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Whole Genome Profiling to Detect Schizophrenia Methylation Markers

ABSTRACT:

Schizophrenia (SCZ) is a devastating psychiatric disorder. The aim of this study was to detect DNA methylation (5meC) profiles in whole blood associated with SCZ. The sample consisted of schizophrenia cases and controls selected from national population registers in Sweden. We employed MBD protein-based enrichment of the methylated DNA fraction, followed by single end sequencing (50 bp reads) on the SOLiD platform. To improve methylome-wide coverage we used an existing protocol variant, which increases the relative number of fragments from CpG poor regions. To analyze the data, we used an analysis pipeline described elsewhere7, that was designed specifically for MBD-seq and included alignment, quality control (QC) of reads and samples, coverage calculations for the 26,752,702 autosomal CpGs in the reference genome using a non-parametric estimate of the fragment size distribution, an in silico experiment to identify CpGs in loci with alignment problems, a 2-stage adaptive algorithm to combine data from correlated adjacent CpG sites in "blocks", principal component analysis (PCA), association testing, bioinformatics annotation and network analysis. After QC, 1459 subjects with on average 32.4 million high quality reads remained. Association testing was performed on 4.3 million high quality blocks after regressing out possible assay related technical artifacts, sex/age, and unmeasured confounders through the PCA components.

PROVIDER: phs000608 | dbGaP |

SECONDARY ACCESSION(S): PRJNA212799PRJNA212798

REPOSITORIES: dbGaP

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Whole Genome Profiling to Detect Schizophrenia Methylation Markers

Project description:<p>Schizophrenia (SCZ) is a devastating psychiatric disorder. The aim of this study was to detect DNA methylation (5meC) profiles in whole blood associated with SCZ. The sample consisted of schizophrenia cases and controls selected from national population registers in Sweden. We employed MBD protein-based enrichment of the methylated DNA fraction, followed by single end sequencing (50 bp reads) on the SOLiD platform. To improve methylome-wide coverage we used an existing protocol variant, which increases the relative number of fragments from CpG poor regions. To analyze the data, we used an analysis pipeline described elsewhere7, that was designed specifically for MBD-seq and included alignment, quality control (QC) of reads and samples, coverage calculations for the 26,752,702 autosomal CpGs in the reference genome using a non-parametric estimate of the fragment size distribution, an in silico experiment to identify CpGs in loci with alignment problems, a 2-stage adaptive algorithm to combine data from correlated adjacent CpG sites in "blocks", principal component analysis (PCA), association testing, bioinformatics annotation and network analysis. After QC, 1459 subjects with on average 32.4 million high quality reads remained. Association testing was performed on 4.3 million high quality blocks after regressing out possible assay related technical artifacts, sex/age, and unmeasured confounders through the PCA components.</p>

| phs000608.v1.p1 | EGA

Chickpea Transcriptome Atlas - I

Project description:In this study, we aim to present a global view of transcriptome dynamics during flower development in chickpea. We generated around 234 million high-quality reads for eight flower development stages (ranging from 16 to 40 million reads for each stage) and 91 million high-quality reads from three vegetative tissues using Illumina high-throughput sequencing GAII platform. Because of non-availability of reference genome sequence, we mapped the reads to chickpea transcriptome comprised of 34,760 transcripts for estimation of their transcriptional activity in different tissue samples. The transcriptome dynamics was studied by comparison of gene expression during flower development stages with vegetative tissues. We collected different tissue samples used in this study and total RNA isolated was subjected to Illumina sequencing. The sequenced data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were mapped to 34760 chickpea transcripts and reads per kilobase per million (RPKM) was calculated for each gene in all the sample to measure their gene expression. Differential expression analysis was performed using DESeq software. The genes preferentially expression during various stages of flower development as compared to vegetative stages and those with speciifc expression were identified.

2014-01-09 | E-GEOD-42679 | biostudies-arrayexpress

Porteresia transcriptome sequencing

Project description:In this study, we aim to present the complete transcriptome of Asian wild rice, Porteresia. We generated about 375 million high-quality reads for five different conditions (ranging from 65 to 90 million reads for each condition) using Illumina high-throughput sequencing GAII platform. We mapped the reads to Porteresia transcripts for estimation of their transcriptional activity in different tissue samples. The transcriptome dynamics was studied by comparison of gene expression during conditions. We collected different tissue samples after various treatments (control, in water; salt450, in 450 mM sodium chloride solution; salt700, in 700 mM sodium chloride solution; submergence, submerged in water; salt+submergence, submerged in 450 mM sodium chloride solution) and total RNA isolated was subjected to Illumina sequencing. The sequenced data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were mapped to Porteresia transcripts and reads per kilobase per million (RPKM) was calculated for each transcript in all the samples to measure their gene expression. Differential expression analysis was performed using DESeq software. The genes showing differential expression under various stress conditions were identified.

