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Ellen Leffler

Assistant Professor of Human Genetics

Leffler Photo

B.A. Amherst College

Ph.D. University of Chicago



Ellen Leffler's Lab Page

Ellen Leffler's PubMed Literature Search


Molecular Biology Program

Genomics, evolution, population genetics, non-human primates, malaria


Evolutionary and infectious disease genomics in humans and non-human primates

Research in the Leffler lab focuses on evolutionary and population genetics in humans and other primates. We apply computational approaches to diverse genomics datasets to study the origin, evolution, and functional consequences of genetic variation. We are especially interested in structural variation and variation that influences infectious disease susceptibility within and between species.

Copy number variation at the host-pathogen interface

Copy number variants (CNVs), which include deletions, duplications, and more complex changes, occur frequently throughout the genome and can have major functional effects. A single copy number mutation can alter gene or regulatory element content, and/or change their spacing. CNVs affect even more sequence than single nucleotide polymorphisms (SNPs), yet they are more difficult to identify and genotype accurately and so are often overlooked. Some regions of the genome are particularly prone to CNVs due to their repetitive content, and are difficult to characterize for the same reason. While many of these regions are known because of their contribution to disease through recurrent de novo mutations, it is thought that the propensity for CNVs at others may be evolutionarily advantageous. For example, CNVs at immune gene clusters or pathogen receptors may create new variation that challenges pathogens, such as the example shown here. We are currently working on developing methods to improve calling of CNVs in repetitive regions and incorporate them into evolutionary and association studies. We are also interested in the mutational mechanisms that give rise to these CNVs, which often involve mistakes by the recombination machinery in recognizing homology.

Non-human primates and their malaria parasites

Malaria has been an important selective pressure throughout human history and many genetic adaptations have now been discovered, including the sickle cell allele, O blood group, Dantu blood group, and Duffy-negative blood group. Non-human primates are frequently infected with related parasite species and yet we do not know whether they have adapted similarly in response. We are using population and comparative genomic approaches combined with functional data to investigate malaria infections in non-human primates and identify loci that may contribute to why some individuals and some species are more resistant to parasites than others. We are currently focusing on macaque species (genus Macaca) in south and southeast Asia, which are host to multiple Plasmodium species and differ in susceptibility. We are also analyzing sequence data for macaque malaria parasites to investigate their genome evolution and species-specific features.

Malaria-protective variation around the world

Malaria-protective alleles show heterogeneity across the world as to where they are present and at what frequencies. This is due to the influence of a combination of evolutionary forces, including mutation (where the variants arose), selection (where malaria has been present and how prevalent), and gene flow (how variants have spread between populations). We are interested in modeling these processes and evaluating genetic variation data for diverse populations to investigate how they have influenced the distribution of malaria-protective alleles.

Joint analyses of host and pathogen

So far, genetic studies have largely focused on either host or pathogen genetic variation. It is now possible to generate genomic or transcriptomic datasets for both host and pathogen from the same infection to more comprehensively study their effects on disease susceptibility and outcome, and identify interaction effects between species. A direction we are moving towards is to generate paired datasets for diseases that have been longstanding evolutionary battlegrounds between humans and pathogens, such as malaria, tuberculosis or cholera.


