scholarly journals Genetic Dissection of Resistance to Common Rust (Puccinia Sorghi) in Tropical Maize (Zea mays L.) by Combined Genetic Mapping and Genomic Prediction

2020 ◽  
Author(s):  
Xuecai Zhang ◽  
Jiaojiao Ren ◽  
Zhimin Li ◽  
Penghao Wu ◽  
Alexander Loladze ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Linkage Mapping ◽  
Rust Resistance ◽  
Genome Wide Association Study ◽  
Genetic Dissection ◽  
Nucleotide Polymorphisms ◽  
Maize Breeding ◽  
Dh Population ◽  
Association Panel ◽  
Maize Varieties

Abstract Background: Common rust is one of the major foliar diseases of maize, leading to significant grain yield losses and poor grain quality. The most sustainable strategy for controlling common rust is to develop resistant maize varieties, which requires a further understanding of genetic dissection of common rust resistance. Results: In this study, an association panel and two bi-parental doubled haploid (DH) populations were used to perform genome-wide association study (GWAS), linkage mapping, and genomic prediction analyses. All the populations were phenotyped in multi-environment trials for common rust resistance and genotyped with genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs). GWAS revealed six SNPs significantly associated with common rust resistance at bins 1.05, 1.10, 3.04, 3.05, 4.08, and 10.04, respectively. The SNP effect of each SNP ranged from 0.13 to 0.17. Linkage mapping identified six quantitative trait loci (QTL) in the first DH population (DH1) and two QTL in the second DH population (DH2), distributed on chromosomes 1, 2, 3, 4, 6, 7, and 9, respectively. The phenotypic variation explained (PVE) of each QTL ranged from 3.55% to 12.45%. A new major QTL was detected in DH1 on chromosome 7 in the region between 144,585,945 and 149,528,489 bp, it had the highest LOD score of 7.82 and the largest PVE value of 12.45%. The genomic regions located at bins 1.05, 1.10, and 4.08 were detected by both GWAS and linkage mapping. GRMZM2G114893 (bin 1.05) and GRMZM2G138949 (bin 4.08) were identified as the putative candidate genes conferring common rust resistance. The genomic prediction accuracies observed in the association panel and two bi-parental DH populations were 0.61, 0.51, and 0.10, respectively. Conclusions: These results provided new insight into the genetic architecture of common rust resistance in maize and a better understanding of the application of genomic prediction for common rust resistance in maize breeding.

scholarly journals Complex Genetic System Involved in Fusarium Ear Rot Resistance in Maize as Revealed by GWAS, Bulked Sample Analysis, and Genomic Prediction

Plant Disease ◽  
2020 ◽  
Vol 104 (6) ◽  
pp. 1725-1735 ◽  
Author(s):  
Zifeng Guo ◽  
Cheng Zou ◽  
Xiaogang Liu ◽  
Shanhong Wang ◽  
Wen-Xue Li ◽  
...  
Keyword(s):  
Confidence Level ◽  
Genomic Prediction ◽  
Complex Traits ◽  
Genome Wide Association Study ◽  
Fusarium Verticillioides ◽  
Chromosome 1 ◽  
Nucleotide Polymorphisms ◽  
Fusarium Ear Rot ◽  
Ear Rot ◽  
Sample Analysis

Fusarium ear rot (FER) caused by Fusarium verticillioides is one of the most prevalent maize diseases in China and worldwide. Resistance to FER is a complex trait controlled by multiple genes highly affected by environment. In this paper, genome-wide association study (GWAS), bulked sample analysis (BSA), and genomic prediction were performed for understanding FER resistance using 509 diverse inbred lines, which were genotyped by 37,801 high-quality single-nucleotide polymorphisms (SNPs). Ear rot evaluation was performed using artificial inoculation in four environments in China: Xinxiang, Henan, and Shunyi, Beijing, during 2017 and 2018. Significant phenotypic and genetic variation for FER severity was observed, and FER resistance was significantly correlated among the four environments with a generalized heritability of 0.78. GWAS identified 23 SNPs that were associated with FER resistance, 2 of which (1_226233417 on chromosome 1 and 10_14501044 on chromosome 10) were associated at threshold of 2.65 × 10−7 [−log(0.01/37,801)]. Using BSA, resistance quantitative trait loci were identified on chromosomes 3, 4, 7, 9, and 10 at the 90% confidence level and on chromosomes 3 and 10 at the 95% confidence level. A key region, bin 10.03, was detected by both GWAS and BSA. Genomic prediction for FER resistance showed that the prediction accuracy by trait-related markers was higher than that by randomly selected markers under different levels of marker density. Marker-assisted selection using genomic prediction could be an efficient strategy for genetic improvement for complex traits like FER resistance.

scholarly journals Unraveling the Role of Maize Cell Wall Hydroxycinnamates in Digestibility, Biofuel Production and Pest Resistance Using A Multi-Parent Advanced Generation Intercross (MAGIC) Approach. 

