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The Pattern of Polymorphism in Arabidopsis thaliana

Magnus NordborgMolecular and Computational Biology, University of Southern California, Los Angeles, California, USA. [email protected]Tina T. HuMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaYoko IshinoMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaJinal JhaveriMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaChristopher ToomajianMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaHonggang ZhengMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaErica BakkerDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of AmericaPeter CalabreseMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaJean GladstoneDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of AmericaRana GoyalMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaMattias JakobssonDepartment of Cell and Organism Biology, Lund University, Lund, SwedenSung Hoon KimMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaYu. G. MorozovGenaissance Pharmaceuticals, New Haven, Connecticut, United States of AmericaBadri PadhukasahasramMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaVincent PlagnolMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaNoah A. RosenbergMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaChitiksha ShahMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaJeffrey D. WallMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaJue WangDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of AmericaKeyan ZhaoMolecular and Computational Biology, University of Southern California, Los Angeles, California, United States of AmericaTed KalbfleischGenaissance Pharmaceuticals, New Haven, Connecticut, United States of AmericaVincent SchulzGenaissance Pharmaceuticals, New Haven, Connecticut, United States of AmericaMartin KreitmanDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of AmericaJoy BergelsonDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America

2005en

ABI

Annotatsiya

We resequenced 876 short fragments in a sample of 96 individuals of Arabidopsis thaliana that included stock center accessions as well as a hierarchical sample from natural populations. Although A. thaliana is a selfing weed, the pattern of polymorphism in general agrees with what is expected for a widely distributed, sexually reproducing species. Linkage disequilibrium decays rapidly, within 50 kb. Variation is shared worldwide, although population structure and isolation by distance are evident. The data fail to fit standard neutral models in several ways. There is a genome-wide excess of rare alleles, at least partially due to selection. There is too much variation between genomic regions in the level of polymorphism. The local level of polymorphism is negatively correlated with gene density and positively correlated with segmental duplications. Because the data do not fit theoretical null distributions, attempts to infer natural selection from polymorphism data will require genome-wide surveys of polymorphism in order to identify anomalous regions. Despite this, our data support the utility of A. thaliana as a model for evolutionary functional genomics.

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DOI: 10.1371/journal.pbio.0030196

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