|Minnesota cornfield, Wikimedia Commons|
The important point for Mermaid's Tale is that crop breeders have been facing causal complexity for millennia, and from a molecular point of view for decades. Their experience should be instructive for the attitudes and expectations we have for genomewide association studies (GWAS) and other 'personalized genomic medicine.' To develop useful crop traits means to select individual plants that have a desired trait that is genetic--that is, that is known to be transmitted from parent to seed, and to replicate the trait (at least, under the highly controlled, standardized kinds of conditions in which agricultural crops are grown). For this to work, one needs to be able to breed, cross, or inter-breed seeds conferring desired traits to proliferate those into a constrained strain-specific gene pool. Traditionally, this requires generations of breeding, and selection of seed from desired plants, repeated for many generations.
The idea of molecular breeding is to use genome-spanning sets of genetic markers--the same kinds of data that human geneticists use in GWAS--to identify regions of the genome that differ between plants with desirable, and those with less desirable, versions of a desired trait. If the regions of the genome that are responsible can be identified, it is easier to pick plants with the desired genotype and remove some of the 'noise' introduced by the kind of purely empirical choice during breeding that farmers have done for millennia.
Relating phenotype to genotype in this way, to identify contributing regions of the genome and select for them specifically is in a sense like personalized genome-based prediction. As discussed in the article, 'Biotech without foreign genes', by Paul Voosen in The Land Report (which, unfortunately, doesn't seem to be online) molecular breeding is a way to greatly speed up the process of empirical crop improvement. What we mean by empirical is that the result uses whatever genome regions are identified, without worrying about finding the specific gene(s) in the regions that are actually responsible (this means, in technical terms, using linkage disequilibrium between observed 'marker' genotype, and the actual causal gene).
For crops with small genomes, like rice, breeders have been more readily able to identify specific genes responsible for desired traits. But for others, the large size of the genome has yielded much more subtle and complex control that is not dominated by a few clearly identifiable genes. Sound familiar? If so, then we should be able to learn from what breeders have experienced, as it may apply to the problem of human genomic medicine and public health.
We'll discuss that in our next post.