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Fungi have evolved over millions of years and their species diversity is predicted to be the second largest on the earth. Fungi have cross-kingdom interactions with many organisms that have mutually shaped their evolutionary trajectories. Zygomycete fungi hold a pivotal position in the fungal tree of life and provide important perspectives on the early evolution of fungi from aquatic to terrestrial environments. Phylogenomic analyses have found that zygomycete fungi diversified into two separate clades, the Mucoromycota which are frequently associated with plants and Zoopagomycota that are commonly animal-associated fungi. Genetic elements that contributed to the fitness and divergence of these lineages may have been shaped by the varied interactions these fungi have had with plants, animals, bacteria, and other microbes. To investigate this, we performed comparative genomic analyses of the two clades of zygomycetes in the context of Kingdom Fungi, benefiting from our generation of a new collection of zygomycete genomes, including nine produced for this study. We identified lineage-specific genomic content that may contribute to the disparate biology observed in these zygomycetes. Our findings include the discovery of undescribed diversity in CotH, a Mucormycosis pathogenicity factor, which was found in a broad set of zygomycetes. Reconciliation analysis identified multiple duplication events and an expansion of CotH copies throughout the Mucoromycotina, Mortierellomycotina, Neocallimastigomycota, and Basidiobolus lineages. A kingdom-level phylogenomic analysis also identified new evolutionary relationships within the subphyla of Mucoromycota and Zoopagomycota, including supporting the sister-clade relationship between Glomeromycotina and Mortierellomycotina and the placement of Basidiobolus as sister to other Zoopagomycota lineages.

International audience; Summary The ectomycorrhizal (ECM) symbiosis has independently evolved from diverse types of saprotrophic ancestors. In this study, we seek to identify genomic signatures of the transition to the ECM habit within the hyper-diverse Russulaceae. We present comparative analyses of the genomic architecture and the total and secreted gene repertoires of 18 species across the order Russulales of which 13 are newly sequenced, including a representative of a saprotrophic member of Russulaceae, Gloeopeniophorella convolvens. The genomes of ECM Russulaceae are characterized by a loss of genes for plant cell-wall degrading enzymes (PCWDEs), an expansion of genome size through increased transposable element (TE) content, a reduction in secondary metabolism clusters, and an association of small secreted proteins (SSPs) with TE “nests”, or dense aggregations of TEs. Some PCWDEs have been retained or even expanded, mostly in a species-specific manner. The genome of Gloeopeniophorella convolvens possesses some characteristics of ECM genomes (e.g., loss of some PCWDEs, TE expansion, reduction in secondary metabolism clusters). Functional specialization in ectomycorrhizal decomposition may drive diversification. Accelerated gene evolution predates the evolution of the ECM habit, indicating that changes in genome architecture and gene content may be necessary to prime the evolutionary switch.

Most of the described species in kingdom Fungi are contained in two phyla, the Ascomycota and the Basidiomycota (subkingdom Dikarya). As a result, our understanding of the biology of the kingdom is heavily influenced by traits observed in Dikarya, such as aerial spore dispersal and life cycles dominated by mitosis of haploid nuclei. We now appreciate that Fungi comprises numerous phylum-level lineages in addition to those of Dikarya, but the phylogeny and genetic characteristics of most of these lineages are poorly understood due to limited genome sampling. Here, we addressed major evolutionary trends in the non-Dikarya fungi by phylogenomic analysis of 69 newly generated draft genome sequences of the zoosporic (flagellated) lineages of true fungi. Our phylogeny indicated five lineages of zoosporic fungi and placed Blastocladiomycota, which has an alternation of haploid and diploid generations, as branching closer to the Dikarya than to the Chytridiomyceta. Our estimates of heterozygosity based on genome sequence data indicate that the zoosporic lineages plus the Zoopagomycota are frequently characterized by diploid-dominant life cycles. We mapped additional traits, such as ancestral cell-cycle regulators, cell-membrane– and cell-wall–associated genes, and the use of the amino acid selenocysteine on the phylogeny and found that these ancestral traits that are shared with Metazoa have been subject to extensive parallel loss across zoosporic lineages. Together, our results indicate a gradual transition in the genetics and cell biology of fungi from their ancestor and caution against assuming that traits measured in Dikarya are typical of other fungal lineages.

