Genetic diversity, identification, and certification of Chilean rice varieties using molecular markers

Becerra, Viviana; Paredes, Mario; Gutiérrez, E. A.; Rojo, Carmen

doi:10.4067/s0718-58392015000400001

Cited by 22 publications

(10 citation statements)

References 21 publications

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“…A wide range of genetic distances represented by the fixation index (F ST values) have been reported in previous studies, such as 0.87 for an elite rice genotype from Chile (Becerra et al, 2015), 0.86 for Ugandan rice (Mogga et al, 2018), and 0.01-0.76 for African rice (Ndjiondjop et al, 2018). In this study, the F ST values of wild rice with landrace, weedy, and bred rice were relatively larger compared to those among the three variety types (Figure 2C).…”

Section: Discussionmentioning

confidence: 95%

Haplotype Variations and Evolutionary Analysis of the Granule-Bound Starch Synthase I Gene in the Korean World Rice Collection

et al. 2021

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Granule-bound starch synthase I (GBSSI) is responsible for Waxy gene encoding the, which is involved in the amylose synthesis step of starch biosynthesis. We investigated the genotypic and haplotypic variations of GBSSI (Os06g0133000) gene, including its evolutionary relatedness in the nucleotide sequence level using single-nucleotide polymorphisms (SNPs), indels, and structural variations (SVs) from 475 Korean World Rice Collection (KRICE_CORE), which comprised 54 wild rice and 421 cultivated represented by 6 ecotypes (temperate japonica, indica, tropical japonica, aus, aromatic, and admixture) or in another way by 3 varietal types (landrace, weedy, and bred). The results revealed that 27 of 59 haplotypes indicated a total of 12 functional SNPs (fSNPs), identifying 9 novel fSNPs. According to the identified novel fSNPs, we classified the entire rice collection into three groups: cultivated, wild, and mixed (cultivated and wild) rice. Five novel fSNPs were localized in wild rice: four G/A fSNPs in exons 2, 9, and 12 and one T/C fSNP in exon 13. We also identified the three previously reported fSNPs, namely, a G/A fSNP (exon 4), an A/C fSNP (exon 6), and a C/T fSNP (exon 10), which were observed only in cultivated rice, whereas an A/G fSNP (exon 4) was observed exclusively in wild rice. All-against-all comparison of four varietal types or six ecotypes of cultivated rice with wild rice showed that the GBSSI diversity was higher only in wild rice (π = 0.0056). The diversity reduction in cultivated rice can be useful to encompass the origin of this gene GBSSI during its evolution. Significant deviations of positive (wild and indica under balancing selection) and negative (temperate and tropical japonica under purifying selection) Tajima's D values from a neutral model can be informative about the selective sweeps of GBSSI genome insights. Despite the estimation of the differences in population structure and principal component analysis (PCA) between wild and subdivided cultivated subgroups, an inbreeding effect was quantified by FST statistic, signifying the genetic relatedness of GBSSI. Our findings of a novel wild fSNPS can be applicable for future breeding of waxy rice varieties. Furthermore, the signatures of selective sweep can also be of informative into further deeper insights during domestication.

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Section: Discussionmentioning

confidence: 95%

Haplotype Variations and Evolutionary Analysis of the Granule-Bound Starch Synthase I Gene in the Korean World Rice Collection

et al. 2021

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“…Hence with the aid of microsatellite makers and clustering data, different distantly related rice genotypes may be combined by intercrossing genotypes such as Aweil rice genotypes with IRRI rice genotypes from different clusters to get hybrid varieties with high heterosis. Many studies have also reported significantly greater allelic diversity of microsatellite markers than other molecular markers (Aguirre et al, 2005) and USA (Xu et al, 2004) and Chile (Becerra et al 2015). The narrow genetic base observed in this study is not surprising and it could be due to the fact that only a few varieties are available in the country.…”

Section: Discussionmentioning

confidence: 98%

Genetic diversity of rice (Oryza sativa L.) accessions collected from Sudan and IRRI using SSR markers

Gasim¹,

Abuanja²,

Abdalla³

2019

Afr. J. Agric. Res.

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The assessment of genetic diversity of the traditional rice varieties or landraces is an essential component in germplasm characterization and conservation to identify potential parents. In the present study SSR markers (588 SSR markers) were used for the assessment of genetic diversity and relatedness among 31 rice accessions. These included 18 accessions from Sudan and 13 from IRRI. Among the SSR markers used only 483 generated polymorphic patterns, and showed 1274 alleles. The number of alleles per locus ranged from 2 (about 214 markers) to 5 (RM16820 and AP3206a) with an average of 2.64 alleles per locus. The polymorphic information content (PIC) values ranged from 0.06 (RM3138, RM10671, SKC3, R1M7, R6M30, S07101 and S12041B) to 0.69 (RM7643), with an average of 0.39. The major allele frequency per locus varied from 32% (RM7643) to 97% (RM3138, RM10671, SKC3, R1M7, R6M30, S07101 and S12041B), with an average of 64%. Among the primers used in the present investigation, RM7643 was highly informative as it recorded the highest PIC value (0.69). The UPGMA resulted in allelic richness of four major clusters in which cluster I is composed of a high number of accessions. The pairwise genetic dissimilarity indices revealed the highest genetic dissimilarity of 62.3% between Pipanfary Red1 and FL478. The lowest genetic dissimilarity was found between NBGS3 and NBGS2 (4.1%), but they showed wide dissimilarity with other accessions. The study highlighted the usefulness of the application markers for efficient characterization of the Sudanese rice accessions.

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“…The quality and quantity of rice seed is usually determined based on its various characteristics and characteristics. Classification of rice varieties in a specific area is of utmost importance to the specialists group for assessing the level of morality, as well as improving the quality of rice outside of the country [5].…”

Section: Introductionmentioning

confidence: 99%

Identification of Rice Quality Through Pattern Classification Using Computer Vision Image Processing

2020

CEIS

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Rice is the source of Pakistan agriculture industry and food. For agriculture, industry and the oldest sector in the world use rice for different purpose. There are many challenges in the particular sector such as their analysis. This analysis mostly often related to its texture, color, shape, grain etc. In this study, Vision system used to check the quality of rice using some texture features such as color, shape and characteristics. In this study Computer Vision Image Processing tool applied on three different types of rice. Using this tool we apply pattern classification using nearest neighbor and K-nearest neighbor algorithm. Using these algorithms we get results of three varieties of rice Bastmati, Jasmine and White rice. In both algorithms white rice result show best from Basmati rice and Jasmine rice. White rice result is 93.75 % which is best as quality wise. Other tool also available like as MATLAB, Mazda etc for future more best prediction.

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Genetic diversity, identification, and certification of Chilean rice varieties using molecular markers

Cited by 22 publications

References 21 publications

Haplotype Variations and Evolutionary Analysis of the Granule-Bound Starch Synthase I Gene in the Korean World Rice Collection

Haplotype Variations and Evolutionary Analysis of the Granule-Bound Starch Synthase I Gene in the Korean World Rice Collection

Genetic diversity of rice (Oryza sativa L.) accessions collected from Sudan and IRRI using SSR markers

Identification of Rice Quality Through Pattern Classification Using Computer Vision Image Processing

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