Biology subjects

Krjutskov, K.

Publications and source records attributed to Krjutskov, K..

10 recordsLinked to original sources

bioRxiv2025

Timing matters: exon skipping therapy is most effective when initiated early in a mouse model of Duchenne muscular dystrophy

Exon skipping is a leading therapeutic approach for Duchenne muscular dystrophy (DMD), a progressive muscle wasting disorder caused by pathogenic variants in the DMD gene that typically disrupt the translation reading frame. This approach aims to modulate DMD pre-mRNA splicing to re-frame the transcript and generate an internally deleted but partially functional quasi-dystrophin protein. Four exon skipping drugs have received FDA accelerated approval, although their clinical efficacy is very limited. To investigate how treatment timing influences exon skipping outcomes, dystrophin-deficient mdx mice were injected with peptide-phosphorodiamidate morpholino oligonucleotide (PPMO) exon skipping conjugates beginning at either the adult (12-week) or aged (75-week) stages, and tibialis anterior muscles harvested for biochemical and transcriptomic analyses. Mean Dmd exon 23 skipping was 79% in adults and 44% in aged PPMO-treated mdx mice, whereas dystrophin protein restoration was 35% and 8%, respectively. Histopathological improvements were only evident in the adult-treated mice. PPMO-treatment in adult mdx mice induced a broad transcriptomic shift towards a wild-type signature, whereas treatment in aged mice resulted in negligible gene expression changes, indicating that late intervention is ineffective at reversing disease-associated pathologies despite low-level dystrophin restoration. Dystrophin transcript imbalance was corrected only in adult-treated mdx mice. Increased expression of the dystrophin-repressing microRNA miR-31-5p, which was more strongly upregulated in aged mdx muscle, provides a potential mechanistic explanation. In conclusion, PPMO-mediated exon skipping is substantially more effective when initiated in adult rather than aged dystrophic muscle, supporting early therapeutic intervention in DMD-affected individuals.

neuroscience↗

bioRxiv2024

Honey bulk DNA metagenomic analysis to identify honey biological composition and monitor honeybee pathogens

Honeys DNA mixture originates from various organismal groups like plants, arthropods, fungi, bacteria, and viruses. Conventional methods like melissopalynological analysis and targeted honey DNA metabarcoding offer a limited view of honeys biological composition. We conducted a honey bulk DNA metagenomic analysis to characterize the honeys taxonomic composition and identify honey bee-related pathogens and parasites based on 266 Estonian and 103 foreign honey samples. 70.4% of the DNA in Estonian honey was derived from green plant families like Brassicaceae, Rosaceae, Fabaceae, and Pinaceae. Geographical distribution analysis revealed distinct botanical compositions between Estonian mainland and island samples. The bacterial family Lactobacillaceae was prevalent overall, reflecting the honey bee microbiota in honey. We detected 12 honey bee pathogens and parasites, including Paenibacillus larvae and Nosema ceranae. In conclusion, the study underscores the potential of bulk DNA-based and non-targeted metagenomic approaches for monitoring honey bee health, environmental quality, and honey composition, origin, and authenticity.

genomics↗

bioRxiv2021

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

MotivationNon-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no comprehensive and direct accuracy comparison of these tools is published. Here, we evaluate and determine the precision of five commonly used computational NIPT aneuploidy analysis tools, considering diverse sequencing depth (coverage) and fetal DNA fraction (FF) on clinically validated NIPT samples. MethodsWe evaluated computational NIPT aneuploidy analysis tools WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq, on the same set of clinically validated samples, subsampled to different sequencing coverages between 1.25-20M reads per sample (RPS). These clinically validated samples consisted of 423 samples, including 19 samples with fetal chromosome 21 trisomy (T21, Down syndrome), eight trisomy 18 (T18, Edwards syndrome) and three trisomy 13 (T13, Patau syndrome) samples. For each software and sequencing coverage, we determined the number of false-negative and false-positive trisomy/euploidy calls. For a uniform trisomy detection interpretation, we defined a framework based on the percent-point function for determining the cut-off threshold for calling aneuploidy based on the sample Z-score and the reference group Z-score distribution. We also determined the effect of the naturally occurring arbitrary read placement driven uncertainty on T21 detection at very low sequencing coverage and the effect of cell-free fetal DNA fraction (FF) on the accuracy of these computational tools in the case of various sequencing coverages. ResultsThis is the first head-to-head comparison of NIPT aneuploidy detection tools for the low-coverage whole-genome sequencing approach. We determined that, with the currently available software tools, the minimum sequencing coverage with no false-negative trisomic cases was 5M RPS. Secondly, for these compared tools, the number of false-negative trisomic cases could be reduced if the trisomy call cut-off threshold considers the Z-score distribution of euploid reference samples. Thirdly, we observed that in the case of low FF, both aneuploidy Z-score and FF inference was considerably less accurate, especially in NIPT assays with 5M RPS or lower coverage. ConclusionsWe determined that all compared computational NIPT tools were affected by lower sequencing depth, resulting in systematically increasing the proportions of false-negative trisomy results as the sequencing depth decreased. Trisomy detection for lower coverage NIPT samples (e.g. 2.5M RPS) is technically possible but can increase the proportion of false-positive and false-negative trisomic cases, especially in the case of low FF.

bioinformatics↗

bioRxiv2020

Profiling of extracellular small RNAs highlights a strong bias towards non-vesicular secretion

