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      Genomic alignment.

      Journal of Molecular Evolution

      Algorithms, Software, methods, Sequence Alignment, Reading Frames, Molecular Sequence Data, genetics, HIV-2, HIV-1, Genes, pol, Genes, gag, DNA, Viral, Base Sequence, Amino Acid Sequence

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          Abstract

          As sequencing techniques become increasingly efficient, the average length of a sequence is bound to grow. Traditional sequence-comparison algorithms can either compare DNA or protein, but not a mixture, which is actually a common situation. Most obtained DNA sequences contain coding regions, and it is more reliable to compare the coding regions as protein than just as DNA. A heuristic algorithm is presented that can compare DNA with both coding and noncoding regions, but that also can compare multiple reading frames and determine which exons are homologous. A program, GenA1 (Genomic Alignment), was developed that implements the algorithm. Its use is demonstrated on two retroviruses.

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