Exploiting genome-wide association in oilseed Brassica speciesThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 853-855
Author(s):  
E. Balázs ◽  
W.A. Cowling
Keyword(s):  
Genetic Improvement ◽  
Genome Wide Association ◽  
Sustainable Farming ◽  
Genome Wide ◽  
Oilseed Brassicas ◽  
Selection Of

scholarly journals Statistical genetic issues for genome-wide association studiesThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 869-875 ◽  
Author(s):  
Bruce S. Weir
Keyword(s):  
Quality Control ◽  
Association Mapping ◽  
Genetic Improvement ◽  
Genome Wide Association ◽  
Plant Association ◽  
Similar Activity ◽  
Genome Wide ◽  
Oilseed Brassicas ◽  
Genotyping Technology ◽  
Selection Of

Genotyping technology now allows the rapid and affordable generation of million-SNP profiles for humans, leading to considerable activity in association mapping. Similar activity is anticipated for many plant species, including Brassica . These plant association mapping activities will require the same care in quality control and quality assurance as for humans. The subsequent analyses may draw upon the same body of theory that is described here in the language of quantitative genetics.

Future tools for association mapping in crop plantsThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 1017-1023 ◽  
Author(s):  
Chris Duran ◽  
Dominic Eales ◽  
Daniel Marshall ◽  
Michael Imelfort ◽  
Jiri Stiller ◽  
...  
Keyword(s):  
Association Mapping ◽  
Genetic Improvement ◽  
Sequence Data ◽  
Nucleotide Polymorphisms ◽  
Snp Discovery ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Oilseed Brassicas ◽  
Paired Read ◽  
Selection Of

Association mapping currently relies on the identification of genetic markers. Several technologies have been adopted for genetic marker analysis, with single nucleotide polymorphisms (SNPs) being the most popular where a reasonable quantity of genome sequence data are available. We describe several tools we have developed for the discovery, annotation, and visualization of molecular markers for association mapping. These include autoSNPdb for SNP discovery from assembled sequence data; TAGdb for the identification of gene specific paired read Illumina GAII data; CMap3D for the comparison of mapped genetic and physical markers; and BAC and Gene Annotator for the online annotation of genes and genomic sequences.

scholarly journals Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Bingru Zhao ◽  
Hanpeng Luo ◽  
Xixia Huang ◽  
Chen Wei ◽  
Jiang Di ◽  
...  
Keyword(s):  
Association Study ◽  
Candidate Genes ◽  
Genetic Improvement ◽  
Genome Wide Association Study ◽  
Growth Traits ◽  
Fibre Diameter ◽  
Single Step ◽  
Genome Wide Association ◽  
Six Traits ◽  
Genome Wide

Abstract Background Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW). Results Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from − 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans. Conclusions Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysisThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 1002-1016 ◽  
Author(s):  
B.R. Cullis ◽  
A.B. Smith ◽  
C.P. Beeck ◽  
W.A. Cowling
Keyword(s):  
Pedigree Information ◽  
Environment Interaction ◽  
Correlation Matrices ◽  
New Approach ◽  
Genome Wide ◽  
Selection Indices ◽  
New Varieties ◽  
Oilseed Brassicas ◽  
Analytic Models ◽  
Selection Of

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.

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 Genome-wide association study and genomic predictions for resistance against Piscirickettsia salmonis in coho salmon (Oncorhynchus kisutch) using ddRAD sequencing

2017 ◽  
Author(s):  
Agustín Barría ◽  
Kris A. Christensen ◽  
Katharina Correa ◽  
Ana Jedlicki ◽  
Jean P. Lhorente ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Genetic Improvement ◽  
Coho Salmon ◽  
Association Studies ◽  
Oncorhynchus Kisutch ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Selection Models ◽  
Genome Wide ◽  
Piscirickettsia Salmonis

ABSTRACTPiscirickettsia salmonis is one of the main infectious diseases affecting coho salmon (Oncorhynchus kisutch) farming. Current treatments have been ineffective for the control of the disease. Genetic improvement for P. salmonis resistance has been proposed as a feasible alternative for the control of this infectious disease in farmed fish. Genotyping by sequencing (GBS) strategies allow genotyping hundreds of individuals with thousands of single nucleotide polymorphisms (SNPs), which can be used to perform genome wide association studies (GWAS) and predict genetic values using genome-wide information. We used double-digest restriction-site associated DNA (ddRAD) sequencing to dissect the genetic architecture of resistance against P. salmonis in a farmed coho salmon population and identify molecular markers associated with the trait. We also evaluated genomic selection (GS) models in order to determine the potential to accelerate the genetic improvement of this trait by means of using genome-wide molecular information. 764 individuals from 33 full-sib families (17 highly resistant and 16 highly susceptible) which were experimentally challenged against P. salmonis were sequenced using ddRAD sequencing. A total of 4,174 SNP markers were identified in the population. These markers were used to perform a GWAS and testing genomic selection models. One SNP related with iron availability was genome-wide significantly associated with resistance to P. salmonis defined as day of death. Genomic selection models showed similar accuracies and predictive abilities than traditional pedigree-based best linear unbiased prediction (PBLUP) method.

scholarly journals Genome-Wide Association Study Identifies Genomic Regions for Important Morpho-Agronomic Traits in Mesoamerican Common Bean

2021 ◽  
Vol 12 ◽  
Author(s):  
Jessica Delfini ◽  
Vânia Moda-Cirino ◽  
José dos Santos Neto ◽  
Douglas Mariani Zeffa ◽  
Alison Fernando Nogueira ◽  
...  
Keyword(s):  
Common Bean ◽  
Quantitative Trait ◽  
Seed Weight ◽  
Genetic Improvement ◽  
Agronomic Traits ◽  
Genome Wide Association ◽  
Multiple Methods ◽  
Favorable Alleles ◽  
Genome Wide ◽  
Multiple Environments

The population growth trend in recent decades has resulted in continuing efforts to guarantee food security in which leguminous plants, such as the common bean (Phaseolus vulgaris L.), play a particularly important role as they are relatively cheap and have high nutritional value. To meet this demand for food, the main target for genetic improvement programs is to increase productivity, which is a complex quantitative trait influenced by many component traits. This research aims to identify Quantitative Trait Nucleotides (QTNs) associated with productivity and its components using multi-locus genome-wide association studies. Ten morpho-agronomic traits [plant height (PH), first pod insertion height (FPIH), number of nodules (NN), pod length (PL), total number of pods per plant (NPP), number of locules per pod (LP), number of seeds per pod (SP), total seed weight per plant (TSW), 100-seed weight (W100), and grain yield (YLD)] were evaluated in four environments for 178 Mesoamerican common bean domesticated accessions belonging to the Brazilian Diversity Panel. In order to identify stable QTNs, only those identified by multiple methods (mrMLM, FASTmrMLM, pLARmEB, and ISIS EM-BLASSO) or in multiple environments were selected. Among the identified QTNs, 64 were detected at least thrice by different methods or in different environments, and 39 showed significant phenotypic differences between their corresponding alleles. The alleles that positively increased the corresponding traits, except PH (for which lower values are desired), were considered favorable alleles. The most influenced trait by the accumulation of favorable alleles was PH, showing a 51.7% reduction, while NN, TSW, YLD, FPIH, and NPP increased between 18 and 34%. Identifying QTNs in several environments (four environments and overall adjusted mean) and by multiple methods reinforces the reliability of the associations obtained and the importance of conducting these studies in multiple environments. Using these QTNs through molecular techniques for genetic improvement, such as marker-assisted selection or genomic selection, can be a strategy to increase common bean production.

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