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MULTIPLE SEQUENCE ALIGNMENT
R.RAJAGOPAL M.Sc Marine Biotechnology
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Multiple sequence alignment
A multiple sequence alignment (MSA)is a sequence alignment of three or more Biological sequences, generally protein , DNA or RNA.
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Why we do multiple alignments?
Multiple nucleotide or amino sequence alignment techniques are usually performed to fit one of the following scopes : In order to characterize protein families, identify shared regions of homology in a multiple sequence alignment; (this happens generally when a sequence search revealed homologies to several sequences) Determination of the consensus sequence of several aligned sequences.
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Why we do multiple alignments?
Help prediction of the secondary and tertiary structures of new sequences; Preliminary step in molecular evolution analysis using Phylogenetic methods for constructing phylogenetic trees.
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Databases of multiple alignments
The power of multiple sequence analysis lies in the ability to draw together related sequences from various species and express the degree of similarity in relatively concise format.
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Multiple Alignment Method
Once homology sequences have been identified , which program should be preferentially used to align them? Several multiple alignment methods (algorithms)have been developed, but none of them is ideal.
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1.optimal methods for global multiple alignments
2.progressive global alignment. 3.Block-based global alignment. 4.Motif-based local multiple alignments 5.Particular case :alignment protein-coding DNA sequences.
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1.optimal methods for global multiple alignments
In this section ,several methods that are said to be optimal, because they guarantee to find the ‘best’ multiple alignment among all possible solutions for a given scoring scheme 1.Scring schemes for multiple alignments. 2.Algorthemic complexity of optimal multiple alignment methods .
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Progressive global alignment
Progressive global alignment is the most commonly used method to align biological sequences . This heuristic approach is very rapid, requires low memory space and offers good performance on relatively well- conserved , homologous sequences.
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Block –based global alignment
The sequences to be compared may share conserved blocks . Separated by non conserved regions containing large ideals . In such cases , the result of optimal or progressive alignment methods will depend greatly on the choice of gapv penalty parameters.
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Motif-based local multiple alignments
The sequences to compare may share similar regions , without necessarily being globally related. These homologous models may be duplicated in different sequences. In such cases it is not possible to compute a global alignment , but one may look for ‘good’ local alignments of segments taken in the sequences.
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Particular case; aligning protein-coding DNA sequences
It is sometimes necessary to align protein coding DNA sequences rather than proteins . 2 examples are the design to primers to identify related genes by PCR or for molecular phylogenies relying measure of substitution rates at synonymous(ks)or non –synonymous (Ka) sites of codons . Due to the degeneracy of the genetic code.
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Dynamic programming &computational complexity
MSA uses the dynamic programming technique to identify the globally optimal alignment solution. For proteins this method involve 2 sets 1.gap penalty 2.substitution matrix
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Databases of multiple alignments
1 .protein families 2 .protein domains 3 .RNA/DNA
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Protein families PIRALN HOVERGEN PROTOMAP megaclass
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Protein domains proDom PRINTS DOMO http://infobiogen .fr/gracy/domo/
PFAM .wustl.edu/pfam/ BLOCKS- .fhcrs.org
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DNA/RNA Ribosomal database project –http://www.cme.msu.edu/RDP.
The r RNA WWW server-http//rrna.uia.ac.be/ ACUTS-
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Advantage The advantage of using representations of multiple sequence alignment data in database searches is that more information is used ,resulting in higher sensitivity compared with pairwise searches.
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Disadvantage The disadvantage,or trade-off, is that such searches take longer to run and the results are often more difficult to interpret.
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Thank you…….
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