scholarly journals Dynamic Network Analysis of the 4D Nucleome

2018 ◽  
Author(s):  
Sijia Liu ◽  
Pin-Yu Chen ◽  
Alfred Hero ◽  
Indika Rajapakse

AbstractMotivationFor many biological systems, it is essential to capture simultaneously the function, structure, and dynamics in order to form a comprehensive understanding of underlying phenomena. The dynamical interaction between 3D genome spatial structure and transcriptional activity creates a genomic signature that we refer to as the four-dimensional organization of the nucleus, or 4D Nucleome (4DN). The study of 4DN requires assessment of genome-wide structure and gene expression as well as development of new approaches for data analysis.ResultsWe propose a dynamic multilayer network approach to study the co-evolution of form and function in the 4D Nucleome. We model the dynamic biological system as a temporal network with node dynamics, where the network topology is captured by chromosome conformation (Hi-C), and the function of a node is measured by RNA sequencing (RNA-seq). Network-based approaches such as von Neumann graph entropy, network centrality, and multilayer network theory are applied to reveal universal patterns of the dynamic genome. Our model integrates knowledge of genome structure and gene expression along with temporal evolution and leads to a description of genome behavior on a system wide level. We illustrate the benefits of our model via a real biological dataset on MYOD1-mediated reprogramming of human fibroblasts into the myogenic lineage. We show that our methods enable better predictions on form-function relationships and refine our understanding on how cell dynamics change during cellular reprogramming.Availability: The software is available upon [email protected] informationSee Supplementary Material.

Nucleus ◽  
2017 ◽  
Vol 8 (4) ◽  
pp. 383-391 ◽  
Author(s):  
Haiming Chen ◽  
Laura Seaman ◽  
Sijia Liu ◽  
Thomas Ried ◽  
Indika Rajapakse

2015 ◽  
Vol 112 (26) ◽  
pp. 8002-8007 ◽  
Author(s):  
Haiming Chen ◽  
Jie Chen ◽  
Lindsey A. Muir ◽  
Scott Ronquist ◽  
Walter Meixner ◽  
...  

The 4D organization of the interphase nucleus, or the 4D Nucleome (4DN), reflects a dynamical interaction between 3D genome structure and function and its relationship to phenotype. We present initial analyses of the human 4DN, capturing genome-wide structure using chromosome conformation capture and 3D imaging, and function using RNA-sequencing. We introduce a quantitative index that measures underlying topological stability of a genomic region. Our results show that structural features of genomic regions correlate with function with surprising persistence over time. Furthermore, constructing genome-wide gene-level contact maps aided in identifying gene pairs with high potential for coregulation and colocalization in a manner consistent with expression via transcription factories. We additionally use 2D phase planes to visualize patterns in 4DN data. Finally, we evaluated gene pairs within a circadian gene module using 3D imaging, and found periodicity in the movement of clock circadian regulator and period circadian clock 2 relative to each other that followed a circadian rhythm and entrained with their expression.


2018 ◽  
Author(s):  
Liam Spurr ◽  
Nawaf Alomran ◽  
Piotr Słowiński ◽  
Muzi Li ◽  
Pavlos Bousounis ◽  
...  

MotivationBy testing for association of DNA genotypes with gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation can be measured at expressed genome regions, and differs from the DNA genotype in sites subjected to regulatory forces. Therefore, assessment of correlation between RNA genetic variation and gene expression can reveal regulatory genomic relationships in addition to eQTLs.ResultsWe introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele frequency (VAF) at expressed SNV loci in the transcriptome. We exemplify the method on sets of RNA-sequencing data from human tissues obtained though the Genotype-Tissue Expression Project (GTEx) and demonstrate that ReQTL analyses show consistently high performance and sufficient power to identify both previously known and novel molecular associations. The majority of the SNVs implicated in significant cis-ReQTLs identified by our analysis were previously reported as significant cis-eQTL loci. Notably, trans ReQTL loci in our data were substantially enriched in RNA-editing sites. In summary, ReQTL analyses are computationally feasible and do not require matched DNA data, hence they have a high potential to facilitate the discovery of novel molecular interactions through exploration of the increasingly accessible RNA-sequencing datasets.Availability and implementationSample scripts used in our ReQTL analyses are available with the Supplementary Material (ReQTL_sample_code)[email protected] or [email protected] InformationRe_QTL_Supplementary_Data.zip


