Prosite UCSC Genome Browser MSAs and Phylogeny Exercise 2

Turning information into knowledge  The outcome of a sequencing project is masses of raw data  The challenge is to turn this raw data into biological knowledge  A valuable tool for this challenge is an automated diagnostic pipe through which newly determined sequences can be streamlined

From sequence to function  Nature tends to innovate rather than invent  Proteins are composed of functional elements: domains and motifs Domains are structural units that carry out a certain function Domains are structural units that carry out a certain function The same domains are The same domains are shared between different proteins Motifs are shorter Motifs are shorter sequences with certain biological activity

InterPro  An integrated documentation resource for protein families, domains and sites  Groups signatures describing the same protein family or domain  Combines a number of databases that use different methodologies to derive protein signature: UniProt: UniProtKB Swiss-Prot, TrEMBL, UniRef,UniParc UniProt: UniProtKB Swiss-Prot, TrEMBL, UniRef,UniParc prosite: documented DB on domains, families and functional sites. prosite: documented DB on domains, families and functional sites. Pfam: a DB of protein families represented by MSAs Pfam: a DB of protein families represented by MSAs

InterPro search

prosite  A method for determining the function of uncharacterized translated protein sequences  Consists of a DB of annotated biologically important sites/patterns/motifs/signature/fingerprints

prosite  Entries are represented with patterns or profiles pattern A.1000T C G profile [AC]-A-[GC]-T-[TC]-[GC] Profiles are used in prosite when the motif is relatively divergent, and it is difficult to represent as a pattern

Scanning prosite Query: sequence Query: pattern Result: all patterns found in sequence Result: all sequences which adhere to this pattern

Patterns with a high probability of occurrence  Entries describing commonly found post- translational modifications or compositionally biased regions.  Found in the majority of known protein sequences  High probability of occurrence

prosite sequence query

prosite pattern query

UCSC Genome Browser

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UCSC Genome Browser query results

UCSC Genome Browser Annotation tracks Vertebrate conservation mRNA (GenBank) RefSeq UCSC Genes Base position Single species compared SNPs Repeats Gene Direction Exon Intron UTR

USCS Gene

UCSC Genome Browser - movement Zoom x3 + Center

UCSC Genome Browser – Base view

Annotation track options dense squish full pack

Annotation track options Another option to toggle between ‘pack’ and ‘dense’ view is to click on the track title Sickle-cell anemia distr. Malaria distr.

BLAT  BLAT = Blast-Like Alignment Tool  BLAT is designed to find similarity of >95% on DNA, >80% for protein  Rapid search by indexing entire genome. Good for: 1. Finding genomic coordinates of cDNA 2. Determining exons/introns 3. Finding human (or chimp, dog, cow…) homologs of another vertebrate sequence

BLAT on UCSC Genome Browser

BLAT Results

Match Non-Match (mismatch/indel) Indel boundaries

BLAT Results

BLAT Results on the browser

Getting DNA sequence of region

Clustal X – A Multiple Alignment Tool

Input: multiple sequence Fasta file >gi| |ref|NP_ | mesotrypsin preproprotein [Homo sapiens] MNPFLILAFVGAAVAVPFDDDDKIVGGYTCEENSLPYQVSLNSGSHFCGGSLISEQWVVSAAHCYKTRIQVRLGEHNIKVLEGNEQFINAAKIIRHPKYNRDTLDNDIMLIKLSSPAVINARVSTISLPTAPPAAGTECLISGWGNTLSFGADYPDELKCLDAPVLTQAECKASYPGKITNSMFCVGFLEGGKDSCQRDSGGPVVCNGQLQGVVSWGHGCAWKNRPGVYTKVYNYVDWIKDTIAANS >gi| |ref|NP_ | protease, serine, 2 [Macaca mulatta] MNPLLILAFVGVAVAAPFDDDDKIVGGYTCEENSVPYQVSLNSGYHFCGGSLINEQWVVSAAHCYKTRIQVRLGEHNIEVLEGTEQFINAAKIIRHPDYDRKTLNNDILLIKLSSPAVINARVSTISLPTAPPAAGAEALISGWGNTLSSGADYPDELQCLEAPVLSQAECEASYPGKITSNMFCVGFLEGGKDSCQGDSGGPVVSNGQLQGIVSWGYGCAQKNRPGVYTKVYNYVDWIRDTIAANS >gi| |ref|NP_ | mesotrypsin [Mus musculus] MNALLILALVGAAVAFPVDDDDKIVGGYTCQENSVPYQVSLNSGYHFCGGSLINDQWVVSAAHCYKTRIQVRLGEHNINVLEGNEQFVNAAKIIKHPNFNRKTLNNDIMLLKLSSPVTLNARVATVALPSSCAPAGTQCLISGWGNTLSFGVSEPDLLQCLDAPLLPQADCEASYPGKITGNMVCAGFLEGGKDSCQGDSGGPVVCNRELQGIVSWGYGCALPDNPGVYTKVCNYVDWIQDTIAAN >gi| |ref|NP_ | protease, serine, 2 [Rattus norvegicus] MRALLFLALVGAAVAFPVDDDDKIVGGYTCQENSVPYQVSLNSGYHFCGGSLINDQWVVSAAHCYKSRIQVRLGEHNINVLEGNEQFVNAAKIIKHPNFDRKTLNNDIMLIKLSSPVKLNARVATVALPSSCAPAGTQCLISGWGNTLSSGVNEPDLLQCLDAPLLPQADCEASYPGKITDNMVCVGFLEGGKDSCQGDSGGPVVCNGELQGIVSWGYGCALPDNPGVYTKVCNYVDWIQDTIAAN >gi| |ref|NP_ | pancreatic anionic trypsinogen [Bos taurus] MHPLLILAFVGAAVAFPSDDDDKIVGGYTCAENSVPYQVSLNAGYHFCGGSLINDQWVVSAAHCYQYHIQVRLGEYNIDVLEGGEQFIDASKIIRHPKYSSWTLDNDILLIKLSTPAVINARVSTLALPSACASGSTECL...

