Kai P. Voss‐Fels

Genomic and Epigenomic Relationships Capture Different Patterns of Genotype-by-Environment Interaction in Grapevine Clones

This study compares how genomic and epigenomic relationships contribute to genotype-by-environment interaction in grapevine clones, finding that epigenomic factors capture more GEI variance than genomic factors.

High-throughput sequencing of unmethylated DNA (UMR-seq) reveals extensive epigenetic variation in the hypomethylome of diverse plant species

UMR-seq reveals epigenetic variation in plant hypomethylomes, showing UMRs are enriched in regulatory loci and improve genomic prediction and trait association mapping in wheat.

Leveraging synthetic environmental covariates to explore crop genotype by environment interactions

The paper introduces a method to analyze genotype by environment interactions by examining environmental effects across growth stages, finding that early grain fill stages have the greatest impact on yield variance.

Comparison of localGEBV and Optimal Haplotype Stacking Fitness Functions using a Novel R Package: HapSelect

The paper compares localGEBV and OHS fitness functions for parent selection in inbred crops using a novel R package, finding similar long-term genetic gains with dosage-based localGEBV offering simpler workflows.

Leaf and cluster spectral signatures reveal trait-dependent prediction performance for grapevine cluster architecture and juice quality

This study evaluates how hyperspectral reflectance from different grapevine organs predicts cluster architecture and juice quality traits, finding that cluster reflectance outperforms leaf reflectance for most traits.

A dual genomic-epigenomic map of clonal evolution in grapevine

This paper maps clonal genetic and epigenetic variation in grapevine using a phased diploid genome and Oxford Nanopore sequencing, showing that CG methylation patterns accurately reconstruct clonal phylogeny.

Local genomic estimates provide a powerful framework for haplotype discovery

This paper introduces localGEBV, a haplotype-based method that improves QTL discovery and phenotypic prediction compared to traditional GWAS approaches in barley.

Envirotyping Facilitates Understanding of Genotype x Environment Interactions and Highlights the Potential of Stay-green Traits in Wheat

This study uses envirotyping to analyze genotype x environment interactions in wheat, showing stay-green traits improve yield across environments.

Evolutionary computing to assemble standing genetic diversity and achieve long-term genetic gain

This paper compares selection strategies for crop breeding, finding that optimal haplotype selection (OHS) maintains more genetic diversity and achieves higher long-term gains than truncation selection or optimal cross selection.

Genomic mate-allocation strategies exploiting additive and non-additive genetic effects to maximise total clonal performance in sugarcane

The paper compares mate-allocation strategies in sugarcane breeding that use additive and non-additive genetic effects to maximize clonal performance and reduce inbreeding.

genomicSimulation: fast R functions for stochastic simulation of breeding programs

The paper introduces genomicSimulation, a fast R tool for stochastic simulation of breeding programs using real genotypes, showing it accurately reproduces key population features.

Investigations into the emergent properties of gene-to-phenotype networks across cycles of selection: A case study of shoot branching in plants

The paper develops a gene-to-phenotype network for shoot branching in plants to explore how genetic canalization affects selection responses and trait prediction across different contexts.

Physiological and genetic drivers underpinning canopy development are associated with durum wheat yield in rainfed environments

This study identifies QTL associated with canopy closure timing in durum wheat that improve yield in rainfed environments without yield penalties.

Modelling selection response in plant breeding programs using crop models as mechanistic gene-to-phenotype (CGM-G2P) multi-trait link functions

The paper explores using crop models as gene-to-phenotype link functions to optimize selection in plant breeding programs by integrating quantitative genetic theory and trait modeling.