1
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Kose C, Lindsey-Boltz LA, Sancar A, Jiang Y. Genome-wide analysis of transcription-coupled repair reveals novel transcription events in Caenorhabditis elegans. PLoS Genet 2024; 20:e1011365. [PMID: 39028758 PMCID: PMC11290646 DOI: 10.1371/journal.pgen.1011365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 07/31/2024] [Accepted: 07/08/2024] [Indexed: 07/21/2024] Open
Abstract
Bulky DNA adducts such as those induced by ultraviolet light are removed from the genomes of multicellular organisms by nucleotide excision repair, which occurs through two distinct mechanisms, global repair, requiring the DNA damage recognition-factor XPC (xeroderma pigmentosum complementation group C), and transcription-coupled repair (TCR), which does not. TCR is initiated when elongating RNA polymerase II encounters DNA damage, and thus analysis of genome-wide excision repair in XPC-mutants only repairing by TCR provides a unique opportunity to map transcription events missed by methods dependent on capturing RNA transcription products and thus limited by their stability and/or modifications (5'-capping or 3'-polyadenylation). Here, we have performed eXcision Repair-sequencing (XR-seq) in the model organism Caenorhabditis elegans to generate genome-wide repair maps in a wild-type strain with normal excision repair, a strain lacking TCR (csb-1), and a strain that only repairs by TCR (xpc-1). Analysis of the intersections between the xpc-1 XR-seq repair maps with RNA-mapping datasets (RNA-seq, long- and short-capped RNA-seq) reveal previously unrecognized sites of transcription and further enhance our understanding of the genome of this important model organism.
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Affiliation(s)
- Cansu Kose
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
| | - Laura A. Lindsey-Boltz
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
| | - Aziz Sancar
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, North Carolina, United States of America
| | - Yuchao Jiang
- Department of Statistics, College of Arts and Sciences, Texas A&M University, College Station, Texas, United States of America
- Department of Biology, College of Arts and Sciences, Texas A&M University, College Station, Texas, United States of America
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, Texas, United States of America
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2
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Wang C, Chen C, Lei B, Qin S, Zhang Y, Li K, Zhang S, Liu Y. Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs. Genet Sel Evol 2024; 56:28. [PMID: 38594607 PMCID: PMC11003151 DOI: 10.1186/s12711-024-00897-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 04/03/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking. RESULTS Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model. CONCLUSIONS Our work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.
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Affiliation(s)
- Chao Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Choulin Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Bowen Lei
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Shenghua Qin
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
| | - Yuanyuan Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- School of Life Sciences, Henan University, Kaifeng, 475004, People's Republic of China
- Shenzhen Research Institute of Henan University, Shenzhen, 518000, People's Republic of China
| | - Kui Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
| | - Song Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China.
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan, 528226, People's Republic of China.
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3
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Walter NG. Are non-protein coding RNAs junk or treasure?: An attempt to explain and reconcile opposing viewpoints of whether the human genome is mostly transcribed into non-functional or functional RNAs. Bioessays 2024; 46:e2300201. [PMID: 38351661 DOI: 10.1002/bies.202300201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/18/2024] [Accepted: 01/19/2024] [Indexed: 03/28/2024]
Abstract
The human genome project's lasting legacies are the emerging insights into human physiology and disease, and the ascendance of biology as the dominant science of the 21st century. Sequencing revealed that >90% of the human genome is not coding for proteins, as originally thought, but rather is overwhelmingly transcribed into non-protein coding, or non-coding, RNAs (ncRNAs). This discovery initially led to the hypothesis that most genomic DNA is "junk", a term still championed by some geneticists and evolutionary biologists. In contrast, molecular biologists and biochemists studying the vast number of transcripts produced from most of this genome "junk" often surmise that these ncRNAs have biological significance. What gives? This essay contrasts the two opposing, extant viewpoints, aiming to explain their bases, which arise from distinct reference frames of the underlying scientific disciplines. Finally, it aims to reconcile these divergent mindsets in hopes of stimulating synergy between scientific fields.