2017 ◽  
Author(s):  
Chris Chatzinakos ◽  
Donghyung Lee ◽  
Bradley T Webb ◽  
Vladimir I Vladimirov ◽  
Kenneth S Kendler ◽  
...  

AbstractMotivationTo increase detection power, researchers use gene level analysis methods to aggregate weak marker signals. Due to gene expression controlling biological processes, researchers proposed aggregating signals for expression Quantitative Trait Loci (eQTL). Most gene-level eQTL methods make statistical inferences based on i) summary statistics from genome-wide association studies (GWAS) and ii) linkage disequilibrium (LD) patterns from a relevant reference panel. While most such tools assume homogeneous cohorts, our Gene-level Joint Analysis of functional SNPs in Cosmopolitan Cohorts (JEPEGMIX) method accommodates cosmopolitan cohorts by using heterogeneous panels. However, JEPGMIX relies on brain eQTLs from older gene expression studies and does not adjust for background enrichment in GWAS signals.ResultsWe propose JEPEGMIX2, an extension of JEPEGMIX. When compared to JPEGMIX, it uses i) cis-eQTL SNPs from the latest expression studies and ii) brains specific (sub)tissues and tissues other than brain. JEPEGMIX2 also i) avoids accumulating averagely enriched polygenic information by adjusting for background enrichment and ii), to avoid an increase in false positive rates for studies with numerous highly enriched (above the background) genes, it outputs gene q-values based on Holm adjustment of [email protected] informationSupplementary material is available at Bioinformatics online.


2018 ◽  
Author(s):  
Adam McDermaid ◽  
Xin Chen ◽  
Yiran Zhang ◽  
Juan Xie ◽  
Cankun Wang ◽  
...  

AbstractMotivationOne of the main benefits of using modern RNA-sequencing (RNA-Seq) technology is the more accurate gene expression estimations compared with previous generations of expression data, such as the microarray. However, numerous issues can result in the possibility that an RNA-Seq read can be mapped to multiple locations on the reference genome with the same alignment scores, which occurs in plant, animal, and metagenome samples. Such a read is so-called a multiple-mapping read (MMR). The impact of these MMRs is reflected in gene expression estimation and all downstream analyses, including differential gene expression, functional enrichment, etc. Current analysis pipelines lack the tools to effectively test the reliability of gene expression estimations, thus are incapable of ensuring the validity of all downstream analyses.ResultsOur investigation into 95 RNA-Seq datasets from seven species (totaling 1,951GB) indicates an average of roughly 22% of all reads are MMRs for plant and animal species. Here we present a tool called GeneQC (Gene expression Quality Control), which can accurately estimate the reliability of each gene’s expression level. The underlying algorithm is designed based on extracted genomic and transcriptomic features, which are then combined using elastic-net regularization and mixture model fitting to provide a clearer picture of mapping uncertainty for each gene. GeneQC allows researchers to determine reliable expression estimations and conduct further analysis on the gene expression that is of sufficient quality. This tool also enables researchers to investigate continued re-alignment methods to determine more accurate gene expression estimates for those with low reliability.AvailabilityGeneQC is freely available at http://bmbl.sdstate.edu/GeneQC/[email protected] informationSupplementary data are available at Bioinformatics online.


2020 ◽  
Vol 98 (2) ◽  
pp. 178-190 ◽  
Author(s):  
Zachery R. Belak ◽  
Joshua. A. Pickering ◽  
Zoe. E. Gillespie ◽  
Gerald Audette ◽  
Mark Eramian ◽  
...  

