scholarly journals Population Structure of Nation-Wide Rice in Thailand

Rice ◽  
2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Phanchita Vejchasarn ◽  
Jeremy R. Shearman ◽  
Usawadee Chaiprom ◽  
Yotwarit Phansenee ◽  
Arissara Suthanthangjai ◽  
...  
Keyword(s):  
Machine Learning ◽  
Population Structure ◽  
Strong Evidence ◽  
Reference Point ◽  
Clustering Analysis ◽  
Agronomic Traits ◽  
Pca Analysis ◽  
Rice Varieties ◽  
Genetic Patterns ◽  
Wide Population

Abstract 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.

scholarly journals Population Structure of Nation-wide Rice in Thailand

2021 ◽  
Author(s):  
Phanchita Vejchasarn ◽  
Jeremy R. Shearman ◽  
Usawadee Chaiprom ◽  
Yotwarit Phansenee ◽  
Tatpong Tulyananda ◽  
...  
Keyword(s):  
Machine Learning ◽  
Population Structure ◽  
Strong Evidence ◽  
Qtl Analysis ◽  
Clustering Analysis ◽  
Agronomic Traits ◽  
Pca Analysis ◽  
Rice Varieties ◽  
Genetic Pattern ◽  
Wide Population

Background: Thailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice varieties 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 SNPs selected by QTL analysis also supported the inferred population structure. Conclusion: The population structure, which was inferred in this study, contains five populations s.t. each population has a unique ecological system, genetic pattern, as well as agronomic traits. 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.

scholarly journals Population Structure of Nation-Wide Rice in Thailand

2021 ◽  
Author(s):  
Phanchita Vejchasarn ◽  
Jeremy R. Shearman ◽  
Usawadee Chaiprom ◽  
Yotwarit Phansenee ◽  
Tatpong Tulyananda ◽  
...  
Keyword(s):  
Machine Learning ◽  
Population Structure ◽  
Strong Evidence ◽  
Qtl Analysis ◽  
Clustering Analysis ◽  
Agronomic Traits ◽  
Pca Analysis ◽  
Rice Varieties ◽  
Genetic Pattern ◽  
Wide Population

Abstract BackgroundThailand is a country with large diversity in rice varieties due to its rich and diverse ecology. In this paper, 300 rice varieties from all across Thailand were sequenced to identify SNP variants allowing for the population structure to be explored.ResultsThe 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 SNPs selected by QTL analysis also supported the inferred population structure.ConclusionThe population structure, which was inferred in this study, contains ve subpopulations such that each subpopulation has a unique ecological system, genetic pattern, as well as agronomic traits. 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.

scholarly journals Population Structure of 93 Varieties of Rice ( Oryza Sativa L. subsp. Hsien Ting) in Qinba, China

2020 ◽  
Author(s):  
Yu Zhang ◽  
Ye wen Wang ◽  
Yue xing Wang ◽  
Shi mao Zheng ◽  
Wan ying Zhou ◽  
...  
Keyword(s):  
Population Structure ◽  
Genetic Variation ◽  
Agronomic Traits ◽  
Distance Matrix ◽  
Mantel Test ◽  
Rice Varieties ◽  
Genetic Distance Matrix ◽  
History Of ◽  
Variation Explained ◽  
Population Genetic Variation

Abstract BackgroundThe Qinba region is the transition region between indica and japonica varieties with a long history of indica varieties planting. 72,824 SNPs data based on GBS method, 48 pairs core primers of SSRs, and 15 agronomic traits were employed to explore the population structure of 93 rice varieties. The Mantel test was used to analyze the distance matrix generated using NlaIII-GBS only, MseI-GBS only, by combining NlaIII-GBS and MseI-GBS data and SSR.ResultIn this study, a total of 379 alleles were obtained using 48 pairs core primer of SSR, encompassing an average of 8.0 alleles per primer. The PPB and PIC was 88.65% and 0.77, respectively. Among these, RM278 possess the highest TNB and NPB, and the PPB in 29 pairs of SSR markers was 100%. RM176 showed the highest PIC. MAF was set to 0.05, and 39,872, 35,547 and 67,621 SNPs were obtained via NlaIII-GBS only, MseI-GBS only, and merged NlaIII-GBS and MseI-GBS data, respectively. The IBS genetic similarity coefficient average was 0.74. The results showed that the correlation between the genetic distance matrix based on NlaIII-GBS and MseI-GBS was the largest (R2=0.88), followed by NlaIII-GBS and SSR (R2=0.35), then by merged NlaIII-GBS and MseI-GBS data and SSR (R2=0.33), and the smallest by MseI-GBS and SSR (R2=0.27). The results showed that the 93 rice varieties could be clustered into two subgroups. Molecular variance analysis revealed that the genetic variation was 2% among populations and 98% within populations. Tajima’s D value was 1.66, and the FST between the two populations was 0.61, and the Nm was 0.16.ConclusionThe population genetic variation explained by SNP was larger than that explained by SSR. Through cluster analysis, the 93 samples were divided into 2 subgroups, with more than 97% of the samples clustered into one subgroup. The gene flow of 93 samples used in this study is larger than that of naturally self-pollinated crops, which may be caused by long-term breeding selection of indica varieties in the Qinba region. However, the genetic structure of the rice population is simple and lacked rare alleles.

