1. Genome Center of Wisconsin, UW-Madison
Making Sense of DNA and protein sequence analysis tools (course #2)
Dave Baumler
Genome Center of Wisconsin, UW-Madison

2. Todays session an overview
You have been given a 5 KB piece of DNA sequence
GeneScan: find any exons in the DNA sequence and generate a predicted protein sequence
ScanProsite: scan the protein sequence for domains/motifs/patterns found in the prosite database
BLASTP: run a BLASTP search against the Swissprot database find some of the best matches (hits) and copy each protein sequence into a word doc for the alignment
MultAlin: conduct protein sequence alignments from the BLASTP search

3. In this session you will try out 4 different tools, Lots of other tools exist

4. Where are the coding regions?
TCAGCGAAGATGAGATAGTTTTTAAAGGTGGGATTTCCCCACCTTTAAAAAGCGAGAAGTCCCGGTTTTAAAGAGGAGTAAAATCCTCTTTTTCTAGCCCACTCAGGTGGTTTTTTTGGTTTTCGCTCCTTGCCGCATCTTCTGTGCCTTTGATGGCGGCTGGTTGGGGTGAAAGGCTGCATATTCCAGAATTTCAGACAGTAGATTGTTTTTGAAATCTTCCGTTTTATCGTTGACGAACTTAACCATCCTGTTGAAATCATCTTCCTTTGATACACCTTCAGGAAATGCCTTAGGAACTGATGTTTGGCTATCCAAGGCATCTTGCAATATCTGCACGATCTCCGAATTCATTGATCGCCCATTGGCCTTTGCTCTGGCGGCAACTGCGTCACGCATACCGTCAGGCATCCTAACTGTAAATCTCTCAATGAAAGCTGGATCTTCTTTTTCAGTCATCATCTTAAACCATAAAAATTTATACAAAACACACTAGCATCATATTGACATTACCCACAATGACATCATAATGGTGTCAGGCATCAAAATGATGTCATCATGACAAGGGGAAAGTAAATGCAAGATGTTCTCTATACAGGTCGTAAGAACGACAGCTTTCAGCTTCGTCTGCCTGAGCGAATGAAAGAAGAGATCCGTCGCATGGCAGAGATGGACGGCATTTCGATTAATTCTGCAATCGTGCAGCGCCTTGCTAAAAGCTTGCGTGAGGAAAGAGTTAATGGGCAGTAAAAACAGCGAAGCCCGGAAGTGTGGGGACACTAACCGGGCTTCTAATGTCAGTTACCTAGCGGGAAACCAACAATGACCAGTATAGCAATCTTTGAAGCAGTAAACACTATCTCTCTTCCATTCCACGGACAGAAGATCATAACTGCGATGGTGGCGGGTGTGGCGTATGTGGCAATGAAGCCCATCGTGGAAAACATCGGTTTAGACTGGAAGAGCCAGTATGCCAAGCTCGTTAGTCAGCGTGAAAAGTTCGGGTGTGGTGATATCACCATACCTACCAAAGGTGGTGTTCAGCAGATGCTTTGCATCCCTTTGAAGAAACTGAATGGATGGCTCTTCAGCATTAACCCAGCAAAAGTACGTGATGCAGTTCGTGAAGGTTTAATTCGCTATCAAGAAGAGTGTTTTACAGCTTTGCACGATTACTGGAGCAAAGGTGTTGCAACGAATCCCCGGACACCGAAGAAACAGGAAGACAAAAAGTCACGCTATCACGTTCGCGTTATTGTCTATGACAACCTGTTTGGTGGATGCGTTGAATTTCAGGGGCGTGCGGATACGTTTCGGGGGATTGCATCGGGTGTAGCAACCGATATGGGATTTAAGCCAACAGGATTTATCGAGCAGCCTTACGCTGTTGAAAAAATGAGGAAGGTCTACTGATTGGCGTATTGGAAGGCGCAAAAAGAAAAGCCAGCAGATGGGCTGCTGGCATTCATTGGGTATATGAACTTTCGGAGAACATATGAAGTCAATTATCAAGCATTTTGAGTTTAAGTCAAGTGAAGGGCATGTAGTGAGCCTTGAGGCTGCAAGCTTTAAAGGCAAGCCAGTTTTTTTAGCAATTGATTTGGCTAAGGCTCTCGGGTACTCAAATCCGTCA

