Similar Datasets
Project description:While Illumina X technology has helped to reduce the cost of whole genome sequencing substantially, its application for bisulphite sequencing is not straightforward. We describe the optimization of a library preparation and sequencing approach that maximizes the yield and quality of sequencing, and how to eliminate a previously unrecognized artefact affecting several percent of bisulphite sequencing reads.
2018-07-12 | GSE103502 | GEO
Project description:While Illumina X technology has helped to reduce the cost of whole genome sequencing substantially, its application for bisulphite sequencing is not straightforward. We describe the optimization of a library preparation and sequencing approach that maximizes the yield and quality of sequencing, and how to eliminate a previously unrecognized artefact affecting several percent of bisulphite sequencing reads.
2018-07-12 | GSE103503 | GEO
Project description:While Illumina X technology has helped to reduce the cost of whole genome sequencing substantially, its application for bisulphite sequencing is not straightforward. We describe the optimization of a library preparation and sequencing approach that maximizes the yield and quality of sequencing, and how to eliminate a previously unrecognized artefact affecting several percent of bisulphite sequencing reads.
2018-07-12 | GSE103498 | GEO
Project description:While Illumina X technology has helped to reduce the cost of whole genome sequencing substantially, its application for bisulphite sequencing is not straightforward. We describe the optimization of a library preparation and sequencing approach that maximizes the yield and quality of sequencing, and how to eliminate a previously unrecognized artefact affecting several percent of bisulphite sequencing reads.
2018-07-12 | GSE103301 | GEO
Project description:Whole genome bisulphite sequencing using the Illumina X system
| PRJNA401433 | ENA
Project description:BACKGROUND:Comprehensive genome-wide DNA methylation profiling is critical to gain insights into epigenetic reprogramming during development and disease processes. Among the different genome-wide DNA methylation technologies, whole genome bisulphite sequencing (WGBS) is considered the gold standard for assaying genome-wide DNA methylation at single base resolution. However, the high sequencing cost to achieve the optimal depth of coverage limits its application in both basic and clinical research. To achieve 15×?coverage of the human methylome, using WGBS, requires approximately three lanes of 100-bp-paired-end Illumina HiSeq 2500 sequencing. It is important, therefore, for advances in sequencing technologies to be developed to enable cost-effective high-coverage sequencing. RESULTS:In this study, we provide an optimised WGBS methodology, from library preparation to sequencing and data processing, to enable 16-20× genome-wide coverage per single lane of HiSeq X Ten, HCS 3.3.76. To process and analyse the data, we developed a WGBS pipeline (METH10X) that is fast and can call SNPs. We performed WGBS on both high-quality intact DNA and degraded DNA from formalin-fixed paraffin-embedded tissue. First, we compared different library preparation methods on the HiSeq 2500 platform to identify the best method for sequencing on the HiSeq X Ten. Second, we optimised the PhiX and genome spike-ins to achieve higher quality and coverage of WGBS data on the HiSeq X Ten. Third, we performed integrated whole genome sequencing (WGS) and WGBS of the same DNA sample in a single lane of HiSeq X Ten to improve data output. Finally, we compared methylation data from the HiSeq 2500 and HiSeq X Ten and found high concordance (Pearson r?>?0.9×). CONCLUSIONS:Together we provide a systematic, efficient and complete approach to perform and analyse WGBS on the HiSeq X Ten. Our protocol allows for large-scale WGBS studies at reasonable processing time and cost on the HiSeq X Ten platform.
| S-EPMC5971424 | biostudies-literature
Project description:Whole genome bisulphite sequencing (WGBS) permits the genome-wide study of single molecule methylation patterns. One of the key goals of mammalian cell-type identity studies, in both normal differentiation and disease, is to locate differential methylation patterns across the genome. We discuss the most desirable characteristics for DML (differentially methylated locus) and DMR (differentially methylated region) detection tools in a genome-wide context and choose a set of statistical methods that fully or partially satisfy these considerations to compare for benchmarking. Our data simulation strategy is both biologically informed-employing distribution parameters derived from large-scale consortium datasets-and thorough. We report DML detection ability with respect to coverage, group methylation difference, sample size, variability and covariate size, both marginally and jointly, and exhaustively with respect to parameter combination. We also benchmark these methods on FDR control and computational time. We use this result to backend and introduce an expanded version of DMRcate: an existing DMR detection tool for microarray data that we have extended to now call DMRs from WGBS data. We compare DMRcate to a set of alternative DMR callers using a similarly realistic simulation strategy. We find DMRcate and RADmeth are the best predictors of DMRs, and conclusively find DMRcate the fastest.
