Project description:We benchmark Illumina’s HiseqX10 instrument against Beijing Genomics Institute’s (BGI) DNBSEQ-G400 platform, a considerably cheaper sequencing alternative. For comparisons, the same bulk ATAC-seq libraries generated from pluripotent stem cells (PSCs) and fibroblasts were sequenced on both platforms. Both instruments generate sequencing reads with comparable mapping rates and genomic context. However DNBSEQ-G400 data contained a significantly higher number of small, sub-nucleosomal reads (>30% increase) and a reduced number of bi-nucleosomal reads (>75% decrease), which resulted in narrower peak-bases and improved peak calling, enabling the identification of 4% more differentially accessible regions between PSCs and fibroblasts. Ability to identify master TFs that underpin the PSC state relative to fibroblasts, including aggregate and de novo foot-printing capacity, were highly similar between data generated on both platforms.
Project description:The aim of this project is to use an integrated approach involving label-free strategy, HPLC fractionation and LC-MS/MS to quantify the dynamic changes of the whole proteome of Mouse Cell(MEF and R1 cells).
Project description:We benchmark Illumina’s HiseqX10 instrument against Beijing Genomics Institute’s (BGI) DNBSEQ-G400 platform, a considerably cheaper sequencing alternative. For comparisons, the same bulk ATAC-seq libraries generated from pluripotent stem cells (PSCs) and fibroblasts were sequenced on both platforms. Both instruments generate sequencing reads with comparable mapping rates and genomic context. However DNBSEQ-G400 data contained a significantly higher number of small, sub-nucleosomal reads (>30% increase) and a reduced number of bi-nucleosomal reads (>75% decrease), which resulted in narrower peak-bases and improved peak calling, enabling the identification of 4% more differentially accessible regions between PSCs and fibroblasts. Ability to identify master TFs that underpin the PSC state relative to fibroblasts, including aggregate and de novo foot-printing capacity, were highly similar between data generated on both platforms.