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bioRxiv2018

Kinetic analysis of yeast-yeast interactions in oenological conditions

Fermentation by microorganisms is a key step in the production of traditional food products such as bread, cheese, beer and wine. In these fermentative ecosystems, microorganisms interact in various ways, namely competition, predation, commensalism and mutualism. Traditional wine fermentation is a complex microbial process performed by Saccharomyces and non-Saccharomyces (NS) yeast species. To better understand the different interactions occurring within wine fermentation, isolated yeast cultures were compared with mixed co-cultures of one reference strain of S. cerevisiae with one strain of four NS yeast species (Metschnikowia pulcherrima, M. fructicola, Hanseniaspora opuntiae and H. uvarum). In each case, we studied population dynamics, resource consumed and metabolites produced from central carbon metabolism. This phenotyping of competition kinetics allowed us to confirm the main mechanisms of interaction between strains of four NS species. S. cerevisiae competed with H. uvarum and H. opuntiae for resources although both Hanseniaspora species were characterized by a strong mortality either in isolated or mixed fermentations. M. pulcherrima and M. fructicola displayed a negative interaction with the S. cerevisiae strain tested, with a decrease in viability in co-culture, probably due to iron depletion via the production of pulcherriminic acid. Overall, this work highlights the importance of measuring specific cell populations in mixed cultures and their metabolite kinetics to understand yeast-yeast interactions. These results are a first step towards ecological engineering and the rational design of optimal multi-species starter consortia using modeling tools. In particular the originality of this paper is for the first times to highlight the joint-effect of different species population dynamics on glycerol production and also to discuss on the putative role of lipid uptake on the limitation of some non-conventional species growth although interaction processes.

microbiology↗
bioRxiv2018

Delayed differentiation of vaginal and uterine microbiomes in dairy cows developing postpartum endometritis

Bacterial infection of the uterus is a normal event after parturition. While the healthy cow achieves uterine clearance early postpartum, cows unable to control the infection within 21 days after calving develop postpartum endometritis. Studies on the Microbial Ecology of the bovine reproductive tract have focused on either vaginal or uterine microbiomes. This is the first study that compares both microbiomes in the same animals. Terminal Restriction Fragment Length Polymorphism of the 16S rRNA gene showed that despite large differences associated to individuals, a shared community exist in vagina and uterus during the postpartum period. The largest changes associated with development of endometritis were observed at 7 days postpartum, a time when vaginal and uterine microbiomes were most similar. 16S rRNA Pyrosequencing of the vaginal microbiome at 7 days postpartum showed at least three different microbiome types that were associated with postpartum endometritis. All three microbiome types featured reduced bacterial diversity. Taken together, the above findings support a scenario where disruption of the compartmentalization of the reproductive tract during parturition results in the dispersal and mixing of the vaginal and uterine microbiomes, which subsequently are subject to differentiation. This microbial succession is likely associated to early clearance in the healthy cow. In contrast, loss of bacterial diversity and dominance of the microbiome by few bacterial taxa were related to a delayed succession in cows developing endometritis at 7 DPP.

microbiology↗
bioRxiv2018

Estimating recent migration and population size surfaces

In many species a fundamental feature of genetic diversity is that genetic similarity decays with geographic distance; however, this relationship is often complex, and may vary across space and time. Methods to uncover and visualize such relationships have widespread use for analyses in molecular ecology, conservation genetics, evolutionary genetics, and human genetics. While several frameworks exist, a promising approach is to infer maps of how migration rates vary across geographic space. Such maps could, in principle, be estimated across time to reveal the full complexity of population histories. Here, we take a step in this direction: we present a method to infer separate maps of population sizes and migration rates for different time periods from a matrix of genetic similarity between every pair of individuals. Specifically, genetic similarity is measured by counting the number of long segments of haplotype sharing (also known as identity-by-descent tracts). By varying the length of these segments we obtain parameter estimates for qualitatively different time periods. Using simulations, we show that the method can reveal time-varying migration rates and population sizes, including changes that are not detectable when ignoring haplotypic structure. We apply the method to a dataset of contemporary European individuals (POPRES), and provide an integrated analysis of recent population structure and growth over the last ~3,000 years in Europe. Software implementing the methods is available at https://github.com/halasadi/MAPS.

