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Project Proposals

Project Proposals. Due Monday Feb. 12 Two Parts: Background—describe the question Why is it important and interesting? What is already known about it? Proposed Work What will you do? How will you do it? Include references and figures as needed. Phylogeny.

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Project Proposals

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  1. Project Proposals • Due Monday Feb. 12 • Two Parts: • Background—describe the question • Why is it important and interesting? • What is already known about it? • Proposed Work • What will you do? • How will you do it? • Include references and figures as needed

  2. Phylogeny • Reread background papers from weeks 3 &4 • Desulc et al • Holder and Lewis

  3. The twenty amino acids

  4. Protein Weight Matrices

  5. BLOSUM45 BLOSUM62 BLOSUM90 PAM 250 PAM 160 PAM100 More Divergent Less Divergent Two Main kinds of weight matrices PAM (Point Accepted Mutation) Based on explicit evolutionary model. Based on mutations observed thoughout a global alignment (includes both highly conserved and highly mutable regions) of a small protein dataset BLOSUM (Blocks Substitution Matrix) Based only on highly conserved regions in series of alignments forbidden to contain gaps. Sensitive for local alignment of related sequences. Based on larger dataset than PAM. BLOSUM62 is the BLASTP default

  6. Other Types of BLAST • MegaBLAST (nt) • Mega BLAST uses the greedy algorithm for nucleotide sequence alignment search. Optimized for aligning sequences that differ slightly as a result of sequencing or other similar "errors". Also able to efficiently handle much longer DNA sequences than the blastn program of traditional BLAST algorithm. • Discontinous MegaBLAST (nt) • Designed specifically for comparison of diverged sequences, especially sequences from different organisms, which have alignments with low degree of identity, where the original Mega BLAST is not very effective. • See Also, MUMMER at TIGR

  7. Other BLAST options • Search for short nearly exact matches • (nt or aa) • Special page with altered parameters • Expect value has been increased • word size decreased to optimise for short hits which generally score a large E value • For proteins a different scoring matrix used, optimized for smaller evolutionary distances

  8. Low complexity sequence • Regions of biased composition including homopolymeric runs, short-period repeats, and more subtle overrepresentation of one or a few residues • Examples: AAATAAAAAAAATAAAAAAT or PPCDPPPPPKDKKKKDDGPP • Filters are used to remove low-complexity sequence because it can cause artifactual hits • Filters result in strings of Ns or Xs substituted in your query • Without a filter- • Some hits may be reported with high scores only because of the presence of a low-complexity region. • Usually not the result of homology shared by the sequences. • Rather, it is as if the low-complexity region is "sticky" and is pulling out many sequences that are not truly related.

  9. Phylogenetic Profiling Pattern of presence or absence of genes across genomes Idea: proteins that function in the same cellular context frequently have similar phylogenetic profiles

  10. Environmental Genomic Datasets Sargasso SeaStation AlohaAcid Mine DrainageWhale Fallsludgesoilsmarine viromesHuman Gut

  11. Global Ocean Survey: phase I Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis CAMERA Online since Jan. 23rd!

  12. Today’s Lab Use IMG (http://img.jgi.doe.gov/cgi-bin/pub/main.cgi) to explore precomputed homologs for your gene of interest genomic neighborhoods for your gene of interest phylogenetic profile of your gene of interest genes that fit a specific phylogenetic profile of a subset of genomes of interest to you Register as a CAMERA user http://cameradev.calit2.net/index.php See if you can find homologs of your gene of interest in one of available databases

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