scholarly journals Exploiting genetic diversity in two European maize landraces for improving Gibberella ear rot resistance using genomic tools

2020 ◽  
Author(s):  
David Sewordor Gaikpa ◽  
Bettina Kessel ◽  
Thomas Presterl ◽  
Milena Ouzunova ◽  
Ana L. Galiano-Carneiro ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Yield Reduction ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Ear Rot ◽  
Significant Qtls ◽  
Gibberella Ear Rot ◽  
Genomic Tools ◽  
Maize Landraces ◽  
European Maize

Abstract Key message High genetic variation in two European maize landraces can be harnessed to improve Gibberella ear rot resistance by integrated genomic tools. Abstract Fusarium graminearum (Fg) causes Gibberella ear rot (GER) in maize leading to yield reduction and contamination of grains with several mycotoxins. This study aimed to elucidate the molecular basis of GER resistance among 500 doubled haploid lines derived from two European maize landraces, “Kemater Landmais Gelb” (KE) and “Petkuser Ferdinand Rot” (PE). The two landraces were analyzed individually using genome-wide association studies and genomic selection (GS). The lines were genotyped with a 600-k maize array and phenotyped for GER severity, days to silking, plant height, and seed-set in four environments using artificial infection with a highly aggressive Fg isolate. High genotypic variances and broad-sense heritabilities were found for all traits. Genotype-environment interaction was important throughout. The phenotypic (r) and genotypic ($${r}_{g}$$ r g ) correlations between GER severity and three agronomic traits were low (r =  − 0.27 to 0.20; $${r}_{g}\hspace{0.17em}$$ r g =  − 0.32 to 0.22). For GER severity, eight QTLs were detected in KE jointly explaining 34% of the genetic variance. In PE, no significant QTLs for GER severity were detected. No common QTLs were found between GER severity and the three agronomic traits. The mean prediction accuracies ($$\rho $$ ρ ) of weighted GS (wRR-BLUP) were higher than $$\rho $$ ρ of marker-assisted selection (MAS) and unweighted GS (RR-BLUP) for GER severity. Using KE as the training set and PE as the validation set resulted in very low $$\rho $$ ρ that could be improved by using fixed marker effects in the GS model.

scholarly journals Variance Components and Correlations between Doubled Haploid Lines from Two European Flint Landraces and Their Corresponding Testcrosses for Gibberella Ear Rot Resistance, Silking Time, and Plant Height in Maize

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1039
Author(s):  
Félicien Akohoue ◽  
David Sewordor Gaikpa ◽  
Bettina Kessel ◽  
Thomas Presterl ◽  
Thomas Miedaner
Keyword(s):  
Plant Height ◽  
Agronomic Traits ◽  
Genotype By Environment Interaction ◽  
Hybrid Breeding ◽  
Environment Interaction ◽  
Ear Rot ◽  
Gibberella Ear Rot ◽  
Dh Lines ◽  
Selection Stage ◽  
First Time

Predicting the resistance of hybrids from lines is a relevant approach for accelerating the improvement of disease resistance in hybrid breeding. In this study, genetic variation and covariation among 76 DH lines from two flint landraces, Kemater (KE) and Petkuser (PE), and their corresponding testcrosses (TC) were estimated for the first time for this material for Gibberella ear rot (GER), days to silking (DS), and plant height (PHT). Lines and TC were evaluated in four and two environments, respectively, under artificial infection with GER. TC were, on average, 42% less GER infected than their lines. TC matured 3–4 days earlier and were about 110 cm taller than the lines. GER resistance was 10% higher in KE lines and TC than PE lines and TC. Significant (p < 0.001) genotypic and genotype-by-environment interaction variances were found for all traits. Genotypic variances were generally smaller among TC than lines. Broad-sense heritability estimates were moderate to high for GER severity (0.56–0.82) and high for DS (0.78–0.88) and PHT (0.86–0.94) with higher values always observed in lines. Significant, moderate correlations between TC and line per se performance were found for GER resistance in both KE and PE (r = 0.37 and 0.55, respectively). For the two agronomic traits, correlations were higher (r = 0.59–0.76) than for GER resistance. Genomic prediction accuracies were moderate to high for GER resistance (r = 0.49–0.63) and generally higher for DS and PHT. In conclusion, a pre-selection of DH lines for GER resistance should be feasible; however, TC should be additionally tested on a later selection stage to aim for GER-resistant hybrid cultivars.