bioinformatics↗
bioRxiv2018

Fallen Pillars: The Past, Present, and Future Population Dynamics of a Rare, Specialist Coral-Algal Symbiosis

Rare and ecologically specialized species are at greater risk of extinction. Rarity in terms of low genotypic diversity may be obscured in sessile foundation species that can reproduce asexually. Asexual propagules are often only distinguishable from sexual recruits through molecular tools. Thus, molecular markers are necessary to assess genotypic variation and population structure in clonal organisms such as corals. The global decline of corals has necessitated marker development for improved conservation of rare coral species. We infer past demographic changes, describe modern population structure, and quantify asexual reproduction of the uncommon Caribbean pillar coral, Dendrogyra cylindrus and its endosymbiotic dinoflagellate, Symbiodinium dendrogyrum using de novo microsatellite markers. Results show that D. cylindrus comprises three distinct populations in the Caribbean whereas the symbiont was differentiated into four populations. Thus, barriers to gene flow differ between host and symbiont. In Florida, host and symbiont reproduced mainly asexually, yielding lower genotypic diversity than predicted from census size. Models of past demographic events revealed no evidence of historical changes in population size, consistent with the geological record of D. cylindrus indicating it has been rare for hundreds of thousands of years. The most recent global thermal stress event triggered a severe disease outbreak among D. cylindrus in Florida, resulting in a precipitous population decline. Projections indicate a high likelihood that this species may become locally extinct within the coming decades. The ecosystem consequences of losing rare coral species and their symbionts with increasingly frequent extreme warming events are not known but require urgent study.

genetics↗
bioRxiv2018

Unbiased whole genomes from mammalian feces using fluorescence-activated cell sorting

Ecological flexibility, extended lifespans, and large brains, have long intrigued evolutionary biologists, and comparative genomics offers an efficient and effective tool for generating new insights into the evolution of such traits. Studies of capuchin monkeys are particularly well situated to shed light on the selective pressures and genetic underpinnings of local adaptation to diverse habitats, longevity, and brain development. Distributed widely across Central and South America, they are inventive and extractive foragers, known for their sensorimotor intelligence. Capuchins have the largest relative brain size of any monkey and a lifespan that exceeds 50 years, despite their small (3-5 kg) body size. We assemble a de novo reference genome for Cebus imitator and provide the first genome annotation of a capuchin monkey. Through high-depth sequencing of DNA derived from blood, various tissues and feces via fluorescence activated cell sorting (fecalFACS) to isolate monkey epithelial cells, we compared genomes of capuchin populations from tropical dry forests and lowland rainforests and identified population divergence in genes involved in water balance, kidney function, and metabolism. Through a comparative genomics approach spanning a wide diversity of mammals, we identified genes under positive selection associated with longevity and brain development. Additionally, we provide a technological advancement in the use of non-invasive genomics for studies of free-ranging mammals. Our intra- and interspecific comparative study of capuchin genomics provides new insights into processes underlying local adaptation to diverse and physiologically challenging environments, as well as the molecular basis of brain evolution and longevity. SIGNIFICANCESurviving challenging environments, living long lives, and engaging in complex cognitive processes are hallmark characteristics of human evolution. Similar traits have evolved in parallel in capuchin monkeys, but their genetic underpinnings remain unexplored. We developed and annotated a reference assembly for white-faced capuchin monkeys to explore the evolution of these phenotypes. By comparing populations of capuchins inhabiting rainforest versus dry forests with seasonal droughts, we detected selection in genes associated with kidney function, muscular wasting, and metabolism, suggesting adaptation to periodic resource scarcity. When comparing capuchins to other mammals, we identified evidence of selection in multiple genes implicated in longevity and brain development. Our research was facilitated by our new method to generate high- and low-coverage genomes from non-invasive biomaterials.

genomics↗
bioRxiv2018

Do we predict upcoming speech content in naturalistic environments?

