bioRxivGeneticsPreprint
Mobile elements in human population-specific genome and phenotype divergence
Shohei KojimaiD, Satoshi KoyamaiD, Mirei KaiD, Yuka SaitoiD, Erica H. Parrish, Mikiko EndoiD, Sadaaki TakataiD, Misaki Mizukoshi, Keiko HikinoiD, Atsushi Takeda, Asami F. Gelinas, Steven M. HeatoniD, Rie Koide, Anselmo Jiro KamadaiD, Michiya Noguchi, Michiaki HamadaiD, Yoichiro KamataniiD, Yasuhiro MurakawaiD, Kazuyoshi IshigakiiD, Yukio NakamuraiD, Kaoru ItoiD, Chikashi C. TeraoiD, Yukihide MomozawaiD, Nicholas F. ParrishiD
Abstract
Mobile genetic elements (MEs) are heritable mutagens that contribute to divergence between lineages by recursively generating structural variants. ME variants (MEVs) are difficult to genotype, obscuring their impact on recent genome and trait diversification. We developed a tool that uses short-read sequence data to accurately genotype MEVs, enabling us to study them using statistical genetics methods in global human genomes. We observe population-specific differences in the distribution of Alu insertions that distinguish Japanese from other populations. We integrated MEVs with epigenomic and expression quantitative trait loci (eQTL) maps to determine how they impact traits. This reveals coherent patterns by which specific MEs regulate tissue-specific gene expression, including creating or attenuating enhancers and recruiting post-transcriptional regulators. We pinpoint MEVs as genetic causes of disease risk, including a LINE-1 insertion linked to keloid and other diseases of fibroblast inflammation, by introducing MEVs into the genome-wide association study (GWAS) framework. In addition to nominating previously-hidden MEVs as causes of human diseases, this work highlights MEs as accelerators of human population divergence and begins to decipher the semantics of MEs.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: gene regulatory network inference
- research focus: GWAS / association mapping
- approach: statistical model
- approach: experimental assay
- Citations
- 9
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