Evidence map›Paper›PMID 38321522›Full record

ArticleAlgorithms for molecular biology : AMB2024

Global exact optimisations for chloroplast structural haplotype scaffolding.

Victor Epain, Rumen Andonov

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Article in Algorithms for molecular biology : AMB, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

2 authors.

Victor EpainGenScale, Centre Inria de l'Université de Rennes, IRISA, 263 Avenue Général Leclerc, 35700, Rennes, France.
Rumen AndonovGenScale, Centre Inria de l'Université de Rennes, IRISA, 263 Avenue Général Leclerc, 35700, Rennes, France. rumen.andonov@irisa.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundScaffolding is an intermediate stage of fragment assembly. It consists in orienting and ordering the contigs obtained by the assembly of the sequencing reads. In the general case, the problem has been largely studied with the use of distances data between the contigs. Here we focus on a dedicated scaffolding for the chloroplast genomes. As these genomes are small, circular and with few specific repeats, numerous approaches have been proposed to assemble them. However, their specificities have not been sufficiently exploited.

resultsWe give a new formulation for the scaffolding in the case of chloroplast genomes as a discrete optimisation problem, that we prove the decision version to be [Formula: see text]-Complete. We take advantage of the knowledge of chloroplast genomes and succeed in expressing the relationships between a few specific genomic repeats in mathematical constraints. Our approach is independent of the distances and adopts a genomic regions view, with the priority on scaffolding the repeats first. In this way, we encode the structural haplotype issue in order to retrieve several genome forms that coexist in the same chloroplast cell. To solve exactly the optimisation problem, we develop an integer linear program that we implement in Python3 package khloraascaf. We test it on synthetic data to investigate its performance behaviour and its robustness against several chosen difficulties.

conclusionsWe succeed to model biological knowledge on genomic structures to scaffold chloroplast genomes. Our results suggest that modelling genomic regions is sufficient for scaffolding repeats and is suitable for finding several solutions corresponding to several genome forms.

Indexed as

Genome assemblyInteger linear programmingInverted repeatsNP-complete problem

Identifiers

PMID38321522
PMCPMC11288059

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.