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DNA replication occurs in a defined temporal order known as the replication-timing (RT) program. RT is regulated during development in discrete chromosomal units, coordinated with transcriptional activity and 3D genome organization. Here, we derived distinct cell types from F1 hybrid musculus × castaneus mouse crosses and exploited the high single-nucleotide polymorphism (SNP) density to characterize allelic differences in RT (Repli-seq), genome organization (Hi-C and promoter-capture Hi-C), gene expression (total nuclear RNA-seq), and chromatin accessibility (ATAC-seq). We also present HARP, a new computational tool for sorting SNPs in phased genomes to efficiently measure allele-specific genome-wide data. Analysis of six different hybrid mESC clones with different genomes (C57BL/6, 129/sv, and CAST/Ei), parental configurations, and gender revealed significant RT asynchrony between alleles across ∼12% of the autosomal genome linked to subspecies genomes but not to parental origin, growth conditions, or gender. RT asynchrony in mESCs strongly correlated with changes in Hi-C compartments between alleles but not as strongly with SNP density, gene expression, imprinting, or chromatin accessibility. We then tracked mESC RT asynchronous regions during development by analyzing differentiated cell types, including extraembryonic endoderm stem (XEN) cells, four male and female primary mouse embryonic fibroblasts (MEFs), and neural precursor cells (NPCs) differentiated in vitro from mESCs with opposite parental configurations. We found that RT asynchrony and allelic discordance in Hi-C compartments seen in mESCs were largely lost in all differentiated cell types, accompanied by novel sites of allelic asynchrony at a considerably smaller proportion of the genome, suggesting that genome organization of homologs converges to similar folding patterns during cell fate commitment.
Pubmed ID: 29735606
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ReplicationDomain is an online database resource for storing, sharing and visualizing DNA replication timing and transcription data, as well as other numerical epigenetic data types. Data is typically obtained from DNA microarrays or DNA sequencing. Our site has a user registration system that allows registered users to upload their own data sets. While non-registered users may freely view and download public data sets, registered users may upload their own data sets and view them privately, share them with other registered users, or make published data sets publicly available. In addition we have implemented additional mechanisms that allow users to restrict sharing of data sets to a user designated group of registered users. Further details on the database usage are in the User Guide Page, while data set details are in the Documentation Page. Replication timing data were obtained by hybridizing early and late replication intermediates to Nimblegen oligonucleotide arrays, as described in Hiratani et al [PLoS Biology (2008) 6: e245]. Briefly, replication intermediates are prepared from cells that are first pulse-labeled with BrdU and then sorted into early and late stages of S-phase by flow cytometry, followed by anti-BrdU immunoprecipitation of the BrdU-substituted (nascent) replication intermediates that were synthesized either early or late during S-phase. After unbiased amplification of recovered DNA, the samples are differentially labeled with Cy3 and Cy5 and hybridized to Nimblegen CGH arrays containing one oligonucleotide probe every 5.8 kb across the mouse genome (Nimblegen, 2006-07-26_MM8_WG_CGH). Raw data from two independent biological replicates in which the early and late replicating DNA were labeled reciprocally with Cy3 and Cy 5 (dye switch) are loess-normalized and scaled to have the same median-absolute deviation using the limma package (R/Bioconductor) and then averaged. Finally, the data are smoothed with a weighted moving average (loess: local polynomial smoothing).
View all literature mentionsSoftware R package. Methods for Cluster analysis. Performs variety of types of cluster analysis and other types of processing on large microarray datasets.
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