Bayesian Networks Illustrate Genomic and Residual Trait Connections in Maize (Zea mays L.)
Relationships among traits were investigated on the genomic and residual levels using
novel methodology. This included inference on these relationships via Bayesian networks …
novel methodology. This included inference on these relationships via Bayesian networks …
Multiple quantitative trait analysis using Bayesian networks
Abstract Models for genome-wide prediction and association studies usually target a single
phenotypic trait. However, in animal and plant genetics it is common to record information on …
phenotypic trait. However, in animal and plant genetics it is common to record information on …
Epistasis and covariance: how gene interaction translates into genomic relationship
Key message Models based on additive marker effects and on epistatic interactions can be
translated into genomic relationship models. This equivalence allows to perform predictions …
translated into genomic relationship models. This equivalence allows to perform predictions …
Genome-Wide Association Studies with a Genomic Relationship Matrix: A Case Study with Wheat and Arabidopsis
Standard genome-wide association studies (GWAS) scan for relationships between each of
p molecular markers and a continuously distributed target trait. Typically, a marker-based …
p molecular markers and a continuously distributed target trait. Typically, a marker-based …
Modeling multiple phenotypes in wheat using data‐driven genomic exploratory factor analysis and Bayesian network learning
Inferring trait networks from a large volume of genetically correlated diverse phenotypes
such as yield, architecture, and disease resistance can provide information on the manner in …
such as yield, architecture, and disease resistance can provide information on the manner in …
The Use of Targeted Marker Subsets to Account for Population Structure and Relatedness in Genome-Wide Association Studies of Maize (Zea mays L.)
A typical plant genome-wide association study (GWAS) uses a mixed linear model (MLM)
that includes a trait as the response variable, a marker as an explanatory variable, and fixed …
that includes a trait as the response variable, a marker as an explanatory variable, and fixed …
Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study
The present study evaluated the importance of auxiliary traits of a principal trait based on
phenotypic information and previously known genetic structure using computational …
phenotypic information and previously known genetic structure using computational …
Improving genomic prediction for seed quality traits in oat (Avena sativa L.) using trait-specific relationship matrices
The observable phenotype is the manifestation of information that is passed along different
organization levels (transcriptional, translational, and metabolic) of a biological system. The …
organization levels (transcriptional, translational, and metabolic) of a biological system. The …
Enhancing genomic prediction with genome-wide association studies in multiparental maize populations
Y Bian, JB Holland - Heredity, 2017 - nature.com
Genome-wide association mapping using dense marker sets has identified some nucleotide
variants affecting complex traits that have been validated with fine-mapping and functional …
variants affecting complex traits that have been validated with fine-mapping and functional …
Utilizing trait networks and structural equation models as tools to interpret multi-trait genome-wide association studies
Background Plant breeders seek to develop cultivars with maximal agronomic value, which
is often assessed using numerous, often genetically correlated traits. As intervention on one …
is often assessed using numerous, often genetically correlated traits. As intervention on one …