The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived genomes lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e. for a number of viruses they yield erroneous predictions or no prediction at all. Here we describe iPHoP, a two-step framework that integrates multiple methods to provide host predictions for a broad range of viruses while retaining a low (https://bitbucket.org/srouxjgi/iphop, through a Bioconda recipe, and a Docker container.

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB's impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.The brain is an immensely complex organ which regulates many of the behaviors that animals need to survive. To understand how the brain works, scientists monitor and record brain activity under different conditions using a variety of experimental techniques. These neurophysiological studies are often conducted on multiple types of cells in the brain as well as a variety of species, ranging from mice to flies, or even frogs and worms. Such a range of approaches provides us with highly informative, complementary ‘views’ of the brain. However, to form a complete, coherent picture of how the brain works, scientists need to be able to integrate all the data from these different experiments. For this to happen effectively, neurophysiology data need to meet certain criteria: namely, they must be findable, accessible, interoperable, and re-usable (or FAIR for short). However, the sheer diversity of neurophysiology experiments impedes the ‘FAIR’-ness of the information obtained from them. To overcome this problem, researchers need a standardized way to communicate their experiments and share their results – in other words, a ‘standard language’ to describe neurophysiology data. Rübel, Tritt, Ly, Dichter, Ghosh et al. therefore set out to create such a language that was not only FAIR, but could also co-evolve with neurophysiology research. First, they produced a computer software program (called Neurodata Without Borders, or NWB for short) which generated and defined the different components of the new standard language. Then, other tools for data management were created to expand the NWB platform using the standardized language. This included data analysis and visualization methods, as well as an ‘archive’ to store and access data. Testing the new language and associated tools showed that they indeed allowed researchers to access, analyze, and share information from many different types of experiments, in organisms ranging from flies to humans. The NWB software is open-source, meaning that anyone can obtain a copy and make changes to it. Thus, NWB and its associated resources provide the basis for a collaborative, community-based system for sharing neurophysiology data. Rübel et al. hope that NWB will inspire similar developments across other fields of biology that share similar levels of complexity with neurophysiology.

Wood-decaying fungi of the class Agaricomycetes (phylum Basidiomycota) are saprotrophs that break down lignocellulose and play an important role in the nutrient recycling. They secrete a wide range of extracellular plant cell wall degrading enzymes that break down cellulose, hemicellulose and lignin, the main building blocks of plant biomass. Although the production of these enzymes is regulated mainly at the transcriptional level, no activating regulators have been identified in any wood-decaying fungus in the class Agaricomycetes. We studied the regulation of cellulase expression in the wood-decaying fungus Schizophyllum commune. Comparative genomics and transcriptomics on two wild isolates revealed a Zn2Cys6-type transcription factor gene (roc1) that was highly up-regulated during growth on cellulose, when compared to glucose. It is only conserved in the class Agaricomycetes. A roc1 knockout strain showed an inability to grow on medium with cellulose as sole carbon source, and growth on cellobiose and xylan (other components of wood) was inhibited. Growth on non-wood-related carbon sources was not inhibited. Cellulase activity was reduced in the growth medium of the Δroc1 strain. ChIP-Seq identified 1474 binding sites of the Roc1 transcription factor. Promoters of genes involved in lignocellulose degradation were enriched with these binding sites, especially those of LPMO (lytic polysaccharide monooxygenase) CAZymes, indicating that Roc1 directly regulates these genes. A GC-rich motif was identified as the binding site of Roc1, which was confirmed by a functional promoter analysis. Together, Roc1 is a key regulator of cellulose degradation and the first identified in wood-decaying fungi in the phylum Basidiomycota.