2013-11-05 | E-GEOD-44913 | biostudies-arrayexpress

Global methylation alteration in Dnmt3aKO-Idh2 mutant double mutant HSPCs

Project description:We investigated DNA methylation alterations in Dnmt3aKO-Idh2 mutant HSPCs in comparison with the megarkaryocyte erythroid progenitor (MEP) and Granulocyte Macrophage Progenitor(GMP) of Dnmt3a knockout, Idh2 mutant, WT genotypes. We generated an average of 17.42 million reads per sample (12.17 - 24.53 million) of which an average of 16.39 million could be mapped to the mm9 genome (11.74 - 23.73 million). We achieved an average CpG coverage depth of 27.88-fold (19.52 - 35.89-fold) and average bisulfite conversion efficiency of 99.61% (98.43 - 99.94%).

2017-08-04 | GSE60054 | GEO

Small RNAs in stress-related rice cultivars

Project description:In this study, we sequenced small RNA content from three different rice cultivars employing Illumina technology. More than 15 million reads were generated using Illumina high-throughput sequencing platform. After pre-processing, distinct small RNA sequences were identified for each rice cultivars. We collected seedlings of different rice cultivars and total RNA isolated was subjected to Illumina sequencing. The sequenced data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were pre-processed using modified perl script provided in the miRTools software. After quality control, the identical reads were collapsed into a unique read and read count for each sequence was recorded. All the filtered unique reads from each sample were mapped on the rice genome to find their location.

2015-12-31 | E-GEOD-64651 | biostudies-arrayexpress

Catharanthus Transcriptome and Gene Expression

Project description:In this study, we aim to present a global transcriptome analysis of medicinal plant, Catharanthus roseus. We generated about 343 million high-quality reads from three tissues (leaf, root and flower) using Illumina platform. We performed an optimized de novo assembly of the reads and estimated transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses among tissue samples. We collected different tissue samples from the mature plants. Total RNA isolated from these tissue samples was subjected to Illumina sequencing. The sequence data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were used for de novo assembly optimization. The reads were further mapped to the Catharanthus transcripts via CLC Genomics Workbench and differential gene expression analysis was performed using DESeq software.

2014-07-29 | E-GEOD-57326 | biostudies-arrayexpress

Next Generation Sequencing Facilitates Quantitative Analysis of E. coli K-12 LE392, P. putida KT2440, and RP4 plasmid Transcriptomes under AgNP and silver ion exposure

Project description:The goals of this study are to use Next-generation sequencing (NGS)to detect bacterial mRNA profiles of E. coli K-12 LE392, P. putida KT2440 and IncPα RP4 plasmid in response to 0 and 1 μg/L AgNPs or silver ion for 2 h, in duplicate, using Illumina HiSeq 2500.The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the E. coli reference genome (NC_000913) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.

2020-02-01 | GSE128246 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of E. coli K-12 LE392, P. putida KT2440, and RP4 plasmid Transcriptomes under triclosan exposure

Project description:The goals of this study are to use Next-generation sequencing (NGS)to detect bacterial mRNA profiles of E. coli K-12 LE392, P. putida KT2440 and IncPα RP4 plasmid in response to 0, 0.02, 20 and 2000 μg/L triclosan for 2 h, in duplicate, using Illumina HiSeq 2500.The NGS QC toolkit (version 2.3.3) was used to treat the raw sequence reads to trim the 3’-end residual adaptors and primers, and the ambiguous characters in the reads were removed. Then, the sequence reads consisting of at least 85% bases were progressively trimmed at the 3’-ends until a quality value ≥ 20 were kept. Downstream analyses were performed using the generated clean reads of no shorter than 75 bp. The clean reads of each sample were aligned to the E. coli reference genome (NC_000913) using SeqAlto (version 0.5). Cufflinks (version 2.2.1) was used to calculate the strand-specific coverage for each gene, and to analyze the differential expression in triplicate bacterial cell cultures. The statistical analyses and visualization were conducted using CummeRbund package in R (http://compbio.mit.edu/cummeRbund/). Gene expression was calculated as fragments per kilobase of a gene per million mapped reads (FPKM, a normalized value generated from the frequency of detection and the length of a given gene.

2019-04-01 | GSE112451 | GEO

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2018-12-01 | GSE107048 | GEO

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