scholarly journals Genotyping by Sequencing Reveals Genetic Relatedness of Southwestern U.S. Blue Maize Landraces

2021 ◽  
Vol 22 (7) ◽  
pp. 3436
Author(s):  
Amol N. Nankar ◽  
Richard C. Pratt
Keyword(s):  
Genetic Relatedness ◽  
Plant Traits ◽  
Phenotypic Diversity ◽  
Phenotypic Variability ◽  
Principal Component ◽  
Genotyping By Sequencing ◽  
Genotypic Analysis ◽  
Maize Landraces ◽  
Blue Maize ◽  
Kernel Traits

Maize has played a key role in the sustenance and cultural traditions of the inhabitants of the southwestern USA for many centuries. Blue maize is an important component of the diverse landraces still cultivated in the region but the degree to which they are related is unknown. This research was designed to ascertain the genotypic, morphological, and phenotypic diversity of six representative southwestern blue maize landraces. Their genotypic diversity was examined using tunable genotyping-by-sequencing (tGBS™). A total of 81,038 high quality SNPs were identified and obtained through tGBS. A total of 45 morphological and biochemical traits were evaluated at two locations in New Mexico. The varieties Los Lunas High and Flor del Rio were genetically less related with other southwestern landraces whereas diffusion between Navajo Blue, Hopi Blue, Yoeme Blue, and Taos Blue demonstrated that these landraces were genetically related. Phenotypic variability was highest for kernel traits and least for plant traits. Plant, ear, and kernel traits were fairly consistent within and across locations. Principal component analysis and tGBS showed that Corn Belt variety ‘Ohio Blue’ was distinctly different from southwestern landraces. Genotypic analysis displayed that southwestern landraces are genetically closely related, but selection has resulted in differing phenotypes. This study has provided additional insight into the genetic relatedness of southwestern blue maize landraces.

scholarly journals A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses

2021 ◽  
Vol 12 ◽  
Author(s):  
Felipe Bitencourt Martins ◽  
Aline Costa Lima Moraes ◽  
Alexandre Hild Aono ◽  
Rebecca Caroline Ulbricht Ferreira ◽  
Lucimara Chiari ◽  
...  
Keyword(s):  
Principal Component ◽  
Genotyping By Sequencing ◽  
Snp Markers ◽  
Correct Identification ◽  
Forage Grasses ◽  
Mendelian Segregation ◽  
Breeding Programs ◽  
Tropical Forage ◽  
Genotypic Analysis ◽  
Shiny App

Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones (ACs), self-fertilized individuals, half-siblings (HSs), and full contaminants (FCs), in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation, and clustering analysis (CA). The combination of these methods allowed for the correct identification of all contaminants in all simulated progenies and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid species. The proposed pipeline was made available through the polyCID Shiny app and can be easily coupled with traditional genetic approaches, such as linkage map construction, thereby increasing the efficiency of breeding programs.

scholarly journals Assessment of phenotypic variability among EEA INTA Pergamino sunflower lines: Its relationship with the grain yield and oil content

OCL ◽  
2021 ◽  
Vol 28 ◽  
pp. 33
Author(s):  
Matías Domínguez ◽  
Stefanía Herrera ◽  
Julio Horacio González
Keyword(s):  
Grain Yield ◽  
Oil Content ◽  
Phenotypic Diversity ◽  
Phenotypic Variability ◽  
Morphological Variability ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Breeding Program ◽  
Depth Study ◽  
Selective Forces

The aims of the present study were to assess the phenotypic diversity among 221 sunflower accessions of INTA Pergamino Sunflower Breeding Program, to obtain discriminant functions that allow the classification of new accessions in similar groups and to evaluate the relationship between genetic distance pairwise accessions and hybrid performance for grain yield and oil content. We used 19 quantitative descriptors to evaluate phenotypic and morphological variability. Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were used to evaluate simultaneously all the variables and to describe phenotypic variation patterns of the germplasm. The distribution of germplasm in the dendrogram did not follow a clear pattern with regard to the predefined groups. This study revealed the variability observed among the lines that form the INTA Pergamino breeding program despite the highly selective forces applied to obtain inbred lines that produce superior hybrids for the Argentinean sunflower area. This work demonstrates the need for more in-depth study of genetic variability to be used as a predictor of heterosis in sunflower.

scholarly journals Admixture Analysis Using Genotyping-by-Sequencing Reveals Genetic Relatedness and Parental Lineage Distribution in Highbush Blueberry Genotypes and Cross Derivatives