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB’s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

The ectomycorrhizal symbiosis is an essential guild of many forested ecosystems and has a dynamic evolutionary history across kingdom Fungi, having independently evolved from diverse types of saprotrophic ancestors. In this study, we seek to identify genomic features of the transition to the ectomycorrhizal habit within the Russulaceae, one of the most diverse lineages of ectomycorrhizal fungi. We present comparative analyses of the pangenome and gene repertoires of 21 species across the order Russulales, including a closely related saprotrophic member of Russulaceae. The ectomycorrhizal Russulaceae is inferred to have originated around the Cretaceous-Paleogene extinction event (73.6-60.1 million years ago (MY)). The genomes of the ectomycorrhizal Russulaceae are characterized by a loss of genes for plant cell-wall degrading enzymes (PCWDEs), an expansion of genome size through increased transposable element (TE) content, a reduction in secondary metabolism clusters, and an association of genes coding for certain secreted proteins with TE “nests”. The saprotrophic sister group of the ectomycorrhizal Russulaceae, Gloeopeniophorella convolvens, possesses some of these aspects (e.g., loss of some PCWDE and protease orthologs, TE expansion, reduction in secondary metabolism clusters), resulting from an accelerated rate of gene evolution in the shared ancestor of Russulaceae that predates the evolution of the ectomycorrhizal habit. Genomes of Russulaceae possess a high degree of synteny, including a conserved set of terpene secondary metabolite gene clusters. We hypothesize that the evolution of the ectomycorrhizal habit requires premodification of the genome for plant root association followed by an accelerated rate of gene evolution within the secretome for host-defense circumvention and symbiosis establishment.

19 p.-6 fig., As actors of global carbon cycle, Agaricomycetes (Basidiomycota) have developed complex enzymatic machineries that allow them to decompose all plant polymers, including lignin. Among them, saprotrophic Agaricales are characterized by an unparalleled diversity of habitats and lifestyles. Comparative analysis of 52 Agaricomycetes genomes (14 of them sequenced de novo) reveals that Agaricales possess a large diversity of hydrolytic and oxidative enzymes for lignocellulose decay. Based on the gene families with the predicted highest evolutionary rates -namely cellulose-binding CBM1, glycoside hydrolase GH43, lytic polysaccharide monooxygenase AA9, class-II peroxidases, glucose-methanol-choline oxidase/dehydrogenases, laccases, and unspecific peroxygenases- we reconstructed the lifestyles of the ancestors that led to the extant lignocellulose-decomposing Agaricomycetes. The changes in the enzymatic toolkit of ancestral Agaricales are correlated with the evolution of their ability to grow not only on wood but also on leaf-litter and decayed wood, with grass-litter decomposers as the most recent eco-physiological group. In this context, the above families were analyzed in detail in connection with lifestyle diversity. Peroxidases appear as a central component of the enzymatic toolkit of saprotrophic Agaricomycetes, consistent with their essential role in lignin degradation and high evolutionary rates. This includes not only expansions/losses in peroxidase genes common to other basidiomycetes, but also the widespread presence in Agaricales (and Russulales) of new peroxidases types not found in wood-rotting Polyporales, and other Agaricomycetes orders. Therefore, we analyzed the peroxidase evolution in Agaricomycetes by ancestral-sequence reconstruction revealing several major evolutionary pathways, and mapped the appearance of the different enzyme types in a time-calibrated species tree., This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness (BIO2017-86559-R to F.J.R.-D., S.C. and A.T.M., BIO2015-7369-JIN to J.B, and AGL2014-55971-R to A.G.P and L.R., projects cofinanced by FEDER funds); National Science Foundation (grant 1457721 to D.C.); Bundesministerium für Bildung und Forschung (CEFOX 031B0831B to H.K.); Deutsche Forschungsgemeinschaft (Biodiversity-Exploratories BLD-MFD-HZG III, KE 1742/2-1 to H.K.); Consejo Superior de Investigaciones Científicas (PIE-201620E081 to A.T.M.); and the Laboratory of Excellence ARBRE (ANR-11-LABX-0002-01), the Region Lorraine, the European Regional Development Fund, and the Plant–Microbe Interfaces Scientific Focus Area in the Genomic Science Program, U.S. DOE Office of Science to F.M. The work conducted by the JGI, a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. DOE under contract DE-AC02-05CH11231.

