Low-pass whole genome bisulfite sequencing of neonatal dried blood spots identifies a role for RUNX1 in Down syndrome DNA methylation profiles

Abstract

Neonatal dried blood spots (NDBS) are a widely banked sample source that enable retrospective investigation into early-life molecular events. Here, we performed low-pass whole genome bisulfite sequencing (WGBS) of 86 NDBS DNA to examine early-life Down syndrome (DS) DNA methylation profiles. DS represents an example of genetics shaping epigenetics, as multiple array-based studies have demonstrated that trisomy 21 is characterized by genome-wide alterations to DNA methylation. By assaying over 24 million CpG sites, thousands of genome-wide significant (q < 0.05) DMRs that distinguished DS from typical development (TD) and idiopathic developmental delay (DD) were identified. Machine learning feature selection refined these DMRs to 22 loci. The DS DMRs mapped to genes involved in neurodevelopment, metabolism, and transcriptional regulation. Based on comparisons to previous DS methylation studies and reference epigenomes, the hypermethylated DS DMRs were significantly (q < 0.05) enriched across tissues while the hypomethylated DS DMRs were significantly (q < 0.05) enriched for blood-specific chromatin states. A ~ 28 kb block of hypermethylation was observed on chromosome 21 in the RUNX1 locus, which encodes a hematopoietic transcription factor whose binding motif was the most significantly enriched (q < 0.05) overall and specifically within the hypomethylated DMRs. Finally, we also identified DMRs that distinguished DS NDBS based on the presence or absence of congenital heart disease (CHD). Together, these results not only demonstrate the utility of low-pass WGBS on NDBS samples for epigenome-wide association studies, but also provide new insights into the early-life mechanisms of epigenomic dysregulation resulting from trisomy 21.

DNA Methylation Alterations in Blood Cells of Toddlers with Down Syndrome

“…In addition, an overdosage of transcription factors located on chromosome 21, such as RUNX1 binding to the core element of many enhancers and promoters, may disturb the genome-wide pattern of the chromatin structure and DNA methylation [3,4]. Accordingly, significant genome-wide perturbations in DNA methylation in DS, in comparison to matched controls, have been revealed in various cells and tissues, such as placenta tissue [5], blood cells [6][7][8][9], buccal epithelial cells [10], and neural tissue [4,[11][12][13]. Genomewide DNA methylation alterations have been detected in individuals with DS at different developmental stages throughout the lifespan-specifically, at the prenatal [11,14] and early postnatal stages [7][8][9] and in adulthood [6,10,12].…”

Comethyl: A network-based methylome approach to investigate the multivariate nature of health and disease

“…We explored the use of Comethyl in a previously published WGBS dataset of 74 male newborn cord blood samples, including those that were diagnosed with ASD or classified as typically developing by 36 months of age (TD n = 39, ASD n = 35). WGBS read alignment and quality control was performed using the CpG_Me workflow [14]–[17], which includes the generation of a Bismark CpG report. In Comethyl, individual sample Bismark CpG reports are read into a single BSseq object.…”

“…We explored the use of Comethyl in a previously published WGBS dataset of 74 male newborn cord blood samples, including those that were diagnosed with ASD or classified as typically developing by 36 months of age (TD n = 39, ASD n = 35). WGBS read alignment and quality control was performed using the CpG_Me workflow [14]- [17], which includes the generation of a Bismark CpG report. In Comethyl, individual sample Bismark CpG reports are read into a single Starting with CpG-level data from whole-genome bisulfite sequencing (WGBS), the Comethyl pipeline consists of a suite of functions that allow users to summarize DNA methylation at the region level in a biologically-driven manner, construct a comethylation network, and explore associations of comethylation modules with traits.…”

Genome-Wide DNA Methylation Profiles of Neurodevelopmental Disorder Genes in Mouse Placenta and Fetal Brain Following Prenatal Exposure to Polychlorinated Biphenyls

“…The CpG_Me alignment pipeline (v1.4, https://github.com/ben-laufer/CpG_Me), which is based on Trim Galore (v0.6.5), FastQ Screen (v0.14.0), Bismark (v0.22.3), Picard (v2.18.4), and MultiQC (v1.9), was used to trim adapters and methylation bias, screen for contaminating genomes, align to the reference genome (mm10), remove duplicates, calculate coverage and insert size metrics, extract CpG methylation values, generate genome-wide cytosine reports (CpG count matrices), and examine quality control metrics (Ewels et al 2016; Krueger and Andrews 2011; Langmead and Salzberg 2012; Laufer et al 2020; Martin 2011; Wingett and Andrews 2018). The raw fastq files and processed CpG count matrices (Bismark genome-wide cytosine reports) are available in the NCBI Gene Expression Omnibus (GEO) repository, through accession number: (available upon publication).…”

“…Since PCB exposure and NDDs are known to have substantial sex-specific effects (Keil et al 2019; Sethi et al 2017b), the primary analyses were stratified by sex. DMR calling and most downstream analyses and visualizations were performed via DMRichR (v1.6.1, https://github.com/ben-laufer/DMRichR), which utilizes the dmrseq (v1.6.0) and bsseq (v1.22.0) algorithms (Hansen et al 2012; Korthauer et al 2018; Laufer et al 2020). ComplexHeatmap (v2.2.0) was used to create the heatmaps (Gu et al 2016).…”