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Affiliation(s)
- Nils G Walter
- Center for RNA Biomedicine, Single Molecule Analysis Group, Department of Chemistry, University of Michigan, Ann Arbor, Michigan, USA
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4
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Kose C, Lindsey-Boltz LA, Sancar A, Jiang Y. Genome-wide analysis of transcription-coupled repair reveals novel transcription events in Caenorhabditis elegans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.12.562083. [PMID: 37904932 PMCID: PMC10614815 DOI: 10.1101/2023.10.12.562083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
Bulky DNA adducts such as those induced by ultraviolet light are removed from the genomes of multicellular organisms by nucleotide excision repair, which occurs through two distinct mechanisms, global repair, requiring the DNA damage recognition-factor XPC (xeroderma pigmentosum complementation group C), and transcription-coupled repair (TCR), which does not. TCR is initiated when elongating RNA polymerase II encounters DNA damage, and thus analysis of genome-wide excision repair in XPC-mutants only repairing by TCR provides a unique opportunity to map transcription events missed by methods dependent on capturing RNA transcription products and thus limited by their stability and/or modifications (5'-capping or 3'-polyadenylation). Here, we have performed the eXcision Repair-sequencing (XR-seq) in the model organism Caenorhabditis elegans to generate genome-wide repair maps from a wild-type strain with normal excision repair, a strain lacking TCR (csb-1), or one that only repairs by TCR (xpc-1). Analysis of the intersections between the xpc-1 XR-seq repair maps with RNA-mapping datasets (RNA-seq, long- and short-capped RNA-seq) reveal previously unrecognized sites of transcription and further enhance our understanding of the genome of this important model organism.
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Affiliation(s)
- Cansu Kose
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Laura A. Lindsey-Boltz
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Aziz Sancar
- Department of Biochemistry and Biophysics, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Yuchao Jiang
- Department of Statistics, College of Arts and Sciences, Texas A&M University, College Station, TX 77843, USA
- Department of Biology, College of Arts and Sciences, Texas A&M University, College Station, TX 77843
- Department of Biomedical Engineering, College of Engineering, Texas A&M University, College Station, TX 77843
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5
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Wang Y, Jin W, Pan X, Liao W, Shen Q, Cai J, Gong W, Tian Y, Xu D, Li Y, Li J, Gong J, Zhang Z, Yuan X. Pig-eRNAdb: a comprehensive enhancer and eRNA dataset of pigs. Sci Data 2024; 11:157. [PMID: 38302497 PMCID: PMC10834423 DOI: 10.1038/s41597-024-02960-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Accepted: 01/11/2024] [Indexed: 02/03/2024] Open
Abstract
Enhancers and the enhancer RNAs (eRNAs) have been strongly implicated in regulations of transcriptions. Based the multi-omics data (ATAC-seq, ChIP-seq and RNA-seq) from public databases, Pig-eRNAdb is a dataset that comprehensively integrates enhancers and eRNAs for pigs using the machine learning strategy, which incorporates 82,399 enhancers and 37,803 eRNAs from 607 samples across 15 tissues of pigs. This user-friendly dataset covers a comprehensive depth of enhancers and eRNAs annotation for pigs. The coordinates of enhancers and the expression patterns of eRNAs are downloadable. Besides, thousands of regulators on eRNAs, the target genes of eRNAs, the tissue-specific eRNAs, and the housekeeping eRNAs are also accessible as well as the sequence similarity of eRNAs with humans. Moreover, the tissue-specific eRNA-trait associations encompass 652 traits are also provided. It will crucially facilitate investigations on enhancers and eRNAs with Pig-eRNAdb as a reference dataset in pigs.
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Affiliation(s)
- Yifei Wang
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Weiwei Jin
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Xiangchun Pan
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Weili Liao
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Qingpeng Shen
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jiali Cai
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Wentao Gong
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yuhan Tian
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Dantong Xu
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Yipeng Li
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jiaqi Li
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China
| | - Jing Gong
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Zhe Zhang
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
| | - Xiaolong Yuan
- Guangdong Provincial Key Laboratory of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, National Engineering Research Center for Breeding Swine Industry, State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science, South China Agricultural University, Guangzhou, 510642, China.
