Including marker x environment interactions improves genomic prediction in red clover ( L.).

Genomic prediction has mostly been used in single environment contexts, largely ignoring genotype x environment interaction, which greatly affects the performance of plants. However, in the last decade, prediction models including marker x environment (MxE) interaction have been developed. We evaluated the potential of genomic prediction in red clover ( L.

Genome-wide association study for yield-related traits in faba bean ( L.).

Yield is the most complex trait to improve crop production, and identifying the genetic determinants for high yield is a major issue in breeding new varieties. In faba bean ( L.), quantitative trait loci (QTLs) have previously been detected in studies of biparental mapping populations, but the genes controlling the main trait components remain largely unknown.

A genome-wide association study of freezing tolerance in red clover ( L.) germplasm of European origin.

Improvement of persistency is an important breeding goal in red clover ( L.). In areas with cold winters, lack of persistency is often due to poor winter survival, of which low freezing tolerance (FT) is an important component.

Genome-wide association analysis for drought tolerance and associated traits in faba bean ( L.).

Faba bean ( L.) is an important high protein legume adapted to diverse climatic conditions with multiple benefits for the overall sustainability of the cropping systems. Plant-based protein demand is being expanded and faba bean is a good candidate to cover this need.

Phenotypic variation and quantitative trait loci for resistance to southern anthracnose and clover rot in red clover.

High variability for and candidate loci associated with resistance to southern anthracnose and clover rot in a worldwide collection of red clover provide a first basis for genomics-assisted breeding. Red clover (Trifolium pratense L.) is an important forage legume of temperate regions, particularly valued for its high yield potential and its high forage quality.

How to achieve a higher selection plateau in forest tree breeding? Fostering heterozygote × homozygote relationships in optimal contribution selection in the case study of .

In breeding, optimal contribution selection (OCS) is one of the most effective strategies to balance short- and long-term genetic responses, by maximizing genetic gain and minimizing global coancestry. Considering genetic diversity in the selection dynamic-through coancestry-is undoubtedly the reason for the success of OCS, as it avoids preliminary loss of favorable alleles. Originally formulated with the pedigree relationship matrix, global coancestry can nowadays be assessed with one of the possible formulations of the realized genomic relationship matrix.

Favorable Conditions for Genomic Evaluation to Outperform Classical Pedigree Evaluation Highlighted by a Proof-of-Concept Study in Poplar.

Forest trees like poplar are particular in many ways compared to other domesticated species. They have long juvenile phases, ongoing crop-wild gene flow, extensive outcrossing, and slow growth. All these particularities tend to make the conduction of breeding programs and evaluation stages costly both in time and resources.

Sequence imputation from low density single nucleotide polymorphism panel in a black poplar breeding population.

Background: Genomic selection accuracy increases with the use of high SNP (single nucleotide polymorphism) coverage. However, such gains in coverage come at high costs, preventing their prompt operational implementation by breeders. Low density panels imputed to higher densities offer a cheaper alternative during the first stages of genomic resources development.

Development and evaluation of a genome-wide Coffee 8.5K SNP array and its application for high-density genetic mapping and for investigating the origin of Coffea arabica L.

Coffee species such as Coffea canephora P. (Robusta) and C. arabica L.