The group focuses on research aimed at understanding the interaction between genotype, environment and management by using all kinds of different techniques and databases. Therefore database development, maintenance and use is an important area of attention. Furthermore statistical aspects of using large datasets especially in the field of transcriptomics and metabolomics is a major focus area.
Crops: potato, brassica, tomato and other crops of importance.
- Construction of linkage maps and QTL analysis
- Linkage Disequillibrium mapping and association mapping
- Epistatis mapping
- Genetical genomics
- Genomic prediction and selection
- Estimation of Genotype x Environment interaction
- Relating henotype data to microarray, metabolomics or proteomics data
- Methods and software for genetic analysis in polyploid species
Plant breeding has a strong link with quantitative genetics, statistics and bioinformatics, for example in identifying regions on crop genomes that are associated with observed variation in phenotypic traits, and in identifying candidate genes for these genomic regions.
Research within Plant breeding is multi-disciplinary and is dealing with a lot of different types of data, obtained from field-trials but also from high-throughput analysis of molecular markers, RNA transcripts (microarrays), proteins and secondary metabolites.
An efficient database will help in elucidating the genetics of economically important traits, in identifying molecular markers associated with agronomic traits, in allele mining and choosing interesting accessions fur further breeding with improved traits important for consumers, processors and producers.
One goal within plant breeding is to find the causal gene(s) explaining a given phenotype. Semantic web technology brings opportunities to integration data and information across spread data sources. For example, Annotex and Marker2sequence are two applications developed by Plant Breeding, which rely on this semantic web technology to integration genes, proteins, metabolites, pathways, and literature.
Contact: Richard Finkers
Current activities include combined data analysis of molecular markers, gene expression and metabolomics data and phenotype (e.g. disease resistance or product quality) scored on segregating populations of crosses. Methods being used are procedures such as random forest for classification or multiple regression in cases where the number of predictor variables (e.g. molecular markers, genes, metabolites) is much larger than the number of samples in which they have been measured (plants, tissues). Other areas of interest are modelling genotype x environment interaction, mapping and QTL analysis in single segregating populations, multiple populations or collections of germplasm. A specific focus area is also the development of a genetic analysis pipeline for polyploid crops.
Contact: Chris Maliepaard
Resistentie tegen bladluizen in paprika
Aphid populations showing differential levels of virulence on Capsicum accessions
Insect Science (2018). - ISSN 1672-9609
QTL mapping of insect resistance components of Solanum galapagense
Theoretical and Applied Genetics (2018). - ISSN 0040-5752 - 11 p.
Combining QTL mapping with transcriptome and metabolome profiling reveals a possible role for ABA signaling in resistance against the cabbage whitefly in cabbage
PLoS One 13 (2018)11. - ISSN 1932-6203
The effect of plant development on thrips resistance in Capsicum
Arthropod-Plant Interactions (2018). - ISSN 1872-8855 - 8 p.
polymapR-linkage analysis and genetic map construction from F1 populations of outcrossing polyploids
Bioinformatics 34 (2018)20. - ISSN 1367-4803 - p. 3496 - 3502.
Genetic variation in phytochemicals in leaves of pepper (Capsicum) in relation to thrips resistance
Arthropod-Plant Interactions (2018). - ISSN 1872-8855 - 9 p.
Multi-environment QTL analysis of plant and flower morphological traits in tetraploid rose
Theoretical and Applied Genetics 131 (2018)10. - ISSN 0040-5752 - p. 2055 - 2069.
Reduced phloem uptake of Myzus persicae on an aphid resistant pepper accession
BMC Plant Biology 18 (2018)1. - ISSN 1471-2229
A high-quality genome sequence of Rosa chinensis to elucidate ornamental traits
Nature Plants 4 (2018). - ISSN 2055-026X - p. 473 - 484.
- Aina Kokare
- Peter Bourke