Shotgun bisulfite sequencing of the Arabidopsis genome reveals DNA methylation patterning

Cytosine DNA methylation is important in regulating gene expression and in silencing transposons and other repetitive sequences 1 , 2 . Recent genomic studies in Arabidopsis have revealed that many endogenous genes are methylated either within their promoters or within their transcribed regions, and...

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Veröffentlicht in:Nature (London) 2008-02, Vol.452 (7184), p.215-219
Hauptverfasser: Cokus, Shawn J., Feng, Suhua, Zhang, Xiaoyu, Chen, Zugen, Merriman, Barry, Haudenschild, Christian D., Pradhan, Sriharsa, Nelson, Stanley F., Pellegrini, Matteo, Jacobsen, Steven E.
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Sprache:eng
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Zusammenfassung:Cytosine DNA methylation is important in regulating gene expression and in silencing transposons and other repetitive sequences 1 , 2 . Recent genomic studies in Arabidopsis have revealed that many endogenous genes are methylated either within their promoters or within their transcribed regions, and that gene methylation is highly correlated with transcription levels 3 - 5 . However, plants have different types of methylation controlled by different genetic pathways, and detailed information on the methylation status of each cytosine in any given genome is lacking. To this end, we generated a map at single base pair resolution of methylated cytosines for Arabidopsis, by combining bisulfite treatment of genomic DNA with ultra-high-throughput sequencing using the Illumina 1G Genome Analyzer and Solexa sequencing technology 6 . This approach, termed BS-Seq, unlike previous microarray-based methods, allows one to sensitively measure cytosine methylation on a genome-wide scale within specific sequence contexts. We describe methylation on previously inaccessible components of the genome along with an analysis of the DNA methylation sequence composition and distribution. We also describe the effect of various DNA methylation mutants on genome-wide methylation patterns, and demonstrate that our newly developed library construction and computational methods can be applied to large genomes such as mouse.
ISSN:0028-0836
1476-4687
DOI:10.1038/nature06745