- BLAST, which stands for Basic Local Alignment Search Tool, is one of the most widely used computational tools in molecular biology and bioinformatics. It is designed to find regions of similarity between biological sequences and can compare nucleotide or protein sequences against sequence databases. BLAST is widely used to investigate unknown DNA or protein sequences, identify genes and homologs, study sequence relationships, and support many types of genomic and molecular biology research.
- The basic idea behind BLAST is relatively simple. A researcher has a sequence of interest, called the query sequence, and wants to know whether similar sequences are already present in a biological sequence database. BLAST searches the database for matching or similar regions and produces alignments together with statistical information that helps the researcher evaluate the significance of the matches. The sequences found in the database are commonly referred to as subject sequences.
- The word “local” in Basic Local Alignment Search Tool is important. BLAST is designed to identify regions of similarity rather than requiring two sequences to match across their entire lengths. This makes BLAST particularly useful for biological sequences that share only part of their sequence because of conserved genes, domains, mutations, insertions, deletions, evolutionary divergence, or differences in sequence length.
- BLAST is therefore different from a simple comparison in which two sequences are aligned from beginning to end. A local similarity search can identify a biologically meaningful region even when the remainder of the sequences is very different. NCBI also provides a separate Global Alignment tool for comparing two sequences across their entire span, illustrating the conceptual difference between local and global sequence alignment.
- BLAST can be used with both nucleotide and protein sequences. For example, a DNA sequence can be compared with nucleotide sequences using BLASTN, while a protein sequence can be compared with protein sequences using BLASTP. Other BLAST programs perform translated searches, allowing nucleotide sequences to be compared with protein databases or protein sequences to be compared with translated nucleotide databases.
- For researchers working with DNA sequences, BLASTN is one of the most important BLAST programs. BLASTN searches a nucleotide query against a nucleotide database and is commonly used for identifying DNA sequences, comparing genes, examining genomic regions, and investigating sequence similarity. NCBI’s nucleotide BLAST interface accepts nucleotide sequences in formats such as FASTA and can also accept accession numbers and other sequence identifiers.
- BLASTP performs the corresponding type of search for proteins. It compares a protein query against a protein database and is commonly used to identify similar proteins, investigate possible protein functions, and find members of protein families. Because protein sequences can remain functionally related despite substantial nucleotide-level differences, protein-based searches can sometimes reveal relationships that are difficult to detect using direct nucleotide comparison.
- Other BLAST programs extend these capabilities. BLASTX translates a nucleotide query in all six reading frames and searches the resulting protein sequences against a protein database. TBLASTN compares a protein query against a nucleotide database after dynamically translating the nucleotide sequences. TBLASTX translates both the nucleotide query and nucleotide database sequences before performing the comparison. These approaches can be useful when the relationship between nucleotide and protein sequences needs to be investigated.
- There are also specialized BLAST approaches for particular research questions. For example, PSI-BLAST can be used to identify more distantly related proteins through iterative searches, while other NCBI tools support conserved-domain analysis and specialized sequence comparisons. The appropriate program therefore depends on the type of query sequence, the database being searched, and the biological question being investigated.
- One of the most common uses of BLAST is sequence identification. Suppose a researcher obtains an unknown DNA sequence from a laboratory experiment. The researcher can submit the sequence to a nucleotide BLAST search and compare it with sequences in a database. If the query produces strong matches to known sequences, the researcher can use those matches as evidence about the possible identity or origin of the unknown sequence.
- This is where BLAST becomes especially useful in combination with GenBank. GenBank is a major public nucleotide sequence database, whereas BLAST is a tool for searching for sequence similarity. A BLAST search can identify sequences that resemble the query, and the researcher can then examine the corresponding GenBank records to obtain additional information about the matching sequences.
- A GenBank record may contain the sequence itself together with information about the organism, accession number, sequence description, genes, coding sequences, RNA features, source information, and other annotations. Consequently, BLAST can be viewed as a way of finding potentially relevant sequences, while the associated database records provide the biological context needed to interpret those sequences.
- BLAST is also widely used for gene identification. An experimentally obtained sequence may not have an obvious annotation, but a similarity search may reveal that it resembles a known gene from another organism. Researchers can then examine the matching sequences and their annotations to determine whether the query is likely to represent the same gene or a related member of a gene family.
- Another important application is homology analysis. Homologous sequences are sequences that share a common evolutionary origin. BLAST can help identify candidate homologs by finding statistically significant sequence similarities. However, sequence similarity alone should not automatically be interpreted as definitive proof of homology or identical biological function. Additional evidence and appropriate evolutionary analyses may be required, particularly for distantly related sequences.
- BLAST is also useful in comparative genomics. Researchers can compare sequences from different organisms to identify conserved regions and investigate how genes or genomic regions vary across species. Highly conserved sequences may indicate regions that have been maintained through evolution because of their biological importance, whereas more variable regions may provide useful information for distinguishing organisms or evolutionary lineages.
- In microbiology, BLAST is frequently used to investigate bacterial, archaeal, fungal, viral, and other microbial sequences. Researchers may compare a newly sequenced gene or genomic fragment with reference sequences to help identify an organism, characterize a gene, investigate possible contamination, or examine genetic variation. The reliability of such conclusions depends on the quality of the query sequence, the reference database, and the interpretation of the resulting matches.
- BLAST can also be useful for sequence quality control. If a researcher expects to have obtained a particular gene or genomic region, the sequence can be searched against an appropriate database to determine whether it resembles the expected target. Unexpected matches can sometimes reveal sequencing problems, contamination, sample mix-ups, incorrect assemblies, or other issues that require further investigation.