2020 ◽  
Author(s):  
Krishnanand P. Kulkarni ◽  
Nicholi Vorsa ◽  
Purushothaman Natarajan ◽  
Sathya Elavarthi ◽  
Massimo Iorizzo ◽  
...  
Keyword(s):  
Genetic Relatedness ◽  
Principal Component ◽  
Genotyping By Sequencing ◽  
Vaccinium Corymbosum ◽  
Snp Markers ◽  
Fixation Index ◽  
Nucleotide Polymorphisms ◽  
Admixture Analysis ◽  
Cross Derivatives ◽  
Southern Highbush

Blueberries (Vaccinium section Cyanococcus) are perennial shrubs widely cultivated for their edible fruits. In this study, we used admixture and genetic relatedness analysis of northern highbush (NHB, V. corymbosum) and southern highbush (SHB, V. darrowii) blueberry genotypes and F2 progenies of the V. corymbosum × V. darrowii cross. Using genotyping-by-sequencing (GBS), we generated ~3.34 billion reads (75 bp). The GBS reads were aligned to the Vaccinium corymbosum cv. Draper v1.0 reference genome sequence, and ~2.8 million reads were successfully mapped. From the alignments, we identified 2,244,039 single nucleotide polymorphisms (SNPs), which were used for principal component, haplotype, and admixture analysis. PCA formed three main groups: 1) NHB cultivars, 2) SHB cultivars, and 3) BNJ16-5 progenies. The overall fixation index (FST) and nucleotide diversity for NHB and SHB, indicated wide genetic differentiation, and haplotype analysis revealed that SHB cultivars are more genetically diverse than NHB cultivars. The admixture analysis identified a mix of various lineages of parental genomic introgression. This study demonstrated the effectiveness of GBS-derived SNP markers in genetic and admixture analyses to reveal genetic relatedness and to examine parental lineages in blueberry, which may be useful for future breeding plans.

Evaluation of phenotypic diversity and geographical variation of cultivated (Eruca sativa L.) and wild (Diplotaxis tenuifolia L.) rocket plant

2011 ◽  
Vol 9 (3) ◽  
pp. 454-463 ◽  
Author(s):  
M. Kadri Bozokalfa ◽  
Dursun Eşiyok ◽  
Hülya İlbi ◽  
Süleyman Kavak ◽  
Tansel Kaygısız Aşçıoğul
Keyword(s):  
Genetic Resources ◽  
Geographical Origin ◽  
Plant Traits ◽  
Phenotypic Diversity ◽  
Plant Genetic Resources ◽  
Principal Component ◽  
Qualitative And Quantitative ◽  
Mediterranean Countries ◽  
Wide Range ◽  
Breeding Programmes

Rocket (Eruca spp. and Diplotaxis spp.) is widely cultivated as a green vegetable in Mediterranean countries, Europe, United States and Brazil, but few rocket cultivars are available and limited variety selection has taken place. Plant genetic resources and germplasm are fundamental sources for plant breeding, and the assessment of the genetic diversity among germplasm accessions is useful to facilitate the more efficient use of plant genetic resources. The objective of this study was to characterize phenotypic diversity and relationships among genotypes of Eruca and Diplotaxis originating from 11 countries across three regions (Europe, Africa and Asia). Principal component analyses explained over 85% of total variation for 51 qualitative and quantitative agromorphological traits. Cluster analyses divided the accessions into five major clusters according to plant traits, siliqua properties and geographical origin of genotype with a few exceptions. These findings indicate a number of useful traits in the gene pool and a wide range of phenotypic variation that provides a good source of diversity for use in modern Eruca breeding programmes.

scholarly journals An Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses

2021 ◽  
Author(s):  
Felipe Bitencourt Martins ◽  
Aline da Costa Lima Moraes ◽  
Alexandre Hild Aono ◽  
Rebecca Caroline Ulbricht Ferreira ◽  
Lucimara Chiari ◽  
...  
Keyword(s):  
Principal Component ◽  
Genotyping By Sequencing ◽  
Snp Markers ◽  
Correct Identification ◽  
Forage Grasses ◽  
Mendelian Segregation ◽  
Breeding Programs ◽  
Tropical Forage ◽  
Genotypic Analysis ◽  
Shiny App

Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones, self-fertilized individuals, half-siblings and full contaminants, in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation and clustering analysis (CA). The combination of these methods allowed the correct identification of all contaminants in all simulated progenies and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid species. The proposed pipeline was made available through the polyCID Shiny app and can be easily coupled with traditional genetic approaches, such as linkage map construction, thereby increasing the efficiency of breeding programs.

scholarly journals Phenotypic Diversity of Clarias gariepinus (Burchell, 1822) from Benue River and a Tributary in North East Nigeria.