2020 ◽  
Author(s):  
Ana López-Malvar ◽  
Rosa Ana Malvar ◽  
Ana Butrón ◽  
Pedro Revilla ◽  
Xose Carlos Souto ◽  
...  
Keyword(s):  
Cell Wall ◽  
Genome Wide Association Study ◽  
Biofuel Production ◽  
Mechanical Resistance ◽  
Nucleotide Polymorphisms ◽  
Corn Borer ◽  
A Genome ◽  
Maize Varieties ◽  
Saccharification Efficiency ◽  
Total Variability

Abstract Background: Mechanical resistance due to higher hydroxycinnamate content makes maize tissues more recalcitrant to damage by insects, less digestible by ruminants, and less suitable for biofuel production. The integrated study of the maize functional genetic variability for each hydroxycinnamate component could be crucial to identify relevant genetic variants that may be incorporated into selection programs to breed maize varieties for multiple uses. A Genome Wide Association study was carried out a in a maize Multiparent-Advanced Intercross (MAGIC) Population to indentify Single Nucleotide Polymorphisms (SNPs) associated with cell wall bound hydroxycinnamates;and we checked thereafter their relationship with SNPs significantly associated with saccharification efficiency, digestibility of organic matter and corn borer damage.Results: We found 24 SNPs, corresponding to15 QTL, significantly associated with cell wall bound hydroxycinnamates. Each SNP explained between 6 and 8% of the total variability. We define new genomic regions and genes involved in polysaccharide synthesis and modifications, and the oxidative coupling associatted to cell wall hydroxycinnamates content. Conclusions: SNPs explained a small proportion of the variability for hydroxycinnamates, saccharification efficiency, digestibility or insect damage, therefore we recommend a genomic selection approach for future breeding programs of these traits. In addition, no colocalizations were found between hydroxycinnamates and final-use-related traits so breeding strategies can be focus on each particular trait with no side effects on the others.

scholarly journals Genetic Dissection of Grain Yield of Maize and Yield-Related Traits Through Association Mapping and Genomic Prediction

2021 ◽  
Vol 12 ◽  
Author(s):  
Juan Ma ◽  
Yanyong Cao
Keyword(s):  
Grain Yield ◽  
Genomic Prediction ◽  
Fixed Effects ◽  
Prediction Accuracy ◽  
Reproducing Kernel ◽  
Genome Wide Association Study ◽  
Kernel Weight ◽  
Primary Objective ◽  
High Yield ◽  
Nucleotide Polymorphisms

High yield is the primary objective of maize breeding. Genomic dissection of grain yield and yield-related traits contribute to understanding the yield formation and improving the yield of maize. In this study, two genome-wide association study (GWAS) methods and genomic prediction were made on an association panel of 309 inbred lines. GWAS analyses revealed 22 significant trait–marker associations for grain yield per plant (GYP) and yield-related traits. Genomic prediction analyses showed that reproducing kernel Hilbert space (RKHS) outperformed the other four models based on GWAS-derived markers for GYP, ear weight, kernel number per ear and row, ear length, and ear diameter, whereas genomic best linear unbiased prediction (GBLUP) showed a slight superiority over other modes in most subsets of the trait-associated marker (TAM) for thousand kernel weight and kernel row number. The prediction accuracy could be improved when significant single-nucleotide polymorphisms were fitted as the fixed effects. Integrating information on population structure into the fixed model did not improve the prediction performance. For GYP, the prediction accuracy of TAMs derived from fixed and random model Circulating Probability Unification (FarmCPU) was comparable to that of the compressed mixed linear model (CMLM). For yield-related traits, CMLM-derived markers provided better accuracies than FarmCPU-derived markers in most scenarios. Compared with all markers, TAMs could effectively improve the prediction accuracies for GYP and yield-related traits. For eight traits, moderate- and high-prediction accuracies were achieved using TAMs. Taken together, genomic prediction incorporating prior information detected by GWAS could be a promising strategy to improve the grain yield of maize.

scholarly journals GWAS and WGCNA uncover hub genes controlling salt tolerance in maize (Zea mays L.) seedlings

