scholarly journals Quantitative resistance loci to southern rust mapped in a temperate maize diversity panel

2021 ◽  
Author(s):  
Guangchao Sun ◽  
Ravi V. Mural ◽  
Jonathan D. Turkus ◽  
James C. Schnable
Keyword(s):  
Disease Severity ◽  
Quantitative Resistance ◽  
Association Studies ◽  
Disease Incidence ◽  
Genome Wide Association Studies ◽  
Maize Germplasm ◽  
Photosynthetic Productivity ◽  
Maize Diversity ◽  
Puccinia Polysora ◽  
Candidate Loci

Southern rust is a severe foliar disease of maize (Zea mays) resulting from infection with the obligate biotrophic fungus Puccinia polysora. This disease reduces photosynthetic productivity, which in turn reduces yields, with the greatest yield losses (up to 50%) associated with earlier onset infections. P. polysora urediniospores overwinter only in tropical and subtropical regions but cause outbreaks when environmental conditions favor initial infection. Increased temperatures and humidity during the growing season combined with an increased frequency of moderate winters are likely to increase the frequency of severe southern rust outbreaks in the US corn belt. In summer 2020, a severe outbreak of southern rust was observed in eastern Nebraska (NE), USA. We scored a replicated maize association panel planted in Lincoln, NE for disease severity and found that disease incidence and severity showed significant variation among maize genotypes. Genome-wide association studies identified four loci associated with significant quantitative variation in disease severity. These loci were associated with candidate genes with plausible links to quantitative disease resistance. A transcriptome-wide association study identified additional genes associated with disease severity. Together, these results indicate that substantial diversity in resistance to southern rust exists among current temperate-adapted maize germplasm, including several candidate loci that may explain the observed variation in resistance to southern rust.

scholarly journals Quantitative resistance loci to southern rust mapped in a temperate maize diversity panel

2021 ◽  
Author(s):  
Guangchao Sun ◽  
Ravi V Mural ◽  
Jonathan D. Turkus ◽  
James C Schnable
Keyword(s):  
Disease Severity ◽  
Quantitative Resistance ◽  
Association Studies ◽  
Disease Incidence ◽  
Genome Wide Association Studies ◽  
Maize Germplasm ◽  
Photosynthetic Productivity ◽  
Maize Diversity ◽  
Puccinia Polysora ◽  
Candidate Loci

Southern rust is a severe foliar disease of maize resulting from infection with the obligate biotrophic fungus, Puccinia polysora. The disease reduces photosynthetic productivity which reduces yields with the greatest yield losses (up to 50 %) associated with earlier onset infections. Puccinia polysora urediniospores overwinter only in tropical and subtropical regions but cause outbreaks when environmental conditions favor initial infection. Increased temperatures and humidity during the growing season, combined with an increased frequency of moderate winters are likely to increase the frequency of severe southern rust outbreaks in the US corn belt. In summer 2020, a severe outbreak of Southern Rust was observed in eastern Nebraska (NE), USA. Disease incidence severity showed significant variation among maize genotypes. A replicated maize association panel planted in Lincoln, NE was scored for disease severity. Genome wide association studies identified four loci associated with significant quantitative variation in disease severity which were associated with candidate genes with plausible links to quantitative disease resistance and a transcriptome wide association study conducted identified additional associated genes. Together these results indicate substantial diversity in resistance to southern rust exists among current temperate adapted maize germplasm, including several candidate loci which may explain observed variation in resistance to southern rust.

scholarly journals Genome-wide association mapping reveals race-specific SNP markers associated with anthracnose resistance in carioca common beans

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251745
Author(s):  
Caléo Panhoca de Almeida ◽  
Jean Fausto de Carvalho Paulino ◽  
Caio Cesar Ferrari Barbosa ◽  
Gabriel de Moraes Cunha Gonçalves ◽  
Roberto Fritsche-Neto ◽  
...  
Keyword(s):  
Quantitative Resistance ◽  
Association Studies ◽  
Colletotrichum Lindemuthianum ◽  
Genome Wide Association ◽  
High Yield ◽  
Genome Wide Association Studies ◽  
Anthracnose Resistance ◽  
Resistant Cultivars ◽  
Genome Wide ◽  
Selection Of

