Project description:Genome editing was conducted on a t(3;8) K562 model to investigate the effects of deleting different modules or CTCF binding sites within the MYC super-enhancer. To check mutations after targeting with CRISPR-Cas9 we performed amplicon sequencing using the Illumina PCR-based custom amplicon sequencing method using the TruSeq Custom Amplicon index kit (Illumina). The first PCR was performed using Q5 polymerase (NEB), the second nested PCR with KAPA HiFi HotStart Ready mix (Roche). Samples were sequenced paired-end (2x 250bp) on a MiSeq (Illumina).
Project description:Nitrate-reducing iron(II)-oxidizing (NDFO) bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. A second NDFO culture, culture BP, was obtained with a sample taken in 2015 at the same pond and cultured in a similar way. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture BP. Raw sequencing data of 16S rRNA amplicon sequencing (V4 region with Illumina and near full-length with PacBio), shotgun metagenomics, metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA693457. This dataset contains proteomics data for 2 conditions in triplicates. Samples R23, R24, and R25 are grown in autotrophic conditions, samples R26, R27, and R28 in heterotrophic conditions.
Project description:Aim: We aim to compare current (MeDIP-seq), new (Illumina Infinium 450K BeadChip) and future (PacBio) methods for whole genome DNA methylation analysis. As the interest in determination of disease methylation profiles increases, the scope, advantages and limitations of these methods requires assessment. There are key questions to answer and specific challenges to overcome. For example, how much detail/resolution is sufficient to identify regions of differential methylation and regions of biological/medical significance within a sample? How much coverage of the genome is required for accurate methylation analysis? Is it important to confirm which regions of the genome are unmethylated in addition to focusing on those that are methylated? Loss of methylation may be of equal importance within the cell since this may also contribute to disease pathogenesis. A multi-method (affinity enrichment/bisulphite-conversion based/direct sequencing of methyl-cytosine) and technology platform (Illumina HiSeq/PacBio/Illumina Infinium BeadChip) comparison will enable us to determine the strengths and weakness of each method. We propose to compare four methods using two DNA samples from the Coriell Institute for Cell Repository to assess both current and future capabilities for whole genome methylation analysis in parallel: A) MeDIP-seq using Illumina HiSeq B) Illumina Infinium HumanMethylation 450K BeadChip and C) whole genome methylation sequencing using PacBio. Existing single molecule deep bisulphite sequencing data generated previously from these same samples at the WTSI for targeted regions (30-40 genes) on the human X chromosome will be used to assess performance of each method. The methods selected for this study will generate data covering a range of resolutions from a whole genome scan to array (target defined) resolution and up to single base pair, single molecule resolution; the highest level of detail possible with methods currently available.Samples: DNA from sibling pair GM01240 (female) and GM01240 (male).Requirements: Both samples will be analysed using;A.MeDIP-seq using Illumina HiSeq (one HiSeq lane, 75bp paired end, per sample) B.Illumina Infinium HumanMethylation 450K BeadChipWe are expecting a potentially unnecessary high coverage using one HiSeq lane per sample. However, for the MeDIP procedure we do not have a multiplexing procedure in place. Our requirements for PacBio sequencing have been discussed with and will be supported by the Sequencing Technology Development group.
2013-01-22 | E-ERAD-139 | biostudies-arrayexpress
Project description:Comparison of large deletions amplicon sequencing on Illumina and PacBio
Project description:Amplicon-based targeted re-sequencing analysis was performed in the patient-derived gliobastoma cell culture samples. For this purpose, genomic DNA (gDNA) was isolated and DNA libraries were prepared using the TruSeq Custom Amplicon Low Input (Illumina, Inc.) technology. By this, a pool of 375 amplicons was generated for each single sample in order to enrich for the target genes ATRX1, EGFR, IDH1, NF1, PDGFRA, PIK3CG, PIK3R1, PTEN, RB1 and TP53. Sequencing was performed on the Illumina MiSeq® next generation sequencing system (Illumina Inc.) and its 2 x 250 bp paired-end v2 read chemistry. The resulting reads were quality controlled and mapped against the human reference genome (hg19). For all samples, sequence variations of the amplified regions of interest in comparison to the human reference sequence were identified and filtered based on reliability.
Project description:We present MultiEditR, the first algorithm specifically designed to detect and quantify RNA editing from Sanger sequencing (z.umn.edu/multieditr). Although RNA editing is routinely evaluated by measuring the heights of peaks from in Sanger sequencing traces, the accuracy and the precision of this approach has yet to be evaluated against gold-standards next-generation sequencing methods. Through a comprehensive comparison to RNA-seq and amplicon based deep sequencing, we show that MultiEditR is accurate, precise, and reliable for detecting endogenous and programmable RNA editing.
Project description:We used PacBio data to identify more reliable transcripts from hESC, based on which we can estimate gene/transcript abundance better from Illumina data. PacBio long reads and Illumina short reads were generated from the same hESC cell line H1. PacBio reads were error-corrected by Illumina reads to identify transcripts. rSeq is used to estimate gene/transcript abundance of the identified transcriptome.
Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.