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In molecular biology and bioinformatics, the consensus sequence is the calculated order of most frequent residues, either nucleotide or amino acid, found at each position in a sequence alignment. It represents the results of multiple sequence alignments in which related sequences are compared to each other and similar sequence motifs are calculated. Such information is important when considering sequence-dependent enzymes such as RNA polymerase.[1]

Biological significance[edit]

A protein binding site, represented by a consensus sequence, may be a short sequence of nucleotides which is found several times in the genome and is thought to play the same role in its different locations. For example, many transcription factors recognize particular patterns in the promoters of the genes they regulate. In the same way restriction enzymes usually have palindromic consensus sequences, usually corresponding to the site where they cut the DNA. Transposons act in much the same manner in their identification of target sequences for transposition. Finally splice sites (sequences immediately surrounding the exon-intron boundaries) can also be considered as consensus sequences.

Thus a consensus sequence is a model for a putative DNA binding site: it is obtained by aligning all known examples of a certain recognition site and defined as the idealized sequence that represents the predominant base at each position. All the actual examples shouldn't differ from the consensus by more than a few substitutions, but counting mismatches in this way can lead to inconsistencies.[2]

Any mutation allowing a mutated nucleotide in the core promoter sequence to look more like the consensus sequence is known as an up mutation. This kind of mutation will generally make the promoter stronger, and thus the RNA polymerase forms a tighter bind to the DNA it wishes to transcribe and transcription is up-regulated. On the contrary, mutations that destroy conserved nucleotides in the consensus sequence are known as down mutations. These types of mutations down-regulate transcription since RNA polymerase can no longer bind as tightly to the core promoter sequence.

Sequence analysis[edit]

Developing software for pattern recognition is a major topic in genetics, molecular biology, and bioinformatics. Specific sequence motifs can function as regulatory sequences controlling biosynthesis, or as signal sequences that direct a molecule to a specific site within the cell or regulate its maturation. Since the regulatory function of these sequences is important, they are thought to be conserved across long periods of evolution. In some cases, evolutionary relatedness can be estimated by the amount of conservation of these sites.


The conserved sequence motifs are called consensus sequences and they show which residues are conserved and which residues are variable. Consider the following example DNA sequence:


In this notation, A means that an A is always found in that position; [CT] stands for either C or T; N stands for any base; and {A} means any base except A. Y represents any pyrimidine, and R indicates any purine.

In this example, the notation [CT] does not give any indication of the relative frequency of C or T occurring at that position. An alternative method of representing a consensus sequence uses a sequence logo. This is a graphical representation of the consensus sequence, in which the size of a symbol is related to the frequency that a given nucleotide (or amino acid) occurs at a certain position. In sequence logos the more conserved the residue, the larger the symbol for that residue is drawn; the less frequent, the smaller the symbol. Sequence logos can be generated using WebLogo, or using the Gestalt Workbench, a publicly available visualization tool written by Gustavo Glusman at the Institute for Systems Biology.[2]


Bioinformatics tools are able to calculate and visualize consensus sequences. Examples of the tools are JalView and UGENE.

See also[edit]


  1. ^ Pierce, Benjamin A. 2002. Genetics : A Conceptual Approach. 1st ed. New York: W.H. Freeman and Co.
  2. ^ a b Schneider TD (2002). "Consensus Sequence Zen". Appl Bioinformatics 1 (3): 111–119. PMC 1852464. PMID 15130839. 

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150 news items

Fred Hutch News Service

Fred Hutch News Service
Tue, 17 Nov 2015 10:22:30 -0800

The authors wondered if the sites in the slow binding class were enriched for certain shapes of DNA and whether that could account for their binding more than whether they matched the consensus sequence. They compared shape features of the DNA such ...


Mon, 23 Nov 2015 04:33:45 -0800

The HipB binding motif consists of inverted repeats of the consensus sequence TATCC. The two repeats are spaced by eight nucleotides. In the constructed ELRM of HipB, the model considered 25 association features and zero single-base features.


Tue, 17 Nov 2015 07:06:03 -0800

In order to create a consensus sequence of the novel variant, the contigs from three samples were realigned against the DWV genome. Any contigs containing sequence other than the novel variant were removed. If a contig contained the novel variant as ...


Thu, 05 Nov 2015 01:37:07 -0800

As noted in the Methods, we determined the consensus sequence of the HA gene for each sample using the information available at the Influenza Research Database (http://www.fludb.org). Afterwards, we used PhyML to generate phylogenetic trees across ...


Fri, 13 Nov 2015 07:00:00 -0800

Genes involved in the phosphorus starvation response (Pho regulon) are regulated by the two-component system PhoR/PhoB and share a consensus sequence named Pho box in their promoter regions. Using bioinformatics approaches, we identified ...

The Scientist

The Scientist
Wed, 19 Aug 2015 11:02:38 -0700

The researchers designed an artificial consensus sequence of the MERS-CoV glycoprotein based on sequences of isolates from past and ongoing MERS outbreaks. “[The sequence is changed slightly to emphasize conserved regions of the protein that ...
Wed, 16 Sep 2015 11:57:12 -0700

In an alternate experimental mode, a so-called circular consensus sequence (CCS) algorithm is applied to the data in bax.h5 files in an initial mapping step. The output from this step, a ccs.h5 file, then serves as the input to the SMRT Analysis ...


Tue, 27 Oct 2015 08:01:40 -0700

The maximum percentage of mismatches per read accepted was 5% and no gaps per read were allowed. To examine individual reads that make up the consensus sequence of each contig, the VICUNA analysis tool was used. To view the reads in Geneious, ...

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