Dothideomycetes is the largest class of kingdom Fungi and comprises an incredible diversity of lifestyles, many of which have evolved multiple times. Plant pathogens represent a major ecological niche of the class Dothideomycetes and they are known to infect most major food crops and feedstocks for biomass and biofuel production. Studying the ecology and evolution of Dothideomycetes has significant implications for our fundamental understanding of fungal evolution, their adaptation to stress and host specificity, and practical implications with regard to the effects of climate change and on the food, feed, and livestock elements of the agro-economy. In this study, we present the first large-scale, whole-genome comparison of 101 Dothideomycetes introducing 55 newly sequenced species. The availability of whole-genome data produced a high-confidence phylogeny leading to reclassification of 25 organisms, provided a clearer picture of the relationships among the various families, and indicated that pathogenicity evolved multiple times within this class. We also identified gene family expansions and contractions across the Dothideomycetes phylogeny linked to ecological niches providing insights into genome evolution and adaptation across this group. Using machine-learning methods we classified fungi into lifestyle classes with >95 % accuracy and identified a small number of gene families that positively correlated with these distinctions. This can become a valuable tool for genome-based prediction of species lifestyle, especially for rarely seen and poorly studied species. This manuscript has been authored by an author at Lawrence Berkeley National Laboratory under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy. R. A. and I. V. G. were supported by the NSF grants DEB-1354625 and IOS-1456958. Sequencing of Dothideomycetes genomes were conducted as part of the 1000 Fungal Genomes Project supported by the JGI Community Sequencing Project #662.

A ubiquitous problem in aggregating data across different experimental and observational data sources is a lack of software infrastructure that enables flexible and extensible standardization of data and metadata. To address this challenge, we developed HDMF, a hierarchical data modeling framework for modern science data standards. With HDMF, we separate the process of data standardization into three main components: (1) data modeling and specification, (2) data I/O and storage, and (3) data interaction and data APIs. To enable standards to support the complex requirements and varying use cases throughout the data life cycle, HDMF provides object mapping infrastructure to insulate and integrate these various components. This approach supports the flexible development of data standards and extensions, optimized storage backends, and data APIs, while allowing the other components of the data standards ecosystem to remain stable. To meet the demands of modern, large-scale science data, HDMF provides advanced data I/O functionality for iterative data write, lazy data load, and parallel I/O. It also supports optimization of data storage via support for chunking, compression, linking, and modular data storage. We demonstrate the application of HDMF in practice to design NWB 2.0 [13], a modern data standard for collaborative science across the neurophysiology community.

Divergence of breeding system plays an important role in fungal speciation. Ectomycorrhizal fungi, however, pose a challenge for the study of reproductive biology because most cannot be mated under laboratory conditions. To overcome this barrier, we sequenced the draft genomes of the ectomycorrhizal sister species Rhizopogon vinicolor Smith and Zeller and R. vesiculosus Smith and Zeller (Basidiomycota, Boletales)—the first genomes available for Basidiomycota truffles—and characterized gene content and organization surrounding their mating type loci. Both species possess a pair of homeodomain transcription factor homologs at the mating type A-locus as well as pheromone receptor and pheromone precursor homologs at the mating type B-locus. Comparison of Rhizopogon genomes with genomes from Boletales, Agaricales, and Polyporales revealed synteny of the A-locus region within Boletales, but several genomic rearrangements across orders. Our findings suggest correlation between gene content at the B-locus region and breeding system in Boletales with tetrapolar species possessing more diverse gene content than bipolar species. Rhizopogon vinicolor possesses a greater number of B-locus pheromone receptor and precursor genes than R. vesiculosus, as well as a pair of isoprenyl cysteine methyltransferase genes flanking the B-locus compared to a single copy in R. vesiculosus. Examination of dikaryotic single nucleotide polymorphisms within genomes revealed greater heterozygosity in R. vinicolor, consistent with increased rates of outcrossing. Both species possess the components of a heterothallic breeding system with R. vinicolor possessing a B-locus region structure consistent with tetrapolar Boletales and R. vesiculosus possessing a B-locus region structure intermediate between bipolar and tetrapolar Boletales.

