Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Single-base resolution DNA methylomes of rice and functional roles of DNA methylation

ABSTRACT: To examine the rice genome methylation landscape and assess its functional significance, we generated the first single-base resolution genome methylation maps for Oryza sativa ssp. japonica, indica and their wild relatives, Oryza rufipogon and Oryza nivara. The methylation level of rice genomes is four times higher than that of Arabidopsis. Methylation in the promoter and gene body regions have similar patterns and effects on gene expression as those in Arabidopsis but different from a previous study on rice chromosomes 4 and 10. Most interestingly, we discovered for the first time that methylation in gene transcriptional termination regions can significantly repress gene expression, and the effect is even stronger than promoter methylation, which opens a new direction in the study of epigenetic regulation of gene expressions. Through integrated analysis of genetic, methylome and expression variation between cultivated and wild rice, we found that the genetic factor reflected by DNA variations may be the major determinant for methylation patterns at the whole-genome level and that methylation variation can only account for limited expression variation of genes between cultivated and wild rice. A single young panicle from each of the cultivated rice subspecies and the two wild rice species was ground in liquid nitrogen to fine powder using mortar and pestle. Total RNAs were isolated using the RNeasy Plant Mini Kit (Qiagen). DGE-tag libraries were constructed using the DGE-Tag Profiling NlaIII Sample Prep Kit (Illumina) according to the manufacturer's instructions. This submission represents the gene expression component of the study.

ORGANISM(S): Oryza rufipogon

SUBMITTER: xin li

PROVIDER: E-GEOD-20871 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Purpose: Development of resistance to tamoxifen is an important clinical issue in the treatment of patients with breast cancer. Tamoxifen resistance may be the result of the acquisition of epigenetic regulation such as DNA methylation within breast cancer cells resulting in changed mRNA expression of genes being pivotal for estrogen dependent growth. Alternatively, tamoxifen resistance may be due to selection of preexisting resistant cells, which may exhibit cancer stem-like characteristics or a combination of the two mechanisms. Methods: To evaluate the contribution of these possible mechanisms to tamoxifen resistance, we applied modified DNA methylation-specific digital karyotyping (MMSDK) and digital gene expression (DGE) in combination with massively parallel sequencing to analyze a well-established tamoxifen resistant cell line model: MCF-7/S0.5 (tamoxifen sensitive parental cell line) and 4 high-dosage tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8). MMSDK uses BssHII as mapping enzyme (DNA methylation sensitive enzyme). Both MMSDK and DGE use NlaIII and MmeI to produce 20-21 bp tag. The indexed single-end sequencing was performed by Illumina HiSeq 2000 in BGI-Shenzhen. A dynamic programming algorithm-FASTX-Toolkit implemented in Perl was used to trim the adaptor sequence. The trimmed tags were subjected to quality filtering, so that only tags with sequencing quality higher than 30 for more than 80% of the nucleotides were used for subsequent analysis. For MMSDK tag mapping, we generated a simulated reference library, i.e., BssHII reference library, by in silico enzyme digestion of the human genome (hg19, UCSC) regardless of the methylation state. This library was used as reference for subsequent mapping of the tags in the MMSDK analysis. In the DGE analysis, refMrna (hg19, UCSC) was used as reference for mapping cDNA tags. Subsequently, the BurrowsM-bM-^@M-^SWheeler Aligner (BWA) procedure for aligning the MMSDK and DGE tags to the simulated BssHII reference library and refMrna reference library, respectively, was applied. Results: MMSDK libraries using BssHII/NlaIII were generated from the parental tamoxifen sensitive subline MCF-7/S0.5 and the 4 TAMR cell lines: TAMR-1, TAMR-4, TAMR-7 and TAMR-8. The 5 indexed MMSDK libraries were sequenced in one lane and 1.38 Gb clean tag data for all 5 cell lines were obtained, with an average sequencing amount of ~270 Mb per library. On average, 59.5 % of the tags with mapping quality M-bM-^IM-% 20 were mapped back to the simulated BssHII/NlaIII reference library. DGE libraries were also generated from MCF-7/S0.5 and the 4 TAMR cell lines. The 5 indexed DGE libraries were sequenced in one lane and obtained 1.71 Gb clean tag data for all 5 cell lines with an average sequencing amount of ~340 Mb per library. On average, 40.8 % with mapping quality M-bM-^IM-% 20 were mapped back to the simulated NlaIII human transcriptome (refMrna reference library). Our present study demonstrates large differences in global gene expression and DNA methylation profiles between parental tamoxifen-sensitive cell line and 4 high-dosage tamoxifen treatment selected resistant sublines. The tamoxifen resistant cell lines exhibited globally higher methylation level than the parental cell line and an inverse relationship between gene expression and DNA methylation in the promoter regions were noticed. High expression of SOX2 and alterations of other SOX gene family members, E2F gene family members and RB-related pocket protein genes as well as highlighted stem cell pathways imply that cancer initiating cells/stem cells are involved in the resistance to tamoxifen. DNA methylation and mRNA expression profiles from tamoxifen sensitive parental cell line MCF-7/S0.5 and 4 high dosage of tamoxifen selected resistant offspring sublines (MCF-7/TAMR-1, MCF-7/TAMR-4, MCF-7/TAMR-7 and MCF-7/TAMR-8) were analyzed by MMSDK and DGE methods, respectively, in combination of massively parallel sequencing, using Illumina HiSeq 2000

Project description:Single-base resolution DNA methylomes have been accomplished for both Arabidopsis and human cells which have high genome methylation levels by Illumina ultra-high-throughput bisulfite sequencing technology (MethylC-Seq). Here by combining MethylC-Seq and biological replicate strategies we generated single-base resolution methylome for the silkworm which has low genome methylation levels like other insects. Our conservative estimation showed that methylcytosines (mCs) accout for about 0.11% of genomic cytosines, exclusively in CG context. The CG methylation is significantly enriched in gene bodies and positively correlated with gene expression levels, suggesting its positive role in gene transcription in silkworms. However, the well-documented functions of methylation on promoters and rDNAs in plants and mammals do not seem to have effects in insects. Methylated genes are enriched in functions involved in cellular metabolism and biosynthesis. Small RNA (smRNA) loci are also significantly enriched in gene bodies, and moreover, the smRNA loci and the predicted target sites of microRNA have high level of CG methylation, indicating functional involvement of smRNAs in the genic methylation This first methylome for silkworms provides a foundation for further studies on the epigenetic gene regulation of silkworms’ or even insects’ gene methylation. Each silk gland of 5th instar larvae of two individuals (called Biological Replicate 1 and 2, respectively) of the silkworm (Bombyx mori) strain Dazao was ground into powder in liquid nitrogen. Half of the powder from each silk gland was used to extract total DNAs using DNeasy Blood & Tissue Kit (Qiagen) and another half was used to extract total RNAs using RNeasy Mini Kit (Qiagen). We sequenced bisulfite-treated total DNA extracted from the silk glands of the two individuals, using Illumina Ultra-High-Throughput Sequencing, generating the Single-Base Resolution Methylomes. To reveal functional consequences of gene body methylation, we generated expression profiles for the two individuals’ silk glands using Digital Gene Expression tag profiling (DGE) technology, which combines classic SAGE (Serial Analysis of Gene Expression) and Illumina ultra-high-throughput sequencing technology.

Dataset Information

Single-base resolution DNA methylomes of rice and functional roles of DNA methylation

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets