MUSCLE: multiple sequence alignment with high accuracy and high throughput

Abstract

We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

Figure 1

Motifs misaligned by a progressive method. A set of 41 sequences containing SH2 domains (44) were aligned by the progressive method T-Coffee (above), and by MUSCLE (below). The N-terminal region of a subset of five sequences is shown. The highlighted columns (upper case) are conserved within this family but are misaligned by T-Coffee. It should be noted that T-Coffee aligns these motifs correctly when given these five sequences alone; the problem arises in the context of the other sequences. Complete alignments are available at http://www.drive5.com/muscle.

Figure 2

This diagram summarizes the flow of the MUSCLE algorithm. There are three main stages: Stage 1 (draft progressive), Stage 2 (improved progressive) and Stage 3 (refinement). A multiple alignment is available at the completion of each stage, at which point the algorithm may terminate.