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6
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Song C, Zhang G, Mu X, Feng C, Zhang Q, Song S, Zhang Y, Yin M, Zhang H, Tang H, Li C. eRNAbase: a comprehensive database for decoding the regulatory eRNAs in human and mouse. Nucleic Acids Res 2024; 52:D81-D91. [PMID: 37889077 PMCID: PMC10767853 DOI: 10.1093/nar/gkad925] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/26/2023] [Accepted: 10/12/2023] [Indexed: 10/28/2023] Open
Abstract
Enhancer RNAs (eRNAs) transcribed from distal active enhancers serve as key regulators in gene transcriptional regulation. The accumulation of eRNAs from multiple sequencing assays has led to an urgent need to comprehensively collect and process these data to illustrate the regulatory landscape of eRNAs. To address this need, we developed the eRNAbase (http://bio.liclab.net/eRNAbase/index.php) to store the massive available resources of human and mouse eRNAs and provide comprehensive annotation and analyses for eRNAs. The current version of eRNAbase cataloged 10 399 928 eRNAs from 1012 samples, including 858 human samples and 154 mouse samples. These eRNAs were first identified and uniformly processed from 14 eRNA-related experiment types manually collected from GEO/SRA and ENCODE. Importantly, the eRNAbase provides detailed and abundant (epi)genetic annotations in eRNA regions, such as super enhancers, enhancers, common single nucleotide polymorphisms, expression quantitative trait loci, transcription factor binding sites, CRISPR/Cas9 target sites, DNase I hypersensitivity sites, chromatin accessibility regions, methylation sites, chromatin interactions regions, topologically associating domains and RNA spatial interactions. Furthermore, the eRNAbase provides users with three novel analyses including eRNA-mediated pathway regulatory analysis, eRNA-based variation interpretation analysis and eRNA-mediated TF-target gene analysis. Hence, eRNAbase is a powerful platform to query, browse and visualize regulatory cues associated with eRNAs.
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Affiliation(s)
- Chao Song
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Guorui Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Xinxin Mu
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Chenchen Feng
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
| | - Qinyi Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Shuang Song
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Yuexin Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Mingxue Yin
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Cell Biology and Genetics, School of Basic Medical Sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Hang Zhang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
| | - Huifang Tang
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
- The First Affiliated Hospital, Cardiovascular Lab of Big Data and Imaging Artificial Intelligence, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Institute of Cardiovascular Disease, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Clinical Research Center for Myocardial Injury in Hunan Province, Hengyang, Hunan, 421001, China
| | - Chunquan Li
- The First Affiliated Hospital & Hunan Provincial Key Laboratory of Multi-omics And Artificial Intelligence of Cardiovascular Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences & MOE Key Lab of Rare Pediatric Diseases, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- Hunan Provincial Maternal and Child Health Care Hospital, National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China
- School of Computer, University of South China, Hengyang, Hunan, 421001, China
- The First Affiliated Hospital, Department of Cardiology, Hengyang Medical School, University of South China, Hengyang, China
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7
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Chen Y, Wang X, Xiao B, Luo Z, Long H. Mechanisms and Functions of Activity-Regulated Cytoskeleton-Associated Protein in Synaptic Plasticity. Mol Neurobiol 2023; 60:5738-5754. [PMID: 37338805 DOI: 10.1007/s12035-023-03442-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/10/2023] [Indexed: 06/21/2023]
Abstract
Activity-regulated cytoskeleton-associated protein (Arc) is one of the most important regulators of cognitive functions in the brain regions. As a hub protein, Arc plays different roles in modulating synaptic plasticity. Arc supports the maintenance of long-term potentiation (LTP) by regulating actin cytoskeletal dynamics, while it guides the endocytosis of AMPAR in long-term depression (LTD). Moreover, Arc can self-assemble into capsids, leading to a new way of communicating among neurons. The transcription and translation of the immediate early gene Arc are rigorous procedures guided by numerous factors, and RNA polymerase II (Pol II) is considered to regulate the precise timing dynamics of gene expression. Since astrocytes can secrete brain-derived neurotrophic factor (BDNF) and L-lactate, their unique roles in Arc expression are emphasized. Here, we review the entire process of Arc expression and summarize the factors that can affect Arc expression and function, including noncoding RNAs, transcription factors, and posttranscriptional regulations. We also attempt to review the functional states and mechanisms of Arc in modulating synaptic plasticity. Furthermore, we discuss the recent progress in understanding the roles of Arc in the occurrence of major neurological disorders and provide new thoughts for future research on Arc.