The ability to predict upcoming actions is a characteristic hallmark of cognition and therefore not surprisingly a central topic in cognitive science. It remains unclear, however, whether the predictive behaviour commonly observed in strictly controlled lab environments generalizes to rich, everyday settings. In four virtual reality experiments, we tested whether a well-established marker of linguistic prediction (i.e. anticipatory eye movements as observed in the visual world paradigm) replicated when increasing the naturalness of the paradigm by means of i) immersing participants in naturalistic everyday scenes, ii) increasing the number of distractor objects present, iii) manipulating the location of referents in central versus peripheral vision, and iv) modifying the proportion of predictable nounreferents in the experiment. Robust anticipatory eye movements were observed, even in the presence of 10 objects (hereby testing working memory) and when only 25% of all sentences contained a visually present referent (hereby testing error-based learning). The anticipatory effect disappeared, however, when referents were placed in peripheral vision. Together, our findings suggest that working memory may play an important role in predictive processing in everyday communication, but only in contexts where upcoming referents have been explicitly attended to prior to encountering the spoken referential act. Methodologically, our study confirms that ecological validity and experimental control may go hand in hand in future studies of human predictive behaviour.

neuroscience↗
bioRxiv2018

Genomic signatures of honey bee association in an acetic acid symbiont

Honey bee queens are central to the success and productivity of their colonies; queens are the only reproductive members of the colony, and therefore queen longevity and fecundity can directly impact overall colony health. Recent declines in the health of the honey bee have startled researchers and lay people alike as honey bees are agricultures most important pollinator. Honey bees are important pollinators of many major crops and add billions of dollars annually to the US economy through their services. One factor that may influence queen and colony health is the microbial community. Although honey bee worker guts have a characteristic community of bee-specific microbes, the honey bee queen digestive tracts are colonized by a few bacteria, notably an acetic acid bacterium not seen in worker guts: Bombella apis. This bacterium is related to flower-associated microbes such as Saccharibacter floricola and other species in the genus Saccharibacter, and initial phylogenetic analyses placed it as sister to these environmental bacteria. We used comparative genomics of multiple honey bee-associated strains and the nectar-associated Saccharibacter to identify genomic changes associated with the ecological transition to bee association. We identified several genomic differences in the honey bee-associated strains, including a complete CRISPR/Cas system. Many of the changes we note here are predicted to confer upon them the ability to survive in royal jelly and defend themselves against mobile elements, including phages. Our results are a first step towards identifying potential benefits provided by the honey bee queen microbiota to the colonys matriarch.

genomics↗
bioRxiv2018

Patterns of speciation and parallel genetic evolution under adaptation from standing variation

