scholarly journals Field Screen and Genotyping of Phaseolus vulgaris against Two Begomoviruses in Georgia, USA

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 49
Author(s):  
Gaurav Agarwal ◽  
Saritha Raman Kavalappara ◽  
Saurabh Gautam ◽  
Andre da Silva ◽  
Alvin Simmons ◽  
...  
Keyword(s):  
Disease Severity ◽  
Association Studies ◽  
Lima Bean ◽  
Phaseolus Lunatus ◽  
Genome Wide Association Studies ◽  
Snap Bean ◽  
Copy Numbers ◽  
Genome Wide ◽  
Greenhouse Evaluation ◽  
Virus Complex

The production and quality of Phaseolusvulgaris (snap bean) have been negatively impacted by leaf crumple disease caused by two whitefly-transmitted begomoviruses: cucurbit leaf crumple virus (CuLCrV) and sida golden mosaic Florida virus (SiGMFV), which often appear as a mixed infection in Georgia. Host resistance is the most economical management strategy against whitefly-transmitted viruses. Currently, information is not available with respect to resistance to these two viruses in commercial cultivars. In two field seasons (2018 and 2019), we screened Phaseolus spp. genotypes (n = 84 in 2018; n = 80 in 2019; most of the genotypes were common in both years with a few exceptions) for resistance against CuLCrV and/or SiGMFV. We also included two commonly grown Lima bean (Phaseolus lunatus) varieties in our field screening. Twenty Phaseolus spp. genotypes with high to moderate-levels of resistance (disease severity ranging from 5%–50%) to CuLCrV and/or SiGMFV were identified. Twenty-one Phaseolus spp. genotypes were found to be highly susceptible with a disease severity of ≥66%. Furthermore, based on the greenhouse evaluation with two genotypes-each (two susceptible and two resistant; identified in field screen) exposed to viruliferous whiteflies infected with CuLCrV and SiGMFV, we observed that the susceptible genotypes accumulated higher copy numbers of both viruses and displayed severe crumple severity compared to the resistant genotypes, indicating that resistance might potentially be against the virus complex rather than against the whiteflies. Adult whitefly counts differed significantly among Phaseolus genotypes in both years. The whole genome of these Phaseolus spp. [snap bean (n = 82); Lima bean (n = 2)] genotypes was sequenced and genetic variability among them was identified. Over 900 giga-base (Gb) of filtered data were generated and >88% of the resulting data were mapped to the reference genome, and SNP and Indel variants in Phaseolus spp. genotypes were obtained. A total of 645,729 SNPs and 68,713 Indels, including 30,169 insertions and 38,543 deletions, were identified, which were distributed in 11 chromosomes with chromosome 02 harboring the maximum number of variants. This phenotypic and genotypic information will be helpful in genome-wide association studies that will aid in identifying the genetic basis of resistance to these begomoviruses in Phaseolus spp.

scholarly journals Whole-genome sequencing and phenotyping revealed structural variants and varied level of resistance against leaf crumple disease in diverse lines of snap bean (Phaseolus vulgaris)

2020 ◽  
Author(s):  
Gaurav Agarwal ◽  
Saritha Raman Kavalappara ◽  
Saurabh Gautam ◽  
Andre Luiz Biscaia Ribeiro da Silva ◽  
Alvin M. Simmons ◽  
...  
Keyword(s):  
Phaseolus Vulgaris ◽  
Disease Severity ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Snap Bean ◽  
Genome Wide ◽  
Cucurbit Leaf Crumple Virus ◽  
Varied Level

