Long-read sequencing maps transposable element variation and its regulatory and epigenetic effects in the human brain
Ayuketah, A.; Meredith, M.; Groza, C.; Moller, A.; Daida, K.; Catching, A.; Weller, C.; Kouam, C.; Paulin, L.; Malik, L.; Baker, B.; Hu, F.; Bromberek, S.; Jerez, P. A.; Paquette, K.; Izydorczyk, M.; Gu, B.; Chaisson, M. J. P.; Middlehurst, B.; Bubb, V. J.; Quinn, J. P.; Price, E.; Singleton, A. B.; Jain, M.; Blauwendraat, C.; Nalls, M. A.; Cookson, M. R.; Reed, X.; Sedlazeck, F. J.; Goubert, C.; Billingsley, K. J.
Show abstract
Transposable elements (TEs) are mobile DNA sequences that shape genome architecture and gene regulation, yet their roles in the human brain remain largely unresolved. Short-read sequencing lacks the resolution to accurately map TE insertions, detect associated structural variants, and resolve highly repetitive regions. Here, we leverage long-read whole-genome sequencing to profile germline TE insertions in postmortem brain tissue from two ancestrally diverse cohorts: the North American Brain Expression Consortium (NABEC; European ancestry, n = 205) and the Human Brain Collection Core (HBCC; African and African-admixed ancestry, n = 146). We identified 2,842 and 1,660 high-confidence non-reference insertions in HBCC and NABEC, respectively, spanning Alu, LINE-1, and SVA elements. We then also further characterized complex short tandem repeat and variable number tandem repeat variation within reference SVA and Alu loci. Reference TEs were also found to mediate complex structural variants at loci implicated in brain development and neurodegenerative disease, with several showing ancestry-specific patterns. Integration of bulk RNA-sequencing data identified TE expression quantitative trait loci, including insertions that modulate neuronal gene expression. Single-nucleus RNA sequencing revealed cell-type-specific effects of TE regulation across cortical populations. Long-read methylation profiling further demonstrated age-associated epigenetic regulation of both reference and non-reference Alu elements. As a community resource, we release a catalog of TE insertions, allele frequencies, and ancestry-specific distributions to enable future functional and disease-focused investigations. Together, these findings highlight the widespread regulatory and epigenetic influence of TEs in the human brain and establish long-read sequencing as a powerful approach for uncovering cell-type- and population-specific TE dynamics.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control 95%
- CpG island turnover events predict evolutionary changes in enhancer activity 95%
- Allele-specific DNA methylation is increased in cancers and its dense mapping in normal plus neoplastic cells increases the yield of disease-associated regulatory SNPs 94%
Similar papers in this journal
Similar papers in this journal
- Implication of DNA methylation changes at chromosome 1q21.1 in the brain pathology of Primary Progressive Multiple Sclerosis 95%
- Divergent impacts of C9orf72 repeat expansion on neurons and glia in ALS and FTD 95%
- Transposable elements strongly contribute to cell-specific and species-specific looping diversity in mammalian genomes. 95%
Similar papers in this journal
- Illuminating links between cis-regulators and trans-acting variants in the human prefrontal cortex 93%
- Leveraging genomic diversity for discovery in an EHR-linked biobank: the UCLA ATLAS Community Health Initiative 93%
- Sequence dependencies and mutation rates of localized mutational processes in cancer 93%
Similar papers in this journal
- Population-level variation of enhancer expression identifies novel disease mechanisms in the human brain 94%
- Prioritization of autoimmune disease-associated genetic variants that perturb regulatory element activity in T cells 93%
- SingleBrain: A Meta-Analysis of Single-Nucleus eQTLs Linking Genetic Risk to Brain Disorders 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.