scholarly journals Meta-QTL and ortho-MQTL analyses identified genomic regions controlling rice yield, yield-related traits and root architecture under water deficit conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bahman Khahani ◽  
Elahe Tavakol ◽  
Vahid Shariati ◽  
Laura Rossini
Keyword(s):  
Water Deficit ◽  
Root Architecture ◽  
Agronomic Traits ◽  
Heading Date ◽  
Dry Weight ◽  
Genetic Dissection ◽  
Rice Varieties ◽  
Average Confidence ◽  
Stable Qtls ◽  
Genomic Regions

AbstractMeta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.

scholarly journals Genetic Diversity and Population Structure in Landraces and Improved Rice Varieties from India

Rice Science ◽  
2015 ◽  
Vol 22 (3) ◽  
pp. 99-107 ◽  
Author(s):  
Shailesh D. Kumbhar ◽  
Pawan L. Kulwal ◽  
Jagannath V. Patil ◽  
Chandrakant D. Sarawate ◽  
Anil P. Gaikwad ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Population Structure ◽  
Rice Varieties

scholarly journals A multi-approach analysis of the genetic diversity in populations of Astyanax aff. bimaculatus Linnaeus, 1758 (Teleostei: Characidae) from Northeastern Brazil

2008 ◽  
Vol 6 (4) ◽  
pp. 621-630 ◽  
Author(s):  
Vanessa de Carvalho Cayres Pamponet ◽  
Paulo Luiz Souza Carneiro ◽  
Paulo Roberto Antunes de Mello Affonso ◽  
Viviam Souto Miranda ◽  
Juvenal Cordeiro Silva Júnior ◽  
...  
Keyword(s):  
Population Structure ◽  
Human Activities ◽  
Evolutionary History ◽  
Main Channel ◽  
Northeastern Brazil ◽  
Dam Reservoir ◽  
Effective Barrier ◽  
Significant Difference ◽  
Genetic Patterns ◽  
Structure Index

Few reports are available about the ichthyofauna of typical semi-arid rivers, although the regional diversity has been constantly threatened by human activities, mainly related to impoundment and construction of dams. The goal of the present work was to evaluate using different methods, the population genetic structure of a characin fish, Astyanax aff. bimaculatus, widespread throughout hydrographic basins of Bahia, Northeastern Brazil. Morphological (meristic and morphometric data), cytogenetic (karyotype and Ag-NOR), and molecular (RAPD and SPAR) analyses were carried out in specimens collected upstream and downstream of Pedra Dam, in the main channel of Contas River (Contas River Basin), and in the Mineiro stream, which belongs to the adjacent Recôncavo Sul basin. Few external differences were detected among populations, where the individuals collected upstream of Pedra Dam were slightly larger than the others. Cytogenetic data also showed a similar karyotypic pattern (2n=50; 6m+28sm+12st+4a; FN= 96) and NORs located on the short arms of up to two chromosome pairs, with numerical inter- and intra-populational variation. Nonetheless, RAPD and SPAR analyses differentiated reliably the three populations, revealing striking differences in the allele frequencies among the localities studied and a significant difference in population structure index (Fst=0.1868, P<0.0001). The differences between populations within a same river were as significant as those between distinct hydrographic basins, indicating that the dam/reservoir represents an effective barrier to gene flow. Additionally, environmental peculiarities from each locality are also believed to influence the genetic patterns detected herein. On the other hand, the similarity between samples from Contas River and Recôncavo Sul basins could be related to a common evolutionary history, since both basins are geographically close to each other. Finally, the present study shows that a multi-approach analysis is particularly useful in identifying the population structure of widely distributed species and to evaluate the impacts of human activities on natural fish populations.

scholarly journals The use of Principle Component Analysis and MALDI-TOF MS for the differentiation of mineral forming Virgibacillus and Bacillus species isolated from Sabkhas

2020 ◽  
Author(s):  
Rim Abdel Samad ◽  
Zulfa Al Disi ◽  
Mohammad Ashfaq ◽  
Nabil Zouari
Keyword(s):  
Clustering Analysis ◽  
Potential Role ◽  
Protein Profiling ◽  
Bacillus Species ◽  
Pca Analysis ◽  
Bacterial Strains ◽  
Protein Biomarkers ◽  
Maldi Tof Ms ◽  
Maldi Tof ◽  
Tof Ms

