Genetics and biotechnology based on diploid potato


Jiming Jiang1 and David Douches2, Michigan State University, 1Department of Plant Biology and 2Department of Plant, Soil and Microbial Sciences

Cultivated potato is one of few cytologically characterized and natural autotetraploid (2n=4x=48). Classical genetic studies in an autotetraploid is highly challenging due to the complex segregation patterns of traits and a requirement of a large mapping population. Therefore, there was very few, if any, genetic studies of potato before the advent of molecular marker technology in late 1980s. Not surprisingly, the first genetic map of potato was developed based on a population derived from two diploid potato clones (Bonierbale et al. 1988, Genetics 120: 1095-1103). Since then, the vast majority of the potato genetic studies have been based on diploid lines. Recent development of sequencing homozygous or nearly homozygous diploid clones as well as high-throughput genotyping techniques have allowed us to conduct high-resolution genetic mapping similar to model diploid plant species. Diploid-based high-resolution genetic mapping will be an important foundation for gene identification and diploid potato breeding in the future.
The development of gene editing technology has dramatically changed the potential of biotech-based crop improvement. Although tetraploid potato can be readily transformed, major hurdles remain to be overcome before we can edit the current potato cultivars without going through meiosis. It is still technically challenging to edit all four alleles in a tetraploid plant. In addition, the transgenes used in the editing experiments cannot be easily separated and eliminated. We have successfully adapted CRISPR/Cas-based gene editing techniques in several self-compatible diploid potato clones. Several near-homozygous and self-compatible diploid clones have been used in gene editing experiments. We have edited several known potato genes associated with important agronomic traits and candidate genes identified based on genetic mapping and bioinformatics.