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      Large-scale comparative epigenomics reveals hierarchical regulation of non-CG methylation in Arabidopsis

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          In plants, DNA cytosine methylation plays a central role in diverse cellular functions, from transcriptional regulation to maintenance of genome integrity. Vast numbers of whole-genome bisulphite sequencing (WGBS) datasets have been generated to profile DNA methylation at single-nucleotide resolution, yet computational analyses vary widely among research groups, making it difficult to cross-compare findings. Here we reprocessed hundreds of publicly available Arabidopsis WGBS libraries using a uniform pipeline. We identified high-confidence differentially methylated regions and compared libraries using a hierarchical framework, allowing us to identify relationships between methylation pathways. Furthermore, by using a large number of independent wild-type controls, we effectively filtered out spontaneous methylation changes from those that are biologically meaningful.


          Genome-wide characterization by next-generation sequencing has greatly improved our understanding of the landscape of epigenetic modifications. Since 2008, whole-genome bisulfite sequencing (WGBS) has become the gold standard for DNA methylation analysis, and a tremendous amount of WGBS data has been generated by the research community. However, the systematic comparison of DNA methylation profiles to identify regulatory mechanisms has yet to be fully explored. Here we reprocessed the raw data of over 500 publicly available Arabidopsis WGBS libraries from various mutant backgrounds, tissue types, and stress treatments and also filtered them based on sequencing depth and efficiency of bisulfite conversion. This enabled us to identify high-confidence differentially methylated regions (hcDMRs) by comparing each test library to over 50 high-quality wild-type controls. We developed statistical and quantitative measurements to analyze the overlapping of DMRs and to cluster libraries based on their effect on DNA methylation. In addition to confirming existing relationships, we revealed unanticipated connections between well-known genes. For instance, MET1 and CMT3 were found to be required for the maintenance of asymmetric CHH methylation at nonoverlapping regions of CMT2 targeted heterochromatin. Our comparative methylome approach has established a framework for extracting biological insights via large-scale comparison of methylomes and can also be adopted for other genomics datasets.

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          Most cited references 14

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          Shotgun bisulphite 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. Recent genomic studies in Arabidopsis thaliana 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. 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 bisulphite treatment of genomic DNA with ultra-high-throughput sequencing using the Illumina 1G Genome Analyser and Solexa sequencing technology. 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. Here we describe methylation on previously inaccessible components of the genome and analyse 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 that of mouse.
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            Spontaneous epigenetic variation in the Arabidopsis thaliana methylome.

            Heritable epigenetic polymorphisms, such as differential cytosine methylation, can underlie phenotypic variation. Moreover, wild strains of the plant Arabidopsis thaliana differ in many epialleles, and these can influence the expression of nearby genes. However, to understand their role in evolution, it is imperative to ascertain the emergence rate and stability of epialleles, including those that are not due to structural variation. We have compared genome-wide DNA methylation among 10 A. thaliana lines, derived 30 generations ago from a common ancestor. Epimutations at individual positions were easily detected, and close to 30,000 cytosines in each strain were differentially methylated. In contrast, larger regions of contiguous methylation were much more stable, and the frequency of changes was in the same low range as that of DNA mutations. Like individual positions, the same regions were often affected by differential methylation in independent lines, with evidence for recurrent cycles of forward and reverse mutations. Transposable elements and short interfering RNAs have been causally linked to DNA methylation. In agreement, differentially methylated sites were farther from transposable elements and showed less association with short interfering RNA expression than invariant positions. The biased distribution and frequent reversion of epimutations have important implications for the potential contribution of sequence-independent epialleles to plant evolution.
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              Transgenerational epigenetic instability is a source of novel methylation variants.

              Epigenetic information, which may affect an organism's phenotype, can be stored and stably inherited in the form of cytosine DNA methylation. Changes in DNA methylation can produce meiotically stable epialleles that affect transcription and morphology, but the rates of spontaneous gain or loss of DNA methylation are unknown. We examined spontaneously occurring variation in DNA methylation in Arabidopsis thaliana plants propagated by single-seed descent for 30 generations. We identified 114,287 CG single methylation polymorphisms and 2485 CG differentially methylated regions (DMRs), both of which show patterns of divergence compared with the ancestral state. Thus, transgenerational epigenetic variation in DNA methylation may generate new allelic states that alter transcription, providing a mechanism for phenotypic diversity in the absence of genetic mutation.

                Author and article information

                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                30 January 2018
                16 January 2018
                16 January 2018
                : 115
                : 5
                : E1069-E1074
                aInstitute of Plant and Food Science, Department of Biology, Southern University of Science and Technology , 518055 Shenzhen, China;
                bInstitute for Advanced Studies, Wuhan University , 430072 Wuhan, China;
                cCollege of Life Science, Wuhan University , 430072 Wuhan, China;
                dDepartment of Molecular, Cell and Developmental Biology, University of California, Los Angeles , CA 90095;
                eBasic Forestry and Proteomics Research Center, Fujian Agriculture and Forestry University , 350002 Fuzhou, China;
                fUCLA-FAFU Joint Research Center on Plant Proteomics, University of California , Los Angeles, CA 90095;
                gDepartment of Statistics, University of California, Los Angeles , CA 90095;
                hState Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, Fujian Agriculture and Forestry University , 350002 Fuzhou, China;
                iHoward Hughes Medical Institute , University of California, Los Angeles , CA 90095
                Author notes
                2To whom correspondence may be addressed. Email: haifengwang@ , zhaijx@ , or jacobsen@ .

                Contributed by Steven E. Jacobsen, December 16, 2017 (sent for review September 15, 2017; reviewed by Paoyang Chen and Daniel Schubert)

                Author contributions: C.J.H., J.Z., and S.E.J. designed research; J.Z. and S.E.J. oversaw the study and advised on experimental design and data analysis; Y.Z., C.J.H., Q.L., I.A., Y.L., L.X., L.F., Xu Chen, Xinyuan Chen, L.Z., S.F., H.W., and J.Z. performed research; Y.Z., W.L., Y.X., J.J.L., and J.Z. contributed new reagents/analytic tools; Y.Z., C.J.H., Q.L., W.L., and J.Z. analyzed data; and Y.Z., C.J.H., Q.L., H.W., J.Z., and S.E.J. wrote the paper.

                Reviewers: P.C., Academia Sinica; and D.S., Freie Universität Berlin.

                1Y.Z., C.J.H., and Q.L. contributed equally to this work.

                Copyright © 2018 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                Page count
                Pages: 6
                Funded by: HHS | National Institutes of Health (NIH) 100000002
                Award ID: GM60398
                Funded by: National Natural Science Foundation of China (NSFC) 501100001809
                Award ID: 31700192
                Funded by: European Molecular Biology Organization (EMBO) 100004410
                Award ID: ALTF 1138-2014
                Funded by: National Natural Science Foundation of China (NSFC) 501100001809
                Award ID: 31501031
                Funded by: Thousand Talents Program for Young Scholars
                Award ID: na
                Funded by: Guangdong Introducing Innovative and Entrepreneurial Teams
                Award ID: 2016ZT06S172
                PNAS Plus
                Biological Sciences
                Plant Biology
                PNAS Plus


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