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Dark septate endophytes (DSE) are a form-group of root endophytic fungi with elusive functions. Here, the genomes of two common DSE of semiarid areas, Cadophora sp. and Periconia macrospinosa were sequenced and analyzed with another 32 ascomycetes of different lifestyles. Cadophora sp. (Helotiales) and P. macrospinosa (Pleosporales) have genomes of 70.46 Mb and 54.99 Mb with 22,766 and 18,750 gene models, respectively. The majority of DSE-specific protein clusters lack functional annotation with no similarity to characterized proteins, implying that they have evolved unique genetic innovations. Both DSE possess an expanded number of carbohydrate active enzymes (CAZymes), including plant cell wall degrading enzymes (PCWDEs). Those were similar in three other DSE, and contributed a signal for the separation of root endophytes in principal component analyses of CAZymes, indicating shared genomic traits of DSE fungi. Number of secreted proteases and lipases, aquaporins, and genes linked to melanin synthesis were also relatively high in our fungi. In spite of certain similarities between our two DSE, we observed low levels of convergence in their gene family evolution. This suggests that, despite originating from the same habitat, these two fungi evolved along different evolutionary trajectories and display considerable functional differences within the endophytic lifestyle.
Pubmed ID: 29679020
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Fungal genomics database and interactive analytical tools that integrates all fungal genomes for diverse fungi that are important for energy and environment, the focus of the JGI Fungal program. It integrates genomics data from the DOE JGI and its users and promotes user community participation in data submission, annotation and analysis. Over 100 newly sequenced and annotated fungal genomes from JGI and elsewhere are available to the public through MycoCosm, and new annotated genomes are being added to this resource upon completion of annotation. MycoCosm offers web-based genome analysis tools for fungal biologists to ''navigate'' through sequenced genomes and explore them in the context of ''genome-centric'' and ''comparative views''.
View all literature mentionsDatabase that integrates information on sequence and structure of lipases and related proteins sharing the same a/b hydrolase fold to facilitate protein engineering. Users can browse the database by classification, organism, hierarchic tree, and structure. They can also perform homology searches against the lipase database, and query the Lipase Engineering Database using SQL.
View all literature mentionsAn information resource for peptidases (also termed proteases, proteinases and proteolytic enzymes) and the proteins that inhibit them. The MEROPS database uses an hierarchical, structure-based classification of the peptidases. In this, each peptidase is assigned to a Family on the basis of statistically significant similarities in amino acid sequence, and families that are thought to be homologous are grouped together in a Clan. There is a Summary page for each family and clan, and these have indexes. Each of the Summary pages offers links to supplementary pages. About 3000 individual peptidases and inhibitors are included in the database, and there is a Summary page describing each one. You can navigate to this by any of several routes. There are indexes of Name, MEROPS Identifier and source Organism on the menu bar. Each Summary page describes the classification and nomenclature of the peptidase or inhibitor, and provides links to supplementary pages showing sequence identifiers, the structure if known, literature references and more.
View all literature mentionsDatabase that describes the families of structurally-related catalytic and carbohydrate-binding modules (or functional domains) of enzymes that degrade, modify, or create glycosidic bonds. This specialist database is dedicated to the display and analysis of genomic, structural and biochemical information on Carbohydrate-Active Enzymes (CAZymes). CAZy data are accessible either by browsing sequence-based families or by browsing the content of genomes in carbohydrate-active enzymes. New genomes are added regularly shortly after they appear in the daily releases of GenBank. New families are created based on published evidence for the activity of at least one member of the family and all families are regularly updated, both in content and in description. An original aspect of the CAZy database is its attempt to cover all carbohydrate-active enzymes across organisms and across subfields of glycosciences. One can search for CAZY Family pages using the Protein Accession (Genpept Accession, Uniprot Accession or PDB ID), Cazy family name or EC number. In addition, genomes can be searched using the NCBI TaxID. This search can be complemented by Google-based searches on the CAZy site.
View all literature mentionsA database of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). Users can analyze protein sequences for Pfam matches, view Pfam family annotation and alignments, see groups of related families, look at the domain organization of a protein sequence, find the domains on a PDB structure, and query Pfam by keywords. There are two components to Pfam: Pfam-A and Pfam-B. Pfam-A entries are high quality, manually curated families that may automatically generate a supplement using the ADDA database. These automatically generated entries are called Pfam-B. Although of lower quality, Pfam-B families can be useful for identifying functionally conserved regions when no Pfam-A entries are found. Pfam also generates higher-level groupings of related families, known as clans (collections of Pfam-A entries which are related by similarity of sequence, structure or profile-HMM).
View all literature mentionsTool for searching sequence databases for homologs of protein sequences, and for making protein sequence alignments. It implements methods using probabilistic models called profile hidden Markov models (profile HMMs). Compared to BLAST, FASTA, and other sequence alignment and database search tools based on older scoring methodology, HMMER aims to be significantly more accurate and more able to detect remote homologs because of the strength of its underlying mathematical models. In the past, this strength came at significant computational expense, but in the new HMMER3 project, HMMER is now essentially as fast as BLAST.
View all literature mentionsSoftware program for phylogenetic analyses of large datasets under maximum likelihood.
View all literature mentionsSoftware designed to assemble Illumina single or paired-end reads.
View all literature mentionsWeb application for prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.
View all literature mentionsWelcome to the Neuroscience Information Framework Project, designed to serve the biomedical research community. NIF maintains the largest searchable collection of neuroscience data, the largest catalog of biomedical resources, and the largest ontology for neuroscience on the web. We welcome all feedback and suggestions and are actively looking for resource providers to make their resources accessible through NIF. Learn about the tools available to help you share your data and discover a dynamic inventory of Web-based neuroscience resources.