Brazil is the largest consumer of dry edible beans (Phaseolus vulgaris L.) in the world, 70% of consumption is of the carioca variety. Although the variety has high yield, it is susceptible to several diseases, among them, anthracnose (ANT) can lead to losses of up to 100% of production. The most effective strategy to overcome ANT, a disease caused by the fungus Colletotrichum lindemuthianum, is the development of resistant cultivars. For that reason, the selection of carioca genotypes resistant to multiple ANT races and the identification of loci/markers associated with genetic resistance are extremely important for the genetic breeding process. Using a carioca diversity panel (CDP) with 125 genotypes and genotyped by BeadChip BARCBean6K_3 and a carioca segregating population AM (AND-277 × IAC-Milênio) genotyped by sequencing (GBS). Multiple interval mapping (MIM) and genome-wide association studies (GWAS) were used as mapping tools for the resistance genes to the major ANT physiological races present in the country. In general, 14 single nucleotide polymorphisms (SNPs) showed high significance for resistance by GWAS, and loci associated with multiple races were also identified, as the Co-3 locus. The SNPs ss715642306 and ss715649427 in linkage disequilibrium (LD) at the beginning of chromosome Pv04 were associated with all the races used, and 16 genes known to be related to plant immunity were identified in this region. Using the resistant cultivars and the markers associated with significant quantitative resistance loci (QRL), discriminant analysis of principal components (DAPC) was performed considering the allelic contribution to resistance. Through the DAPC clustering, cultivar sources with high potential for durable anthracnose resistance were recommended. The MIM confirmed the presence of the Co-14 locus in the AND-277 cultivar which revealed that it was the only one associated with resistance to ANT race 81. Three other loci were associated with race 81 on chromosomes Pv03, Pv10, and Pv11. This is the first study to identify new resistance loci in the AND-277 cultivar. Finally, the same Co-14 locus was also significant for the CDP at the end of Pv01. The new SNPs identified, especially those associated with more than one race, present great potential for use in marker-assisted and early selection of inbred lines.

scholarly journals Coevolutionary Dynamics of Rice Blast Resistance Gene Pi-ta and Magnaporthe oryzae Avirulence Gene AVR-Pita 1

2016 ◽  
Vol 106 (7) ◽  
pp. 676-683 ◽  
Author(s):  
Yulin Jia ◽  
Erxun Zhou ◽  
Seonghee Lee ◽  
Tracy Bianco
Keyword(s):  
Magnaporthe Oryzae ◽  
Marker Assisted Selection ◽  
Defense Mechanism ◽  
Allelic Variation ◽  
Blast Resistance ◽  
Quantitative Resistance ◽  
Association Studies ◽  
The United States ◽  
Avirulence Gene ◽  
Genome Wide Association Studies

The Pi-ta gene in rice is effective in preventing infections by Magnaporthe oryzae strains that contain the corresponding avirulence gene, AVR-Pita1. Diverse haplotypes of AVR-Pita1 have been identified from isolates of M. oryzae from rice production areas in the United States and worldwide. DNA sequencing and mapping studies have revealed that AVR-Pita1 is highly unstable, while expression analysis and quantitative resistance loci mapping of the Pi-ta locus revealed complex evolutionary mechanisms of Pi-ta-mediated resistance. Among these studies, several Pi-ta transcripts were identified, most of which are probably derived from alternative splicing and exon skipping, which could produce functional resistance proteins that support a new concept of coevolution of Pi-ta and AVR-Pita1. User-friendly DNA markers for Pi-ta have been developed to support marker-assisted selection, and development of new rice varieties with the Pi-ta markers. Genome-wide association studies revealed a link between Pi-ta-mediated resistance and yield components suggesting that rice has evolved a complicated defense mechanism against the blast fungus. In this review, we detail the current understanding of Pi-ta allelic variation, its linkage with rice productivity, AVR-Pita allelic variation, and the coevolution of Pi-ta and AVR-Pita in Oryza species and M. oryzae populations, respectively. We also review the genetic and molecular basis of Pi-ta and AVR-Pita interaction, and its value in marker-assisted selection and engineering resistance.

