Background: X-linked dystonia-parkinsonism (XDP) is an adult-onset neurodegenerative disorder characterized by progressive dystonia and parkinsonism. It is caused by a SINE-VNTR-Alu (SVA) retrotransposon insertion in the TAF1 gene with a polymorphic (CCCTCT)_n domain that acts as a genetic modifier of disease onset and expressivity. Methods: Herein, we used Nanopore sequencing to investigate SVA genetic variability and methylation. We used blood-derived DNA from 96 XDP patients for amplicon-based deep Nanopore sequencing and validated it with fragment analysis which was performed using fluorescence-based PCR. To detect methylation from blood- and brain-derived DNA, we used a Cas9-targeted approach. Results: High concordance was observed for hexanucleotide repeat numbers detected with Nanopore sequencing and fragment analysis. Within the SVA locus, there was no difference in genetic variability other than variations of the repeat motif between patients. We detected high CpG methylation frequency (MF) of the SVA and flanking regions (mean MF = 0.94, SD = ±0.12). Our preliminary results suggest only subtle differences between the XDP patient and the control in predicted enhancer sites directly flanking the SVA locus. Conclusions: Nanopore sequencing can reliably detect SVA hexanucleotide repeat numbers, methylation and, lastly, variation in the repeat motif.

Purpose: Subclinical alterations of the vaginal microbiome have been described to be associated with female infertility and may serve as predictors for failure of in vitro fertilization treatment. While large prospective studies to delineate the role of microbial composition are warranted, integrating microbiome information into clinical management depends on economical and practical feasibility, specifically on a short duration from sampling to final results. The currently most used method for microbiota analysis is either metagenomics sequencing or amplicon-based microbiota analysis using second-generation methods such as sequencing-by-synthesis approaches (Illumina), which is both expensive and time-consuming. Thus, additional approaches are warranted to accelerate the usability of the microbiome as a marker in clinical praxis. Methods: Herein, we used a set of ten selected vaginal swabs from women undergoing assisted reproduction, comparing and performing critical optimization of nanopore-based microbiota analysis with the results from MiSeq-based data as a quality reference. Results: The analyzed samples carried varying community compositions, as shown by amplicon-based analysis of the V3V4 region of the bacterial 16S rRNA gene by MiSeq sequencing. Using a stepwise procedure to optimize adaptation, we show that a close approximation of the microbial composition can be achieved within a reduced time frame and at a minimum of costs using nanopore sequencing. Conclusions: Our work highlights the potential of a nanopore-based methodical setup to support the feasibility of interventional studies and contribute to the development of microbiome-based clinical decision-making in assisted reproduction.