Dataset Information

Nanopore-based DNA long-read sequencing analysis of the aged human brain.

ABSTRACT: Aging disrupts cellular processes such as DNA repair and epigenetic control, leading to a gradual buildup of genomic alterations that can have detrimental effects in post-mitotic cells. Genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark loci," are difficult to resolve using traditional sequencing approaches. New long-read technologies offer promising avenues for exploration of previously inaccessible regions of the genome. Using nanopore-based long-read whole-genome sequencing of DNA extracted from aged 18 human brains, we identify previously unreported structural variants and methylation patterns within repetitive DNA, focusing on transposable elements ("jumping genes") as crucial sources of variation, particularly in dark loci. Our analyses reveal potential somatic insertion variants and provides DNA methylation frequencies for many retrotransposon families. We further demonstrate the utility of this technology for the study of these challenging genomic regions in brains affected by Alzheimer's disease and identify significant differences in DNA methylation in pathologically normal brains versus those affected by Alzheimer's disease. Highlighting the power of this approach, we discover specific polymorphic retrotransposons with altered DNA methylation patterns. These retrotransposon loci have the potential to contribute to pathology, warranting further investigation in Alzheimer's disease research. Taken together, our study provides the first long-read DNA sequencing-based analysis of retrotransposon sequences, structural variants, and DNA methylation in the aging brain affected with Alzheimer's disease neuropathology.

SUBMITTER: Ramirez P

PROVIDER: S-EPMC10871260 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Publications

Nanopore Long-Read Sequencing Unveils Genomic Disruptions in Alzheimer's Disease.

Ramirez Paulino P Sun Wenyan W Dehkordi Shiva Kazempour SK Zare Habil H Pascarella Giovanni G Carninci Piero P Fongang Bernard B Bieniek Kevin F KF Frost Bess B

bioRxiv : the preprint server for biology 20250303

Studies in laboratory models and postmortem human brain tissue from patients with Alzheimer's disease have revealed disruption of basic cellular processes such as DNA repair and epigenetic control as drivers of neurodegeneration. While genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark regions," are difficult to resolve using traditional sequencing approaches, long-read technologies offer promising new avenues to explore previously inaccessible ...[more]

PMID: 38370753

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Project description:Among molecular-based techniques for fungal identification, Sanger sequencing of the primary universal fungal DNA barcode, the internal transcribed spacer (ITS) region (ITS1, 5.8S, ITS2), is commonly used in clinical routine laboratories due to its simplicity, universality, efficacy, and affordability for fungal species identification. However, Sanger sequencing fails to identify mixed ITS sequences in the case of mixed infections. To overcome this limitation, different high-throughput sequencing technologies have been explored. The nanopore-based technology is now one of the most promising long-read sequencing technologies on the market as it has the potential to sequence the full-length ITS region in a single read. In this study, we established a workflow for species identification using the sequences of the entire ITS region generated by nanopore sequencing of both pure yeast isolates and mocked mixed species reads generated with different scenarios. The species used in this study included Candida albicans (n = 2), Candida tropicalis (n = 1), Nakaseomyces glabratus (formerly Candida glabrata) (n = 1), Trichosporon asahii (n = 2), Pichia kudriavzevii (formerly Candida krusei) (n = 1), and Cryptococcus neoformans (n = 1). Comparing various methods to generate the consensus sequence for fungal species identification, the results from this study indicate that read clustering using a modified version of the NanoCLUST pipeline is more sensitive than Canu or VSEARCH, as it classified species accurately with a lower abundance cluster of reads (3% abundance compared to 10% with VSEARCH). The modified NanoCLUST also reduced the number of classified clusters compared to VSEARCH, making the subsequent BLAST+ analysis faster. Subsampling of the datasets, which reduces the size of the datasets by approximately tenfold, did not significantly affect the identification results in terms of the identified species name, percent identity, query coverage, percentage of reads in the classified cluster, and the number of clusters. The ability of the method to distinguish mixed species within sub-populations of large datasets has the potential to aid computer analysis by reducing the required processing power. The herein presented new sequence analysis pipeline will facilitate better interpretation of fungal sequence data for species identification.

Dataset Information

Nanopore-based DNA long-read sequencing analysis of the aged human brain.

Publications

Nanopore Long-Read Sequencing Unveils Genomic Disruptions in Alzheimer's Disease.

Similar Datasets

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