Overview

The CMR was previously funded by two grants, one from the U.S. Department of Energy (DOE) and one from the National Science Foundation (NSF). It is currently partially funded by a Microbial Sequence Center (MSC) grant from the National Institute of Allergy and Infectious Diseases (NIAID)

Updates

At JCVI we are continuously adding newly published prokaryotic genomes to our CMR database. As new genomes not sequenced at JCVI become available at GenBank we load the genome and sequencing center annotation into an individual organism database and perform JCVI automated annotation. Once the JCVI automated annotation is complete, we add the genome to an internal version of the CMR database which is not visible from the CMR web site.

All of the proteins in the CMR are routinely blasted against one another to produce the "All v/s All" data. Many of the tools on the CMR depend on the results from the All v/s All searches. Once several new genomes have been added to the internal CMR database we run All v/s All searches. After the All v/s All searches are complete we push the new data to the external CMR database, where it is visible from the CMR web site.

Because of the amount of time it takes to prepare a genome for inclusion on the CMR, as well as the amount of time needed to perform the All v/s All searches, genomes must be present at GenBank at least two months prior to the date the external CMR is updated to be included in the update. As we approach an update a more specific date will be posted. Newly published JCVI genomes will be made available on the CMR web site on the date of publication.

Click here for our Update Schedule.

The CMR Database

Availability

Common CMR Terms

• expect=.001 - the evalue cutoff we can have, the range is 0.001-1000 (default is 10) lower numbers are more stringent
• cutoff=120 - the cutoff score for reporting 'HSP's, the range is 50-120 (default value is calculated from the EXPECT value) higher numbers are more stringent
• alignments=500 - gives us at most 500 different accessions in the btab file (default is 250)
• descriptions=500 - gives us at most 500 different accessions in the alignment file (default is 500)
• filter=seg+xnu - added filters. These filters mask off segments of the query sequence that have low compositional complexity, as determined by the SEG program of Wootton & Federhen (Computers and Chemistry, 1993), or segments consisting of short-periodicity internal repeats, as determined by the XNU program of Claverie & States (Computers and Chemistry, 1993). Filtering can eliminate statistically significant but biologically uninteresting reports from the blast output (e.g., hits against common acidic-, basic- or proline-rich regions), leaving the more biologically interesting regions of the query sequence available for specific matching against database sequences.

All v/s All Protein Blast Searches
All of the proteins in the CMR are routinely blasted against one another. We call these the "All v/s All" searches. When a new genome is added to the database the all v/s all searches are re-run. The information from the All v/s All blast searches is displayed thoughout the CMR.

BER (Blast-Extend-Repraze) Searches
The Smith-Waterman alignment (what we call Blast-Extend-Repraze or BER) is computed dynamically on the website when the user selects the results to see in the alignment. Here is a description of the BER/Smith-Waterman process we use to generate the alignments for the website on the fly:

The reference protein is the protein for which the blast results are being shown. If you go to the BA0058 Gene Page and click on "Protein vs. All Alignment" you'll see that in this example the reference protein is BA0058. The user then selects the comparison proteins for which they wish to see the alignments (the proteins in the table for the above example), these proteins make up the mini-database of comparison BLAST hits. Then a modified Smith-Waterman alignment (Smith, 1981) is performed on the reference protein against the mini-database of comparison BLAST hits. In order to identify potential frameshifts or point mutations in the sequence, the nucleotide gene of the reference protein is extended 300 nucleotides upstream and downstream of the predicted coding region. If significant homology to a comparison protein exists and extends into a different frame from that predicted, or extends through a stop codon, the program will continue the alignment past the boundaries of the predicted coding region.

NCBI COGs
COGs or Clusters of Orthologous Proteins are phylogenetic classifications of proteins encoded in complete genomes. COGs were delineated by comparing protein sequences encoded in 21 complete genomes, representing 17 major phylogenetic lineages. Each COG consists of individual proteins or groups of paralogs from at least 3 lineages and thus corresponds to an ancient conserved domain. For more information, visit the COG Home Page at NCBI.

