eggNOG is a public resource that provides Orthologous Groups (OGs) of proteins at different taxonomic levels, each with integrated and summarized functional annotations. Developments since the latest public release include changes to the algorithm for creating OGs across taxonomic levels, making nested groups hierarchically consistent. This allows for a better propagation of functional terms across nested OGs and led to the novel annotation of 95 890 previously uncharacterized OGs, increasing overall annotation coverage from 67% to 72%. The functional annotations of OGs have been expanded to also provide Gene Ontology terms, KEGG pathways and SMART/Pfam domains for each group. Moreover, eggNOG now provides pairwise orthology relationships within OGs based on analysis of phylogenetic trees. We have also incorporated a framework for quickly mapping novel sequences to OGs based on precomputed HMM profiles. Finally, eggNOG version 4.5 incorporates a novel data set spanning 2605 viral OGs, covering 5228 proteins from 352 viral proteomes. All data are accessible for bulk downloading, as a web-service, and through a completely redesigned web interface. The new access points provide faster searches and a number of new browsing and visualization capabilities, facilitating the needs of both experts and less experienced users. eggNOG v4.5 is available at http://eggnog.embl.de.

https://www.zora.uzh.ch/id/eprint/120037/1/26582926.pdf

eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences

Advances in high-throughput sequencing and ‘omics technologies are revolutionizing studies of naturally occurring microbial communities. Comprehensive investigations of microbial lifestyles require the ability to interactively organize and visualize genetic information and to incorporate subtle differences that enable greater resolution of complex data. Here we introduce anvi’o, an advanced analysis and visualization platform that offers automated and human-guided characterization of microbial genomes in metagenomic assemblies, with interactive interfaces that can link ‘omics data from multiple sources into a single, intuitive display. Its extensible visualization approach distills multiple dimensions of information about each contig, offering a dynamic and unified work environment for data exploration, manipulation, and reporting. Using anvi’o, we re-analyzed publicly available datasets and explored temporal genomic changes within naturally occurring microbial populations through de novo characterization of single nucleotide variations, and linked cultivar and single-cell genomes with metagenomic and metatranscriptomic data. Anvi’o is an open-source platform that empowers researchers without extensive bioinformatics skills to perform and communicate in-depth analyses on large ‘omics datasets.

Anvi'o: an advanced analysis and visualization platform for 'omics data.

Almost all land plants form symbiotic associations with mycorrhizal fungi. These below-ground fungi play a key role in terrestrial ecosystems as they regulate nutrient and carbon cycles, and influence soil structure and ecosystem multifunctionality. Up to 80% of plant N and P is provided by mycorrhizal fungi and many plant species depend on these symbionts for growth and survival. Estimates suggest that there are c. 50 000 fungal species that form mycorrhizal associations with c. 250 000 plant species. The development of high-throughput molecular tools has helped us to better understand the biology, evolution, and biodiversity of mycorrhizal associations. Nuclear genome assemblies and gene annotations of 33 mycorrhizal fungal species are now available providing fascinating opportunities to deepen our understanding of the mycorrhizal lifestyle, the metabolic capabilities of these plant symbionts, the molecular dialogue between symbionts, and evolutionary adaptations across a range of mycorrhizal associations. Large-scale molecular surveys have provided novel insights into the diversity, spatial and temporal dynamics of mycorrhizal fungal communities. At the ecological level, network theory makes it possible to analyze interactions between plant-fungal partners as complex underground multi-species networks. Our analysis suggests that nestedness, modularity and specificity of mycorrhizal networks vary and depend on mycorrhizal type. Mechanistic models explaining partner choice, resource exchange, and coevolution in mycorrhizal associations have been developed and are being tested. This review ends with major frontiers for further research.

https://nph.onlinelibrary.wiley.com/doi/epdf/10.1111/nph.13288

Mycorrhizal ecology and evolution: the past, the present, and the future

MycoCosm is a fungal genomics portal (http://jgi.doe.gov/fungi), developed by the US Department of Energy Joint Genome Institute to support integration, analysis and dissemination of fungal genome sequences and other 'omics' data by providing interactive web-based tools. MycoCosm also promotes and facilitates user community participation through the nomination of new species of fungi for sequencing, and the annotation and analysis of resulting data. By efficiently filling gaps in the Fungal Tree of Life, MycoCosm will help address important problems associated with energy and the environment, taking advantage of growing fungal genomics resources.

