Multi-omics prediction of oat agronomic and seed nutritional traits across environments and in distantly related populations

Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.)

(2021) Malachy T Campbell et al.   GENETICS

Improving Genomic Prediction for Seed Quality Traits in Oat (Avena sativa L.) Using Trait-Specific Relationship Matrices

(2021) Malachy T. Campbell et al.   Frontiers in Genetics

Incorporation of parental phenotypic data into multi‐omic models improves prediction of yield related traits in hybrid rice

(2020) Yang Xu et al.   PLANT BIOTECHNOLOGY JOURNAL

Multi-omics-data-assisted genomic feature markers preselection improves the accuracy of genomic prediction

(2020) Shaopan Ye et al.   Journal of Animal Science and Biotechnology

Identification of optimal prediction models using multi-omic data for selecting hybrid rice

(2019) Shibo Wang et al.   HEREDITY

Trans Effects on Gene Expression Can Drive Omnigenic Inheritance

(2019) Xuanyao Liu et al.   CELL

Multivariate Genome-Wide Association Analyses Reveal the Genetic Basis of Seed Fatty Acid Composition in Oat (Avena sativa L.)

(2019) Maryn O. Carlson et al.   G3-Genes Genomes Genetics

Pitfalls and Remedies for Cross Validation with Multi-trait Genomic Prediction Methods

(2019) Daniel Runcie et al.   G3-Genes Genomes Genetics

Heritable temporal gene expression patterns correlate with metabolomic seed content in developing hexaploid oat seed

(2019) Haixiao Hu et al.   PLANT BIOTECHNOLOGY JOURNAL

Beyond Genomic Prediction: Combining Different Types ofomicsData Can Improve Prediction of Hybrid Performance in Maize

(2018) Tobias A. Schrag et al.   GENETICS

Haplotype-based genotyping-by-sequencing in oat genome research

(2018) Wubishet A. Bekele et al.   PLANT BIOTECHNOLOGY JOURNAL

Metabolomics 20 years on: what have we learned and what hurdles remain?

(2018) Saleh Alseekh et al.   PLANT JOURNAL

Unraveling lipid metabolism in maize with time-resolved multi-omics data

(2018) Francisco de Abreu e Lima et al.   PLANT JOURNAL

Combining population genomics and fitness QTLs to identify the genetics of local adaptation inArabidopsis thaliana

(2018) Nicholas Price et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Beyond Genomic Prediction: Combining Different Types ofomicsData Can Improve Prediction of Hybrid Performance in Maize

(2018) Tobias A. Schrag et al.   GENETICS

Genomic Prediction of Breeding Values Using a Subset of SNPs Identified by Three Machine Learning Methods

(2018) Bo Li et al.   Frontiers in Genetics

QuantSeq 3′ mRNA sequencing for RNA quantification

(2018) Pamela Moll et al.   NATURE METHODS

Impact of residual covariance structures on genomic prediction ability in multi-environment trials

(2018) Boby Mathew et al.   PLoS One

Prediction and association mapping of agronomic traits in maize using multiple omic data

(2017) Y Xu et al.   HEREDITY

Omics-based hybrid prediction in maize

(2017) Matthias Westhues et al.   THEORETICAL AND APPLIED GENETICS

Exploiting biological priors and sequence variants enhances QTL discovery and genomic prediction of complex traits

(2016) I. M. MacLeod et al.   BMC GENOMICS

Predicting Responses in Multiple Environments: Issues in Relation to Genotype × Environment Interactions

(2016) Marcos Malosetti et al.   CROP SCIENCE

Evaluation of the utility of gene expression and metabolic information for genomic prediction in maize

(2016) Zhigang Guo et al.   THEORETICAL AND APPLIED GENETICS

A Genomic Bayesian Multi-trait and Multi-environment Model

(2016) Osval A. Montesinos-López et al.   G3-Genes Genomes Genetics

Genome-Assisted Prediction of Quantitative Traits Using the R Package sommer

(2016) Giovanny Covarrubias-Pazaran   PLoS One

Evaluating Imputation Algorithms for Low-Depth Genotyping-By-Sequencing (GBS) Data

(2016) Ariel W. Chan et al.   PLoS One

Adding Genetically Distant Individuals to Training Populations Reduces Genomic Prediction Accuracy in Barley

(2015) Aaron J. Lorenz et al.   CROP SCIENCE

Genome-based establishment of a high-yielding heterotic pattern for hybrid wheat breeding

(2015) Yusheng Zhao et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Genome-Wide Regression and Prediction with the BGLR Statistical Package

(2014) P. Perez et al.   GENETICS

Estimation of linkage disequilibrium and interspecific gene flow inFicedulaflycatchers by a newly developed 50k single-nucleotide polymorphism array

(2014) Takeshi Kawakami et al.   Molecular Ecology Resources

Genomic Prediction of Breeding Values when Modeling Genotype × Environment Interaction using Pedigree and Dense Molecular Markers

(2012) Juan Burgueño et al.   CROP SCIENCE

Genomic and metabolic prediction of complex heterotic traits in hybrid maize

(2012) Christian Riedelsheimer et al.   NATURE GENETICS

Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP

(2011) Jeffrey B. Endelman   Plant Genome

WGCNA: an R package for weighted correlation network analysis

(2008) Peter Langfelder et al.   BMC BIOINFORMATICS