Practical Aspects of Multiple Sequence Alignments

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Practical Aspects of Multiple Sequence Alignments

• Mike Thomas, Ph.D.
• Bioinformatics Research Center, Medical College
  of Wisconsin

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Outline Practical aspects of MSE

• Why it is important to accurately assess
  alignments
• How do conduct MSEs
• What we do with MSEs

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Why do we do multiple sequence alignments?

• Infer phylogenetic relationships
• Understand evolutionary pressures acting on a
  gene
• Formulate test hypotheses about protein 3-D
  structure (based on conserved regions)
• Formulate test hypotheses about protein
  function
• Understand how protein function has changed
• Identify primers and probes to search for
  homologous sequences in other organisms

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The relationship of MSA to phylogenetics

• The goal of phylogenetics is to reconstruct
  evolutionary history using share, derived
  characters
• Characters that have a common evolutionary
  history (are homologous)
• For example, eyes of humans and rats (but not
  humans and octopi)
• Traditionally, morphological characters were
  used.
• Now, DNA and amino acid sequence alignments are
  very common for phylogenetic reconstruction
• It is assumed that properly aligned sequences
  represents homology

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The relationship between MSA and evolutionary
history of a group of genes or organisms
NFS
NFLS
NYLS
NKYLS
-L
K
NYLS
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Using known evolutionary relationship for
sequence alignment
NFS
NFLS
NYLS
NKYLS
NFL/-S
NK/-YLS
NK/-Y/FL/-S
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What happens when a sequence alignment is wrong?
A
B
C
A
C
B
B
C
A
A AGT B AT C ATC
A AGT- B A-T- C A-TC
A AGT B AT- C ATC
A AGT- B A-T- C A-TC
III
II
I
Unaligned
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Parameter considerations consequences
transitions, transversions, and gaps
4 possible alignments of AATCGCG AACCCGG
Gaps, tv, ts
A.
AATCGCG AACCCGG
0, 2, 1
B.
AATCGCG- AACC-CGG
2, 0, 1
C.
AATCGCG- AA-CCCGG
2, 1, 0

• transition rate
• transversion rate
• These are treated the same for long divergence
  times.

D.
AATCGC-G- AA-C-CCGG
4, 0, 0
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Parameter considerations consequences
transitions, transversions, and gaps
4 possible alignments of AATCGCG AACCCGG
Indels, tvs, tss
AATCGCG AACCCGG
A.
0, 2, 1
AATCGCG- AACC-CGG
B.
2, 0, 1
AATCGCG- AA-CCCGG
C.
2, 1, 0
AATCGC-G- AA-C-CCGG
D.
4, 0, 0
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Tools for MSE

• Clustal web server or run locally
• Web server http//www.ebi.ac.uk/clustalw/index.ht
  ml
• Manuscript with details http//www.csc.fi/molbio/
  progs/clustalw/ms.html
• Goal Find an optimal multiple alignment

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ClustalW

• CLUSTAL Has number of variations, the most
  commonly used is CLUSTALW
• Generates pairwise alignments of all input
  sequences, then ranks scores of identities among
  pairs of sequences.
• High scoring pairs of sequences align most
  readily to each other.
• More divergent (less related) pairs are then
  added to the alignment.
• Generates a phylogenetic tree of relationships to
  determine steps in constructing the alignment.
• One can view the phylogenetic tree used to
  generate the alignment.
• Individual pairs in the alignment are aligned
  using a FASTA-type (word-based, fast alignment)
  or by a dynamic programming algorithm, which is
  slower, but produces optimal pairwise alignments.

