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Mammalian cells stably maintain high levels of DNA methylation despite expressing both positive (DNMT3A/B) and negative (TET1-3) regulators. Here, we analyzed the independent and combined effects of these regulators on the DNA methylation landscape using a panel of knockout human embryonic stem cell (ESC) lines. The greatest impact on global methylation levels was observed in DNMT3-deficient cells, including reproducible focal demethylation at thousands of normally methylated loci. Demethylation depends on TET expression and occurs only when both DNMT3s are absent. Dynamic loci are enriched for hydroxymethylcytosine and overlap with subsets of putative somatic enhancers that are methylated in ESCs and can be activated upon differentiation. We observe similar dynamics in mouse ESCs that were less frequent in epiblast stem cells (EpiSCs) and scarce in somatic tissues, suggesting a conserved pluripotency-linked mechanism. Taken together, our data reveal tightly regulated competition between DNMT3s and TETs at thousands of somatic regulatory sequences within pluripotent cells.

DNA methylation plays a critical role during development, particularly in repressing retrotransposons. The mammalian methylation landscape is dependent on the combined activities of the canonical maintenance enzyme Dnmt1 and the de novo Dnmts, 3a and 3b. Here, we demonstrate that Dnmt1 displays de novo methylation activity in vitro and in vivo with specific retrotransposon targeting. We used whole-genome bisulfite and long-read Nanopore sequencing in genetically engineered methylation-depleted mouse embryonic stem cells to provide an in-depth assessment and quantification of this activity. Utilizing additional knockout lines and molecular characterization, we show that the de novo methylation activity of Dnmt1 depends on Uhrf1, and its genomic recruitment overlaps with regions that enrich for Uhrf1, Trim28 and H3K9 trimethylation. Our data demonstrate that Dnmt1 can catalyze DNA methylation in both a de novo and maintenance context, especially at retrotransposons, where this mechanism may provide additional stability for long-term repression and epigenetic propagation throughout development.

Summary Long-read third-generation nanopore sequencing enables researchers to now address a range of questions that are difficult to tackle with short read approaches. The rapidly expanding user base and continuously increasing throughput have sparked the development of a growing number of specialized analysis tools. However, streamlined processing of nanopore datasets using reproducible and transparent workflows is still lacking. Here we present Nanopype, a nanopore data processing pipeline that integrates a diverse set of established bioinformatics software while maintaining consistent and standardized output formats. Seamless integration into compute cluster environments makes the framework suitable for high-throughput applications. As a result, Nanopype facilitates comparability of nanopore data analysis workflows and thereby should enhance the reproducibility of biological insights. Availability and implementation https://github.com/giesselmann/nanopype, https://nanopype.readthedocs.io. Supplementary information Supplementary data are available at Bioinformatics online.

Expansions of short tandem repeats are genetic variants that have been20 implicated in neuropsychiatric and other disorders but their assessment 21 remains challenging with current molecular methods. Here, we developed a 22 Cas12a-based enrichment strategy for nanopore sequencing that, combined 23 with a new algorithm for raw signal analysis, enables us to efficiently target, 24 sequence and precisely quantify repeat numbers as well as their DNA 25 methylation status. Taking advantage of these single molecule nanopore 26 signals provides therefore unprecedented opportunities to study pathological 27 repeat expansions. 28 The expansion of unstable genomic Short Tandem Repeats (STRs) causes more 29 than 30 Mendelian human disorders 1 . For example, expansion of a GGGGCC-repeat 30 [(G 4 C 2 ) n ] within the C9orf72 gene is the most frequent monogenic cause of 31 Frontotemporal Dementia (FTD) and Amyotrophic Lateral Sclerosis (ALS; 32 c9FTD/ALS; OMIM: # 105550) 2,3 . Similarly, accumulation of a CGG motif in the 33 FMR1 gene underlies the Fragile X Syndrome (FXS; OMIM # 300624), currently the 34 most common identifiable genetic cause of mental retardation and autism 4 . In both 35 prototypical repeat expansion disorders (Suppl. Discussion 1), recent evidence has 36 suggested pronounced inter-and intraindividual repeat variability as well as changes 37 in DNA methylation of the respective genomic regions to modulate disease 38 phenotype 5-8 . 39 To overcome current difficulties in characterizing expanded STRs (Suppl. Discussion 40 2) most notably we focused on three areas: i) optimization of Nanopore sequencing 41 and signal processing to capture STRs ii) development and implementation of a 42 3 target enrichment strategy to increase efficiency and iii) integration of expansion 43 measurements with DNA methylation of the same molecule. 44 45 Figure1 nanoSTRique: Generic repeat detection pipeline on raw nanopore signals. 46 a) Repeat quantification by signal-alignment of flanking prefix and suffix regions and HMM based 47 count on signal of interest. b) BioAnalyzer electropherogram, decoy alignment, RepeatHMM and 48 nanoSTRique counts of synthetic (G 4 C 2 ) n repeats (10k random reads per barcode, +/-10 % intervals 49 around expected repeat length). c) Nanopore sequencing and analysis of BAC clone 239 from a 50 c9ALS/FTD patient compared to cropped corresponding lane from Ref. 15 for illustration purpose. d) 51manual confirmation of detected repeat counts in synthetic repeats (n=16, 50, 49, 49, 47). 52 First, for benchmarking repeat expansion counting methods we constructed, verified 53 and nanopore sequenced plasmids with several synthetic (G 4 C 2 ) n -repeat lengths 9 . 54 We analyzed our results with currently available STR quantification pipelines 10,11 but 55 found those methods to become unreliable for more than 32 (G 4 C 2 ) n -repeats with 56 nanopore reads. To further improve the repeat analysis we developed a signal 57 processing algorithm for a more exact quantification of STR numbers in raw 58 na...