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With increases in throughput and reductions in cost, long read sequencing has become the standard for most genome assembly projects and has opened up new avenues for large-scale genomic research. While more amenable to assembly than short-read sequence data, long-read datasets tend to have higher error rates. To address this problem numerous tools have been developed to correct reads before assembly and polish assembled contigs. Although, numerous studies have been conducted to assess or benchmark these tools, few capture the real variance in long read sequence data that might affect tool performance much less full pipeline performance. To address these shortcomings, we compiled a dataset containing long-read sequences of 116 different strains of brewers’ yeast, S. cerevisiae, gathered largely from public databases and evaluated different assembly-related tools as well as their interactions. We found that pre-assembly short-read error correction of long reads combined with post-assembly short-read polishing provided the best assemblies. We also found that correction/polishing steps with uncorrected long reads often lead to degradation of assembly quality. Finally, we show which tools and pipelines work best with different types of input data.

Biological phenotypes are products of complex evolutionary processes in which selective forces influence multiple biological trait measurements in unknown ways. Phylogenetic factor analysis disentangles these relationships across the evolutionary history of a group of organisms. Scientists seeking to employ this modeling framework confront numerous modeling and implementation decisions, the details of which pose computational and replicability challenges. General and impactful community employment requires a data scientific analysis plan that balances flexibility, speed and ease of use, while minimizing model and algorithm tuning. Even in the presence of non-trivial phylogenetic model constraints, we show that one may analytically address latent factor uncertainty in a way that (a) aids model flexibility, (b) accelerates computation (by as much as 500-fold) and (c) decreases required tuning. We further present practical guidance on inference and modeling decisions as well as diagnosing and solving common problems in these analyses. We codify this analysis plan in an automated pipeline that distills the potentially overwhelming array of modeling decisions into a small handful of (typically binary) choices. We demonstrate the utility of these methods and analysis plan in four real-world problems of varying scales., 27 pages, 7 figures, 1 table

It is hard to imagine a world without food-associated microbes. The production of bread, wine, beer, salami, coffee, chocolate, cheese and many other foods and beverages all rely on specific microbes. In cheese, myriad microbial species collaborate to yield the complex organoleptic properties that are appreciated by millions of people worldwide. In the early days of cheese making, these complex communities emerged spontaneously from the natural flora associated with the raw materials, the equipment, the production environment or craftsmen involved in the production process. However, in some cases, the microbes shifted their natural habitat to the new cheese-associated environment. The most obvious cause of this is backslopping, where part of a fermented product is used to inoculate the next batch. In addition, some microbes may simply adhere to the tools used in the production process. These microbial communities gradually adapted to the novel man-made niches, a process referred to as "domestication." Domestication is associated with specific genomic and phenotypic changes and ultimately leads to lineages that are genetically and phenotypically distinct from their wild ancestors. In this issue of Molecular Ecology, Dumas et al. have investigated a prime example of cheese-associated microbes, the fungus Penicillium roqueforti. The authors identified several hallmarks of domestication in the genome and phenome of this species, allowing them to hypothesize about the origin of blue-veined cheese fungi domestication, and the specific evolutionary processes involved in adaptation to the cheese matrix. ispartof: MOLECULAR ECOLOGY vol:29 issue:14 pages:2517-2520 ispartof: location:England status: published

Domestication refers to artificial selection and breeding of wild species to obtain cultivated variants that thrive in man-made niches and meet human or industrial requirements. Several genotypic and phenotypic signatures of domestication have been described in crops, livestock and pets. However, domestication is not unique to plants and animals. Microbial diversity has also been shaped by the emergence of novel and highly specific man-made environments, like food and beverage fermentations. This allowed rapid adaptation and diversification of various microbes, such as certain Lactococcus, Lactobacillus, Oenococcus, Saccharomyces and Aspergillus species. During the domestication process, microbes gained the capacity to efficiently consume particular nutrients, cope with a multitude of industry-specific stress factors and produce desirable compounds, often at the cost of a reduction in fitness in their original, natural environments. Moreover, different lineages of the same species adapted to highly diverse niches, resulting in genetically and phenotypically distinct strains. In this Review, we discuss the basic principles of microbial domestication and describe how recent research is uncovering its genetic underpinnings. ispartof: CURRENT BIOLOGY vol:29 issue:10 pages:R381-R393 ispartof: location:England status: published

