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Parwati sihag
- 1. Sequence Alignment Method BY:- ParwatiSihag M.Sc. Biotechnology
- 2. SEQUENCE ALIGNMENT Itis the way of arranging the sequence of DNA, RNA, Protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationship between the sequence.
- 3. Global Alignment Inglobal alignment, two sequences to be aligned are assumed to be generally similar over their entire length. Alignment is carried out from beginning to end of both sequences to find the best possible alignment across the entire length between the two sequences. This method is more applicable for aligning two closely related sequences of roughly the same length.
- 5. Local Alignment Localalignment, on the other hand, does not assume that the two sequences in question have similarity over the entire length. It only finds local regions with the highest level of similarity between the two sequences and aligns these regions without regard for the alignment of the rest of the sequence regions. This approach can be used for aligning more divergent sequences with the goal of searching for conserved patterns in DNA or protein sequences. The two sequences to be aligned can be of different lengths.
- 7. •It is simplestmethod of alignment. •In pairwise alignment sequence there is a aligning of two sequences. •It is used in structural, functional and evolutionary analysis of sequence. •By pairwise alignment high accuracy result is obtained. •It is also used to identify homologous sequence. Advantage of Pairwise alignment
- 8. Disadvantage of pairwise alignment •Itis not useful when we align more than two sequence. •Pairwise alignment is difficult if we use long sequences for alignment.
- 9. •It is alsoknown as the dot plot method. •It is a graphical way of comparison two sequence in a two dimensional matrix. •In a dot matrix two sequences to be compared are written in the horizontal and vertical axis of the matrix. •The comparison is done by scanning each residue of one sequence for similarity with all residue in the other sequence. DOT MATRIX METHOD
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- 11. DYNAMIC PROGRAMING METHOD Itis the method that determines optimal alignment by matching two sequence for all possible pair of character between the two sequence. It is similar to dot matrix as,it finds alignment in a more quantitative way by converting a dot matrix into scoring matrix
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- 13. MULTIPLE SEQUENCE ALIGNMENT •Itis a sequence alignment of three or more biological sequence, generally protein, DNA, or RNA. •MSAs require more sophisticated methodologies than pairwise alignment because they are more computational complex. •Most multiple sequence alignment program use heuristic methods rather than global optimization. • Because identifying the optimal alignment between more than a few sequence of moderate length is prohibitively computational expensive.
- 16. Advantage of multiplesequence alignment •MSA is used for comparing more than two sequences. •It is used to identify homologous residue within sequence. •To find out identical sequence.
- 17. Disadvantage of multiple sequencealignment •It is more complex method as compare to pairwise allignment. •It is more time consuming. •Due to gap within the sequence it show error. •Low accuracy as compare to pairwise sequence allignment.
- 18. Online tool forsequence alignment There are following online tool for sequence alignment. •BLAST •FASTA •CLUSTAL OMEGA
- 19. BASIC STEPS PERFORMEDIN BLAST Open NCBI SITE All data bases (choosed gene ) Enter the name of gene(thyroid peroxidase) Click on search Get list of search result Get the gene I.D and location Click on FASTA Obtained FASTA format and NCBI reference sequence Run BLAST
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- 27. NCBI Enter All databases Select Nucleotideor Protein Name of Protein, gene or nucleotide gene open Select file BASIC STEPS INVOLVED IN FASTA
- 28. FASTA Format Copy andpaste the FASTA format file in BLAST query file Run BLAST
- 34. It is themost commonly used approach to multiple sequence alignment. It speeds up the alignment of multiple sequence through a multistep process. It first conducts pairwise alignment for each possible pair of sequences using the Needleman-Wunsch alignment and record these similarity scores from the pairwise comparison. PROGRESSIVE ALIGNMENT
- 35. •The scores arethen converted into evolutionary distances to generate a distance matrix for all the sequence involved. •As a result,a phylogenetic tree is generated using the neighbor-joining method. •In the next step,the closest sequence based on guide tree is aligned with the consensus sequence using dynamic programming.
- 37. •It is basedon the idea that an optimal solution can be found by repeatedly modifying existing suboptimal solution. •The procedure starts by producing a low quality alignment and gradually improves it by iterative realignment through well defined procedures until no more improvement in the alignment can be achieved. ITERATION ALIGNMENT
- 39. It performs multiplealignment through two sets of iteration. 1.Outer iteration=In this an initial random alignment is generated that is used to derive a UPGMA tree 2.Inner iteration=In this the sequence are randomly divided into two groups The process is repeated over many cycles until there is no further improvement in the overall alignment scores.
- 40. •If a residuematch is found, a dot is placed within the graph. •Otherwise, the matrix position are left bank. •When the two sequences have substantial regions of similarity, many dots line up to form contiguous diagonal lines, which reveal the sequence alignment. •If there are interruptions in the middle of a diagonal line, they indicate insertion or deletion