Adaptation often proceeds via the sorting of standing variation, and natural selection acting on pairs of populations is a quantitative continuum ranging from parallel to divergent. Yet, it is unclear how the extent of parallel genetic evolution during adaptation from standing variation is affected by the difference in the direction of selection between populations. Nor is it clear whether the availability of standing variation for adaptation affects progress toward speciation in a manner that depends on the difference in the direction of selection. We conducted a theoretical study investigating these questions and have two primary findings. First, the extent of parallel genetic evolution between two populations is expected to rapidly decline as the difference in their directions of selection increases from fully parallel toward divergent, and this decline occurs more rapidly in organisms with greater trait dimensionality. This rapid decline results because seemingly small differences in the direction of selection cause steep reductions in the fraction of alleles that are beneficial in both populations. For example, populations adapting to optima separated by an angle of 33{degrees} have only 50% of potentially beneficial alleles in common (for a case of five trait dimensions). Second, we find that adaptation from standing variation leads to higher ecologically-dependent hybrid fitness under parallel selection, relative to when adaptation is from new mutation only. This occurs because genetic parallelism based on standing variation reduces the phenotypic segregation variance in hybrids when parents adapt to similar environments. In contrast, under divergent selection, the pleiotropic effects of alternative alleles fixed from standing variation change the major axes of phenotypic variation in hybrids and reduce their fitness in parental habitats. We conclude that adaptation from standing genetic variation is expected to slow progress toward speciation via parallel natural selection and can facilitate progress toward speciation via divergent natural selection.\n\nImpact summaryIt is increasingly clear that much of adaptation, especially that which occurs rapidly, proceeds from the sorting of ancestral standing variation rather than complete reliance on de novo mutation. In addition, evolutionary biologists are increasingly embracing the fact that the difference in the direction of natural selection on pairs of populations is a quantitative continuum ranging from completely parallel to completely divergent. In this article, we ask two questions. First, how does the degree of genetic parallelism--here, adaptation using the same alleles in allopatric populations--depend on the differences in the direction of natural selection acting on two populations, from parallel (0{degrees}) to divergent (180{degrees})? And second, how does adaptation from standing variation affect progress toward speciation, and does its effect depend on the direction of natural selection? We develop theory to address these questions. We first find that very small differences in the direction of selection (angle) can largely preclude genetic parallelism. Second, we find that adaptation from standing variation has implications for speciation that change along the continuum from parallel to divergent selection. Under parallel selection, high genetic parallelism causes inter-population hybrids to have high mean fitness when their parents adapt from standing variation. As selection tends toward divergent, adaptation from standing variation is less beneficial for hybrid fitness and under completely divergent selection causes inter-population hybrids to have lower mean fitness than when adaptation was from new mutation alone. In sum, our results provide general insight into patterns of genetic parallelism and speciation along the continuum of parallel to divergent natural selection when adaptation is from standing variation.

evolutionary biology↗
bioRxiv2018

Expansion of a core regulon in specialized metabolism by mobile genetic elements promotes chemical diversity in Arabidopsis thaliana

Plants synthesize hundreds of thousands of ecologically specialized, lineage-specific metabolites through biosynthetic gene duplication and functional specialization. However, the rewiring of duplicated genes into existing regulatory networks remains unclear. We show that the duplicated gene CYP82C2 was recruited into the WRKY33 regulon and indole-3-carbonylnitrile (ICN) biosynthetic pathway through exaptation of a retroduplicated LINE retrotransposon (EPCOT3) into a novel enhancer. The stepwise development of a chromatin-accessible WRKY33-binding site on EPCOT3 potentiated the regulatory neofunctionalization of CYP82C2 and the evolution of inducible defense metabolite 4-hydroxy-ICN in Arabidopsis thaliana. Transposable elements (TEs) have long been recognized to have the potential to rewire regulatory networks; these results establish a more complete understanding of how duplicated genes and TEs contribute in concert to chemical diversity and pathogen defense.

evolutionary biology↗
bioRxiv2018

Exploration of plant biodiversity to investigate regulation of photosynthesis in natural environment

Photosynthesis is regulated in response to dynamic environmental conditions to satisfy plant metabolic demand but also to avoid over-excitation of the electron transport chain generating harmful reactive oxygen species. Photosynthetic organisms evolved several mechanisms to modulate light harvesting and electron transport efficiency to respond to conditions changing at different timescales, going from fast sun flecks to slow seasonal variations.\n\nThese regulatory mechanisms changed during evolution of photosynthetic organisms, also adapting to various ecological niches. The investigation of plant biodiversity is valuable to uncover conserved traits and plasticity of photosynthetic regulation. In this work a set of plants belonging to different genera of angiosperms, gymnosperms, ferns and lycophytes was investigated by monitoring their photosynthetic parameters in different seasons, looking for common trends and differences. In all plants analysed photosynthetic electron transport rate was found to be modulated by growth light intensity, ensuring a balance between available energy and photochemical capacity. Growth light also influenced the threshold where heat dissipation of excitation energy, also called Non-Photochemical Quenching (NPQ), was activated. On the contrary NPQ amplitude did not correlate with light intensity experienced by the plants but was a species-specific feature.\n\nNPQ zeaxanthin-dependent component, qZ, was found to be the most variable between different plants, modulating the intensity of the response but also the kinetic properties of its activation and relaxation. The slower NPQ component, qI, was instead found to be uncorrelated with photoinhibition eventually suffered by plants.

plant biology↗
bioRxiv2018

Diversification rates and phylogenies: what are we estimating, and how good are the estimates?

