Cross-species Amplification of Common Bean (Phaseolus vulgaris) EST-SSRs within Hyacinth Bean, Pea and Soybean

Background: The emerging expressed sequence tag-derived simple sequence repeats (EST-SSRs) offer an important approach to investigate plant genetic diversity. Methods: A total of seventy common bean polymorphic EST-SSRs were utilized for assessing genetic diversity among 19 hyacinth, 20 pea and 21 soybean accessions, respectively. The genetic statistics and principal coordinates analysis (PCoA) were conducted by GenAlEx 6.5. Result: The transferability rates of common bean EST-SSRs in hyacinth, pea and soybean were 27.1%, 20.0% and 21.4%. And the ratios of polymorphic SSR markers in these legumes were 42.1%, 85.71% and 100.0%, respectively. The hyacinth, pea and soybean accessions could be assigned to three distinct clusters for the germplasm types greatly depending on the geographic distributions. The present results revealed that the common bean EST-SSRs are highly transferable to hyacinth bean, pea and soybean. Moreover, these transferable markers would provide a set of inexpensive and effective tools for future research on molecular breeding, taxonomy and comparative mapping.

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Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge

Biology Direct ◽

10.1186/s13062-020-00284-1 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Runzhi Zhang ◽

Alejandro R. Walker ◽

Susmita Datta

Keyword(s):

Machine Learning ◽

Error Rates ◽

Average Error ◽

Importance Score ◽

Learning Methods ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Total Variability ◽

The Common ◽

Feature Selecting

Abstract Background Composition of microbial communities can be location-specific, and the different abundance of taxon within location could help us to unravel city-specific signature and predict the sample origin locations accurately. In this study, the whole genome shotgun (WGS) metagenomics data from samples across 16 cities around the world and samples from another 8 cities were provided as the main and mystery datasets respectively as the part of the CAMDA 2019 MetaSUB “Forensic Challenge”. The feature selecting, normalization, three methods of machine learning, PCoA (Principal Coordinates Analysis) and ANCOM (Analysis of composition of microbiomes) were conducted for both the main and mystery datasets. Results Features selecting, combined with the machines learning methods, revealed that the combination of the common features was effective for predicting the origin of the samples. The average error rates of 11.93 and 30.37% of three machine learning methods were obtained for main and mystery datasets respectively. Using the samples from main dataset to predict the labels of samples from mystery dataset, nearly 89.98% of the test samples could be correctly labeled as “mystery” samples. PCoA showed that nearly 60% of the total variability of the data could be explained by the first two PCoA axes. Although many cities overlapped, the separation of some cities was found in PCoA. The results of ANCOM, combined with importance score from the Random Forest, indicated that the common “family”, “order” of the main-dataset and the common “order” of the mystery dataset provided the most efficient information for prediction respectively. Conclusions The results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which could be used to identify the sample origins. This was also supported by the results from ANCOM and importance score from the RF. In addition, the accuracy of the prediction could be improved by more samples and better sequencing depth.

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Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge

10.21203/rs.2.20675/v1 ◽

2020 ◽

Author(s):

Runzhi Zhang ◽

Alejandro R. Walker ◽

Susmita Datta

Keyword(s):

Machine Learning ◽

Feature Selection ◽

Error Rates ◽

Average Error ◽

Importance Score ◽

Learning Methods ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Total Variability ◽

The Common

Abstract BackgroundComposition of microbial communities can be location specific, and the different abundance of taxon within location could help us to unravel city-specific signature and predict the sample origin locations accurately. In this study, the whole genome shotgun (WGS) metagenomics data from samples across 16 cities around the world and samples from another 8 cities were provided as the main and mystery datasets respectively as the part of the CAMDA 2019 MetaSUB “Forensic Challenge”. The feature selection, normalization, three methods of machine learning, PCoA (Principal Coordinates Analysis) and ANCOM (Analysis of composition of microbiomes) were conducted for both the main and mystery datasets.ResultsFeature selection, combined with the machines learning methods, revealed that the combination of the common features was effective for predicting the origin of the samples. The average error rates of 11.6% and 30.0% of three machine learning methods were obtained for main and mystery datasets respectively. Using the samples from main dataset to predict the labels of samples from mystery dataset, nearly 89.98% of the test samples could be correctly labeled as “mystery” samples. PCoA showed that nearly 60% of the total variability of the data could be explained by the first two PCoA axes. Although many cities overlapped, the separation of some cities was found in PCoA. The results of ANCOM, combined with importance score from the Random Forest, indicated that the common “family”, “order” of the main-dataset and the common “order” of the mystery dataset provided the most efficient information for prediction respectively.ConclusionsThe results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which was also supported by the results from ANCOM and importance score from the RF. The analysis utilized in this study can be of great help in field of forensic science to efficiently predict the origin of the samples. And the accurate of the prediction could be improved by more samples and better sequencing depth.