2021 ◽  
Vol 2 (1) ◽  
pp. 09-018
Author(s):  
Mamndeyati Ndekimbe Uruku ◽  
Innocent Agbo Adikwu ◽  
Oyediran Olusegun Oyebola ◽  
Timothy E. Uchendu
Keyword(s):  
Phenotypic Diversity ◽  
Phenotypic Variability ◽  
Clarias Gariepinus ◽  
Principal Component ◽  
Mean Value ◽  
Adaptive Traits ◽  
North East ◽  
Fishing Gears ◽  
Coefficient Of Variability ◽  
The Mean

Phenotypic Variability of Sampled Clarias gariepinus (Burchell, 1822) Population were assessed. 30 matured samples of Clarias gariepinus of different sizes were bought from artisanal fisherfolks using various fishing gears, morphometric and meristic attributes and other adaptive traits were characterized. Phenotypic heterogeneity (Coefficient of Variability > 10%) and multiple modes in Meristic and morphometric Values were assessed to imply plasticity and taxonomic complications respectively. Twenty morphometric and nine meristic attributes were measured in all the collected individuals and measured to the nearest 0.01cm, using Vernier calipers. The mean value of meristic attributes varied from 6.20±0.93 in PELFR-R to 71.40±5.64 in DFR. Coefficient of variability of the population varied from 7.89 in DFR to 54.02 in PESES-L. Heterogeneity occurred in 77.8% of meristic attributes except DFR and CFR. Multiple modal was recorded in PESES-L, while the mean value of the morphometric attributes varied from 5.20±0.82 in OPD to 64.52±5.00 in DFL. Coefficient of variability of the population varied from 7.76 in DFL to 18.07 in CFW. Heterogeneity occurred in 82.4% of morphometric attributes. Five components accounted for 78.65% of the total variation using Principal Component Analysis on morphometric attributes. Two of the extracted components had CV > 10 (41.70%, and 15.02%). However, the scree plot shows the slope of the variation to favors the five component with Eigenvalue greater than one. The studied C. gariepinus population was characterized by heterogeneity of phenotypic values and the population can be taxonomically discriminated by meristic and morpho types.

scholarly journals Admixture Analysis Using Genotyping-by-Sequencing Reveals Genetic Relatedness and Parental Lineage Distribution in Highbush Blueberry Genotypes and Cross Derivatives

2020 ◽  
Vol 22 (1) ◽  
pp. 163
Author(s):  
Krishnanand P. Kulkarni ◽  
Nicholi Vorsa ◽  
Purushothaman Natarajan ◽  
Sathya Elavarthi ◽  
Massimo Iorizzo ◽  
...  
Keyword(s):  
Genetic Relatedness ◽  
Principal Component ◽  
Genotyping By Sequencing ◽  
Fixation Index ◽  
Nucleotide Polymorphisms ◽  
Admixture Analysis ◽  
Single Nucleotide ◽  
Cross Derivatives ◽  
Southern Highbush ◽  
Genomic Introgression

Blueberries (Vaccinium section Cyanococcus) are perennial shrubs widely cultivated for their edible fruits. In this study, we performed admixture and genetic relatedness analysis of northern highbush (NHB, primarily V. corymbosum) and southern highbush (SHB, V. corymbosum introgressed with V. darrowii, V. virgatum, or V. tenellum) blueberry genotypes, and progenies of the BNJ16-5 cross (V. corymbosum × V. darrowii). Using genotyping-by-sequencing (GBS), we generated more than 334 million reads (75 bp). The GBS reads were aligned to the V. corymbosum cv. Draper v1.0 reference genome sequence, and ~2.8 million reads were successfully mapped. From the alignments, we identified 2,244,039 single-nucleotide polymorphisms, which were used for principal component, haplotype, and admixture analysis. Principal component analysis revealed three main groups: (1) NHB cultivars, (2) SHB cultivars, and (3) BNJ16-5 progenies. The overall fixation index (FST) and nucleotide diversity for NHB and SHB cultivars indicated wide genetic differentiation, and haplotype analysis revealed that SHB cultivars are more genetically diverse than NHB cultivars. The admixture analysis identified a mixture of various lineages of parental genomic introgression. This study demonstrated the effectiveness of GBS-derived single-nucleotide polymorphism markers in genetic and admixture analyses to reveal genetic relatedness and to examine parental lineages in blueberry, which may be useful for future breeding plans.