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 RubricOE: a learning framework for genetic epidemiology

2021 ◽  
Author(s):  
Subrata Saha ◽  
Aldo Guzmán-Sáenz ◽  
Aritra Bose ◽  
Filippo Utro ◽  
Daniel E. Platt ◽  
...  
Keyword(s):  
Genetic Epidemiology ◽  
Association Studies ◽  
Disease Incidence ◽  
Data Sets ◽  
Genome Wide Association Studies ◽  
Single Marker Analysis ◽  
Area Of Interest ◽  
Error Bar ◽  
Genetic Features ◽  
Single Marker

AbstractGenetic epidemiology is a growing area of interest in the past years due to the availability of genetic data with the decreasing cost of sequencing. Machine learning (ML) algorithms can be a very useful tool to study the genetic factors on disease incidence or on different traits characterizing a population. There are many challenges that plagues the field of genetic epidemiology including the unbalanced case-control data sets, fallibility of standard genome wide association studies with single marker analysis, heavily underdetermined systems with millions of markers in contrast of a few thousands of samples, to name a few. Ensemble ML methods can be a very useful tool to tackle many of these challenges and thus we propose RubricOE, a pipeline of ML algorithms with error bar computations to obtain interpretable genetic and non-genetic features from genomic or transcriptomic data combined with clinical factors in the form of electronic health records. RubricOE is shown to be robust in simulation studies, detecting true associations with traits of interest in arbitrarily structured multi-ethnic populations.

scholarly journals Assessment of Polygenic Architecture and Risk Prediction based on Common Variants Across Fourteen Cancers

2019 ◽  
Author(s):  
Yan Zhang ◽  
Amber N. Wilcox ◽  
Haoyu Zhang ◽  
Parichoy Pal Choudhury ◽  
Douglas F. Easton ◽  
...  
Keyword(s):  
Association Studies ◽  
Disease Incidence ◽  
Effect Sizes ◽  
European Ancestry ◽  
Risk Scores ◽  
Average Risk ◽  
Genome Wide Association Studies ◽  
Lymphoid Leukemia ◽  
Polygenic Risk ◽  
Wide Range

AbstractWe analyzed summary-level data from genome-wide association studies (GWAS) of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) contributing to risk, as well as the distribution of their associated effect sizes. All cancers evaluated showed polygenicity, involving at a minimum thousands of independent susceptibility variants. For some malignancies, particularly chronic lymphoid leukemia (CLL) and testicular cancer, there are a larger proportion of variants with larger effect sizes than those for other cancers. In contrast, most variants for lung and breast cancers have very small associated effect sizes. For different cancer sites, we estimate a wide range of GWAS sample sizes, required to explain 80% of GWAS heritability, varying from 60,000 cases for CLL to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores, compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that polygenic risk scores have substantial potential for risk stratification for relatively common cancers such as breast, prostate and colon, but limited potential for other cancer sites because of modest heritability and lower disease incidence.

scholarly journals What Is the Heritability of Periodontitis? A Systematic Review

2019 ◽  
Vol 98 (6) ◽  
pp. 632-641 ◽  
Author(s):  
L. Nibali ◽  
J. Bayliss-Chapman ◽  
S.A. Almofareh ◽  
Y. Zhou ◽  
K. Divaris ◽  
...  
Keyword(s):  
Systematic Review ◽  
Disease Severity ◽  
Genetic Factors ◽  
Association Studies ◽  
Severe Disease ◽  
Family Studies ◽  
Google Scholar ◽  
Cochrane Library ◽  
Genome Wide Association Studies ◽  
Hand Search

