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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2018

Collective search with finite perception: transient dynamics and search efficiency

Motile organisms often use finite spatial perception of their surroundings to navigate and search their habitats. Yet standard models of search are usually based on purely local sensory information. To model how a finite perceptual horizon affects ecological search, we propose a framework for optimal navigation that combines concepts from random walks and optimal control theory. We show that, while local strategies are optimal on asymptotically long and short search times, finite perception yields faster convergence and increased search efficiency over transient time scales relevant in biological systems. The benefit of the finite horizon can be maintained by the searchers tuning their response sensitivity to the length scale of the stimulant in the environment, and is enhanced when the agents interact as a result of increased consensus within subpopulations. Our framework sheds light on the role of spatial perception and transients in search movement and collective sensing of the environment.

biophysics↗
bioRxiv2018

Genomic sequence capture of haemosporidian parasites: Methods and prospects for enhanced study of host-parasite evolution

Avian malaria and related haemosporidians (Plasmodium, [Para]Haemoproteus, and Leucocytoozoon) represent an exciting multi-host, multi-parasite system in ecology and evolution. Global research in this field accelerated after 1) the publication in 2000 of PCR protocols to sequence a haemosporidian mitochondrial (mtDNA) barcode, and 2) the development in 2009 of an open-access database to document the geographic and host ranges of parasite mtDNA haplotypes. Isolating haemosporidian nuclear DNA from bird hosts, however, has been technically challenging, slowing the transition to genomic-scale sequencing techniques. We extend a recently-developed sequence capture method to obtain hundreds of haemosporidian nuclear loci from wild bird samples, which typically have low levels of infection, or parasitemia. We tested 51 infected birds from Peru and New Mexico and evaluated locus recovery in light of variation in parasitemia, divergence from reference sequences, and pooling strategies. Our method was successful for samples with parasitemia as low as [~]0.03% (3 of 10,000 blood cells infected) and mtDNA divergence as high as 15.9% (one Leucocytozoon sample), and using the most cost-effective pooling strategy tested. Phylogenetic relationships estimated with >300 nuclear loci were well resolved, providing substantial improvement over the mtDNA barcode. We provide protocols for sample preparation and sequence capture including custom probe kit sequences, and describe our bioinformatics pipeline using aTRAM 2.0, PHYLUCE, and custom Perl and Python scripts. This approach can be applied to the tens of thousands of avian samples that have already been screened for haemosporidians, and greatly improve our understanding of parasite speciation, biogeography, and evolutionary dynamics.

genomics↗
bioRxiv2018

Characteristics of a SAR11 strain grown in batch and continuous culture

In this study, a strain of SAR11 subgroup IIIa (termed HIMB114) isolated from the tropical Pacific Ocean was grown in seawater-based batch and continuous culture in order to quantify cellular features and metabolism relevant to SAR11 ecology. We report the first direct measurements of cellular elemental quotas for nitrogen (N) and phosphorus (P) for SAR11: 1.4 {+/-} 0.9 fg N and 0.44 {+/-} 0.01 fg P, respectively, that were consistent with the small size of HIMB114 cells (average volume of 0.09 {micro}m3). However, the mean carbon (C) cellular quota of 50 {+/-} 47 fg C was anomalously high, but variable. Rates of phosphate (PO43-) uptake measured from both batch and continuous cultures were exceptionally slow: in chemostats growing at 0.3 d-1, HIMB114 took up 1.1 {+/-} 0.3 amol P cell-1 d-1, suggesting that <30% of the cellular P requirement of HIMB114 was met by PO43- assimilation. The mean rate of leucine incorporation, a measure of bacterial production, during late log phase growth of batch HIMB114 cultures was 0.042 {+/-} 0.02 amol Leu cell-1 h-1. While only weakly correlated with changes in specific growth rates, the onset of stationary phase resulted in decreases in cell-specific leucine incorporation that were proportional to changes in growth rate. Rates of cellular production, respiratory oxygen consumption, and changes in total organic C concentrations constrained cellular growth efficiencies to 13 {+/-} 4%. Hence, despite the small, streamlined genome and diminutively sized cells, SAR11 strain HIMB114 appears to grow at efficiencies similar to naturally occurring bacterioplankton communities.\n\nImportanceWhile SAR11 bacteria contribute a significant fraction to the total picoplankton biomass in the ocean and likely are major players in organic C and nutrient cycling, the cellular characteristics and metabolic features of most lineages have either been only hypothesized from genomes or otherwise not measured in controlled laboratory experimentation. The dearth of data on even the most basic characteristics for what is arguably the most abundant heterotroph in seawater has limited the specific consideration of SAR11 in ocean ecosystem modeling efforts. In this study, we provide measures of cellular P, N, C, aerobic respiration and bacterial production for a SAR11 strain growing in natural seawater media that can be used to directly relate these features of SAR11 to biogeochemical cycling in the oceans. Through the development of a chemostat system to measure nutrient uptake during steady-state growth, we have also documented inorganic P uptake rates that allude to the importance of organic phosphorous to meet cellular P demands, even in the presence of non-limiting PO43- concentrations.

