifying a specific agro-ecology (upland, lowland, and mangrove swamp) or originating country were noted. Using the maximum length sub-tree method, we selected 10% of the total accessions to form the "AfricaRice O. sativa Core Collection" (AROSCC). The subset of 600 O. sativa accessions captures more than 95% of the SNP polymorphisms in the entire collection. The AROSCC is an important resource to support pre-breeding and rice improvement programs around the world.

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Development and application of indica–japonica SNP assays using the Fluidigm platform for rice genetic analysis and molecular breeding

Cited by 26 publications

References 64 publications

Characterization of the <em>Common japonica</em>-Originated Genomic Regions in the High Yielding Varieties Developed from Inter-Subspecific Crosses in Rice (<em>Oryza sativa</em> L.)

Characterization of the <em>Common japonica</em>-Originated Genomic Regions in the High Yielding Varieties Developed from Inter-Subspecific Crosses in Rice (<em>Oryza sativa</em> L.)

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

Genetic variation and population structure of Oryza sativa accessions in the AfricaRice collection and development of the AfricaRice O. sativa Core Collection

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