O_LISpecies-specific diversification rates, or \"tip rates\", can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology, and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait-dependent diversification studies. However, there is substantial confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics across simulated diversification scenarios.\nC_LIO_LIWe compared the statistical performance of three model-free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model-based approach (BAMM). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes; scenarios included multi-regime time-constant and diversity-dependent trees, as well as trees where the rate of speciation evolves under a diffusion process. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates.\nC_LIO_LIWe show decisively that model-free tip rate metrics provide a better estimate of the rate of speciation than of net diversification. Error in net diversification rate estimates increases as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Overall, and in particular when relative extinction was high, BAMM inferred the most accurate tip rates and exhibited lower error than non-model-based approaches. DR was highly correlated with true speciation rates but exhibited high error variance, and was the best metric for very small rate regimes.\nC_LIO_LIWe found that, of the metrics tested, DR and BAMM are the most useful metrics for studying speciation rate dynamics and trait-dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important.\nC_LI

evolutionary biology↗
bioRxiv2018

Modern wolves trace their origin to a late Pleistocene expansion from Beringia

Grey wolves (Canis lupus) are one of the few large terrestrial carnivores that maintained a wide geographic distribution across the Northern Hemisphere throughout the Pleistocene and Holocene. Recent genetic studies have suggested that, despite this continuous presence, major demographic changes occurred in wolf populations between the late Pleistocene and early Holocene, and that extant wolves trace their ancestry to a single late Pleistocene population. Both the geographic origin of this ancestral population and how it became widespread remain a mystery. Here we analyzed a large dataset of novel modern and ancient mitochondrial wolf genomes, spanning the last 50,000 years, using a spatially and temporally explicit modeling framework to show that contemporary wolf populations across the globe trace their ancestry to an expansion from Beringia at the end of the Last Glacial Maximum - a process most likely driven by the significant ecological changes that occurred across the Northern Hemisphere during this period. This study provides direct ancient genetic evidence that long-range migration has played an important role in the population history of a large carnivore and provides an insight into how wolves survived the wave of megafaunal extinctions at the end of the last glaciation. Moreover, because late Pleistocene grey wolves were the likely source from which all modern dogs trace their origins, the demographic history described in this study has fundamental implications for understanding the geographical origin of the dog.

evolutionary biology↗
bioRxiv2018

Assessing taxonomic metagenome profilers with OPAL

Taxonomic metagenome profilers predict the presence and relative abundance of microorganisms from shotgun sequence samples of DNA isolated directly from a microbial community. Over the past years, there has been an explosive growth of software and algorithms for this task, resulting in a need for more systematic comparisons of these methods based on relevant performance criteria. Here, we present OPAL, a software package implementing commonly used performance metrics, including those of the first challenge of the Initiative for the Critical Assessment of Metagenome Interpretation (CAMI), together with convenient visualizations. In addition, OPAL implements diversity metrics from microbial ecology, as well as run time and memory efficiency measurements. By allowing users to customize the relative importance of metrics, OPAL facilitates in-depth performance comparisons, as well as the development of new methods and data analysis workflows. To demonstrate the application, we compared seven profilers on benchmark datasets of the first and second CAMI challenges using all metrics and performance measurements available in OPAL. The software is implemented in Python 3 and available under the Apache 2.0 license on GitHub (https://github.com/CAMI-challenge/OPAL).\n\nAuthor summaryThere are many computational approaches for inferring the presence and relative abundance of taxa (i.e. taxonomic profiling) from shotgun metagenome samples of microbial communities, making systematic performance evaluations a very important task. However, there has yet to be introduced a computational framework in which profiler performances can be compared. This delays method development and applied studies, as researchers need to implement their own custom evaluation frameworks. Here, we present OPAL, a software package that facilitates standardized comparisons of taxonomic metagenome profilers. It implements a variety of performance metrics frequently employed in microbiome research, including runtime and memory usage, and generates comparison reports and visualizations. OPAL thus facilitates and accelerates benchmarking of taxonomic profiling techniques on ground truth data. This enables researchers to arrive at informed decisions about which computational techniques to use for specific datasets and research questions.

bioinformatics↗
bioRxiv2018

The soil microbial foodweb revisited with metatranscriptomics - predatory Myxobacteria as keystone taxon?

