scholarly journals Pyramiding of scald resistance genes in four spring barley MAGIC populations

2021 ◽  
Author(s):  
Juho Hautsalo ◽  
Fluturë Novakazi ◽  
Marja Jalli ◽  
Magnus Göransson ◽  
Outi Manninen ◽  
...  
Keyword(s):  
Association Studies ◽  
Spring Barley ◽  
Field Trials ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Yield Losses ◽  
Barley Cultivars ◽  
Genome Wide ◽  
Barley Leaf ◽  
Advanced Generation

AbstractGenome-Wide Association Studies (GWAS) of four Multi-parent Advanced Generation Inter-Cross (MAGIC) populations identified nine regions on chromosomes 1H, 3H, 4H, 5H, 6H and 7H associated with resistance against barley scald disease. Three of these regions are putatively novel resistance Quantitative Trait Loci (QTL). Barley scald is caused by Rhynchosporium commune, one of the most important barley leaf diseases that are prevalent in most barley-growing regions. Up to 40% yield losses can occur in susceptible barley cultivars. Four MAGIC populations were generated in a Nordic Public–Private Pre-breeding of spring barley project (PPP Barley) to introduce resistance to several important diseases. Here, these MAGIC populations consisting of six to eight founders each were tested for scald resistance in field trials in Finland and Iceland. Eight different model covariate combinations were compared for GWAS studies, and the models that deviated the least from the expected p-values were selected. For all QTL, candidate genes were identified that are predicted to be involved in pathogen defence. The MAGIC progenies contained new haplotypes of significant SNP-markers with high resistance levels. The lines with successfully pyramided resistance against scald and mildew and the significant markers are now distributed among Nordic plant breeders and will benefit development of disease-resistant cultivars.

scholarly journals You Had Me at “MAGIC”!: Four Barley MAGIC Populations Reveal Novel Resistance QTL for Powdery Mildew

Genes ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1512
Author(s):  
Fluturë Novakazi ◽  
Lene Krusell ◽  
Jens Jensen ◽  
Jihad Orabi ◽  
Ahmed Jahoor ◽  
...  
Keyword(s):  
Powdery Mildew ◽  
Association Studies ◽  
Significant Snps ◽  
Field Trials ◽  
Resistance Quantitative Trait Locus ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Barley Leaf ◽  
Trait Locus ◽  
Exotic Alleles

Blumeria graminis f. sp. hordei (Bgh), the causal agent of barley powdery mildew (PM), is one of the most important barley leaf diseases and is prevalent in most barley growing regions. Infection decreases grain quality and yields on average by 30%. Multi-parent advanced generation inter-cross (MAGIC) populations combine the advantages of bi-parental and association panels and offer the opportunity to incorporate exotic alleles into adapted material. Here, four barley MAGIC populations consisting of six to eight founders were tested for PM resistance in field trials in Denmark. Principle component and STRUCTURE analysis showed the populations were unstructured and genome-wide linkage disequilibrium (LD) decay varied between 14 and 38 Mbp. Genome-wide association studies (GWAS) identified 11 regions associated with PM resistance located on chromosomes 1H, 2H, 3H, 4H, 5H and 7H, of which three regions are putatively novel resistance quantitative trait locus/loci (QTL). For all regions high-confidence candidate genes were identified that are predicted to be involved in pathogen defense. Haplotype analysis of the significant SNPs revealed new allele combinations not present in the founders and associated with high resistance levels.

scholarly journals Genome wide association analyses to understand genetic basis of flowering and plant height under three levels of nitrogen application in Brassica juncea (L.) Czern & Coss

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Javed Akhatar ◽  
Anna Goyal ◽  
Navneet Kaur ◽  
Chhaya Atri ◽  
Meenakshi Mittal ◽  
...  
Keyword(s):  
Plant Height ◽  
Indian Subcontinent ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Strong Interactions ◽  
N Availability ◽  
Oilseed Crop ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractTimely transition to flowering, maturity and plant height are important for agronomic adaptation and productivity of Indian mustard (B. juncea), which is a major edible oilseed crop of low input ecologies in Indian subcontinent. Breeding manipulation for these traits is difficult because of the involvement of multiple interacting genetic and environmental factors. Here, we report a genetic analysis of these traits using a population comprising 92 diverse genotypes of mustard. These genotypes were evaluated under deficient (N75), normal (N100) or excess (N125) conditions of nitrogen (N) application. Lower N availability induced early flowering and maturity in most genotypes, while high N conditions delayed both. A genotyping-by-sequencing approach helped to identify 406,888 SNP markers and undertake genome wide association studies (GWAS). 282 significant marker-trait associations (MTA's) were identified. We detected strong interactions between GWAS loci and nitrogen levels. Though some trait associated SNPs were detected repeatedly across fertility gradients, majority were identified under deficient or normal levels of N applications. Annotation of the genomic region (s) within ± 50 kb of the peak SNPs facilitated prediction of 30 candidate genes belonging to light perception, circadian, floral meristem identity, flowering regulation, gibberellic acid pathways and plant development. These included over one copy each of AGL24, AP1, FVE, FRI, GID1A and GNC. FLC and CO were predicted on chromosomes A02 and B08 respectively. CDF1, CO, FLC, AGL24, GNC and FAF2 appeared to influence the variation for plant height. Our findings may help in improving phenotypic plasticity of mustard across fertility gradients through marker-assisted breeding strategies.

