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DOT PLOT Daniel Svozil. Software choice source: Bioinformatics for Dummies.

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Presentation on theme: "DOT PLOT Daniel Svozil. Software choice source: Bioinformatics for Dummies."— Presentation transcript:

1 DOT PLOT Daniel Svozil

2 Software choice source: Bioinformatics for Dummies

3 Dotlet Learn by example – use the sequence from the Repeated domains

4 In this case, the darker the pixel, the lower the score. There will be a large number of pixels with low scores and only a few ones with high scores. Tune the grayscale in order to make the background noise (low scores) disappear and the similar regions stand out more clearly. To do this, use the histogram window. This represents the frequency of each score, over all the pixels, on linear (blue) and logarithmic (purple) scales. lowest possible score on the left and the highest on the right If the sequence has some similarity, there will be a smaller peak of higher scores. Semi-logarithmic plot makes it even more visible.

5 With the scrollbars below and above the histogram, respectively, bring the lower threshold just past the first peak, and the higher threshold just past the second peak. Now, the background noise has disappeared from the dots window, and the similar regions stand out more clearly.

6 Well matching residues – blue. The cursor can also be moved with the keyboard with the arrow keys, and with ' ' (down right), '[' (up right), and ']' (down left). Now play with all sequences in Dotlet exampes section, read the comment and try to understand: http://myhits.isb-sib.ch/util/dotlet/doc/dotlet_examples.html

7 Getting the right window size Long windows = clean plots. The size of a window should be within the same range as the size of the elements you’re looking for. For instance, if you’re looking for conserved domains in proteins, a size of 50 amino acids or higher is appropriate. Shorter windows are more sensitive but bring some noise with them. Start with a large window and narrow it a little until the signal you’re looking for appears.

8 More of Dotlet What is the UniProtKB database? What are the UniProtKB/Swiss-Prot and UniProtKB/TrEMBL? What is the difference between them? Using Dotlet, compare following two Uniprot sequences: P05049 (1 st sequence) and P08246 (2 nd sequence). Are these sequences homologous? What is the function of P05049? P05049 is a serine protease. Would you run a wet lab experiment to check the protease activity of P08246? You should check if these two sequences are homologous in the serine protease region. Do you see some homologous regions on the dotplot?

9 Working with a single DNA sequence

10 Removing vector sequences Contamination from your own vector sequence (as a responsible scientist, you’re expected to have this information) – you may search for the vector sequence you expect Cross-contamination by somebody else’s vector – search not only for the sequence you expect, but also for other possible vector sequences. Before working with your DNA sequence, you should always clean it with e.g. NCBI VecScreen http://www.ncbi.nlm.nih.gov/VecScreen/VecScreen.html http://www.ncbi.nlm.nih.gov/VecScreen/VecScreen.html Basically, it performs a blastn search against UniVec – database of vector sequences

11 VecScreen Sources of contamination - http://www.ncbi.nlm.nih.gov/VecScreen/contam.html http://www.ncbi.nlm.nih.gov/VecScreen/contam.html Try sequence1.txt "No significant similarity found“ - a good news, indicates that the sequence does not contain any vector contamination sequences. sequence2.txt

12 the query sequence matches three vector sequences Let’s say we know the vector used for cloning: pCR2.1-TOPO. Which sequence would you remove? Remove this sequence and check the results on the cleaned sequence.