The production and quality of Phaseolus vulgaris (snap bean) have been negatively impacted by leaf crumple disease caused by two whitefly-transmitted begomoviruses; cucurbit leaf crumple virus (CuLCrV) and sida golden mosaic Florida virus (SiGMFV), which often appear as a mixed infection in Georgia. Host resistance is the most economical management strategy against whitefly-transmitted viruses. Currently, information is not available with respect to resistance to these two viruses in commercial cultivars. In two field seasons (2018 and 2019), we screened Phaseolus sp. genotypes (n = 84 in 2018; n = 80 in 2019; most of the genotypes were common in both years with a few exceptions) for resistance against CuLCrV and/or SiGMFV. Twenty genotypes with high- to moderate-levels of resistance (disease severity ranging from 5-50%) to CuLCrV and/or SiGMFV were identified. Twenty-one genotypes were found to be highly susceptible with a disease severity of ≥66%. Adult whitefly counts differed significantly among snap bean genotypes for both years. The whole genome of these Phaseolus sp. (n=82) genotypes was sequenced and genetic variability among them was identified. Over 900 giga-base (Gb) of filtered data were generated and >88% of the resulting data were mapped to the reference genome, and SNP and Indel variants in Phaseolus genotypes were obtained. A total of 645,729 SNPs and 68,713 Indels including 30,169 insertions and 38,543 deletions were identified, which were distributed in 11 chromosomes with chromosome 02 harboring the maximum number of variants. These phenotypic and genotypic information will be helpful in genome-wide association studies that will aid in identifying genetic basis of resistance to these begomoviruses in Phaseolus sp.

scholarly journals Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

2019 ◽  
Author(s):  
Amber C. A. Hendriks ◽  
Frans A.G. Reubsaet ◽  
A.M.D. (Mirjam) Kooistra ◽  
John W. A. Rossen ◽  
Bas E. Dutilh ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Disease Severity ◽  
Genetic Variants ◽  
Association Studies ◽  
Control Measures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Severity Scores ◽  
Shigella Spp

Abstract Background We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the used methods, the genetic differences between the genera Shigella and Escherichia were used as control. Results The obtained isolates were representative for a population structure as encountered in a Western European country. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. One potentially associated intergenic region was found using a k-mer approach, however, this turned out to be a false positive. Our benchmark characteristic, genus, resulted in eight associated genes and >3,000,000 k-mers, indicating adequate performance of the used algorithms. Conclusions To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

scholarly journals Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

2019 ◽  
Author(s):  
Amber C. A. Hendriks ◽  
Frans A.G. Reubsaet ◽  
A.M.D. (Mirjam) Kooistra ◽  
John W. A. Rossen ◽  
Bas E. Dutilh ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Disease Severity ◽  
Genetic Variants ◽  
Association Studies ◽  
Control Measures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Severity Scores ◽  
Shigella Spp

Abstract Background We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the used methods, the genetic differences between the genera Shigella and Escherichia were used as control. Results The obtained isolates were representative for a population structure as encountered in a Western European country. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. One potentially associated intergenic region was found using a k-mer approach, however, this turned out to be a false positive. Our benchmark characteristic, genus, resulted in eight associated genes and >3,000,000 k-mers, indicating adequate performance of the used algorithms. Conclusions To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

scholarly journals ALLELES ASSOCIATED TO DISEASE SEVERITY INDEX OF MAL DE RÍO CUARTO DISEASE IN MAIZE EXOTIC GERMPLASM

2020 ◽  
Vol 31 (Issue 2) ◽  
pp. 45-53
Author(s):  
E.A. Rossi ◽  
M. Ruiz ◽  
N.C. Bonamico ◽  
M.G. Balzarini
Keyword(s):  
Disease Severity ◽  
Genome Wide Association Study ◽  
Association Studies ◽  
Severity Index ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Exotic Germplasm ◽  
Disease Severity Index ◽  
Genome Wide

Mal de Río Cuarto (MRC) is one of the most important viral diseases of maize in Argentina. The disease severity index (DSI) allows to combine the incidence and severity of a disease in a single metric. The genotypic reaction to MRC has been extensively studied in biparental populations. However, this complex trait has not been analyzed by genome-wide association studies (GWAS). The aim of this work is to identify new resistance alleles associated with DSI of MRC in an exotic germplasm from the International Maize and Wheat Improvement Center (CIMMYT). A population of maize lines from CIMMYT was phenotypically evaluated in environments in the area where the disease is endemic. The predictors of genetic effects (BLUP, best linear unbiased predictor) and 78,376 SNP markers (Single Nucleotide Polymorphism) were used to perform the GWAS in 186 maize lines. The values of variance components and mean-basis heritability suggest a wide genotypic variability in the population. The GWAS allowed to identify 11 putative QTL of resistance to MRC. The incorporation of exotic germplasm into local maize breeding programs could contribute favorably to the creation of hybrids with a higher level of resistance to MRC. The predictive ability of associated markers with MRC resistance indicates that marker-assisted selection is an advisable tool for selecting MRC resistant genotypes. Key words: Disease severity index; genome-wide association study; QTL; SNP

scholarly journals Improving the Health Benefits of Snap Bean: Genome-Wide Association Studies of Total Phenolic Content

