Inferring Single-Cell 3D Chromosomal Structures Based on the Lennard-Jones Potential.
Inferring Single-Cell 3D Chromosomal Structures Based on the Lennard-Jones Potential.
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DOI：
10.3390/ijms22115914
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发表时间：
2021-05-31
影响因子：
5.6
通讯作者：
Wang Z
中科院分区：
文献类型：
--
作者：
Zha M;Wang N;Zhang C;Wang Z
由于单细胞Hi-C数据的极端稀疏性，基于单细胞Hi-C数据重建三维（3D）染色体结构是一个具有挑战性的科学问题。在这项研究中，我们使用Lennard-Jones势来重建基于单细胞Hi-C数据的500 kb和高分辨率50 kb染色体结构。染色体由一串500 kb或50 kb的DNA珠粒表示，并放入3D立方晶格中进行模拟。使用2D高斯函数来估算稀疏单细胞Hi-C接触矩阵。我们设计了一种新的损失函数的基础上的Lennard-Jones潜力，其中的价值，即，井深用于表示每对珠子的结合有多稳定。对于具有单细胞Hi-C接触的珠对及其相邻珠对，损失函数赋予它们更强的结合稳定性。Metropolis-Hastings算法用于尝试DNA珠的不同位置，并且模拟退火用于优化损失函数。通过对模型的多项评价标准以及与3D-FISH数据的比较，证明了重建的三维结构的正确性和有效性。
Reconstructing three-dimensional (3D) chromosomal structures based on single-cell Hi-C data is a challenging scientific problem due to the extreme sparseness of the single-cell Hi-C data. In this research, we used the Lennard-Jones potential to reconstruct both 500 kb and high-resolution 50 kb chromosomal structures based on single-cell Hi-C data. A chromosome was represented by a string of 500 kb or 50 kb DNA beads and put into a 3D cubic lattice for simulations. A 2D Gaussian function was used to impute the sparse single-cell Hi-C contact matrices. We designed a novel loss function based on the Lennard-Jones potential, in which the value, i.e., the well depth, was used to indicate how stable the binding of every pair of beads is. For the bead pairs that have single-cell Hi-C contacts and their neighboring bead pairs, the loss function assigns them stronger binding stability. The Metropolis–Hastings algorithm was used to try different locations for the DNA beads, and simulated annealing was used to optimize the loss function. We proved the correctness and validness of the reconstructed 3D structures by evaluating the models according to multiple criteria and comparing the models with 3D-FISH data.
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影响因子：
16.6
作者：
Conte, Mattia;Fiorillo, Luca;Nicodemi, Mario
通讯作者：
Nicodemi, Mario
影响因子：
64.5
作者：
Bonev B;Mendelson Cohen N;Szabo Q;Fritsch L;Papadopoulos GL;Lubling Y;Xu X;Lv X;Hugnot JP;Tanay A;Cavalli G
通讯作者：
Cavalli G
DOI：
10.1126/science.1237973
发表时间：
2013-08-16
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Engreitz JM;Pandya-Jones A;McDonel P;Shishkin A;Sirokman K;Surka C;Kadri S;Xing J;Goren A;Lander ES;Plath K;Guttman M
通讯作者：
Guttman M
影响因子：
64.8
作者：
Beagrie RA;Scialdone A;Schueler M;Kraemer DC;Chotalia M;Xie SQ;Barbieri M;de Santiago I;Lavitas LM;Branco MR;Fraser J;Dostie J;Game L;Dillon N;Edwards PA;Nicodemi M;Pombo A
通讯作者：
Pombo A
影响因子：
7
作者：
Dostie, Josee;Richmond, Todd A.;Dekker, Job
通讯作者：
Dekker, Job