Agouron/University of Hawaii Summer Course

Databases & web resources for analyzing and comparing genomic and metagenomic sequences

Objectives: 1) Explore the variety of genomic databases and tools currently available for gene and genome analyses and comparison.    2) Learn about the current limitations in gene identification and genome analyses, especially in the context of the “flood” of new environmental genomic data;   3) Gain a bit of some practical hands-on experience using web-based tools for ab initiio gene calling,  gene identification, pathway analyses, and genome comparisons.  

Introduction:
 The first complete microbial genome sequence, that of Haemophilus influenza, was reported in 1995.  Over the past decade that number has increased to the point where soon thousands of complete or near-complete genome sequences will soon become available.   In addition, the number of ribosomal RNAs (still the “gold standard”  for phylogenetic identification) currently numbers in the tens of thousands,   Besides whole genomes,  and ribosomal rRNA surveys, environmental “functional gene surveys”  continue to increase in number and volume.   Given the constantly decreasing costs of sequencing, and improved sequencing technologies,  the amount of sequence data is expected to continue to increase exponentially.    New technologies are soon likely to include single molecule sequencing strategies, which will impact the field even more greatly.  What tools are currently available for genome sequence comparisons ?   How is the application of these technologies to environmental science and oceanography likely to change in the future, and change the playing field ?  What new types of databases, datafields, and metadata, are likely to be required for the new era of ecologically oriented  molecular sequence inquiries and molecular ecology, oceanography and microbial community genomics?   We won’t answer all these questions in one lab/discussion session, but we’ll explore them.  In addition, we’ll take a look at, and  try and implement, some of the currently available we resources and tools for gene and genome characterization, identification and analysis.

Logistical plan:
Well first briefly overview the intersection between microbial oceanography and  current approaches in genomic analyses, including  ab initio gene finding, similarity-based gene finding/identification approaches, comparative genome analyses and  databases.  We’ll also discuss where the future seems to be headed with regard to microbial oceanography and comparative community genomic analyses.   The exercises below are provided to get you started on a few of the different genomic and  metagenomic sites.  We will be spending more time explicitly in exploring and using the MG-RAST and CAMERA resources with Station ALOHA and other metagenomic datasets.

If you haven’t explored any of the below yet, its worth a look at some point ….

INTRODUCTORY EXERCISES
1.  If you have never used NCBIs site or Genbank, go there first.

http://www.ncbi.nih.gov/

Click on BLAST
Click on nucleotide_blast   (nucleotide query versus nucleotide database)
Paste in the sequence “genbank_nuc.fna” in the Entry Query box
Select nr/nt under “Choose search set”  databases
Click on “optimize for somewhat similar sequences (blastn) 
Click BLAST and wait and observe the result
A new screen will pop up – hit format and wait for the result
What organism appears to encode the most similar sequence ? 

Go back to the BLAST Home page
Click on blastx    (translated query versus protein database)
Paste in the genbank_nuc.fna sequence
Leave the database setting at “nr”  (non-redundant protein)  database
Observe your result.  What gene does this DNA sequence appear to code for ?  What function it most likely encode, and in what pathway is it likely involved in ?
 
If you haven’t played with or seen PubMed, go to NCBI homepage and scoll search to PubMed
Type in Karl D, or your favorite authors and click ‘go’
Check especially the Links hypertext to the right.  This pulls down a scroll down bar that can take you directly to sequences submitted with the specific citation.

2. If you have never seen the process of ab initio gene calling and want to, go to the Softberry site.

http://www.softberry.com/all.htm

Click on FGENESB - Operon and Gene finding in Bacteria

Paste in the DNA sequence softberry_4E07.fna
Select “Archaea_bacterial generic” for the “organism”  (precomputed HMM model)

Click “process” – observer the result.
Copy the called genes (starting with >Gene 1, and past into a text file for later processing.

3. JGIs  Integrated Microbial Genome (IMG) genome exploration tools

Go to http://img.jgi.doe.gov/cgi-bin/pub/main.cgi

Click on Find Genomes
Click on “View Phylogenetically” button at bottom of list
Click on “Clear All”
Scroll down to Bacteria, click on “All”
Scroll to bottom of page and click “Save Selections
Scroll to top of page and Click “Find Genes”
Type in “rhodopsin” in the keyword box, and click “Go”
Select a few hits (Anabaena sp. PCC 7120, Exiguobacterium sp. 255-15 , Kineococcus radiotolerans SRS30216, Pelagibacter ubique HTCC1062, Rubrobacter xylanophilus DSM 9941)
Click “Add Selected to Gene Cart”
Click “Show neighborhoods” and observe your result.  The gene you searched for is shown in its chromosomal context, in red.  Mouse over to see if there are any shared genes in the genomes….

Go back to the previous page, and click “Show phylogenetic profiles”
These profiles are very useful for exploring gene distributions across taxa.

IMG contains only whole genomes right now, but is a very useful tool.  To explore it, go to a particular task like “Find Genes” and then click on a topic in the task bar below, like BLAST.  This allows you to blast across the IMG Genomes.  Many of the Search functions allow you to select subsets of your genes and place them in a gene cart, for later download or analyses, light profiling or alignment.

A “metagenomic” site has beendeveloped at JGI, that is also very worth exploring: http://img.jgi.doe.gov/cgi-bin/m/main.cgi

4.  Login into the CAMERA website. 
http://camera.calit2.net/	

You will need to register, and make an account to get started.
Currently CAMERA is used and useful for performing large BLAST jobs against metagenomic datasets, and doing “fragment recruitment” : e.g., lining up individual metagenomic reads against a reference genome, to get an idea of the distribution and abundance of that organism and its genes within and among different samples.  A recently added feature allows you to upload your own genome sequence or fragment, and perform a recruitment analysis against all the metagenomic datasets in CAMERA.   See the html Help pages provided  in this folder to get started.  The best way to learn is to play around with your favorite organisms, genes,  and sequences, and see what you can learn.

A new iteration of CAMERA, CAMERA 2.0 will be released this summer.  This will enable relational database searches across samples, sequences and metadata.  It will also enable users to construct, implement, store and share their own metagenomic analytical work flows employing tools incorporated in CAMERA.

USEFUL LINKS
MARINE MICRO SPECIFIC

https://research.venterinstitute.org/moore

http://www.moore.org/microgenome/

http://egg.umh.es/micromar/

http://www.megx.net/
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GENERIC TOOLS AND MICROBIAL GENOME/Metagenome EXPLORATION

http://metagenomics.nmpdr.org/			MG-RAST

http://camera.calit2.net/				CAMERA

http://www.softberry.com/all.htm			Gene finding

http://www.ncbi.nih.gov/				(NCBI)

http://img.jgi.doe.gov/cgi-bin/pub/main.cgi		(IMG)

http://img.jgi.doe.gov/cgi-bin/m/main.cgi 	(IMG/M)

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RIBOSOMAL RNA DATABASE AND PROBE RESOURCES AND TOOLS
http://greengenes.lbl.gov/cgi-bin/nph-index.cgi

http://www.microbial-ecology.net/probebase/

http://www.arb-home.de/

http://rdp.cme.msu.edu/
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TARGETED PROTEIN DATABASES AND SEARCH TOOLS ONLINE
http://nar.oxfordjournals.org/content/vol34/suppl_1/index.dtl

http://www.genome.jp/kegg/

http://www.ncbi.nlm.nih.gov/COG/

http://pfam.sanger.ac.uk/

http://www.ebi.ac.uk/interpro/

http://string.embl.de

Gene Ontology (GO;  not a database - rather, sequence semantics !)
http://www.geneontology.org/GO.doc.shtml