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

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.

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Low Genetic Variation and No Detectable Population Structure in Aspergillus fumigatus Compared to Closely Related Neosartorya Species

Eukaryotic Cell ◽

10.1128/ec.5.4.650-657.2006 ◽

2006 ◽

Vol 5 (4) ◽

pp. 650-657 ◽

Cited By ~ 77

Author(s):

Carla Rydholm ◽

George Szakacs ◽

François Lutzoni

Keyword(s):

Genetic Variation ◽

Aspergillus Fumigatus ◽

Data Set ◽

Neosartorya Fischeri ◽

Natural Isolates ◽

Immunosuppressed Patients ◽

History Of ◽

America South ◽

Population Genetic Variation ◽

Intensive Work

ABSTRACT Aspergillus fumigatus is an anamorphic euascomycete mold with a ubiquitous presence worldwide. Despite intensive work to understand its success as a pathogen infecting immunosuppressed patients, the population dynamics and recent evolutionary history of A. fumigatus remain understudied. We examined patterns of genetic variation at three intergenic loci for 70 natural isolates from Europe, North America, South America, Asia, Africa, and Australia. The same loci were used to analyze within-population genetic variation for 33 isolates obtained from five geographic locations. Neither data set detected evidence of population differentiation or found any association between the genetic and geographic distances among these isolates. No evidence for genetic differentiation within the two A. fumigatus mating types was detected. The genetic diversity of A. fumigatus, contrasted with that of its close teleomorphic relatives, Neosartorya fischeri and Neosartorya spinosa, is remarkably low.

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Genetic Characterization of Apulian Olive Germplasm as Potential Source in New Breeding Programs

Plants ◽

10.3390/plants8080268 ◽

2019 ◽

Vol 8 (8) ◽

pp. 268 ◽

Cited By ~ 7

Author(s):

Sion ◽

Taranto ◽

Montemurro ◽

Mangini ◽

Camposeo ◽

...

Keyword(s):

Genetic Variation ◽

Agronomic Traits ◽

Rural Landscape ◽

Sources Of Resistance ◽

Breeding Programs ◽

Potential Source ◽

History Of ◽

Olive Cultivation ◽

Olive Quick Decline Syndrome

The olive is a fruit tree species with a century-old history of cultivation in theMediterranean basin. In Apulia (Southern Italy), the olive is of main social, cultural and economicimportance, and represents a hallmark of the rural landscape. However, olive cultivation in thisregion is threatened by the recent spread of the olive quick decline syndrome (OQDS) disease, thusthere is an urgent need to explore biodiversity and search for genetic sources of resistance. Herein,a genetic variation in Apulian olive germplasm was explored, as a first step to identify genotypeswith enhanced bio-agronomic traits, including resistance to OQDS. A preselected set of nuclearmicrosatellite markers allowed the acquisition of genotypic profiles, and to define geneticrelationships between Apulian germplasm and widespread cultivars. The analysis highlighted thebroad genetic variation in Apulian accessions and the presence of different unique genetic profiles.The results of this study lay a foundation for the organization of new breeding programs for olivegenetic improvement.

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Posterior predictive checks to quantify lack-of-fit in admixture models of latent population structure

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1412301112 ◽

2015 ◽

Vol 112 (26) ◽

pp. E3441-E3450 ◽

Cited By ~ 6

Author(s):

David Mimno ◽

David M. Blei ◽

Barbara E. Engelhardt

Keyword(s):

Population Structure ◽

Genetic Variation ◽

Population Genetic ◽

Association Studies ◽

Model Fit ◽

Widespread Application ◽

Posterior Predictive Checks ◽

Genomic Studies ◽

Population Genetic Variation

Admixture models are a ubiquitous approach to capture latent population structure in genetic samples. Despite the widespread application of admixture models, little thought has been devoted to the quality of the model fit or the accuracy of the estimates of parameters of interest for a particular study. Here we develop methods for validating admixture models based on posterior predictive checks (PPCs), a Bayesian method for assessing the quality of fit of a statistical model to a specific dataset. We develop PPCs for five population-level statistics of interest: within-population genetic variation, background linkage disequilibrium, number of ancestral populations, between-population genetic variation, and the downstream use of admixture parameters to correct for population structure in association studies. Using PPCs, we evaluate the quality of the admixture model fit to four qualitatively different population genetic datasets: the population reference sample (POPRES) European individuals, the HapMap phase 3 individuals, continental Indians, and African American individuals. We found that the same model fitted to different genomic studies resulted in highly study-specific results when evaluated using PPCs, illustrating the utility of PPCs for model-based analyses in large genomic studies.