5. Genemark.hmm a statistical model

6. Exon prediction in Eukaryotic DNA using Genescan: Net result is a protein sequence
GeneScan looks for start and stop codons, promoters, splice sites, polyA tails, provides statistics for coding potential

7. GeneScan results

8. GeneScan results

10. I have a protein sequence, now what?
-Amos Bairoch, (creater of SWISS-PROT), created a collection of small well-conserved segments (patterns) to classify and analyze new proteins
-PROSITE is the name he gave to this pattern database
-PROSITE also contains profiles which describe every position of a protein family
-ScanProsite is a server that compares your protein to the PROSITE database
-if your protein contains a PROSITE pattern, it can give you a pretty clear indication of its function

11. What does it look for on the protein sequence?
-profiles of protein families
-conserved patterns in the sequence ([RK]-x-[ST])
-cofactor binding motifs
-substrate binding motifs
ScanProsite:
Around the world there are ~8 other major collections of domains, such as Interproscan, CD server, or Pfscan

13. ScanProsite results continued

14. Sequence Similarity Searches using BLAST
-If you have a region of sequenced DNA, and you want to know what the protein encoded does
-If you can find similar sequences you can say, “if something is true for that sequence, it is probably true for mine as well.”
-could take years in the lab, can take only seconds to search a database for similarity
The Basic Local Alignment Search Tool (BLAST) finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches. BLAST can be used to infer functional and evolutionary relationships between sequences as well as help identify members of gene families.
This is an unknown gene sequence used in the next few slides
ATGGAACTGACTCCAAGAGAAAAAGACAAACTATTACTGTTTACCGCTGCACTGCTGGCAGAGCGTCGTCTGGCCCGCGGCCTGAAACTTAACTATCCCGAATCCGTGGCCCTGATTAGCGCTTTTATAATGGAGGGCGCTCGCGACGGCAAAAGCGTCGCTGCGCTGATGGAAGAAGGACGGCATGTCCTGAGTCGCGAGCAGGTCATGGAAGGCATACCAGAAATGATCCCCGATATCCAGGTCGAAGCCACCTTTCCGGACGGCTCCAAGCTGGTTACCGTCCATAATCCGATAATCTGA

15. The different types of BLAST
BLAST = Basic Local Alignment Search Tool
“The most popular data mining tool ever”
BLASTN DNA sequence vs. DNA sequence database
BLASTP protein sequence vs. protein sequence database
BLASTX DNA sequence translated in 6 reading frames
vs. protein sequence database
tBLASTX DNA sequence translated in 6 reading frames
vs. DNA sequence database translated in 6 frames

16. Steps to use Blast #1) Paste sequence here #2) Choose search set
(Either nucleotide collection or Protein Data Bank)
#4 push blast button
#3) select program to use

17. The number of sequences in the database
Blast output #1
The number of sequences in the database
Red, pink, and green are good matches
The number of letters (base pairs) in the database
This is the length of your query (in this case it was nucleotides)

18. How good is your BLAST hit?
The bit score: a measure of the statistical significance of the score (The higher the score the better and matches <50 are unreliable)
E-value: it is the number of times that your database match may have occurred by chance. The lower (closest to zero) the better, matches above are close to the “twilight zone”
Click here next to get to this genbank entry

19. A GenBank file Organism from which the sequence was characterized
List of annotated features
Product
Structural annotation
Function
Name of the gene (ureC)

20. Once you find some protein sequences with BLAST, copy and paste in word or a text editor
Note: each one will need a FASTA header with the organism name following as the first line

21. MultAlin: conduct protein sequence alignments from the BLASTP search
B Asx Aspartic acid or Asparagine
Z Glx Glutamine or Glutamic acid

22. Its your turn http://www.ncbi.nlm.nih.gov/Class/minicourses/
Choose Course #2: Making sense of DNA and protein sequences
Questions to consider as they work through these exercises:
#1) What aspects of the tools/resources are confusing or problematic? What questions do you think your students would have?
#2) How can we design similar exercises for our classes that are more compelling? How can we make the students more engaged, invested and motivated to learn?
#3 Group compilation of additional resources/websites that might be even better or more intuitive than the NCBI tools?