An Introduction to Multiple Sequence Alignments Cédric Notredame

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. :

Manguel M, Samaniego F.J., Abraham Wald’s Work on Aircraft Suvivability, J. American Statistical Association. 79, , (1984)

Our Scope How Can I Use My Alignment? How Does The Computer Align The Sequences? How Can I Assemble a Mult. Aln? What are the Difficulties?

Outline -Why Do We Need Multiple Sequence Alignment ? -The progressive Alignment Algorithm -A possible Strategy… -Potential Difficulties

Pre-requisite -How Do Sequences Evolve? -How can We COMPARE Sequences ? -How can We ALIGN Sequences ?

Why Do We Need Multiple Sequence Alignment ?

Sometimes Two Sequences Are Not Enough… The man with TWO watches NEVER knows the time

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : What is A Multiple Sequence Alignment? Structural Criteria: Residues are arranged so that those playing a similar role end up in the same column. Evolution Criteria: Residues are arranged so that those having the same ancestor end up in the same column.

Phylogenic Relation Functional Relation

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP unknown -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM unknown AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Beyond The Twilight Zone SwissProt Unkown Sequence Homology? Less Than 30 % id BUT Conserved where it MATTERS

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Prosite Patterns

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Prosite Patterns P-K-R-[PA]-x(1)-[ST]…

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Prosite Patterns SwissProt Uncharacterised Signature Match?

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-IQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Prosite Patterns Profiles And HMMs -More Sensitive -More Specific L? K>R A F D E F G H Q I V L W

A PROSITE PROFILE A Substitution Cost For Every Amino Acid, At Every Position

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Motifs/Patterns Phylogeny chite wheat trybr mouse -Evolution -Paralogy/Orthology Profiles

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Motifs/Patterns Phylogeny Profiles Struc. Prediction Column Constraint  Evolution Constraint  Structure Constraint

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Extrapolation Motifs/Patterns Phylogeny Profiles Struc. Prediction PsiPred OR PhD For secondary Structure Prediction: 75% Accurate. Threading: is improving but is not yet as good.

chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : How Can I Use A Multiple Sequence Alignment? Automatic Multiple Sequence Alignment methods are not always perfect… You know better… With your big BRAIN

Why Is It Difficult To Compute A multiple Sequence Alignment? A CROSSROAD PROBLEM BIOLOGY: What is A Good Alignment COMPUTATION What is THE Good Alignment chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: *

The Biological Problem. Same as PairWise Alignment Problem We do NOT know how Sequences Evolve. We do NOT understand the Relation Between Structures and Sequences. We would NOT recognize the Correct Alignment if we had it IN FRONT of our eyes…

The Biological Problem. The Charlie Chaplin Paradox

The Biological Problem. How to Evaluate an Alignment -Substitution Matrix (Blosum) -An Evaluation Function A AAACCAAACC -Gap Penalties. -A nice set of Sequences A A A C Sums of Pairs: Cost=6 C Over-estimation of the Substitutions Easy to compute

The COMPUTATIONAL Problem. Producing the Alignment -Substitution Matrix (Blosum) -An Evaluation Function -Gap Penalties. -A nice set of Sequences -An Alignment Algorithm GLOBAL Alignment Will It Work ?

HOW CAN I ALIGN MANY SEQUENCES 2 Globins =>1 Min

3 Globins =>2 hours HOW CAN I ALIGN MANY SEQUENCES

4 Globins => 10 days HOW CAN I ALIGN MANY SEQUENCES

5 Globins => 3 years HOW CAN I ALIGN MANY SEQUENCES

6 Globins =>300 years HOW CAN I ALIGN MANY SEQUENCES ! DHEA Loaded

7 Globins => years HOW CAN I ALIGN MANY SEQUENCES Solidified Fossil, Old stuff

8 Globins =>3 Million years HOW CAN I ALIGN MANY SEQUENCES

The Progressive Multiple Alignment Algorithm (Clustal W)

Making An Alignment Any Exact Method would be TOO SLOW We will use a Heuristic Algorithm. Progressive Alignment Algorithm is the most Popular -Fast -ClustalW -Greedy Heuristic (No Guarranty).

Progressive Alignment Feng and Dolittle, 1988; Taylor 1989 Clustering

Dynamic Programming Using A Substitution Matrix Progressive Alignment

-Depends on the ORDER of the sequences (Tree). -Depends on the CHOICE of the sequences. -Depends on the PARAMETERS: Substitution Matrix. Penalties (Gop, Gep). Sequence Weight. Tree making Algorithm.

