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.

Genome-wide association mapping in maize: status and prospects

3 Biotech ◽  
2021 ◽  
Vol 11 (5) ◽  
Author(s):  
Kumari Shikha ◽  
J. P. Shahi ◽  
M. T. Vinayan ◽  
P. H. Zaidi ◽  
A. K. Singh ◽  
...  
Keyword(s):  
Association Mapping ◽  
Genome Wide Association ◽  
Genome Wide

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.

Genome-wide association mapping of starch granule size distribution in common wheat

2017 ◽  
Vol 77 ◽  
pp. 211-218 ◽  
Author(s):  
Jieyun Li ◽  
Awais Rasheed ◽  
Qi Guo ◽  
Yan Dong ◽  
Jindong Liu ◽  
...  
Keyword(s):  
Association Mapping ◽  
Size Distribution ◽  
Common Wheat ◽  
Starch Granule ◽  
Granule Size ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection

Genomics ◽  
2019 ◽  
Vol 111 (6) ◽  
pp. 1794-1801 ◽  
Author(s):  
Nathanael Fickett ◽  
Andres Gutierrez ◽  
Mohit Verma ◽  
Michael Pontif ◽  
Anna Hale ◽  
...  
Keyword(s):  
Association Mapping ◽  
Yield Components ◽  
Core Collection ◽  
Genome Wide Association ◽  
Cane Yield ◽  
Genome Wide
Sign in / Sign up

Export Citation Format

Share Document