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Unix version of ClustalX, the graphical interface
to ClustalW, run locally. Note colors for amino
acid qualities and score indicator.
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Web ClustalW options
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FOSB_MOUSE Protein fosB MFQAFPGDYD SGSRCSSSPS
AESQYLSSVD SFGSPPTAAA SQECAGLGEM PGSFVPTVTA
ITTSQDLQWL VQPTLISSMA QSQGQPLASQ PPAVDPYDMP
GTSYSTPGLS AYSTGGASGS GGPSTSTTTS GPVSARPARA
RPRRPREETL TPEEEEKRRV RRERNKLAAA KCRNRRRELT
DRLQAETDQL EEEKAELESE IAELQKEKER LEFVLVAHKP
GCKIPYEEGP GPGPLAEVRD LPGSTSAKED GFGWLLPPPP
PPPLPFQSSR DAPPNLTASL FTHSEVQVLG DPFPVVSPSY
TSSFVLTCPE VSAFAGAQRT SGSEQPSDPL
NSPSLLAL FOSB_HUMAN Protein fosB MFQAFPGDYD
SGSRCSSSPS AESQYLSSVD SFGSPPTAAA SQECAGLGEM
PGSFVPTVTA ITTSQDLQWL VQPTLISSMA QSQGQPLASQ
PPVVDPYDMP GTSYSTPGMS GYSSGGASGS GGPSTSGTTS
GPGPARPARA RPRRPREETL TPEEEEKRRV RRERNKLAAA
KCRNRRRELT DRLQAETDQL EEEKAELESE IAELQKEKER
LEFVLVAHKP GCKIPYEEGP GPGPLAEVRD LPGSAPAKED
GFSWLLPPPP PPPLPFQTSQ DAPPNLTASL FTHSEVQVLG
DPFPVVNPSY TSSFVLTCPE VSAFAGAQRT SGSDQPSDPL
NSPSLLAL FOS_CHICK Proto-oncogene protein
c-fos MMYQGFAGEY EAPSSRCSSA SPAGDSLTYY PSPADSFSSM
GSPVNSQDFC TDLAVSSANF VPTVTAISTS PDLQWLVQPT
LISSVAPSQN RGHPYGVPAP APPAAYSRPA VLKAPGGRGQ
SIGRRGKVEQ LSPEEEEKRR IRRERNKMAA AKCRNRRREL
TDTLQAETDQ LEEEKSALQA EIANLLKEKE KLEFILAAHR
PACKMPEELR FSEELAAATA LDLGAPSPAA AEEAFALPLM
TEAPPAVPPK EPSGSGLELK AEPFDELLFS AGPREASRSV
PDMDLPGASS FYASDWEPLG AGSGGELEPL CTPVVTCTPC
PSTYTSTFVF TYPEADAFPS CAAAHRKGSS
SNEPSSDSLS FOS_RAT Proto-oncogene protein
c-fos MMFSGFNADY EASSSRCSSA SPAGDSLSYY HSPADSFSSM
GSPVNTQDFC ADLSVSSANF IPTVTAISTS PDLQWLVQPT
LVSSVAPSQT RAPHPYGLPT PSTGAYARAG VVKTMSGGRA
QSIGRRGKVE QLSPEEEEKR RIRRERNKMA AAKCRNRRRE
LTDTLQAETD QLEDEKSALQ TEIANLLKEK EKLEFILAAH
RPACKIPNDL GFPEEMSVTS LDLTGGLPEA TTPESEEAFT
LPLLNDPEPK PSLEPVKNIS NMELKAEPFD DFLFPASSRP
SGSETARSVP DVDLSGSFYA ADWEPLHSSS LGMGPMVTEL
EPLCTPVVTC TPSCTTYTSS FVFTYPEADS FPSCAAAHRK
GSSSNEPSSD SLSSPTLLAL FOS_MOUSE Proto-oncogene
protein c-fos MMFSGFNADY EASSSRCSSA SPAGDSLSYY
HSPADSFSSM GSPVNTQDFC ADLSVSSANF IPTVTAISTS
PDLQWLVQPT LVSSVAPSQT RAPHPYGLPT QSAGAYARAG
MVKTVSGGRA QSIGRRGKVE QLSPEEEEKR RIRRERNKMA
AAKCRNRRRE LTDTLQAETD QLEDEKSALQ TEIANLLKEK
EKLEFILAAH RPACKIPDDL GFPEEMSVAS LDLTGGLPEA
STPESEEAFT LPLLNDPEPK PSLEPVKSIS NVELKAEPFD
DFLFPASSRP SGSETSRSVP DVDLSGSFYA ADWEPLHSNS
LGMGPMVTEL EPLCTPVVTC TPGCTTYTSS FVFTYPEADS
FPSCAAAHRK GSSSNEPSSD SLSSPTLLAL
Sequence data for two related genes fosB from
mouse and human c-fos from chicken, mouse, and
rat.
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• Significant differences between FosB and C-Fos.
• Rat and mouse C-Fos sequences differ from chicken
  C-Fos.
• Long conserved region between130 and 225.
• Symbols
• Identity across all sequences
• Conservation of amino acid characteristics
• . Semi-conserved substitutions

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• To better visualize conservation, colors can be
  used.
• Color code
• AVFPMILW RED, Small (small hydrophobic
  (incl.aromatic -Y))
• DE BLUE, Acidic
• RHK MAGENTA, Basic
• STYHCNGQ GREEN, Hydroxyl Amine Basic Q
• Others Grey
• Differences between the genes and species are
  more apparent.