We previously demonstrated that genome reorganization, through chromosome territory repositioning, occurs concurrently with significant changes in gene expression in normal primary human fibroblasts treated with the drug rapamycin, or stimulated into quiescence. Although these events occurred concomitantly, it is unclear how specific changes in gene expression relate to reorganization of the genome at higher resolution. We used computational analyses, genome organization assays, and microscopy, to investigate the relationship between chromosome territory positioning and gene expression. We determined that despite relocation of chromosome territories, there was no substantial bias in the proportion of genes changing expression on any one chromosome, including chromosomes 10 and 18. Computational analyses identified that clusters of serum deprivation and rapamycin-responsive genes along the linear extent of chromosomes. Chromosome conformation capture (3C) analysis demonstrated the strengthening or loss of specific long-range chromatin interactions in response to rapamycin and quiescence induction, including a cluster of genes containing Interleukin-8 and several chemokine genes on chromosome 4. We further observed that the LIF gene, which is highly induced upon rapamycin treatment, strengthened interactions with up- and down-stream intergenic regions. Our findings indicate that the repositioning of chromosome territories in response to cell stimuli, this does not reflect gene expression changes occurring within physically clustered groups of genes.


Author(s):  
Muhammad Muzammal Adeel ◽  
Hao Jiang ◽  
Yibeltal Arega ◽  
Kai Cao ◽  
Da Lin ◽  
...  

Human papillomavirus (HPV) integration is the major contributor to cervical cancer (CC) development by inducing structural variations (SVs) in the human genome. SVs are directly associated with the three-dimensional (3D) genome structure leading to cancer development. The detection of SVs is not a trivial task, and several genome-wide techniques have greatly helped in the identification of SVs in the cancerous genome. However, in cervical cancer, precise prediction of SVs mainly translocations and their effects on 3D-genome and gene expression still need to be explored. Here, we have used high-throughput chromosome conformation capture (Hi-C) data of cervical cancer to detect the SVs, especially the translocations, and validated it through whole-genome sequencing (WGS) data. We found that the cervical cancer 3D-genome architecture rearranges itself as compared to that in the normal tissue, and 24% of the total genome switches their A/B compartments. Moreover, translocation detection from Hi-C data showed the presence of high-resolution t(4;7) (q13.1; q31.32) and t(1;16) (q21.2; q22.1) translocations, which disrupted the expression of the genes located at and nearby positions. Enrichment analysis suggested that the disrupted genes were mainly involved in controlling cervical cancer-related pathways. In summary, we detect the novel SVs through Hi-C data and unfold the association among genome-reorganization, translocations, and gene expression regulation. The results help understand the underlying pathogenicity mechanism of SVs in cervical cancer development and identify the targeted therapeutics against cervical cancer.


2021 ◽  
Author(s):  
Stephen M Lindsly ◽  
Can Chen ◽  
Sam Dilworth ◽  
Sivakumar Jeyarajan ◽  
Cooper Stansbury ◽  
...  

Chromatin architecture, a key regulator of gene expression, is inferred through chromatin contacts. However, classical analyses of chromosome conformation data do not preserve multi-way relationships. Here we use long sequencing reads to map genome-wide multi-way contacts and investigate higher order chromatin organization of the human genome. We use the theory of hypergraphs for data representation and analysis, and quantify higher order structures in primary human fibroblasts and B lymphocytes. Through integration of multi-way contact data with chromatin accessibility, gene expression, and transcription factor binding data, we introduce a data-driven method to extract transcriptional clusters.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1094.2-1095
Author(s):  
A. S. Siebuhr ◽  
S. F. Madsen ◽  
M. Karsdal ◽  
A. C. Bay-Jensen ◽  
P. Juhl