Progressive Alignment When Does It Work Works Well When Phylogeny is Dense No outlayer Sequence. Image: River Crossing

SeqA GARFIELD THE LAST FA-T CAT SeqB GARFIELD THE FAST CA-T --- SeqC GARFIELD THE VERY FAST CAT SeqD THE ---- FA-T CAT CLUSTALW (Score=20, Gop=-1, Gep=0, M=1) SeqA GARFIELD THE LAST FA-T CAT SeqB GARFIELD THE FAST ---- CAT SeqC GARFIELD THE VERY FAST CAT SeqD THE ---- FA-T CAT CORRECT (Score=24) Progressive Alignment When Doesn’t It Work

GARFIELD THE LAST FAT CAT GARFIELD THE FAST CAT --- GARFIELD THE LAST FAT CAT GARFIELD THE FAST CAT GARFIELD THE VERY FAST CAT THE FAT CAT GARFIELD THE VERY FAST CAT THE ---- FA-T CAT GARFIELD THE LAST FA-T CAT GARFIELD THE FAST CA-T --- GARFIELD THE VERY FAST CAT THE ---- FA-T CAT

Building the Right Multiple Sequence Alignment.

Recognizing The Right Sequences When you Meet Them…

Gathering Sequences: BLAST

Common Mistake: Sequences Too Closely Related PRVA_MACFU SMTDLLNAEDIKKAVGAFSAIDSFDHKKFFQMVGLKKKSADDVKKVFHILDKDKSGFIEE PRVA_HUMAN SMTDLLNAEDIKKAVGAFSATDSFDHKKFFQMVGLKKKSADDVKKVFHMLDKDKSGFIEE PRVA_GERSP SMTDLLSAEDIKKAIGAFAAADSFDHKKFFQMVGLKKKTPDDVKKVFHILDKDKSGFIEE PRVA_MOUSE SMTDVLSAEDIKKAIGAFAAADSFDHKKFFQMVGLKKKNPDEVKKVFHILDKDKSGFIEE PRVA_RAT SMTDLLSAEDIKKAIGAFTAADSFDHKKFFQMVGLKKKSADDVKKVFHILDKDKSGFIEE PRVA_RABIT AMTELLNAEDIKKAIGAFAAAESFDHKKFFQMVGLKKKSTEDVKKVFHILDKDKSGFIEE :**::*.*******:***:* :****************..::******:*********** PRVA_MACFU DELGFILKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES PRVA_HUMAN DELGFILKGFSPDARDLSAKETKMLMAAGDKDGDGKIGVDEFSTLVAES PRVA_GERSP DELGFILKGFSSDARDLSAKETKTLLAAGDKDGDGKIGVEEFSTLVSES PRVA_MOUSE DELGSILKGFSSDARDLSAKETKTLLAAGDKDGDGKIGVEEFSTLVAES PRVA_RAT DELGSILKGFSSDARDLSAKETKTLMAAGDKDGDGKIGVEEFSTLVAES PRVA_RABIT EELGFILKGFSPDARDLSVKETKTLMAAGDKDGDGKIGADEFSTLVSES :*** ******.******.**** *:************.:******:** -IDENTICAL SEQUENCES BRING NO INFORMATION FOR THE MULTIPLE SEQUENCE ALIGNMENT -MULTIPLE SEQUENCE ALIGNMENTS THRIVE ON DIVERSITY…

Sequence Weighting Within ClustalW

Selecting Diverse Sequences (Opus II)

Respect Information! This Alignment Is not Informative about the relation Betwwen TPCC MOUSE and the rest of the sequences. PRVA_MACFU SMTDLLN----AEDIKKA PRVA_HUMAN SMTDLLN----AEDIKKA PRVA_GERSP SMTDLLS----AEDIKKA PRVA_MOUSE SMTDVLS----AEDIKKA PRVA_RAT SMTDLLS----AEDIKKA PRVA_RABIT AMTELLN----AEDIKKA TPCC_MOUSE MDDIYKAAVEQLTEEQKNEFKAAFDIFVLGAEDGCISTKELGKVMRMLGQNPTPEELQEM : :*..*:::: PRVA_MACFU VGAFSAIDS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGFI PRVA_HUMAN VGAFSATDS--FDHKKFFQMVG------LKKKSADDVKKVFHMLDKDKSGFIEEDELGFI PRVA_GERSP IGAFAAADS--FDHKKFFQMVG------LKKKTPDDVKKVFHILDKDKSGFIEEDELGFI PRVA_MOUSE IGAFAAADS--FDHKKFFQMVG------LKKKNPDEVKKVFHILDKDKSGFIEEDELGSI PRVA_RAT IGAFTAADS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGSI PRVA_RABIT IGAFAAAES--FDHKKFFQMVG------LKKKSTEDVKKVFHILDKDKSGFIEEEELGFI TPCC_MOUSE IDEVDEDGSGTVDFDEFLVMMVRCMKDDSKGKSEEELSDLFRMFDKNADGYIDLDELKMM -A better Spread of the Sequences is needed