Trophic interactions in the microbial food web of soils are crucial for nutrient and carbon cycling. Traditionally, protozoa are considered the major micropredators of bacteria in soil. However, some prokaryotes, such as Myxobacteria and Bdellovibrio are also famous for bacterivorous life style. Until recently, it was impossible to assess the abundance of pro- and eukaryotic micropredators in soils simultaneously. Using a metatranscriptomic three-domain profiling of small subunit ribosomal RNA we investigated the abundance of bacterivores in 28 datasets from eleven European mineral and organic soils of different climatic zones. In all soils, Myxobacteria comprised a significant proportion from 4 - 19% of prokaryotic 16S rRNA transcripts and more than 60% of all bacterivores in most soils. Haliangiaceae and Polyangiaceae were most abundant, while the name-giving Myxococcaceae were barely present. Other bacterial predators like Bdellovibrio were low abundant. Also Protozoan micropredator 18S rRNA transcripts, e.g. from Cercozoa, Amoebozoa and Ciliophora, were on average less abundant, especially in mineral soils. Nematodes were even less abundant. In addition, we applied a longitudinal approach to identify bacterivores during beech litter colonisation. Here, Myxobacteria showed prey-dependent, protozoa-like community dynamics during colonisation. Thus, their broad prey range and high abundance suggests a major influence of Myxobacteria on structuring the prokaryotic community composition in soil, and might warrant their classification as keystone taxon. Our results suggest the presence of an ecologically important \"bacterial loop\" in soil food webs, independent of protozoa and nematodes.

microbiology↗
bioRxiv2018

Fast and general-purpose linear mixed models for genome-wide genetics

Linear mixed effect models are powerful tools used to account for population structure in genome-wide association studies (GWASs) and estimate the genetic architecture of complex traits. However, fully-specified models are computationally demanding and common simplifications often lead to reduced power or biased inference. We describe Grid-LMM (https://github.com/deruncie/GridLMM), an extendable algorithm for repeatedly fitting complex linear models that account for multiple sources of heterogeneity, such as additive and non-additive genetic variance, spatial heterogeneity, and genotype-environment interactions. Grid-LMM can compute approximate (yet highly accurate) frequentist test statistics or Bayesian posterior summaries at a genome-wide scale in a fraction of the time compared to existing general-purpose methods. We apply Grid-LMM to two types of quantitative genetic analyses. The first is focused on accounting for spatial variability and non-additive genetic variance while scanning for QTL; and the second aims to identify gene expression traits affected by non-additive genetic variation. In both cases, modeling multiple sources of heterogeneity leads to new discoveries.\n\nAuthor summaryThe goal of quantitative genetics is to characterize the relationship between genetic variation and variation in quantitative traits such as height, productivity, or disease susceptibility. A statistical method known as the linear mixed effect model has been critical to the development of quantitative genetics. First applied to animal breeding, this model now forms the basis of a wide-range of modern genomic analyses including genome-wide associations, polygenic modeling, and genomic prediction. The same model is also widely used in ecology, evolutionary genetics, social sciences, and many other fields. Mixed models are frequently multi-faceted, which is necessary for accurately modeling data that is generated from complex experimental designs. However, most genomic applications use only the simplest form of linear mixed methods because the computational demands for model fitting can be too great. We develop a flexible approach for fitting linear mixed models to genome scale data that greatly reduces their computational burden and provides flexibility for users to choose the best statistical paradigm for their data analysis. We demonstrate improved accuracy for genetic association tests, increased power to discover causal genetic variants, and the ability to provide accurate summaries of model uncertainty using both simulated and real data examples.

