scholarly journals Genome-wide Identification of Powdery Mildew Resistance in Common Bean

2020 ◽  
Author(s):  
Papias Hongera Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Common Bean ◽  
Resistance Genes ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein

Abstract Background: Genome-wide association studies (GWAS) was utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed. Results: Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for the identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 206 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosomes 4 and 10 (Pv04 and Pv10) were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the chromosome 4 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on Pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on Pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions.Conclusion: Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

scholarly journals Genome-wide Identification of Powdery Mildew Resistance in Common Bean

2020 ◽  
Author(s):  
Papias Hongera Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Common Bean ◽  
Resistance Genes ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein

Abstract Background: Genome-wide association studies (GWAS) have been utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed.Results: Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for the identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 211 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosomes Pv04 and Pv10 were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the Pv04 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on Pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on Pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions.Conclusion: Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

scholarly journals Genome-wide Identification of Powdery Mildew Resistance in Common Bean

2020 ◽  
Author(s):  
Papias Hongera Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Common Bean ◽  
Resistance Genes ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein

Abstract Background Genome-wide association studies (GWAS) was utilized to detect genetic variations related to the powdery mildew (PM) resistance and several agronomic traits in common bean. However, its application in common bean and the PM interactions to identify genes and their location in the common bean genome has not been fully addressed. Results Genome-wide association studies (GWAS) through marker-trait association are useful molecular tools for identification of disease resistance and other agronomic traits. SNP genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to resistance to PM disease in a panel of 206 genotypes grown under field conditions for two consecutive years. Significant SNPs identified on chromosome 4 and 10 were repeatable, confirming the reliability of the phenotypic data scored from the genotypes grown in two locations within two years. A cluster of resistance genes was revealed on the chromosome 4 of common bean genome among which CNL and TNL like resistance genes were identified. Furthermore, two resistance genes Phavu_010G1320001g and Phavu_010G136800g were also identified on pv10; further sequence analysis showed that these genes were homologs to the Arabidopsis disease resistance protein (RLM1A-like) and the putative disease resistance protein (At4g11170.1), respectively. Two LRR receptor-like kinases (RLK) were also identified on pv11 in samples collected in 2018 only. Many genes encoding auxin-responsive protein, TIFY10A protein, growth-regulating factor 5-like, ubiquitin-like protein, cell wall protein RBR3-like protein related to PM resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed and may generate several layers of defense barriers or inducible reactions. Conclusion Our results provide new insights into common bean and PM interactions, and revealed putative resistance genes as well as their location on common bean genome that could be used for marker-assisted selection, functional genomic study approaches to confirm the role of these putative genes; hence, developing common bean resistance lines to the PM disease.

scholarly journals Genome-Wide Identification of Powdery Mildew Resistance in Common Bean (Phaseolus vulgaris L.)

2021 ◽  
Vol 12 ◽  
Author(s):  
Papias H. Binagwa ◽  
Sy M. Traore ◽  
Marceline Egnin ◽  
Gregory C. Bernard ◽  
Inocent Ritte ◽  
...  
Keyword(s):  
Disease Resistance ◽  
Powdery Mildew ◽  
Common Bean ◽  
Resistance Genes ◽  
Significant Snps ◽  
Leucine Rich Repeat ◽  
Genome Wide ◽  
Disease Resistance Protein ◽  
Resistance Protein ◽  
The Common

Genome-wide association studies (GWAS) have been utilized to detect genetic variations related to several agronomic traits and disease resistance in common bean. However, its application in the powdery mildew (PM) disease to identify candidate genes and their location in the common bean genome has not been fully addressed. Single-nucleotide polymorphism (SNP) genotyping with a BeadChip containing 5398 SNPs was used to detect genetic variations related to PM disease resistance in a panel of 211 genotypes grown under two field conditions for two consecutive years. Significant SNPs identified on chromosomes Pv04 and Pv10 were repeatable, ensuring the phenotypic data’s reliability and the causal relationship. A cluster of resistance genes was revealed on the Pv04 of the common bean genome, coiled-coil-nucleotide-binding site–leucine-rich repeat (CC-NBS-LRR, CNL), and Toll/interleukin-1 receptor-nucleotide-binding site–leucine-rich repeat type (TIR-NBS-LRR, TNL)-like resistance genes were identified. Furthermore, two resistance genes, Phavu_010G1320001g and Phavu_010G136800g, were also identified on Pv10. Further sequence analysis showed that these genes were homologs to the disease-resistance protein (RLM1A-like) and the putative disease-resistance protein (At4g11170.1) in Arabidopsis. Significant SNPs related to two LRR receptor-like kinases (RLK) were only identified on Pv11 in 2018. Many genes encoding the auxin-responsive protein, TIFY10A protein, growth-regulating factor five-like, ubiquitin-like protein, and cell wall RBR3-like protein related to PM disease resistance were identified nearby significant SNPs. These results suggested that the resistance to PM pathogen involves a network of many genes constitutively co-expressed.