2021 ◽  
Author(s):  
Langlang Ma ◽  
Minyan Zhang ◽  
Jie Chen ◽  
Chunyan Qing ◽  
Shijiang He ◽  
...  
Keyword(s):  
Salt Stress ◽  
Salt Tolerance ◽  
Genome Wide Association Study ◽  
Salinity Treatment ◽  
Nucleotide Polymorphisms ◽  
Maize Seedlings ◽  
Salt Tolerant ◽  
Hub Genes ◽  
A Genome ◽  
Maize Varieties

Abstract Salt stress influences maize growth and development. To decode the genetic basis and hub genes controlling salt tolerance is a meaningful exploration for cultivating salt-tolerant maize varieties. Herein, we used an association panel consisting of 305 lines to identify the genetic loci responsible for Na+- and K+-related traits in maize seedlings. Under the salt stress, seven significant single nucleotide polymorphisms were identified using a genome-wide association study, and 120 genes were obtained by scanning the linkage disequilibrium regions of these loci. According to the transcriptome data of the above 120 genes under salinity treatment, we conducted a weighted gene co-expression network analysis. Combined the gene annotations, two SNaC/SKC (shoot Na+ content/shoot K+ content)-associated genes GRMZM2G075104 and GRMZM2G333183 were finally identified as the hub genes involved in salt tolerance. Subsequently, these two genes were verified to affect salt tolerance of maize seedlings by candidate gene association analysis. Haplotypes TTGTCCG-CT and CTT were determined as favorable/salt-tolerance haplotypes for GRMZM2G075104 and GRMZM2G333183, respectively. These findings provide novel insights into genetic architectures underlying maize salt tolerance and contribute to the cultivation of salt-tolerant varieties in maize.

scholarly journals Genomic Prediction of Rust Resistance in Tetraploid Wheat under Field and Controlled Environment Conditions

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1843
Author(s):  
Shiva Azizinia ◽  
Harbans Bariana ◽  
James Kolmer ◽  
Raj Pasam ◽  
Sridhar Bhavani ◽  
...  
Keyword(s):  
Genomic Prediction ◽  
Prediction Accuracy ◽  
Rust Resistance ◽  
Genetic Correlations ◽  
Tetraploid Wheat ◽  
Adult Plant ◽  
Breeding Cycle ◽  
Nucleotide Polymorphisms ◽  
Plant Host ◽  
Individual Gene

Genomic selection can increase the rate of genetic gain in crops through accumulation of positive alleles and reduce phenotyping costs by shortening the breeding cycle time. We performed genomic prediction for resistance to wheat rusts in tetraploid wheat accessions using three cross-validation with the objective of predicting: (1) rust resistance when individuals are not tested in all environments/locations, (2) the performance of lines across years, and (3) adult plant resistance (APR) of lines with bivariate models. The rationale for the latter is that seedling assays are faster and could increase prediction accuracy for APR. Predictions were derived from adult plant and seedling responses for leaf rust (Lr), stem rust (Sr) and stripe rust (Yr) in a panel of 391 accessions grown across multiple years and locations and genotyped using 16,483 single nucleotide polymorphisms. Different Bayesian models and genomic best linear unbiased prediction yielded similar accuracies for all traits. Site and year prediction accuracies for Lr and Yr ranged between 0.56–0.71 for Lr and 0.51–0.56 for Yr. While prediction accuracy for Sr was variable across different sites, accuracies for Yr were similar across different years and sites. The changes in accuracies can reflect higher genotype × environment (G × E) interactions due to climate or pathogenic variation. The use of seedling assays in genomic prediction was underscored by significant positive genetic correlations between all stage resistance (ASR) and APR (Lr: 0.45, Sr: 0.65, Yr: 0.50). Incorporating seedling phenotypes in the bivariate genomic approach increased prediction accuracy for all three rust diseases. Our work suggests that the underlying plant-host response to pathogens in the field and greenhouse screens is genetically correlated, but likely highly polygenic and therefore difficult to detect at the individual gene level. Overall, genomic prediction accuracies were in the range suitable for selection in early generations of the breeding cycle.

scholarly journals Tracing founder haplotypes of Japanese apple varieties: application in genomic prediction and genome-wide association study

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Mai F. Minamikawa ◽  
Miyuki Kunihisa ◽  
Koji Noshita ◽  
Shigeki Moriya ◽  
Kazuyuki Abe ◽  
...  
Keyword(s):  
Association Study ◽  
Genomic Prediction ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Quality Traits ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Fruit Quality Traits ◽  
History Of