Nutrients ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2509 ◽  
Author(s):  
James R. Myers ◽  
Lyle T. Wallace ◽  
Samira Mafi Moghaddam ◽  
Adrienne E. Kleintop ◽  
Dimas Echeverria ◽  
...  
Keyword(s):  
Total Phenolic Content ◽  
Phenolic Content ◽  
Association Studies ◽  
Health Benefits ◽  
Genome Wide Association ◽  
Total Phenolic ◽  
Genome Wide Association Studies ◽  
Snap Bean ◽  
Snap Beans ◽  
Genome Wide

Snap beans are a significant source of micronutrients in the human diet. Among the micronutrients present in snap beans are phenolic compounds with known beneficial effects on human health, potentially via their metabolism by the gut-associated microbiome. The genetic pathways leading to the production of phenolics in snap bean pods remain uncertain. In this study, we quantified the level of total phenolic content (TPC) in the Bean Coordinated Agriculture Program (CAP) snap bean diversity panel of 149 accessions. The panel was characterized spectrophotometrically for phenolic content with a Folin–Ciocalteu colorimetric assay. Flower, seed and pod color were also quantified, as red, purple, yellow and brown colors are associated with anthocyanins and flavonols in common bean. Genotyping was performed through an Illumina Infinium Genechip BARCBEAN6K_3 single nucleotide polymorphism (SNP) array. Genome-Wide Association Studies (GWAS) analysis identified 11 quantitative trait nucleotides (QTN) associated with TPC. An SNP was identified for TPC on Pv07 located near the P gene, which is a major switch in the flavonoid biosynthetic pathway. Candidate genes were identified for seven of the 11 TPC QTN. Five regulatory genes were identified and represent novel sources of variation for exploitation in developing snap beans with higher phenolic levels for greater health benefits to the consumer.

scholarly journals Genome-wide association studies of Shigella spp. and Enteroinvasive Escherichia coli isolates demonstrate an absence of genetic markers for prediction of disease severity

2020 ◽  
Author(s):  
Amber C. A. Hendriks ◽  
Frans A.G. Reubsaet ◽  
A.M.D. (Mirjam) Kooistra ◽  
John W. A. Rossen ◽  
Bas E. Dutilh ◽  
...  
Keyword(s):  
Escherichia Coli ◽  
Disease Severity ◽  
Genetic Variants ◽  
Association Studies ◽  
Control Measures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Severity Scores ◽  
Shigella Spp

Abstract Background: We investigated the association of symptoms and disease severity of shigellosis patients with genetic determinants of infecting Shigella and entero-invasive Escherichia coli (EIEC), because determinants that predict disease outcome per individual patient could be used to prioritize control measures. For this purpose, genome wide association studies (GWAS) were performed using presence or absence of single genes, combinations of genes, and k-mers. All genetic variants were derived from draft genome sequences of isolates from a multicenter cross-sectional study conducted in the Netherlands during 2016 and 2017. Clinical data of patients consisting of binary/dichotomous representation of symptoms and their calculated severity scores were also available from this study. To verify the suitability of the methods used, the genetic differences between the genera Shigella and Escherichia were used as control. Results: The isolates obtained were representative of the population structure encountered in other Western European countries. No association was found between single genes or combinations of genes and separate symptoms or disease severity scores. Our benchmark characteristic, genus, resulted in eight associated genes and >3,000,000 k-mers, indicating adequate performance of the algorithms used. Conclusions: To conclude, using several microbial GWAS methods, genetic variants in Shigella spp. and EIEC that can predict specific symptoms or a more severe course of disease were not identified, suggesting that disease severity of shigellosis is dependent on other factors than the genetic variation of the infecting bacteria. Specific genes or gene fragments of isolates from patients are unsuitable to predict outcomes and cannot be used for development, prioritization and optimization of guidelines for control measures of shigellosis or infections with EIEC.

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