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Morphological and genetic diversity of Senecio vulgaris L. (Asteraceae) in Iran

Acta Botanica Croatica ◽

10.37427/botcro-2021-012 ◽

2021 ◽

Vol 80 (2) ◽

Author(s):

Mostafa Ebadi ◽

Rosa Eftekharian

Keyword(s):

Genetic Diversity ◽

Principal Component ◽

Morphological Characters ◽

Mantel Test ◽

Morphological Data ◽

Principal Coordinates Analysis ◽

Cauline Leaf ◽

Senecio Vulgaris ◽

Molecular Features ◽

Principal Coordinates

Senecio vulgaris L., an annual herb belonging to the Asteraceae, is widely distributed in different regions of the world. There is no information on the intraspecific variations of the morphological and molecular features of this species. In the present investigation, we studied the morphological and genetic diversity of 81 accessions of S. vulgaris collected from 10 geographical populations. Eleven inter simple sequence repeat (ISSR) primers were used for the examination of genetic variations among the populations. Analysis of molecular variance (AMOVA) and GST analyses revealed significant differences among the investigated populations. A significant correlation between genetic distance and geographical distance was revealed by the Mantel test. However, reticulation analysis indicated the occurrence of gene flow among most of the populations studied. Principal component analysis (PCA) plot showed that the number of capitula, length of the cauline leaf and plant height were the most variable morphological characters. Principal coordinates analysis (PCoA) plot revealed two groups of populations, according to molecular and morphological data. The results suggested the existence of possible intraspecific taxonomic ranks within this species.

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Genetic diversity analysis of the Greek lentil (Lens culinaris) landrace ‘Eglouvis’ using morphological and molecular markers

Plant Genetic Resources ◽

10.1017/s1479262118000096 ◽

2018 ◽

Vol 16 (5) ◽

pp. 469-477 ◽

Cited By ~ 5

Author(s):

Georgios F. Tsanakas ◽

Photini V. Mylona ◽

Katerina Koura ◽

Anthoula Gleridou ◽

Alexios N. Polidoros

Keyword(s):

Genetic Diversity ◽

Molecular Markers ◽

Genetic Variability ◽

Morphological Analysis ◽

Phenotypic Variability ◽

Market Price ◽

Genetic Distances ◽

Reaction Products ◽

Principal Coordinates Analysis ◽

Principal Coordinates

AbstractThe Greek lentil landrace ‘Eglouvis’ is cultivated continuously at the Lefkada island for more than 400 years. It has great taste, high nutritional value and high market price. In the present study, we used morphological and molecular markers to estimate genetic diversity within the landrace. Morphological analysis was based on characteristics of the seed. Molecular analysis was performed using simple sequence repeat (SSR) molecular markers in a high-resolution melting (HRM) approach. ‘Samos’ and ‘Demetra’, two of the most widely cultivated commercial lentil varieties in Greece, were used for comparisons. Morphological analysis was performed with 584 seeds randomly selected from a lot. Analysis of seed dimensions and colour distributed the samples in different categories and highlighted the phenotypic variability in ‘Eglouvis’ lentil seeds. Genetic variability was estimated from 91 individual DNA samples with 11 SSR markers using HRM analysis. Genotyping was based upon the shape of the melting curves and the difference plots; all polymerase chain reaction products were also run on agarose gels. Genetic distances of individuals and principal coordinates analysis suggested that ‘Eglouvis’ landrace has a unique genetic background that significantly differs from ‘Samos’ and ‘Demetra’ and no overlapping could be detected. Genetic variability within the ‘Eglouvis’ landrace can be considered in targeted breeding programs as a significant phytogenetic resource of lentils in Greece.