Occurrence of mineral forming and other bacteria in mats is well demonstrated. However, their high diversity shown by ribotyping was not explained, although it could explain the diversity of formed minerals. Common biomarkers as well as phylogenic relationships are useful tools to clustering the isolates and predict their potential role in the natural niche. In this study, combination of MALDI-TOF MS with PCA was shown a powerful tool to categorize 35 mineral forming bacterial strains isolated from Dohat Fshaikh sabkha, at northwest of Qatar (23 from decaying mats and 12 from living ones). 23 strains from decaying mats belong to Virgibacillus genus as identified by ribotyping and are shown highly involved in formation of protodolomite and a diversity of minerals. They were used as internal references in categorization of sabkha bacteria. Combination of isolation of bacteria on selective mineral forming media, their MALDI TOF MS protein profiling and PCA analysis established their relationship in a phyloproteomic based on protein biomarkers including m/z 4905, 3265, 5240, 6430, 7765, and 9815. PCA analysis clustered the studied strains into 3 major clusters, showing strong correspondence to the 3 phyloproteiomic groups that were established by the dendrogram. Both clustering analysis means have evidently demonstrated a relationship between known Virgibacillus strains and other related bacteria based on profiling of their synthesized proteins. Thus, larger populations of bacteria in mats can be easily screened for their potential to exhibit certain activities, which is of ecological, environmental and biotechnological significance.

Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant, Evidence from the Biomedical Literature: A Systematic Review (Preprint)

2021 ◽  
Author(s):  
Wael Abdelkader ◽  
Tamara Navarro ◽  
Rick Parrish ◽  
Chris Cotoi ◽  
Federico Germini ◽  
...  
Keyword(s):  
Machine Learning ◽  
Systematic Review ◽  
Strong Evidence ◽  
Clinical Care ◽  
Biomedical Literature ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Learning Approaches ◽  
High Quality ◽  
Applied Machine Learning

BACKGROUND The rapid growth of the biomedical literature makes identifying strong evidence a time-consuming task. Applying machine learning to the process could be a viable solution that limits effort while maintaining accuracy. OBJECTIVE To summarize the nature and comparative performance of machine learning approaches that have been applied to retrieve high-quality evidence for clinical consideration from the biomedical literature. METHODS We conducted a systematic review of studies that applied machine learning techniques to identify high-quality clinical articles in the biomedical literature. Multiple databases were searched to July 2020. Extracted data focused on the applied machine learning model, steps in the development of the models, and model performance. RESULTS From 3918 retrieved studies, 10 met our inclusion criteria. All followed a supervised machine learning approach and applied, from a limited range of options, a high-quality standard for the training of their model. The results show that machine learning can achieve a sensitivity of 95% while maintaining a high precision of 86%. CONCLUSIONS Applying machine learning to distinguish studies with strong evidence for clinical care has the potential to decrease the workload of manually identifying these. The evidence base is active and evolving. Reported methods were variable across the studies but focused on supervised machine learning approaches. Performance may improve by applying more sophisticated approaches such as active learning, auto-machine learning, and unsupervised machine learning approaches.

scholarly journals The Green Revolution shaped the population structure of the rice pathogen Xanthomonas oryzae pv. oryzae

2019 ◽  
Vol 14 (2) ◽  
pp. 492-505 ◽  
Author(s):  
Ian Lorenzo Quibod ◽  
Genelou Atieza-Grande ◽  
Eula Gems Oreiro ◽  
Denice Palmos ◽  
Marian Hanna Nguyen ◽  
...  
Keyword(s):  
Population Structure ◽  
Plant Pathogens ◽  
Crop Improvement ◽  
Green Revolution ◽  
Agricultural Practices ◽  
The Philippines ◽  
Xanthomonas Oryzae ◽  
Rice Varieties ◽  
Evolutionary Trajectory ◽  
The Impact

Abstract The impact of modern agriculture on the evolutionary trajectory of plant pathogens is a central question for crop sustainability. The Green Revolution replaced traditional rice landraces with high-yielding varieties, creating a uniform selection pressure that allows measuring the effect of such intervention. In this study, we analyzed a unique historical pathogen record to assess the impact of a major resistance gene, Xa4, in the population structure of Xanthomonas oryzae pv. oryzae (Xoo) collected in the Philippines in a span of 40 years. After the deployment of Xa4 in the early 1960s, the emergence of virulent pathogen groups was associated with the increasing adoption of rice varieties carrying Xa4, which reached 80% of the total planted area. Whole genomes analysis of a representative sample suggested six major pathogen groups with distinctive signatures of selection in genes related to secretion system, cell-wall degradation, lipopolysaccharide production, and detoxification of host defense components. Association genetics also suggested that each population might evolve different mechanisms to adapt to Xa4. Interestingly, we found evidence of strong selective sweep affecting several populations in the mid-1980s, suggesting a major bottleneck that coincides with the peak of Xa4 deployment in the archipelago. Our study highlights how modern agricultural practices facilitate the adaptation of pathogens to overcome the effects of standard crop improvement efforts.

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