microbiology↗
bioRxiv2018

Precision weighting of musical prediction error: converging neurophysiological and behavioral evidence

Theories of predictive processing propose that prediction error responses are modulated by the certainty of the predictive model or precision. While there is some evidence for this phenomenon in the visual and, to a lesser extent, the auditory modality, little is known about whether it operates in the complex auditory contexts of daily life. Here, we examined how prediction error responses behave in a more complex and ecologically valid auditory context than those typically studied. We created musical tone sequences with different degrees of pitch uncertainty to manipulate the precision of participants auditory expectations. Magnetoencephalography was used to measure the magnetic counterpart of the mismatch negativity (MMNm) as a neural marker of prediction error in a multi-feature paradigm. Pitch, slide, intensity and timbre deviants were included. We compared high-entropy stimuli, consisting of a set of non-repetitive melodies, with low-entropy stimuli consisting of a simple, repetitive pitch pattern. Pitch entropy was quantitatively assessed with an information-theoretic model of auditory expectation. We found a reduction in pitch and slide MMNm amplitudes in the high-entropy as compared to the low-entropy context. No significant differences were found for intensity and timbre MMNm amplitudes. Furthermore, in a separate behavioral experiment investigating the detection of pitch deviants, similar decreases were found for accuracy measures in response to more fine-grained increases in pitch entropy. Our results are consistent with a precision modulation of auditory prediction error in a musical context, and suggest that this effect is specific to features that depend on the manipulated dimension--pitch information, in this case.\n\nHighlightsO_LIThe mismatch negativity (MMNm) is reduced in musical contexts with high pitch uncertainty\nC_LIO_LIThe MMNm reduction is restricted to pitch-related features\nC_LIO_LIAccuracy during deviance detection is reduced in contexts with higher uncertainty\nC_LIO_LIThe results suggest a feature-selective precision modulation of prediction error\nC_LI\n\nMaterials, data and scripts can be found in the Open Science Framework repository: http://bit.ly/music_entropy_MMN\n\nDOI: 10.17605/OSF.IO/MY6TE

neuroscience↗
bioRxiv2018

Strategies of host resistance to pathogens in spatially structured populations: An agent-based evaluation.

