Literature DB >> 35781769

Optimized Repli-seq: improved DNA replication timing analysis by next-generation sequencing.

Juan Carlos Rivera-Mulia1,2,3, Claudia Trevilla-Garcia4, Santiago Martinez-Cifuentes4.   

Abstract

The human genome is divided into functional units that replicate at specific times during S-phase. This temporal program is known as replication timing (RT) and is coordinated with the spatial organization of the genome and transcriptional activity. RT is also cell type-specific, dynamically regulated during development, and alterations in RT are observed in multiple diseases. Thus, the precise measure of RT is critical to understand the role of RT in gene function regulation. Distinct methods for assaying the RT program exist; however, conventional methods require thousands of cells as input, prohibiting its applicability to samples with limited cell numbers such as those from disease patients or from early developing embryos. Although single-cell RT analyses have been developed, these methods are low throughput, require generation of numerous libraries, increased sequencing costs, and produce low resolution data. Here, we developed an improved method to measure RT genome-wide that enables high-resolution analysis of low input samples. This method incorporates direct cell sorting into lysis buffer, as well as DNA fragmentation and library preparation in a single tube, resulting in higher yields, increased quality, and reproducibility with decreased costs. We also performed a systematic data processing analysis to provide standardized parameters for RT measurement. This optimized method facilitates RT analysis and will enable its application to a broad range of studies investigating the role of RT in gene expression, nuclear architecture, and disease.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.

Entities:  

Keywords:  DNA replication; genomics; library preparation; next-generation sequencing; replication timing

Year:  2022        PMID: 35781769     DOI: 10.1007/s10577-022-09703-7

Source DB:  PubMed          Journal:  Chromosome Res        ISSN: 0967-3849            Impact factor:   4.620


  2 in total

1.  TIGER: inferring DNA replication timing from whole-genome sequence data.

Authors:  Amnon Koren; Dashiell J Massey; Alexa N Bracci
Journal:  Bioinformatics       Date:  2021-03-11       Impact factor: 6.931

Review 2.  Molecular pathology of rare progeroid diseases.

Authors:  Matthias Rieckher; George A Garinis; Björn Schumacher
Journal:  Trends Mol Med       Date:  2021-07-13       Impact factor: 11.951

  2 in total

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