genomics↗
bioRxiv2018

The landscape of coadaptation in Vibrio parahaemolyticus

Investigating fitness interactions in natural populations remains a considerable challenge. We take advantage of the unique population structure of Vibrio parahaemolyticus, a bacterial pathogen of humans and shrimp, to perform a genome-wide screen for coadapted genetic elements. We identified 90 interaction groups involving 1,560 coding genes. 82 of these interaction groups are between accessory genes, many of which have functions related to carbohydrate transport and metabolism. Only 8 interaction groups involve both core and accessory genomes. The largest includes 1,540 SNPs in 82 genes and 338 accessory genome elements, many involved in lateral flagella and cell wall biogenesis. The interactions have a complex hierarchical structure encoding at least four distinct ecological strategies. Preliminary experiments imply that the strategies influence biofilm formation and bacterial growth rate in vitro. One strategy involves a divergent profile in multiple genome regions, implying that strains have irreversibly specialized, while the others involve fewer genes and are more plastic. Our results imply that most genetic alliances are ephemeral but that increasingly complex strategies can evolve and eventually cause speciation.

microbiology↗
bioRxiv2018

Asgard archaea are diverse, ubiquitous, and transcriptionally active microbes

Asgard is a newly proposed archaeal superphylum. Phylogenetic position of Asgard archaea and its relationships to the origin of eukaryotes is attracting increasingly research interest. However, in-depth knowledge of their diversity, distribution, and activity of Asgard archaea remains limited. Here, we used phylogenetic analysis to cluster the publicly available Asgard archaeal 16S rRNA gene sequences into 13 subgroups, including five previously unknown subgroups. These lineages were widely distributed in anaerobic environments, with the majority of 16S rRNA gene sequences (92%) originating from sediment habitats. Co-occurrence analysis revealed potential relationships between Asgard, Bathyarchaeota, and Marine Benthic Group D archaea. Genomic analysis suggested that Asgard archaea are potentially mixotrophic microbes with divergent metabolic capabilities. Importantly, metatranscriptomics confirmed the versatile lifestyles of Lokiarchaeota and Thorarchaeota, which can fix CO2 using the tetrahydromethanopterin Wood-Ljungdahl pathway, perform acetogenesis, and degrade organic matters. Overall, this study broadens the understandings of Asgard archaea ecology, and also provides the first evidence to support a transcriptionally active mixotrophic lifestyle of Asgard archaea, shedding light on the potential roles of these microorganisms in the global biogeochemical cycling.

microbiology↗
bioRxiv2018

SMRT long-read sequencing and Direct Label and Stain optical maps allow the generation of a high-quality genome assembly for the European barn swallow (Hirundo rustica rustica)

BackgroundThe barn swallow (Hirundo rustica) is a migratory bird that has been the focus of a large number of ecological, behavioural and genetic studies. To facilitate further population genetics and genomic studies, here we present a reference genome assembly for the European subspecies (H. r. rustica).\n\nFindingsAs part of the Genome10K (G10K) effort on generating high quality vertebrate genomes, we have assembled a highly contiguous genome assembly using Single Molecule Real-Time (SMRT) DNA sequencing and several Bionano optical map technologies. We compared and integrated optical maps derived both from the Nick, Label, Repair and Stain and from the Direct Label and Stain (DLS) technologies. As proposed by Bionano, the DLS more than doubled the scaffold N50 with respect to the nickase. The dual enzyme hybrid scaffold led to a further marginal increase in scaffold N50 and an overall increase of confidence in the scaffolds. After removal of haplotigs, the final assembly is approximately 1.21 Gbp in size, with a scaffold N50 value of over 25.95 Mbp.\n\nConclusionsThis high-quality genome assembly represents a valuable resource for further studies of population genetics and genomics in the barn swallow, and for studies concerning the evolution of avian genomes. It also represents one of the very first genomes assembled by combining SMRT long-read sequencing with the new Bionano DLS technology for scaffolding. The quality of this assembly demonstrates the potential of this methodology to substantially increase the contiguity of genome assemblies.

genomics↗