scholarly journals Genome-wide association study reveals candidate genes for flowering time in cowpea (Vigna unguiculata [L.] Walp)

2021 ◽  
Author(s):  
Dev Paudel ◽  
Rocheteau Dareus ◽  
Julia Rosenwald ◽  
Maria Munoz-Amatriain ◽  
Esteban Rios
Keyword(s):  
Flowering Time ◽  
Candidate Genes ◽  
Vigna Unguiculata ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Human Consumption ◽  
Phenotypic Variance ◽  
Genome Wide Association Studies ◽  
Genome Wide

Cowpea (Vigna unguiculata [L.] Walp., diploid, 2n = 22) is a major crop used as a protein source for human consumption as well as a quality feed for livestock. It is drought and heat tolerant and has been bred to develop varieties that are resilient to changing climates. Plant adaptation to new climates and their yield are strongly affected by flowering time. Therefore, understanding the genetic basis of flowering time is critical to advance cowpea breeding. The aim of this study was to perform genome-wide association studies (GWAS) to identify marker trait associations for flowering time in cowpea using single nucleotide polymorphism (SNP) markers. A total of 367 accessions from a cowpea mini-core collection were evaluated in Ft. Collins, CO in 2019 and 2020, and 292 accessions were evaluated in Citra, FL in 2018. These accessions were genotyped using the Cowpea iSelect Consortium Array that contained 51,128 SNPs. GWAS revealed seven reliable SNPs for flowering time that explained 8-12% of the phenotypic variance. Candidate genes including FT, GI, CRY2, LSH3, UGT87A2, LIF2, and HTA9 that are associated with flowering time were identified for the significant SNP markers. Further efforts to validate these loci will help to understand their role in flowering time in cowpea, and it could facilitate the transfer of some of this knowledge to other closely related legume species.

scholarly journals Genome Wide Association Studies for Four Physiological Traits in Groundnut (Arachis hypogaea L.) Minicore Collection

2019 ◽  
Author(s):  
Abdulwahab Saliu Shaibu ◽  
Clay Sneller ◽  
Babu N. Motagi ◽  
Jackline Chepkoech ◽  
Mercy Chepngetich ◽  
...  
Keyword(s):  
Marker Assisted Selection ◽  
Association Studies ◽  
Canopy Temperature ◽  
Snp Markers ◽  
Physiological Traits ◽  
Rapid Decline ◽  
Genome Wide Association Studies ◽  
Area Index ◽  
Trait Association ◽  
Genome Wide

Abstract Background In order to integrate genomics in breeding and development of drought tolerant groundnut genotypes, identification of genomic regions/genetic markers for drought surrogate traits is essential. We used SNP markers for a genetic analysis of the ICRISAT groundnut minicore collection for genome wide marker-trait association for some physiological traits and to determine the magnitude of linkage disequilibrium (LD) present in the genetic resources. Results The LD analysis showed that about 36% of loci pairs were in significant LD (P < 0.05 and r2 > 0.2) and 3.14% of the pairs were in complete LD. There was rapid decline in LD with distance and the LD was <0.2 at a distance of 41635 bp. The marker trait association (MTAs) studies revealed 20 significant MTAs (p <0.001) with 11 markers for leaf area index (4), canopy temperature (13), chlorophyll content (1) and NDVI (2). The markers explained 2 to 21% of the phenotypic variation observed. Most of the MTAs identified on the A subgenome were also identified on the respective homeologous chromosome on the B subgenome. The duplications of effect observed could be due to common ancestor of the A and B genome which explains the linkage detected between markers lying on different chromosomes seen in the current study. Conclusions The present study identified a total of 20 highly significant marker trait associations with 11 markers for four physiological traits of importance in groundnut; LAI, CT, SCMR and NDVI. The markers identified in this study can serve as useful genomic resources to initiate marker-assisted selection and trait introgression of groundnut for drought tolerance. The identified markers in this study may be useful for marker assisted selection after further validation.

scholarly journals Genome-wide association studies for agronomical traits in a world wide spring barley collection

2012 ◽  
Vol 12 (1) ◽  
pp. 16 ◽  
Author(s):  
Raj K Pasam ◽  
Rajiv Sharma ◽  
Marcos Malosetti ◽  
Fred A van Eeuwijk ◽  
Grit Haseneyer ◽  
...  
Keyword(s):  
World Wide ◽  
Association Studies ◽  
Spring Barley ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Agronomical Traits

scholarly journals 301 Methods of genome-wide association studies and their applications in dairy cattle

