Mathov Yoav, Nissim-Rafinia Malka, Leibson Chen, Galun Nir, Marques-Bonet Tomas, Kandel Arye, Liebergal Meir, Meshorer Eran, Carmel Liran
Department of Genetics, The Alexander Silberman Institute of Life Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel.
Nat Ecol Evol. 2025 Jan;9(1):153-165. doi: 10.1038/s41559-024-02571-w. Epub 2024 Nov 20.
Genome-wide premortem DNA methylation patterns can be computationally reconstructed from high-coverage DNA sequences of ancient samples. Because DNA methylation is more conserved across species than across tissues, and 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 datasets. 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 neuroblastoma breaking point family (NBPF) gene family, which probably 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 palaeontological record, and therefore provides new ways to study the evolutionary impacts of epigenetic changes.
全基因组死前DNA甲基化模式可通过古代样本的高覆盖度DNA序列进行计算重建。由于DNA甲基化在物种间比在组织间更为保守,且古代DNA通常从骨骼和牙齿中提取,此前利用古代DNA甲基化图谱的研究主要集中于骨骼系统的进化变化。在此我们提出,在某些条件下,一个组织中的DNA甲基化模式可能有助于了解同一个体其他组织中的DNA甲基化模式。利用组织特异性DNA甲基化在胚胎发育过程中逐渐形成这一事实,我们确定了允许进行这种跨组织推断的条件,并设计了一种算法来实现这一推断。我们用现存物种的甲基化数据对该算法进行训练,验证数据集的精度高达0.92。然后我们将该算法应用于古人类,识别出1850多个位点,在这些位点我们能够观察到前额叶皮质神经元中DNA甲基化的差异。这些位点与数百个基因相关,其中许多基因参与神经功能,如结构和发育过程。六个位点位于神经母细胞瘤断点家族(NBPF)基因家族中,该家族可能在人类大脑进化中发挥了作用。我们在此展示的算法能够检测古生物学记录中缺失的组织和细胞类型中的表观遗传变化,从而为研究表观遗传变化的进化影响提供了新方法。