Project description:Here, we report an enrichment-based ultra-low input cfDNA methylation profiling method using methyl-CpG binding proteins capture, termed cfMBD-seq. We optimized the conditions of cfMBD capture by adjusting the amount of MethylCap protein along with using methylated filler DNA. Our data showed that cfMBD-seq performs equally to the standard MBD-seq (>1000 ng input) even when using 1 ng DNA as the input. cfMBD-seq demonstrated equivalent sequencing data quality as well as similar methylation profile when compared to cfMeDIP-seq. We showed that cfMBD-seq outperforms cfMeDIP-seq in the enrichment of CpG islands. This new bisulfite-free ultra-low input methylation profiling technology has a great potential in non-invasive and cost-effective cancer detection and classification.
Project description:In this study, the Infinium BeadChip DNA methylome profiling technology was optimized for suboptimal input DNA conditions, including ultra-low input down to single cells. We acquired knowledge on the boundaries and limits of the Infinium DNA methylation BeadChips with suboptimal input DNA. These findings offer comprehensive solutions to expand the application of this technology to cases with limited DNA.
Project description:Ultra low input sequencing of FACS sorted primary murine microglia from CSF-1 or IL-34 deficient forebrain and cerebella, at P8 and 9 weeks
Project description:CD34+ hematopoietic stem progenitor cells (HSPCs) from cryo-preserved blood or bone marrow were FACS sorted in TriZol and RNA was isolated according to the manufacturer’s protocol. SMARTer Ultra Low Input RNA kit for sequencing (Clontech, v4 Cat# 634891) was used to generate cDNA. Sequencing libraries were generated using TruSeq Nano DNA Sample Preparation kits (Illumina, Cat# 20015964), according to the low sample protocol and paired-end sequenced on a HiSeq 2500 or Novaseq 6000 (both Illumina).
Project description:Next Generation Sequencing has proven to be an exceptionally powerful tool in the field of genomics and transcriptomics. With recent development it is nowadays possible to analyze ultra-low input sample material down to single cells. Nevertheless investigating such sample material still limits the analysis to either the genome or transcriptome, hence a combined analysis of both types of nucleic acids from the same sample material is still in demand.We developed a protocol which enables the combined analysis of the genome as well as the transcriptome by Next Generation Sequencing from ultra-low input samples. The protocol was evaluated by sequencing sub-colony structures from human embryonic stem cells containing 150 to 200 cells. The method can be adapted to any available sequencing system (e.g. Illumina, SOLiD, 454, etc.).To our knowledge, this is the first report where sub-colonies of human embryonic stem cells have been analyzed both at the genomic as well as transcriptome level. The method of this proof of concept study may find useful practical applications for cases where only a limited number of cells are available, e.g. for tissues samples from biopsies, circulating tumor cells and cells from early embryonic development. The results we present demonstrate that a combined analysis of genomic DNA and messenger RNA from ultra low input samples is feasible and can readily be applied to other cellular systems with limited material available.
Project description:We applied ultra-low-input native ChIP-seq and profiled genome-wide H3K9me3 distribution in four germ cell types during spermatogenesis.
Project description:High-throughput RNA-sequencing has now become the gold standard method for whole-transcriptome gene expression analysis. It is widely used in a number of applications studying various transcriptomes of cells and tissues. It is also being increasingly considered for a number of clinical applications, including expression profiling for diagnostics or alternative transcripts detection. However, RNA sequencing can be challenging in some situations, for instance due to low input quantities or degraded RNA samples. Several protocols have been proposed to overcome some of these challenges, and many are available as commercial kits. Here we perform a comprehensive testing of three recent commercial technologies for RNA-seq library preparation (Truseq, Smarter and Smarter Ultra-Low) on human reference tissue preparations, for standard (1ug), low (100 and 10 ng) and ultra-low (< 1 ng) input quantities, and for mRNA and total RNA, stranded or unstranded. We analyze the results using read quality and alignments metrics, gene detection and differential gene expression metrics. Overall, we show that the Truseq kit performs well at 100 ng input quantity, while the Smarter kit shows degraded performances for 100 and 10 ng input quantities, and that the Smarter Ultra-Low kit performs quite well for input quantities < 1 ng. All the results are discussed in details, and we provide guidelines for the selection of a RNA-seq library preparation kits by biologists.