When faced with environmental changes, microbes enter a lag phase during which cell growth is arrested, allowing cells to adapt to the new situation. The discovery of the lag phase started the field of gene regulation and led to the unraveling of underlying mechanisms. However, the factors determining the exact duration and dynamics of the lag phase remain largely elusive. Naively, one would expect that cells adapt as quickly as possible, so they can resume growth and compete with other organisms. However, recent studies show that the lag phase can last from several hours up to several days. Moreover, some cells within the same population take much longer than others, despite being genetically identical. In addition, the lag phase duration is also influenced by the past, with recent exposure to a given environment leading to a quicker adaptation when that environment returns. Genome-wide screens in Saccharomyces cerevisiae on carbon source shifts now suggest that the length of the lag phase, the heterogeneity in lag times of individual cells, and the history-dependent behavior are not determined by the time it takes to induce a few specific genes related to uptake and metabolism of a new carbon source. Instead, a major shift in general metabolism, and in particular a switch between fermentation and respiration, is the major bottleneck that determines lag duration. This suggests that there may be a fitness trade-off between complete adaptation of a cell’s metabolism to a given environment, and a short lag phase when the environment changes. Electronic supplementary material The online version of this article (10.1007/s00294-019-00938-2) contains supplementary material, which is available to authorized users.

Hybridization between species often leads to non-viable or infertile offspring, yet examples of evolutionarily successful interspecific hybrids have been reported in all kingdoms of life. However, many questions on the ecological circumstances and evolutionary aftermath of interspecific hybridization remain unanswered. In this study, we sequenced and phenotyped a large set of interspecific yeast hybrids isolated from brewing environments to uncover the influence of interspecific hybridization in yeast adaptation and domestication. Our analyses demonstrate that several hybrids between Saccharomyces species originated and diversified in industrial environments by combining key traits of each parental species. Furthermore, posthybridization evolution within each hybrid lineage reflects subspecialization and adaptation to specific beer styles, a process that was accompanied by extensive chimerization between subgenomes. Our results reveal how interspecific hybridization provides an important evolutionary route that allows swift adaptation to novel environments. ispartof: NATURE ECOLOGY & EVOLUTION vol:3 issue:11 pages:1562-1575 ispartof: location:England status: published

Today's beer market is challenged by a decreasing consumption of traditional beer styles and an increasing consumption of specialty beers. In particular, lager-type beers (pilsner), characterized by their refreshing and unique aroma and taste, yet very uniform, struggle with their sales. The development of novel variants of the common lager yeast, the interspecific hybrid Saccharomyces pastorianus, has been proposed as a possible solution to address the need of product diversification in lager beers. Previous efforts to generate new lager yeasts through hybridization of the ancestral parental species (S. cerevisiae and S. eubayanus) yielded strains with an aromatic profile distinct from the natural biodiversity. Unfortunately, next to the desired properties, these novel yeasts also inherited unwanted characteristics. Most notably is their phenolic off-flavor (POF) production, which hampers their direct application in the industrial production processes. Here, we describe a CRISPR-based gene editing strategy that allows the systematic and meticulous introduction of a natural occurring mutation in the FDC1 gene of genetically complex industrial S. cerevisiae strains, S. eubayanus yeasts and interspecific hybrids. The resulting cisgenic POF- variants show great potential for industrial application and diversifying the current lager beer portfolio. ispartof: PLOS ONE vol:14 issue:1 ispartof: location:United States status: published

Cells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells' ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types. ispartof: ELIFE vol:7 ispartof: location:England status: published

Yeasts have been used for food and beverage fermentations for thousands of years. Today, numerous different strains are available for each specific fermentation process. However, the nature and extent of the phenotypic and genetic diversity and specific adaptations to industrial niches have only begun to be elucidated recently. In Saccharomyces, domestication is most pronounced in beer strains, likely because they continuously live in their industrial niche, allowing only limited genetic admixture with wild stocks and minimal contact with natural environments. As a result, beer yeast genomes show complex patterns of domestication and divergence, making both ale (S. cerevisiae) and lager (S. pastorianus) producing strains ideal models to study domestication and, more generally, genetic mechanisms underlying swift adaptation to new niches. ispartof: Current Opinion in Biotechnology vol:49 pages:148-155 ispartof: location:England status: published

Because of an increased interest in complex niche products and the ongoing quest for improved brewing efficiency and quality, the interest in novel yeasts is increasing. However, many of these nonconventional yeasts and newly developed hybrids often produce undesirable off-flavors and, in particular, are characterized by strong production of phenolic aromas such as 4-vinyl guaiacol (4VG). Here, we describe a novel high-throughput, low-cost absorbance-based screening method that allows quick determination of the phenolic off-flavor (POF) production capacity of yeasts. We show that this method correlates well with the standard, more laborious GC-based methods and that it can be used to assess POF production of many different strains in parallel with minimal hands-on labor. This new method therefore opens exciting new routes to select rare variants or mutations that combine desirable phenotypes without showing unwanted production of POFs such as 4VG.

