Biology subjects

Mooijman, D.

Publications and source records attributed to Mooijman, D..

3 recordsLinked to original sources

bioRxiv2024

10x GENOMICS GENE EXPRESSION FLEX IS A POWERFUL TOOL FOR SINGLE-CELL TRANSCRIPTOMICS OF XENOGRAFT MODELS

The 10x Genomics Gene Expression Flex protocol allows profiling of fixed or frozen material, greatly simplifying the logistics of sample collection, storage and transfer prior to single -cell sequencing. The method makes single-cell transcriptomics possible for existing fresh-frozen or FFPE tissue samples, but also facilitates the logistics of the sampling process, allowing instant preservation of samples. The technology relies on species-specific probes available for human and mouse. Nevertheless, processing of patient-derived (PDX) or cell line (CDX) xenografts, which contain mixed human and mouse cells, is currently not supported by this protocol due to the high degree of homology between the probe sets. Here we show that it is feasible to simultaneously profile populations containing both human and mouse cells by mixing the transcriptome probe sets of both species. Cellranger outputs a count table for each of the species allowing evaluation of the performance of the different probe sets. Cross-reactive probes are greatly outperformed by the specific probe hybridizations leading to a clear difference in the recovery of UMIs and unique genes per cell. Furthermore, we developed a pipeline that removes cross-reactive signal from the data and provides species-specific count tables for further downstream analysis. Hence, the 10x Genomics Gene Expression Flex protocol can be used to process xenograft samples without the need for separation of human and mouse cells by flow sorting and allows analysis of the human and mouse single-cell transcriptome from each sample. We anticipate it will be increasingly used for single-cell sequencing of cancer cell line and patient-derived xenografts, facilitating the preservation of the samples and allowing the interrogation of both the (human) xenograft and the (mouse) tumor microenvironment at single-cell resolution.

genomics↗

bioRxiv2019

Strand-specific single-cell methylomics reveals distinct modes of DNA demethylation dynamics during early mammalian development

DNA methylation (5mC) is central to cellular identity and the global erasure of 5mC from the parental genomes during preimplantation mammalian development is critical to reset the methylome of terminally differentiated gametes to the pluripotent cells in the blastocyst. While active and passive modes of demethylation have both been suggested to play a role in this process, the relative contribution of these two mechanisms to genome-wide 5mC erasure remains unclear. Here, we report a new high-throughput single-cell method (scMspJI-seq) that enables strand-specific quantification of 5mC, thereby allowing us to systematically probe the dynamics of global demethylation. First, when applied to hybrid mouse embryonic stem cells, we identified substantial cell-to-cell strand-specific 5mC heterogeneity, with a small group of cells displaying asymmetric levels of 5mCpG between the two DNA strands of a chromosome suggesting loss of maintenance methylation. Next, using scMspJI-seq in preimplantation mouse embryos, we discovered that methylation maintenance is active till the 16-cell stage followed by passive demethylation in a fraction of cells within the early blastocyst at the 32-cell stage of development. Finally, we found that human preimplantation embryos qualitatively show temporally delayed yet similar demethylation dynamics as mouse preimplantation embryos. Collectively, these results demonstrate that scMspJI-seq is a sensitive and cost-effective method to map the strand-specific genome-wide patterns of 5mC in single cells, thereby enabling quantitative investigation of methylation dynamics in developmental systems.

genomics↗

bioRxiv2019

Simultaneous quantification of protein-DNA contacts and transcriptomes in single cells

The epigenome plays a critical role in regulating gene expression in mammalian cells. However, understanding how cell-to-cell heterogeneity in the epigenome influences gene expression variability remains a major challenge. Here we report a novel method for simultaneous single-cell quantification of protein-DNA contacts with DamID and transcriptomics (scDamID&T). This method enables quantifying the impact of protein-DNA contacts on gene expression from the same cell. By profiling lamina-associated domains (LADs) in human cells, we reveal different dependencies between genome-nuclear lamina (NL) association and gene expression in single cells. In addition, we introduce the E. coli methyltransferase, Dam, as an in vivo marker of chromatin accessibility in single cells and show that scDamID&T can be utilized as a general technology to identify cell types in silico while simultaneously determining the underlying gene-regulatory landscape. With this strategy the effect of chromatin states, transcription factor binding, and genome organization on the acquisition of cell-type specific transcriptional programs can be quantified.

molecular biology↗