RESUMEN
Accurately quantifying the functional consequences of non-coding mosaic variants requires the pairing of DNA sequence with both accessible and closed chromatin architectures along individual DNA molecules-a pairing that cannot be achieved using traditional fragmentation-based chromatin assays. We demonstrate that targeted single-molecule chromatin fiber sequencing (Fiber-seq) achieves this, permitting single-molecule, long-read genomic and epigenomic profiling across targeted >100 kilobase loci with ~10-fold enrichment over untargeted sequencing. Targeted Fiber-seq reveals that pathogenic expansions of the DMPK CTG repeat that underlie Myotonic Dystrophy 1 are characterized by somatic instability and disruption of multiple nearby regulatory elements, both of which are repeat length-dependent. Furthermore, we reveal that therapeutic adenine base editing of the segmentally duplicated γ-globin ( HBG1/HBG2 ) promoters in primary human hematopoietic cells induced towards an erythroblast lineage increases the accessibility of the HBG1 promoter as well as neighboring regulatory elements. Overall, we find that these non-protein coding mosaic variants can have complex impacts on chromatin architectures, including extending beyond the regulatory element harboring the variant.
RESUMEN
Long-read DNA sequencing has recently emerged as a powerful tool for studying both genetic and epigenetic architectures at single-molecule and single-nucleotide resolution. Long-read epigenetic studies encompass both the direct identification of native cytosine methylation as well as the identification of exogenously placed DNA N6-methyladenine (DNA-m6A). However, detecting DNA-m6A modifications using single-molecule sequencing, as well as coprocessing single-molecule genetic and epigenetic architectures, is limited by computational demands and a lack of supporting tools. Here, we introduce fibertools, a state-of-the-art toolkit that features a semisupervised convolutional neural network for fast and accurate identification of m6A-marked bases using PacBio single-molecule long-read sequencing, as well as the coprocessing of long-read genetic and epigenetic data produced using either PacBio or Oxford Nanopore sequencing platforms. We demonstrate accurate DNA-m6A identification (>90% precision and recall) along >20 kilobase long DNA molecules with a ~1,000-fold improvement in speed. In addition, we demonstrate that fibertools can readily integrate genetic and epigenetic data at single-molecule resolution, including the seamless conversion between molecular and reference coordinate systems, allowing for accurate genetic and epigenetic analyses of long-read data within structurally and somatically variable genomic regions.
RESUMEN
Long-read DNA sequencing has recently emerged as a powerful tool for studying both genetic and epigenetic architectures at single-molecule and single-nucleotide resolution. Long-read epigenetic studies encompass both the direct identification of native cytosine methylation as well as the identification of exogenously placed DNA N6-methyladenine (DNA-m6A). However, detecting DNA-m6A modifications using single-molecule sequencing, as well as co-processing single-molecule genetic and epigenetic architectures, is limited by computational demands and a lack of supporting tools. Here, we introduce fibertools, a state-of-the-art toolkit that features a semi-supervised convolutional neural network for fast and accurate identification of m6A-marked bases using PacBio single-molecule long-read sequencing, as well as the co-processing of long-read genetic and epigenetic data produced using either PacBio or Oxford Nanopore sequencing platforms. We demonstrate accurate DNA-m6A identification (>90% precision and recall) along >20 kilobase long DNA molecules with a ~1,000-fold improvement in speed. In addition, we demonstrate that fibertools can readily integrate genetic and epigenetic data at single-molecule resolution, including the seamless conversion between molecular and reference coordinate systems, allowing for accurate genetic and epigenetic analyses of long-read data within structurally and somatically variable genomic regions.
RESUMEN
Low-level DNA N 6-methyldeoxyadenosine (DNA-m6A) has recently been reported across various eukaryotes. Although anti-m6A antibody-based approaches are commonly used to measure DNA-m6A levels, this approach is known to be confounded by DNA secondary structures, RNA contamination, and bacterial contamination. To evaluate for these confounding features, we introduce an approach for systematically validating the selectivity of antibody-based DNA-m6A methods and use a highly selective anti-DNA-m6A antibody to reexamine patterns of DNA-m6A in C. reinhardtii, A. thaliana, and D. melanogaster Our findings raise caution about the use of antibody-based methods for endogenous m6A quantification and mapping in eukaryotes.