The lag phase is arguably one of the prime characteristics of microbial growth. Longer lag phases result in lower competitive fitness in variable environments, and the duration of the lag phase is also important in many industrial processes where long lag phases lead to sluggish, less efficient fermentations. Despite the immense importance of the lag phase, surprisingly little is known about the exact molecular processes that determine its duration. Our study uses the molecular toolbox of S. cerevisiae combined with detailed growth experiments to reveal how the transition from fermentative to respirative metabolism is a key bottleneck for cells to overcome the lag phase. Together, our findings not only yield insight into the key molecular processes and genes that influence lag duration but also open routes to increase the efficiency of industrial fermentations and offer an experimental framework to study other types of lag behavior., When faced with environmental changes, microbes often enter a temporary growth arrest during which they reprogram the expression of specific genes to adapt to the new conditions. A prime example of such a lag phase occurs when microbes need to switch from glucose to other, less-preferred carbon sources. Despite its industrial relevance, the genetic network that determines the duration of the lag phase has not been studied in much detail. Here, we performed a genome-wide Bar-Seq screen to identify genetic determinants of the Saccharomyces cerevisiae glucose-to-galactose lag phase. The results show that genes involved in respiration, and specifically those encoding complexes III and IV of the electron transport chain, are needed for efficient growth resumption after the lag phase. Anaerobic growth experiments confirmed the importance of respiratory energy conversion in determining the lag phase duration. Moreover, overexpression of the central regulator of respiration, HAP4, leads to significantly shorter lag phases. Together, these results suggest that the glucose-induced repression of respiration, known as the Crabtree effect, is a major determinant of microbial fitness in fluctuating carbon environments.

Changes in transcriptional regulatory networks can significantly contribute to species evolution and adaptation. However, identification of genome-scale regulatory networks is an open challenge, especially in non-model organisms. Here, we introduce multi-species regulatory network learning (MRTLE), a computational approach that uses phylogenetic structure, sequence-specific motifs, and transcriptomic data, to infer the regulatory networks in different species. Using simulated data from known networks and transcriptomic data from six divergent yeasts, we demonstrate that MRTLE predicts networks with greater accuracy than existing methods because it incorporates phylogenetic information. We used MRTLE to infer the structure of the transcriptional networks that control the osmotic stress responses of divergent, non-model yeast species and then validated our predictions experimentally. Interrogating these networks reveals that gene duplication promotes network divergence across evolution. Taken together, our approach facilitates study of regulatory network evolutionary dynamics across multiple poorly studied species.

Summary Whereas domestication of livestock, pets, and crops is well documented, it is still unclear to what extent microbes associated with the production of food have also undergone human selection and where the plethora of industrial strains originates from. Here, we present the genomes and phenomes of 157 industrial Saccharomyces cerevisiae yeasts. Our analyses reveal that today’s industrial yeasts can be divided into five sublineages that are genetically and phenotypically separated from wild strains and originate from only a few ancestors through complex patterns of domestication and local divergence. Large-scale phenotyping and genome analysis further show strong industry-specific selection for stress tolerance, sugar utilization, and flavor production, while the sexual cycle and other phenotypes related to survival in nature show decay, particularly in beer yeasts. Together, these results shed light on the origins, evolutionary history, and phenotypic diversity of industrial yeasts and provide a resource for further selection of superior strains. PaperClip, Graphical Abstract Image 1, Highlights • We sequenced and phenotyped 157 S. cerevisiae yeasts • Present-day industrial yeasts originate from only a few domesticated ancestors • Beer yeasts show strong genetic and phenotypic hallmarks of domestication • Domestication of industrial yeasts predates microbe discovery, The history and domestication of yeast used for making beer and other types of alcohol are revealed through genomic and phenotypic analyses.

Background The brewer’s yeast Saccharomyces cerevisiae is exploited in several industrial processes, ranging from food and beverage fermentation to the production of biofuels, pharmaceuticals and complex chemicals. The large genetic and phenotypic diversity within this species offers a formidable natural resource to obtain superior strains, hybrids, and variants. However, most industrially relevant traits in S. cerevisiae strains are controlled by multiple genetic loci. Over the past years, several studies have identified some of these QTLs. However, because these studies only focus on a limited set of traits and often use different techniques and starting strains, a global view of industrially relevant QTLs is still missing. Results Here, we combined the power of 1125 fully sequenced inbred segregants with high-throughput phenotyping methods to identify as many as 678 QTLs across 18 different traits relevant to industrial fermentation processes, including production of ethanol, glycerol, isobutanol, acetic acid, sulfur dioxide, flavor-active esters, as well as resistance to ethanol, acetic acid, sulfite and high osmolarity. We identified and confirmed several variants that are associated with multiple different traits, indicating that many QTLs are pleiotropic. Moreover, we show that both rare and common variants, as well as variants located in coding and non-coding regions all contribute to the phenotypic variation. Conclusions Our findings represent an important step in our understanding of the genetic underpinnings of industrially relevant yeast traits and open new routes to study complex genetics and genetic interactions as well as to engineer novel, superior industrial yeasts. Moreover, the major role of rare variants suggests that there is a plethora of different combinations of mutations that can be explored in genome editing.