| S-EPMC8565305 | biostudies-literature
Project description:BackgroundComplete chloroplast genome sequences provide a valuable source of molecular markers for studies in molecular ecology and evolution of plants. To obtain complete genome sequences, recent studies have made use of the polymerase chain reaction to amplify overlapping fragments from conserved gene loci. However, this approach is time consuming and can be more difficult to implement where gene organisation differs among plants. An alternative approach is to first isolate chloroplasts and then use the capacity of high-throughput sequencing to obtain complete genome sequences. We report our findings from studies of the latter approach, which used a simple chloroplast isolation procedure, multiply-primed rolling circle amplification of chloroplast DNA, Illumina Genome Analyzer II sequencing, and de novo assembly of paired-end sequence reads.ResultsA modified rapid chloroplast isolation protocol was used to obtain plant DNA that was enriched for chloroplast DNA, but nevertheless contained nuclear and mitochondrial DNA. Multiply-primed rolling circle amplification of this mixed template produced sufficient quantities of chloroplast DNA, even when the amount of starting material was small, and improved the template quality for Illumina Genome Analyzer II (hereafter Illumina GAII) sequencing. We demonstrate, using independent samples of karaka (Corynocarpus laevigatus), that there is high fidelity in the sequence obtained from this template. Although less than 20% of our sequenced reads could be mapped to chloroplast genome, it was relatively easy to assemble complete chloroplast genome sequences from the mixture of nuclear, mitochondrial and chloroplast reads.ConclusionsWe report successful whole genome sequencing of chloroplast DNA from karaka, obtained efficiently and with high fidelity.
| S-EPMC2956718 | biostudies-literature
Project description:MOTIVATION:As the number of studies looking at differences between DNA methylation increases, there is a growing demand to develop and benchmark statistical methods to analyse these data. To date no objective approach for the comparison of these methods has been developed and as such it remains difficult to assess which analysis tool is most appropriate for a given experiment. As a result, there is an unmet need for a DNA methylation data simulator that can accurately reproduce a wide range of experimental setups, and can be routinely used to compare the performance of different statistical models. RESULTS:We have developed WGBSSuite, a flexible stochastic simulation tool that generates single-base resolution DNA methylation data genome-wide. Several simulator parameters can be derived directly from real datasets provided by the user in order to mimic real case scenarios. Thus, it is possible to choose the most appropriate statistical analysis tool for a given simulated design. To show the usefulness of our simulator, we also report a benchmark of commonly used methods for differential methylation analysis. AVAILABILITY AND IMPLEMENTATION:WGBS code and documentation are available under GNU licence at http://www.wgbssuite.org.uk/ CONTACT:: owen.rackham@imperial.ac.uk or l.bottolo@imperial.ac.uk SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
| S-EPMC4495289 | biostudies-literature
Project description:BackgroundDNBSEQ-T7 is a new whole-genome sequencer developed by Complete Genomics and MGI using DNA nanoball and combinatorial probe anchor synthesis technologies to generate short reads at a very large scale-up to 60 human genomes per day. However, it has not been objectively and systematically compared against Illumina short-read sequencers.FindingsBy using the same KOREF sample, the Korean Reference Genome, we have compared 7 sequencing platforms including BGISEQ-500, DNBSEQ-T7, HiSeq2000, HiSeq2500, HiSeq4000, HiSeqX10, and NovaSeq6000. We measured sequencing quality by comparing sequencing statistics (base quality, duplication rate, and random error rate), mapping statistics (mapping rate, depth distribution, and percent GC coverage), and variant statistics (transition/transversion ratio, dbSNP annotation rate, and concordance rate with single-nucleotide polymorphism [SNP] genotyping chip) across the 7 sequencing platforms. We found that MGI platforms showed a higher concordance rate for SNP genotyping than HiSeq2000 and HiSeq4000. The similarity matrix of variant calls confirmed that the 2 MGI platforms have the most similar characteristics to the HiSeq2500 platform.ConclusionsOverall, MGI and Illumina sequencing platforms showed comparable levels of sequencing quality, uniformity of coverage, percent GC coverage, and variant accuracy; thus we conclude that the MGI platforms can be used for a wide range of genomics research fields at a lower cost than the Illumina platforms.
| S-EPMC7953489 | biostudies-literature