Abstract
High-altitude adaptation of Tibetans represents a remarkable case of natural selection during recent human evolution. Previous genome-wide scans found many non-coding variants under selection, suggesting a pressing need to understand the functional role of non-coding regulatory elements (REs). Here, we generate time courses of paired ATAC-seq and RNA-seq data on cultured HUVECs under hypoxic and normoxic conditions. We further develop a variant interpretation methodology (vPECA) to identify active selected REs (ASREs) and associated regulatory network. We discover three causal SNPs of EPAS1, the key adaptive gene for Tibetans. These SNPs decrease the accessibility of ASREs with weakened binding strength of relevant TFs, and cooperatively down-regulate EPAS1 expression. We further construct the downstream network of EPAS1, elucidating its roles in hypoxic response and angiogenesis. Collectively, we provide a systematic approach to interpret phenotype-associated noncoding variants in proper cell types and relevant dynamic conditions, to model their impact on gene regulation.
Highlights
High-altitude adaptation of Tibetans represents a remarkable case of natural selection during recent human evolution
We confirm that response to being in culture for different periods of time are not significant compared to the responses to hypoxia (“Methods”)
We develop a statistical methodology vPECA to fully utilize this dataset by integrating with public genomic data
Summary
High-altitude adaptation of Tibetans represents a remarkable case of natural selection during recent human evolution. Han Chinese lowlanders moving to high altitude develop increased Hb concentration to compensate for hypoxia but usually leads to polycythemia that increases the risk of heart attack, stroke, and fetal loss during pregnancy[4,5,6,7] This blunted response to hypoxia in Tibetans is the result of natural selection acting on genes in oxygen intake, delivery, and utilization. To address the above challenges, here we generate accessibility maps of REs across time series of hypoxia experiments in both Tibetan and Han Chinese and inferred hypoxia regulatory networks by linking these REs to their target genes (TG) and their transcription factor (TF) regulators These maps and circuits allow us to understand how human genetic variants contribute to hypoxia adaptation
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