Computing Chromosome Conformation

Author(s):  
James Fraser ◽  
Mathieu Rousseau ◽  
Mathieu Blanchette ◽  
Josée Dostie
Nature ◽  
2021 ◽  
Author(s):  
Fides Zenk ◽  
Yinxiu Zhan ◽  
Pavel Kos ◽  
Eva Löser ◽  
Nazerke Atinbayeva ◽  
...  

AbstractFundamental features of 3D genome organization are established de novo in the early embryo, including clustering of pericentromeric regions, the folding of chromosome arms and the segregation of chromosomes into active (A-) and inactive (B-) compartments. However, the molecular mechanisms that drive de novo organization remain unknown1,2. Here, by combining chromosome conformation capture (Hi-C), chromatin immunoprecipitation with high-throughput sequencing (ChIP–seq), 3D DNA fluorescence in situ hybridization (3D DNA FISH) and polymer simulations, we show that heterochromatin protein 1a (HP1a) is essential for de novo 3D genome organization during Drosophila early development. The binding of HP1a at pericentromeric heterochromatin is required to establish clustering of pericentromeric regions. Moreover, HP1a binding within chromosome arms is responsible for overall chromosome folding and has an important role in the formation of B-compartment regions. However, depletion of HP1a does not affect the A-compartment, which suggests that a different molecular mechanism segregates active chromosome regions. Our work identifies HP1a as an epigenetic regulator that is involved in establishing the global structure of the genome in the early embryo.


Author(s):  
Wayne Xu ◽  
James R Tucker ◽  
Wubishet A Bekele ◽  
Frank M You ◽  
Yong-Bi Fu ◽  
...  

Abstract Barley (Hordeum vulgare L.) is one of the most important global crops. The six-row barley cultivar Morex reference genome has been used by the barley research community worldwide. However, this reference genome can have limitations when used for genomic and genetic diversity analysis studies, gene discovery, and marker development when working in two-row germplasm that is more common to Canadian barley. Here we assembled, for the first time, the genome sequence of a Canadian two-row malting barley, cultivar AAC Synergy. We applied deep Illumina paired-end reads, long mate-pair reads, PacBio sequences, 10X chromium linked read libraries, and chromosome conformation capture sequencing (Hi-C) to generate a contiguous assembly. The genome assembled from super-scaffolds had a size of 4.85 Gb, N50 of 2.32 Mb and an estimated 93.9% of complete genes from a plant database (BUSCO, benchmarking universal single-copy orthologous genes). After removal of small scaffolds (< 300 Kb), the assembly was arranged into pseudomolecules of 4.14 Gb in size with seven chromosomes plus unanchored scaffolds. The completeness and annotation of the assembly were assessed by comparing it with the updated version of six-row Morex and recently released two-row Golden Promise genome assemblies.


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Julen Mendieta-Esteban ◽  
Marco Di Stefano ◽  
David Castillo ◽  
Irene Farabella ◽  
Marc A Marti-Renom

Abstract Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer–promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2–3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.


2021 ◽  
Vol 22 (S2) ◽  
Author(s):  
Daniele D’Agostino ◽  
Pietro Liò ◽  
Marco Aldinucci ◽  
Ivan Merelli

Abstract Background High-throughput sequencing Chromosome Conformation Capture (Hi-C) allows the study of DNA interactions and 3D chromosome folding at the genome-wide scale. Usually, these data are represented as matrices describing the binary contacts among the different chromosome regions. On the other hand, a graph-based representation can be advantageous to describe the complex topology achieved by the DNA in the nucleus of eukaryotic cells. Methods Here we discuss the use of a graph database for storing and analysing data achieved by performing Hi-C experiments. The main issue is the size of the produced data and, working with a graph-based representation, the consequent necessity of adequately managing a large number of edges (contacts) connecting nodes (genes), which represents the sources of information. For this, currently available graph visualisation tools and libraries fall short with Hi-C data. The use of graph databases, instead, supports both the analysis and the visualisation of the spatial pattern present in Hi-C data, in particular for comparing different experiments or for re-mapping omics data in a space-aware context efficiently. In particular, the possibility of describing graphs through statistical indicators and, even more, the capability of correlating them through statistical distributions allows highlighting similarities and differences among different Hi-C experiments, in different cell conditions or different cell types. Results These concepts have been implemented in NeoHiC, an open-source and user-friendly web application for the progressive visualisation and analysis of Hi-C networks based on the use of the Neo4j graph database (version 3.5). Conclusion With the accumulation of more experiments, the tool will provide invaluable support to compare neighbours of genes across experiments and conditions, helping in highlighting changes in functional domains and identifying new co-organised genomic compartments.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hong-Lei Li ◽  
Lin Wu ◽  
Zhaoming Dong ◽  
Yusong Jiang ◽  
Sanjie Jiang ◽  
...  

