Chromosome inversions and ecological plasticity in the main African malaria mosquitoes

Abstract

Chromosome inversions have fascinated the scientific community, mainly because of their role in the rapid adaption of different taxa to changing environments. However, the ecological traits linked to chromosome inversions have been poorly studied. Here, we investigated the roles played by 23 chromosome inversions in the adaptation of the four major African malaria mosquitoes to local environments in Africa. We studied their distribution patterns by using spatially explicit modeling and characterized the ecogeographical determinants of each inversion range. We then performed hierarchical clustering and constrained ordination analyses to assess the spatial and ecological similarities among inversions. Our results show that most inversions are environmentally structured, suggesting that they are actively involved in processes of local adaptation. Some inversions exhibited similar geographical patterns and ecological requirements among the four mosquito species, providing evidence for parallel evolution. Conversely, common inversion polymorphisms between sibling species displayed divergent ecological patterns, suggesting that they might have a different adaptive role in each species. These results are in agreement with the finding that chromosomal inversions play a role in Anopheles ecotypic adaptation. This study establishes a strong ecological basis for future genome-based analyses to elucidate the genetic mechanisms of local adaptation in these four mosquitoes.

Keywords: Anopheles; chromosome inversions; ecological divergence; local adaptation; parallel evolution.

Figure 1. Sampling villages

Map of the main African habitat types (Olson et al. 2001) showing the distribution of the villages where the four Anopheles species were sampled: Anopheles gambiae (yellow dots), An. coluzzii (red dots), An. arabiensis (blue dots) and An. funestus (grey dots). A detailed representation of the West-Central Africa area that was selected to plot the predicted maps and carry out the similarity analyses is shown. Species’ points out of the study area were used for calibration purposes (see Materials and Methods)

Figure 2

Maps of the predicted inversion frequencies for Anopheles gambiae, An. coluzzii, An. arabiensis and An. funestus. Predicted inversion distributions were passively plotted in the West-Central Africa study area. Blue represents a probability of 100% for the standard inversion, red represents a probability of 100% for the inverted inversion form, according to the literature data for each species (Green and Hunt 1980; Coluzzi et al. 2002). To improve their representativity, probabilities were reclassified in four classes: 0.00–0.25; 0.25–0.50; 0.50–0.75; 0.75–1.0.

Figure 3. Dendrogram of the predicted inversion frequency distribution in West-Central Africa showing similar environmental patterns in Anopheles species

Inversions included in the three chorotype clusters (Chorotype 1, Chorotype 2 and Chorotype 3) are enclosed in squares. Anopheles spp. are coded by letters and colours: g (yellow): An. gambiae; c (red): An. coluzzii; a (blue): An. arabiensis; f (grey): An. funestus. In x-axis, S corresponds to the Baroni-Urbani and Buser similarity index (Olivero et al. 2011). Chorotype 1 and Chorotype 2 have both a IH =1, while Chorotype 3 has a IH = 0.822 (G-test, p-value<0.001) (Olivero et al. 2011).

Figure 4. Canonical correspondence analysis of the inversion ecological distribution throughout West-Central Africa to highlight local adaptation patterns among chromosome inversions and mosquito species

CCA diagram showing the ordination of the chromosomal inversions (standard and inverted; red crosses indicate their ecological optima) for each species along the first two canonical axes (CCA1 and 2) that, together, explain ~80% of variance. Anopheles spp. are coded by letters and colours: g (yellow): An. gambiae; c (red): An. coluzzii; a (blue): An. arabiensis; f (grey): An. funestus. Asterisks represent the standard form of each inversion. Ecological predictors are passively plotted on the graph: elevation, temperature (mean temperature of the wettest quarter of the year), precipitations (mean precipitations of the wettest quarter of the year) and NDVI variables (yearly mean, yearly variation, quarterly variation and wettest quarter variation for the period included in the study). An inset of the main Figure is provided in the bottom-righ corner for clarity purposses, showing the inversions encompassed in the red square.