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Dave Baumler Genome Center of Wisconsin, UW-Madison dbaumler@wisc

Making Sense of DNA and protein sequence analysis tools (course #2) http://www.ncbi.nlm.nih.gov/Class/minicourses/. Dave Baumler Genome Center of Wisconsin, UW-Madison dbaumler@wisc.edu. Todays session an overview You have been given a 5 KB piece of DNA sequence

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Dave Baumler Genome Center of Wisconsin, UW-Madison dbaumler@wisc

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  1. Making Sense of DNA and protein sequence analysis tools (course #2) http://www.ncbi.nlm.nih.gov/Class/minicourses/ Dave Baumler Genome Center of Wisconsin, UW-Madison dbaumler@wisc.edu

  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 http://bioinformatics.ca/links_directory/

  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

  9. 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

  10. 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

  11. ScanProsite results continued

  12. 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

  13. 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 The different types of BLAST BLAST = Basic Local Alignment Search Tool “The most popular data mining tool ever”

  14. 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

  15. Blast output #1 The number of sequences in thedatabase 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)

  16. 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 0.001 are close to the “twilight zone” Click here next to get to this genbank entry

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

  18. 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

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

  20. 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?

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