Selecting Diverse Sequences (Opus II)

PRVB_CYPCA -AFAGVLNDADIAAALEACKAADSFNHKAFFAKVGLTSKSADDVKKAFAIIDQDKSGFIE PRVB_BOACO -AFAGILSDADIAAGLQSCQAADSFSCKTFFAKSGLHSKSKDQLTKVFGVIDRDKSGYIE PRV1_SALSA MACAHLCKEADIKTALEACKAADTFSFKTFFHTIGFASKSADDVKKAFKVIDQDASGFIE PRVB_LATCH -AVAKLLAAADVTAALEGCKADDSFNHKVFFQKTGLAKKSNEELEAIFKILDQDKSGFIE PRVB_RANES -SITDIVSEKDIDAALESVKAAGSFNYKIFFQKVGLAGKSAADAKKVFEILDRDKSGFIE PRVA_MACFU -SMTDLLNAEDIKKAVGAFSAIDSFDHKKFFQMVGLKKKSADDVKKVFHILDKDKSGFIE PRVA_ESOLU --AKDLLKADDIKKALDAVKAEGSFNHKKFFALVGLKAMSANDVKKVFKAIDADASGFIE : *:.:..*.:*. * ** *: * : * :* * **:** PRVB_CYPCA EDELKLFLQNFKADARALTDGETKTFLKAGDSDGDGKIGVDEFTALVKA- PRVB_BOACO EDELKKFLQNFDGKARDLTDKETAEFLKEGDTDGDGKIGVEEFVVLVTKG PRV1_SALSA VEELKLFLQNFCPKARELTDAETKAFLKAGDADGDGMIGIDEFAVLVKQ- PRVB_LATCH DEELELFLQNFSAGARTLTKTETETFLKAGDSDGDGKIGVDEFQKLVKA- PRVB_RANES QDELGLFLQNFRASARVLSDAETSAFLKAGDSDGDGKIGVEEFQALVKA- PRVA_MACFU EDELGFILKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES PRVA_ESOLU EEELKFVLKSFAADGRDLTDAETKAFLKAADKDGDGKIGIDEFETLVHEA :**.*:.*.* *: ** ::.* **** **::** ** -A REASONABLE Model Now Exists. -Going Further:Remote Homologues.

Aligning Remote Homologues PRVA_MACFU SMTDLLNA----EDIKKA PRVA_ESOLU AKDLLKA----DDIKKA PRVB_CYPCA AFAGVLND----ADIAAA PRVB_BOACO AFAGILSD----ADIAAG PRV1_SALSA MACAHLCKE----ADIKTA PRVB_LATCH AVAKLLAA----ADVTAA PRVB_RANES SITDIVSE----KDIDAA TPCS_RABIT -TDQQAEARSYLSEEMIAEFKAAFDMFDADGG-GDISVKELGTVMRMLGQTPTKEELDAI TPCS_PIG -TDQQAEARSYLSEEMIAEFKAAFDMFDADGG-GDISVKELGTVMRMLGQTPTKEELDAI TPCC_MOUSE MDDIYKAAVEQLTEEQKNEFKAAFDIFVLGAEDGCISTKELGKVMRMLGQNPTPEELQEM : :: PRVA_MACFU VGAFSAIDS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGFI PRVA_ESOLU LDAVKAEGS--FNHKKFFALVG------LKAMSANDVKKVFKAIDADASGFIEEEELKFV PRVB_CYPCA LEACKAADS--FNHKAFFAKVG------LTSKSADDVKKAFAIIDQDKSGFIEEDELKLF PRVB_BOACO LQSCQAADS--FSCKTFFAKSG------LHSKSKDQLTKVFGVIDRDKSGYIEEDELKKF PRV1_SALSA LEACKAADT--FSFKTFFHTIG------FASKSADDVKKAFKVIDQDASGFIEVEELKLF PRVB_LATCH LEGCKADDS--FNHKVFFQKTG------LAKKSNEELEAIFKILDQDKSGFIEDEELELF PRVB_RANES LESVKAAGS--FNYKIFFQKVG------LAGKSAADAKKVFEILDRDKSGFIEQDELGLF TPCS_RABIT IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNADGYIDAEELAEI TPCS_PIG IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNMDGYIDAEELAEI TPCC_MOUSE IDEVDEDGSGTVDFDEFLVMMVRCMKDDSKGKSEEELSDLFRMFDKNADGYIDLDELKMM :..:... *: * : * :* :.*:*: :**. PRVA_MACFU LKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES- PRVA_ESOLU LKSFAADGRDLTDAETKAFLKAADKDGDGKIGIDEFETLVHEA- PRVB_CYPCA LQNFKADARALTDGETKTFLKAGDSDGDGKIGVDEFTALVKA-- PRVB_BOACO LQNFDGKARDLTDKETAEFLKEGDTDGDGKIGVEEFVVLVTKG- PRV1_SALSA LQNFCPKARELTDAETKAFLKAGDADGDGMIGIDEFAVLVKQ-- PRVB_LATCH LQNFSAGARTLTKTETETFLKAGDSDGDGKIGVDEFQKLVKA-- PRVB_RANES LQNFRASARVLSDAETSAFLKAGDSDGDGKIGVEEFQALVKA-- TPCS_RABIT FR---ASGEHVTDEEIESLMKDGDKNNDGRIDFDEFLKMMEGVQ TPCS_PIG FR---ASGEHVTDEEIESIMKDGDKNNDGRIDFDEFLKMMEGVQ TPCC_MOUSE LQ---ATGETITEDDIEELMKDGDKNNDGRIDYDEFLEFMKGVE ::.. :: : ::.* :.** *. :** ::

