Introduction:Genome sequence plays an important role in both basic and applied studies.Gossypium raimondii,the putative contributor of the D subgenome of upland cotton(G.hirsutum,highlights the need to improve the gen...Introduction:Genome sequence plays an important role in both basic and applied studies.Gossypium raimondii,the putative contributor of the D subgenome of upland cotton(G.hirsutum,highlights the need to improve the genome quality rapidly and efficiently.Methods:We performed Hi-C sequencing of G.raimondii and reassembled its genome based on a set of new Hi-C data and previously published scaffolds.We also compared the reassembled genome sequenee with the previously published G raimondii genomes for gene and genome sequence collinearity.Result:A total of 9842%of scaffold sequences were clustered successfully,among which 99.72%of the clustered sequences were ordered and 99.92%of the ordered sequences were oriented with high-quality.Further evaluation of results by heat-map and collinearity analysis revealed that the current reassembled genome is significantly improved than the previous one(Nat Genet 44:98-1103,2012).Conclusion:This improvement in G raimondii genome not only provides a better reference to increase study efficiency but also offers a new way to assemble cotton genomes.Furthermore,Hi-C data of G.raimondii may be used for 3D structure research or regulating analysis.展开更多
Recent advances in high-throughput chromosome conformation capture(Hi-C)techniques have allowed us to map genome-wide chromatin interactions and uncover higher-order chromatin structures,thereby shedding light on the ...Recent advances in high-throughput chromosome conformation capture(Hi-C)techniques have allowed us to map genome-wide chromatin interactions and uncover higher-order chromatin structures,thereby shedding light on the principles of genome architecture and functions.However,statistical methods for detecting changes in large-scale chromatin organization such as topologically associating domains(TADs)are still lacking.Here,we proposed a new statistical method,DiffGR,for detecting differentially interacting genomic regions at the TAD level between Hi-C contact maps.We utilized the stratum-adjusted correlation coefficient to measure similarity of local TAD regions.We then developed a nonparametric approach to identify statistically significant changes of genomic interacting regions.Through simulation studies,we demonstrated that DiffGR can robustly and effectively discover differential genomic regions under various conditions.Furthermore,we successfully revealed cell type-specific changes in genomic interacting regions in both human and mouse Hi-C datasets,and illustrated that DiffGR yielded consistent and advantageous results compared with state-of-the-art differential TAD detection methods.The DiffGR R package is published under the GNU General Public License(GPL)≥2 license and is publicly available at https://github.com/wmalab/DiffGR.展开更多
Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells.However,high sequencing cost impedes the generation of biological Hi-C data with high sequencing dept...Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells.However,high sequencing cost impedes the generation of biological Hi-C data with high sequencing depths and multiple replicates for downstream analysis.Here,we developed a single-cell Hi-C simulator(scHi-CSim)that generates high-fidelity data for benchmarking.scHi-CSim merges neighboring cells to overcome the sparseness of data,samples interactions in distance-stratified chromosomes to maintain the heterogeneity of single cells,and estimates the empirical distribution of restriction fragments to generate simulated data.We demonstrated that scHi-CSim can generate high-fidelity data by comparing the performance of single-cell clustering and detection of chromosomal high-order structures with raw data.Furthermore,scHi-CSim is flexible to change sequencing depth and the number of simulated replicates.We showed that increasing sequencing depth could improve the accuracy of detecting topologically associating domains.We also used scHi-CSim to generate a series of simulated datasets with different sequencing depths to benchmark scHi-C clustering methods.展开更多
Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among thes...Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources(GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains(TADs). GITAR is composed of two main modules:(1)HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and(2)processed data library, a large collection of human and mouse datasets processed using HiCtool.HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.展开更多
Chromatins are not randomly packaged in the nucleus and their organization plays important roles in transcription regulation,which is best studied in the mammalian models.Using in situ Hi-C,we have compared the 3D chr...Chromatins are not randomly packaged in the nucleus and their organization plays important roles in transcription regulation,which is best studied in the mammalian models.Using in situ Hi-C,we have compared the 3D chromatin architectures of rice mesophyll and endosperm,foxtail millet bundle sheath and mesophyll,and maize bundle sheath,mesophyll and endosperm tissues.We found that their global A/B compartment partitions are stable across tissues,while local A/B compartment has tissue-specific dynamic associated with differential gene expression.Plant domains are largely stable across tissues,while new domain border formations are often associated with transcriptional activation in the region.Genes inside plant domains are not conserved across species,and lack significant co-expression behavior unlike those in mammalian TADs.Although we only observed chromatin loops between gene islands in the large genomes,the maize loop gene pairs’syntenic orthologs have shorter physical distances in small genome monocots,suggesting that loops instead of domains might have conserved biological function.Our study showed that plants’chromatin features might not have conserved biological functions as the mammalian ones.展开更多
