ABSTRACT: Reduced representation libraries from DNA pools analysed with next generation semiconductor based-sequencing to identify SNPs in extreme and divergent pigs for back fat thickness.
Project description:Sequencing based approaches have led to new insights about DNA methylation. While many different techniques for genome-scale mapping of DNA methylation have been employed, throughput has been a key limitation for most. To further facilitate the mapping of DNA methylation, we describe a protocol for gel-free multiplexed reduced representation bisulfite sequencing (mRRBS) that reduces the workload dramatically and enables processing of 96 or more samples per week. mRRBS achieves similar CpG coverage as the original RRBS protocol, while the higher throughput and lower cost make it better suited for large-scale DNA methylation mapping studies including cohorts of cancer samples.
Project description:CRISPR–Cas9 screening relies on uniform representation of single-guide RNA (sgRNA) libraries to enable accurate gene discovery. However, technical biases during library preparation can compromise screen performance. Here we show that commonly used “all-in-one” CRISPR vectors expressing both Cas9 and sgRNAs drive unintended Cas9 protein expression in Escherichia coli during plasmid amplification. This bacterial Cas9 expression causes guide-specific toxicity, leading to selective loss of sgRNAs and highly skewed library representation. We demonstrate that this effect occurs across multiple bacterial strains and affects both targeted and genome-wide libraries, including widely used human CRISPR libraries. Mechanistically, toxicity is driven by Cas9 expression rather than plasmid size and is only partially alleviated by catalytically inactive Cas9. Importantly, replacing the EF-1α promoter with a mouse phosphoglycerate kinase promoter suppresses Cas9 expression in bacteria while preserving genome editing efficiency in mammalian cells and restoring sgRNA uniformity. These findings identify a previously unrecognized source of bias in CRISPR library preparation and provide a practical solution to improve screening fidelity.
Project description:Sequencing based approaches have led to new insights about DNA methylation. While many different techniques for genome-scale mapping of DNA methylation have been employed, throughput has been a key limitation for most. To further facilitate the mapping of DNA methylation, we describe a protocol for gel-free multiplexed reduced representation bisulfite sequencing (mRRBS) that reduces the workload dramatically and enables processing of 96 or more samples per week. mRRBS achieves similar CpG coverage as the original RRBS protocol, while the higher throughput and lower cost make it better suited for large-scale DNA methylation mapping studies including cohorts of cancer samples. Libraries of 96 human samples
Project description:CRISPR–Cas9 screening relies on uniform representation of single-guide RNA (sgRNA) libraries to enable accurate gene discovery. However, technical biases during library preparation can compromise screen performance. Here we show that commonly used “all-in-one” CRISPR vectors expressing both Cas9 and sgRNAs drive unintended Cas9 protein expression in Escherichia coli during plasmid amplification. This bacterial Cas9 expression causes guide-specific toxicity, leading to selective loss of sgRNAs and highly skewed library representation. We demonstrate that this effect occurs across multiple bacterial strains and affects both targeted and genome-wide libraries, including widely used human CRISPR libraries. Mechanistically, toxicity is driven by Cas9 expression rather than plasmid size and is only partially alleviated by catalytically inactive Cas9. Importantly, replacing the EF-1α promoter with a mouse phosphoglycerate kinase promoter suppresses Cas9 expression in bacteria while preserving genome editing efficiency in mammalian cells and restoring sgRNA uniformity. These findings identify a previously unrecognized source of bias in CRISPR library preparation and provide a practical solution to improve screening fidelity.
Project description:DNA methylation at cytosine-phospho-guanine (CpG) residues is a vital biological process that regulates cell identity and function. Although widely used, bisulfite-based cytosine conversion procedures for DNA methylation sequencing require high temperature and extreme pH, which leads to DNA degradation, especially among unmethylated cytosines. This disproportionate damage to unmethylated cytosines contributes to inaccuracies in GC content representation. EM-seq, an enzyme-based cytosine conversion method, has been proposed as a less biased alternative to methylation profiling. Compared to bisulfite-based methods, EM-seq boasts greater genome coverage with less GC bias and has the potential to cover more CpGs with the same number of reads (i.e., higher signal-to-noise ratio). Reduced representation approaches enrich samples for CpG-rich genomic regions, thereby enhancing throughput and cost effectiveness. We hypothesized that enzyme-based technology could be adapted for reduced representation methylation sequencing to enable high-resolution DNA methylation profiling on low inputs samples. We leveraged the well-established differences in methylation profile between mouse CD4+ T cell populations to compare reduced representation EM-seq (RREM-seq) performance against our previously published modified reduced representation bisulfite sequencing (mRRBS). While the mRRBS method failed to generate reliable DNA libraries when using <2-ng inputs (equivalent to DNA from around 350 cells), the RREM-seq method successfully generated DNA libraries from 1–25 ng of mouse and human genomic DNA. These libraries fell within the expected size range, and primer contamination was not observed. Low-input (<2-ng) RREM-seq libraries’ final concentration, regulatory genomic element coverage, and methylation status within the lineage-defining Treg cell-specific super-enhancers were comparable to mRRBS libraries with more than 10-fold higher DNA input. RREM-seq libraries also successfully detected the methylation differences between alveolar Tconv and Treg cells in mechanically ventilated patients with severe SARS-CoV-2 pneumonia. Our results suggest that the RREM-seq method can generate reliable libraries for single-nucleotide resolution methylation profiling using low input clinical samples.
