Genetic Mapping Populations for Conducting High-Resolution Trait Mapping in Plants

• Published in: Advances in biochemical engineering, biotechnology Vol. 164; p. 109
• Main Authors: Cockram, James, Mackay, Ian
• Format: Journal Article
• Language: English
• Published: Germany 01.01.2018
• Subjects: Chromosome Mapping; Crosses, Genetic; Genetics, Population; Phenotype; Polymorphism, Single Nucleotide; Quantitative Trait Loci - genetics; Nested association mapping (NAM); Fine-mapping; Linkage disequilibrium (LD); Precision; Multi-founder advanced generation inter cross (MAGIC); Arabidopsis multi-parent recombinant inbred line (AMPRIL); Genome wide association scans (GWAS); Power
• ISSN: 0724-6145
• DOI: 10.1007/10_2017_48

Fine mapping of quantitative trait loci (QTL) is the route to more detailed molecular characterization and functional studies of the relationship between polymorphism and trait variation. It is also of direct relevance to breeding since it makes QTL more easily integrated into marker-assisted breeding and into genomic selection. Fine mapping requires that marker-trait associations are tested in populations in which large numbers of recombinations have occurred. This can be achieved by increasing the size of mapping populations or by increasing the number of generations of crossing required to create the population. We review the factors affecting the precision and power of fine mapping experiments and describe some contemporary experimental approaches, focusing on the use of multi-parental or multi-founder populations such as the multi-parent advanced generation intercross (MAGIC) and nested association mapping (NAM). We favor approaches such as MAGIC since these focus explicitly on increasing the amount of recombination that occurs within the population. Whatever approaches are used, we believe the days of mapping QTL in small populations must come to an end. In our own work in MAGIC wheat populations, we started with a target of developing 1,000 lines per population: that number now looks to be on the low side. Graphical Abstract.