Bioinfo

The Poor Beginners’ Guide to Bioinformatics

What we have – and don’t have...  a computer connected to the Internet (incl. Web browser)  a text editor (Notepad or better)  public databases of genomic sequences  public databases of cDNA + EST  public databases of protein sequences, structures and motifs  money for specialised software packages  public servers capable of (almost) anything we wish to do

Dealing with a sequence: model tasks • basic (DNA) sequence manipulation: restriction analysis, translation… • sequence similarity and pattern/motif searches • gene building: modelling exon-intron structures • protein domain searches,structure analysis • construction and interpretation of sequence alignments

Notes on basic sequence handling  Make sure you have the correct format.  FASTA format is (almost) always correct. >sequencename thisisasequenceinfastaformat

 If not, you can always use raw data.  If things don’t work, check for gaps in sequence, empty lines, and file extension.  BEWARE OF MICROSOFT!

Model tasks continued … • basic (DNA) sequence manipulation: restriction analysis, translation… • sequence similarity and pattern/motif searches • gene building: modelling exon-intron structures • protein domain searches,structure analysis • construction and interpretation of sequence alignments

Defining a gene family… • By overall domain structure FH3?

FH1

FH2

• By domain sequence

• Based on a peptide motif

L-X-X-G-N-X-[ML]-N

Sequence comparison-based searches • Entrez “related sequences”  easy identification of “false starts”  no organism selection

• BLAST/FASTA  all DNA/protein combinations  taxonomy selection possible  statistical data provided  domain structure comparison available  divergent motifs may be missed

Two methods are better than one.

Notes on all sequence comparisons, searches, alignments…  Start with defaults (the authors know what they are doing)…  … BUT don’t be afraid to vary the parameters  Chose a reasonable scoring matrix: Distant sequences: low BLOSUM, high PAM Closely related sequences: low PAM, high BLOSUM

Motif-based searches  sensitive  no statistics  only protein databases can be searched

• TAIR PatMatch  Arabidopsis - specific  Problematic user interface

• ISREC - INSECTS  admirable technology  access to SwissProt and TrEMBL  no organism selection

Model tasks continued … • basic (DNA) sequence manipulation: restriction analysis, translation… • sequence similarity and pattern/motif searches • gene building: modelling exon-intron structures • protein domain searches,structure analysis • construction and interpretation of sequence alignments

Some genes are more alike than others… • A number of splicing prediction servers available • Agreement of different methods is a good sign but no absolute measure • Always align ESTs if possible • Beware of non-conventional intron boundaries (GC-AG instead of GT-AG) • Plant data for transcription start/factor binding sites prediction are limited

Model tasks continued … • basic (DNA) sequence manipulation: restriction analysis, translation… • sequence similarity and pattern/motif searches • gene building: modelling exon-intron structures • protein domain searches,structure analysis • construction and interpretation of sequence alignments

Searching for known domains/motifs

• Searching for PROSITE patterns – allowing ambiguities

• PROSITE and Pfam profile searches • SMART, CDsearch (domains and more)

Predicting protein localisation

• predicting signal peptides/anchors • 2 methods available • possibility to predict organelle localisation

• transmembrane segments prediction

Model tasks continued … • basic (DNA) sequence manipulation: restriction analysis, translation… • sequence similarity and pattern/motif searches • gene building: modelling exon-intron structures • protein domain searches,structure analysis • construction and interpretation of sequence alignments

Alignment: “manual” or automated?

 locally installed, free, for Mac and PC  interactive domain definition  statistical data provided  may produce falsepositive blocks (read the on-line manual!)

 “objective” results  a number of servers available  recommended for wellconserved proteins  empiric parameters (e.g. gap penalties)  bad for divergent sequences

Phylogenetic analyses  Two methods are better than one.  Your phylogeny cannot be better than your alignment.  Gaps are no data.  Allways do bootstrapping (100-500 cycles)  Certain questions cannot be answered from an unrooted tree.

Points to take off... • go to the Bioinformatics page http://www2.rhul.ac.uk/~ujba110/Bioinfo.htm

• select your exercise (A,B,C,D,E) • … and enjoy it! If you mean it seriously: • create your own bookmarks (seed provided on the course web page)