Protein family models used by PGAP are now available for download

A new release of the NCBI protein families profiles used by PGAP (the Prokaryotic Genome Annotation Pipeline) is now available. You can search this collection of Hidden Markov models (HMM) against your favorite prokaryotic proteins to identify their function using hmmer.

The HMMs are used as hints for the structural annotation of protein-coding genes in bacterial genomes and are also one of the sources for the names assigned to PGAP-annotated proteins presented in the Evidence-For-Name-Assignment comment block of RefSeq protein records (See for example, WP_004152100.1).

The collection comprises 12,753 HMMs that were built at NCBI, and 4,486 TIGRFAM HMMs whose ownership was transferred to NCBI in April 2018. In addition to the HMM profiles and seed alignments, a tab-delimited file containing the product names and other attributes added to the HMMs by curators is available.

  • 85% of models were assigned a product name that can be transferred to proteins hit by the model.
  • 7702 models have gene symbols.
  • 14508 are supported by a least one publication.
  • 6266 are assigned an Enzyme Commission number.
  • 617 represent anti-microbial resistance proteins.
  • Product names added to 4,686 PFAM HMMs owned by EBI-EMBL and used for functional annotation by PGAP are also included.

A total of 57 million RefSeq prokaryotic proteins have been named based on these curated HMMs, and can be identified with the Entrez query “meta Evidence-For-Name-Assignment”[Properties] AND “Evidence Category=HMM”[Text Word]. See an example and more information on web displays of HMMs in a previous post.

New PGAP release with Singularity, no-internet option, and Taxonomy Check

A new version of the Prokaryotic Genome Annotation Pipeline (PGAP) with several important features is now available on Github.

  • In response to several requests we have added the option of running PGAP with Singularity, Podman or any other Docker-compatible executable you wish to use.
  • We have also lifted the requirement for internet access in case you have privacy concerns. To run the pipeline without internet access, set the flag
    --no-internet.
  • Are you unsure about the identity of organism you sequenced? We’ve added the Taxonomy-Check module to help you. This module will confirm the organism name or suggest a new taxonomic assignment through average nucleotide identity comparison with type material assemblies from GenBank. The check is currently an optional validation step prior to PGAP.

Try these new features and let us know what you think! Or submit your PGAP-annotated assembly to GenBank. And remember that if you are still improving the assembly and your genome doesn’t pass the pre-annotation validation, you can use the --ignore-all-errors flag to get a preliminary annotation.

Important changes coming to prokaryotic Reference and Representative genome assemblies

We are making changes to the set of bacterial and archaeal RefSeq Reference and Representative assemblies in February 2020.

  • We will reduce the number of Reference assemblies to 15 that have annotation provided by outside experts (Table 1) and re-annotate the 105 other current Reference assemblies using the latest Prokaryotic Genome Annotation Pipeline (PGAP) software. The re-annotated assemblies will lose reference status.
  • We will reassess and revise the set of Representative assemblies so that there is one assembly per species to better reflect the taxonomic diversity of the RefSeq bacterial and archaeal assemblies.

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NCBI on YouTube: Get the most out of NCBI resources with these videos

Check out the latest videos on YouTube to learn how to best use NCBI graphical viewers, SRA, PGAP, and other resources.

Genome Data Viewer: Analyzing Remote BAM Alignment Files and Other Tips

This video shows you how to upload remote BAM files, and succinctly demonstrates handy viewer settings, such as Pileup display options, and highlights the very helpful tooltips in the Genome Data Viewer (GDV). There’s also a brief blog post on the same topic.

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New release of the Prokaryotic Genome Annotation Pipeline with updated tRNAscan and protein models

A new version of the Prokaryotic Genome Annotation Pipeline (PGAP) is now available on GitHub. This release uses a new and improved version of tRNAscan (tRNAscan-SE:2.0.4) and includes our most up-to-date Hidden Markov Model and BlastRule collections for naming proteins.

Remember that you can submit the results of PGAP to GenBank. Or, if you are still improving the assembly and your genome doesn’t pass the pre-annotation validation, you can use the –ignore-all-errors mode to get a preliminary annotation.

See our previous post and our documentation for details on how to set up and run PGAP yourself.

Try PGAP and let us know how you like it!

Prokaryotic Genome Annotation Pipeline (PGAP) now produces results suitable for submission to GenBank

We are happy to announce that you can now submit your genome sequences annotated by  your own local copy of the standalone Prokaryotic Genome Annotation Pipeline (PGAP) to GenBank.

How does it work? Download PGAP from GitHub, provide some basic information and the FASTA sequences for your genome sequence, and run the pipeline on your own machine, compute farm or the cloud. PGAP will produce annotation consistent with NCBI’s internal PGAP. Submit the resulting annotated genome to GenBank through the genome submission portal, and get an accession back.

As with any other submitted assembly, PGAP-annotated genomes will be screened for foreign contaminants and vector sequences at submission.  Any annotated assemblies that don’t pass may need to be modified. We are developing an automated process to handle these edits!

We are also working on other  improvements to stand-alone PGAP such as a module for calculating Average Nucleotide Identity (ANI) to confirm the assembly’s taxonomic assignment. Stay tuned for new developments!

 

Run the Prokaryotic Genome Annotation Pipeline (PGAP) on your own machine

You can now download PGAP from GitHub and run it on your machine, compute farm or the cloud, on any public or privately-owned genome. PGAP predicts genes on bacterial and archaeal genomes using the same inputs and applications used inside NCBI. This is a great opportunity for you to try it now and send us comments (please use GitHub issues).

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The TIGRFAM collection of protein family Hidden Markov Models moves to NCBI

NCBI has been asked to take over the ownership and maintenance of the TIGRFAM collection of Hidden Markov Models (HMMs), which is widely used for the annotation of prokaryotic genomes. The TIGRFAMs are a collection of curated protein families started in 1998 at The Institute of Genomic Research (TIGR), precursor to the J. Craig Venter Institute (JCVI). This collection is publicly available under a Creative Commons license and downloadable from NCBI. We have already made hundreds of improvements to TIGRFAM names and descriptions and we will continue to make regular updates.\

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Join NCBI at PAG in San Diego, January 12–16, 2019

Next week, NCBI staff will attend the Plant and Animal Genome (PAG) Conference. We have several activities planned, including 1 booth (#223), 4 workshops, 1 talk and 2 posters.

Read on to learn more about what you can look forward to if you’re attending PAG this year. (Note: The listed times are Pacific time.)

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Improved annotation of Streptomyces RefSeq genomes

We’ve completed the RefSeq reannotation of over 1,000 Streptomyces genomes! The genomes were reannotated using the Prokaryotic Genome Annotation Pipeline (PGAP). PGAP detected nearly 100% of ribosomally synthesized and post-translationally modified peptide natural products (RiPP)-encoding genes from known families, despite their small size, using a set of over 30 hidden Markov Models (HMMs) built by RefSeq biocurators. Over 70% (251) of lasso peptides now present in Streptomyces RefSeq genomes (354) were annotated for the first time.

If you are aware of any class of RiPP precursor in Streptomyces that was not found in our recent re-annotation, please contact us through the NCBI Help Desk, and we will add new HMMs to the rules we use to find and annotate RiPP precursor genes.