AbstractGinger (Zingiber officinale), the type species of Zingiberaceae, is one of the most widespread medicinal plants and spices. Here, we report a high-quality, chromosome-scale reference genome of ginger ‘Zhugen’, a traditionally cultivated ginger in Southwest China used as a fresh vegetable, assembled from PacBio long reads, Illumina short reads, and high-throughput chromosome conformation capture (Hi-C) reads. The ginger genome was phased into two haplotypes, haplotype 1 (1.53 Gb with a contig N50 of 4.68 M) and haplotype 0 (1.51 Gb with a contig N50 of 5.28 M). Homologous ginger chromosomes maintained excellent gene pair collinearity. In 17,226 pairs of allelic genes, 11.9% exhibited differential expression between alleles. Based on the results of ginger genome sequencing, transcriptome analysis, and metabolomic analysis, we proposed a backbone biosynthetic pathway of gingerol analogs, which consists of 12 enzymatic gene families, PAL, C4H, 4CL, CST, C3’H, C3OMT, CCOMT, CSE, PKS, AOR, DHN, and DHT. These analyses also identified the likely transcription factor networks that regulate the synthesis of gingerol analogs. Overall, this study serves as an excellent resource for further research on ginger biology and breeding, lays a foundation for a better understanding of ginger evolution, and presents an intact biosynthetic pathway for species-specific gingerol biosynthesis.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 946.2-947
Author(s):  
C. Duncan ◽  
E. Hunter ◽  
C. Koutsothanasi ◽  
M. Salter ◽  
A. Akoulitchev ◽  
...  

Background:Rheumatoid arthritis (RA) is a chronic autoimmune disease with substantial immunopathogenic heterogeneity. It is well established that early diagnosis and initiation of effective therapy is crucial to prevent loss of function. Previously, various RA treatment trajectories have been identified, however there are currently no clinically validated biomarkers that can identify these trajectories at the start of treatment. Evaluation of the structural epigenome has revealed that chromosome conformation signatures (CCS) offer great potential as binary, informative biomarkers, and have been previously shown to predict early RA patient response to Methotrexate with 90% sensitivity (1). These signatures can also reveal highly regulated areas of the genome, which may be underpinning disease endotypes.Objectives:The objective of this study was to evaluate the structural epigenome in early RA over longitudinal samples to determine whether it is associated with treatment trajectories.Methods:Patient data and samples were from the Scottish Early Rheumatoid Arthritis (SERA) cohort; a pan-Scotland inception cohort. CDAI, DAS28 ESR and DAS28 CRP measurements were calculated at baseline, 6 months and 12 months to determine longitudinal treatment response. From 3 principal longitudinal response trajectories, 18 patients (who had equivalent disease activity at baseline) were chosen to investigate the structural epigenome. These 18 comprised of responders (R), non-responders (NR) and initial responders (IR; low disease activity/remission at 6 months but moderate/high disease activity at 12 months) with 6 patients per group at each time point. 20 pooled healthy samples were used as a comparator population. EpiSwitch libraries were probed on 180K Agilent SureSelect custom arrays that were designed using EpiSwitch propriety information and publicly available data from Walshet al(2). Microarray data was analysed using the Limma package within R studio.Results:EpiSwitch array analysis showed that there were >10,000 statistically significant differential chromosomal loops between R, NR and IR. Evaluation of the 3 trajectory groups (R, NR and IR), taking into account the healthy chromosomal conformation, revealed an RA-associated structural epigenome that comprised of 10,445 chromosomal loops that were stable, over the three time points. Subsequent analysis of the distinct treatment trajectories demonstrated that 3683 of the stable, disease-associated chromosomal loops were shared by all 3. However, 4496 were associated with distinct response trajectories, with 1221, 2574 and 701 loops unique to R, NR and IR respectively.Conclusion:The stable chromosomal architecture unique to each treatment trajectory suggests that various underlying molecular endotypes may exist. Moreover, the stable loops common to all groups allude to a baseline level of dysregulation in RA and offers the potential to discover novel drivers of disease. This work provides the foundation to further our understanding of RA pathogenesis and the potential of finding a biomarker that would be of significant value in a clinical setting.References:[1] Carini, C., Hunter, E., Scottish Early Rheumatoid Arthritis Inception cohort Investigators, Ramadass, A. S., Green, J., Akoulitchev, A., et al. (2018). Chromosome conformation signatures define predictive markers of inadequate response to methotrexate in early rheumatoid arthritis.Journal of Translational Medicine,16(1), 18–11[2] Walsh, A. M., Whitaker, J. W., Huang, C. C., Cherkas, Y., Lamberth, S. L., Brodmerkel, C., et al. (2016). Integrative genomic deconvolution of rheumatoid arthritis GWAS loci into gene and cell type associations.Genome Biology,17(1), 2205Disclosure of Interests:Caitlin Duncan: None declared, Ewan Hunter: None declared, Christina Koutsothanasi: None declared, Matthew Salter: None declared, Alexandre Akoulitchev: None declared, Iain McInnes Grant/research support from: Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Janssen, and UCB, Consultant of: AbbVie, Bristol-Myers Squibb, Celgene, Eli Lilly and Company, Gilead, Janssen, Novartis, Pfizer, and UCB, Carl Goodyear: None declared


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