There is growing theoretical evidence that spatial structure can affect the ecological and evolutionary outcomes of host-parasite interactions. Locally restricted interactions have been shown in particular to affect host resistance and tolerance. In this study we investigate the evolution of several types of host disease resistance strategies, alone or in combination, in spatially structured populations. We construct a spatially explicit, individual-based stochastic model where hosts and parasites interact with each other in a spatial lattice, and interactions are restricted to a given neighbourhood of varying size. We investigate several host resistance strategies, including constitutive (expressed in all resistant hosts), induced (expressed only upon infection), and combinations thereof. We show that the specific resistance mechanism against a pathogen as well as the size of the neighbourhood both affect resistance spread and parasite dynamics, an effect modulated by the level of the cost of resistance. Our results shed new light on the dynamics of disease resistance in a spatially-structured host-pathogen system, and illustrate the conditions in which a variety of resistance mechanisms can be maintained, including when they are costly. Overall these results advance our theoretical understanding of the evolutionary dynamics of disease resistance, a necessary step to elaborate more efficient and sustainable strategies for disease management.

evolutionary biology↗
bioRxiv2018

Detection of adaptive divergence in populations of the stream mayfly Ephemera strigata with machine learning

Adaptive divergence is a key mechanism shaping the genetic variation of natural populations. A central question linking ecology with evolutionary biology concerns the role of environmental heterogeneity in determining adaptive divergence among local populations within a species. In this study, we examined adaptive the divergence among populations of the stream mayfly Ephemera strigata in the Natori River Basin in northeastern Japan. We used a genome scanning approach to detect candidate loci under selection and then applied a machine learning method (i.e. Random Forest) and traditional distance-based redundancy analysis (dbRDA) to examine relationships between environmental factors and adaptive divergence at non-neutral loci. We also assessed spatial autocorrelation at neutral loci to quantify the dispersal ability of E. strigata. Our main findings were as follows: 1) random forest shows a higher resolution than traditional statistical analysis for detecting adaptive divergence; 2) separating markers into neutral and non-neutral loci provides insights into genetic diversity, local adaptation and dispersal ability and 3) E. strigata shows altitudinal adaptive divergence among the populations in the Natori River Basin.

evolutionary biology↗
bioRxiv2018

Flavor-Cyber-Agriculture: Optimization of plant metabolites in an open-source control environment through surrogate modeling

Food production in conventional agriculture faces numerous challenges such as reducing waste, meeting demand, maintaining flavor, and providing nutrition. Contained environments under artificial climate control, or cyber-agriculture, could in principle be used to meet many of these challenges. Through such environments, phenotypic expression of the plant---mass, edible yield, flavor, and nutrients---can be actuated through a "climate recipe," where light, water, nutrients, temperature, and other climate and ecological variables are optimized to achieve a desired result. This paper describes a method for doing this optimization for the desired result of flavor by combining cyber-agriculture, metabolomic phenotype (chemotype) measurements, and machine learning. In a pilot experiment, (1) environmental conditions, i.e. photoperiod and ultraviolet (UV) light (known to affect production of flavor-active molecules in edible plants) were applied under different regimes to basil plants (Ocimum basilicum) growing inside a hydroponic farm with an open-source design; (2) flavor-active volatile molecules were measured in each plant using gas chromatography-mass spectrometry (GC-MS); and (3) symbolic regression was used to construct a surrogate model of this chemistry from the input environmental variables, and this model was used to discover new combinations of photoperiod and UV light to increase this chemistry. These new combinations, or climate recipes, were then implemented in the hydroponic farm, and several of them resulted in a marked increase in volatiles over control. The process also led to two important insights: it demonstrated a "dilution effect", i.e. a negative correlation between weight and desirable chemical species, and it discovered the surprising effect that a 24-hour photoperiod of photosynthetic-active radiation, the equivalent of all-day light, induces the most flavor molecule production in basil. In this manner, surrogate optimization through machine learning can be used to discover effective recipes for cyber-agriculture that would be difficult and time-consuming to find using hand-designed experiments.

plant biology↗
bioRxiv2018

Inducible Cooperation in a Synthetic Gut Bacterial Consortium Introduces Population Balance and Stability