/pdf/mycocosm-portal-gearing-up-for-1000-fungal-genomes-1cu30ls0n4.pdf

MycoCosm portal: gearing up for 1000 fungal genomes

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.

/pdf/convergent-losses-of-decay-mechanisms-and-rapid-turnover-of-w59lj8ik6y.pdf

Convergent losses of decay mechanisms and rapid turnover of symbiosis genes in mycorrhizal mutualists.

The US Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization The JGI Genome Portal (http://genomejgidoegov) provides unified access to all JGI genomic databases and analytical tools The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes Here we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI

https://escholarship.org/content/qt8kv6x7p3/qt8kv6x7p3.pdf?t=p0lnom

The genome portal of the Department of Energy Joint Genome Institute: 2014 updates

The Department of Energy (DOE) Joint Genome Institute (JGI) is a national user facility with massive-scale DNA sequencing and analysis capabilities dedicated to advancing genomics for bioenergy and environmental applications. Beyond generating tens of trillions of DNA bases annually, the Institute develops and maintains data management systems and specialized analytical capabilities to manage and interpret complex genomic data sets, and to enable an expanding community of users around the world to analyze these data in different contexts over the web. The JGI Genome Portal (http://genome.jgi.doe.gov) provides a unified access point to all JGI genomic databases and analytical tools. A user can find all DOE JGI sequencing projects and their status, search for and download assemblies and annotations of sequenced genomes, and interactively explore those genomes and compare them with other sequenced microbes, fungi, plants or metagenomes using specialized systems tailored to each particular class of organisms. We describe here the general organization of the Genome Portal and the most recent addition, MycoCosm (http://jgi.doe.gov/fungi), a new integrated fungal genomics resource.

/pdf/the-genome-portal-of-the-department-of-energy-joint-genome-17x09vdb1y.pdf

The Genome Portal of the Department of Energy Joint Genome Institute

Motivation: The recent revolution in sequencing technologies has led to an exponential growth of sequence data. As a result, most of the current bioinformatics tools become obsolete as they fail to scale with data. To tackle this ‘data deluge’, here we introduce the BioPig sequence analysis toolkit as one of the solutions that scale to data and computation. Results: We built BioPig on the Apache’s Hadoop MapReduce system and the Pig data flow language. Compared with traditional serial and MPI-based algorithms, BioPig has three major advantages: first, BioPig’s programmability greatly reduces development time for parallel bioinformatics applications; second, testing BioPig with up to 500 Gb sequences demonstrates that it scales automatically with size of data; and finally, BioPig can be ported without modification on many Hadoop infrastructures, as tested with Magellan system at National Energy Research Scientific Computing Center and the Amazon Elastic Compute Cloud. In summary, BioPig represents a novel program framework with the potential to greatly accelerate data-intensive bioinformatics analysis. Availability and implementation: BioPig is released as open-source software under the BSD license at https://sites.google.com/a/lbl.gov/ biopig/

/pdf/biopig-a-hadoop-based-analytic-toolkit-for-large-scale-ln2ruvxe55.pdf

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data

In many scientific domains, experimental devices or simulation programs generate large volumes of data. The volumes of data may reach hundreds of terabytes and therefore it is impractical to store them on disk systems. Rather they are stored on robotic tape systems that are managed by some mass storage system (MSS). A major bottleneck in analyzing the simulated/collected data is the retrieval of subsets from the tertiary storage system. We describe the architecture and implementation of a Storage Access Coordination System (STACS) designed to optimize the use of a disk cache, and thus minimize the number of files read from tape. We achieve this by using a specialized index to locate the relevant data on tapes, and by coordinating file caching over multiple queries. We focus on a specific application area, a high energy physics data management and analysis environment. STACS was implemented and is being incorporated in an operational system, scheduled to go online at the end of 1999. We also include the results of various tests that demonstrate the benefits and efficiency gained of using the STACS.

/pdf/multidimensional-indexing-and-query-coordination-for-29zv15dvpm.pdf

Henrik P. Nordberg

Papers

MycoCosm portal: gearing up for 1000 fungal genomes

The genome portal of the Department of Energy Joint Genome Institute: 2014 updates

The Genome Portal of the Department of Energy Joint Genome Institute

BioPig: a Hadoop-based analytic toolkit for large-scale sequence data

Multidimensional indexing and query coordination for tertiary storage management