TY - JOUR
T1 - Inferring DNA methylation in non-skeletal tissues of ancient specimens
AU - Mathov, Yoav
AU - Nissim-Rafinia, Malka
AU - Leibson, Chen
AU - Galun, Nir
AU - Marques-Bonet, Tomas
AU - Kandel, Arye
AU - Liebergal, Meir
AU - Meshorer, Eran
AU - Carmel, Liran
N1 - Publisher Copyright:
© The Author(s) 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85209652121&partnerID=8YFLogxK
U2 - 10.1038/s41559-024-02571-w
DO - 10.1038/s41559-024-02571-w
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C2 - 39567757
AN - SCOPUS:85209652121
SN - 2397-334X
JO - Nature Ecology and Evolution
JF - Nature Ecology and Evolution
ER -