Genetic diversity analysis and subspecies classification of Thailand rice landraces using DNA markers

Kladmook, Maytinee; Kumchoo, Tanavadee; Hongtrakul, Vipa

doi:10.5897/ajb11.3289

Cited by 6 publications

(5 citation statements)

References 19 publications

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“…The results showed a good consistency between STRUCTURE and DAPC. The population structure analysis using these approaches suggested that the Thai rice landraces could be divided into two main subpopulations, corresponding to indica and japonica groups, similar to the previous reports [21,23,24]. However, the majority of accessions present in our panel were indica rice.…”

Section: Discussionsupporting

confidence: 86%

“…To effectively utilize this germplasm, an assessment and classification of the diversity is necessary. While studies on genetic diversity are available for many rice collections around the world [19,20], those for Thai rice germplasm have been conducted on limited sets of accessions [21][22][23][24][25]. According to the previous studies on the genetic structure of Thai rice evaluated using indel and simple sequence repeat (SSR) markers, two distinct groups of rice accessions have been revealed to correspond to indica and japonica groups [23,24].…”

Section: Introductionmentioning

confidence: 99%

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Estimation of the Genetic Diversity and Population Structure of Thailand’s Rice Landraces Using SNP Markers

et al. 2021

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Rice is a staple food for more than half of the world’s population. Modern rice varieties have been developed for high yield and quality; however, there has been a substantial loss of diversity. A greater number of genetically dynamic landraces could offer valuable and useful genetic resources for rice improvement. In this study, the genetic diversity and population structure of 365 accessions of lowland and upland landraces from four populations from different geographical regions of Thailand were investigated using 75 SNP markers. Clustering analyses using maximum likelihood, Principal Coordinate Analysis (PCoA), and Discriminant Analysis of Principal Components (DAPC) clustered these landraces into two main groups, corresponding to indica and japonica groups. The indica group was further clustered into two subgroups according to the DAPC and STRUCTURE analyses (K = 3). The analysis of molecular variance (AMOVA) analysis results revealed that 91% of the variation was distributed among individuals, suggesting a high degree of genetic differentiation among rice accessions within the populations. Pairwise FST showed the greatest genetic differentiation between the northeastern and southern populations and the smallest genetic differentiation between the northern and northeastern populations. Isolation-by-distance analysis based on a Mantel test indicated a significant relationship between the genetic distance and geographic distance among the Thai rice landraces. The results from this study provide insight into the genetic diversity of Thai rice germplasm, which will enhance the germplasm characterization, conservation, and utilization in rice genetics and breeding.

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Section: Discussionsupporting

confidence: 86%

Section: Introductionmentioning

confidence: 99%

Estimation of the Genetic Diversity and Population Structure of Thailand’s Rice Landraces Using SNP Markers

et al. 2021

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“…Molecular markers are able to reveal variation present between them at DNA level (Ni et al 2002, Chakravarthi andNaravaneni, 2006). These DNA-based markers are highly precise, dependable and not prone to environmental conditions and fluctuations [9][10][11][12][13].…”

Section: Inroductionmentioning

confidence: 99%

Molecular Characterization of Rice Genotypes Using Molecular Markers

Thete A. M.,

Dahat D. V.,

Jambhale V. M.

et al. 2023

IJPSS

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Rice, (Oryza sativa L. 2n=24) belongs to the family Gramineae and subfamily Oryzoideae. Oryza has two cultivated species: Oryza sativa and Oryza glaberrima. Breeding for good-quality traits requires the selection of parents with a wider genetic diversity. Molecular markers are used in molecular biology and biotechnology to identify a sequence of DNA. Molecular markers have played an increasing role in rice breeding for cultivar improvement, screening, selection, and germplasm collections. The present investigation is undertaken to study the genetic diversity among thirty rice genotypes using the ISSR marker. Out of 40 ISSR primers, 9 amplified and showed polymorphism, viz., ISSR 807, ISSR 808, ISSR 809, ISSR 811, ISSR 816, ISSR 823, ISSR 826, ISSR 827 and ISSR 829. A total of 76 loci were generated by amplification with 9 polymorphic primers, out of which 66 loci were polymorphic with an average of 86.84 percent polymorphism. Among ISSR primers, ISSR 807 produced the maximum number of 11 loci. A dendrogram constructed using NTSYSpc 2.02i software grouped all 30 genotypes into two major clusters (clusters A and B). Cluster A Kalbhat alone is present in one sub-cluster at 69.2% similarity with Karjat 2, Jaya, Sairam, Saubhagya Dhan, RPBIO 226, Karjat 6, Ratnagiri 1, DRR Dhan 44, DRR Dhan 45, DRR Dhan 46, MTU 10010, Karjat 7, Swarna Shreya, Sugandha, and Madhumati. In Cluster B Karjat 3 alone forms one sub- cluster and has 70 % similarity with MTU 1001, PKVHMT, JGL 1798, Indrayani, Phule Samruddhi, Phule Maval, Sonsal, Pavana, DRR Dhan 41, kundalika, Bhogawati, Ambemohar, and Phule Radha.

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“…Moreover, there is a higher level of diversity in Thai rice accessions compared to selected rice accessions obtained from International Rice Research Institute (IRRI) germplasm based on InDel markers (Chakhonkaen et al 2012). Limited data shows that Upland Thai rice forms a cluster of tropical japonica (Pathaichindachote et al 2019;Chakhonkaen et al 2012;Kladmook et al 2012), while lowland rice forms indica clusters.…”

Section: Introductionmentioning

confidence: 99%

Population Structure of Nation-Wide Rice in Thailand

Vejchasarn

Shearman

Chaiprom³

et al. 2021

Rice

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Background Thailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice accessions from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored. Results The result of inferred population structure from admixture and clustering analysis illustrated strong evidence of substructure in each geographical region. The results of phylogenetic tree, PCA analysis, and machine learning on population identifying SNPs also supported the inferred population structure. Conclusion The population structure inferred in this study contains five subpopulations that tend to group individuals based on location. So, each subpopulation has unique genetic patterns, agronomic traits, as well as different environmental conditions. This study can serve as a reference point of the nation-wide population structure for supporting breeders and researchers who are interested in Thai rice.

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Genetic diversity analysis and subspecies classification of Thailand rice landraces using DNA markers

Cited by 6 publications

References 19 publications

Estimation of the Genetic Diversity and Population Structure of Thailand’s Rice Landraces Using SNP Markers

Estimation of the Genetic Diversity and Population Structure of Thailand’s Rice Landraces Using SNP Markers

Molecular Characterization of Rice Genotypes Using Molecular Markers

Population Structure of Nation-Wide Rice in Thailand

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