Articolo in rivista, 2019, ENG, 10.1109/TCBB.2018.2791439

Estimation of the spatial chromatin structure based on a multiresolution bead-chain model

Caudai C.; Salerno E.; Zoppe M.; Tonazzini A.

CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; CNR-IFC, Pisa, Italy; CNR-ISTI, Pisa, Italy

We present a method to infer 3D chromatin configurations from Chromosome Conformation Capture data. Quite a few methods have been proposed to estimate the structure of the nuclear DNA in homogeneous populations of cells from this kind of data. Many of them transform contact frequencies into Euclidean distances between pairs of chromatin fragments, and then reconstruct the structure by solving a distance-to-geometry problem. To avoid inconsistencies, our method is based on a score function that does not require any frequency-to-distance translation. We propose a multiscale chromatin model where the chromatin fibre is suitably partitioned at each scale. The partial structures are estimated independently, and connected to rebuild the whole fibre. Our score function consists in a data-fit part and a penalty part, balanced automatically at each scale and each subchain. The penalty part enforces "soft" geometric constraints. As many different structures can fit the data, our sampling strategy produces a set of solutions with similar scores. The procedure contains a few parameters, independent of both the scale and the genomic segment treated. The partition of the fibre, along with intrinsically parallel parts, make this method computationally efficient. Results from human genome data support the biological plausibility of our solutions.

IEEE/ACM transactions on computational biology and bioinformatics (Print) 16 (2), pp. 550–559

Keywords

Bayesian estimation, Bioinformatics, Biological system modeling, Chromatin configuration, Chromosome conformation capture, Computational modeling, Data models, DNA, Genomics, Polymers

CNR authors

Caudai Claudia, Zoppe Monica Maria, Salerno Emanuele, Tonazzini Anna

CNR institutes

ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"

ID: 386323

Year: 2019

Type: Articolo in rivista

Creation: 2018-04-13 11:04:08.000

Last update: 2021-04-09 23:41:35.000

External IDs

CNR OAI-PMH: oai:it.cnr:prodotti:386323

DOI: 10.1109/TCBB.2018.2791439

Scopus: 2-s2.0-85041192987

ISI Web of Science (WOS): 000469284500019