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 31-31
Author(s):  
Li Ma
Keyword(s):  
Dairy Cattle ◽  
Complex Traits ◽  
Mixed Model ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetics Research ◽  
Genome Wide ◽  
Dairy Cattle Breeding

Abstract Genome-wide association studies (GWAS) has been widely used to map quantitative trait loci (QTL) of complex traits and diseases since 2007. To date, the human GWAS catalog has accumulated 4,410 publications and 172,351 associations, and the animal QTLdb has curated 983 publications and 130,407 QTLs for cattle, largest in livestock species. During the past 13 years of development, GWAS methods has evolved from simple linear regression, using principal components to address sample relatedness, mixed models, to Bayesian full model approaches. These methods have their advantages and limitations, so it is important to choose an appropriate method, especially for studies in livestock where sample size is often limited. Note that the most popular GWAS approach, the mixed model method, originated from animal breeding and genetics research. Leveraging the national cattle genomic database at the Council on Dairy Cattle Breeding (CDCB), we have conducted GWAS analyses of various dairy traits to identify QTLs and SNP markers of importance. Combining with sequence and functional annotation data, we seek to understand the genetic basis of complex traits and to reveal useful knowledge that can be incorporated into more accurate genomic predictions in the future.

scholarly journals Unravelling the complex genetic basis of growth in New Zealand silver trevally (Pseudocaranx georgianus)

2021 ◽  
Author(s):  
Noemie Valenza-Troubat ◽  
Sara Montanari ◽  
Peter Ritchie ◽  
Maren Wellenreuther
Keyword(s):  
Qtl Mapping ◽  
Complex Traits ◽  
Genetic Basis ◽  
Growth Traits ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Powerful Approach ◽  
Trait Locus

AbstractGrowth directly influences production rate and therefore is one of the most important and well-studied trait in animal breeding. However, understanding the genetic basis of growth has been hindered by its typically complex polygenic architecture. Here, we performed quantitative trait locus (QTL) mapping and genome-wide association studies (GWAS) for 10 growth traits that were observed over two years in 1,100 F1 captive-bred trevally (Pseudocaranx georgianus). We constructed the first high-density linkage map for trevally, which included 19,861 single nucleotide polymorphism (SNP) markers, and discovered eight QTLs for height, length and weight on linkage groups 3, 14 and 18. Using GWAS, we further identified 113 SNP-trait associations, uncovering 10 genetic hot spots involved in growth. Two of the markers found in the GWAS co-located with the QTLs previously mentioned, demonstrating that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex traits. This is the first study of its kind for trevally. Our findings provide important insights into the genetic architecture of growth in this species and supply a basis for fine mapping QTLs, marker-assisted selection, and further detailed functional analysis of the genes underlying growth in trevally.

scholarly journals 026.Endometriosis — linkage, positional cloning and genome wide association

2004 ◽  
Vol 16 (9) ◽  
pp. 26
Author(s):  
G. W. Montgomery ◽  
J. Wicks ◽  
Z. Z. Zhao ◽  
D. R. Nyholt ◽  
N. G. Martin ◽  
...  
Keyword(s):  
High Throughput ◽  
Positional Cloning ◽  
Complex Disease ◽  
Association Studies ◽  
Snp Markers ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Experiment ◽  
Priority List ◽  
Genome Wide

Endometriosis is a complex disease which affects up to 10% of women in their reproductive years. Common symptoms include severe dysmenorrhea and pelvic pain. The disease is associated with subfertility and some malignancies. Genetic and environmental factors both influence endometriosis. The aim of our studies is to identify genetic variation contributing to endometriosis and define pathways leading to disease. We recruited a large cohort of affected sister pair (ASP) families where two sisters have had surgically confirmed disease and conducted a 10�cM genome scan. The results of the linkage analysis identified one chromosomal region with significant linkage and one region of suggestive linkage. The regions implicated by these studies are generally of the order of 20–30�cM and include several hundred genes. Locating the gene or genes contributing to disease within the region is a challenging task. The best approach to the problem is association studies using a high density of SNP markers. The recent development of human SNP maps and high throughput SNP genotyping platforms makes this task easier. We have developed high throughput SNP typing at QIMR using the Sequenom MassARRAY platform. The method allows multiple SNP assays to be genotyped on the same sample in a single experiment. Throughput and genotyping costs depend critically on this level of multiplexing and we routinely genotype 6–8 SNPs in a single assay. We are using bioinformatics and functional approaches to develop a priority list of genes to screen early in the project. SNP markers in these genes are being genotyped using the MassARRAY platform to search for genes contributing to endometriosis. In the future, genome wide association studies with our families may locate additional genes contributing to endometriosis.

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

Sign in / Sign up

Export Citation Format

Share Document