Background:Systemic sclerosis has vascular, inflammatory and fibrotic components, which may be associated with different growth factors and cytokines. Platelet derived growth factor (PDGF) is associated with the vasculature, whereas tumor necrosis factor beta (TGFβ) is associated with inflammation and fibrosis. We have developed a fibroblast model system of dermal fibrosis for anti-fibrotic drugs testing, but the effect of the fibroblasts mechanistic properties are unknown.Objectives:We investigated different mechanical capacities of PDGF and TGFβ treated human healthy dermal fibroblasts in the SiaJ setting.Methods:Primary human healthy dermal fibroblasts were grown in DMEM medium containing 0.4% fetal calf serum, ficoll (to produce a crowded environment) and ascorbic acid for up to 17 days. A wound was induced by scratching the cells at 0, 1, 3 or 7 days after treatment initiation. Wound closure was followed for 3 days. Contraction capacity was tested by creating gels of human fibroblasts produced collagens containing dermal fibroblasts and contraction was assessed at day 2 by calculating the percentage of gel size to total well size. Collagen type I, III and VI formation (PRO-C1, PRO-C3 and PRO-C6) and fibronectin (FBN-C) were evaluated by validated ELISAs (Nordic Bioscience). Gene expression was analyzed after 2 days in culture. Statistical analyses included One-way ANOVA and student’s t-test.Results:Generally, PDGF closed the wound in half the time of w/o and TGFβ, when treatment and cells are added concurrently or scratched one day after treatment initiation. When treatments were added 3 or 7 days prior to scratch, the cells treated with PDGF had proliferated to a higher degree than w/o and TGFβ. A consequence of this, was that when cells were scratch the sheet of cells produced was lifted from the bottom and fold over itself, leaving a much greater scratch than in the other treatments. However, despite this increased gap the PDGF treated cells closed the wound at the same time as w/o and TGFβ, confirming the results of the cells scratched at day 0 and 1.Inhibition of contraction by ML-7 of otherwise untreated cells inhibited contraction significantly compared to untreated cells alone (p=0.0009). Contraction was increased in both TGFβ and PDGF treated cells compared to untreated cells (both p<0.0001). TGFβ+ ML-7 inhibited the contraction to the level of w/o (p=0.0024), which was only 35% of ML-7 alone. In the contraction study the cells were terminated after 2 days of culture, thus prior to when biomarker of ECM remodeling is usually assessed. However, FBN-C was detectable and a significant release of fibronectin by TGFβ and PDGF compared to w/o was found in the supernatant (both p<0.0001). The gene expression of FBN was only increased with TGFβ (p<0.05) and not PDGF. ML-7 alone tended to decrease FBN-C and in combination with TGFβ the FBN level was significantly decreased compared to TGFβ alone (p<0.0001). However, the level of TGFβ+ML-7 was significantly higher than ML-7 alone (p=0.038).TGFβ increased the gene expression of most genes assessed, except Col6a1. PDGF increased the gene expression of Col3a1, Col5a1 and Col6a1 above the critical fold change of 2, but only significantly in Col5a1 and Col6a1 (both p<0.05).Conclusion:This study demonstrates that TGFβ and PDGF have different mechanical capacities in human healthy dermal fibroblasts; TGFβ increased gene expression of ECM related genes, such as collagens and have increased FBN release in the supernatant already 2 days after initial treatment. PDGF has increased contraction, proliferation and migratory capacities and less expression of ECM related genes and proteins.Disclosure of Interests:Anne Sofie Siebuhr Employee of: Nordic Bioscience, Sofie Falkenløve Madsen: None declared, Morten Karsdal Shareholder of: Nordic Bioscience A/S., Employee of: Full time employee at Nordic Bioscience A/S., Anne-Christine Bay-Jensen Shareholder of: Nordic Bioscience A/S, Employee of: Full time employee at Nordic Bioscience A/S., Pernille Juhl Employee of: Nordic Bioscience


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