scholarly journals Gene body methylation mediates epigenetic inheritance of plant traits

2021 ◽  
Author(s):  
Zaigham Shahzad ◽  
Jonathan D. Moore ◽  
Daniel Zilberman
Keyword(s):  
Gene Expression ◽  
Flowering Time ◽  
Cytosine Methylation ◽  
Plant Traits ◽  
Phenotypic Diversity ◽  
Strong Association ◽  
Epigenetic Inheritance ◽  
Evolutionary Significance ◽  
Gene Body ◽  
Gene Body Methylation

AbstractCytosine methylation is an epigenetically heritable DNA modification common in plant and animal genes, but the functional and evolutionary significance of gene body methylation (gbM) has remained enigmatic. Here we show that gbM enhances gene expression in Arabidopsis thaliana. We also demonstrate that natural gbM variation influences drought and heat tolerance and flowering time by modulating gene expression, including that of Flowering Locus C (FLC). Notably, epigenetic variation accounts for as much trait heritability in natural populations as DNA sequence polymorphism. Furthermore, we identify gbM variation in numerous genes associated with environmental variables, including a strong association between flowering time, spring atmospheric NO2 – a by-product of fossil fuel burning – and FLC epialleles. Our study demonstrates that gbM is an important modulator of gene expression, and its natural variation fundamentally shapes phenotypic diversity in plant populations. Thus, gbM provides an epigenetic basis for adaptive evolution independent of genetic polymorphism.

scholarly journals Selection of consistent plant traits for sunflower growth using principal component analysis

Helia ◽  
2004 ◽  
Vol 27 (41) ◽  
pp. 113-122 ◽  
Author(s):  
Sankar Maruthi ◽  
M. Vanaja ◽  
V. Maruthi ◽  
Raghuram Reddy ◽  
Murthy Narasimha
Keyword(s):  
Principal Component Analysis ◽  
Plant Traits ◽  
Principal Component ◽  
Component Analysis ◽  
Selection Of

scholarly journals Correlations and Multivariate Analysis Across Non- Segregation and Segregation Generations in Two Cotton Crosses

2021 ◽  
Author(s):  
Waleed Yehia ◽  
Essam Fathy El-Hashash
Keyword(s):  
Multivariate Analysis ◽  
Plant Traits ◽  
Natural Fibers ◽  
Principal Component ◽  
Cotton Yield ◽  
Seed Cotton ◽  
Similarity Coefficients ◽  
Seed Cotton Yield ◽  
Textile Manufacture ◽  
Positive Correlations

Abstract Background: The cotton crop is one of the most important natural fibers crops for textile manufacture in the world. The present research uses Pearson’s correlation coefficient and multivariate analysis to assess the interrelationships, similarities and dissimilarities among non- segregation (P1, P2 and F1) and segregation (F2, BC1 and BC2) generations for seed cotton yield and yield components in the two crosses Giza 92 x Pima S6 and Giza 93 x C.B. 58.Results: The analysis of variance exhibited highly significant genetic variability among six generations for all studied traits in the two crosses. The F1 performance was higher than the other generations for all the studied traits in the two crosses. The results had positive and high significant correlations between seed cotton yield/plant, lint cotton yield/plant and No. of bolls/plant traits across all six generations in the two crosses. A number of positive correlations were observed among the six generations for all studied traits in the two crosses. The UPGMA hierarchical clustering showed higher level of similarity coefficients among the six generations and among the studied traits. Similarity coefficients ranged from 0.96 to 0.99 and from 0.65 to 0.96, respectively. In the principal component analysis (PCA), the PCA1 extracted had Eigenvalue >1 across six generations for all studied traits in the two crosses. The PCA displayed total variation of 91.84% among the six generations contributed by PCA1 (79.47%) and PCA2 (12.38%) and had mainly distinguished the generations in different groups. The PCA1 and PCA2 were dominated by F1 and segregation generations in the two crosses, respectively, showing high correlations with the first two PCAs. All studied traits as well as boll weight and lint percentage traits contributed positive significant component loadings for the PCA1 and PCA2, respectively. The biplot analysis of the relationship between the six generations revealed that the most appropriate generations for selecting yield traits were F1 in the two crosses and BC1 and BC2 in the cross Giza 93 x C.B. 58. Conclusion: From the obtained results, we recommend considering backcrossing may be done for 2–5 cycles (BC2 – BC5) at C.B. 58 parent for improving Egyptian cotton yield in the future.

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