Background： Although significant progress has been made to map chromatin structure at unprecedented resolution and scales, we are short of tools that enable the intuitive visualization and navigation along the three-...Background： Although significant progress has been made to map chromatin structure at unprecedented resolution and scales, we are short of tools that enable the intuitive visualization and navigation along the three-dimensional （3D） structure of chromatins. The available tools people have so far are generally script-based or present basic features that do not easily enable the integration of genomic data along with 3D chromatin structure, hence, many scientists find themselves in the obligation to hack tools designed for other purposes such as tools for protein structure study. Methods： We present HiC-3DViewer, a new browser-based interactive tool designed to provide an intuitive environment for investigators to facilitate the 3D exploratory analysis of Hi-C data along with many useful annotation functionalities. Among the key features of HiC-3DViewer relevant to chromatin conformation studies, the most important one is the 1D-to-2D-to-3D mapping, to highlight genomic regions of interest interactively. This feature enables investigators to explore their data at different levels/angels. Additionally, investigators can superpose different genomic signals （such as ChIP-Seq, SNP） on the top of the 3D structure. Results： As a proof of principle we applied HiC-3DViewer to investigate the quality of Hi-C data and to show the spatial binding of GATA1 and GATA2 along the genome. Conclusions： As a user-friendly tool, HiC-3DViewer enables the visualization of inter/intra-chromatin interactions and gives users the flexibility to customize the look-and-feel of the 3D structure with a simple click. HiC-3DViewer is implemented in Javascript and Python, and is freely available at： http：//bioinfo.au.tsinghua.edu.cn/member/nadhir/ HiC3DViewer/. Supplementary information （User Manual, demo data） is also available at this website.展开更多
文摘Introduction:Genome sequence plays an important role in both basic and applied studies.Gossypium raimondii,the putative contributor of the D subgenome of upland cotton(G.hirsutum,highlights the need to improve the genome quality rapidly and efficiently.Methods:We performed Hi-C sequencing of G.raimondii and reassembled its genome based on a set of new Hi-C data and previously published scaffolds.We also compared the reassembled genome sequenee with the previously published G raimondii genomes for gene and genome sequence collinearity.Result:A total of 9842%of scaffold sequences were clustered successfully,among which 99.72%of the clustered sequences were ordered and 99.92%of the ordered sequences were oriented with high-quality.Further evaluation of results by heat-map and collinearity analysis revealed that the current reassembled genome is significantly improved than the previous one(Nat Genet 44:98-1103,2012).Conclusion:This improvement in G raimondii genome not only provides a better reference to increase study efficiency but also offers a new way to assemble cotton genomes.Furthermore,Hi-C data of G.raimondii may be used for 3D structure research or regulating analysis.
基金supported by the National Science Foundation,USA(Grant No.DBI-1751317)the National Institute of Health,USA(Grant No.R35GM133678).
文摘Recent advances in high-throughput chromosome conformation capture(Hi-C)techniques have allowed us to map genome-wide chromatin interactions and uncover higher-order chromatin structures,thereby shedding light on the principles of genome architecture and functions.However,statistical methods for detecting changes in large-scale chromatin organization such as topologically associating domains(TADs)are still lacking.Here,we proposed a new statistical method,DiffGR,for detecting differentially interacting genomic regions at the TAD level between Hi-C contact maps.We utilized the stratum-adjusted correlation coefficient to measure similarity of local TAD regions.We then developed a nonparametric approach to identify statistically significant changes of genomic interacting regions.Through simulation studies,we demonstrated that DiffGR can robustly and effectively discover differential genomic regions under various conditions.Furthermore,we successfully revealed cell type-specific changes in genomic interacting regions in both human and mouse Hi-C datasets,and illustrated that DiffGR yielded consistent and advantageous results compared with state-of-the-art differential TAD detection methods.The DiffGR R package is published under the GNU General Public License(GPL)≥2 license and is publicly available at https://github.com/wmalab/DiffGR.
基金supported by the National Natural Science Foundation of China(61873198 and 62132015 to L.G.,62002275 to Y.Y.,and 61621003 to S.Z.)the National Key ResearchandDevelopment ProgramoCf hina(2019YFA0709501)+1 种基金the Strategic Priority Research Program of the Chinese Academy of Sciences(XDA16021400 and XDPB17 to S.z.)the Key-Area Research and Development of Guangdong Province(2020B1111190001).
