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      Evolutionary and Experimental Loss of Gene Body Methylation and Its Consequence to Gene Expression

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          Abstract

          In flowering plants, gene body methylation (gbM) is associated with a subset of constitutively expressed genes. It has been proposed that gbM modulates gene expression. Here, we show that there are no consistent and direct differences to expression following the loss of gbM. By comparing expression of gbM genes in Arabidopsis thaliana accessions to orthologous genes in two Eutrema salsugineum genotypes, we identified both positive and negative expression differences associated with gbM loss. However, expression is largely unaffected by gbM loss in E. salsugineum. Expression differences between species were within the variation of expression observed within A. thaliana accessions that displayed variation in gbM. Furthermore, experimentally induced loss of gbM did not consistently lead to differences in expression compared to wild type. To date, there is no convincing data to support a direct causal link between the presence/absence of gbM and the modulation of expression in flowering plants.

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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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            Biases in Illumina transcriptome sequencing caused by random hexamer priming

            Generation of cDNA using random hexamer priming induces biases in the nucleotide composition at the beginning of transcriptome sequencing reads from the Illumina Genome Analyzer. The bias is independent of organism and laboratory and impacts the uniformity of the reads along the transcriptome. We provide a read count reweighting scheme, based on the nucleotide frequencies of the reads, that mitigates the impact of the bias.
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              From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline

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                Author and article information

                Journal
                G3 (Bethesda)
                Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                30 May 2019
                August 2019
                : 9
                : 8
                : 2441-2445
                Affiliations
                [* ]Department of Plant Biology,
                []Institute of Bioinformatics, and
                []Department of Genetics, University of Georgia, Athens, GA 30602
                Author notes
                [1 ]Corresponding authors: Department of Genetics, University of Georgia, 120 East Green Street, Davison Life Sciences, B416 Athens, GA 30602. E-mail: schmitz@ 123456uga.edu and bewickaj@ 123456uga.edu
                Author information
                http://orcid.org/0000-0002-4609-7966
                http://orcid.org/0000-0001-8776-6823
                http://orcid.org/0000-0002-0663-3779
                http://orcid.org/0000-0003-2670-8413
                http://orcid.org/0000-0001-7538-6663
                Article
                GGG_400365
                10.1534/g3.119.400365
                6686912
                31147389
                fa03ef53-990c-46b3-9e45-bf50fa4d586b
                Copyright © 2019 Bewick et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 04 March 2019
                : 23 May 2019
                Page count
                Figures: 1, Tables: 0, Equations: 0, References: 27, Pages: 5
                Categories
                Investigations

                Genetics
                dna methylation,gene body methylation,gene expression,epigenetics
                Genetics
                dna methylation, gene body methylation, gene expression, epigenetics

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