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BackgroundThe number of reported examples of chromatin architecture alterations involved in the regulation of gene transcription and in disease is increasing. However, no genome-wide testing has been performed to assess the abundance of these events and their importance relative to other factors affecting genome regulation. This is particularly interesting given that a vast majority of genetic variations identified in association studies are located outside coding sequences. This study attempts to address this lack by analyzing the impact on chromatin spatial organization of genetic variants identified in individuals from 26 human populations and in genome-wide association studies.ResultsWe assess the tendency of structural variants to accumulate in spatially interacting genomic segments and design an algorithm to model chromatin conformational changes caused by structural variations. We show that differential gene transcription is closely linked to the variation in chromatin interaction networks mediated by RNA polymerase II. We also demonstrate that CTCF-mediated interactions are well conserved across populations, but enriched with disease-associated SNPs. Moreover, we find boundaries of topological domains as relatively frequent targets of duplications, which suggest that these duplications can be an important evolutionary mechanism of genome spatial organization.ConclusionsThis study assesses the critical impact of genetic variants on the higher-order organization of chromatin folding and provides insight into the mechanisms regulating gene transcription at the population scale, of which local arrangement of chromatin loops seems to be the most significant. It provides the first insight into the variability of the human 3D genome at the population scale. ; This work was carried out within the TEAM program of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Found, co-supported by Polish National Science Centre (2014/15/B/ST6/05082), and the grant 1U54DK107967-01 "Nucleome Positioning System for Spatiotemporal Genome Organization and Regulation" within 4D Nucleome NIH program.

Recent advances in high-throughput chromosome conformation capture (3C) technology, such as HiC and ChIA-PET, have demonstrated the importance of 3D genome organization in development, cell differentiation and transcriptional regulation. There is now a widespread need for computational tools to generate and analyze 3D structural models from 3C data. Here we introduce our 3D GeNOme Modeling Engine (3D-GNOME), a web service which generates 3D structures from 3C data and provides tools to visually inspect and annotate the resulting structures, in addition to a variety of statistical plots and heatmaps which characterize the selected genomic region. Users submit a bedpe (paired-end BED format) file containing the locations and strengths of long range contact points, and 3D-GNOME simulates the structure and provides a convenient user interface for further analysis. Alternatively, a user may generate structures using published ChIA-PET data for the GM12878 cell line by simply specifying a genomic region of interest. 3D-GNOME is freely available at http://3dgnome.cent.uw.edu.pl/. ; National Leading Research Centre in Bialystok [to P.S., D.P.]; European Union under the European Social Fund [to P.S., D.P.]; Polish National Science Centre [2014/15/B/ST6/05082, 2013/09/B/NZ2/00121 to D.P., G.M., P.W.]; European Cooperation in Science and Technology action [COST BM1405, BM1408 to D.P., G.M., P.W.]; Director Innovation Fund from Jackson Laboratory and NCI [R01 CA186714 to Y.R.]. Y.R. is also supported by the Roux family as a Florine Roux Endowed Chair and Professor in Genomics and Computational Biology. Funding for open access charge: Polish National Science Centre [2014/15/B/ST6/05082].

ChIA-PET is a high-throughput mapping technology that reveals long-range chromatin interactions and provides insights into the basic principles of spatial genome organization and gene regulation mediated by specific protein factors. Recently, we showed that a single ChIA-PET experiment provides information at all genomic scales of interest, from the high-resolution locations of binding sites and enriched chromatin interactions mediated by specific protein factors, to the low resolution of nonenriched interactions that reflect topological neighborhoods of higher-order chromosome folding. This multilevel nature of ChIA-PET data offers an opportunity to use multiscale 3D models to study structural-functional relationships at multiple length scales, but doing so requires a structural modeling platform. Here, we report the development of 3D-GNOME (3-Dimensional Genome Modeling Engine), a complete computational pipeline for 3D simulation using ChIA-PET data. 3D-GNOME consists of three integrated components: a graph-distance-based heat map normalization tool, a 3D modeling platform, and an interactive 3D visualization tool. Using ChIA-PET and Hi-C data derived from human B-lymphocytes, we demonstrate the effectiveness of 3D-GNOME in building 3D genome models at multiple levels, including the entire genome, individual chromosomes, and specific segments at megabase (Mb) and kilobase (kb) resolutions of single average and ensemble structures. Further incorporation of CTCF-motif orientation and high-resolution looping patterns in 3D simulation provided additional reliability of potential biologically plausible topological structures. ; D.P., P.S., M.S., and M.J.P. are supported by grants from the Polish National Science Centre (2014/15/B/ST6/05082 and 2013/09/B/ NZ2/00121), and the European Cooperation in Science and Technology action (COST BM1405 and BM1408). P.S. and D.P. are supported by funds from National Leading Research Centre in Bialystok and the European Union under the European Social Fund. Y.R. is supported by the Director Innovation Fund from the Jackson Laboratory and National Cancer Institute (NCI) grant R01 CA186714. Y.R. is also supported by the Roux family as a Florine Roux Endowed Chair and Professor in Genomics and Computational Biology. All authors were supported by National Institutes of Health grant 1U54DK107967-01, "Nucleome Positioning System for Spatiotemporal Genome Organization and Regulation," within the 4DNucleome NIH program.

The human genome contains many thousands of long noncoding RNAs (lncRNAs). While several studies have demonstrated compelling biological and disease roles for individual examples, analytical and experimental approaches to investigate these genes have been hampered by the lack of comprehensive lncRNA annotation. Here, we present and analyze the most complete human lncRNA annotation to date, produced by the GENCODE consortium within the framework of the ENCODE project and comprising 9277 manually annotated genes producing 14,880 transcripts. Our analyses indicate that lncRNAs are generated through pathways similar to that of protein-coding genes, with similar histone-modification profiles, splicing signals, and exon/intron lengths. In contrast to protein-coding genes, however, lncRNAs display a striking bias toward two-exon transcripts, they are predominantly localized in the chromatin and nucleus, and a fraction appear to be preferentially processed into small RNAs. They are under stronger selective pressure than neutrally evolving sequences-particularly in their promoter regions, which display levels of selection comparable to protein-coding genes. Importantly, about one-third seem to have arisen within the primate lineage. Comprehensive analysis of their expression in multiple human organs and brain regions shows that lncRNAs are generally lower expressed than protein-coding genes, and display more tissue-specific expression patterns, with a large fraction of tissue-specific lncRNAs expressed in the brain. Expression correlation analysis indicates that lncRNAs show particularly striking positive correlation with the expression of antisense coding genes. This GENCODE annotation represents a valuable resource for future studies of lncRNAs. ; This work has been carried out under grants RD07/0067/0012, BIO2006-03380, and CSD2007-00050 from the Spanish Ministry of Science, grant SGR-1430 from the Catalan Government, grants 1U54HG004557-01 and 1U54HG004555-01 from the National Institutes of Health, and INBISCIII from Instituto de Salud Carlos III and FEDER. This research project has been cofinanced by the European Commission, within the 7th Framework Programme, Grant Agreement KBBE-2A-222664 (''Quantomics''). C.N. is financed by the Plan Nacional BFU2008-00419. G.B. is supported by the La Caixa Ph.D. program