One of the options to get multiple sequence Fasta file

Input: multiple sequence Fasta file >gi| |ref|NP_ | mesotrypsin preproprotein [Homo sapiens] MNPFLILAFVGAAVAVPFDDDDKIVGGYTCEENSLPYQVSLNSGSHFCGGSLISEQWVVSAAHCYKTRIQVRLGEHNIKVLEGNEQFINAAKIIRHPKYNRDTLDNDIMLIKLSSPAVINARVSTISLPTAPPAAGTECLISGWGNTLSFGADYPDELKCLDAPVLTQAECKASYPGKITNSMFCVGFLEGGKDSCQRDSGGPVVCNGQLQGVVSWGHGCAWKNRPGVYTKVYNYVDWIKDTIAANS >gi| |ref|NP_ | protease, serine, 2 [Macaca mulatta] MNPLLILAFVGVAVAAPFDDDDKIVGGYTCEENSVPYQVSLNSGYHFCGGSLINEQWVVSAAHCYKTRIQVRLGEHNIEVLEGTEQFINAAKIIRHPDYDRKTLNNDILLIKLSSPAVINARVSTISLPTAPPAAGAEALISGWGNTLSSGADYPDELQCLEAPVLSQAECEASYPGKITSNMFCVGFLEGGKDSCQGDSGGPVVSNGQLQGIVSWGYGCAQKNRPGVYTKVYNYVDWIRDTIAANS >gi| |ref|NP_ | mesotrypsin [Mus musculus] MNALLILALVGAAVAFPVDDDDKIVGGYTCQENSVPYQVSLNSGYHFCGGSLINDQWVVSAAHCYKTRIQVRLGEHNINVLEGNEQFVNAAKIIKHPNFNRKTLNNDIMLLKLSSPVTLNARVATVALPSSCAPAGTQCLISGWGNTLSFGVSEPDLLQCLDAPLLPQADCEASYPGKITGNMVCAGFLEGGKDSCQGDSGGPVVCNRELQGIVSWGYGCALPDNPGVYTKVCNYVDWIQDTIAAN >gi| |ref|NP_ | protease, serine, 2 [Rattus norvegicus] MRALLFLALVGAAVAFPVDDDDKIVGGYTCQENSVPYQVSLNSGYHFCGGSLINDQWVVSAAHCYKSRIQVRLGEHNINVLEGNEQFVNAAKIIKHPNFDRKTLNNDIMLIKLSSPVKLNARVATVALPSSCAPAGTQCLISGWGNTLSSGVNEPDLLQCLDAPLLPQADCEASYPGKITDNMVCVGFLEGGKDSCQGDSGGPVVCNGELQGIVSWGYGCALPDNPGVYTKVCNYVDWIQDTIAAN >gi| |ref|NP_ | pancreatic anionic trypsinogen [Bos taurus] MHPLLILAFVGAAVAFPSDDDDKIVGGYTCAENSVPYQVSLNAGYHFCGGSLINDQWVVSAAHCYQYHIQVRLGEYNIDVLEGGEQFIDASKIIRHPKYSSWTLDNDILLIKLSTPAVINARVSTLALPSACASGSTECL...