Author(s): Rubel, Oliver; Tritt, Andrew; Dichter, Benjamin; Braun, Thomas; Cain, Nicholas; Clack, Nathan; Davidson, Thomas; Dougherty, Max; Fillion-Robin, Jean-Christophe; Graddis, Nile; Grauer, Michael; Kiggins, Justin; Niu, Lawrence; Ozturk, Doruk; Schroeder, William; Soltesz, Ivan; Sommer, Friedrich; Svoboda, Karel; Lydia, Ng; Frank, Loren; Bouchard, Kristofer | Abstract: ABSTRACT Neurodata Without Borders: Neurophysiology (NWB:N) is a data standard for neurophysiology, providing neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data. With NWB:N version 2.0 (NWB:N 2.0) we made significant advances towards creating a usable standard, software ecosystem, and vibrant community for standardizing neurophysiology data. In this manuscript we focus in particular on the NWB:N data standard schema and present advances towards creating an accessible data standard for neurophysiology.

chipD is a web server that facilitates design of DNA oligonucleotide probes for high-density tiling arrays, which can be used in a number of genomic applications such as ChIP-chip or gene-expression profiling. The server implements a probe selection algorithm that takes as an input, in addition to the target sequences, a set of parameters that allow probe design to be tailored to specific applications, protocols or the array manufacturer’s requirements. The algorithm optimizes probes to meet three objectives: (i) probes should be specific; (ii) probes should have similar thermodynamic properties; and (iii) the target sequence coverage should be homogeneous and avoid significant gaps. The output provides in a text format, the list of probe sequences with their genomic locations, targeted strands and hybridization characteristics. chipD has been used successfully to design tiling arrays for bacteria and yeast. chipD is available at http://chipd.uwbacter.org/.

To elucidate the genetic bases of mycorrhizal lifestyle evolution, we sequenced new fungal genomes, including 13 ectomycorrhizal (ECM), orchid (ORM) and ericoid (ERM) species, and five saprotrophs, which we analyzed along with other fungal genomes. Ectomycorrhizal fungi have a reduced complement of genes encoding plant cell wall–degrading enzymes (PCWDEs), as compared to their ancestral wood decayers. Nevertheless, they have retained a unique array of PCWDEs, thus suggesting that they possess diverse abilities to decompose lignocellulose. Similar functional categories of nonorthologous genes are induced in symbiosis. Of induced genes, 7–38% are orphan genes, including genes that encode secreted effector-like proteins. Convergent evolution of the mycorrhizal habit in fungi occurred via the repeated evolution of a ‘symbiosis toolkit’, with reduced numbers of PCWDEs and lineage-specific suites of mycorrhiza-induced genes. This material is based on work conducted by the US Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, supported under contract no. DE-AC02-05CH11231. This work was also supported by the Laboratory of Excellence ARBRE (ANR-11-LABX-0002-01), the Genomic Science Program (Plant-Microbe Interactions project) funded by the US Department of Energy, Office of Science, Biological and Environmental Research (contract DE-AC05-00OR22725), the Lorraine Region Council (to F.M.), US National Science Foundation grants DEB-1208719 and DEB-0933081 (both to D.S.H. and DEB-1021606 (to A.P.)), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig (DFG FTZ 118) and the German Science Foundation (DFG, grant BU941/20-1) (to F.B.) and the Swedish Research Council (to A. Tunlid). This work was partly supported by the Laboratory of Excellence TULIP (ANR-10-LABX-41 and ANR-11-IDEX-0002-02). F.M. would like to acknowledge M.A. Selosse and B. Lindahl for helpful discussions.

