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METHimpute: imputation-guided construction of complete methylomes from WGBS data.
Taudt, Aaron; Roquis, David; Vidalis, Amaryllis; Wardenaar, René; Johannes, Frank; Colomé-Tatché, Maria.
Afiliação
  • Taudt A; European Research Institute for the Biology of Ageing, University of Groningen, University Medical Centre Groningen, A. Deusinglaan 1, Groningen, NL-9713 AV, The Netherlands.
  • Roquis D; Institute of Computational Biology, Helmholtz Zentrum München, Ingolstädter Landstr. 1, Neuherberg, 85764, Germany.
  • Vidalis A; Department of Plant Sciences, Hans Eisenmann-Zentrum for Agricultural Sciences, Technical University Munich, Liesel-Beckmann-Str. 2, Freising, 85354, Germany.
  • Wardenaar R; Department of Plant Sciences, Hans Eisenmann-Zentrum for Agricultural Sciences, Technical University Munich, Liesel-Beckmann-Str. 2, Freising, 85354, Germany.
  • Johannes F; Department of Plant Sciences, Hans Eisenmann-Zentrum for Agricultural Sciences, Technical University Munich, Liesel-Beckmann-Str. 2, Freising, 85354, Germany.
  • Colomé-Tatché M; Department of Plant Sciences, Hans Eisenmann-Zentrum for Agricultural Sciences, Technical University Munich, Liesel-Beckmann-Str. 2, Freising, 85354, Germany. frank@johanneslab.org.
BMC Genomics ; 19(1): 444, 2018 06 07.
Article em En | MEDLINE | ID: mdl-29879918
BACKGROUND: Whole-genome bisulfite sequencing (WGBS) has become the standard method for interrogating plant methylomes at base resolution. However, deep WGBS measurements remain cost prohibitive for large, complex genomes and for population-level studies. As a result, most published plant methylomes are sequenced far below saturation, with a large proportion of cytosines having either missing data or insufficient coverage. RESULTS: Here we present METHimpute, a Hidden Markov Model (HMM) based imputation algorithm for the analysis of WGBS data. Unlike existing methods, METHimpute enables the construction of complete methylomes by inferring the methylation status and level of all cytosines in the genome regardless of coverage. Application of METHimpute to maize, rice and Arabidopsis shows that the algorithm infers cytosine-resolution methylomes with high accuracy from data as low as 6X, compared to data with 60X, thus making it a cost-effective solution for large-scale studies. CONCLUSIONS: METHimpute provides methylation status calls and levels for all cytosines in the genome regardless of coverage, thus yielding complete methylomes even with low-coverage WGBS datasets. The method has been extensively tested in plants, but should also be applicable to other species. An implementation is available on Bioconductor.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Metilação de DNA / Genômica / Sequenciamento Completo do Genoma Tipo de estudo: Health_economic_evaluation Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Metilação de DNA / Genômica / Sequenciamento Completo do Genoma Tipo de estudo: Health_economic_evaluation Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2018 Tipo de documento: Article País de afiliação: Holanda