{ "titles": [ "2020 - The Genomics of Auditory.pdf", "2016 - Genetics and Genomics of Coronary Artery Disease..pdf", "2021 - Interpreting type 1 diabetes risk.pdf", "2020 - Visualizing and interpreting cancer genomics.pdf", "2016 - Genetics and Genomics of Coronary Artery Disease..pdf", "2018 - High-Throughput Approaches onto Uncover (Epi)Genomic Architecture of Type 2 Diabetes.pdf", "2018 - Human Genetics of Obesity and Type 2 Diabetes Mellitus.pdf", "2022 - Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease.pdf", "2020 - Advances of single?cell genomics and epigenomics in human disease.pdf", "2021 - Moving from in vitro to in vivo CRISPR screens.pdf" ], "extraction_id": [ "0c7a27ef-7a65-5b32-8129-b168a336018a", "203710b7-3267-5ecf-9397-b5becdaeead1", "607a959f-6f63-5f18-8935-b76d87aa4820", "ffc72db8-67ea-508a-aba1-d2592bd00ea2", "2e588b06-841f-50d7-b161-330199d5c4cf", "9cd48835-a7bf-50aa-928f-adb817e229d4", "786d21d6-5544-5357-8163-1a1a96f6a791", "d26b98eb-66cc-5185-9061-cda1fe904ba6", "f740892a-7817-58b0-bec4-8648086b2353", "6078715b-9964-5922-8fc9-5f105d0001ca" ], "document_id": [ "f56b6ae4-e05a-5851-9c10-4bd62f237778", "23a1b7be-9541-5e16-b9cc-24ea420a4961", "9f13ec69-195b-55eb-a549-b3eb3dc0f321", "eaae9d37-9c40-5e1c-9de9-d5ebcce9eae3", "23a1b7be-9541-5e16-b9cc-24ea420a4961", "1cb0c4ac-c1fe-55c2-919c-52cd5018c00d", "2083de31-17c6-5d1e-9aa6-2efc6c1d9ac2", "b9194555-5fdb-549e-9edb-d108132a7dd1", "afe53f5a-3962-520f-be55-9df5bfdaad70", "31d137b9-90a3-5b5a-ba4f-7a4d5b2c61bc" ], "id": [ "chatcmpl-AIGs1N0h1lzkHw7McrwTnV7iXLWUI", "9172db35-cec2-5970-8e5d-d73357f13abe", "2020244c-6b6e-5613-900e-d7e32f6c4d57", "f4ae7779-bbfc-5a13-bcd2-2e6724011eb8", "1bdc47f8-9b31-5f89-8381-2238c4aec987", "6b16574f-b513-5361-a0a8-a19f86ef6316", "5297cd77-3ccf-570e-9ff9-bdb778638793", "a49d3e49-6005-5890-ba75-8e5d59df13e5", "eafc949f-7238-5776-bfef-5ccd9f91787e", "c93bf9e1-39bd-59a9-8dd1-1b67a0853b8c", "6442bc7c-4e2e-553f-82c4-b2f09e01823e" ], "contexts": [ "high-throughput sequencing (ATAC-seq) allows the characterization of accessible chromatin re- gions,whichcorrespondtoareasoftranscriptionactivity(149).Examiningthethree-dimensional organization of the genome can facilitate the association between regulatory elements and their target genes by dividing the genome into discrete functional blocks, commonly known as topologically associating domains (139). The Encyclopedia of DNA Elements (ENCODE) and", "variants, it is still unclear how multiple independent variants influence gene networks through changes in chromatin states. The Assay for Transpose Accessible Chromatin (ATAC-seq) was recently developed to address the need for sensitive as- says requiring less starting material, which also has the ability to simultaneously profile open chromatin, transcription factor- binding footprints, as well as nucleosome positioning in a single assay [ 57]. Given the limited availability of primary", "Data Fig.4a). To relate cell-type-resolved accessible chromatin to gene expression, we created a single-cell RNA sequencing (scRNA-seq) refer - ence map of peripheral blood and pancreas. We assigned cell-type identi - ties for 90,495 cells to 29 clusters, which identified similar cell types and proportions to snATACseq (Extended Data Fig.5ac). To characterize cis-regulatory programs, we aggregated reads from cells within each snATACseq cluster and identified accessible chroma -", "DNA methylation and ATAC-seq data (Supplementary Fig. 3). Integration across gene- and coordinate-centric views helps users examine genomic events in different chromosome contexts. For example, Xenas Visual Spreadsheet can help elucidate whether a gene amplification is part of a chromosomal arm duplication or a focal amplification (Supplementary Fig. 6).", "matin accessibility assay ATAC-seq has been applied to single cells and has been