Your browser doesn't support javascript.
loading
Decoding chromosome organization using CheC-PLS: chromosome conformation by proximity labeling and long-read sequencing.
Xu, Kewei; Zhang, Yichen; Baldwin-Brown, James; Sasani, Thomas A; Phadnis, Nitin; Miller, Matthew P; Rog, Ofer.
Afiliación
  • Xu K; School of Biological Sciences, University of Utah.
  • Zhang Y; Center for Cell and Genome Sciences, University of Utah.
  • Baldwin-Brown J; School of Biological Sciences, University of Utah.
  • Sasani TA; Center for Cell and Genome Sciences, University of Utah.
  • Phadnis N; School of Biological Sciences, University of Utah.
  • Miller MP; Department of Human Genetics, University of Utah.
  • Rog O; School of Biological Sciences, University of Utah.
bioRxiv ; 2024 Jun 03.
Article en En | MEDLINE | ID: mdl-38895449
ABSTRACT
Genomic approaches have provided detailed insight into chromosome architecture. However, commonly deployed techniques do not preserve connectivity-based information, leaving large-scale genome organization poorly characterized. Here, we developed CheC-PLS a proximity-labeling technique that indelibly marks, and then decodes, protein-associated sites. CheC-PLS tethers dam methyltransferase to a protein of interest, followed by Nanopore sequencing to identify methylated bases - indicative of in vivo proximity - along reads >100kb. As proof-of-concept we analyzed, in budding yeast, a cohesin-based meiotic backbone that organizes chromatin into an array of loops. Our data recapitulates previously obtained association patterns, and, importantly, exposes variability between cells. Single read data reveals cohesin translocation on DNA and, by anchoring reads onto unique regions, we define the internal organization of the ribosomal DNA locus. Our versatile technique, which we also deployed on isolated nuclei with nanobodies, promises to illuminate diverse chromosomal processes by describing the in vivo conformations of single chromosomes.

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article