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Genome-wide SNP genotyping highlights the role of natural selection in Plasmodium falciparum population divergence

Daniel E Neafsey1, Stephen F Schaffner1, Sarah K Volkman23, Daniel Park1, Philip Montgomery1, Danny A Milner2, Amanda Lukens2, David Rosen2, Rachel Daniels1, Nathan Houde1, Joseph F Cortese1, Erin Tyndall1, Casey Gates1, Nicole Stange-Thomann1, Ousmane Sarr4, Daouda Ndiaye4, Omar Ndir4, Soulyemane Mboup4, Marcelo U Ferreira5, Sandra do Lago Moraes6, Aditya P Dash7, Chetan E Chitnis8, Roger C Wiegand1, Daniel L Hartl9, Bruce W Birren1, Eric S Lander1, Pardis C Sabeti1 and Dyann F Wirth2*

Author Affiliations

1 Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, MA 02142, USA

2 Department of Immunology and Infectious Diseases, Harvard School of Public Health, 677 Huntington Ave, Boston, MA 02115, USA

3 School for Health Studies, Simmons College, 300 The Fenway, Boston, MA 02115, USA

4 Faculty of Medicine and Pharmacy, Cheikh Anta Diop University, BP 7325 Dakar, Senegal

5 Departamento de Parasitologia, Instituto de Ciencias Biomedicas da USP, Av. Prof. Lineu Prestes 1374, Cidade Universitaria, 05508-900 Sao Paulo, SP, Brazil

6 Instituto de Medicina Tropical de Sao Paulo, Universidade de Sao Paulo, Av Dr. Eneas de Carvalho Aguiar 470, 05403-907 Sao Paulo, SP, Brazil

7 National Institute of Malaria Research, 22, Sham Nath Marg, Delhi-110054, India

8 International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi-110067, India

9 Department of Organismic and Evolutionary Biology, Harvard University, 16 Divinity Avenue, Cambridge, MA 02138, USA

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Genome Biology 2008, 9:R171  doi:10.1186/gb-2008-9-12-r171

Published: 15 December 2008

Additional files

Additional data file 1:

Lines indicate the number of SNPs exhibiting various call rates using the DM, BRLMM, and BRLMM-P SNP calling algorithms. BRLMM-P SNP calls were used for analysis.

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Additional data file 2:

Array performance in the presence of human DNA and malaria DNA from mixed (non-clonal) infections.

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Additional data file 3:

Reported results are for SNP loci known to exhibit different alleles between the HB3 and Dd2 lines. The highest proportion of heterozygous calls was observed for the even (1:1) mixture of malaria.

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Additional data file 4:

Concordance with known genotype can be improved using more stringent confidence cutoff values with the BRLMM-P calling algorithm.

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Additional data file 5:

Genomic location and genotype data for SNPs assayed on the array with a call rate of at least 80%.

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Additional data file 6:

(a) High MAF (MAF > 0.25) topology. (b) Low MAF (MAF < 0.25) topology. Nodes exhibiting bootstrap support levels of at least 50% or 90% are indicated by gray dots and black dots, respectively. Bootstrap support and branch length differ between the topologies, but the American and Asian parasites form congruent clades.

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Additional data file 7:

(a) Plot of the likelihood of the genotyping data given that the samples derive from K = 1-5 populations. (b) Plot of the posterior probability of population membership for each sample hybridized to the array, assuming three underlying populations.

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Additional data file 8:

(a) First two principal components for Brazil data; clusters suggest population structure. (b) First two components for worldwide data set. (c) First and third components for worldwide data set.

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Additional data file 9:

Significantly greater nonsynonymous divergence (determined by bootstrapping) is indicated by asterisks: **P < 0.001.

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Additional data file 10:

Nonsynonymous and silent SNP DAF correlation between Senegal and Thailand.

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