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Genetic Diversity and Population Structure of 93 Rice Cultivars (Lines) (Oryza Sativa Xian Group) in Qinba in China by 3 Types of Genetic Markers

10.21203/rs.3.rs-1050153/v1 ◽

2021 ◽

Author(s):

Yu Zhang ◽

Yewen Wang ◽

Peijiang Li ◽

Yuexing Wang ◽

Shimao Zheng ◽

...

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Genetic Variation ◽

Genetic Markers ◽

Ssr Markers ◽

Diversity Index ◽

Indica Rice ◽

Mantel Test ◽

Phenotypic Traits ◽

Phenotypic Analysis

Abstract Background: The Qinba region is the transition region between Indica and Japonica varieties in China. It has a long history of Indica rice planting of more than 7000 years and is also a planting area for fine-quality Indica rice. The aims of this study are to explore different genetic markers applied to the analysis population structure, genetic diversity, selection and optimization of molecular markers of Indica rice, thus providing more information for the protection and utilization on germplasm resources of Indica rice. Methods: 15 phenotypic traits, a core set of 48 SSR markers as well as SNPs data obtained by genotyping-by-sequencing (GBS, NlaIII and MseI digestion, referred to as SNPs-NlaIII and SNPs-MseI, respectively) for this panel of 93 samples using the Illumina HiSeq2000 sequencing platform, were employed to explore the genetic diversity and population structure of 93 samples.Results: The average of coefficient of variation (CV) and diversity index (He) were 29.72% and 1.83 ranging from 3.07% to 137.43%, and from 1.45 to 2.03, respectively. The correlation coefficient between 15 phenotypic traits ranged from 0.984 to -0.604. The first four PCs accounted for 70.693% phenotypic variation based on phenotypic analysis. A total of 379 alleles were obtained using SSR markers, encompassing an average of 8.0 alleles per primer. Polymorphic bands (PPB) and polymorphism information content (PIC) was 88.65% and 0.77, respectively. The Mantel test showed that the correlation between the genetic distance matrix based on SNPs-NlaIII and SNPs-MseI was the largest (R2=0.88), and that based on 15 phenotypic traits and SSR was the smallest (R2=0.09). The 93 samples could be clustered into two subgroups by 3 types of genetic markers. Molecular variance analysis revealed that the genetic variation was 2% among populations and 98% within populations (the Nm was 0.16), Tajima’s D value was 1.66, the FST between the two populations was 0.61 based on 72,824 SNPs. Conclusions: The population genetic variation explained by SNPs was larger than that explained by SSRs. The gene flow of 93 samples used in this study was larger than that of naturally self-pollinated crops, which may be caused by long-term breeding selection of Indica rice in the Qinba region. The genetic structure of the 93 samples was simple and lacked rare alleles.

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

Agronomy ◽

10.3390/agronomy11050995 ◽

2021 ◽

Vol 11 (5) ◽

pp. 995

Author(s):

Wanchana Aesomnuk ◽

Siriphat Ruengphayak ◽

Vinitchan Ruanjaichon ◽

Tanee Sreewongchai ◽

Chanate Malumpong ◽

...

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Genetic Differentiation ◽

Isolation By Distance ◽

Mantel Test ◽

Snp Markers ◽

High Yield ◽

Rice Varieties ◽

Rice Landraces ◽

Geographical Regions

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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Reproductive system and population structure in two Hedysarum subspecies. I. Genetic variation within and between populations

Genome ◽

10.1139/g91-061 ◽

1991 ◽

Vol 34 (3) ◽

pp. 396-406 ◽

Cited By ~ 9

Author(s):

Hedi Baatout ◽

Daniel Combes ◽

Mohamed Marrakchi

Keyword(s):