Colocalization of QTL for Gibberella Ear Rot Resistance and Low Mycotoxin Contamination in Early European Maize

Crop Science ◽  
2011 ◽  
Vol 51 (5) ◽  
pp. 1935-1945 ◽  
Author(s):  
M. Martin ◽  
T. Miedaner ◽  
B. S. Dhillon ◽  
U. Ufermann ◽  
B. Kessel ◽  
...  
Keyword(s):  
Ear Rot ◽  
Gibberella Ear Rot ◽  
Mycotoxin Contamination ◽  
European Maize

Low validation rate of quantitative trait loci for Gibberella ear rot resistance in European maize

2016 ◽  
Vol 130 (1) ◽  
pp. 175-186 ◽  
Author(s):  
Pedro Correa Brauner ◽  
Albrecht E. Melchinger ◽  
Tobias A. Schrag ◽  
H. Friedrich Utz ◽  
Wolfgang Schipprack ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Quantitative Trait ◽  
Ear Rot ◽  
Gibberella Ear Rot ◽  
Validation Rate ◽  
Trait Loci ◽  
European Maize

scholarly journals Climate-Resilient Dairy Cattle Production: Applications of Genomic Tools and Statistical Models

2021 ◽  
Vol 8 ◽  
Author(s):  
Mullakkalparambil Velayudhan Silpa ◽  
Sven König ◽  
Veerasamy Sejian ◽  
Pradeep Kumar Malik ◽  
Mini Ravi Reshma Nair ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Dairy Cows ◽  
Milk Production ◽  
Statistical Models ◽  
Association Studies ◽  
Farm Animals ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Climate Trend ◽  
Genomic Tools

The current changing climate trend poses a threat to the productive efficacy and welfare of livestock across the globe. This review is an attempt to synthesize information pertaining to the applications of various genomic tools and statistical models that are available to identify climate-resilient dairy cows. The different functional and economical traits which govern milk production play a significant role in determining the cost of milk production. Thus, identification of these traits may revolutionize the breeding programs to develop climate-resilient dairy cattle. Moreover, the genotype–environment interaction also influences the performance of dairy cattle especially during a challenging situation. The recent advancement in molecular biology has led to the development of a few biotechnological tools and statistical models like next-generation sequencing (NGS), microarray technology, whole transcriptome analysis, and genome-wide association studies (GWAS) which can be used to quantify the molecular mechanisms which govern the climate resilience capacity of dairy cows. Among these, the most preferred option for researchers around the globe was GWAS as this approach jointly takes into account all the genotype, phenotype, and pedigree information of farm animals. Furthermore, selection signatures can also help to demarcate functionally important regions in the genome which can be used to detect potential loci and candidate genes that have undergone positive selection in complex milk production traits of dairy cattle. These identified biomarkers can be incorporated in the existing breeding policies using genomic selection to develop climate-resilient dairy cattle.

Genotype×environment interaction for wheat yield in different drought stress conditions and agronomic traits suitable for selection

2008 ◽  
Vol 59 (6) ◽  
pp. 536 ◽  
Author(s):  
Dejan Dodig ◽  
Miroslav Zoric ◽  
Desimir Knezevic ◽  
Stephen R. King ◽  
Gordana Surlan-Momirovic
Keyword(s):  
Grain Yield ◽  
Agronomic Traits ◽  
Wheat Yield ◽  
Triticum Aestivum L ◽  
Stress Conditions ◽  
Drought Indices ◽  
Yield Reduction ◽  
Total Biomass ◽  
Environment Interaction ◽  
Predicting Performance

Wheat cultivars grown in south-eastern Europe are exposed to variable rainfed environments. Climate change predictions indicate that the frequency of dry years will likely increase in the future. This study examined relationships among agronomic traits and some drought indices with grain yield as influenced by genotype and environment. In a 4-year experiment, 100 cultivars and landraces of bread wheat (Triticum aestivum L.) from different countries were tested under 3 watering regimes: fully irrigated, rainfed, and in a rain-out plot shelter. Three selection indices, mean productivity (MP), tolerance (TOL), and stress susceptibility index (SSI), were calculated based on grain yield in irrigated and drought-stressed conditions. The additive main effects and multiplicative interaction (AMMI) models were used to study the genotype × environment effects. Average yield reduction due to drought in the sheltered plots was 37.5%. High-yielding genotypes in each treatment showed high values of MP and high rank for SSI and, particularly, TOL. Conversely, low-yielding genotypes in each treatment had low values of MP and high drought tolerance according to SSI and TOL (i.e. low ranks). MP values were noted as being particularly well suited for predicting performance in this experiment. Total biomass and early vigour were found to be the most important agronomic traits for selecting high-yielding genotypes in a range of stress and non-stress conditions.

