Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data

Sep 21, 2026

Uploaded by Riley

Study dysregulated DNA replication in aneuploid cancers by integrating replication timing (RT) and copy number alterations (CNAs) at single-cell resolution. A probabilistic framework, PERT, infers cell-specific replication and copy number states from single-cell whole genome sequencing (scWGS) data. Using PERT on more than 50,000 cells across cell lines, xenografts, and primary cancers reveals bidirectional RT–CNA relationships and clone-level S-phase enrichment linked to proliferation rates in stable but not unstable cells.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages19

Reading Time48 min

AccessFree to download

Introduction

Replication timing and genomic context

Motivation: RT and CNAs in aneuploid tumors

S-phase quantification and clonal fitness

Limitations of existing approaches

Article [https://doi.org/10.1038/s41467-024-52544-7](https://doi.org/10.1038/s41467-024-52544-7) Inferring replication timing and proliferation dynamics from single-cell DNA sequencing data Received: 29 January 2024 | Accepted: 11 September 2024 | | --- | | | | Check for updates | Adam C. Weiner 1,2, Marc J. Williams 1, HongyuShi1,3, Ignacio Vázquez-García1, Sohrab Salehi1, Nicole Rusk 1, Samuel Aparicio 4,5, Sohrab P. Shah 1,6 & Andrew McPherson 1,6 Dysregulated DNA replication is a cause and a consequence of aneuploidy in cancer, yet the interplay between copy number alterations (CNAs), replication timing (RT) and cell cycle dynamics remain understudied in aneuploid tumors. We developed a probabilistic method, PERT, for simultaneous inference of cell-speciﬁc replication and copy number states from single-cell whole genome sequencing (scWGS) data. We used PERT to investigate clone-speciﬁcRT and proliferation dynamics in >50,000 cells obtained from aneuploid and clonally heterogeneous cell lines, xenografts and primary cancers. We observed bidirectional relationships between RT and CNAs, with CNAs affecting X-inactivation producing the largest RT shifts. Additionally, we found that clone-speciﬁcS-phase enrichment positively correlated with ground-truth proliferation rates in genomically stable but not unstable cells. Together, these results demonstrate robust computational identiﬁcation ofS-phase cells from scWGS data, and highlight the importance of RT and cell cycle properties in studying the genomic evolution of aneuploid tumors. DNA replication and cell cycle regulation are frequently disrupted as part of a cancer’s progression toward uncontrolled proliferation1–3. The resulting dysregulation creates a positive feedback loop of increasing replication stress and genomic instability4–6, generating new somatic copy number alterations (CNAs) which drives intratumoral heterogeneity and subsequent clonal evolution7–9. One key component of DNA replication is the relative timing at which different genomic regions replicate during synthesis (S)-phase of the cell cycle, known as replication timing (RT). Genome-wide RT proﬁles are visible at resolutions ranging from 10kb to 10MB and have well-deﬁned associations with chromatin organization, mutation rate, and transcription, and cellular phenotype3,10–18. Structural variations and CNAs have been shown to impact transcription and epigenetic state19–21 but little is known about their associations with RT as technical limitations in isolating S-phase cells have prevented measurement of both bulk and single-cell RT in primary tumors with subclonal CNAs3,13,14,17,22–28. This limitation has forced previous studies of RT to compare CNAs from tumor samples against RT proﬁles from unmatched cell lines, often of different tissue types12,29–31, or RT proﬁles predicted from matched chromatin accessibility data18. Therefore, there remain open questions about the bi-directional interplay between ongoing genomic instability and RT dynamics. Outside of studying RT, quantifying S-phase cells in tumors can be used to better understand proliferation and clonal ﬁtness dynamics. The most accurate way to measure clonal ﬁtness is through ﬁtting population genetics models to time-series data32–34; however, such 1Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 2Tri-Institutional PhD Program in Computational Biology and Medicine, Weill Cornell Medicine, New York, NY, USA. 3Gerstner Sloan Kettering Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA. 4Department of Molecular Oncology, British Columbia Cancer, Vancouver, BC, Canada. 5Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada. 6These authors contributed equally: Sohrab P. Shah, Andrew McPherson. e-mail: [shahs3@mskcc.org](shahs3@mskcc.org); [mcphera1@mskc

FAQs

What problem does the study address in aneuploid tumors?

It targets the understudied relationship between copy number alterations (CNAs), replication timing (RT), and cell cycle dynamics in aneuploid cancers.

What method is introduced for single-cell analysis?

The study develops PERT, a probabilistic method to infer cell-specific replication and copy number states from single-cell whole genome sequencing data.

What key relationships are reported between RT and CNAs?

The results show bidirectional relationships between RT and CNAs, with CNAs—especially those involving X-inactivation—producing the largest RT shifts.

Sep 21, 2026

Uploaded by Riley