Some Guidelines …

Do Not Use Two Many Sequences…

Reading Your Alignment

Going Further… PRVA_MACFU VGAFSAIDS--FDHKKFFQMVG------LKKKSADDVKKVFHILDKDKSGFIEEDELGFI PRVB_BOACO LQSCQAADS--FSCKTFFAKSG------LHSKSKDQLTKVFGVIDRDKSGYIEEDELKKF PRV1_SALSA LEACKAADT--FSFKTFFHTIG------FASKSADDVKKAFKVIDQDASGFIEVEELKLF TPCS_RABIT IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNADGYIDAEELAEI TPCS_PIG IEEVDEDGSGTIDFEEFLVMMVRQMKEDAKGKSEEELAECFRIFDRNMDGYIDAEELAEI TPCC_MOUSE IDEVDEDGSGTVDFDEFLVMMVRCMKDDSKGKSEEELSDLFRMFDKNADGYIDLDELKMM TPC_PATYE SDEMDEEATGRLNCDAWIQLFER---KLKEDLDERELKEAFRVLDKEKKGVIKVDVLRWI. :... ::. : * :* :.* *. : *. PRVA_MACFU LKGFSPDARDLSAKETKTLMAAGDKDGDGKIGVDEFSTLVAES-- PRVB_BOACO LQNFDGKARDLTDKETAEFLKEGDTDGDGKIGVEEFVVLVTKG-- PRV1_SALSA LQNFCPKARELTDAETKAFLKAGDADGDGMIGIDEFAVLVKQ--- TPCS_RABIT FR---ASGEHVTDEEIESLMKDGDKNNDGRIDFDEFLKMMEGVQ- TPCS_PIG FR---ASGEHVTDEEIESIMKDGDKNNDGRIDFDEFLKMMEGVQ- TPCC_MOUSE LQ---ATGETITEDDIEELMKDGDKNNDGRIDYDEFLEFMKGVE- TPC_PATYE LS---SLGDELTEEEIENMIAETDTDGSGTVDYEEFKCLMMSSDA :. :: : :: * :..* :. :** ::

WHAT MAKES A GOOD ALIGNMENT… -THE MORE DIVERGEANT THE SEQUENCES, THE BETTER -THE FEWER INDELS, THE BETTER -NICE UNGAPPED BLOCKS SEPARATED WITH INDELS -DIFFERENT CLASSES OF RESIDUES WITHIN A BLOCK: Completely Conserved Conserved For Size and Hydropathy Conserved For Size or Hydropathy -THE ULTIMATE EVALUATION IS A MATTER OF PERSONNAL JUDGEMENT AND KNOWLEDGE.

