Many crops display differential geographic phenotypes and sensorial signatures, encapsulated by the concept of terroir. The drivers behind these differences remain elusive and the potential contribution of microbes has been ignored until recently. Significant genetic differentiation between microbial communities and populations from different geographic locations has been demonstrated, but crucially it has not been shown whether this correlates with differential agricultural phenotypes or not. Using wine as a model system, we utilize the regionally genetically differentiated population of Saccharomyces cerevisiae in New Zealand and objectively demonstrate that these populations differentially affect wine phenotype, which is driven by a complex mix of chemicals. These findings reveal the importance of microbial populations for the regional identity of wine and potentially extend to other important agricultural commodities. Moreover, this suggests that long-term implementation of methods maintaining differential biodiversity may have tangible economic imperatives as well as being desirable in terms of employing agricultural practices that increase responsible environmental stewardship.

Eukaryotic microbes are key ecosystem drivers; however, we have little theory and few data elucidating the processes influencing their observed population patterns. Here we provide an in-depth quantitative analysis of population separation and similarity in the yeast Saccharomyces cerevisiae with the aim of providing a more detailed account of the population processes occurring in microbes. Over 10 000 individual isolates were collected from native plants, vineyards and spontaneous ferments of fruit from six major regions spanning 1000 km across New Zealand. From these, hundreds of S. cerevisiae genotypes were obtained, and using a suite of analytical methods we provide comprehensive quantitative estimates for both population structure and rates of gene flow or migration. No genetic differentiation was detected within geographic regions, even between populations inhabiting native forests and vineyards. We do, however, reveal a picture of national population structure at scales above ∼100 km with distinctive populations in the more remote Nelson and Central Otago regions primarily contributing to this. In addition, differential degrees of connectivity between regional populations are observed and correlate with the movement of fruit by the New Zealand wine industry. This suggests some anthropogenic influence on these observed population patterns.

Microbes influence the quality of agricultural commodities and contribute to their distinctive sensorial attributes. Increasingly studies have demonstrated not only differential geographic patterns in microbial communities and populations, but that these contribute to valuable regionally distinct agricultural product identities, the most well-known example being wine. However, little is understood about microbial geographic patterns at scales of less than 100 km. For wine, single vineyards are the smallest (and most valuable) scale at which wine is asserted to differ; however, it is unknown whether microbes play any role in agricultural produce differentiation at this scale. Here we investigate whether vineyard fungal communities and yeast populations driving the spontaneous fermentation of fruit from these same vineyards are differentiated using metagenomics and population genetics. Significant differentiation of fungal communities was revealed between four Central Otago (New Zealand) Pinot Noir vineyard sites. However, there was no vineyard demarcation between fermenting populations of S. cerevisiae. Overall, this provides evidence that vineyard microbiomes potentially contribute to vineyard specific attributes in wine. Understanding the scale at which microbial communities are differentiated, and how these communities influence food product attributes has direct economic implications for industry and could inform sustainable management practices that maintain and enhance microbial diversity.

Bayesian inference methods are extensively used to detect the presence of population structure given genetic data. The primary output of software implementing these methods are ancestry profiles of sampled individuals. While these profiles robustly partition the data into subgroups, currently there is no objective method to determine whether the fixed factor of interest (e.g. geographic origin) correlates with inferred subgroups or not, and if so, which populations are driving this correlation. We present ObStruct, a novel tool to objectively analyse the nature of structure revealed in Bayesian ancestry profiles using established statistical methods. ObStruct evaluates the extent of structural similarity between sampled and inferred populations, tests the significance of population differentiation, provides information on the contribution of sampled and inferred populations to the observed structure and crucially determines whether the predetermined factor of interest correlates with inferred population structure. Analyses of simulated and experimental data highlight ObStruct's ability to objectively assess the nature of structure in populations. We show the method is capable of capturing an increase in the level of structure with increasing time since divergence between simulated populations. Further, we applied the method to a highly structured dataset of 1,484 humans from seven continents and a less structured dataset of 179 Saccharomyces cerevisiae from three regions in New Zealand. Our results show that ObStruct provides an objective metric to classify the degree, drivers and significance of inferred structure, as well as providing novel insights into the relationships between sampled populations, and adds a final step to the pipeline for population structure analyses.

Due to its commercial value and status as a research model there is an extensive body of knowledge concerning Saccharomyces cerevisiae's cell biology and genetics. Investigations into S. cerevisiae's ecology are comparatively lacking, and are mostly focused on the behaviour of this species in high sugar, fruit-based environments; however, fruit is ephemeral, and presumably, S. cerevisiae has evolved a strategy to survive when this niche is not available. Among other places, S. cerevisiae has been isolated from soil which, in contrast to fruit, is a permanent habitat. We hypothesize that S. cerevisiae employs a life history strategy targeted at self-preservation rather than growth outside of the fruit niche, and resides in forest niches, such as soil, in a dormant and resistant sporulated state, returning to fruit via vectors such as insects. One crucial aspect of this hypothesis is that S. cerevisiae must be able to sporulate in the ‘forest’ environment. Here, we provide the first evidence for a natural environment (soil) where S. cerevisiae sporulates. While there are further aspects of this hypothesis that require experimental verification, this is the first step towards an inclusive understanding of the more cryptic aspects of S. cerevisiae's ecology.