Evidence map›Paper›PMID 36293364›Full record

ArticleInternational journal of molecular sciences2022

Methylation in the CHH Context Allows to Predict Recombination in Rice.

Mauricio Peñuela, Jenny Johana Gallo-Franco, Jorge Finke, Camilo Rocha, Anestis Gkanogiannis, Thaura Ghneim-Herrera, Mathias Lorieux

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Mauricio PeñuelaiÓMICAS, Facultad de Ingeniería y Ciencias, Pontificia Universidad Javeriana, Cali 760031, Colombia.ORCID 0000-0003-3417-8950
Jenny Johana Gallo-FrancoiÓMICAS, Facultad de Ingeniería y Ciencias, Pontificia Universidad Javeriana, Cali 760031, Colombia.
Jorge FinkeiÓMICAS, Facultad de Ingeniería y Ciencias, Pontificia Universidad Javeriana, Cali 760031, Colombia.
Camilo RochaiÓMICAS, Facultad de Ingeniería y Ciencias, Pontificia Universidad Javeriana, Cali 760031, Colombia.ORCID 0000-0003-4356-7704
Anestis GkanogiannisThe Alliance of Bioversity International and the International Center for Tropical Agriculture (CIAT), Palmira 763537, Colombia.ORCID 0000-0002-6441-0688
Thaura Ghneim-HerreraDepartamento de Ciencias Biológicas, Universidad ICESI, Cali 760031, Colombia.ORCID 0000-0001-5716-0900
Mathias LorieuxDIADE, University of Montpellier, CIRAD, IRD, 34394 Montpellier, France.
Pontificia Universidad Javeriana · COBioversity International · COCentre de Coopération Internationale en Recherche Agronomique pour le Développement · FRIcesi University · CO

Funding

This work was funded by the OMICAS program: Optimización Multiescala In-silico de Cultivos Agrícolas Sostenibles (Infraestructura y Validación en Arroz y Caña de Azúcar), anchored at the Pontificia Universidad Javeriana in Cali and funded within the Colom FP44842-217-2018
6 · The paper itself

Abstract

DNA methylation is the most studied epigenetic trait. It is considered a key factor in regulating plant development and physiology, and has been associated with the regulation of several genomic features, including transposon silencing, regulation of gene expression, and recombination rates. Nonetheless, understanding the relation between DNA methylation and recombination rates remains a challenge. This work explores the association between recombination rates and DNA methylation for two commercial rice varieties. The results show negative correlations between recombination rates and methylated cytosine counts for all contexts tested at the same time, and for CG and CHG contexts independently. In contrast, a positive correlation between recombination rates and methylated cytosine count is reported in CHH contexts. Similar behavior is observed when considering only methylated cytosines within genes, transposons, and retrotransposons. Moreover, it is shown that the centromere region strongly affects the relationship between recombination rates and methylation. Finally, machine learning regression models are applied to predict recombination using the count of methylated cytosines in the CHH context as the entrance feature. These findings shed light on the understanding of the recombination landscape of rice and represent a reference framework for future studies in rice breeding, genetics, and epigenetics.

Indexed as

OryzaCytosineDNA MethylationGene Expression Regulation, PlantPlant BreedingRecombination, GeneticRetroelementsCytosineRetroelementsbisulfite sequencingDNA methylationepigeneticmachine learningmodeling

Identifiers

PMID36293364
PMCPMC9604423
OpenAlexW4306849723

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.