The study examines the pattern of genetic polymorphism in Arabidopsis thaliana, a selfing plant species, using genomic data from 96 individuals. Despite being selfing, the polymorphism pattern aligns with expectations for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb, and variation is shared globally, though population structure and isolation by distance are evident. The data do not fit standard neutral models, showing a genome-wide excess of rare alleles, likely due to selection. There is significant variation in polymorphism levels across genomic regions, with higher levels in regions with segmental duplications and lower levels in gene-dense regions. The study highlights the need for genome-wide surveys to identify anomalous regions influenced by natural selection. Despite this, the data support A. thaliana as a model for evolutionary functional genomics. The study reveals a complex population structure, with individuals showing strong geographic clustering. The pattern of polymorphism is influenced by both demographic factors and intrinsic genomic features. The level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. The study also finds that the pattern of polymorphism is affected by recombination and gene conversion, with LD decaying within 25–50 kb. The results suggest that A. thaliana has a high level of LD, similar to humans, but with higher SNP density. The study emphasizes the importance of considering population structure and genomic factors when interpreting polymorphism data. The findings highlight the need for more robust inference methods and the potential of A. thaliana as a model for studying functional genomics. The data also suggest that A. thaliana may have a recent human introduction to the New World, leading to reduced haplotype variation. The study provides insights into the genetic diversity and population structure of A. thaliana, with implications for understanding evolutionary processes and functional genomics.The study examines the pattern of genetic polymorphism in Arabidopsis thaliana, a selfing plant species, using genomic data from 96 individuals. Despite being selfing, the polymorphism pattern aligns with expectations for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb, and variation is shared globally, though population structure and isolation by distance are evident. The data do not fit standard neutral models, showing a genome-wide excess of rare alleles, likely due to selection. There is significant variation in polymorphism levels across genomic regions, with higher levels in regions with segmental duplications and lower levels in gene-dense regions. The study highlights the need for genome-wide surveys to identify anomalous regions influenced by natural selection. Despite this, the data support A. thaliana as a model for evolutionary functional genomics. The study reveals a complex population structure, with individuals showing strong geographic clustering. The pattern of polymorphism is influenced by both demographic factors and intrinsic genomic features. The level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. The study also finds that the pattern of polymorphism is affected by recombination and gene conversion, with LD decaying within 25–50 kb. The results suggest that A. thaliana has a high level of LD, similar to humans, but with higher SNP density. The study emphasizes the importance of considering population structure and genomic factors when interpreting polymorphism data. The findings highlight the need for more robust inference methods and the potential of A. thaliana as a model for studying functional genomics. The data also suggest that A. thaliana may have a recent human introduction to the New World, leading to reduced haplotype variation. The study provides insights into the genetic diversity and population structure of A. thaliana, with implications for understanding evolutionary processes and functional genomics.