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Higher-order temporal network effects through triplet evolution.

ABSTRACT: We study the evolution of networks through 'triplets'-three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm's performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

SUBMITTER: Yao Q

PROVIDER: S-EPMC8322211 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature

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Higher-order temporal network effects through triplet evolution.

Yao Qing Q Chen Bingsheng B Evans Tim S TS Christensen Kim K

Scientific reports 20210729 1

We study the evolution of networks through 'triplets'-three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pa ...[more]

PMID: 34326379

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Project description:It is increasingly being recognized that physical interactions between distant chromosomal loci influence the expressivity of the genome. Thus, multiple enhancers may converge on a single gene promoter 1,2 and a single enhancer can stochastically loop to multiple promoters 3. Regulatory elements from neighboring domains or from other chromosomes may interact to generate chromatin structures poised for transcription4-8 or repression 9-11. However, a broader perspective on the formation and function of such networks remains largely unexplored. Using the high-resolution 4C (Circular Chromosome Conformation Capture) analysis, we identify here a genome-wide physical network between genomically imprinted domains impinging H19 imprinting control region (ICR). Sequences interacting with the H19 ICR constitutively map at or within most of known imprinted domains both in mouse embryonic stem cells and in vitro-derived embryoid bodies, despite distinct differences in chromatin environments. Moreover, all-to-all 3D DNA FISH analyses revealed that imprinted domains from 7 different chromosomes co-localize with each other in pair-wise patterns, highlighting the dynamic nature of these interactions. The observed interaction network is dependent on CTCF binding sites within the maternally inherited H19 ICR allele and delays reprogramming of epigenetic features at imprinted domains during male germline development. As other imprinted regions can interact with each other in an H19 ICR-dependent manner, the H19 ICR emerges as an organizer of chromosomal networks by specifically recognizing and reconfiguring imprinted domains. We propose that an ancient key regulatory region, such as the H19 ICR, gradually impacted epigenetic modifications via long-range interactions in the germline to facilitate the recruitment of imprinted genes and their formation in clusters during mammalian radiation. Furthermore, the perspective of epigenetic lesions de-stabilizing such chromosomal networks may advance our understanding of how quantitative traits influence human diseases, such as cancer.

Dataset Information

Higher-order temporal network effects through triplet evolution.

Publications

Higher-order temporal network effects through triplet evolution.

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