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Affiliation(s)
- Yifan Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Xiangya School of Stomatology, Central South University, Changsha, 410008, Hunan, China
| | - Xiaohu Wang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bo Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, Hunan, People's Republic of China, 410008
| | - Zhaohui Luo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, Hunan, People's Republic of China, 410008.
| | - Hongyu Long
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
- Clinical Research Center for Epileptic Disease of Hunan Province, Central South University, Changsha, Hunan, People's Republic of China, 410008.
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8
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Wang Z, Ge P, Zhou XL, Shui KM, Geng H, Yang J, Chen JY, Wang J. nASAP: A Nascent RNA Profiling Data Analysis Platform. J Mol Biol 2023; 435:168142. [PMID: 37356907 DOI: 10.1016/j.jmb.2023.168142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/19/2023] [Accepted: 04/30/2023] [Indexed: 06/27/2023]
Abstract
Although nascent RNA profiling data are widely used in transcriptional regulation studies, the development and standardization of data processing pipeline lags far behind RNA-seq. We are filling this gap by establishing the nASAP web server (https://grobase.top/nasap/) to provide practical quality evaluation and comprehensive analysis of nascent RNA datasets. In nASAP, four customized analysis modules are provided, including i) quality assessment, which summarizes the sequencing statistics, mapping ratio, and evaluates RNA integrity and mRNA contamination; ii) quantification analysis for mRNAs, lncRNAs and eRNAs; iii) pausing analysis across the whole genome based on sequencing reads distribution; and iv) network analysis to better understand the gene regulatory mechanism by obtaining annotated enhancer-promoter interactomes. The nASAP is user-friendly and outperforms the existing pipeline for quality control of nascent RNA profiling data. We anticipate that nASAP, which eases both basic and advanced analysis of nascent RNA data, will be extremely useful in various fields.
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Affiliation(s)
- Zhi Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Peng Ge
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Xiao-Long Zhou
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China
| | - Kun-Ming Shui
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210023, China
| | - Huichao Geng
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210023, China
| | - Jie Yang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China.
| | - Jia-Yu Chen
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China; Chemistry and Biomedicine Innovation Center (ChemBIC), Nanjing University, Nanjing 210023, China.
| | - Jin Wang
- State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing 210023, China; NJU Advanced Institute for Life Sciences (NAILS), Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Nanjing University, Nanjing 210023, China.
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9
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Stefos GC, Theodorou G, Politis I. Genomic distribution and polymorphism of G-quadruplex motifs occupying ovine promoters and enhancers. Mamm Genome 2023:10.1007/s00335-023-09988-x. [PMID: 36964238 PMCID: PMC10382345 DOI: 10.1007/s00335-023-09988-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 03/10/2023] [Indexed: 03/26/2023]
Abstract
G-quadruplexes are non-canonical DNA structures that are formed in regions with short runs of guanines. During the last decade they have gained considerable attention due to their involvement in basic cellular processes, linking them to several physiological processes and pathological conditions. Regulation of gene transcription is among the crucial roles that G-quadruplexes play in the cells. Several ways in which these structures affect transcription have been described, both negatively and positively. Recently, G-quadruplexes have been shown to be implicated in the three-dimensional rearrangement of the chromosomes that enables the interaction of enhancers and gene promoters during regulation of transcription. Sheep is a species for which almost no G-quadruplex-related studies have been conducted and thus research on this species is kept out from the progress that has been made in the G-quadruplex field. In this context, we investigated the DNA sequences with potential to form G-quadruplexes (G4-motifs) in the ovine enhancers and promoters. We describe the distribution of G4-motifs within the regulatory regions which is shown to be enriched in G4-motifs in a way similar to other mammals. Furthermore, our data suggest that G4-motifs promote promoter-enhancer interactions in sheep. The single nucleotide polymorphisms colocalizing with promoter- and enhancer-associated ovine G4-motifs constitute a considerable pool of polymorphism and given the crucial role of these specific G4-motifs on regulation of transcription, we suggest this polymorphism as an interesting target for ovine genetic studies.
