DNA methylation profiles unique to Kalahari KhoeSan individuals.
Alexander GoncearencoBrenna A LaBarreHanna M PetrykowskaWeerachai JaratlerdsiriM S Riana BornmanStephen D TurnerVanessa M HayesLaura ElnitskiPublished in: Epigenetics (2020)
Genomes of KhoeSan individuals of the Kalahari Desert provide the greatest understanding of single nucleotide diversity in the human genome. Compared with individuals in industrialized environments, the KhoeSan have a unique foraging and hunting lifestyle. Given these dramatic environmental differences, and the responsiveness of the methylome to environmental exposures of many types, we hypothesized that DNA methylation patterns would differ between KhoeSan and neighbouring agropastoral and/or industrial Bantu. We analysed Illumina HumanMethylation 450 k array data generated from blood samples from 38 KhoeSan and 42 Bantu, and 6 Europeans. After removing CpG positions associated with annotated and novel polymorphisms and controlling for white blood cell composition, sex, age and technical variation we identified 816 differentially methylated CpG loci, out of which 133 had an absolute beta-value difference of at least 0.05. Notably SLC39A4/ZIP4, which plays a role in zinc transport, was one of the most differentially methylated loci. Although the chronological ages of the KhoeSan are not formally recorded, we compared historically estimated ages to methylation-based calculations. This study demonstrates that the epigenetic profile of KhoeSan individuals reveals differences from other populations, and along with extensive genetic diversity, this community brings increased accessibility and understanding to the diversity of the human genome.
Keyphrases
- dna methylation
- genome wide
- genetic diversity
- gene expression
- endothelial cells
- copy number
- induced pluripotent stem cells
- healthcare
- mental health
- type diabetes
- metabolic syndrome
- heavy metals
- cardiovascular disease
- physical activity
- cell therapy
- mesenchymal stem cells
- life cycle
- molecular dynamics simulations
- molecular dynamics
- machine learning
- human health
- big data
- stem cells
- bone marrow
- density functional theory
- genome wide association study
- artificial intelligence
- high throughput sequencing