Homology

Homology is a similarity due to a shared common ancestor in . Therefore, homology is the result of ; in contrast, is a consequence of . Originally, homology was used for morphological characters, such as organs. For example, homologous organs were defined as organs that are related to each other through a common descent, even though now they perhaps exhibit different functions. At the present time, however, the term is used in relation to molecular traits, in particular, nucleotide sequences and amino acid sequences.

 Any two sequences can be compared by alignment, where maximum similarity is used as the basis of measurement. Once the alignment is made, the proportion of identical nucleotides, site by site, can be computed. This proportion is the simplest measure for the “degree of sequence similarity.” When the proportion is statistically significant, it is reasonable to say that the two sequences being compared are homologous, because the probability that the similarity was derived by mere chance is, in most cases, extremely small. In general, if the proportion of identical sites is at least 25–30% in an amino acid sequence, or over 40% in a nucleotide sequence, the two sequences may be said to be homologous. This is because there is an extremely high possibility that this similarity is due to a common ancestor and a very low probability that it occurred randomly. The degree of sequence similarity can then be called the “degree of homology.”

By using sequence similarity, one can search for homologous sequences in the nucleotide and amino acid . A given sequence is used as a query sequence and is compared with a sequence in an entry of the database by sliding one site in each comparison, until all possible comparisons have been made. This procedure is repeated for all entries of the database. Only the entries where the sequence homology is statistically significant to the query sequence are noted. This search is called a “homology search.” In practice, algorithms called “dynamic programming” are used to make the homology search more efficient.

The homology search is particularly useful for predicting the function of a newly identified gene or protein. This is based on the following logic: In general, conservation of a sequence is known to be stronger for functionally important regions of a protein. If we search a sequence and find a region where conservation is strong, it is reasonable to conclude that the region is functionally important and that the function is possibly shared by the homologous sequences. Doolittle constructed his own public database of amino acid sequences, which were deduced from nucleotide sequences (1). He conducted a primitive homology search by using a viral oncogene (sis) as a query sequence and then found homology with human (Figure 1). He found that the homology was very high, and for this reason he proposed that the sis gene may have a function as a . Following Doolittle's prediction, experiments confirmed the hypothesis (2). In fact, it was found that the sis gene was the host gene that was inserted into the viral genome. This was the first report in which a homology search was successful for predicting biological function of an unknown sequence. Since then, the homology search has become a very popular tool in molecular biology.

References                                                                                     

“Homology” in , Vol. 2, pp. 1165–1166, by T. Gojobori; “Homology” in  (online), posting date: January 15, 2002, by T. Gojobori, National Institute of Genetics, Shizuoka, Japan.

1. R. F. Doolittle (1981) Science 214, 149–159. 

2. T. F. Deuel, J. S. Huang, S. S. Huang, P. Stroobant, and M. D. Waterfield (1983) Science 221, 1348–1350. 

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