By Tim Martinson and Michelle Podolec.
Public and private breeders of commodity crops such as maize and soybeans have long used sophisticated bioinformatics, statistical tools, and ‘big data’ to guide their breeding programs. These tools increasingly leverage detailed DNA sequence information to predict the performance of each crop’s breeding lines – and ultimately help breeders release improved varieties more quickly.
But these sophisticated breeding tools have not been available to breeders of smaller-scale specialty crops. With their limited resources, obtaining even rudimentary genetic maps has been time-consuming and expensive. So specialty crop breeding has relied heavily upon field observations (phenotyping), and the breeder’s individual knowledge and experience in making crosses and selecting (or discarding) progeny. Specialty crop breeding has been as much of an ‘art’ as a ‘science’.
Dramatic drops in the cost of DNA sequencing and genome assembly have, for the first time, made genetic data abundant and financially accessible to specialty crop breeders. In grapes, for example, obtaining high quality whole-genome sequences of the ~500 million DNA base pairs on 19 chromosomes has dropped in cost from millions of dollars in the early 2000s to about $3000 per accession today.
Now specialty crop breeders have access to a torrent of new DNA sequence data. But they still lack the infrastructure and access to bioinformatics that commodity crop breeders have enjoyed for decades.