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Genetic Structure and Eco-Geographical Differentiation of Lancea tibetica in the Qinghai-Tibetan Plateau

Genes ◽

10.3390/genes10020097 ◽

2019 ◽

Vol 10 (2) ◽

pp. 97 ◽

Cited By ~ 2

Author(s):

Xiaofeng Chi ◽

Faqi Zhang ◽

Qingbo Gao ◽

Rui Xing ◽

Shilong Chen

Keyword(s):

Genetic Diversity ◽

Cluster Analysis ◽

Gene Flow ◽

Tibetan Plateau ◽

Environmental Changes ◽

Restricted Gene Flow ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Genetic Diversity And Structure ◽

Tanggula Mountains

The uplift of the Qinghai-Tibetan Plateau (QTP) had a profound impact on the plant speciation rate and genetic diversity. High genetic diversity ensures that species can survive and adapt in the face of geographical and environmental changes. The Tanggula Mountains, located in the central of the QTP, have unique geographical significance. The aim of this study was to investigate the effect of the Tanggula Mountains as a geographical barrier on plant genetic diversity and structure by using Lancea tibetica. A total of 456 individuals from 31 populations were analyzed using eight pairs of microsatellite makers. The total number of alleles was 55 and the number per locus ranged from 3 to 11 with an average of 6.875. The polymorphism information content (PIC) values ranged from 0.2693 to 0.7761 with an average of 0.4378 indicating that the eight microsatellite makers were efficient for distinguishing genotypes. Furthermore, the observed heterozygosity (Ho), the expected heterozygosity (He), and the Shannon information index (I) were 0.5277, 0.4949, and 0.9394, respectively, which indicated a high level of genetic diversity. We detected high genetic differentiation among all sampling sites and restricted gene flow among populations. Bayesian-based cluster analysis (STRUCTURE), principal coordinates analysis (PCoA), and Neighbor-Joining (NJ) cluster analysis based on microsatellite markers grouped the populations into two clusters: the southern branch and the northern branch. The analysis also detected genetic barriers and restricted gene flow between the two groups separated by the Tanggula Mountains. This study indicates that the geographical isolation of the Tanggula Mountains restricted the genetic connection and the distinct niches on the two sides of the mountains increased the intraspecific divergence of the plants.

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Temporal diversity changes among 198 Nordic bread wheat landraces and cultivars detected by retrotransposon-based S-SAP analysis

Plant Genetic Resources ◽

10.1017/s1479262108983544 ◽

2008 ◽

Vol 6 (02) ◽

pp. 113-125 ◽

Cited By ~ 11

Author(s):

Shu-Chin Hysing ◽

Torbjörn Säll ◽

Hilde Nybom ◽

Erland Liljeroth ◽

Arnulf Merker ◽

...

Keyword(s):

Genetic Diversity ◽

Bread Wheat ◽

Growth Habit ◽

Gene Diversity ◽

Pedigree Information ◽

Principal Coordinates Analysis ◽

Subsequent Increase ◽

Principal Coordinates ◽

Frequent Exchange ◽

Wheat Landraces

The sequence-specific amplified polymorphism (S-SAP) method was used to genotype 198 Nordic bread wheat landraces and cultivars from the 19th to the 21st centuries. It was shown that theSukkula-9900-LARD retrotransposon primer was highly suitable for resolving closely related wheat materials. Cluster analysis was generally consistent with pedigree information and revealed a clear separation for growth habit but not for countries. A principal coordinates analysis (PCoA) showed a separation into different time periods (before 1910, 1910–1969 and 1970–2003). These results are consistent with the breeding history and pedigree information, indicating that little hybridization has occurred between winter and spring wheat, in contrast to frequent exchange of germplasm between the Nordic countries. Estimates of gene diversity, the PCoA results, and changes in band frequencies across time indicate that plant breeding has led to substantial genetic shifts in Nordic wheat. Diversity was reduced through selections from landraces during the early 20th century, followed by a period of relatively lower genetic diversity, and a subsequent increase and net gains in diversity from the late 1960s onwards through the use of exotic germplasm. Thus, an anticipated loss of overall genetic diversity was found to be negligible, although allele losses have occurred at specific loci.