Enzyme Commission Number
Enzyme Commission Numbers or EC#s are numbers assigned to enzymes that reflect their function. For more information and a complete list of all EC#s, visit the Enzyme Nomenclature Page.

MUMmer
MUMmer or the Whole Genome Alignment Tool is a system for aligning whole genome sequences. Using an efficient data structure called a suffix tree, the system is able rapidly to align sequences containing millions of nucleotides. It is fully described in: A.L. Delcher, S. Kasif, R.D. Fleischmann, J. Peterson, O. White, and S.L. Salzberg. Alignment of whole genomes. Nucleic Acids Research, 27:11 (1999), 2369-2376.

The CMR Database: The Omniome
The Omniome is the database that stores all of the information that is displayed in the Comprehensive Microbial Resource. It contains the sequence and annotation of each of the completed genomes as well as associated information about the organisms (such as taxon and gram stain pattern), the structure and composition of their DNA molecules (such as plasmid vs. chromosome and GC content), and many attributes of the protein sequences predicted from the DNA sequence (such as pI and molecular weight). In the CMR the user can query the Omniome about all of the genomes at once or any subset of them. Annotation from both the sequencing center which sequenced the genome and automated annotation from JCVI are included for each genome not sequenced at JCVI. In addition there are prerun searches of all of the proteins in the Omniome against themselves to determine the closest homolog in the completed set of genomes. There are also prerun analyses of many of the protein attributes available for viewing. The CMR can be used to mine the completed genomes stored in the Omniome in ways not before possible with single genome databases. This will result in the ability of users to ask more precise and meaningful questions and further the progress of genome research.

JCVI Annotation

SOPs

• Gene Prediction SOP
• Homology Searches SOP
• Automated Annotation SOP
• Manual Curation SOP
• Overlaps SOP
• Start Site Curation SOP
• Short ORF SOP
• Frameshift SOP

Gene Finding

Searches

AutoAnnotate

Levels of Database Match

1.  Confident assignment: indicated by a specific name and gene symbol
   
   • The protein translation has a good database match to a protein of known function. Both pairwise and multiple protein sequence alignments reveal high degree of identity/similarity (typically >35% identity) along  the entire length of the protein.  There may be a match to a highly specific (i.e., 'equivalog' isology type) HMM.  Active sites, substrate or cofactor binding sites, or motifs that are characteristic of a protein should be conserved. Note: we use the Escherichia coli gene symbol when available.
     

We annotate each gene by assigning as many descriptors as are relevant.  Descriptors include at minimum a common name, role category, and Gene Ontology (GO) 'fucntion' and 'process' terms for each gene, but may also include a gene symbol, an Enzyme Commission number, and public comments.  In
2. Function uncertain: indicated by "putative" or 'homolog' in the name (gene symbol optional)
   
   • If we think the gene is almost certainly performing the function the name implies, but are less than fully confident, we precede the name with "putative". In this case, the evidence for function is very much like that for 'confident assignment', except for one or two weak lines of evidence, e.g.,  the percent identity/similarity or HMM score is marginally lower than for confident assignment.
     
     
   • A different type of 'function uncertain' assignment is indicated by the use of 'homolog' in the common name. The assignment can arise from two situations. In the first, sequence homology is very strong, but unlike a ‘putative’ match, we do NOT believe the query protein has the same function as the match. This might be because some critical piece of evidence is absent (e.g., non-conservation of catalytic residues in an enzyme), or because the function is not predicted to exist in this particular organism (e.g., photosynthetic enzyme matches in a non-photosynthetic organism).  In the second situation,  evidence is too weak to apply 'confident' or putative names, and there are also no family names available.  However, based on sequence homology there may be important information which would be lost if we called the gene product just a 'conserved hypothetical' protein, e.g., the matching protein in a pathogen is known to be toxic to host organisms, but has no other functional characterization. In this case we could use the matching protein's name but add 'homolog' to it, and apply descriptors appropriate for a protein of unknown function and process.
     
