Decimated little brown bats show potential for adaptive change

Abstract

The degree to which species can rapidly adapt is key to survival in the face of climatic and other anthropogenic changes. For little brown bats (Myotis lucifugus), whose populations have experienced declines of over 90% because of the introduced fungal pathogen that causes white-nose syndrome (WNS), survival of the species may ultimately depend upon its capacity for adaptive change. Here, we present evidence of selectively driven change (adaptation), despite dramatic nonadaptive genomic shifts (genetic drift) associated with population declines. We compared the genetic makeups of wild survivors versus non-survivors of WNS, and found significant shifts in allele frequencies of genes associated with regulating arousal from hibernation (GABARB1), breakdown of fats (cGMP-PK1), and vocalizations (FOXP2). Changes at these genes are suggestive of evolutionary adaptation, given that WNS causes bats to arouse with unusual frequency from hibernation, contributing to premature depletion of fat reserves. However, whether these putatively adaptive shifts in allele frequencies translate into sufficient increases in survival for the species to rebound in the face of WNS is unknown.

Figure 1

Sampling locations of little brown bats. (A) Sequenced survivors (n = 9, marked by stars) and non-survivors (n = 29, crosses), jittered around similar collection sites (black dots); the size of the symbol indicates relative differences in the number of samples per site (see Table S1 for details). Survivors undertake short-distance migrations away from hibernacula in spring, which is reflected in their scattered collection locations. Non-survivors are closely associated with underground hibernation sites, with most (B) collected within hibernacula (~26 carcasses marked by circles on the floor of a mine), although some (C) leave these sites prematurely, like these dead bats on the outer screen of a house <1 km from a hibernaculum (note the snowy landscape). Photo credits A. Kurta (top) and C. Rockey (bottom).

Figure 2

Stochastic drift induced genetic change. (A) PCA of survivors of WNS, with non-survivors projected onto the PC axes; PC1 explained 27% and 66% of the variance among survivors and non-survivors, respectively, and PC2 explained 13% and 6% of the variance. (B) The estimated degree of genetic drift (F, as estimated in Structure^,) is an order of magnitude greater for survivors compared to non-survivors, as illustrated by the contrasting branch lengths from an inferred common ancestor.

Figure 3

Putative loci under positive selection. AMOVA-corrected F_ST-values of SNPs versus alignment position, highlighting the three genes that our SNPs map to, as well as an outlier SNP nearby to PLA2G7 (*), and the outlier SNP which is adjacent to CGMP-PK1 (†). The dashed line marks the significance threshold and alternating colors indicate different genomic scaffolds (1,214 in our dataset).