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Use of expressed sequence tag microsatellite markers for population genetic research of Helicoverpa armigera (Lepidoptera: Noctuidae) from India

The Canadian Entomologist ◽

10.4039/tce.2015.47 ◽

2015 ◽

Vol 148 (2) ◽

pp. 187-199

Author(s):

Thiruvengadam Venkatesan ◽

Vaddi Sridhar ◽

Yan R. Tomason ◽

Sushil Kumar Jalali ◽

Gajanan T. Behere ◽

...

Keyword(s):

Genetic Diversity ◽

Gene Flow ◽

Microsatellite Markers ◽

Population Genetic ◽

Expressed Sequence Tag ◽

Genetic Research ◽

Western India ◽

Diversity Analysis ◽

Lepidoptera Noctuidae ◽

Expressed Sequence

AbstractCotton bollworm, Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae), is a serious pest of several crops throughout the world, representing millions of United States of America dollars worth of damage. This pest can adapt to various cropping systems in a wide geographical range and has high migratory potential. It features high fecundity and can develop resistance to almost all insecticides used for its management. Several investigations to develop microsatellite markers for H. armigera have not been successful because of the paucity of microsatellites in the lepidopteran genome. As well, collections of H. armigera from cotton fields of southern and western India were not yet studied for molecular genetic diversity. The current study aimed to screen publicly available expressed sequence tag resources for simple sequence repeats and assess their potential as DNA markers for assessment of gene flow between collections of southern and western India. We identified 30 polymorphic microsatellites for potential use in diversity analysis of H. armigera collections. Genetic diversity analysis revealed that the collections were widely diverse with population differentiation index (Fst) of 0.17. Furthermore, gene flow analysis revealed a mean frequency of private alleles of 11% within the collections. The microsatellite resources we developed could be widely used for molecular diversity or population genetic research involving this important pest of cotton and food crops.

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Genotyping-by-Sequencing Reveals Molecular Genetic Diversity in Italian Common Bean Landraces

Diversity ◽

10.3390/d11090154 ◽

2019 ◽

Vol 11 (9) ◽

pp. 154 ◽

Cited By ~ 2

Author(s):

Lucia Lioi ◽

Diana L. Zuluaga ◽

Stefano Pavan ◽

Gabriella Sonnante

Keyword(s):

Genetic Diversity ◽

Common Bean ◽

Genotyping By Sequencing ◽

Fixation Index ◽

Most Probable Number ◽

Probable Number ◽

Individual Snps ◽

Starting Point ◽

Genetic Diversity And Structure ◽

The Common

The common bean (Phaseolus vulgaris L.) is one of the main legumes worldwide and represents a valuable source of nutrients. Independent domestication events in the Americas led to the formation of two cultivated genepools, namely Mesoamerican and Andean, to which European material has been brought back. In this study, Italian common bean landraces were analyzed for their genetic diversity and structure, using single nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing (GBS) technology. After filtering, 11,866 SNPs were obtained and 798 markers, pruned for linkage disequilibrium, were used for structure analysis. The most probable number of subpopulations (K) was two, consistent with the presence of the two genepools, identified through the phaseolin diagnostic marker. Some landraces were admixed, suggesting probable hybridization events between Mesoamerican and Andean material. When increasing the number of possible Ks, the Andean germplasm appeared to be structured in two or three subgroups. The subdivision within the Andean material was also observed in a principal coordinate analysis (PCoA) plot and a dendrogram based on genetic distances. The Mesoamerican landraces showed a higher level of genetic diversity compared to the Andean landraces. Calculation of the fixation index (FST) at individual SNPs between the Mesoamerican and Andean genepools and within the Andean genepool evidenced clusters of highly divergent loci in specific chromosomal regions. This work may help to preserve landraces of the common bean from genetic erosion, and could represent a starting point for the identification of interesting traits that determine plant adaptation.

