Population genomic analysis of Tunisian Medicago truncatula reveals candidates for local adaptation
2010
Friesen, Maren L. | Cordeiro, Matilde A. | Penmetsa, R Varma | Badri, Mounawer | Huguet, Thierry | Aouani, Mohamed E. | Cook, Douglas R. | Nuzhdin, Sergey V.
Genome-wide association studies rely upon segregating natural genetic variation, particularly the patterns of polymorphism and correlation between adjacent markers. To facilitate association studies in the model legume Medicago truncatula, we present a genome-scale polymorphism scan using existing Affymetrix microarrays. We develop and validate a method that uses a simple information-criteria algorithm to call polymorphism from microarray data without reliance on a reference genotype. We genotype 12 inbred M. truncatula lines sampled from four wild Tunisian populations and find polymorphisms at approximately 7% of features, comprising 31 419 probes. Only approximately 3% of these markers assort by population, and of these only 10% differentiate between populations from saline and non-saline sites. Fifty-two differentiated probes with unique genome locations correspond to 18 distinct genome regions. Sanger resequencing was used to characterize a subset of maker loci and develop a single nucleotide polymorphism (SNP)-typing assay that confirmed marker assortment by habitat in an independent sample of 33 individuals from the four populations. Genome-wide linkage disequilibrium (LD) extends on average for approximately 10 kb, falling to background levels by approximately 500 kb. A similar range of LD decay was observed in the 18 genome regions that assort by habitat; these LD blocks delimit candidate genes for local adaptation, many of which encode proteins with predicted functions in abiotic stress tolerance and are targets for functional genomic studies. Tunisian M. truncatula populations contain substantial amounts of genetic variation that is structured in relatively small LD blocks, suggesting a history of migration and recombination. These populations provide a strong resource for genome-wide association studies.
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