Multiple Sequence Alignment (MSA) aligns three or more sequences simultaneously. This is essential for:
- **Phylogenetic analysis**: Understanding evolutionary relationships - **Conserved region identification**: Finding functional domains - **Motif discovery**: Identifying shared sequence patterns - **Structure prediction**: Aligning sequences for 3D structure analysis
Advantages over pairwise alignment
- Identifies regions conserved across multiple sequences - Better evolutionary signal detection - More robust than pairwise comparisons
Required
- FASTA format with three or more sequences - Can include DNA, RNA, or protein sequences
Parameters
- **Sequence Type**: DNA/RNA or Protein - **Alignment Algorithm**: Selected automatically based on sequence type
Example input
``` >seq1 ATGCGATCG >seq2 ATGCGATCA >seq3 ATGCGATCG >seq4 ATGCGATCT ```
Alignment Results
- All input sequences aligned with gaps inserted - Conserved positions (columns with identical characters) - Variable positions (columns with different characters) - Gap patterns indicating insertions/deletions
Alignment Quality
- Alignment score (if calculated) - Number of conserved sites - Percentage identity across sequences
Visual Representation
- Sequences displayed in aligned format - Gaps shown as dashes (-) - Conserved positions easily identifiable
**1. Phylogenetic Tree Construction** - Prepare sequences for tree building - Identify orthologous sequences - Study evolutionary relationships
**2. Functional Domain Identification** - Find conserved functional regions - Identify protein domains - Predict function from conservation
**3. Primer Design** - Identify conserved regions for primer binding - Design degenerate primers - Find universal primers
1. **Sequence quality**: Use high-quality, verified sequences 2. **Sequence selection**: Include appropriate diversity (not too similar, not too different) 3. **Homolog identification**: Ensure sequences are homologous (related by evolution) 4. **Gap handling**: Understand gap placement and interpretation 5. **Algorithm selection**: Different algorithms (Clustal, MUSCLE, etc.) may give different results