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. 2019 Oct 15;20(1):738.
doi: 10.1186/s12864-019-6096-0.

EVR: reconstruction of bacterial chromosome 3D structure models using error-vector resultant algorithm

Kang-Jian Hua  1 , Bin-Guang Ma  2
Affiliations

EVR: reconstruction of bacterial chromosome 3D structure models using error-vector resultant algorithm

Kang-Jian Hua et al. BMC Genomics. .

Abstract

Background: More and more 3C/Hi-C experiments on prokaryotes have been published. However, most of the published modeling tools for chromosome 3D structures are targeting at eukaryotes. How to transform prokaryotic experimental chromosome interaction data into spatial structure models is an important task and in great need.

Results: We have developed a new reconstruction program for bacterial chromosome 3D structure models called EVR that exploits a simple Error-Vector Resultant (EVR) algorithm. This software tool is particularly optimized for the closed-loop structural features of prokaryotic chromosomes. The parallel implementation of the program can utilize the computing power of both multi-core CPUs and GPUs.

Conclusions: EVR can be used to reconstruct the bacterial 3D chromosome structure based on the contact frequency matrix derived from 3C/Hi-C experimental data quickly and precisely.

Keywords: 3D genome; Chromatin architecture; Hi-C; Prokaryotes; Structure modelling.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Data flow chart of the EVR algorithm. a Expected distance matrix. b An initial random conformation. c Error vectors on bins: each red arrow is an error vector of a bin. d New conformation after moving bins according to the guidance of error vectors. e The final structure
Fig. 2
Fig. 2
EVR calculation. a Illustration of error-vectors and error-vector resultants. Pj1, Pj2, and Pj3 are 3 bins whose positions (coordinates) need to be adjusted; Pi and Pk are 2 bins whose positions are fixed; Dij and Djk are the expected distances between these 3 bins to bins Pi and Pk; the intersection points of the two dotted circles (centered at Pi and Pk with radii Dij and Djk, respectively) are the target positions of the 3 bins Pj1, Pj2, and Pj3; the closest intersection point is chosen as the target position for each of the 3 bins. b The distances between the 3 bins Pj1, Pj2, Pj3 to their target positions decrease during iteration
Fig. 3
Fig. 3
The required time for standard structure reconstruction with different bin numbers
Fig. 4
Fig. 4
Comparison between reconstructed structures (from noisy data) and original structures using four software tools. Both the absolute RMSD value and its trend with the increase of noise level should be considered
Fig. 5
Fig. 5
Correlation between the structure-based distance and the experimentally measured distance. The chromosome structures were reconstructed by using the four software tools based on recently published 3C data of E. coli [21] and the experimentally measured distances were compiled from literature [36]. See Supplementary Information (Additional file 1: Table S1) for more details
Fig. 6
Fig. 6
Schematic representation of the reconstructed 3D chromosome structures of three model prokaryotes. Macrodomains are colored as indicated by legend. The macrodomains of E. coli are accurately determined according to previous publication [37], while those of C. crescentus and B. subtilis are roughly shown with halos
Fig. 7
Fig. 7
Comparison of chromosome structures of wild-type and Δfis type E. coli. Green and cyan tubes represent the chromosomes of wild-type and Δfis strains, respectively, and the blue parts are the terminus region. There is a clear separation between the two structures in terminus regions, which cannot be easily found without accurate 3D structures
See this image and copyright information in PMC

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