Consistent protein nomenclature is indispensable for communication, literature searching and entry retrieval. NCBI, the European Bioinformatics Institute (EMBL-EBI), the Protein Information Resource (PIR) and the Swiss Institute for Bioinformatics (SIB) revised and reorganized previous guidelines from UniProt and NCBI. This joint effort produced universal guidelines in nomenclature and protein naming to promote clarity in communication and improve consistency in data retrieval across databases.
These guidelines are exclusively focused on nomenclature, providing rules about universal formatting and protein naming choices; they do not include best practices for identifying or predicting function. They cover usage of language, abbreviations, symbols, punctuation, notation, terms and style. Sources of protein names and options for protein naming are also discussed.
During the 2018 INSDC annual meeting, the three collaborating sequence databases (DDBJ, EBI and GenBank) agreed to recommend these guidelines to their submitters. The Protein Naming Guidelines working group plans to write a peer-reviewed publication about protein naming and to track future changes to this document in GitHub.
As of March 2018, there were 141,000 prokaryotic genomes in the Assembly database. As this database grows, misassigned prokaryotic genomes becomes a serious problem. Taxonomy misassignment can occur through simple submission error or can accumulate as new information adds greater specification to the taxonomic tree.
A paper in the International Journal of Systematic and Evolutionary Microbiology presents the method NCBI scientists used to verify taxonomic identities in prokaryotic genomes. The authors used an Average Nucleotide Identity method with optimum threshold ranges for prokaryotic taxa to review all prokaryotic genome assemblies in GenBank. This method relies on Type strain information and is one outcome of a 2015 workshop involving several important parties in the bacteriology community.
By now, the opioid epidemic is a familiar topic to many Americans. According to the National Institute on Drug Abuse (NIDA), “every day, more than 115 American die after overdosing on opioids.” The National Institutes of Health (NIH) is committed to the fight against opioid misuse and addiction. In a May 2017 address, NIH Director Dr. Francis Collins and NIDA Director Dr. Nora Volkow outlined research priorities for ending the opioid crisis, such as finding new ways to treat opioid addiction and improving overdose prevention and reversal. The NCBI Bookshelf, an archive of books and documents in life science and healthcare, offers a variety of resources related to enacting such solutions.
A study (PMID: 28158543) published in the July 2017 issue of Bioinformatics collects, classifies and analyzes single nucleotide variants (SNVs) that may affect response to currently approved drugs. They identified 2,640 SNVs of interest, most of which occur rarely in populations (minor allele frequency <0.01).
The researchers used protein sequence alignment tools and mined open data from multiple information resources accessed through E-utilities including PubChem Compound (Kim et al., 2016 PMID: 26400175), NCBI Gene (Maglott D, et al., 2014. PMID: 25355515), NCBI Protein (Sayers, 2013), MMDB (Madej et al., 2012 PMID: 22135289), PDB (Berman et al., 2000 PMID: 10592235), dbSNP (Sherry et al., 2001 PMID: 11125122), and ClinVar (Landrum et al., 2016 PMID: 26582918).
Questions, comments, and other feedback may be sent to Yanli Wang.
For the past decade, dbGaP, the database of Genotypes and Phenotypes, has been the worldwide resource for genome-wide data. To celebrate this milestone, NCBI threw a party!
The inaugural article in NLM In Focus’s new series on NLM scientists features Kim Pruitt, PhD. Dr. Pruitt is a staff scientist at NCBI; she heads the Reference Sequence Database, better known as RefSeq.
In the article, Dr. Pruitt shares her career trajectory as well as pearls of wisdom for young scientists.
Click on the picture to read NLM’s profile on Kim Pruitt, PhD.
On August 23, Drs. Stephen Bryant and Evan Bolton received the American Chemical Society (ACS) 2016 Herman Skolnik Award for their work in developing, maintaining, and expanding the National Center for Biotechnology Information’s PubChem database of chemical substances and their biological activities. The award was presented at the ACS 252nd National Meeting & Exposition in Philadelphia.
Figure 1. Drs. Bryant and Bolton receive the American Chemical Society 2016 Herman Skolnik Award.
This post is geared toward fungi researchers as well as RefSeq and BLAST users.
Fungi have unique characteristics that can make it difficult to identify and classify species based on morphology. To address these issues, Conrad Schoch, NCBI’s fungi taxonomist, and Barbara Robbertse, NCBI’s fungi RefSeq curator, in collaboration with outside mycology experts, are curating a set of fungal sequences from internal transcribed spacer (ITS) regions of the nuclear ribosomal RNA genes. This set of standard DNA sequences for fungal taxa not only addresses these difficulties in identifying and classifying fungal species by morphology, but is also essential for analyzing environmental (metagenomics) sequencing studies. The curated ITS sequences, described in a recent article in Database (PMC Free Article), all have associated specimen data and, when possible, are taken from sequences from type materials, ensuring correct species identification and tracking of name changes. This article will show you how to access these ITS sequences and search them using the specialized Targeted Loci BLAST service.
The fungal ITS sequences are a RefSeq Targeted Loci BioProject (PRJNA177353). As you may know, a BioProject is a collection of biological data related to a single initiative; in this case, the goal is to collect and curate fungal sequences from targeted loci – specific molecular markers such as protein coding or ribosomal RNA genes used for phylogenetic analysis.
A series of press releases, including one by Science Publishing, recently announced the first findings of the Avian Phylogenomics Consortium, who analyzed genome sequences and annotation data for 48 bird genomes representing all of the bird taxonomic orders. All of the sequenced genomes, along with any annotation provided by the submitter, are available in NCBI resources including Assembly, Nucleotide, Protein, the Sequence Read Archive (SRA), and BLAST, or from species-specific GenBank genomes FTP directories. RNA-Seq data for some of the bird species can be found in SRA.
With the exception of three very fragmented assemblies, NCBI annotated the genome assemblies submitted by the Avian Phylogenomics Consortium using NCBI’s Eukaryotic Genome Annotation Pipeline, and these annotations are now part of the RefSeq project. The RefSeq project also generated annotations for an additional 6 bird assemblies, for a total of 51 RefSeq genomes. A summary of all the bird genomes that have RefSeq annotation is here.
Figure 1. A selection of the bird genomes with RefSeq annotation. At the top right is a legend describing resource links for each bird genome. Detailed annotation reports, accessible through the “AR” link in the far right column, are available for those genomes annotated in 2014. RefSeq annotation is on organism-specific BLAST pages (the “B” link) and on FTP (the “F” link). Click on the picture to go to the summary table.
The Tasmanian devil (Sarcophilus harrisii), the last remaining large marsupial carnivore, now faces extinction because of a strange and deadly infection, a transmissible cancer known as Transmissible Devil Facial Tumor Disease (TDFTD). In a previous NCBI Insights post, we discussed gene expression data from the tumors that established their neural origin and showed the tumors were likely derived from Schwann cells. In this post, we’ll consider some of the genome sequencing projects in the NCBI databases and explore evidence that the tumor originated in a different individual than the affected animal supporting the idea that the tumor cells themselves are infectious agents. Continue reading