Dataset Information

EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient.

ABSTRACT:

Motivation

Reconstruction of 3D structure models is of great importance for the study of chromosome function. Software tools for this task are highly needed.

Results

We present a novel reconstruction algorithm, called EVRC, which utilizes co-clustering coefficients and error-vector resultant for chromosome 3D structure reconstruction. As an update of our previous EVR algorithm, EVRC now can deal with both single and multiple chromosomes in structure modeling. To evaluate the effectiveness and accuracy of the EVRC algorithm, we applied it to simulation datasets and real Hi-C datasets. The results show that the reconstructed structures have high similarity to the original/real structures, indicating the effectiveness and robustness of the EVRC algorithm. Furthermore, we applied the algorithm to the 3D conformation reconstruction of the wild-type and mutant Arabidopsis thaliana chromosomes and demonstrated the differences in structural characteristics between different chromosomes. We also accurately showed the conformational change in the centromere region of the mutant compared with the wild-type of Arabidopsis chromosome 1. Our EVRC algorithm is a valuable software tool for the field of chromatin structure reconstruction, and holds great promise for advancing our understanding on the chromosome functions.

Availability and implementation

The software is available at https://github.com/mbglab/EVRC.

SUBMITTER: Wang X

PROVIDER: S-EPMC11318666 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Publications

EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient.

Wang Xiao X Gu Wei-Cheng WC Li Jie J Ma Bin-Guang BG

Bioinformatics (Oxford, England) 20231101 11

<h4>Motivation</h4>Reconstruction of 3D structure models is of great importance for the study of chromosome function. Software tools for this task are highly needed.<h4>Results</h4>We present a novel reconstruction algorithm, called EVRC, which utilizes co-clustering coefficients and error-vector resultant for chromosome 3D structure reconstruction. As an update of our previous EVR algorithm, EVRC now can deal with both single and multiple chromosomes in structure modeling. To evaluate the effec ...[more]

PMID: 37847746

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Project description:BackgroundThe three-dimensional (3D) configuration of chromosomes within the eukaryote nucleus is an important factor for several cellular functions, including gene expression regulation, and has also been linked with cancer-causing translocation events. While visualization of such architecture remains limited to low resolutions, the ability to infer structures at increasing resolutions has been enabled by recently-devised chromosome conformation capture techniques. In particular, when coupled with next generation sequencing, such methods yield an inventory of genome-wide chromatin contacts or interactions. Various algorithms have been advanced to operate on such contact data to produce reconstructed 3D configurations. Studies have shown that these reconstructions can provide added value over raw interaction data with respect to downstream biological insights. However, only limited, low-resolution reconstructions have been realized for mammals due to computational bottlenecks.ResultsHere we propose a two-stage algorithm to partially overcome these computational barriers. The central idea is to initially utilize existing reconstruction techniques on an individual chromosome basis, using intra-chromosomal contacts, and then to relatively position these chromosome-level reconstructions using inter-chromosomal contacts. This two-stage strategy represents a natural approach in view of the within- versus between- chromosome distribution of contacts. It can increase resolution ≈ 20 fold for mouse and human. After describing the algorithm we present 3D architectures for mouse embryonic stem cells and human lymphoblastoid cells. We evaluate the impact of several factors on reconstruction reproducibility and explore a variety of sampling schemes. We further analyze replicate data at differing resolutions obtained from recently devised in situ Hi-C assays. In all instances we demonstrate insensitivity of the whole-genome 3D reconstruction obtained by the two-stage algorithm to the sampling strategy used.ConclusionsOur two-stage algorithm has the potential to significantly increase the resolution of 3D genome reconstructions. The improvements are such that we can progress from 1 Mb resolution to 100 kb resolution, notable since this latter value has been identified as critical to inferring topological domains in analyses performed on the contact (rather than 3D) level.

Dataset Information

EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient.

Motivation

Results

Availability and implementation

Publications

EVRC: reconstruction of chromosome 3D structure models using error-vector resultant algorithm with clustering coefficient.

Similar Datasets

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