Extracellular environment consists of a plethora of different molecules, including extracellular miRNA that can be secreted in association with extracellular vesicles (EVs) or soluble protein complexes (non-EVs). Yet, it is generally accepted that most of the biological activity is attributed to EV-associated miRNAs. The capability of EVs to transport cargoes has attracted much interest towards developing EVs as therapeutic short RNA carriers by using endogenous loading strategies for miRNA enrichment. Here, by overexpressing miRNA and shRNA sequences of interest in source cells and using size exclusion liquid chromatography (SEC) to separate the cellular secretome into EV and non-EV fractions, we saw that strikingly, <2% of all secreted overexpressed miRNA were found in association with EVs. To see whether the prominent non-EV miRNA secretion also holds true at the basal expression level of native miRNA transcripts, both fractions were further analysed by small RNA sequencing. This revealed a global correlation of EV and non-EV miRNA abundance to that of their parent cells and showed an enrichment only for miRNAs with a relatively low cellular expression level. Further quantification showed that similarly to the transient overexpression context, an outstanding 96.2-99.9% of total secreted miRNA at its basal level was secreted to the non-EV fraction. Yet, even though EVs contain only a fraction of secreted miRNAs, these molecules were found stable at 37{degrees}C in serum-containing environment, indicating that if sufficient miRNA loading to EVs is achieved, EVs can remain miRNA delivery-competent for a prolonged period of time. This study suggests that the passive endogenous EV loading strategy can be a relatively wasteful way of loading miRNA to EVs and active miRNA loading approaches are needed for developing advanced EV miRNA therapies in the future.

molecular biology↗

bioRxiv2019

Balancing Selection at HLA-G Modulates Fetal Survival, Preeclampsia and Human Birth Sex Ratio

The population sex ratio is thought to be maintained through balancing selection on rare phenotypes. However, empirical evidence for genetic influence has thus far proven elusive. We combined 1000 Genomes data and large cohorts to study human sex ratios. We found underrepresentation of male offspring in preeclampsia, a serious pregnancy disorder with uncertain pathogenesis. Genetic variation of fetal human leukocyte antigen G (HLA-G), regulating maternal anti-fetal immune responses, was found to be under balancing selection. Sex-linked downregulation of HLA-G and upregulation of interferon alpha-1 (IFNA1) expression contribute to loss of fetal immunotolerance in preeclampsia and suggest hydroxychloroquine as a treatment option. Our findings indicate that an evolutionary trade-off between fetal immunotolerance and protection against infections promotes genetic diversity in HLA-G, thereby maintaining human sex ratios. One Sentence SummaryFetal HLA-G modulates human sex ratio.

evolutionary biology↗

bioRxiv2019

DUX4 regulates oocyte to embryo transition in human

During the human oocyte-to-embryo transition, the fertilized oocyte undergoes final maturation and the embryo genome is gradually activated during the first three cell divisions. How this transition is coordinated in humans is largely unknown. We show that the double homeodomain transcription factor DUX4 contributes to this transition. DUX4 knockdown in human zygotes caused insufficient transcriptome reprogramming as observed three days after fertilization. Induced DUX4 expression in human embryonic stem cells activated transcription of thousands of newly identified bi-directional transcripts, including putative enhancers for embryonic genome activation genes such as LEUTX. DUX4 protein interacted with transcriptional modifiers that are known to couple enhancers and promoters. Taken together, our results reveal that DUX4 is a pioneer regulating oocyte-to-embryo transition in human through activation of intergenic genome, especially enhancers, and hence setting the stage for early human embryo development.

developmental biology↗

bioRxiv2018

Computational framework for targeted high-coverage sequencing based NIPT

Non-invasive prenatal testing (NIPT) enables accurate detection of fetal chromosomal trisomies. The majority of existing computational methods for sequencing-based NIPT analyses rely on low-coverage whole-genome sequencing (WGS) data and are not applicable for targeted high-coverage sequencing data from cell-free DNA samples.\n\nHere, we present a novel computational framework for a targeted high-coverage sequencing based NIPT analysis. The developed methods use a hidden Markov model (HMM)-based approach in conjunction with supplemental machine learning methods, such as decision tree (DT) and support vector machine (SVM), to detect fetal trisomy and parental origin of additional fetal chromosomes. These methods were tested with simulated datasets covering a wide range of biologically relevant scenarios with various chromosomal quantities, parental origins of extra chromosomes, fetal DNA fractions and sequencing read depths. Consequently, we determined the functional feasibility and limitations of each proposed approach and demonstrated that read count-based HMM achieved the best overall classification accuracy of 0.89 for detecting fetal euploidies and trisomies. Furthermore, we show that by using the DT and SVM methods on the HMM state classification results, it was possible to increase the final trisomy classification accuracy to 0.98 and 0.99, respectively.\n\nWe demonstrated that read count and allelic ratio-based models can achieve a high accuracy (up to 0.98) for detecting fetal trisomy even if the fetal fraction is as low as 2%. Currently existing methods require at least 4% fetal fraction, which can be an issue in the case of early gestational age (<10 weeks) or elevated maternal body mass index (>35 kg/m2). More accurate detection can be achieved at higher sequencing depth using HMM in conjunction with supplemental methods, which significantly improve the trisomy detection especially in borderline scenarios (e.g., very low fetal fraction) and can enable to perform NIPT even earlier than 10 weeks of pregnancy.

genomics↗

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↗