Genome-wide association study for resistance to cassava root rot

2017 ◽  
Vol 155 (9) ◽  
pp. 1424-1441 ◽  
Author(s):  
A. C. BRITO ◽  
S. A. S. OLIVEIRA ◽  
E. J. OLIVEIRA
Keyword(s):  
Root Rot ◽  
Agronomic Traits ◽  
Association Studies ◽  
Significant Snps ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Soil Pathogens ◽  
Kinship Matrix ◽  
Cassava Root ◽  
Genome Wide

SUMMARYCassava root rot (CRR) disease associated with a complex of soil pathogens has caused great yield losses in the crop. The objective of the current work was to obtain insights about the genetic architecture of CRR resistance caused by Fusarium (dry root rot – DRR), Phytophthora (soft root rot – SRR) and Botryosphaeriaceae (black root rot – BRR) species, using genome-wide association studies (GWAS). Phenotyping data of 263 accessions (artificial inoculation) and 14 094 single-nucleotide polymorphisms (SNP) (missing data <0·10 and minor allele frequency >0·05) were used. The severity of CRR in peel and pulp was variable among accessions, but the pathogens that caused DRR were more aggressive. Broad-sense heritability ($h_g^2 $) was of medium magnitude for all groups of resistances for pathogens, with variation from 0·16 ± 0·019 (Fspp Pulp) to 0·31 ± 0·028 (Fspp Peel). The kinship matrix was used to correct for stratification as well as for clustering the accessions. Overall, this analysis showed that there was no relationship between agronomic traits and resistance to CRR and the four clusters obtained from kinship matrix. The GWAS identified 38 significant SNPs, of which eight and 22 are related to the severity of DRR in the pulp and peel, respectively. The other eight SNPs were associated with SRR-peel (1), SRR-pulp (1), BRR-peel (3) and BRR-pulp (3). Half of the SNPs associated with CRR resistance have functional annotations related to defence and response to pathogen attack as well as general cellular processes. The current study revealed that resistance to CRR is controlled by multiple loci with small effects, and significant SNPs can be used to identify putative genes that control these traits.

Genome-wide association studies of 14 agronomic traits in rice landraces

2010 ◽  
Vol 42 (11) ◽  
pp. 961-967 ◽  
Author(s):  
Xuehui Huang ◽  
Xinghua Wei ◽  
Tao Sang ◽  
Qiang Zhao ◽  
Qi Feng ◽  
...  
Keyword(s):  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Rice Landraces ◽  
Genome Wide

scholarly journals Estimating Effect Sizes and Expected Replication Probabilities from GWAS Summary Statistics

2015 ◽  
Author(s):  
Dominic Holland ◽  
Yunpeng Wang ◽  
Wesley K Thompson ◽  
Andrew Schork ◽  
Chi-Hua Chen ◽  
...  
Keyword(s):  
Association Studies ◽  
Significant Snps ◽  
Effect Sizes ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Sample Sizes ◽  
Genetic Components ◽  
Complex Phenotypes ◽  
Genome Wide ◽  
Z Scores

