For Today

• read the Wikipedia entries on PSSMs, HMMER, , and at least skim through the entry for hidden Markov models

For Wednesday:

• Read box on PSI blast below.
• Bring one question to class regarding selection evolution of modern humans.
• Ponder the possibility of complexity arising as a consequences of neutral processes (constructive neutral evolution). Know at least one example?

For Friday:

• read the introduction and the caveat section of the PSI Blast tutorial
• For those interested to learn about a popular alternative to PSI Blast:
  Read through http://en.wikipedia.org/wiki/HMMER and http://en.wikipedia.org/wiki/Hidden_Markov_model
  In case the principle of hidden profiles remains cryptic and for the difference between PSIs and Hmmer, you can try the section in the HMMER manual on "What profile HMMs are".
  (You should be able to address the question why this approach may not be optimal for structural RNAs.)

Discuss Takehome Exam #7

Slides for today on positive selection/ selective sweeps and PSI blast.

PSI BLAST example PSI-blast provides an enormous advantage over normal blast in the detection of distantly related sequences.  It only works, if some closely related sequences are already available, but if this is the case it finds a lot of other distantly related sequences.  The NCBI page describes PSI blast as follows: Position-Specific Iterated BLAST (PSI-BLAST) provides an automated, easy-to-use version of a "profile" search, which is a sensitive way to look for sequence homologues. The program first performs a gapped BLAST database search. The PSI-BLAST program uses the information from any significant alignments returned to construct a position-specific score matrix, which replaces the query sequence for the next round of database searching. PSI-BLAST may be iterated until no new significant alignments are found. At this time PSI-BLAST may be used only for comparing protein queries with protein databases.  A diagram giving an overview on the PSI-blast procedure is here. The results of a normal blast search are aligned and a pattern of conserved residues is extracted from the alignment.  This pattern (the Position Specific Scoring Matrix) is used as query for the next iteration.  An important parameter to adjust is the E-value threshold up to which matches are included in the alignment and pattern extraction.  At higher iterations a PSI blast profile can be corrupted and false positives are identified with significant E-values.   I.e., in a traditional blast search one can be quite certain that a match with an E-value of 10^-13 represents a homologue; this is not clear with PSI blast.  Test studies indicate that profile corruptions are likely after more than 5 iterations. On the positive side: there are many fewer false negatives with PSI blast than with normal blast. False negatives: Homologous sequences that are not detected -- less in PSI blast than in normal blast False positives: Non-homologous sequences that are listed as matches -- very few in normal blast - possible in PSI blast after profile corruption The "problem" is that the E-value reported in a PSI-blast search represents the match with the profile, not with the original sequence!! PSI BLAST Example Query sequence: >gi|18892111|gb|AAL80306.1|[18892111] Pfu VMA intein (including -1 and +1 extein residues) KCVDGDTLILTKEFGLIKIKDLYEKLDGKGRKTVEGNEEWTELEEPITVYGYKNGKIVEIKATHVYKG ASSGMIEIKTRTGRKIKVTPIHKLFTGRVTKDGLVLEEVMAMHIKPGDRIAVVKKIDGGEYVKLDTSS VTKIKVPEVLNEELAEFLGYVIGDGTLKPRTVAIYNNDESLLKRANFlAMKLFGVSGKIVQERTVKAL LIHSKYLVDFLKKLGIPGNKKARTWKVPKElLLSPPSVVKAFINAYIACDGYYNKEKGEIEIVTASEE GAYGLTYLLAKLGIYATIRRKTINGREYYRVVISGKANLEKLGVKREARGYTSIDVVPVDVESIYEAL GRPYSELKKEGIEIHNYLSGENMSYETFRKFAKVVGLEEIAENHLQHILFDEVVEVNYISEPQEVYDI TTETHNFVGGNMPTLLHNT Blast page Use SWISSPROT Check format for PSI-blast Check inclusion limit Turn on Filter for low complexity Increase number of reported matches Point out manual selection of sequences to be included in profile Use PSSM to search something else (e.g., individual genomes (here))

Goals class 23:

• Know that the dN/dS>1 approach can be used to detect positive selection and that this approach is often difficult to apply in case the alignment is unreliable (which results in more non-synonymous substitutions).
• Know that the dN/dS<1 approach to detect purifying selection may not always reflect a selection for function.
• Understand that selection can act at the level of the gene (selfish genetic elements), at the level of of the individual in the population, and possibly through the competition between populations and communities.
• Understand the link between positive selection and selective sweep.
• Know different approaches of how selective sweeps can be detected.
• Know about archaic admixtures to modern human populations
• Understand the mitochondrial Eve and Y chromosome Adam concept, and why this does not work for other genes.