Input: multiple sequence Fasta file >gi| |ref|NP_ | mesotrypsin preproprotein [Homo sapiens] MNPFLILAFVGAAVAVPFDDDDKIVGGYTCEENSLPYQVSLNSGSHFCGGSLISEQWVVSAAHCYKTRIQVRLGEHNIKVLEGNEQFINAAKIIRHPKYNRDTLDNDIMLIKLSSPAVINARVSTISLPTAPPAAGTECLISGWGNTLSFGADYPDELKCLDAPVLTQAECKASYPGKITNSMFCVGFLEGGKDSCQRDSGGPVVCNGQLQGVVSWGHGCAWKNRPGVYTKVYNYVDWIKDTIAANS >gi| |ref|NP_ | protease, serine, 2 [Macaca mulatta] MNPLLILAFVGVAVAAPFDDDDKIVGGYTCEENSVPYQVSLNSGYHFCGGSLINEQWVVSAAHCYKTRIQVRLGEHNIEVLEGTEQFINAAKIIRHPDYDRKTLNNDILLIKLSSPAVINARVSTISLPTAPPAAGAEALISGWGNTLSSGADYPDELQCLEAPVLSQAECEASYPGKITSNMFCVGFLEGGKDSCQGDSGGPVVSNGQLQGIVSWGYGCAQKNRPGVYTKVYNYVDWIRDTIAANS >gi| |ref|NP_ | mesotrypsin [Mus musculus] MNALLILALVGAAVAFPVDDDDKIVGGYTCQENSVPYQVSLNSGYHFCGGSLINDQWVVSAAHCYKTRIQVRLGEHNINVLEGNEQFVNAAKIIKHPNFNRKTLNNDIMLLKLSSPVTLNARVATVALPSSCAPAGTQCLISGWGNTLSFGVSEPDLLQCLDAPLLPQADCEASYPGKITGNMVCAGFLEGGKDSCQGDSGGPVVCNRELQGIVSWGYGCALPDNPGVYTKVCNYVDWIQDTIAAN >gi| |ref|NP_ | protease, serine, 2 [Rattus norvegicus] MRALLFLALVGAAVAFPVDDDDKIVGGYTCQENSVPYQVSLNSGYHFCGGSLINDQWVVSAAHCYKSRIQVRLGEHNINVLEGNEQFVNAAKIIKHPNFDRKTLNNDIMLIKLSSPVKLNARVATVALPSSCAPAGTQCLISGWGNTLSSGVNEPDLLQCLDAPLLPQADCEASYPGKITDNMVCVGFLEGGKDSCQGDSGGPVVCNGELQGIVSWGYGCALPDNPGVYTKVCNYVDWIQDTIAAN >gi| |ref|NP_ | pancreatic anionic trypsinogen [Bos taurus] MHPLLILAFVGAAVAFPSDDDDKIVGGYTCAENSVPYQVSLNAGYHFCGGSLINDQWVVSAAHCYQYHIQVRLGEYNIDVLEGGEQFIDASKIIRHPKYSSWTLDNDILLIKLSTPAVINARVSTLALPSACASGSTECL...

Step1: Load the sequences

Sequences and conservation view

Step2: Perform Alignment

Sequences and conservation view

Step 3: Create tree

Step 4: NJPlot

The Newick tree format is used to represent trees as strings CA D In Newick format: ((A,C),(B,D)); B Each pair of parenthesis () enclose a clade in the tree, and the comma separates the members of the corresponding clade. “;” – is always the last character

How robust is our tree?

 We need some statistical way to estimate the confidence in the tree topology  But we don’t know anything about the tree topology distribution or parameters  The only data source we have is our data (MSA)  So, we must rely on our own resources: “pull up by your own bootstraps” How robust is our tree?

Bootstrap (and jackknife)

Jackknife 1. We create n (typically ) new MSAs (pseudo-data sets) by randomly sampling half of the characters. (random samples without replacement) We do not change the number of sequences, just the number of positions! POS: : TATTT 2 : CATTT 3 : CACTT N : AACTT POS: : TTTAT 2 : TAACC 3 : TAACC N : TGGGA POS: : TTGTA 2 : TAGAC 3 : TAAAC N : TGAGG

Jackknife 2. We reconstruct a tree from each data set, using the same method used for reconstructing the original tree POS: : TATTT 2 : CATTT 3 : CACTT N : AACTT POS: : TTTAT 2 : TAACC 3 : TAACC N : TGGGA POS: : TTGTA 2 : TAGAC 3 : TAAAC N : TGAGG Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4

3. For each node in our original tree, we count the number of times it appeared in the Jackknife analysis Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 Back to Jackknife Sp1 Sp2 Sp3 Sp4 67% 100% In 67% of the data sets, the node SP1+SP2 was found

Bootstrap The same as jackknife, but instead of sampling K/2 positions, we sample K positions with replacement

Bootstrap 1. Resample K positions n times K 1 : ATCTG…A 2 : ATCTG…C 3 : ACTTA…C N : ACCTA…T K 1 : AATTT…T 2 : AATTT…G 3 : AACTT…T N : AACTT…T 47789…K 1 : TTTAT…T 2 : TAACC…G 3 : TAACC…T N : TGGGA…T 15578…K 1 : AGGTA…T 2 : AGGAC…G 3 : AAAAC…A N : AAAGG…C

Bootstrap 2. Reconstruct a tree from each data set using the same method used for reconstructing the original tree Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp K 1 : AATTT…T 2 : AATTT…G 3 : AACTT…T N : AACTT…T 47789…K 1 : TTTAT…T 2 : TAACC…G 3 : TAACC…T N : TGGGA…T 15578…K 1 : AGGTA…T 2 : AGGAC…G 3 : AAAAC…A N : AAAGG…C

Bootstrap 3. For each node in our original tree, we count the number of times it appeared in the bootstrap analysis Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 Sp1 Sp2 Sp3 Sp4 67% 100%

Step Bootstrap

Bootstrap values on NJPlot Note: ClustalX saves trees as.ph file trees with bootstrap are saved as.phb You might have to reopen the tree…