- An important part of understanding BLAST is recognizing that the program does not simply report whether two sequences are “the same.” BLAST calculates alignment scores and statistical measures that help describe the strength of a match. Commonly encountered measures include percentage identity, alignment length, query coverage, bit score, and E-value. These measurements should be considered together when interpreting a result.
- The percentage identity describes how many aligned positions are identical between the query and subject sequences. A high percentage identity generally indicates strong sequence similarity, but the length of the alignment is equally important. A short region with 100% identity may be less informative than a nearly full-length alignment with slightly lower identity.
- The E-value, or expect value, is another central BLAST statistic. It estimates how many matches with a score at least as good as the observed match would be expected by chance under the search conditions. In general, smaller E-values provide stronger statistical evidence for a non-random match. The E-value should nevertheless be interpreted in relation to sequence length, database size, alignment quality, and biological context.
- The bit score is a normalized alignment score that can be used to compare alignment scores from different searches. Higher bit scores generally indicate stronger alignments. Together with the E-value and other alignment statistics, the bit score helps researchers assess the strength of BLAST matches.
- BLAST results should therefore not be interpreted by looking at only one number. A reliable analysis considers several characteristics of the match, including how much of the query is aligned, how similar the sequences are, how statistically significant the match is, and whether the biological information associated with the subject sequence makes sense.
- The choice of BLAST program and database is also critical. A DNA sequence should generally be searched with an appropriate nucleotide-based program when the research question concerns nucleotide similarity. A protein query requires an appropriate protein search. In some situations, translated searches are more appropriate than direct nucleotide comparison, particularly when the researcher expects homologous proteins but the nucleotide sequences may have diverged substantially.
- BLASTN itself provides different search strategies. For example, megablast is optimized for highly similar nucleotide sequences and is particularly useful for comparisons involving closely related sequences. Discontiguous megablast is designed for some comparisons involving more divergent sequences, while the standard BLASTN approach can provide greater sensitivity for certain searches. The appropriate choice depends on the expected level of similarity and the purpose of the analysis.
- BLAST can be used through the NCBI BLAST web interface, which makes sequence similarity searching accessible without requiring local installation. Researchers can enter or upload sequences, select an appropriate BLAST program and database, submit the search, and examine the resulting alignments and statistics through a web browser.
- For larger or repeated analyses, researchers can use BLAST+, NCBI’s collection of command-line BLAST applications. BLAST+ allows researchers to perform searches locally, prepare custom databases, automate analyses, and integrate BLAST into bioinformatics workflows. It is particularly useful when hundreds, thousands, or millions of sequences need to be analyzed or when a researcher needs to search against a custom sequence collection.
- A simple BLAST workflow can therefore be described as prepare a query sequence → select the appropriate BLAST program → choose a suitable database → perform the search → examine the hits → evaluate the alignments and statistics → investigate the corresponding sequence records → interpret the biological significance.
- For example, a researcher who has obtained an unknown 700-base-pair DNA fragment might begin with BLASTN. The resulting hits could reveal sequences with substantial similarity to a known gene. The researcher would then examine percentage identity, alignment coverage, E-value, and the actual alignment. If the strongest reliable matches cover almost the entire query and consistently correspond to the same gene, the evidence may support identification of the fragment. The researcher can then examine the corresponding GenBank records for additional annotation and biological context.
- BLAST is also valuable because it can be applied at many levels of biological investigation. It can help answer questions such as: What organism might this sequence come from? Does this DNA fragment resemble a known gene? Is this protein related to a known protein family? Which organisms contain similar sequences? Is a genomic region conserved? Does an experimentally obtained sequence match the expected reference sequence?
- At the same time, BLAST has limitations. A sequence similarity result does not automatically establish biological function, evolutionary history, or species identity. Closely related organisms may have extremely similar sequences, while unrelated sequences can share short conserved regions. Database errors, incomplete annotations, sequencing errors, contamination, and database representation can also affect interpretation.
- Short sequences require particular caution because relatively short matches can occur by chance or may not contain enough information to distinguish closely related sequences. Low-complexity and repetitive regions can also complicate sequence similarity searches. Consequently, BLAST results should be treated as evidence that needs biological interpretation rather than as an automatic answer to every sequence-identification problem.
- BLAST is therefore best understood as a sequence similarity-searching framework rather than simply a database search engine. It provides a computational method for discovering potentially meaningful relationships between biological sequences. The researcher must then evaluate the quality and significance of those relationships using the alignment statistics, database information, sequence annotations, and biological context.
- The importance of BLAST in modern biology comes from its ability to connect an unknown or newly obtained sequence with the enormous amount of sequence information already available. A single DNA or protein sequence can be compared with millions of reference sequences, potentially revealing its identity, evolutionary relationships, conserved regions, or membership in a gene or protein family.
- BLAST has become an essential part of workflows in bioinformatics, genomics, molecular biology, microbiology, evolutionary biology, genetics, biodiversity research, and sequence annotation. Its integration with databases such as GenBank makes it particularly powerful because sequence similarity results can be connected directly with biological records and annotations.
- In summary, BLAST is a tool for finding regions of similarity between biological sequences. It can compare nucleotide or protein queries with sequence databases and provides alignments and statistical measures that help researchers evaluate the results. BLASTN is commonly used for nucleotide sequences, BLASTP for proteins, and translated BLAST programs provide additional ways to investigate relationships between nucleotide and protein sequences. Used together with GenBank and other sequence resources, BLAST provides one of the fundamental starting points for modern sequence analysis.
- Understanding the basic principles of BLAST provides the foundation for more advanced sequence-analysis topics. The next articles can examine BLASTN in detail, how to use NCBI BLAST step by step, how to interpret BLAST results, E-values and bit scores, percentage identity and query coverage, BLASTN versus megablast, and how to run BLAST locally with BLAST+.
