Super short operations on both gene order and intergenic sizes

Oliveira, André Rodrigues; Jean, Géraldine; Fertin, Guillaume; Dias, Ulisses; Dias, Zanoni

doi:10.1186/s13015-019-0156-5

Cited by 9 publications

(9 citation statements)

References 17 publications

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“… Inversions of one or two regions Oliveira et al. ( 2019 ), Galvao et al. ( 2017 ) Due to biological evidence that the probability of an inversion occurring can depend on the size of the segment being inverted (Darling et al.…”

Section: Rearrangement Modelsmentioning

confidence: 99%

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Rearrangement Events on Circular Genomes

Stevenson,

Terauds,

Sumner

2023

Bull Math Biol

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Early literature on genome rearrangement modelling views the problem of computing evolutionary distances as an inherently combinatorial one. In particular, attention is given to estimating distances using the minimum number of events required to transform one genome into another. In hindsight, this approach is analogous to early methods for inferring phylogenetic trees from DNA sequences such as maximum parsimony—both are motivated by the principle that the true distance minimises evolutionary change, and both are effective if this principle is a true reflection of reality. Recent literature considers genome rearrangement under statistical models, continuing this parallel with DNA-based methods, with the goal of using model-based methods (for example maximum likelihood techniques) to compute distance estimates that incorporate the large number of rearrangement paths that can transform one genome into another. Crucially, this approach requires one to decide upon a set of feasible rearrangement events and, in this paper, we focus on characterising well-motivated models for signed, uni-chromosomal circular genomes, where the number of regions remains fixed. Since rearrangements are often mathematically described using permutations, we isolate the sets of permutations representing rearrangements that are biologically reasonable in this context, for example inversions and transpositions. We provide precise mathematical expressions for these rearrangements, and then describe them in terms of the set of cuts made in the genome when they are applied. We directly compare cuts to breakpoints, and use this concept to count the distinct rearrangement actions which apply a given number of cuts. Finally, we provide some examples of rearrangement models, and include a discussion of some questions that arise when defining plausible models.

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Section: Rearrangement Modelsmentioning

confidence: 99%

“… Transpositions of one or two regions Oliveira et al. ( 2019 ) A similar model to above, but the operation is a transposition rather than an inversion. These are referred to as ‘Super-short transpositions’.…”

Section: Rearrangement Modelsmentioning

confidence: 99%

Rearrangement Events on Circular Genomes

Stevenson,

Terauds,

Sumner

2023

Bull Math Biol

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“…In this section, we consider the categorisation of rearrangements via the positions of cuts they make in the genome, and find expressions for the numbers of distinct rearrangements occurring via two and three cuts. For example, given a position labelling, the permutation (23) (23) represents an instance of an inversion which cuts the genome in two places. That is, between positions 1 and 2 and positions 3 and 4.…”

Section: Cuts and Breakpointsmentioning

confidence: 99%

Rearrangement Events on Circular Genomes

Stevenson¹,

Terauds²,

Sumner³

2022

Preprint

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Early literature on genome rearrangement modelling views the problem of computing evolutionary distances as an inherently combinatorial one. In particular, attention was given to estimating distances using the minimum number of events required to transform one genome into another. In hindsight, this approach is analogous to early methods for inferring phylogenetic trees from DNA sequences such as maximum parsimony-both are motivated by the principle that the true distance minimises evolutionary change, and both are effective if this principle is a true reflection of reality. Recent literature considers genome rearrangement under statistical models, continuing this parallel with DNA-based methods; the goal here is to use model-based methods (for example maximum likelihood techniques) to compute distance estimates that incorporate the large number of rearrangement paths that can transform one genome into another. Crucially, this approach requires one to decide upon a set of feasible rearrangement events and, in this paper, we focus on characterising well-motivated models for signed, uni-chromosomal circular genomes, where the number of regions remains fixed. Since rearrangements are often mathematically described using permutations, we isolate the sets of permutations representing rearrangements that are biologically reasonable in this context, for example inversions and translocations. We provide precise mathematical expressions for these rearrangements, and then describe them in terms of the set of cuts made in the genome when they are applied. We directly compare cuts to breakpoints, and use this concept to count the distinct rearrangement actions which apply a given number of cuts. Finally, we provide some examples of rearrangement models, and include a discussion of some questions that arise when defining plausible models.

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“…The problem with an additional constraint that limits the number of genes affected by each operation, called super short operations, was investigated [ 18 ]. On signed permutations it was proposed a 5-approximation algorithm, while for unsigned permutations it was proposed a 3-approximation algorithm.…”

Section: Introductionmentioning

confidence: 99%

An improved approximation algorithm for the reversal and transposition distance considering gene order and intergenic sizes

Brito

Oliveira

Alexandrino

et al. 2021

Algorithms Mol Biol

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Background In the comparative genomics field, one of the goals is to estimate a sequence of genetic changes capable of transforming a genome into another. Genome rearrangement events are mutations that can alter the genetic content or the arrangement of elements from the genome. Reversal and transposition are two of the most studied genome rearrangement events. A reversal inverts a segment of a genome while a transposition swaps two consecutive segments. Initial studies in the area considered only the order of the genes. Recent works have incorporated other genetic information in the model. In particular, the information regarding the size of intergenic regions, which are structures between each pair of genes and in the extremities of a linear genome. Results and conclusions In this work, we investigate the sorting by intergenic reversals and transpositions problem on genomes sharing the same set of genes, considering the cases where the orientation of genes is known and unknown. Besides, we explored a variant of the problem, which generalizes the transposition event. As a result, we present an approximation algorithm that guarantees an approximation factor of 4 for both cases considering the reversal and transposition (classic definition) events, an improvement from the 4.5-approximation previously known for the scenario where the orientation of the genes is unknown. We also present a 3-approximation algorithm by incorporating the generalized transposition event, and we propose a greedy strategy to improve the performance of the algorithms. We performed practical tests adopting simulated data which indicated that the algorithms, in both cases, tend to perform better when compared with the best-known algorithms for the problem. Lastly, we conducted experiments using real genomes to demonstrate the applicability of the algorithms.

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Super short operations on both gene order and intergenic sizes

Cited by 9 publications

References 17 publications

Rearrangement Events on Circular Genomes

Rearrangement Events on Circular Genomes

Rearrangement Events on Circular Genomes

An improved approximation algorithm for the reversal and transposition distance considering gene order and intergenic sizes

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