BLAST (Basic Local Alignment Search Tool)

 

  BLAST (Basic Local Alignment Search Tool) is a widely used bioinformatics algorithm for comparing biological sequences, such as DNA, RNA, or protein sequences, to sequence databases. It identifies regions of local similarity between sequences, helping researchers find homologous sequences and infer functional and evolutionary relationships.

Key Features of BLAST

1. Database Searching:

   • BLAST compares a query sequence against a database of sequences to find regions of similarity.

2. Local Alignment:

   • Unlike global alignment methods that compare entire sequences, BLAST focuses on finding local regions of similarity, which are often more informative.

3. Statistical Significance:

   • BLAST provides statistical scores, such as E-values, to assess the significance of the matches. Lower E-values indicate more statistically significant matches.

BLAST Variants

1. BLASTN:

   • Purpose: Compares nucleotide sequences against nucleotide databases.
   • Use Case: Identifying homologous genes or sequences in genomic databases.

2. BLASTP:

   • Purpose: Compares protein sequences against protein databases.
   • Use Case: Finding homologous proteins or functional domains.

3. BLASTX:

   • Purpose: Translates nucleotide sequences into protein sequences and compares them against protein databases.
   • Use Case: Identifying potential protein-coding genes or functional domains in nucleotide sequences.

4. TBLASTN:

   • Purpose: Compares protein sequences against translated nucleotide databases (i.e., nucleotide sequences translated into all possible protein sequences).
   • Use Case: Identifying homologous proteins in genomic sequences with unknown coding regions.

5. TBLASTX:

   • Purpose: Compares translated nucleotide sequences against translated nucleotide databases.
   • Use Case: Finding homologous genes across different organisms when both sequences are nucleotide sequences.

How BLAST Works

1. Query Input:

   • A biological sequence (DNA, RNA, or protein) is input as the query.

2. Database Search:

   • The query sequence is compared against a database of sequences. The comparison is typically performed using a heuristic approach to find high-scoring segment pairs (HSPs) quickly.

3. Alignment and Scoring:

   • The algorithm identifies local alignments between the query and database sequences, scoring them based on similarity. The scoring system includes match scores, mismatch penalties, and gap penalties.

4. Statistical Analysis:

   • BLAST calculates E-values to determine the statistical significance of the alignments. An E-value represents the number of hits one might expect to find by chance with a given score. Lower E-values indicate higher confidence in the results.

5. Results Display:

   • BLAST presents the results in a table format, including information on the sequence alignment, scores, E-values, and graphical representations of the matches.

Applications of BLAST

1. Gene Identification:

   • Homology Searching: Identifying genes and their functions by finding similar sequences in databases.

2. Functional Annotation:

   • Domain Prediction: Predicting functional domains or motifs in proteins by comparing against known domain databases.

3. Evolutionary Studies:

   • Phylogenetic Analysis: Studying evolutionary relationships between genes or proteins by identifying conserved sequences.

4. Genomic Research:

   • Annotation: Annotating newly sequenced genomes by identifying homologous genes or functional elements.

5. Drug Discovery:

   • Target Identification: Identifying potential drug targets by comparing sequences of interest against existing databases.

Advantages of BLAST

1. Speed and Efficiency:

   • Heuristic Approach: Uses heuristic methods to provide fast and efficient sequence comparisons.

2. Flexibility:

   • Multiple Variants: Offers different variants for nucleotide and protein sequences, as well as translated sequences.

3. User-Friendly:

   • Accessible Interface: Available through web-based platforms (e.g., NCBI BLAST) and command-line tools, making it accessible to a broad range of users.

Limitations of BLAST

1. Heuristic Nature:

   • Approximate Results: BLAST uses heuristic methods, which may miss some alignments or produce less accurate results compared to exhaustive search methods.

2. Database Dependence:

   • Database Size: The results are dependent on the quality and completeness of the database being searched. Missing or incomplete databases may lead to false negatives.

3. Scoring Parameters:

   • Parameter Sensitivity: Results can vary based on the scoring parameters used, which may require optimization for different types of sequences or searches.

Recent Advances in BLAST

1. BLAST+ Suite:

   • Enhanced Tools: The BLAST+ suite includes updated versions of BLAST tools with improved performance and additional features.

2. Integration with Other Tools:

   • Combined Approaches: BLAST is often used in conjunction with other bioinformatics tools and databases to enhance the analysis of sequence data.

3. Cloud-Based Solutions:

   • Scalability: Cloud-based platforms offer scalable solutions for running large-scale BLAST searches on extensive sequence databases.

References

• Altschul, S.F., Gish, W., Miller, W., Myers, E.W., and Lipman, D.J. (1990). "Basic local alignment search tool." Journal of Molecular Biology, 215(3), 403-410. The original paper introducing BLAST and its algorithm.

• Camacho, C., Coulouris, G., Avagyan, V., et al. (2009). "BLAST+: architecture and applications." BMC Bioinformatics, 10, 421. Describes the updated BLAST+ tools and their applications.

• Madden, T.L. (2003). "The BLAST Sequence Analysis Tool." In: The NCBI Handbook. Provides a comprehensive guide to using BLAST and interpreting its results.

BLAST remains a cornerstone of bioinformatics, offering a robust and efficient method for sequence comparison and functional annotation across a wide range of biological research applications.