In the malaria parasite, its major blood-stage antigen, var genes, have 50-60 variants per parasite genome. In West Africa, there are over 10,000 variants circulating in local populations. How do pathogens evade immune responses through "smart strategies" of organizing the diversity of var genes within the genome and across the population? We present theory to identify signatures of immune selection using networks of genetic similarity that reveal non-neutral structures of var gene strains in an extensively sampled population in Bongo District (BD), Ghana. This work was done in collaboration with Prof. Karen Day's lab at the University of Melbourne.

Q. He, S. Pilosof, K. E. Tiedje, S. Ruybal-Pesántez, Y. Artzy-Randrup, E. B. Baskerville, K. P. Day & M. Pascual. Networks of genetic similarity reveal the role of non-neutral processes in shaping the strain structure of Plasmodium falciparum. Nature Communications, 2018

Climatic or environmental change is not only driving distributional shifts in species today, but it has also caused distributions to expand and contract in the past. Inferences about the geographic locations of past populations, especially regions that served as refugia (i.e., source populations) and migratory routes are a challenging endeavor. Here we present a pipeline we developed (called X-Origin) for statistically inferring the geographic origin of range expansion based on Ψ-statistics, a spatially explicit coalescent model, and an Approximate Bayesian Computation testing framework.

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Q. He, J. Padro, L. L. Knowles. 2017. Inferring the geographic origin of a range expansion: latitudinal and longitudinal coordinates inferred from genomic data in an ABC framework with the program X-ORIGIN. Mol. Ecol. 

Chromosomal inversions are important structural changes that may facilitate divergent selection when they capture co-adaptive loci in the face of gene flow. The number one killer in human history, the mosquito Anopheles gambiae, adapts quickly to different environments through polymorphic inversions. Amazing, right?

However, due to high linkage disequilibrium, as well as the differences in demographic histories between regions within and outside inversions, it is challenging to detect selection targets within inversions. Here we develop a new approach that uses discriminant functions informed from inversion-specific expectations to classify loci that are under selection (or drift). We were able to identify two strongly selected regions within a particular inversion associated with dry habitat.

Q. He, L. L. Knowles. 2016. Identifying targets of selection in mosaic genomes with machine learning: applications in Anopheles gambiae for detecting sites within locally adapted chromosomal inversions. Mol. Ecol. DOI: 10.1111/mec.13619

Population genetic structures can be a representative of contemporary habitat suitability and connectivity, a remnant of historical processes or both. Without the explicit modeling of temporal shifts of habitats and the demographic processes of range contraction, expansion and recolonization, the impact of historical processes may be overlooked or misidentified in the understanding of the diversity structures.

By integrating distributional, demographic, and coalescent (iDDC) models, we evaluated the relative contributions of current or past environmental factors towards current patterns of population genetic variations. 

Q. He, D. Edwards, L. L. Knowles. 2013. Integrative testing of how environments from the past to the present shape genetic structure across landscapes. Evolution. 67:3386-3402

The increased recognition of frequent divergence with gene flow has renewed interest in chromosomal inversions as a source for promoting adaptive divergence. Inversions can suppress recombination between chromosomes with different arrangements so that local adapted inversions will be protected from introgression with the migrants.

We investigated how likely the source of adaptive inversions arise from new mutations or standing variation.

Q. He, L. L. Knowles. 2017. Rapid adaptation with gene flow via a reservoir of chromosomal inversion variation? biorxiv. doi: https://doi.org/10.1101/150771