In nature, microbes interact antagonistically, neutrally or beneficially. To shed light on the effects of positive interactions in microbial consortia we introduced metabolic dependencies and metabolite overproduction into four bacterial species. While antagonistic interactions govern the wildtype consortium behavior, the genetic modifications alleviated antagonistic interactions and resulted in beneficial interactions. Engineered cross-feeding increased population evenness, a component of ecological diversity, in different environments including in a more complex gnotobiotic mouse gut environment. Our findings suggest that metabolite cross-feeding could be used as a tool for intentionally shaping microbial consortia in complex environments.\n\nImportanceMicrobial communities are ubiquitous in nature. Bacterial consortia live in and on our body and in our environment and more recently, biotechnology is applying microbial consortia for bioproduction. As part of our body, bacterial consortia influence us in health and disease. Microbial consortia function is determined by its composition, which in turn is driven by the interactions between species. Further understanding of microbial interactions will help us deciphering how consortia function in complex environments and may enable us to modify microbial consortia for health and environmental benefits.

synthetic biology↗
bioRxiv2018

Mosaic Plasmids are Abundant and Unevenly Distributed Across Prokaryotic Taxa.

Mosaic plasmids, plasmids composed of genetic elements from distinct sources, are associated with the spread of antibiotic resistance genes. Transposons are considered the primary mechanism for mosaic plasmid formation, though other mechanisms have been observed in specific instances. The frequency with which mosaic plasmids have been described suggests they may play an important role in plasmid population dynamics. Our survey of the confirmed plasmid sequences available from complete and draft genomes in the RefSeq database shows that 46% of them fit a strict definition of mosaic. Mosaic plasmids are also not evenly distributed over the taxa represented in the database. Plasmids from some genera, including Piscirickettsia and Yersinia, are almost all mosaic, while plasmids from other genera, including Borrelia, are rarely mosaic. While some mosaic plasmids share identical regions with hundreds of others, the median mosaic plasmid only shares with 8 other plasmids.\n\nWhen considering only plasmids from finished genomes (51.6% of the total), mosaic plasmids have significantly higher proportions of transposases and antibiotic resistance genes. Conversely, only 56.6% of mosaic fragments (DNA fragments shared between mosaic plasmids) contain a recognizable transposase, and only 1.2% of mosaic fragments are flanked by inverted repeats. Mosaic fragments associated with the IS26 transposase are 3.8-fold more abundant than any other sequence shared between mosaic plasmids in the database, though this is at least partly due to overrepresentation of Enterobacteriaceae plasmids.\n\nMosaic plasmids are a complicated trait of some plasmid populations, only partly explained by transposition. Though antibiotic resistance genes led to the identification of many mosaic plasmids, mosaic plasmids are a broad phenomenon encompassing many more traits than just antibiotic resistance. Further research will be required to determine the influence of ecology, host repair mechanisms, conjugation, and plasmid host range on the formation and influence of mosaic plasmids.\n\nAuthor SummaryPlasmids are extrachromosomal genetic entities that are found in many prokaryotes. They serve as flexible storage for genes, and individual cells can make substantial changes to their characteristics by acquiring, losing, or modifying a plasmid. In some pathogenic bacteria, such as Escherichia coli, antibiotic resistance genes are known to spread primarily on plasmids. By analyzing a database of 8,592 plasmid sequences we determined that many of these plasmids have exchanged genes with each other, becoming mosaics of genes from different sources. We next separated these plasmids into groups based on the organism they were isolated from and found that different groups had different fractions of mosaic plasmids. This result was unexpected and suggests that the mechanisms and selective pressures causing mosaic plasmids do not occur evenly over all species. It also suggests that plasmids may provide different levels of potential variation to different species. This work uncovers a previously unrecognized pattern in plasmids across prokaryotes, that could lead to new insights into the evolutionary role that plasmids play.

microbiology↗
bioRxiv2018

Mechanistic basis for the evolution of chalcone synthase catalytic cysteine reactivity in land plants

