On the inversion-indel distance

Willing, Eyla; Zaccaria, Simone; Braga, Marília D. V.; Stoye, Jens

doi:10.1186/1471-2105-14-s15-s3

Cited by 17 publications

(14 citation statements)

References 19 publications

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“…The potential of using the DCJ model to revisit the inversion model in a more efficient way was first demonstrated in [8]. More recently, the DCJ-indel model was used to give the first exact algorithm to compute the inversion-indel distance in the absence of bad components [9]. In the present work, we complete the study of the inversion-indel model by giving a quadratic time algorithm to exactly compute the respective distance even in the presence of bad components.…”

Section: Introductionmentioning

confidence: 89%

“…While doing the inversion-sorting of good components with split inversions only, an entire run can be accumulated into a single edge of the relational diagram [7], [9]. The number ΛpCq is then an upper bound for the contribution of cycle C in the final number of indels obtained while doing the inversion-sorting of Rpα, βq with split inversions only.…”

Section: Runs Indel-potential and Inversion-indel Distance Lower Boundmentioning

confidence: 99%

“…Theorem 1 (from [7], [9]): Given two circular chromosomes α and β, such that Rpα, βq has c cycles and no bad component, we have…”

Section: Runs Indel-potential and Inversion-indel Distance Lower Boundmentioning

confidence: 99%

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Computing the Inversion-Indel Distance

Willing

Stoye

Braga

2021

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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The inversion distance, that is the distance between two unichromosomal genomes with the same content allowing only inversions of DNA segments, can be exactly computed thanks to a pioneering approach of Hannenhalli and Pevzner from 1995. In 2000, El-Mabrouk extended the inversion model to perform the comparison of unichromosomal genomes with unequal contents, combining inversions with insertions and deletions (indels) of DNA segments, giving rise to the inversion-indel distance. However, only a heuristic was provided for its computation. In 2005, Yancopoulos, Attie and Friedberg started a new branch of research by introducing the generic double cut and join (DCJ) operation, that can represent several genome rearrangements (including inversions). In 2006, Bergeron, Mixtacki and Stoye showed that the DCJ distance can be computed in linear time with a very simple procedure. As a consequence, in 2010 we gave a linear-time algorithm to compute the DCJ-indel distance. This result allowed the inversion-indel model to be revisited from another angle. In 2013, we could show that, when the diagram that represents the relation between the two compared genomes has no bad components, the inversionindel distance is equal to the DCJ-indel distance. In the present work we complete the study of the inversion-indel distance by giving the first algorithm to compute it exactly even in the presence of bad components.

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Section: Introductionmentioning

confidence: 89%

Section: Runs Indel-potential and Inversion-indel Distance Lower Boundmentioning

confidence: 99%

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Computing the Inversion-Indel Distance

Willing

Stoye

Braga

2021

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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“…While some studies include indels in the rearrangement analysis (Yancopoulos and Friedberg, 2008;Bader, 2009;Braga et al, 2011;Compeau, 2013;Willing et al, 2013), they are mostly of theoretical nature and/or limited to the case of two genomes. We are aware of the following software tools that can reconstruct ancestral genomes for input genomes with unequal gene content.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of Ancestral Genomes in Presence of Gene Gain and Loss

Avdeyev

Jiang

Aganezov

et al. 2016

Journal of Computational Biology

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Since most dramatic genomic changes are caused by genome rearrangements as well as gene duplications and gain/loss events, it becomes crucial to understand their mechanisms and reconstruct ancestral genomes of the given genomes. This problem was shown to be NP-complete even in the "simplest" case of three genomes, thus calling for heuristic rather than exact algorithmic solutions. At the same time, a larger number of input genomes may actually simplify the problem in practice as it was earlier illustrated with MGRA, a state-of-the-art software tool for reconstruction of ancestral genomes of multiple genomes. One of the key obstacles for MGRA and other similar tools is presence of breakpoint reuses when the same breakpoint region is broken by several different genome rearrangements in the course of evolution. Furthermore, such tools are often limited to genomes composed of the same genes with each gene present in a single copy in every genome. This limitation makes these tools inapplicable for many biological datasets and degrades the resolution of ancestral reconstructions in diverse datasets. We address these deficiencies by extending the MGRA algorithm to genomes with unequal gene contents. The developed next-generation tool MGRA2 can handle gene gain/loss events and shares the ability of MGRA to reconstruct ancestral genomes uniquely in the case of limited breakpoint reuse. Furthermore, MGRA2 employs a number of novel heuristics to cope with higher breakpoint reuse and process datasets inaccessible for MGRA. In practical experiments, MGRA2 shows superior performance for simulated and real genomes as compared to other ancestral genome reconstruction tools.

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“…This is apparently due to the strong role of the abstraction of one consensus string to represent genomes. This abstraction is sufficient in most comparative genomics scenarios when the aim is to measure large-scale mutation events for inter-species comparison, resulting into measures such as the inversion distance [1], the inversion-indel distance [2], and DCJ-indel distance [3,4], to name a few.…”

Section: Introductionmentioning

confidence: 99%

Recombination-aware alignment of diploid individuals

Mäkinen

Valenzuela

2014

BMC Genomics

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BackgroundTraditionally biological similarity search has been studied under the abstraction of a single string to represent each genome. The more realistic representation of diploid genomes, with two strings defining the genome, has so far been largely omitted in this context. With the development of sequencing techniques and better phasing routines through haplotype assembly algorithms, we are not far from the situation when individual diploid genomes could be represented in their full complexity with a pair-wise alignment defining the genome.ResultsWe propose a generalization of global alignment that is designed to measure similarity between phased predictions of individual diploid genomes. This generalization takes into account that individual diploid genomes evolve through a mutation and recombination process, and that predictions may be erroneous in both dimensions. Even though our model is generic, we focus on the case where one wants to measure only the similarity of genome content allowing free recombination. This results into efficient algorithms for direct application in (i) evaluation of variation calling predictions and (ii) progressive multiple alignments based on labeled directed acyclic graphs (DAGs) to represent profiles. The latter may be of more general interest, in connection to covering alignment of DAGs. Extensions of our model and algorithms can be foreseen to have applications in evaluating phasing algorithms, as well as more fundamental role in phasing child genome based on parent genomes.

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On the inversion-indel distance

Cited by 17 publications

References 19 publications

Computing the Inversion-Indel Distance

Computing the Inversion-Indel Distance

Reconstruction of Ancestral Genomes in Presence of Gene Gain and Loss

Recombination-aware alignment of diploid individuals

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