Potential Difficulties

DO NOT OVERTUNE!!! chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. : DO NOT PLAY WITH PARAMETERS IF YOU KNOW THE ALIGNMENT YOU WANT: MAKE IT YOURSELF! chite ---ADKPKRPL-SAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAP-SAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPR-SAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :*:.:... :.. *. *: * chite AATAKQNYIRALQEYERNGG- wheat ANKLKGEYNKAIAAYNKGESA trybr AEKDKERYKREM mouse AKDDRIRYDNEMKSWEEQMAE * :.*. :

TUNING or NOT TUNING!!! -MOST METHODS ARE TUNED FOR WORKING WELL ON AVERAGE -PARAMETERS BEHAVIOUR DO NOT NECESSARILY FOLLOW THE THEORY (i.e. Substitution Matrices). -A GOOD ALIGNMENT IS USUALLY ROBUST(i.e. Changes little). -TUNE IF YOU WANT TO CONVINCE YOURSELF. -PARAMETERS TO TUNE USUALLY INCLUDE: GOP/ GEP MATRIX SENSITIVITY Vs SPEED GOP GEP Substitution Matrices (Etzold and al. 1993) Gonnet61.7 % Blosum % Pam %

KEEP A BIOLOGICAL PERSPECTIVE chite ---ADKPKRPLSAYMLWLNSARESIKRENPDFK-VTEVAKKGGELWRGLKD wheat --DPNKPKRAPSAFFVFMGEFREEFKQKNPKNKSVAAVGKAAGERWKSLSE trybr KKDSNAPKRAMTSFMFFSSDFRS----KHSDLS-IVEMSKAAGAAWKELGP mouse -----KPKRPRSAYNIYVSESFQ----EAKDDS-AQGKLKLVNEAWKNLSP ***. :::.:... :.. *. *: * chite AD--K----PKR-PLYMLWLNS-ARESIKRENPDFK-VT-EVAKKGGELWRGL- wheat -DPNK----PKRAP-FFVFMGE-FREEFKQKNPKNKSVA-AVGKAAGERWKSLS trybr -K--KDSNAPKR-AMT-MFFSSDFR-S-KH-S-DLS-IV-EMSKAAGAAWKELG mouse ----K----PKR-PRYNIYVSESFQEA-K--D-D-S-AQGKL-KLVNEAWKNLS * ***.:: ::... : *... : *. *: * DIFFERENT PARAMETERS WRONG ALIGNMENT !!!

REPEATS THERE IS A PROBLEM WHEN TWO SEQUENCES DO NOT CONTAIN THE SAME NUMBER OF REPEATS IT IS THEN BETTER TO MANUALLY EXTRACT THE REPEATS AND TO ALIGN THEM. INDIVIDUAL REPEATS CAN BE RECOGNIZED USING DOTTER

Naming Your Sequences The Right Way

What Are The Available Methods ???

Simultaneous Alignments : MSA 1) Set Bounds on each pair of sequences (Carillo and Lipman) 2) Compute the Maln within the Hyperspace -Few Small Closely Related Sequence. -Do Well When They Can Run. -Memory and CPU hungry

Simultaneous Alignments : DCA -Few Small Closely Related Sequence, but less limited than MSA -Do Well When Can Run. -Memory and CPU hungry, but less than MSA

Dialign II 1) Identify best chain of segments on each pair of sequence. Assign a Pvalue to each Segment Pair. 3) Assemble the alignment according to the segment pairs. 2) Ré-évaluate each segment pair according to its consistency with the others

Muscle

Progressive Iterative Methods -HMMs, HMMER, SAM, MUSCLE -Slow, Sometimes Inaccurate -Good Profile Generators

Progressive MUSCLE

Progressive MUSCLE phylogenomics.berkeley.edu/cgi-bin/muscle/input_muscle.py

MAFFT Fast Fourrier Transformé

Prank

Stachmo

Mixing Heterogenous Data With T-Coffee Local AlignmentGlobal Alignment Multiple Sequence Alignment Multiple Alignment StructuralSpecialist

Struct Vs Struct Seq Vs Struct Thread Evaluation on Homestrad Superpose Seq Vs Seq Local Global Mixing Sequences and Structures with T-Coffee

What is The Best Method ?

A better Question… What is the Best Alignment ? What is the best bit of my alignment ?

What is the Local Quality of my Alignment ? II I

Choosing the right method

Situation  Solution

Priority  Solution Method Priority TreesProfile2D –Pred3D-PredFunc-Pred Accuracy Speed

Purpose  Solution

Conclusion

-The BEST alignment Method: Your Brain The Right Data -Beware of repeated elements Multiple Alignment -The Best Evaluation Procedure: Experimental Data (SwissProt) -Choosing The Sequences Well is Important

Know Your Problem: What do you want to do with your MSA Multiple Alignment

Addresses MAFFT Progressive/iterativewww.biophys.kyoto-u.jp/katoh POA Progressive/Simultaneouswww.bioinformatics.ucla.edu/poa MUSCLE Progressive/Iterativewww.drive5.com/muscle