Flavonoids are important polyphenolic natural products, ubiquitous in land plants, that play diverse functions in plants survival in their ecological niches, including UV protection, pigmentation for attracting pollinators, symbiotic nitrogen fixation, and defense against herbivores. Chalcone synthase (CHS) catalyzes the first committed step in plant flavonoid biosynthesis and is highly conserved in all land plants. In several previously reported crystal structures of flowering plant CHSs, the catalytic cysteine is oxidized to sulfinic acid, indicating enhanced nucleophilicity in this residue associated with its increased susceptibility to oxidation. In this study, we report a set of new crystal structures of CHSs representing all five major lineages of land plants. We reveal that the structures of CHS from a lycophyte and a moss species preserve the catalytic cysteine in a reduced state, in contrast to the cysteine sulfinic acid seen in all euphyllophyte CHS structures. In vivo complementation, in vitro biochemical and mutagenesis analyses, as well as molecular dynamics simulations identify a set of residues that differ between basal-plant and euphyllophyte CHSs and modulate catalytic cysteine reactivity. We propose that the CHS active-site environment has evolved in euphyllophytes to further enhance the nucleophilicity of the catalytic cysteine since the divergence of euphyllophytes from other vascular plant lineages 400 million years ago. These changes in CHS could have contributed to the diversification of flavonoid biosynthesis in euphyllophytes, which in turn contributed to their dominance in terrestrial ecosystems.

biochemistry↗
bioRxiv2018

Application of long read sequencing to determine expressed antigen diversity in Trypanosoma brucei infections

AO_SCPLOWBSTRACTC_SCPLOWAntigenic variation is employed by many pathogens to evade the host immune response, and Trypanosoma brucei has evolved a complex system to achieve this phenotype, involving sequential use of variant surface glycoprotein (VSG) genes encoded from a large repertoire of [~]2,000 alleles. T. brucei express multiple, sometimes closely related, VSGs in a population at any one time, and the ability to resolve and analyse this diversity has been limited. We applied long read sequencing (PacBio) to VSG amplicons generated from blood extracted from batches of mice sacrificed at time points (days 3, 6, 10 and 12) post-infection with T. brucei TREU927. The data showed that long read sequencing is reliable for resolving allelic differences between VSGs, and demonstrated that there is significant expressed diversity (449 VSGs detected across 20 mice) and across the timeframe of study there was a clear semi-reproducible pattern of expressed diversity (median of 27 VSGs per sample at day 3 post infection (p.i.), 82 VSGs at day 6 p.i., 187 VSGs at day 10 p.i. and 132 VSGs by day 12 p.i.). There was also consistent detection of one VSG dominating expression across replicates at days 3 and 6, and emergence of a second dominant VSG across replicates by day 12. The innovative application of ecological diversity analysis to VSG reads enabled characterisation of hierarchical VSG expression in the dataset, and resulted in a novel method for analysing such patterns of variation. Additionally, the long read approach allowed detection of mosaic VSG expression from very few reads - this was observed as early as day 3, the earliest that such events have been detected. Therefore, our results indicate that long read analysis is a reliable tool for resolving diverse allele expression profiles, and provides novel insights into the complexity and nature of VSG expression in trypanosomes, revealing significantly higher diversity than previously shown and identifying mosaic gene formation unprecedentedly early during the infection process.

genomics↗
bioRxiv2018

USE: An integrative suite for temporally-precise psychophysical experiments in virtual environments