Population Structure ◽

Genetic Variation ◽

Genetic Variability ◽

Population Genetic ◽

Allozyme Variation ◽

Wild Populations ◽

Population Means ◽

Quantitative Characters ◽

Different Populations ◽

Population Genetic Variation

Several samples of wild populations of two subspecies of the genus Hedysarum (H. spinosissimum subspecies capitatum, an outcrosser, and H. spinosissimum subspecies euspinosissimum, a selfer) were examined with respect to variability of 25 quantitative characters and allozyme variation at 13 loci. The amount of phenotypic and genetic variation within and among populations was documented. For most of the 25 quantitative characters, the differences between population means and between the total variances of the populations were higher in the selfer than in the outbreeder. Significant among-population genetic variation was found for nearly all characters in the two subspecies, but the outbreeder had higher within-population variability than the selfer with heterogeneity among characters. However, allozyme variation at 13 loci in about the same number of populations showed higher levels of genetic variability in the outcrossing subspecies capitatum compared with the selfing subspecies euspinosissimum, based on measures of mean number of alleles per locus, mean proportion of polymorphic loci, and mean heterozygosity. Therefore, H. spinosissimum subsp. capitatum appeared to be highly polymorphic in contrast to the greater monomorphism within populations of H. spinosissimum subsp. euspinosissimum. The genetic affinities of different populations of a subspecies are uniformly high, with Nei's genetic identity ranging from 0.983 to 0.997 in the selfing subspecies euspinosissimum and from 0.922 to 1.000 in the outcrossing subspecies capitatum.Key words: Hedysarum, genetic variation, populations, electrophoresis.

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Genetic Diversity and Population Structure of 93 Rice Cultivars (Lines) (Oryza Sativa Xian Group) in Qinba in China By 3 Types of Genetic Markers

10.21203/rs.3.rs-1050153/v2 ◽

2022 ◽

Author(s):

Yu Zhang ◽

Qiaoqiao He ◽

Xixi Zhou ◽

Yewen Wang ◽

Peijiang Li ◽

...

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Genetic Variation ◽

Genetic Markers ◽

Ssr Markers ◽

Diversity Index ◽

Indica Rice ◽

Mantel Test ◽

Phenotypic Traits ◽

Phenotypic Analysis

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Population Structure of Nation-wide Rice in Thailand

10.1101/2021.05.09.443284 ◽

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.

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Population Structure of Nation-Wide Rice in Thailand

10.21203/rs.3.rs-565551/v1 ◽

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.

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Contrasting effects of geographical separation on the genetic population structure of sympatric species of mites in avocado orchards

Bulletin of Entomological Research ◽

10.1017/s0007485314000388 ◽

2014 ◽

Vol 104 (5) ◽

pp. 610-621 ◽

Cited By ~ 4

Author(s):

S. Guzman-Valencia ◽

M.T. Santillán-Galicia ◽

A.W. Guzmán-Franco ◽

H. González-Hernández ◽

M.G. Carrillo-Benítez ◽

...

Keyword(s):

Genetic Diversity ◽

Population Structure ◽

Genetic Variation ◽

Sequence Data ◽

Mite Species ◽

Mantel Test ◽

Sequence Information ◽

Genetic Population ◽

Nucleotide Sequence Data ◽

Geographical Separation

AbstractOligonychus punicae and Oligonychus perseae (Acari: Tetranychidae) are the most important mite species affecting avocado orchards in Mexico. Here we used nucleotide sequence data from segments of the nuclear ribosomal internal transcribed spacers (ITS1 and ITS2) and mitochondrial cytochrome oxidase subunit I (COI) genes to assess the phylogenetic relationships between both sympatric mite species and, using only ITS sequence data, examine genetic variation and population structure in both species, to test the hypothesis that, although both species co-occur, their genetic population structures are different in both Michoacan state (main producer) and Mexico state. Phylogenetic analysis showed a clear separation between both species using ITS and COI sequence information. Haplotype network analysis done on 24 samples of O. punicae revealed low genetic diversity with only three haplotypes found but a significant geographical population structure confirmed by analysis of molecular variance (AMOVA) and Kimura-2-parameter (K2P) analyses. In addition, a Mantel test revealed that geographical isolation was a factor responsible for the genetic differentiation. In contrast, analyses of 22 samples of O. perseae revealed high genetic diversity with 15 haplotypes found but no geographical structure confirmed by the AMOVA, K2P and Mantel test analyses. We have suggested that geographical separation is one of the most important factors driving genetic variation, but that it affected each species differently. The role of the ecology of these species on our results, and the importance of our findings in the development of monitoring and control strategies are discussed.

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