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this last step, connecting a candidate gene to a phenotype via functional studies, is often not much easier for top-down approaches than for candidate genes identified by using population genetics.

Over the past 25 years, top-down approaches have yielded a list of ≈30 genes with well characterized phenotypic effects in plants (Doebley et al., 2006). It is known that these 30 are genes of major effect, i.e., either Mendelian factors or major QTLs, but for most it has not been determined whether they have played an important adaptive role historically. In contrast, limited application of bottom-up approaches in maize have identified ≈50 genes with a signature of adaptation. It is a statistical certainty that some of these will prove to be false positives, but it is also likely that some of these genes contribute to phenotypes that would not or could not be studied via QTL or LD mapping.

In the last year, the number of published, large-scale studies seeking to identify selected genes has exploded. Screens for selection have been applied to polymorphism data from humans (Bustamante et al., 2005; Voight et al., 2006) and Arabidopsis (Toomajian et al., 2006) as well as maize (Wright et al., 2005; Yamasaki et al., 2005). To a much more limited extent bottom-up approaches are being applied to other domesticated species, i.e., rice (Olsen et al., 2006; Zhu et al., 2007), flax (Allaby et al., 2005), sorghum (Hamblin et al., 2006), and dogs (Pollinger et al., 2005). We argue that there is an opportunity, in fact, a pressing need, for a broad-based initiative to implement bottom-up approaches in 15–20 important crops, not unlike a multispecies HapMap project. Such an initiative would be relatively inexpensive given new sequencing technologies and would have far-reaching consequences beyond identifying candidate genes. Important side benefits would include broader-based information on LD, SNP discovery on a panel of sufficient size to limit ascertainment biases, and evolutionary analyses of polymorphism in a genomic context. Data compared across species may also provide insights into the process of adaptation. For example, such data could inform the age-old question as to whether parallel phenotypic changes, such as the domestication syndrome, evolve via parallel genetic mechanisms (Paterson et al., 1995). Wide-scale implementation of bottom-up approaches across species would be of potential agronomic benefit, but would also provide a unique opportunity to identify the genetic basis of adaptation.

ACKNOWLEDGMENTS

We thank S. J. Macdonald and J. G. Waines for helpful discussion, and we thank two anonymous reviewers. This work was supported by National Science Foundation Grants DEB-0426166 (to B.S.G.), DBI-0321467 (to B.S.G.), and DEB-0129247 (to M. T. Clegg).



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