     
   • Note that while using 'homolog' to denote non-conserved function has been a long time-practice of JCVI annotators, using 'homolog' to capture important information that would otherwise be lost is a practice adopted in 2005. The criteria for 'putative' annotation have also been tightened.  Therefore it is likely that some older annotations that were called 'putative' would be called 'homolog' under the new naming criteria.
     

3. Specific assignment not possible, but protein family or domain assignment is possible: indicated by protein family name or domain name.
   
   • When the best (or only) annotation evidence indicates membership in a defined family, rather than orthology to a specific gene, we use family names defined in TIGR or Pfam HMMs, curated databases such as SwissProt, or in the literature.
   
   
   • When the extent of sequence homology is limited to a defined protein domain (usually modelled as an HMM), rather than a defined family, we may use the domain name. Since in the literature domains sometimes are used to define a family, the distinction between such names is not rigid.
   
   
   • Note that the cellular function or process associated with a protein family or domain may be experimentally defined to some degree; however, they can also be completely unknown, in which case the family or domain name connotes nothing more than sequence homology.  This will be reflected in the role categories and GO term descriptors assigned to the protein.
     

4. No evidence of function, defined family, or defined domain: indicated by the name 'conserved hypothetical protein'
   
   • These protein translations only produces full-length matches to conceptual translations in other species, i.e.,  there are no experimentally characterized matches, HMM matches, or family names that can be reasonably derived from the evidence.  Exceptions are made when there is a match to a lipoprotein motif or detection of substantial hydrophobic regions; these are called 'putative lipoprotein' and 'putative membrane protein', respectively.
     

5. No database matches: indicated by the name 'hypothetical protein'
   
   • These protein translations have no significant sequence similarity to any characterized or uncharacterized genes. In these cases, the open reading frame was identified by the gene-finding algorithm but there is no additional evidence to indicate whether it is or is not an actual gene.  
     
   • 
     

Disrupted reading frames

1. authentic frameshifts/authentic point mutations: indicated by  'authentic frameshift' or 'authentic point mutation'
   
   • When an ORF is disrupted by a either a single confirmed frameshift or point mutation, we simply add this information after the common name.
     

2. multiple/mixed frameshifts and point mutations: indicated by 'degenerate'
   
   • When an ORF is disrupted by multiple frameshifts or a mixture of frameshifts and point mutations we assume that the ORF is not functionally expressed. and we denote this with the term "degenerate" after the common name.
     

3. interruptions: indicated by 'interruption'
   
   • Interruptions are cases in which conserved amino and carboxyl terminal portions of an ORF are separated by some other sequence, such as a transposon. These are labelled with "interruption-N" and "interruption-C" after the common name.
     

4. truncations: indicated by 'truncation'   
   
   • When a significant segment of the ORF is missing from the N- or C-terminal end - enough so that we believe that it is no longer functionally expressed - we add 'truncation' to the common name.
     

5. programmed frameshifts: indicated by 'programmed frameshift'
   
   • When an ORF contains an in-frame termination codon and a naturally-occurring frameshift prior to the termination codon regulates translation of the ORF, we add "programmed frameshift" to the common name.

6. internal deletions: indicated by 'internal deletion'
   
   • An internal deletion is the absence of a region of DNA in the interior of an ORF relative to its orthologs. Internal deletions are shorter than interruptions, but long enough such that we expect the deletion to impair function.  We denote them by adding 'internal deletion' to the common name.
     

7. fusions: indicated by 'fusion'
   
   • Two proteins which have been fused into one reading frame by a deletion event in the genome are denoted by 'fusion' in the common name.
     
   • 
     
8. selenocysteine-containing proteins: indicated by 'selenocysteine-containing'
   
   • In certain organisms the 'stop' codon TGA encodes the amino acid selenocysteine. The genome must contain a selenocysteine-tRNA and the enzyme selenide, water dikinase. Proteins which meet these criteria have 'selenocyteine-containing' added to their common names.
     

CMR Extras