Biology subjects

Torkenczy, K. A.

Publications and source records attributed to Torkenczy, K. A..

3 recordsLinked to original sources

bioRxiv2018

The accessible chromatin landscape of the hippocampus at single-cell resolution

Here we present a comprehensive map of the accessible chromatin landscape of the mouse hippocampus at single-cell resolution. Substantial advances of this work include the optimization of single-cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq), a software suite, scitools, for the rapid processing and visualization of single-cell combinatorial indexing datasets, and a valuable resource of hippocampal regulatory networks at single-cell resolution. We utilized sci-ATAC-seq to produce 2,346 high-quality single-cell chromatin accessibility maps with a mean unique read count per cell of 29,201 from both fresh and frozen hippocampi, observing little difference in accessibility patterns between the preparations. Using this dataset, we identified eight distinct major clusters of cells representing both neuronal and non-neuronal cell types and characterized the driving regulatory factors and differentially accessible loci that define each cluster. We then applied a recently described co-accessibility framework, Cicero, which identified 146,818 links between promoters and putative distal regulatory DNA. Identified co-accessibility networks showed cell-type specificity, shedding light on key dynamic loci that reconfigure to specify hippocampal cell lineages. Lastly, we carried out an additional sci-ATAC-seq preparation from cultured hippocampal neurons (899 high-quality cells, 43,532 mean unique reads) that revealed substantial alterations in their epigenetic landscape compared to nuclei from hippocampal tissue. This dataset and accompanying analysis tools provide a new resource that can guide subsequent studies of the hippocampus.

neuroscience↗

bioRxiv2018

Chromosome Removal Via Cellular Fragmentation and Aneuploid Blastomere Exclusion in Primate Embryos

Aneuploidy that arises during meiosis and/or mitosis is a major contributor to early embryo loss. We previously demonstrated that human preimplantation embryos encapsulate mis-segregated chromosomes into micronuclei while undergoing cellular fragmentation and that fragments can contain chromosomal material, but the source of this DNA was unknown. Here, we leveraged the use of a non-human primate model and single-cell DNA-sequencing (scDNA-seq) to examine the chromosomal content of 471 individual samples comprising 254 blastomeres, 42 polar bodies, and 175 cellular fragments from a large number (N=50) of disassembled rhesus cleavage-stage embryos. Our analysis revealed that the frequency of aneuploidy and micronucleation is conserved between humans and macaques and that cellular fragments encapsulate whole and/or partial chromosomes lost from blastomeres. Single-cell/fragment genotyping demonstrated that these chromosome-containing cellular fragments (CCFs) can be either maternal or paternal in origin and display DNA damage via double-stranded breaks. Chromosome breakage and abnormal cytokinesis resulted in reciprocal losses/gains at the terminal ends of chromosome arms, uniparental genome segregation, and mixoploidy between blastomeres. Combining time-lapse imaging with scDNA-seq, we also determined that multipolar divisions at the zygote or 2-cell stage generated chaotic aneuploidy encompassing a complex mixture of maternal and paternal chromosomes. Despite frequent chromosomal mis-segregation at the cleavage-stage, we show that CCFs and non-dividing aneuploid blastomeres exhibiting extensive DNA damage are prevented from incorporation at the blastocyst stage. These findings suggest that embryos respond to chromosomal errors by encapsulation into micronuclei, elimination by cellular fragmentation, and selection against highly aneuploid blastomeres to overcome chromosome instability during preimplantation development.

developmental biology↗

bioRxiv2017

Scalable and efficient single-cell DNA methylation sequencing by combinatorial indexing.

Here we present a novel method: single-cell combinatorial indexing for methylation analysis (sci-MET), which is the first highly scalable assay for whole genome methylation profiling of single cells. We use sci-MET to produce 2,697 total single-cell bisulfite sequencing libraries and achieve read alignment rates of 69 {+/-} 7%, comparable to those of bulk cell methods. As a proof of concept, we applied sci-MET to successfully deconvolve the cellular identity of a mixture of three human cell lines.

genomics↗