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Neighbor Joining tree constructed with a
web-ClustalW applet (Jalview) FosB c-Fos can be
distinguished Rat mouse cluster apart from
chicken, with respect to c-Fos
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A Highly conserved region
B Rather dissimilar region
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Threonyl-tRNA synthetase (thrS2) gene w/
consensus sequence
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Threonyl-tRNA synthetase (thrS2) gene in 6 species
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MALIGN

• construction of pairwise MOTIFS (conserved
  regions of similarity without gaps)
• construction of MULTIPLE MOTIFS (of thickness
  exceeding 2)
• forming of SUPERMOTIFS (groupings of motifs that
  near each other) from MULTIPLE MOTIFS
• construction of MULTIPLE ALIGNMENTS from
  previously obtained MOTIFS and SUPERMOTIFS and
  consequent selection of the best alignment.
• http//www.genebee.msu.su/services/malign_full.htm
  l

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(No Transcript)
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Each motif supermotif has a score and involves
a pair of sequences
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Malign
Possibility of receiving a sum of mismatch
weights along an alignment for random sequences
of the same length includes parameters for gaps
mismatches
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The relationship of MSA to phylogenetics

• The goal of phylogenetics is to reconstruct
  evolutionary history using share, derived
  characters
• Characters that have a common evolutionary
  history (are homologous)
• For example, eyes of humans and rats (but not
  humans and octopi)
• Traditionally, morphological characters were
  used.
• Now, DNA and amino acid sequence alignments are
  very common for phylogenetic reconstruction
• It is assumed that properly aligned sequences
  represents homology

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The relationship of MSA to phylogenetics
AHFGEPDFTV WNAGQFPANL HTQ-DMSSKS TIEINFKAME
MIILGTEYAG ENFGEPDFTV WNAGQFPANT HTS-GMTSKT
TVEINFKQME MVILGTEYAG KNFGEPDFTI YNAGQFPANI
HTK-GMTSAT SVEINFKDME MVILGTEYAG EDFGTPDFTI
YNAGQFPCNR YTH-YMTSST SIDLNLARRE MVIMGTQYAG
ESFGTPDFTI YNAGQFPCNR YTH-YMTSST SVDLNLARRE
MVILGTQYAG LVGFKPDFVV MNGSKVTNPN WKEQGLNSEN
FVAFNLTEGV QLIGGTWYGG LKNFEPDFVV MNGSKVTNPN
WKEQGLNSEN FVAFNLTERI QLIGGTWYGG LAHFKPDFVV
MNGAKCTNAK WKEHGLNSEN FTVFNLTERM QLIGGTWYGG
LKGFEPDFVV LNASKAKVEN FKELGLNSET AVVFNLAEKM
QIILNTWYGG LANFKPDFVV YNASKAKVEN YKELGLHSET
AVVFNLTSRE QVIINTWYGG LENFKADFIV YNACKCINED
YKQDGLNSEV FVIFNVEENI AVIGGTWYGG ATKIKPNFTI
VSAPHFKADP EVD-GTKSET FVIISFKHKV ILIGGTEYAG
KTVEQP-FTI LSAPHFKADP KTD-GTHSET FIIVSFEKRT
ILIGGTEYAG -PAGKDEWQV LNVANFECVP ERD-GTNSDG
CVILNFAQKK VLIAGMRYAG LPSFQPKLTI IDLPSFKADP
VRH-GCRSET VIACDLTNGL VLIGGTSYAG LASFLPKLTI
IDLPSFKANP ERH-GCRGET IIACDLTKGL VLIGGTSYAG
LGQFVPEMTI IDLPSFRADP ARH-GSRTET VIAVDLTRQI
VLIGGTSYAG LENFVPELTL IDLPSFRADP KRH-GCRSEN
VVAIDFARKI VLIGGTQYAG ----SYDMVT IDVP------
-----SYSDV WMLVERRSNS TLVLGSDYYG
Phosphoenolpyruvate carboxylase kinase (PPCK)
gene in 19 species
PPCK_AERPE
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• Phosphoenolpyruvate carboxylase kinase (PPCK)
  gene in 19 species, 720 sites.
• Standard Neighbor-Joining tree constructed by
  ClustalW
• Tree will differ with varying tree-building and
  distance-estimation methods how do we know
  which to use?
• Different methods will provide significantly
  different estimates of branch lengths, especially
  for the long branch.

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Next time inferring evolutionary history from
DNA amino acid sequence alignments

• Introduction to phylogenetic approaches
• Maximum Parsimony
• Minimum Evolution
• Maximum Likelihood
• Introduction to tree-building methods
• Assessing phylogenetic reconstructions
• Practical uses of phylogenies