Molecular and genomic approaches that target mixed microbial communities (e.g., metagenomics or metatranscriptomics) provide insight into the ecological roles, evolutionary histories, and physiological capabilities of the microorganisms and the processes in the environment. Computational tools that harness large-scale sequence surveys have become a valuable resource for characterizing the genetic make-up of the bacterial and archaeal component of the marine microbiome. Yet, fewer studies have focused on the unicellular eukaryotic fraction of the community. Here, we developed the EukHeist automated computational pipeline, to retrieve eukaryotic and prokaryotic metagenome assembled genomes (MAGs). We applied EukHeist to the eukaryote-dominated large-size fraction data (0.8-2000 μm) from the Tara Oceans survey to recover both eukaryotic and prokaryotic MAGs, which we refer to as TOPAZ (Tara Oceans Particle-Associated MAGs). The TOPAZ MAGs consisted of more than 900 eukaryotic MAGs representing environmentally-relevant microbial and multicellular eukaryotes in addition to over 4,000 bacterial and archaeal MAGs. The bacterial and archaeal TOPAZ MAGs retrieved with EukHeist complement previous efforts by expanding the existing phylogenetic diversity through the increase in coverage of many likely particle- and host-associated taxa. We also demonstrate how the novel eukaryotic genomic content recovered from this study might be used to infer functional traits, such as trophic mode. By coupling MAGs and metatranscriptomic data, we explored ecologically-significant protistan groups, such as the Stramenopiles. A global survey of both eukaryotic and prokaryotic MAGs enabled the identification of ecological cohorts, driven by specific environmental factors, and putative host-microbe associations. Accessible and scalable computational tools, such as EukHeist, are likely to accelerate the identification of meaningful genetic signatures from large datasets, ultimately expanding the eukaryotic tree of life.

Summary As the importance of microbiome research continues to become more prevalent and essential to understanding a wide variety of ecosystems (e.g., marine, built, host-associated, etc.), there is a need for researchers to be able to perform highly reproducible and quality analysis of microbial genomes. MetaSanity incorporates analyses from eleven existing and widely used genome evaluation and annotation suites into a single, distributable workflow, thereby decreasing the workload of microbiologists by allowing for a flexible, expansive data analysis pipeline. MetaSanity has been designed to provide separate, reproducible workflows, that (1) can determine the overall quality of a microbial genome, while providing a putative phylogenetic assignment, and (2) can assign structural and functional gene annotations with varying degrees of specificity to suit the needs of the researcher. The software suite combines the results from several tools to provide broad insights into overall metabolic function. Importantly, this software provides built-in optimization for “big data” analysis by storing all relevant outputs in an SQL database, allowing users to query all the results for the elements that will most impact their research. Availability MetaSanity is provided under the GNU General Public License v.3.0 and is available for download at https://github.com/cjneely10/MetaSanity. This application is distributed as a Docker image. MetaSanity is implemented in Python3/Cython and C ++. Instructions for its installation and use are available within the GitHub wiki page at https://github.com/cjneely10/MetaSanity/wiki, and additional instructions are available at https://cjneely10.github.io/year-archive/. MetaSanity is optimized for users with limited programming experience. Supplementary information Supplementary data are available at Bioinformatics online.

Technical analysis suggests that a long-term rally frequently is interrupted by a short-lived decline. Such a dip, according to this view, reinforces the original uptrend. Should the dollar fall below 1.5750 marks, dealers said, technical signals would point to a correction that could pull the dollar back as far as 1.55 marks before it rebounded.

This article reviews the history of the recent shift to electronic trading in equity, foreign exchange, and fixed-income markets. The authors analyze a new data set: the eSpeed electronic Treasury network. They contrast the market microstructure of the eSpeed trading platform with the traditional voice-assisted networks that report through GovPX. The electronic market (eSpeed) has greater volume, smaller spreads, and a lower estimated trade impact than the voice market (GovPX).

Gene prediction and annotation for eukaryotic genomes is challenging with large data demands and complex computational requirements. For most eukaryotes, genomes are recovered from specific target taxa. However, it is now feasible to reconstruct or sequence hundreds of metagenome-assembled genomes (MAGs) or single-amplified genomes directly from the environment. To meet this forthcoming wave of eukaryotic genome generation, we introduce EukMetaSanity, which combines state-of-the-art tools into three pipelines that have been specifically designed for extensive parallelization on high-performance computing infrastructure. EukMetaSanity performs an automated taxonomy search against a protein database of 1,482 species to identify phylogenetically compatible proteins to be used in downstream gene prediction. We present the results for intron, exon, and gene locus prediction for 112 genomes collected from NCBI, including fungi, plants, and animals, along with 1,669 MAGs and demonstrate that EukMetaSanity can provide reliable preliminary gene predictions for a single target taxon or at scale for hundreds of MAGs. EukMetaSanity is freely available at https://github.com/cjneely10/EukMetaSanity.