2003
DOI: 10.1093/bioinformatics/btg1025
|View full text |Cite
|
Sign up to set email alerts
|

Detection and validation of single gene inversions

Abstract: We find a large excess of short inversions, especially those involving a single gene, in comparison with a random inversion model. This is demonstrated through comparison of four pairs of bacterial genomes, using a specially-designed implementation of the Hannenhalli-Pevzner theory, and validated through experimentation on pairs of random genomes matched to the real pairs.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

1
46
0

Year Published

2005
2005
2018
2018

Publication Types

Select...
8

Relationship

0
8

Authors

Journals

citations
Cited by 54 publications
(47 citation statements)
references
References 16 publications
1
46
0
Order By: Relevance
“…A recent study (Lefebvre et al, 2003) indicates that, at least in prokaryotic genomes, short inversions are much more likely than long ones; work on developing new models of evolution that take such results into account is in progress. Applying these methods to large eukaryotic genomes may yield some surprises, however, since there is evidence that certain breakpoints in chromosomes are "hot spots" for rearrangements (Pevzner and Tesler, 2003); if an inversion is thus "anchored" at a fixed position in the chromosome, its net effect over several events is to produce one breakpoint per event, which might be better modelled with breakpoints than with inversions.…”
Section: Parsimony-based Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…A recent study (Lefebvre et al, 2003) indicates that, at least in prokaryotic genomes, short inversions are much more likely than long ones; work on developing new models of evolution that take such results into account is in progress. Applying these methods to large eukaryotic genomes may yield some surprises, however, since there is evidence that certain breakpoints in chromosomes are "hot spots" for rearrangements (Pevzner and Tesler, 2003); if an inversion is thus "anchored" at a fixed position in the chromosome, its net effect over several events is to produce one breakpoint per event, which might be better modelled with breakpoints than with inversions.…”
Section: Parsimony-based Methodsmentioning
confidence: 99%
“…The GNT model contains the Nadeau-Taylor model as a special case: just set α = β = 0. Extensions of this simple model in which the probability of an event depends on the length of the segment affected by the event have been proposed (Bender et al, 2004), but no solid data exist to support one model over another; all that appears certain (see Lefebvre et al (2003)) is that short inversions are more likely than long ones in prokaryotes. Similarly, multichromosomal rearrangements such as translocations and events that affect the gene content of chromosomes such as duplications, insertions, and deletions, have all been considered, but once again we have insufficient biological data to define any model with confidence.…”
Section: Stochastic Models Of Evolutionmentioning
confidence: 99%
“…Yet, aside from methods that weight inversions based on their length [12][13][14][15][16], to our knowledge no algorithmic work exists in this direction.…”
Section: Introductionmentioning
confidence: 99%
“…Ajana et al [9] used these results to support the replication-directed reversal hypothesis. Lefebvre et al [11] and Sankoff et al [12] used similar methodology to gain insight into the distribution of reversal lengths between genomes. Algorithms that attempt to more succinctly represent all shortest-length scenarios [13,14] have also been developed.…”
Section: Introductionmentioning
confidence: 99%
“…This will afford a marked speedup of the aforementioned methods [9][10][11][12][13][14], since listing all sorting reversals is the kernel of repeated computation in each of them, especially when applied to permutations of sizes 3 × 10 3 to 3 × 10 5 (the size of bacterial or mammalian genomes).…”
Section: Introductionmentioning
confidence: 99%