Variation and covariation for Gibberella ear rot resistance and agronomic traits in testcrosses of doubled haploid maize lines

Euphytica ◽  
2012 ◽  
Vol 185 (3) ◽  
pp. 441-451 ◽  
Author(s):  
Matthias Martin ◽  
Wolfgang Schipprack ◽  
Thomas Miedaner ◽  
Baldev S. Dhillon ◽  
Bettina Kessel ◽  
...  
Keyword(s):  
Doubled Haploid ◽  
Agronomic Traits ◽  
Ear Rot ◽  
Gibberella Ear Rot

Epistatic Effects and QTL×Environment Interaction Effects of QTLs for Yield and Agronomic Traits in Soybean

2014 ◽  
Vol 40 (1) ◽  
pp. 37
Author(s):  
Hui-Zhen LIANG ◽  
Yong-Liang YU ◽  
Hong-Qi YANG ◽  
Hai-Yang ZHANG ◽  
Wei DONG ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Interaction Effects ◽  
Environment Interaction ◽  
Epistatic Effects

scholarly journals Family-based gene-environment interaction using sequence kernel association test (FGE-SKAT) for complex quantitative traits

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Chao-Yu Guo ◽  
Reng-Hong Wang ◽  
Hsin-Chou Yang
Keyword(s):  
Complex Traits ◽  
Association Studies ◽  
Association Test ◽  
Whole Genome Sequence ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Whole Genome ◽  
Sequence Kernel Association Test ◽  
Gene Environment ◽  
Family Based

AbstractAfter the genome-wide association studies (GWAS) era, whole-genome sequencing is highly engaged in identifying the association of complex traits with rare variations. A score-based variance-component test has been proposed to identify common and rare genetic variants associated with complex traits while quickly adjusting for covariates. Such kernel score statistic allows for familial dependencies and adjusts for random confounding effects. However, the etiology of complex traits may involve the effects of genetic and environmental factors and the complex interactions between genes and the environment. Therefore, in this research, a novel method is proposed to detect gene and gene-environment interactions in a complex family-based association study with various correlated structures. We also developed an R function for the Fast Gene-Environment Sequence Kernel Association Test (FGE-SKAT), which is freely available as supplementary material for easy GWAS implementation to unveil such family-based joint effects. Simulation studies confirmed the validity of the new strategy and the superior statistical power. The FGE-SKAT was applied to the whole genome sequence data provided by Genetic Analysis Workshop 18 (GAW18) and discovered concordant and discordant regions compared to the methods without considering gene by environment interactions.

scholarly journals Investigation of gene–environment interactions in relation to tic severity

2021 ◽  
Author(s):  
Mohamed Abdulkadir ◽  
Dongmei Yu ◽  
Lisa Osiecki ◽  
Robert A. King ◽  
Thomas V. Fernandez ◽  
...  
Keyword(s):  
Tourette Syndrome ◽  
Association Studies ◽  
Autism Spectrum ◽  
Environment Interaction ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Linear Regression Models ◽  
Compulsive Disorder ◽  
Gene Environment ◽  
Tic Severity

AbstractTourette syndrome (TS) is a neuropsychiatric disorder with involvement of genetic and environmental factors. We investigated genetic loci previously implicated in Tourette syndrome and associated disorders in interaction with pre- and perinatal adversity in relation to tic severity using a case-only (N = 518) design. We assessed 98 single-nucleotide polymorphisms (SNPs) selected from (I) top SNPs from genome-wide association studies (GWASs) of TS; (II) top SNPs from GWASs of obsessive–compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD); (III) SNPs previously implicated in candidate-gene studies of TS; (IV) SNPs previously implicated in OCD or ASD; and (V) tagging SNPs in neurotransmitter-related candidate genes. Linear regression models were used to examine the main effects of the SNPs on tic severity, and the interaction effect of these SNPs with a cumulative pre- and perinatal adversity score. Replication was sought for SNPs that met the threshold of significance (after correcting for multiple testing) in a replication sample (N = 678). One SNP (rs7123010), previously implicated in a TS meta-analysis, was significantly related to higher tic severity. We found a gene–environment interaction for rs6539267, another top TS GWAS SNP. These findings were not independently replicated. Our study highlights the future potential of TS GWAS top hits in gene–environment studies.

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