13 Clean sequence3.txt. What is the result? Such a sequence is generally considered as the esult of a chimeric clone – i.e. clone consisting two sequences. In this case, throwing it away is the safest thing to do! In sequence4.txt is a sequence you cloned in the vector pUC19. Is it contaminated? How would you clean it? VecScreen reports a strong match with the lactose operon genes from E. coli. Not from pUC19! However, this is ok as most commercial vectors are derived from the same initial natural plasmid and E. coli constructs. Their sequences are identical, and UniVec matches are reported in the ordedr they appear in the database. http://www.ncbi.nlm.nih.gov/VecScreen/Interpretation.html

14 Restriction map It is possible to cut DNA sequences using restriction enzymes. Each type of restriction enzyme recognizes and cuts a different sequence: EcoR1: GAATTC BamH1: GGATCC There are more than 900 different restriction enzymes, each with a different specificity The restriction map is the list of all potential cleavage sites in a DNA molecule

15 Restriction map To compute a restriction map is not that difficult. All you need to do is to look for exact matches of a given restriction-enzyme site within your sequence. Enzymes and sites are in the REBASE database - http://rebase.neb.com http://rebase.neb.com Nebcutter - http://tools.neb.com/NEBcutter2/http://tools.neb.com/NEBcutter2/ Webcutter - http://rna.lundberg.gu.se/cutter2/http://rna.lundberg.gu.se/cutter2/ VIRS - http://bis.zju.edu.cn/virs/index.htmlhttp://bis.zju.edu.cn/virs/index.html Try to construct a restriction map of the sequence5.fasta.

16 PCR primer design DNA polymerase needs a template can only extend an existing piece of DNA (primer) always moves in the 5’ → 3’ direction Steps of PCR denaturation – 94°C annealing – 60°C extension – 72°C Heat Cool

17 PCR primer design DNA polymerase needs a template can only extend an existing piece of DNA (primer) always moves in the 5’ → 3’ direction Steps of PCR denaturation – 94°C annealing – 60°C extension – 72°C

18 PCR primer design DNA polymerase needs a template can only extend an existing piece of DNA (primer) always moves in the 5’ → 3’ direction Steps of PCR denaturation – 94°C annealing – 60°C extension – 72°C

19 Primers

20

21 GC content Primers with a 40-60% GC content ensure stable binding of primer/template. The presence of G or C bases at the 3′ end of primers (GC clamp) helps to promote correct binding at the 3′ end due to the stronger hydrogen bonding of G and C bases. However, strings of G and of C can form internal, non-Watson-Crick base pairs that disrupt stable primer binding. Generally, sequences containing more than three repeats of G or of C in sequence should be avoided in the first five bases from the 3′ end of the primer. A short run of G’s at or near the 5′ end of a primer will not disrupt stable binding because the 5′ positioning does not lead to involvement in disruptive secondary structures. It is best to select primers with a random base distribution.

22 Primers no secondary structures Presence of the primer secondary structures produced by intermolecular or intramolecular interactions can lead to poor or no yield of the product. e,g, hairpins, self dimers, cross dimers It is desirable to design specific primer pairs which do not assume secondary structures during the reaction. AutoDimer - screens primers for primer-dimer and hairpins http://www.cstl.nist.gov/div831/strbase/AutoDimerHomepage/AutoDim erProgramHomepage.htm http://www.cstl.nist.gov/div831/strbase/AutoDimerHomepage/AutoDim erProgramHomepage.htm source: http://www.premierbiosoft.com/tech_notes/PCR_Primer_Design.html

23 PCR Primer Design Pick some sequence from NCBI nucleotide (<1000 bp) and play with the primer design tool Primer3 – from http://biotools.umassmed.edu http://biotools.umassmed.edu After you’ve got your primers, you must verify they will not hybridize anywhere except you intend them to hybridize. e.g. primer sequences are not outside the gene you’re interested in or primers do not resemble a frequent repeats in DNA Technique for avoiding this problem: BLAST searches against the vector sequences, the genome sequences, their most common repeats.

24 PCR Primer Design PrimerBLAST at NCBI - http://www.ncbi.nlm.nih.gov/tools/primer-blast/ http://www.ncbi.nlm.nih.gov/tools/primer-blast/ It uses Primer3 to design PCR primers and then submits them to BLAST search against user-selected database. The BLAST results are then automatically analyzed to avoid primer pairs that can cause amplification of targets other than the input template.


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