Wood decay mechanisms in Agaricomycotina have been traditionally separated in two categories termed white and brown rot. Recently the accuracy of such a dichotomy has been questioned. Here, we present the genome sequences of the white-rot fungus Cylindrobasidium torrendii and the brown-rot fungus Fistulina hepatica both members of Agaricales, combining comparative genomics and wood decay experiments. C torrendii is closely related to the white-rot root pathogen Armillaria mellea, while F. hepatica is related to Schizophyllum commune, which has been reported to cause white rot. Our results suggest that C torrendii and S. commune are intermediate between white-rot and brown-rot fungi, but at the same time they show characteristics of decay that resembles soft rot. Both species cause weak wood decay and degrade all wood components but leave the middle lamella intact. Their gene content related to lignin degradation is reduced, similar to brown-rot fungi, but both have maintained a rich array of genes related to carbohydrate degradation, similar to white-rot fungi. These characteristics appear to have evolved from white-rot ancestors with stronger ligninolytic ability. F. hepatica shows characteristics of brown rot both in terms of wood decay genes found in its genome and the decay that it causes. However, genes related to cellulose degradation are still present, which is a plesiomorphic characteristic shared with its white-rot ancestors. Four wood degradation-related genes, homologs of which are frequently lost in brown-rot fungi, show signs of pseudogenization in the genome of F. hepatica. These results suggest that transition toward a brown-rot lifestyle could be an ongoing process in F. hepatica. Our results reinforce the idea that wood decay mechanisms are more diverse than initially thought and that the dichotomous separation of wood decay mechanisms in Agaricomycotina into white rot and brown rot should be revisited. (C) 2015 Elsevier Inc. All rights reserved.

Organisms across the tree of life use a variety of mechanisms to respond to stress-inducing fluctuations in osmotic conditions. Cellular response mechanisms and phenotypes associated with osmoadaptation also play important roles in bacterial virulence, human health, agricultural production and many other biological systems. To improve understanding of osmoadaptive strategies, we have generated 59 high-quality draft genomes for the haloarchaea (a euryarchaeal clade whose members thrive in hypersaline environments and routinely experience drastic changes in environmental salinity) and analyzed these new genomes in combination with those from 21 previously sequenced haloarchaeal isolates. We propose a generalized model for haloarchaeal management of cytoplasmic osmolarity in response to osmotic shifts, where potassium accumulation and sodium expulsion during osmotic upshock are accomplished via secondary transport using the proton gradient as an energy source, and potassium loss during downshock is via a combination of secondary transport and non-specific ion loss through mechanosensitive channels. We also propose new mechanisms for magnesium and chloride accumulation. We describe the expansion and differentiation of haloarchaeal general transcription factor families, including two novel expansions of the TATA-binding protein family, and discuss their potential for enabling rapid adaptation to environmental fluxes. We challenge a recent high-profile proposal regarding the evolutionary origins of the haloarchaea by showing that inclusion of additional genomes significantly reduces support for a proposed large-scale horizontal gene transfer into the ancestral haloarchaeon from the bacterial domain. The combination of broad (17 genera) and deep (≥5 species in four genera) sampling of a phenotypically unified clade has enabled us to uncover both highly conserved and specialized features of osmoadaptation. Finally, we demonstrate the broad utility of such datasets, for metagenomics, improvements to automated gene annotation and investigations of evolutionary processes., Author Summary The ability to adjust to changing osmotic conditions (osmoadaptation) is crucial to the survival of organisms across the tree of life. However, significant gaps still exist in our understanding of this important phenomenon. To help fill some of these gaps, we have produced high-quality draft genomes for 59 osmoadaptation “experts” (extreme halophiles of the euryarchaeal family Halobacteriaceae). We describe the dispersal of osmoadaptive protein families across the haloarchaeal evolutionary tree. We use this data to suggest a generalized model for haloarchaeal ion transport in response to changing osmotic conditions, including proposed new mechanisms for magnesium and chloride accumulation. We describe the evolutionary expansion and differentiation of haloarchaeal general transcription factor families and discuss their potential for enabling rapid adaptation to environmental fluxes. Lastly, we challenge a recent high-profile proposal regarding the evolutionary origins of the haloarchaea by showing that inclusion of additional genomes significantly reduces support for a proposed large-scale horizontal gene transfer into the ancestral haloarchaeon from the bacterial domain. This result highlights the power of our dataset for making evolutionary inferences, a feature which will make it useful to the broader evolutionary community. We distribute our genomic dataset through a user-friendly graphical interface.

