Nature CommunicationsGenomicsPeer-reviewed journal article
The Genetic Architecture of DNA Replication Timing in Human Pluripotent Stem Cells
Qiliang DingiD, Matthew M. EdwardsiD, Ning WangiD, Xiang ZhuiD, Alexa N. BracciiD, Michelle L. HulkeiD, Ya HuiD, Yao TongiD, Joyce Hsiao, Christine J. CharvetiD, Sulagna Dia GhoshiD, Robert E. HandsakeriD, Kevin C. EgganiD, Florian T. MerkleiD, Jeannine GerhardtiD, Dieter M. EgliiD, Andrew G. ClarkiD, Amnon KoreniD
Abstract
DNA replication follows a strict spatiotemporal program that intersects with chromatin structure and gene regulation. However, the genetic basis of the mammalian DNA replication timing program is poorly understood1-3. To systematically identify genetic regulators of DNA replication timing, we exploited inter-individual variation in 457 human pluripotent stem cell lines from 349 individuals. We show that the human genomes replication program is broadly encoded in DNA and identify 1,617 cis-acting replication timing quantitative trait loci (rtQTLs4) - base-pair-resolution sequence determinants of replication initiation. rtQTLs function individually, or in combinations of proximal and distal regulators, to affect replication timing. Analysis of rtQTL locations reveals a histone code for replication initiation, composed of bivalent histone H3 trimethylation marks on a background of histone hyperacetylation. The H3 trimethylation marks are individually repressive yet synergize to promote early replication. We further identify novel positive and negative regulators of DNA replication timing, the former comprised of pluripotency-related transcription factors while the latter involve boundary elements. Human replication timing is controlled by a multi-layered mechanism that operates on target DNA sequences, is composed of dozens of effectors working combinatorially, and follows principles analogous to transcription regulation: a histone code, activators and repressors, and a promoter-enhancer logic.
- organism: human
- assay: DNA methylation
- assay: ChIP-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 39
- FWCI
- 2.20
- Field percentile
- top 10%
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