11.1 BackgroundThere is a growing interest in complex, active, and immersive behavioral neuroscience tasks. However, the development and control of such tasks present unique challenges.\n\n1.2 New MethodThe Unified Suite for Experiments (USE) is an integrated set of hardware and software tools for the design and control of behavioral neuroscience experiments. The software, developed using the Unity video game engine, supports both active tasks in immersive 3D environments and static 2D tasks used in more traditional visual experiments. The custom USE SyncBox hardware, based around an Arduino Mega2560 board, integrates and synchronizes multiple data streams from different pieces of experimental hardware. The suite addresses three key issues with developing cognitive neuroscience experiments in Unity: tight experimental control, accurate sub-ms timing, and accurate gaze target identification.\n\n1.3 ResultsUSE is a flexible framework to realize experiments, enabling (i) nested control over complex tasks, (ii) flexible use of 3D or 2D scenes and objects, (iii) touchscreen-, button-, joystick- and gaze-based interaction, and (v) complete offline reconstruction of experiments for post-processing and temporal alignment of data streams.\n\n1.4 Comparison with Existing MethodsMost existing experiment-creation tools are not designed to support the development of video-game-like tasks. Those that do use older or less popular video game engines as their base, and are not as feature-rich or enable as precise control over timing as USE.\n\n1.5 ConclusionsUSE provides an integrated, open source framework for a wide variety of active behavioral neuroscience experiments using human and nonhuman participants, and artificially-intelligent agents.\n\n2 GlossaryO_LIActive task: Experimental tasks which involve some combination of realistic, usually moving, stimuli, continuous opportunities for action, ecologically valid tasks, complex behaviours, etc. Here, they are contrasted with static tasks (see below)\nC_LIO_LIArduino: A multi-purpose generic micro-processor, here used to control inter-device communication and time synchronization.\nC_LIO_LIRaycast: A game-engine method that sends a vector between two points in a virtual three-dimensional environment, and returns the first object in that environment it hits. Often used to determine if a character in a game can see or shoot another character.\nC_LIO_LIState Machine (also Finite State Machine): A way of conceptualizing and implementing control in software, such that at any one moment the software is in one, and only one, state. In hierarchical state machines, as used in the present software suite, these can be organized into different levels, such that each level can only be in one state, but a state can pass control to a lower level.\nC_LIO_LIStatic task: Experimental tasks like those traditionally used in the cognitive neurosciences. Simple, usually stationary, stimuli, limited opportunities for action, simple behaviours, etc. Here, they are contrasted with active tasks (see above).\nC_LIO_LIUnity: One of the most popular video game engines. Freely available.\nC_LIO_LIVideo game engine: A software development kit designed to handle many of the common issues involved in creating video games, such as interfacing with controllers, simulating physical collisions and lighting, etc.\nC_LI

neuroscience↗
bioRxiv2018

The first draft genomes of the ant Formica exsecta, and its Wolbachia endosymbiont reveal extensive gene transfer from endosymbiont to host.

The wood ant Formica exsecta (Formicidae; Hymenoptera), is a common ant species throughout the Palearctic region. The species is a well established model for studies of ecological characteristics and evolutionary conflict. In this study, we sequenced and assembled draft genomes for Formica exsecta and its endosymbiont Wolbachia. The draft F. exsecta genome is 277.7 Mb long; we identify 13,767 protein coding genes for which we provide gene ontology, and protein domain annotations. This is also the first report of a Wolbachia genome from ants, and provides insights into the phylogenetic position of this endosymbiont. We also identified multiple horizontal gene transfer events (HGTs) from Wolbachia to F. exsecta. Some of these HGTs have also occurred in parallel in multiple other insect genomes, highlighting the extent of HGTs in eukaryotes. We expect that the F. exsecta genome will be valuable resource in further exploration of the molecular basis of the evolution of social organization.

genomics↗
bioRxiv2018

Genome-wide disruption of DNA methylation by 5-aza-2’-deoxycytidine in the parasitioid wasp Nasonia vitripennis

