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3D reconstruction of genomic regions from sparse interaction data.
Mendieta-Esteban, Julen; Di Stefano, Marco; Castillo, David; Farabella, Irene; Marti-Renom, Marc A.
Afiliación
  • Mendieta-Esteban J; CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
  • Di Stefano M; CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
  • Castillo D; CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
  • Farabella I; CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
  • Marti-Renom MA; CNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
NAR Genom Bioinform ; 3(1): lqab017, 2021 Mar.
Article en En | MEDLINE | ID: mdl-33778492
ABSTRACT
Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2-3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: NAR Genom Bioinform Año: 2021 Tipo del documento: Article

Texto completo: 1 Base de datos: MEDLINE Idioma: En Revista: NAR Genom Bioinform Año: 2021 Tipo del documento: Article