The aim of this study was to systematically appraise the existing literature on the yet-unclear heritability of gingivitis and periodontitis. This review was conducted following the PRISMA guidelines. A search was conducted through the electronic databases Medline, Embase, LILACS, Cochrane Library, Open Grey, Google Scholar, and Research Gate, as complemented by a hand search, for human studies reporting measures of heritability of gingivitis and periodontitis. A total of 9,037 papers were initially identified from combined databases and 10,810 on Google Scholar. After full-text reading, 28 articles met the inclusion criteria and were carried forward to data abstraction. The reviewed data included information from >50,000 human subjects. Meta-analyses were performed by grouping studies based on design and outcome. Heritability ( H2) of periodontitis was estimated at 0.38 (95% CI, 0.34 to 0.43; I2 = 12.9%) in twin studies, 0.15 (95% CI, 0.06 to 0.24; I2 = 0%) in other family studies, and 0.29 (95% CI, 0.21 to 0.38; I2 = 61.2%) when twin and other family studies were combined. Genome-wide association studies detected a lower heritability estimate of 0.07 (95% CI, −0.02 to 0.15) for combined definitions of periodontitis, increasing with disease severity and when the interaction with smoking was included. Furthermore, heritability tended to be lower among older age groups. Heritability for the self-reported gingivitis trait was estimated at 0.29 (95% CI, 0.22 to 0.36; I2 = 37.6%), while it was not statistically significant for clinically measured gingivitis. This systematic review brings forward summary evidence to confirm that up to a third of the periodontitis variance in the population is due to genetic factors. This seems consistent across the different studied populations and increases with disease severity. In summary, up to a third of the variance of periodontitis in the population is due to genetic factors, with higher heritability for more severe disease.

scholarly journals Genome-Based Characterization of Emergent Invasive Neisseria meningitidis Serogroup Y Isolates in Sweden from 1995 to 2012

2015 ◽  
Vol 53 (7) ◽  
pp. 2154-2162 ◽  
Author(s):  
Bianca Törös ◽  
Sara T. Hedberg ◽  
Magnus Unemo ◽  
Susanne Jacobsson ◽  
Dorothea M. C. Hill ◽  
...  
Keyword(s):  
Neisseria Meningitidis ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Meningococcal Disease ◽  
Association Studies ◽  
Disease Incidence ◽  
The United States ◽  
Geographic Region ◽  
Genome Wide Association Studies ◽  
Whole Genome

Invasive meningococcal disease (IMD) caused byNeisseria meningitidisserogroup Y has increased in Europe, especially in Scandinavia. In Sweden, serogroup Y is now the dominating serogroup, and in 2012, the serogroup Y disease incidence was 0.46/100,000 population. We previously showed that a strain type belonging to sequence type 23 was responsible for the increased prevalence of this serogroup in Sweden. The objective of this study was to investigate the serogroup Y emergence by whole-genome sequencing and compare the meningococcal population structure of Swedish invasive serogroup Y strains to those of other countries with different IMD incidence. Whole-genome sequencing was performed on invasive serogroup Y isolates from 1995 to 2012 in Sweden (n= 186). These isolates were compared to a collection of serogroup Y isolates from England, Wales, and Northern Ireland from 2010 to 2012 (n= 143), which had relatively low serogroup Y incidence, and two isolates obtained in 1999 in the United States, where serogroup Y remains one of the major causes of IMD. The meningococcal population structures were similar in the investigated regions; however, different strain types were prevalent in each geographic region. A number of genes known or hypothesized to have an impact on meningococcal virulence were shown to be associated with different strain types and subtypes. The reasons for the IMD increase are multifactorial and are influenced by increased virulence, host adaptive immunity, and transmission. Future genome-wide association studies are needed to reveal additional genes associated with serogroup Y meningococcal disease, and this work would benefit from a complete serogroup Y meningococcal reference genome.

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.

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