Identifying genes of agronomic importance in maize by screening microsatellites for evidence of selection during domestication

Abstract

Crop species experienced strong selective pressure directed at genes controlling traits of agronomic importance during their domestication and subsequent episodes of selective breeding. Consequently, these genes are expected to exhibit the signature of selection. We screened 501 maize genes for the signature of selection using microsatellites or simple sequence repeats (SSRs). We applied the Ewens-Watterson test, which can reveal deviations from a neutral-equilibrium model, as well as two nonequilibrium tests that incorporate the domestication bottleneck. We investigated two classes of SSRs: those known to be polymorphic in maize (Class I) and those previously classified as monomorphic in maize (Class II). Fifteen SSRs exhibited some evidence for selection in maize and 10 showed evidence under stringent criteria. The genes containing nonneutral SSRs are candidates for agronomically important genes. Because demographic factors can bias our tests, further independent tests of these candidates are necessary. We applied such an additional test to one candidate, which encodes a MADS box transcriptional regulator, and confirmed that this gene experienced a selective sweep during maize domestication. Genomic scans for the signature of selection offer a means of identifying new genes of agronomic importance even when gene function and the phenotype of interest are unknown.

Combining population genomics and quantitative genetics: finding the genes underlying ecologically important traits

“…Both Vigouroux et al (2002) and Scotti-Saintagne et al (2004) detected loci that behaved as outliers in comparisons of population samples between closely related species. Because linkage maps have been made from experimental crosses, it is possible to determine (1) the genomic position in which these outliers occur, and (2) in some cases, test if loci showing elevated differentiation are also the loci closest to QTL for traits that are differentiated between the species.…”

“…The benefits of combining the population genomics approach with traditional linkage maps can be seen in two studies that focused on closely related plant species (maize and teosinte: Vigouroux et al, 2002;pedunculate and sessile oak: Scotti-Saintagne et al, 2004). Both Vigouroux et al (2002) and Scotti-Saintagne et al (2004) detected loci that behaved as outliers in comparisons of population samples between closely related species.…”

“…Because linkage maps have been made from experimental crosses, it is possible to determine (1) the genomic position in which these outliers occur, and (2) in some cases, test if loci showing elevated differentiation are also the loci closest to QTL for traits that are differentiated between the species. In the maize example, two of the outlier loci were located near known QTL for ear structure and endosperm weight, two traits that differ dramatically between maize and teosinte and could have been past targets of artificial selection (Vigouroux et al, 2002). In fact, because even the largest QTL mapping populations are limited by the number of recombination events, population genomic approaches may be useful in this context to fine-scale map genes.…”

“…These cases provide a test for population genomics methods, at least in cases in which selection is strong and recent. To date, the population genomics approach has been used successfully to confirm loci that might have undergone a selective sweep in maize during domestication (Vigouroux et al, 2002), genes for coat color and shortened limbs in dog breed formation (Pollinger et al, 2005), chloroquine resistance in the malaria-inducing parasite Plasmodium falciparum (Wootton et al, 2002) and warfarin resistance in rats (Kohn et al, 2003). However, it is important to note that in all of these cases, strong artificial rather than natural selection is driving phenotypic divergence.…”

“…Because local adaptation and directional selection should have locus-specific effects of reducing genetic variability within populations and increasing differentiation between populations, loci that are outliers for these characteristics are strong candidate regions for involvement in adaptation. Determining whether an individual locus behaves as an outlier can be statistically evaluated with a battery of approaches, among them: testing whether F ST is significantly different from either zero or neutral expectations (Lewontin and Krakauer, 1973;Beaumont and Nichols, 1996;Vitalis et al, 2001;Beaumont and Balding, 2004); the lnRV and lnRH statistics (natural log of the ratio of the variance and heterozygosity of alleles between two populations; (Schlotterer, 2002)); and the Ewens-Watterson test (Ewens, 1972;Watterson, 1978;Vigouroux et al, 2002); see Storz (2005) for a recent review of such tests. Importantly, the statistical significance of these estimates Genetics Figure 1 Conceptual model for the integration of population genomics and quantitative genetics.…”