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Improved search heuristics find 20,000 new alignments between human and mouse genomes.

ABSTRACT: Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human-dog and melanogaster-pseudoobscura comparisons, but not for human-mouse, which suggests that we still miss many human-mouse alignments. Our optimized heuristics find ?20,000 new human-mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.

SUBMITTER: Frith MC

PROVIDER: S-EPMC3985675 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

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Improved search heuristics find 20,000 new alignments between human and mouse genomes.

Frith Martin C MC Noé Laurent L Noé Laurent L

Nucleic acids research 20140203 7

Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. B ...[more]

PMID: 24493737

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Project description:Gene clusters are groups of genes that are co-locally conserved across various genomes, not necessarily in the same order. Their discovery and analysis is valuable in tasks such as gene annotation and prediction of gene interactions, and in the study of genome organization and evolution. The discovery of conserved gene clusters in a given set of genomes is a well studied problem, but with the rapid sequencing of prokaryotic genomes a new problem is inspired. Namely, given an already known gene cluster that was discovered and studied in one genomic dataset, to identify all the instances of the gene cluster in a given new genomic sequence. Thus, we define a new problem in comparative genomics, denoted PQ-TREE SEARCH that takes as input a PQ-tree T representing the known gene orders of a gene cluster of interest, a gene-to-gene substitution scoring function h, integer arguments [Formula: see text] and [Formula: see text], and a new sequence of genes S. The objective is to identify in S approximate new instances of the gene cluster; These instances could vary from the known gene orders by genome rearrangements that are constrained by T, by gene substitutions that are governed by h, and by gene deletions and insertions that are bounded from above by [Formula: see text] and [Formula: see text], respectively. We prove that PQ-TREE SEARCH is NP-hard and propose a parameterized algorithm that solves the optimization variant of PQ-TREE SEARCH in [Formula: see text] time, where [Formula: see text] is the maximum degree of a node in T and [Formula: see text] is used to hide factors polynomial in the input size. The algorithm is implemented as a search tool, denoted PQFinder, and applied to search for instances of chromosomal gene clusters in plasmids, within a dataset of 1,487 prokaryotic genomes. We report on 29 chromosomal gene clusters that are rearranged in plasmids, where the rearrangements are guided by the corresponding PQ-trees. One of these results, coding for a heavy metal efflux pump, is further analysed to exemplify how PQFinder can be harnessed to reveal interesting new structural variants of known gene clusters.

Dataset Information

Improved search heuristics find 20,000 new alignments between human and mouse genomes.

Publications

Improved search heuristics find 20,000 new alignments between human and mouse genomes.

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