Remarkable advances in DNA sequencing technology have created a need for de novo genome assembly methods tailored to work with the new sequencing data types. Many such methods have been published in recent years, but assembling raw sequence data to obtain a draft genome has remained a complex, multi-step process, involving several stages of sequence data cleaning, error correction, assembly, and quality control. Successful application of these steps usually requires intimate knowledge of a diverse set of algorithms and software. We present an assembly pipeline called A5 (Andrew And Aaron's Awesome Assembly pipeline) that simplifies the entire genome assembly process by automating these stages, by integrating several previously published algorithms with new algorithms for quality control and automated assembly parameter selection. We demonstrate that A5 can produce assemblies of quality comparable to a leading assembly algorithm, SOAPdenovo, without any prior knowledge of the particular genome being assembled and without the extensive parameter tuning required by the other assembly algorithm. In particular, the assemblies produced by A5 exhibit 50% or more reduction in broken protein coding sequences relative to SOAPdenovo assemblies. The A5 pipeline can also assemble Illumina sequence data from libraries constructed by the Nextera (transposon-catalyzed) protocol, which have markedly different characteristics to mechanically sheared libraries. Finally, A5 has modest compute requirements, and can assemble a typical bacterial genome on current desktop or laptop computer hardware in under two hours, depending on depth of coverage. © 2012 Tritt et al.

Summary: High-throughput DNA sequencing technologies have spurred the development of numerous novel methods for genome assembly. With few exceptions, these algorithms are heuristic and require one or more parameters to be manually set by the user. One approach to parameter tuning involves assembling data from an organism with an available high-quality reference genome, and measuring assembly accuracy using some metrics. We developed a system to measure assembly quality under several scoring metrics, and to compare assembly quality across a variety of assemblers, sequence data types, and parameter choices. When used in conjunction with training data such as a high-quality reference genome and sequence reads from the same organism, our program can be used to manually identify an optimal sequencing and assembly strategy for de novo sequencing of related organisms. Availability: GPL source code and a usage tutorial is at http://ngopt.googlecode.com Contact: aarondarling@ucdavis.edu Supplementary information: Supplementary data is available at Bioinformatics online.

© 2015 Muraguchi et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The basidiomycete fungus Coprinopsis cinerea is an important model system for multicellular development. Fruiting bodies of C. cinerea are typical mushrooms, which can be produced synchronously on defined media in the laboratory. To investigate the transcriptome in detail during fruiting body development, high-throughput sequencing (RNA-seq) was performed using cDNA libraries strand-specifically constructed from 13 points (stages/tissues) with two biological replicates. The reads were aligned to 14,245 predicted transcripts, and counted for forward and reverse transcripts. Differentially expressed genes (DEGs) between two adjacent points and between vegetative mycelium and each point were detected by Tag Count Comparison (TCC). To validate RNA-seq data, expression levels of selected genes were compared using RPKM values in RNA-seq data and qRT-PCR data, and DEGs detected in microarray data were examined in MA plots of RNA-seq data by TCC. We discuss events deduced from GO analysis of DEGs. In addition, we uncovered both transcription factor candidates and antisense transcripts that are likely to be involved in developmental regulation for fruiting.