bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.12.15.520535

Cross-tissue patterns of DNA hypomethylation reveal genetically distinct histories of cell development

Abstract

Establishment of DNA methylation (DNAme) patterns is essential for balanced multi-lineage cellular differentiation, but exactly how these patterns drive cellular phenotypes is unclear. While >80% of CpG sites are stably methylated, tens of thousands of discrete CpG loci form hypomethylated regions (HMRs). Because they lack DNAme, HMRs are considered transcriptionally permissive, but not all HMRs actively regulate genes. Unlike promoter HMRs, a subset of non-coding HMRs is cell-type specific and enriched for tissue specific gene regulatory functions. Our data further argues not only that HMR establishment is an important step in enforcing cell identity, but also that complex HMR patterns are functionally instructive to gene regulation. To understand the significance of non-coding HMRs, we systematically dissected HMR patterns across diverse human cell types and developmental timepoints, including embryonic, fetal, and adult tissues. Unsupervised clustering of 102,390 distinct HMRs revealed that levels of HMR specificity reflects a developmental hierarchy supported by enrichment of stage-specific transcription factors and gene ontologies. Using a pseudo-time course of development from embryonic stem cells to adult stem and mature hematopoietic cells, we find that most HMRs observed in differentiated cells (~70-75%) are established at early developmental stages and accumulate as development progresses. HMRs that arise during differentiation frequently (~35%) establish near existing HMRs ([≤] 6kb away), leading to the formation of HMR clusters associated with stronger enhancer activity. Using SNP-based partitioned heritability from GWAS summary statistics across diverse traits and clinical lab values, we discovered that genetic contribution to trait heritability is enriched within HMRs. Moreover, the contribution of heritability to cell-relevant traits increases with both increasing developmental specificity and HMR clustering, supporting the role of distinct HMR subsets in regulating normal cell function. Altogether, our findings reveal that HMRs can predict cellular phenotypes by providing genetically distinct historical records of a cells journey through development. AUTHOR SUMMARYStudies aiming to understand the relationship between DNA methylation patterns and phenotypic outcomes have focused largely on individual differentially methylated regions without consideration of combinatorial changes that drive phenotypes. In non-disease contexts, most of the human genome is stably methylated, except for thousands of discrete DNA hypomethylated regions (HMRs) coinciding with gene regulatory elements. Here, we comprehensively characterize HMR relationships both within and between developmentally diverse cell types to understand the functional significance of complex HMR patterns. We show that levels of HMR specificity across cell-types captures time-point specific branchpoints of development. Our analysis further reveals that HMRs form clusters in proximity to cell identity genes and are associated with stronger gene enhancer activity. This is a wide-spread phenomenon and only a very small subset of HMR clusters is explained by overlapping super-enhancer annotations. Partitioned heritability revealed the functional significance of different HMR patterns linked to specific phenotypic outcomes and indicates a quantitative relationship between HMR patterns and complex trait heritability. Altogether, our findings reveal that HMRs can predict cellular phenotypes by providing genetically distinct historical records of a cells journey through development, ultimately providing novel insights into how DNA hypo-methylation mediates genome function.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Scott, T. J., Hansen, T. J., McArthur, E., Hodges, E.. 2022-12-16. Cross-tissue patterns of DNA hypomethylation reveal genetically distinct histories of cell development. https://doi.org/10.1101/2022.12.15.520535

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Sequence and epigenetic characterization of chromosome 21 centromeres in a family with recurrent Trisomy 21

