DNA methylation-based sex classifier to predict sex and identify sex chromosome aneuploidy

Wang, Yucheng; Hannon, Eilís; Grant, Olivia A; Gorrie-Stone, T.J.; Mill, Jonathan; Zhai, Xiaojun; McDonald-Maier, Klaus D.; Schalkwyk, Leonard C

doi:10.1186/s12864-021-07675-2

Cited by 19 publications

(21 citation statements)

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“…Secondly, the differing normalisation methods applied to DNAme microarray data. Previous research has shown that the methylation levels of CpG sites on the X chromosome differ largely between males and females [ 29 ] and, thus, normalisation methods which normalise array data indiscriminately with CpG sites on the autosomes introduce large technical biases for autosomal CpGs [ 30 ]. Using normalisation methods, which do not handle the technical bias introduced by sex chromosomes, will therefore lead to many autosomal CpG sites being falsely associated with sex and further, a higher number of autosomal CpGs being incorrectly identified as male-biased CpGs.…”

Section: Discussionmentioning

confidence: 99%

“…Samples of whole blood DNA from participants were obtained following the protocol described in [ 88 ]. Raw signal intensities were processed using the R package bigmelon [ 29 ] and watermelon [ 89 ] from idat files. Prior to normalisation of the data, outlier samples were identified using principal component analysis and subsequently removed from the data set.…”

Section: Methodsmentioning

confidence: 99%

“…However, due to X chromosome inactivation in females, large differences in methylation levels of X chromosomes can be observed between males and females [ 29 ]. Recent research suggests that normalising methylation data with the sex chromosomes introduces a large technical bias to many autosomal CpGs [ 30 ].…”

Section: Introductionmentioning

confidence: 99%

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Characterising sex differences of autosomal DNA methylation in whole blood using the Illumina EPIC array

et al. 2022

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Background Sex differences are known to play a role in disease aetiology, progression and outcome. Previous studies have revealed autosomal epigenetic differences between males and females in some tissues, including differences in DNA methylation patterns. Here, we report for the first time an analysis of autosomal sex differences in DNAme using the Illumina EPIC array in human whole blood by performing a discovery (n = 1171) and validation (n = 2471) analysis. Results We identified and validated 396 sex-associated differentially methylated CpG sites (saDMPs) with the majority found to be female-biased CpGs (74%). These saDMP’s are enriched in CpG islands and CpG shores and located preferentially at 5’UTRs, 3’UTRs and enhancers. Additionally, we identified 266 significant sex-associated differentially methylated regions overlapping genes, which have previously been shown to exhibit epigenetic sex differences, and novel genes. Transcription factor binding site enrichment revealed enrichment of transcription factors related to critical developmental processes and sex determination such as SRY and ESR1. Conclusion Our study reports a reliable catalogue of sex-associated CpG sites and elucidates several characteristics of these sites using large-scale discovery and validation data sets. This resource will benefit future studies aiming to investigate sex specific epigenetic signatures and further our understanding of the role of DNA methylation in sex differences in human whole blood.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Characterising sex differences of autosomal DNA methylation in whole blood using the Illumina EPIC array

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“…Age class designations were confirmed based on morphological features (Pruitt, 1954; Rudd, 1955). Shrews were sexed by gel electrophoresis of PCR amplicons of the Y chromosome-linked SRY gene (Cervantes et al, 2013; Matsubara et al, 2001) using custom primers (Table S1); sex assignments were subsequently validated with the methylation assay (Wang et al, 2021).…”

Section: Methodsmentioning

confidence: 99%

Epigenetics and island-mainland divergence in an insectivorous small mammal

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Stewart

Haghani

et al. 2022

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Geographically isolated populations, including island-mainland populations, tend to exhibit phenotypic variation in many species. The so-called island syndrome occurs when different environmental pressures lead to insular divergence from mainland populations. This phenomenon can be seen in an island population of Nova Scotia masked shrews (Sorex cinereus), which have developed a specialized feeding habit and digestive enzyme compared to their mainland counterparts. Epigenetic modifications, such as DNA methylation (DNAm), can impact phenotypes by altering gene expression without changing the DNA sequence. Here, we used a de novo masked shrew genome assembly and epigenome-wide assay to investigate morphological and DNA methylation patterns between island and mainland populations. Island shrews were morphologically and epigenetically different than their mainland counterparts, exhibiting a smaller body size; remarkably, the gene ontology analyses mirrored these phenotypes including genes for the digestive enzyme phenotypes. Moreover, island shrews appeared to age faster than their mainland counterparts. This study provides an example counter to the prevailing island syndrome morphological patterns, along with novel epigenomic insight into the drivers of island-mainland divergence in mammals.

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“…Then the raw methylation beta values is calculated as: , where M denotes methylated intensities and U denotes unmethylated intensities. For all those samples, we estimated their sex by using the estimateSex function [48] from the wateRmelon package [49], any samples with mismatches between its reported sex and the estimated sex from the DNAm data were excluded for downstream analysis. Also, the beta value density distributions of samples within each dataset were manually checked to remove any samples with abnormal distribution profiles.…”

Section: Methodsmentioning

confidence: 99%

Recalibrating the cerebellum DNA methylation clock: implications for ageing rates comparison

Wang

Grant

Zhai

et al. 2022

Preprint

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BackgroundDNA methylation (DNAm) based age clocks have been studied extensively as a biomarker of human ageing and risk factor for age-related diseases. Despite different tissues having vastly different rates of proliferation, it is still largely unknown whether they age at different rates. It was previously reported that the cerebellum ages slowly, however, this claim was drawn from a single clock using a small sample size and so warrants further investigation.ResultsWe collected the largest cerebellum DNAm dataset (N=752). We found the respective epigenetic ages are all severely underestimated by six representative DNAm age clocks, with the underestimation effects more pronounced in the four clocks whose training datasets do not include brain-related tissues. We identified 613 age-associated CpGs in the cerebellum, which accounts for only 14.5% of the number found in the middle temporal gyrus from the same population (N=404), of which only 201 CpGs are both age-associated in the two tissue types. We built a highly accurate age prediction model for the cerebellum named CerebellumClockspecific (Pearson correlation=0.941, MAD=3.18 years). Furthermore, based on the 201 age-associated CpGs, we built two other clocks CerebellumClockcommon and CortexClockcommon for the cerebellum and non-cerebellar brain cortex tissues separately, they both support that the cerebellum has a relative lower DNAm ageing rate.ConclusionsThe large underestimation for the cerebellum by previous clocks mainly reflects the improper usage of the age clocks. There exist strong and consistent ageing effects on the cerebellar methylome despite the cerebellum having unique age-dependent methylome changes. The DNAm clock based ageing rates comparisons are valid only upon models constructed on a small group of CpGs, therefore, more evidence is required to support the idea that different DNAm ageing rates represent different biological ageing rates.

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DNA methylation-based sex classifier to predict sex and identify sex chromosome aneuploidy

Cited by 19 publications

References 50 publications

Characterising sex differences of autosomal DNA methylation in whole blood using the Illumina EPIC array

Characterising sex differences of autosomal DNA methylation in whole blood using the Illumina EPIC array

Epigenetics and island-mainland divergence in an insectivorous small mammal

Recalibrating the cerebellum DNA methylation clock: implications for ageing rates comparison

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