DNA methylation of cytosine residues across the genome influences how genes and phenotypes are regulated in a wide range of organisms. As such, understanding the role of DNA methylation and other epigenetic mechanisms has become very much a part of mapping genotype to phenotype, a major question in evolutionary biology. Ideally, we would like to manipulate DNA methylation patterns on a genome-wide scale, to help us to elucidate the role that epigenetic modifications play in phenotypic expression. Recently, the demethylating agent 5-aza-2-deoxycytidine (5-aza-dC; commonly used in the epigenetic treatment of certain cancers), has been deployed to explore the epigenetic regulation of a number of traits of interest to evolutionary ecologists, including facultative sex allocation in the parasitoid wasp Nasonia vitripennis. In a recent study, we showed that treatment with 5-aza-dC did not ablate the facultative sex allocation response in Nasonia, but shifted the patterns of sex allocation in a way predicted by genomic conflict theory. This was the first (albeit indirect) experimental evidence for genomic conflict over sex allocation facilitated by DNA methylation. However, that work lacked direct evidence of the effects of 5-aza-dC on DNA methylation, and indeed the effect of the chemical has since been questioned in Nasonia. Here, using whole-genome bisulphite sequencing of more than 4 million CpGs, across more than 11,000 genes, we demonstrate unequivocally that 5-aza-dC disrupts methylation on a large scale across the Nasonia vitripennis genome. We show that the disruption can lead to both hypo- and hyper-methylation, may vary across tissues and time of sampling, and that the effects of 5-aza-dC are context- and sequence specific. We conclude that 5-aza-dC does indeed have the potential to be repurposed as a tool for studying the role of DNA methylation in evolutionary ecology, whilst many details of its action remain to be discovered. Author SummaryShedding light on the mechanistic basis of phenotypes is a major aim in the field of evolutionary biology. If we understand how phenotypes are controlled at the molecular level, we can begin to understand how evolution has shaped that phenotype and conversely, how genetic architecture may constrain trait evolution. Epigenetic markers (such as DNA methylation) also influence phenotypic expression by regulating how and when genes are expressed. Recently, 5-aza-2-deoxycytidine (5-aza-dC), a hypomethylating agent used in the treatment of certain cancers, has been used to explore the epigenetic regulation of traits of interest to evolutionary ecologists. Previously, we used 5-aza-dC to validate a role for DNA methylation in facultative sex allocation behaviour in the parasitoid wasp Nasonia vitripennis. However, the direct effects of the chemical were not examined at that point and its efficacy in insects was questioned. Here, we demonstrate that 5-aza-dC disrupts DNA methylation on a genome-wide scale in a context- and sequence-specific manner and results in both hypo- and hyper-methylation. Our work demonstrates that 5-aza-dC has the potential to be repurposed as a tool for studying the role of DNA methylation in phenotypic expression.

evolutionary biology↗
bioRxiv2018

Optimised DNA extraction and library preparation for minute arthropods: application to target enrichment in chalcid wasps used for biocontrol.

Enriching subsets of the genome prior to sequencing allows focusing effort on regions that are relevant to answer specific questions. As experimental design can be adapted to sequence many samples simultaneously, using such approach also contributes to reduce cost. In the field of ecology and evolution, target enrichment is increasingly used for genotyping of plant and animal species or to better understand the evolutionary history of important lineages through the inference of statistically robust phylogenies. Limitations to routine target enrichment by research laboratories are both the complexity of current protocols and low input DNA quantity. Thus, working with tiny organisms such as micro-arthropods can be challenging. Here, we propose easy to set up optimisations for DNA extraction and library preparation prior to target enrichment. Prepared libraries were used to capture 1432 Ultra-Conserved Elements (UCEs) from microhymenoptera (Chalcidoidea), which are among the tiniest insects on Earth and the most commercialized worldwide for biological control purposes. Results show no correlation between input DNA quantities (1.8-250ng, 0.4 ng with an extra whole genome amplification step) and the number of sequenced UCEs. Phylogenetic inferences highlight the potential of UCEs to solve relationships within the families of chalcid wasps, which has not been achieved so far. The protocol (library preparation + target enrichment), allows processing 96 specimens in five working days, by a single person, without requiring the use of expensive robotic molecular biology platforms, which could help to generalize the use of target enrichment for minute specimens.

evolutionary biology↗
bioRxiv2018

Disease mortality in domesticated animals is predicted by host evolutionary relationships