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Does the genetic diversity among pubescent white oaks in southern Italy, Sicily and Sardinia islands support the current taxonomic classification?

European Journal of Forest Research ◽

10.1007/s10342-020-01334-z ◽

2020 ◽

Author(s):

Romeo Di Pietro ◽

Antonio Luca Conte ◽

Piera Di Marzio ◽

Paola Fortini ◽

Emmanuele Farris ◽

...

Keyword(s):

Genetic Diversity ◽

Expressed Sequence Tag ◽

Taxonomic Classification ◽

Genetic Assignment ◽

Molecular Analyses ◽

Genetic Groups ◽

Ecological Features ◽

Weak Separation ◽

Expressed Sequence ◽

Simple Sequence

AbstractMolecular diversity analysis of deciduous pubescent oaks was conducted for populations from Calabria, Sicily and Sardinia. The aims of this study were twofold. First, to provide data on the genetic diversity of pubescent oaks from an understudied area which currently exhibits one of the highest concentrations of pubescent oak species in Europe. Second, to verify if these groups of oaks are genetically distinct and if their identification is in accordance with the current taxonomic classification. Molecular analyses of leaf material of 480 trees from seventeen populations belonging to putatively different pubescent oak species (Quercus amplifolia, Q. congesta, Q. dalechampii, Q. ichnusae, Q. leptobalanos, Q. virgiliana) were performed. Twelve gene-based Expressed Sequence Tag-Simple Sequence Repeat markers were selected, and genetic diversity and differentiation were calculated. The results showed relatively high values of allelic richness, heterozygosity and number of private alleles for the populations investigated. A weak but positive correlation between geographical and genetic distance was detected. Genetic assignment (STRUCTURE) and principle coordinate analyses exhibited a weak separation into two genetic groups which, however, did not correspond to the taxonomic, chorological and ecological features of the populations investigated. Sardinian populations formed one group which was separated from the Calabrian and Sicilian populations. In light of the results obtained, the taxonomic classification for the pubescent white oaks currently reported in the major Italian floras and checklists for the study area was not confirmed by molecular analyses.

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High-Throughput Genotype, Morphology, and Quality Traits Evaluation for the Assessment of Genetic Diversity of Wheat Landraces from Sicily

Plants ◽

10.3390/plants8050116 ◽

2019 ◽

Vol 8 (5) ◽

pp. 116 ◽

Cited By ~ 2

Author(s):

Fiore ◽

Mercati ◽

Spina ◽

Blangiforti ◽

Venora ◽

...

Keyword(s):

Genetic Diversity ◽

Durum Wheat ◽

Extreme Environments ◽

Principal Component ◽

Detailed Knowledge ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Wide Range ◽

Wheat Landraces ◽

Durum Wheat Landraces

During the XX Century, the widespread use of modern wheat cultivars drastically reduced the cultivation of ancient landraces, which nowadays are confined to niche cultivation areas. Several durum wheat landraces adapted to the extreme environments of the Mediterranean region, are still being cultivated in Sicily, Italy. Detailed knowledge of the genetic diversity of this germplasm could lay the basis for their efficient management in breeding programs, for a wide-range range of traits. The aim of the present study was to characterize a collection of durum wheat landraces from Sicily, using single nucleotide polymorphisms (SNP) markers, together with agro-morphological, phenological and quality-related traits. Two modern cv. Simeto, Claudio, and the hexaploid landrace, Cuccitta, were used as outgroups. Cluster analysis and Principal Coordinates Analysis (PCoA) allowed us to identify four main clusters across the analyzed germplasm, among which a cluster included only historical and modern varieties. Likewise, structure analysis was able to distinguish the ancient varieties from the others, grouping the entries in seven cryptic genetic clusters. Furthermore, a Principal Component Analysis (PCA) was able to separate the modern testers from the ancient germplasm. This approach was useful to classify and evaluate Sicilian ancient wheat germplasm, supporting their safeguard and providing a genetic fingerprint that is necessary for avoiding commercial frauds to sustaining the economic profits of farmers resorting to landraces cultivation.

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