bioRxivGenomicsPreprint
Haplotype-Resolved Long-Read Sequencing in Hundreds of Diverse Brains Identifies Structural Variant Impacts on Expression and Allele-Specific Methylation
Melissa MeredithiD, Kensuke DaidaiD, Abraham Moller, Pilar Álvarez JereziD, Shloka NegiiD, Laksh MalikiD, Rylee M. GenneriD, Xinchang ZhengiD, Sophia B GibsoniD, Mira MastorasiD, Breeana BakeriD, Cedric KouamiD, Kimberly PaquetteiD, Paige JarreauiD, Mary B. MakariousiD, Anni Moore, Samantha HongiD, Dan VitaleiD, Syed Shah, Jean MonlongiD, Caroline B. PantazisiD, Mobin AsriiD, Kishwar ShafiniD, Paolo Carnevali, Stefano MarencoiD, , Kimberley J. BillingsleyiD
Abstract
Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants; however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. To resolve cis-regulatory effects, we develop ASM-LR, a method for allele-specific methylation analysis from long-read data, revealing both strong and subtle regulatory effects, including numerous novel methylation QTLs masked in unphased models. Our results highlight the power of haplotype-resolved methylation to uncover regulatory mechanisms and establish a foundational resource for exploring how genetic variation shapes gene expression and epigenetic architecture across diverse ancestries.
- organism: human
- assay: whole-genome sequencing
- assay: DNA methylation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 16
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