Infectious diseases of domesticated animals impact human well-being via food insecurity, loss of livelihoods, and human infections. While much research has focused on parasites that infect single host species, most parasites of domesticated mammals infect multiple species. The impact of multi-host parasites varies across hosts; some rarely result in death, whereas others are nearly always fatal. Despite their high ecological and societal costs, we currently lack theory for predicting the lethality of multi-host parasites. Here, using a global dataset of over 4000 case-fatality rates for 65 infectious diseases (caused by micro and macro-parasites) and 12 domesticated host species, we show that the average evolutionary distance from an infected host to other mammal host species is a strong predictor of disease-induced mortality. We find that as parasites infect species outside of their documented phy-1 logenetic host range, they are more likely to result in lethal infections, with the odds of death doubling for each additional 10 million years of evolutionary distance. Our results for domesticated animal diseases reveal patterns in the evolution of highly lethal parasites that are difficult to observe in the wild, and further suggest that the severity of infectious diseases may be predicted from evolutionary relationships among hosts.

evolutionary biology↗
bioRxiv2018

Aggression and discrimination among closely versus distantly related species of Drosophila

Fighting between different species is widespread in the animal kingdom, yet this phenomenon has been relatively understudied in the field of aggression research. Particularly lacking are studies that test the effect of genetic distance, or relatedness, on aggressive behavior between species. Here we characterized male-male aggression within and between species of fruit flies across the Drosophila phylogeny. We show that male Drosophila discriminate between conspecifics and heterospecifics and show a bias for the target of aggression that depends on the genetic relatedness of opponent males. Specifically, males of closely related species treated conspecifics and heterospecifics equally, whereas males of distantly related species were overwhelmingly aggressive toward conspecifics. To our knowledge, this is the first study to quantify aggression between Drosophila species and to establish a behavioral bias for aggression against conspecifics versus heterospecifics. Our results suggest that future study of heterospecific aggression behavior in Drosophila is warranted to investigate the degree to which these trends in aggression among species extend to broader behavioral, ecological, and evolutionary contexts.

animal behavior and cognition↗
bioRxiv2018

Genome sequence of the corn leaf aphid (Rhopalosiphum maidis Fitch)

BackgroundThe corn leaf aphid (Rhopalosiphum maidis Fitch) is the most economically damaging aphid pest on maize (Zea mays), one of the worlds most important grain crops. In addition to causing direct damage due to the removal of photoassimilates, R. maidis transmits several destructive maize viruses, including Maize yellow dwarf virus, Barley yellow dwarf virus, Sugarcane mosaic virus, and Cucumber mosaic virus.\n\nFindingsA 326-Mb genome assembly of BTI-1, a parthenogenetically reproducing R. maidis clone, was generated with a combination of PacBio (208-fold coverage) and Illumina sequencing (80-fold coverage), which contains a total of 689 contigs with an N50 size of 9.0 Mb. The contigs were further clustered into four scaffolds using the Phase Genomics Hi-C interaction maps, consistent with the commonly observed 2n = 8 karyotype of R. maidis. Most of the assembled contigs (473 spanning 321 Mb) were successfully orientated in the four scaffolds. The R. maidis genome assembly captured the full length of 95.8% of the core eukaryotic genes, suggesting that it is highly complete. Repetitive sequences accounted for 21.2% of the assembly, and a total of 17,647 protein-coding genes were predicted in the R. maidis genome with integrated evidence from ab initio and homology-based gene predictions and transcriptome sequences generated with both PacBio and Illumina. An analysis of likely horizontally transferred genes identified two from bacteria, seven from fungi, two from protozoa, and nine from algae.\n\nConclusionsA high-quality R. maidis genome was assembled at the chromosome level. This genome sequence will enable further research related to ecological interactions, virus transmission, pesticide resistance, and other aspects of R. maidis biology. It also serves as a valuable resource for comparative investigation of other aphid species.

genomics↗