AbstractHaplotypes provide useful information for genomics-based approaches, genomic prediction, and genome-wide association study. As a small number of superior founders have contributed largely to the breeding history of fruit trees, the information of founder haplotypes may be relevant for performing the genomics-based approaches in these plants. In this study, we proposed a method to estimate 14 haplotypes from 7 founders and automatically trace the haplotypes forward to apple parental (185 varieties) and breeding (659 F1 individuals from 16 full-sib families) populations based on 11,786 single-nucleotide polymorphisms, by combining multiple algorithms. Overall, 92% of the single-nucleotide polymorphisms information in the parental and breeding populations was characterized by the 14 founder haplotypes. The use of founder haplotype information improved the accuracy of genomic prediction in 7 traits and the resolution of genome-wide association study in 13 out of 27 fruit quality traits analyzed in this study. We also visualized the significant propagation of the founder haplotype with the largest genetic effect in genome-wide association study over the pedigree tree of the parental population. These results suggest that the information of founder haplotypes can be useful for not only genetic improvement of fruit quality traits in apples but also for understanding the selection history of founder haplotypes in the breeding program of Japanese apple varieties.

scholarly journals Comprehensive Genome-Wide Association Analysis Reveals the Genetic Basis of Root System Architecture in Soybean

2020 ◽  
Vol 11 ◽  
Author(s):  
Waldiodio Seck ◽  
Davoud Torkamaneh ◽  
François Belzile
Keyword(s):  
Root System ◽  
System Architecture ◽  
Phenotypic Variation ◽  
Genetic Basis ◽  
Genome Wide Association Study ◽  
Primary Root ◽  
Root System Architecture ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Genome Wide

Increasing the understanding genetic basis of the variability in root system architecture (RSA) is essential to improve resource-use efficiency in agriculture systems and to develop climate-resilient crop cultivars. Roots being underground, their direct observation and detailed characterization are challenging. Here, were characterized twelve RSA-related traits in a panel of 137 early maturing soybean lines (Canadian soybean core collection) using rhizoboxes and two-dimensional imaging. Significant phenotypic variation (P < 0.001) was observed among these lines for different RSA-related traits. This panel was genotyped with 2.18 million genome-wide single-nucleotide polymorphisms (SNPs) using a combination of genotyping-by-sequencing and whole-genome sequencing. A total of 10 quantitative trait locus (QTL) regions were detected for root total length and primary root diameter through a comprehensive genome-wide association study. These QTL regions explained from 15 to 25% of the phenotypic variation and contained two putative candidate genes with homology to genes previously reported to play a role in RSA in other species. These genes can serve to accelerate future efforts aimed to dissect genetic architecture of RSA and breed more resilient varieties.

EXPRESS: Effect of genetic liability to visceral adiposity on stroke and its subtypes: a Mendelian randomization study

2021 ◽  
pp. 174749302110062
Author(s):  
Bin Yan ◽  
Jian Yang ◽  
Li Qian ◽  
Fengjie Gao ◽  
Ling Bai ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Ischemic Stroke ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Visceral Adiposity ◽  
Large Artery ◽  
Nucleotide Polymorphisms ◽  
Genetic Liability ◽  
A Genome ◽  
Increased Risk

Background: Observational studies have found an association between visceral adiposity and stroke. Aims: The purpose of this study was to investigate the role and genetic effect of visceral adipose tissue (VAT) accumulation on stroke and its subtypes. Methods: In this two-sample Mendelian randomization (MR) study, genetic variants (221 single nucleotide polymorphisms; P<5×10-8) using as instrumental variables for MR analysis was obtained from a genome-wide association study (GWAS) of VAT. The outcome datasets for stroke and its subtypes were obtained from the MEGASTROKE consortium (up to 67,162 cases and 453,702 controls). MR standard analysis (inverse variance weighted method) was conducted to investigate the effect of genetic liability to visceral adiposity on stroke and its subtypes. Sensitivity analysis (MR-Egger, weighted median, MR-PRESSO) were also utilized to assess horizontal pleiotropy and remove outliers. Multi-variable MR analysis was employed to adjust potential confounders. Results: In the standard MR analysis, genetically determined visceral adiposity (per 1 SD) was significantly associated with a higher risk of stroke (odds ratio [OR] 1.30; 95% confidence interval [CI] 1.21-1.41, P=1.48×10-11), ischemic stroke (OR 1.30; 95% CI 1.20-1.41, P=4.01×10-10), and large artery stroke (OR 1.49; 95% CI 1.22-1.83, P=1.16×10-4). The significant association was also found in sensitivity analysis and multi-variable MR analysis. Conclusions: Genetic liability to visceral adiposity was significantly associated with an increased risk of stroke, ischemic stroke, and large artery stroke. The effect of genetic susceptibility to visceral adiposity on the stroke warrants further investigation.

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