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Sample GSM5220630

Query DataSets for GSM5220630

Status

Public on Jun 01, 2021

Title

rCMT3 methylC-seq bent cotyledon (Line #1; biorep #2)

Sample type

SRA

Source name

Bent cotyledon embryos (8 days after pollination)

Organism

Arabidopsis thaliana

Characteristics

accession: rCMT3 (cmt3-11)
genotype: miR823 non-cleavable version of CMT3 transgene in cmt3 mutant background (line #1)
tissue: Bent cotyledon embryos

Treatment protocol

Growth protocol

Arabidopsis thaliana accession Columbia-0 (Col-0) were grown in controlled growth chambers at 20-22˚C under a 16-h light/8-h dark cycle with incandescent lights (130 to 150 µmol/m2/s).

Extracted molecule

genomic DNA

Extraction protocol

Samples 1 to 26 : Genomic DNA was extracted with Quick-DNATM Micro prep Kit (Zymo D3020). MethylC-seq libraries were generated as previously described (Papareddy et al. 2020).
Samples 27 to 35: Total RNA was isolated with TRIzol reagent (Thermo Fisher Scientific). Smart-seq2 mRNA libraries were generated from 1 µl of the 7 µl bent cotyledon embryo total RNA as previously described (Picelli 2013; Hoffman 2019).

Library strategy

Bisulfite-Seq

Library source

genomic

Library selection

RANDOM

Instrument model

Illumina HiSeq 2500

Description

Sample 8
Single-end 100 base read methylC-seq data from second biological replicate of bent cotyledon embryos with miR823 non-cleavable version of CMT3 transgene (line #1).
allC_rCMT3_L1_BentCotyledon.tsv

Data processing

MethylC-seq (samples 1 to 26): Adapters and the first six bases corresponding to random hexamers used during the pre-amplification step were trimmed from MethylC-seq reads using Trim Galore. Bisulfite-converted reads were aligned against the TAIR10 genome (Lamesch et al., 2012) using Bismark (bismark --non_directional -q --score-min L,0,-0.4) (Krueger and Andrews, 2011). Methylpy software was used to extract weighted methylation rate at each available cytosine from BAM files containing only deduplicated and uniquely mapped reads (Schultz et al., 2015).
mRNA-seq (samples 27 to 35): Raw FASTQ files were quality filtered and trimmed for adapter sequences with Trim Galore using default parameters. Trimmed reads were aligned using STAR (Dobin et al., 2013) against a genome index generated using the TAIR10 genome fasta file and all transcripts in the GTF of Ensembl build TAIR10 annotation set (release version 44). Aligned transcriptome bam files were used to quantify read counts per gene and transcript abundance using RSEM (Li and Dewey, 2011).
Genome_build: TAIR10
Supplementary_files_format_and_content: MethylC-seq (samples 1-26): TSV files for methylC-seq processed data files (allC_GENOTYPE_TISSUE.tsv.gz) were output from MethylPy (Schultz et al., 2015) and have following seven columns: 1) chromosome, 2) coordinate position, 3) strand, 4) trinucleotide context, 5) number of reads supporting methylation, 6) number of total reads, 7) whether (1) or not (0) binomial test was performed.
Supplementary_files_format_and_content: mRNA-seq (samples 27-35): TSV files for mRNA-seq processed data files (GENOTYPE_TISSUE_BIOREP.genes.results) were output from RSEM (Li and Dewey, 2011) and have following seven columns: 1) gene_id, 2) transcript(s), 3) transcript length, 4) effective_length, 5) expected_count, 6) TPM, 7) FPKM.

Submission date

Mar 30, 2021

Last update date

Jun 01, 2021

Contact name

Michael D Nodine

E-mail(s)

michael.nodine@wur.nl

Organization name

Wageningen University & Research

Department

Plant Sciences