  1. Band G, Le QC, Clarke GM, Kivinen K, Hubbart C, Jeffreys AE, Rowlands K, Leffler EM, Jallow M, Conway DJ, Sisay-Joof F, d’Alessandro U, Toure OB, Thera MA, Konate S, Sissoko S, Mangano VD, Bougouma ED, Sirima SB, Amenga-Etego LN, Ghansah AK, Hodgson AVO, Wilson MD, Enimil A, Ansong D, Evans J, Ademola SA, Apinjoh TO, Ndila CM, Manjurano A, Drakeley C, Reyburn H, Nguyen HP, Nguyen TNQ, Thai CQ, Hien TT, Teo YY, Manning L, Laman M, Michon P, Karunajeewa H, Siba P, Allen S, Allen, A, Bahlo M, Davis TME, Cornelius V, Shelton J, Spencer CCA, Busby GBJ, Kerasidou A, Drury E, Stalker J, Dilthey A, Mentzer AJ, McVean G, Bojang KA, Doumbo O, Modiano D, Koram KA, Agbenyega T, Amodu OK, Achidi E, Williams TN, Marsh K, Riley EM, Molyneux M, Taylor T, Dunstan SJ, Farrar J, Mueller I, Rockett KA, and DP Kwiatkowski. Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia, and Oceania. Nature Communications 16 December 2019 10, 5732
  2. Busby GBJ, Christ R, Band G, Leffler EM, Le QS, MalariaGEN, Rockett KA, Kwiatkowski DP and CCA Spencer. Inferring adaptive gene flow in recent African history. biorXiv 2017
  3. Leffler EM. Evolutionary insights from wild vervet genomes. Nature Genetics 29 November 2017 49, 1671–1672
  4. Leffler EM, Band G, Busby GBJ, Kivinen K, Le QS, Clarke GM, Bojang KA, Conway DJ, Jallow M, Sisay-Joof F, Bougouma EC, Mangano VD, Modiano D, Sirima SB, Achidi E, Apinjoh TO, Marsh K, Ndila CM, Peshu N, Williams TN, Drakeley C, Manjurano A, Reyburn H, Riley E, Kachala D, Molyneux M, Nyirongo V, Taylor T, Thornton N, Tilley L, Grimsley S, Drury E, Stalker J, Cornelius V, Hubbart C, Jeffreys AE, Rowlands K, Rockett KA, Spencer CCA, Kwiatkowski DP and Malaria Genomic Epidemiology Network. Resistance to malaria through structural variation of red blood cell invasion receptors. Science 16 June 2017 356(6343): eaam6393
  5. Singhal S*, Leffler EM*, Sannareddy K, Turner I, Venn O, Hooper DM, Strand AI, Li Q, Raney B, Balakrishnan CN, Griffith SC, McVean G, and M Przeworski. Stable recombination hotspots in birds. Science 20 Nov 2015 350:928-32
  6. Malaria Genomic Epidemiology Network. A novel locus of resistance to severe malaria in a region of ancient balancing selection. Nature 8 October 2015 526:253-7
  7. Leffler EM*, Gao Z*, Pfeifer S*, Segurel L*, Auton A, Venn O, Bowden R, Bontrop R, Wall JD, Sella G, Donnelly P, McVean G+, and M Przeworski+. Multiple instances of ancient balancing selection shared between humans and chimpanzees. Science 29 March 2013 339:1578-1582
  8. Leffler EM, Bullaughey K*, Matute DR*, Meyer WK*, Segurel L*, Venkat A*, Andolfatto P, and M Przeworski. Revisiting an Old Riddle: What Determines Genetic Diversity Levels within Species? PLoS Biology Sept 2012 10(9):e1001388
  9. Auton A*, Fledel-Alon A*, Pfeifer S*, Venn O*, Ségurel L, Street T, Leffler EM, Bowden R, Ineas I, Broxholme J, Humburg J, Iqbal Z, Lunter G, Maller J, Hernandez RD, Melton SC, Venkat A, Nobrega M, Bontrop R, Donnelly P+, Przeworski M+, and G McVean+. A fine-scale chimpanzee genetic map from population resequencing data. Science 13 April 2012 336:193-198
  10. Segurel L, Leffler EM, and M Przeworski. The case of the fickle fingers: How PRDM9 specifies meiotic recombination hotspots in humans. PLoS Biology Dec 2011 9(12):e1001211
  11. Fledel-Alon A*, Leffler EM*, Guan Y, Stephens M, Coop G+ and M Przeworski+, 2011 Variation in human recombination rates and its genetic determinants. PLoS One June 2011 6(6):e20321

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Last Updated: 8/10/20