Trisomy 21 (T21) is the most common genetic cause of intellectual disability, yet the molecular mechanisms underlying maternal meiosis I errors--responsible for ~70% of free T21 cases--remain poorly understood. In this preliminary study, we used long-read sequencing and genome assembly to investigate the DNA sequence and epigenetic features of chromosome 21 (chr21) centromeres in a family with recurrent free T21 due to maternal meiosis I errors. The mother, who had two affected and three unaffected children, showed no mosaicism or structural rearrangements. One of her two chr21 centromeres lacked a pronounced centromere dip region (CDR), displaying instead a diffuse hypomethylation pattern (dCDR) with much higher methylated CpG levels (55%) compared to its homologue (36%). This dCDR was transmitted to an unaffected child and the affected proband analyzed, suggesting it was present in one of the maternal chr21 since she was at least 32 years of age. Chr21 dCDRs were not observed in seven young mothers with children with T21 or previously described in the literature in 108 population haplotypes. We hypothesize that dCDRs may weaken kinetochore function, increasing nondisjunction risk, and propose two models linking such epigenetic variation to maternal age-related T21 risk. These findings highlight the value of complete centromere characterization in families with children with T21 and suggest centromere methylation status of chr21 as a potential T21 risk factor for future investigation.

genomics↗

Single-Cell Analytics for Dose Response (SCADR) discriminates PTEN missense variants by lipid and protein phosphatase dysfunction

The proliferation of sequencing efforts has revealed a vast and expanding catalog of single nucleotide gene variants, many associated to, but with unclear roles in disease. Fully charactering variant impacts and linking specific protein dysfunctions to disease are challenging due to the multi-functional nature of many proteins and varying degree of variant effects on these functions. Lagging are sensitive approaches to empirically assess the impact of missense variant-induced single amino acid changes on a wide range of protein functions. To address these issues, we have developed an open-source computational analysis tool called SCADR (Single-Cell Analytics for Dose Response) for simultaneously measuring and comparing impacts of exogenously-expressed variants on multiple signaling pathways using multiplex phospho-antibody spectral flow cytometry in human cell lines. SCADR retains and correlates single-cell measures of signal protein activity states along with expression levels of exogenously-expressed variants, providing rich characterization of multiple protein functions, signaling protein interactions, and enhanced discrimination of variant impacts on different signaling pathways, highlighting each variants unique dysfunction profile. Here, we apply SCADR for analyses of the impact of 6 variants of the tumor-suppressor protein PTEN (P38H, C124S, G129E, Y138L, D268E, 4A) expressed in HEK293 cells on the phosphorylation states of the canonical and noncanonical downstream signaling proteins Akt, S6, CREB, ERK, and p38 detected with fluorophore-conjugated phospho-antibodies, along with an antibody detecting an N-terminal HA tag on PTEN variants allowing measures of dose-response effects of each variants expression on signaling cascades. Results identify variant-specific impacts on downstream signaling cascades.

genomics↗

Microsecond molecular dynamics of SOD1 variants suggest a structural basis for divergent ALS clinical outcomes

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterised by progressive motor neuron degeneration. Mutations in the SOD1 gene represent the second most common genetic cause of ALS (ALS), and distinct SOD1 missense variants present with markedly different clinical profiles. A4V leads to an aggressive form of the disease (median survival [~]1y), H46R confers a mild, slowly progressive course and I113T exhibits an intermediate phenotype. The molecular basis by which these mutations produce divergent clinical outcomes remains poorly understood. We performed extensive classical molecular dynamics simulations of wild-type SOD1 and the three ALS-associated variants in the apo monomeric state to attempt to investigate the mechanisms behind such phenotypic differences. Structural stability, global compactness, and conformational flexibility, as well as analysis of collective motions between residues and estimation of free energy, were assessed. The H46R, A4V, and I113T variants exhibited distinct dynamic behaviours, highlighting differences in structural stability, local flexibility, and intramolecular interactions. These findings suggest that specific structural regions may contribute differently to protein dysfunction and could represent key elements for understanding the relationship between molecular dynamic properties and the differing clinical severity associated with these variants. Most strikingly, H46R exhibited exceptional structural stability across every analytical level, the lowest global deviation, most attenuated local flexibility, strongest internal dynamic coordination, and the deepest, most confined free energy basins of any system examined. This convergent multi-layered evidence of structural restraint provides a compelling mechanistic basis for the mild and slowly progressive clinical course of H46R ALS, suggesting that enhanced conformational rigidity, rather than bulk destabilisation, is the defining biophysical feature of this variant, and that its pathogenic mechanism operates through a route fundamentally decoupled from the aggregation-driven toxicity that characterises the more aggressive SOD1-ALS mutations.

genomics↗