Genome-wide Association Studies (GWAS) result in millions of summary statistics (``z-scores'') for single nucleotide polymorphism (SNP) associations with phenotypes. These rich datasets afford deep insights into the nature and extent of genetic contributions to complex phenotypes such as psychiatric disorders, which are understood to have substantial genetic components that arise from very large numbers of SNPs. The complexity of the datasets, however, poses a significant challenge to maximizing their utility. This is reflected in a need for better understanding the landscape of z-scores, as such knowledge would enhance causal SNP and gene discovery, help elucidate mechanistic pathways, and inform future study design. Here we present a parsimonious methodology for modeling effect sizes and replication probabilities that does not require raw genotype data, relying only on summary statistics from GWAS substudies, and a scheme allowing for direct empirical validation. We show that modeling z-scores as a mixture of Gaussians is conceptually appropriate, in particular taking into account ubiquitous non-null effects that are likely in the datasets due to weak linkage disequilibrium with causal SNPs. The four-parameter model allows for estimating the degree of polygenicity of the phenotype -- the proportion of SNPs (after uniform pruning, so that large LD blocks are not over-represented) likely to be in strong LD with causal/mechanistically associated SNPs -- and predicting the proportion of chip heritability explainable by genome wide significant SNPs in future studies with larger sample sizes. We apply the model to recent GWAS of schizophrenia (N=82,315) and additionally, for purposes of illustration, putamen volume (N=12,596), with approximately 9.3 million SNP z-scores in both cases. We show that, over a broad range of z-scores and sample sizes, the model accurately predicts expectation estimates of true effect sizes and replication probabilities in multistage GWAS designs. We estimate the degree to which effect sizes are over-estimated when based on linear regression association coefficients. We estimate the polygenicity of schizophrenia to be 0.037 and the putamen to be 0.001, while the respective sample sizes required to approach fully explaining the chip heritability are 106and 105. The model can be extended to incorporate prior knowledge such as pleiotropy and SNP annotation. The current findings suggest that the model is applicable to a broad array of complex phenotypes and will enhance understanding of their genetic architectures.

Genome-wide association studies of Ca and Mn in the seeds of the common bean (Phaseolus vulgaris L.)

Genomics ◽  
2020 ◽  
Vol 112 (6) ◽  
pp. 4536-4546
Author(s):  
Semih Erdogmus ◽  
Duygu Ates ◽  
Seda Nemli ◽  
Bulent Yagmur ◽  
Tansel Kaygisiz Asciogul ◽  
...  
Keyword(s):  
Phaseolus Vulgaris ◽  
Common Bean ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Phaseolus Vulgaris L ◽  
Genome Wide ◽  
The Common

scholarly journals Genome-Wide Association Studies for the Concentration of Albumin in Colostrum and Serum in Chinese Holstein

Animals ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 2211
Author(s):  
Shan Lin ◽  
Zihui Wan ◽  
Junnan Zhang ◽  
Lingna Xu ◽  
Bo Han ◽  
...  
Keyword(s):  
Association Studies ◽  
Significant Snps ◽  
Albumin Concentration ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Chinese Holstein ◽  
Genome Wide ◽  
Chinese Holstein Cows ◽  
Newborn Calves

Albumin can be of particular benefit in fighting infections for newborn calves due to its anti-inflammatory and anti-oxidative stress properties. To identify the candidate genes related to the concentration of albumin in colostrum and serum, we collected the colostrum and blood samples from 572 Chinese Holstein cows within 24 h after calving and measured the concentration of albumin in the colostrum and serum using the ELISA methods. The cows were genotyped with GeneSeek 150 K chips (containing 140,668 single nucleotide polymorphisms; SNPs). After quality control, we performed GWASs via GCTA software with 91,620 SNPs and 563 cows. Consequently, 9 and 7 genome-wide significant SNPs (false discovery rate (FDR) at 1%) were identified. Correspondingly, 42 and 206 functional genes that contained or were approximate to (±1 Mbp) the significant SNPs were acquired. Integrating the biological process of these genes and the reported QTLs for immune and inflammation traits in cattle, 3 and 12 genes were identified as candidates for the concentration of colostrum and serum albumin, respectively; these are RUNX1, CBR1, OTULIN,CDK6, SHARPIN, CYC1, EXOSC4, PARP10, NRBP2, GFUS, PYCR3, EEF1D, GSDMD, PYCR2 and CXCL12. Our findings provide important information for revealing the genetic mechanism behind albumin concentration and for molecular breeding of disease-resistance traits in dairy cattle.

scholarly journals Genome-wide association study of agronomic traits in bread wheat reveals novel putative alleles for future breeding programs

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yousef Rahimi ◽  
Mohammad Reza Bihamta ◽  
Alireza Taleei ◽  
Hadi Alipour ◽  
Pär K. Ingvarsson
Keyword(s):  
Bread Wheat ◽  
Genome Wide Association Study ◽  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Wheat Varieties ◽  
Data Set ◽  
Protein Coding ◽  
Genome Wide

Abstract Background Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. Results GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016–2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (−log10P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. Conclusions Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.

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