Evidence map›Paper›PMID 34362304›Full record

ArticleBMC bioinformatics2021

BREC: an R package/Shiny app for automatically identifying heterochromatin boundaries and estimating local recombination rates along chromosomes.

Yasmine Mansour, Annie Chateau, Anna-Sophie Fiston-Lavier

Abstract read
In one paragraph

Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yasmine MansourGenomics Department, Institute of Evolution Science of Montpellier (ISEM), Montpellier, France. yasmine.mansour@umontpellier.fr.ORCID http://orcid.org/0000-0001-9785-6697
Annie ChateauInformatics Department, Laboratory of Computer Science, Robotics and Microelectronics of Montpellier (LIRMM), Montpellier, France.
Anna-Sophie Fiston-LavierGenomics Department, Institute of Evolution Science of Montpellier (ISEM), Montpellier, France. anna-sophie.fiston-lavier@umontpellier.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeiotic recombination is a vital biological process playing an essential role in genome's structural and functional dynamics. Genomes exhibit highly various recombination profiles along chromosomes associated with several chromatin states. However, eu-heterochromatin boundaries are not available nor easily provided for non-model organisms, especially for newly sequenced ones. Hence, we miss accurate local recombination rates necessary to address evolutionary questions.

resultsHere, we propose an automated computational tool, based on the Marey maps method, allowing to identify heterochromatin boundaries along chromosomes and estimating local recombination rates. Our method, called BREC (heterochromatin Boundaries and RECombination rate estimates) is non-genome-specific, running even on non-model genomes as long as genetic and physical maps are available. BREC is based on pure statistics and is data-driven, implying that good input data quality remains a strong requirement. Therefore, a data pre-processing module (data quality control and cleaning) is provided. Experiments show that BREC handles different markers' density and distribution issues.

conclusionsBREC's heterochromatin boundaries have been validated with cytological equivalents experimentally generated on the fruit fly Drosophila melanogaster genome, for which BREC returns congruent corresponding values. Also, BREC's recombination rates have been compared with previously reported estimates. Based on the promising results, we believe our tool has the potential to help bring data science into the service of genome biology and evolution. We introduce BREC within an R-package and a Shiny web-based user-friendly application yielding a fast, easy-to-use, and broadly accessible resource. The BREC R-package is available at the GitHub repository https://github.com/GenomeStructureOrganization .

Indexed as

HeterochromatinMobile ApplicationsAnimalsChromosome MappingDrosophila melanogasterRecombination, GeneticHeterochromatinCentromere positionData quality controlGraphical user interfaceHeterochromatin regionsNon-genome-specificRecombination rate

Identifiers

PMID34362304
PMCPMC8349096

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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.