Genetically informed ecological niche models improve climate change predictions.

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change.

Within-host evolution of Burkholderia pseudomallei in four cases of acute melioidosis.

Little is currently known about bacterial pathogen evolution and adaptation within the host during acute infection. Previous studies of Burkholderia pseudomallei, the etiologic agent of melioidosis, have shown that this opportunistic pathogen mutates rapidly both in vitro and in vivo at tandemly repeated loci, making this organism a relevant model for studying short-term evolution. In the current study, B. pseudomallei isolates cultured from multiple body sites from four Thai patients with disseminated melioidosis were subjected to fine-scale genotyping using multilocus variable-number tandem repeat analysis (MLVA). In order to understand and model the in vivo variable-number tandem repeat (VNTR) mutational process, we characterized the patterns and rates of mutations in vitro through parallel serial passage experiments of B. pseudomallei. Despite the short period of infection, substantial divergence from the putative founder genotype was observed in all four melioidosis cases. This study presents a paradigm for examining bacterial evolution over the short timescale of an acute infection. Further studies are required to determine whether the mutational process leads to phenotypic alterations that impact upon bacterial fitness in vivo. Our findings have important implications for future sampling strategies, since colonies in a single clinical sample may be genetically heterogeneous, and organisms in a culture taken late in the infective process may have undergone considerable genetic change compared with the founder inoculum.