In Mauve Product Key, multiple genomes are represented as sets of non-overlapping DNA fragments (also called “segments” or “blocks”). Each fragment or block may be aligned relative to the corresponding fragment or block in another genome. Some fragments or blocks will be reference fragments or blocks, containing one or more reference homologs.
Mauve uses a sequence similarity matrix to identify homologous pairs. Mauve uses two sequences to be aligned as a window within which it scans for the most probable alignment. It starts by finding the most similar region of a given genome. By comparing this region with the rest of the genome, it is possible to identify genes which are orthologs across many genomes, as well as which genes are unique to each genome.
In Mauve, the multiple alignment of a genome is represented as a grid of blocks. Mauve constructs the multiple genome alignment by repeatedly aligning fragments from one genome to a reference genome fragment or block. The resulting alignment is refined by progressively extending fragments from the end of one fragment into gaps between fragments from the other genome. The final alignment is the union of all the fragments from each genome.
Mauve uses a table of relative orientation scores to guide the placement of fragments from one genome onto blocks from the other genome. During the construction of the alignment, Mauve builds an adjacency table for each genome. In this table, blocks of the genome are represented as row entries and fragments of the genome are represented as column entries. Relative orientation information is recorded in each cell of the adjacency table. Mauve uses the relative orientation information to rank blocks in one genome relative to blocks in another genome. The blocks are then sorted in the order of their rank and the top-ranked blocks from each genome are placed onto a grid of fragments.
Mauve uses an alignment graph for representing the overall structure of the alignment. Each of the alignment graphs in Mauve is a directed acyclic graph. Each node of the graph corresponds to a block in one genome and each edge of the graph corresponds to a fragment of one genome being aligned onto a fragment of another genome. Edges are weighted by the score of the alignment between the corresponding fragments. Edges whose weights are all equal are removed and the resulting undirected graph is processed for minimum spanning tree construction.
Mauve uses a variety of techniques to discover large-scale evolutionary events such as inversions and rearrangement. Mauve finds rearrangements by sorting
Mauve aligns genomes using a greedy algorithm. The basis of this algorithm is to find a locally optimal alignment using some of the optimal alignments found by a progressive alignment. Mauve also includes a number of useful alignment views. The main Mauve user interface is an alignment editor that allows the user to visually inspect the alignments produced by Mauve. The Mauve alignment view consists of various displays of information about the alignments, including the placement of gaps in the alignments.
Mauve uses the concept of a ‘backbone’ to describe the overall layout of the genome being aligned. This backbone is constructed by first finding the largest common ‘block’ (a maximally ordered region of shared similarity) of the genome pairs being aligned. Mauve then uses the backbone to guide it to find all of the best possible ways of placing the remaining blocks of the genomes.
In order to maximize the placement of the blocks in the alignment, Mauve utilizes the concept of a ‘score space’. The score space is a continuous measure of the quality of a placement of a block in the alignment. The placement that Mauve considers to be the best placement is one that corresponds to the peak of the score space at that point in the alignment.
For each block in the alignment, Mauve begins by computing a backbone. The backbone is essentially a pointer into the genome, given by the largest common ‘block’ between the two genomes. Mauve then searches all of the possible placements for this block, beginning with a locally optimal placement that corresponds to the backbone.
The placement of a block in Mauve's alignment is defined by three parameters: the start, the end, and the score of the block. Mauve first attempts to place the block at the end of the backbone. It then searches for the best possible placement of the block, beginning with a locally optimal placement that corresponds to the backbone. The placement that Mauve considers to be the best placement is one that corresponds to the peak of the score space at that point in the alignment. Mauve uses the placement of a block to define the placement of the rest of the genome, in such a way that the placement corresponds to the peak of the score space.
The Mauve GUI is a specially designed alignment editor, allowing the user to visually inspect the multiple genome alignments produced by Mauve. Mauve uses the alignment views to show each genome as a set of colored blocks, so that the placement of these blocks in
Mauve has been designed from the ground up to efficiently perform a variety of biological tasks. It incorporates a number of innovations in the field of multiple genome alignment:
Chimera Validation: Mauve finds one-to-one correspondence between each base in each genome. A new Mauve alignment is constructed for each alignment test until a perfect match is found between every genome.
Siblings: In Mauve, a genome is called a sibling if its genome is a simple rearrangement of the genome in question (for example, inversions or transpositions). Mauve aligns each sibling to one of its children, each of which is another sibling.
De Bruijn Graphs: The genetic distance between a pair of genomes, or the length of the shortest path between the genomes, is determined by a de Bruijn graph constructed using the sequences of each genome. Mauve aligns de Bruijn graphs rather than sequences, and for this reason Mauve is able to align more genomes than other multiple genome aligners.
Motif Identification: Mauve analyzes the pairwise alignments between the genomes to identify shared motifs, which are then used to construct a multiple alignment of the genomes. Mauve uses the Constrained Extension Model (CEM) for motif identification.
Missing Genome Alignment: Mauve also solves the multiple genome alignment problem in the presence of missing genomes. In this case, Mauve searches for the missing genomes in the collection of partial alignments (in some cases, it is possible that there is only one missing genome).
Ortholog Detection: Mauve uses a similarity score derived from a single-linkage clustering of the genomes to determine whether two genomes are orthologs.
Projection: Mauve processes an arbitrary number of genomes in one or more files. There is no restriction on the number of genomes and their sizes.
Alignment Selection: Mauve runs a set of pairwise alignments between every possible combination of the genomes. Each pairwise alignment is scored by a metric based on the genome sequences.
There are two ways to compute a pairwise alignment between two genomes:
Creating a de Bruijn graph from each genome and then finding the longest path in the graph
Constructing a multiple alignment from a pair of genomes
Mauve uses the second approach. Mauve creates a single de Bruijn graph and then searches the graph for paths that extend from one genome to another. Mauve applies the algorithm of Wu and Jiang (2006) to efficiently identify the paths that span two genomes, and then extends the paths one genome at a time, searching for a maximum-length alignment as it extends. For details on Mauve's approach to creating and searching for paths, please refer to Mauve documentation.
An additional approach has been developed to align non-coding regions of genomes.
OS: 64-bit Windows 7/Windows 8/Windows 10 (64-bit version)
64-bit Windows 7/Windows 8/Windows 10 (64-bit version) CPU: Intel Core i3 2100 (2.3 GHz) or equivalent
Intel Core i3 2100 (2.3 GHz) or equivalent RAM: 4 GB RAM
4 GB RAM Graphics: NVIDIA GTX 560 (2 GB) or equivalent
NVIDIA GTX 560 (2 GB) or equivalent HDD: 500 GB of free space
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