文摘Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells.However,high sequencing cost impedes the generation of biological Hi-C data with high sequencing depths and multiple replicates for downstream analysis.Here,we developed a single-cell Hi-C simulator(scHi-CSim)that generates high-fidelity data for benchmarking.scHi-CSim merges neighboring cells to overcome the sparseness of data,samples interactions in distance-stratified chromosomes to maintain the heterogeneity of single cells,and estimates the empirical distribution of restriction fragments to generate simulated data.We demonstrated that scHi-CSim can generate high-fidelity data by comparing the performance of single-cell clustering and detection of chromosomal high-order structures with raw data.Furthermore,scHi-CSim is flexible to change sequencing depth and the number of simulated replicates.We showed that increasing sequencing depth could improve the accuracy of detecting topologically associating domains.We also used scHi-CSim to generate a series of simulated datasets with different sequencing depths to benchmark scHi-C clustering methods.
基金supported by the National Institutes of Health,United States(Grant Nos.U01CA200147 and DP1HD087990)awarded to SZ
文摘Interactions between chromatin segments play a large role in functional genomic assays and developments in genomic interaction detection methods have shown interacting topological domains within the genome. Among these methods, Hi-C plays a key role. Here, we present the Genome Interaction Tools and Resources(GITAR), a software to perform a comprehensive Hi-C data analysis, including data preprocessing, normalization, and visualization, as well as analysis of topologically-associated domains(TADs). GITAR is composed of two main modules:(1)HiCtool, a Python library to process and visualize Hi-C data, including TAD analysis; and(2)processed data library, a large collection of human and mouse datasets processed using HiCtool.HiCtool leads the user step-by-step through a pipeline, which goes from the raw Hi-C data to the computation, visualization, and optimized storage of intra-chromosomal contact matrices and TAD coordinates. A large collection of standardized processed data allows the users to compare different datasets in a consistent way, while saving time to obtain data for visualization or additional analyses. More importantly, GITAR enables users without any programming or bioinformatic expertise to work with Hi-C data. GITAR is publicly available at http://genomegitar.org as an open-source software.
基金supported by National Key Research and Development Program of China 2016YFD0101003NSFC 91435108+2 种基金Hong Kong UGC GRF 14104515 and 14108117Area of Excellence Scheme(AoE/M-403/16)the Taishan Pandeng program.
文摘Chromatins are not randomly packaged in the nucleus and their organization plays important roles in transcription regulation,which is best studied in the mammalian models.Using in situ Hi-C,we have compared the 3D chromatin architectures of rice mesophyll and endosperm,foxtail millet bundle sheath and mesophyll,and maize bundle sheath,mesophyll and endosperm tissues.We found that their global A/B compartment partitions are stable across tissues,while local A/B compartment has tissue-specific dynamic associated with differential gene expression.Plant domains are largely stable across tissues,while new domain border formations are often associated with transcriptional activation in the region.Genes inside plant domains are not conserved across species,and lack significant co-expression behavior unlike those in mammalian TADs.Although we only observed chromatin loops between gene islands in the large genomes,the maize loop gene pairs’syntenic orthologs have shorter physical distances in small genome monocots,suggesting that loops instead of domains might have conserved biological function.Our study showed that plants’chromatin features might not have conserved biological functions as the mammalian ones.
文摘Background： Although significant progress has been made to map chromatin structure at unprecedented resolution and scales, we are short of tools that enable the intuitive visualization and navigation along the three-dimensional （3D） structure of chromatins. The available tools people have so far are generally script-based or present basic features that do not easily enable the integration of genomic data along with 3D chromatin structure, hence, many scientists find themselves in the obligation to hack tools designed for other purposes such as tools for protein structure study. Methods： We present HiC-3DViewer, a new browser-based interactive tool designed to provide an intuitive environment for investigators to facilitate the 3D exploratory analysis of Hi-C data along with many useful annotation functionalities. Among the key features of HiC-3DViewer relevant to chromatin conformation studies, the most important one is the 1D-to-2D-to-3D mapping, to highlight genomic regions of interest interactively. This feature enables investigators to explore their data at different levels/angels. Additionally, investigators can superpose different genomic signals （such as ChIP-Seq, SNP） on the top of the 3D structure. Results： As a proof of principle we applied HiC-3DViewer to investigate the quality of Hi-C data and to show the spatial binding of GATA1 and GATA2 along the genome. Conclusions： As a user-friendly tool, HiC-3DViewer enables the visualization of inter/intra-chromatin interactions and gives users the flexibility to customize the look-and-feel of the 3D structure with a simple click. HiC-3DViewer is implemented in Javascript and Python, and is freely available at： http：//bioinfo.au.tsinghua.edu.cn/member/nadhir/ HiC3DViewer/. Supplementary information （User Manual, demo data） is also available at this website.
