Biology subjects

Krjutskov, K.

Publications and source records attributed to Krjutskov, K..

3 recordsLinked to original sources

bioRxiv2018

Maternal Plag1 deficiency delays zygotic genome activation and two-cell stage embryo development

Pleomorphic adenoma gene 1 (PLAG1) is a transcription factor involved in cancer and growth. We discovered a de novo DNA motif containing a PLAG1 binding site in the promoters of genes activated during zygotic genome activation (ZGA) in human embryos. This motif was located within an Alu element in a region that was conserved in the murine B1 element. We show that maternally provided Plag1 is essential for timely mouse preimplantation embryo development. Heterozygous mouse embryos lacking maternal Plag1 showed disrupted regulation of 1,089 genes, spent significantly longer time in the 2-cell stage, and started expressing Plag1 ectopically from the paternal allele. The de novo PLAG1 motif was enriched in the promoters of the genes whose activation was delayed in the absence of Plag1. Further, these mouse genes showed a significant overlap with genes upregulated during human ZGA that also contain the motif. By gene ontology, the mouse and human ZGA genes with de novo PLAG1 motifs were involved in ribosome biogenesis and protein synthesis. Collectively, our data suggest that PLAG1 affects embryo development in mice and humans through a conserved DNA motif within Alu/B1 elements located in the promoters of a subset of ZGA genes.

developmental biology↗

bioRxiv2018

TAC-seq: targeted DNA and RNA sequencing for precise biomarker molecule counting

Targeted next-generation sequencing based biomarker detection methods have become essential for biomedical diagnostics. In addition to their sensitivity and high-throughput capacity, absolute molecule counting based on unique molecular identifier (UMI) has high potential to increase biomarker detection accuracy even further through the reduction of systematic technical biases. Here, we present TAC-seq, a simple and cost-effective targeted allele counting by sequencing method that uses UMIs to estimate the original molecule counts of different biomarker types like mRNAs, microRNAs and cell-free DNA. We applied TAC-seq in three different applications and compared the results with standard sequencing technologies. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX,+21) genomic DNA. TAC-seq mRNA biomarker profiling showed identical clustering results to full transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard sequencing. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant (p=4.8x10-11) excess of molecules in case of trisomy 21. Based on three proof-of-principle applications we show that TAC-seq is a highly accurate and universal method for targeted nucleic acid biomarker profiling.

genomics↗

bioRxiv2017

Human pluripotent reprogramming with CRISPR activators

CRISPR/Cas9 based gene activation (CRISPRa) is an attractive tool for cellular reprogramming applications due to its high multiplexing capacity and direct targeting of endogenous loci. Here we present the reprogramming of primary human skin fibroblasts into induced pluripotent stem cells (iPSC) using CRISPRa, targeting endogenous OCT4, SOX2, KLF4, MYC and LIN28A promoters. The basal reprogramming efficiency can be improved by an order of magnitude by additionally targeting a conserved Alu-motif, enriched near genes involved in embryo genome activation (EEA-motif). This effect is mediated in part by more efficient activation of NANOG and REX1. These data constitute a proof of principle that somatic cells can be reprogrammed into iPSC using only CRISPRa. Furthermore, the results unravel previously uncharacterized involvement of EEA-motif-associated mechanisms in cellular reprogramming.

cell biology↗