1. Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892-0425, USA
2. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA
3. Information Engineering Branch, Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894-6075, USA

Correspondence to: Xin-zhuan Su¹ Correspondence and requests for materials should be addressed to X.-z.S. (e-mail: Email: xsu@niaid.nih.gov).

Abstract

The Malaria's Eve hypothesis, proposing a severe recent population bottleneck (about 3,000–5,000 years ago) of the human malaria parasite Plasmodium falciparum, has prompted a debate about the origin and evolution of the parasite^{1, 2, 3, 4, 5, 6}. The hypothesis implies that the parasite population is relatively homogeneous, favouring malaria control measures. Other studies, however, suggested an ancient origin and large effective population size^{5, 7, 8, 9, 10}. To test the hypothesis, we analysed single nucleotide polymorphisms (SNPs) from 204 genes on chromosome 3 of P. falciparum. We have identified 403 polymorphic sites, including 238 SNPs and 165 microsatellites, from five parasite clones, establishing chromosome-wide haplotypes and a dense map with one polymorphic marker per 2.3 kilobases. On the basis of synonymous SNPs and non-coding SNPs, we estimate the time to the most recent common ancestor to be 100,000–180,000 years, significantly older than the proposed bottleneck. Our estimated divergence time coincides approximately with the start of human population expansion¹¹, and is consistent with a genetically complex organism able to evade host immunity and other antimalarial efforts.

1. Laboratory of Malaria and Vector Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland 20892-0425, USA
2. Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637, USA
3. Information Engineering Branch, Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894-6075, USA

Correspondence to: Xin-zhuan Su¹ Correspondence and requests for materials should be addressed to X.-z.S. (e-mail: Email: xsu@niaid.nih.gov).