Project description:Epigenome constitutes an important layer that regulates gene expression and dynamics during development and diseases. Extensive efforts have been made to develop epigenome profiling methods using a low number of cells and with high throughput. Chromatin immunoprecipitation (ChIP) is the most important approach for profiling genome-wide epigenetic changes such as histone modifications. In this report, we demonstrate microfluidic ChIPmentation (mu-CM), a microfluidic technology that enables profiling cell samples that individually do not generate enough ChIP DNA for sequencing library preparation. We used a simple microfluidic device to allow 8 samples to be processed simultaneously. The samples were indexed differently using a tagmentation-based approach (ChIPmentation) and then merged for library preparation. Histone modification profile for each individual sample was obtained by demultiplexing the sequencing reads based on the indexes. Our technology allowed profiling 20 cells and is well suited for cell-type-specific studies using low-abundance tissues.
Project description:Library preparation for whole genome bisulphite sequencing (WGBS) is challenging due to side effects of the bisulphite treatment, which leads to extensive DNA damage. Recently, a new generation of methods for bisulphite sequencing library preparation have been devised. They are based on initial bisulphite treatment of the DNA, followed by adaptor tagging of single stranded DNA fragments, and enable WGBS using low quantities of input DNA. In this study, we present a novel approach for quick and cost effective WGBS library preparation that is based on splinted adaptor tagging (SPLAT) of bisulphite-converted single-stranded DNA. Moreover, we validate SPLAT against three commercially available WGBS library preparation techniques, two of which are based on bisulphite treatment prior to adaptor tagging and one is a conventional WGBS method.
Project description:Despite the precipitous decline in the cost of genome sequencing over the last few years, library preparation for RNA-seq is still laborious and expensive for high throughput screening for drug discovery. Limited availability of RNA generated by some experimental workflows poses an additional challenge and typically adds to the cost of RNA library preparation. In a search for low cost, automation-compatible RNA library preparation kits that also maintain strand specificity and are amenable to low input RNA quantities, we systematically tested two recent commercial technologies – Swift and Swift Rapid – using the Illumina TruSeq stranded mRNA, the de facto standard workflow for bulk transcriptomics, as our reference. We used the Universal Human Reference RNA (UHRR) (composed of equal quantities of total RNA from 10 human cancer cell lines) to benchmark differential gene expression in these kits, at input quantities ranging between 10 ng to 500 ng. Read quality and alignment metrics revealed high mapping efficiency and uniform read coverage through genes for all samples across all three kits. Normalized read counts between all treatment groups were in high agreement, with pairwise Pearson correlation coefficients >0.97. Compared to the Illumina TruSeq stranded mRNA kit, both Swift RNA library kits are cost effective and offer shorter workflow times enabled by their patented Adaptase technology. Furthermore, the Swift RNA kit allows for a relatively broader (and lower) input range, producing consistent results across diverse samples. The Swift Rapid RNA method is the fastest and most cost effective NGS workflow that is best suited for higher RNA yields, with the exact same RNA input range as the Illumina TruSeq kit. We also found the Swift RNA kit to produce the fewest number of differentially expressed genes and pathways attributable to input mRNA concentration.
Project description:Analysis of allele-specific expression is strongly affected by the technical noise present in RNA-seq experiments. Previously, we showed that technical replicates can be used for precise estimates of this noise, and we provided a tool for correction of technical noise in allele-specific expression analysis. This approach is very accurate but costly due to the need for two or more replicates of each library. Here, we develop a spike-in approach that is highly accurate at only a small fraction of the cost. We show that a distinct RNA added as a spike-in before library preparation reflects technical noise of the whole library and can be used in large batches of samples. We experimentally demonstrate the effectiveness of this approach using combinations of RNA from species distinguishable by alignment, namely, mouse, human, and C.elegans. Our new approach, controlFreq, enables highly accurate and computationally efficient analysis of allele-specific expression in (and between) arbitrarily large studies at an overall cost increase of ∼ 5%.