Parallel analysis of replication timing, gene expression, and copy number with PARTAGE
- Lakshana Sruthi Sadu Murari1,5,
- Quinn Dickinson1,5,
- Silvia Meyer-Nava1 and
- Juan Carlos Rivera-Mulia1,2,3,4
- 1Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA;
- 2Masonic Cancer Center, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA;
- 3Stem Cell Institute, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA;
- 4Masonic Institute on the Biology of Aging and Metabolism, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA
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↵5 These authors contributed equally to this work.
Abstract
The human genome is partitioned into functional compartments that replicate at specific times during S-phase. This temporal program, referred to as replication timing (RT), is coregulated with the 3D genome organization, is cell type–specific, and changes during development in coordination with gene expression. Moreover, RT alterations are linked to abnormal gene expression, genome instability, and structural variation in multiple diseases, including cancer. However, mechanistic links between RT, large-scale 3D genome architecture, and transcriptional regulation remain poorly understood. A major limitation is that current approaches require the separate profiling of RT and transcriptomes from independent batches of samples, which obscures the complex coregulation between the epigenome and transcriptome. Here, we present PARTAGE, a multiomics approach that enables joint profiling of copy number variation (CNV), RT, and gene expression from the same sample, providing a more accurate integrated view of the complex relationships between RT and gene regulation.
Footnotes
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[Supplemental material is available for this article.]
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Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.281532.125.
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Freely available online through the Genome Research Open Access option.
- Received October 6, 2025.
- Accepted March 2, 2026.
This article, published in Genome Research, is available under a Creative Commons License (Attribution-NonCommercial 4.0 International), as described at http://creativecommons.org/licenses/by-nc/4.0/.