shown to capture a higher order chromatin structure resembling the profiles generated by Hi-C [ 72]. Additionally, for CAD candidate genes that are transcrip- tion factors (TF), such as TCF21 and STAT3, protein-DNA interactions could be studied on a genome-wide scale using chromatin immunoprecipitation sequencing (ChIP-Seq). Recently, ChIP-Seq performed against TCF21 in human cor-", "seq), Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), Formaldehyde- Assisted Isolation of Regulatory Elements (FAIRE-seq) and DNase I hypersensitive sites sequencing (DNase-seq). The integration of DNA methylation data (WGBS) and chromatin accessibility data (ATAC-seq) with established ChIP-seq mark ers have provided an opportunity to create high-resolution", "94. Mumbach MR, et al. HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat Methods. 2016;13:919922. doi: 10.1038/nmeth.3999. 95. Kumasaka N, et al. Fine-mapping cellular QTLs with RASQUAL and ATAC- seq. Nat Genet. 2016;48:206213. doi: 10.1038/ng.3467. 96. Buenrostro JD, et al. ATAC-seq: a method for assaying chromatin acces- sibility genome-wide. Curr Protoc Mol Biol. 2015;109:21.29.121.29.9. doi: 10.1002/0471142727.mb2129s109.", "CpG sites. Single nucleus Assay for Transposase-Accessible Chromatinusing sequencing (snATACseq) was informative of chromatin opennessin various kidney cell types. The RegulomeDB is a database with exten-sive epigenetic annotation for SNPs. The promoter capture HiC (PCHiC) sequencing data identified sequence interaction with gene promoters,", "a method for assaying chromatin accessibility genome-wide. Curr Protoc Mol Biol 109:21.29.2121.29.29. https ://doi.org/10.1002/04711 42727 .mb212 9s109 Bysani M etal (2019) ATAC-seq reveals alterations in open chromatin in pancreatic islets from subjects with type 2 diabetes. Sci Rep 9:7785. https ://doi.org/10.1038/s4159 8-019-44076 -8 Camp JG etal (2015) Human cerebral organoids recapitulate gene expression programs of fetal neocortex development. Proc Natl", "genes are involved with multiple biological features. RNA sequencing has been coupled with protein quantication (DNA barcoded antibodies to quantify protein expression) and ATAC-seq to facilitate the study of genes involved with chromatin accessibility remodeling. their environment [14 , 31 , 88 , 95 , 105] . Advances in multiplexed gene editing and transcriptional programing will also enable CRISPR screens" ], "answer": "The integration of ATAC-seq data with RNA-seq data can provide valuable insights into chromatin accessibility and gene regulation by combining information about open chromatin regions with gene expression profiles. ATAC-seq is a technique that characterizes accessible chromatin regions, which are often associated with transcriptional activity [1]. This method can simultaneously profile open chromatin, transcription factor-binding footprints, and nucleosome positioning [2]. By integrating this data with RNA-seq, which measures gene expression levels, researchers can relate chromatin accessibility to gene expression patterns. For example, by creating a reference map using single-cell RNA sequencing (scRNA-seq) and assigning cell-type identities, researchers can relate cell-type-resolved accessible chromatin to gene expression [3]. This integration helps in identifying cis-regulatory programs by aggregating reads from cells within each ATAC-seq cluster and linking them to gene expression data. Overall, the integration of ATAC-seq and RNA-seq data allows for a comprehensive understanding of how chromatin accessibility influences gene regulation, providing insights into the regulatory elements that control gene expression in different cellular contexts.", "question": "How can the integration of ATAC-seq data with RNA-seq data on GeneNetwork.org inform about chromatin accessibility and gene regulation?" }