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Inferring DNA methylation in non-skeletal tissues of ancient specimens

ABSTRACT: Genome-wide premortem DNA methylation patterns can be computationally reconstructed from high-coverage DNA sequences of ancient samples. As DNA methylation is more conserved across species than across tissues, and as ancient DNA is typically extracted from bones and teeth, previous works utilizing ancient DNA methylation maps focused on studying evolutionary changes in the skeletal system. Here, we suggest that DNA methylation patterns in one tissue may, under certain conditions, be informative on DNA methylation patterns in other tissues of the same individual. Using the fact that tissue- specific DNA methylation builds up during embryonic development, we identified the conditions that allow for such cross-tissue inference and devised an algorithm that carries it out. We trained the algorithm on methylation data from extant species and reached high precisions of up to 0.92 for validation data sets. We then used the algorithm on archaic humans, and identified more than 1,850 positions for which we were able to observe differential DNA methylation in prefrontal cortex neurons. These positions are linked to hundreds of genes, many of which are involved in neural functions such as structural and developmental processes. Six positions are located in the NBPF gene family, which likely played a role in human brain evolution. The algorithm we present here allows for the examination of epigenetic changes in tissues and cell types that are absent from the paleontological record, and therefore provides new ways to study the evolutionary impacts of epigenetic changes.

ORGANISM(S): Homo sapiens

PROVIDER: GSE276666 | GEO | 2025/01/22

REPOSITORIES: GEO

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Project description:<p>Aberrant DNA methylation changes are known to occur during prostate cancer progression beginning with precursor lesions. Utilizing fifty nanograms of genomic DNA in Methylplex-Next Generation Sequencing (M-NGS) we mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2). Peaks were located from mapped reads obtained in each sequencing run using a Hidden Markov Model (HMM)-based algorithm previously used for Chip-Seq data analysis(<a href="http://www.sph.umich.edu/csg/qin/HPeak">http://www.sph.umich.edu/csg/qin/HPeak</a>). The total methylation events in intergenic/intronic regions between benign adjacent and cancer tissues were comparable. Promoter CGI methylation gradually increased from -12.6% in benign samples to 19.3% and 21.8% in localized and metastatic cancer tissues and approximately 20% of all CpG islands (CGIs) (68,508) were methylated in tissues. We observed distinct patterns in promoter methylation around transcription start sites, where methylation occurred directly on the CGIs, flanking regions and on CGI sparse promoters. Among the 6,691 methylated promoters in prostate tissues, 2481 differentially methylated regions (DMRs) are cancer specific and several previously studied targets were among them. A novel cancer specific DMR in WFDC2 promoter showed 77% methylation in cancer (17/22), 100% methylation in transformed prostate cell lines (6/6), none in the benign tissues (0/10) and normal PrEC cells. Integration of LNCaP DNA methylation and H3K4me3 data suggested a role for DNA methylation in alternate transcription start site utilization. While methylated promoters containing CGIs had mutually exclusive H3K4me3 modification, the histone mark was absent in CGI sparse promoters. Finally, we observed difference in methylation of LINE-1 elements between transcription factor ERG positive and negative cancers. The comprehensive methylome map presented here will further our understanding of epigenetic regulation of the prostate cancer genome. Overall Design: We mapped the global DNA methylation patterns in prostate tissues (n=17) and cells (n=2) from fifty nanograms of genomic DNA using Methylplex-Next Generation Sequencing (M-NGS). For replicate analysis in cell lines, a total of 4 runs were completed for PrEC prostate normal cell line, and 5 runs were completed for LNCaP prostate cancer cell line. For tissue samples, 2 benign prostate samples were sequenced twice on Illumina next generation sequencing platform to access overall repeatability of M-NGS.</p>

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Inferring DNA methylation in non-skeletal tissues of ancient specimens

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