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Affiliation(s)
- Georgios C Stefos
- Laboratory of Animal Breeding and Husbandry, Department of Animal Science, Agricultural University of Athens, 75 Iera Odos, 118 55, Athens, Greece.
| | - Georgios Theodorou
- Laboratory of Animal Breeding and Husbandry, Department of Animal Science, Agricultural University of Athens, 75 Iera Odos, 118 55, Athens, Greece.
| | - Ioannis Politis
- Laboratory of Animal Breeding and Husbandry, Department of Animal Science, Agricultural University of Athens, 75 Iera Odos, 118 55, Athens, Greece
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10
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Fu Y, Liu H, Dou J, Wang Y, Liao Y, Huang X, Tang Z, Xu J, Yin D, Zhu S, Liu Y, Shen X, Liu H, Liu J, Yang X, Zhang Y, Xiang Y, Li J, Zheng Z, Zhao Y, Ma Y, Wang H, Du X, Xie S, Xu X, Zhang H, Yin L, Zhu M, Yu M, Li X, Liu X, Zhao S. IAnimal: a cross-species omics knowledgebase for animals. Nucleic Acids Res 2022; 51:D1312-D1324. [PMID: 36300629 PMCID: PMC9825575 DOI: 10.1093/nar/gkac936] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/23/2022] [Accepted: 10/11/2022] [Indexed: 01/30/2023] Open
Abstract
With the exponential growth of multi-omics data, its integration and utilization have brought unprecedented opportunities for the interpretation of gene regulation mechanisms and the comprehensive analyses of biological systems. IAnimal (https://ianimal.pro/), a cross-species, multi-omics knowledgebase, was developed to improve the utilization of massive public data and simplify the integration of multi-omics information to mine the genetic mechanisms of objective traits. Currently, IAnimal provides 61 191 individual omics data of genome (WGS), transcriptome (RNA-Seq), epigenome (ChIP-Seq, ATAC-Seq) and genome annotation information for 21 species, such as mice, pigs, cattle, chickens, and macaques. The scale of its total clean data has reached 846.46 TB. To better understand the biological significance of omics information, a deep learning model for IAnimal was built based on BioBERT and AutoNER to mine 'gene' and 'trait' entities from 2 794 237 abstracts, which has practical significance for comprehending how each omics layer regulates genes to affect traits. By means of user-friendly web interfaces, flexible data application programming interfaces, and abundant functional modules, IAnimal enables users to easily query, mine, and visualize characteristics in various omics, and to infer how genes play biological roles under the influence of various omics layers.
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Affiliation(s)
- Yuhua Fu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Hong Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Jingwen Dou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Yue Wang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Yong Liao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Xin Huang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Zhenshuang Tang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - JingYa Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Dong Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Shilin Zhu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Yangfan Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Xiong Shen
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Hengyi Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Jiaqi Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Xin Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Yi Zhang
- School of Computer Science and Technology, Wuhan University of Technology, Wuhan, Hubei 430070, PR China
| | - Yue Xiang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Jingjin Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Zhuqing Zheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China
| | - Yunxia Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Yunlong Ma
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Haiyan Wang
- Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Xiaoyong Du
- Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Shengsong Xie
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Xuewen Xu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Haohao Zhang
- School of Computer Science and Technology, Wuhan University of Technology, Wuhan, Hubei 430070, PR China
| | - Lilin Yin
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Mengjin Zhu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Mei Yu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Xinyun Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, Key Laboratory of Swine Genetics and Breeding, Ministry of Agriculture, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei 430070, PR China,Frontiers Science Center for Animal Breeding and Sustainable Production, Wuhan, Hubei 430070, PR China
| | - Xiaolei Liu
- Correspondence may also be addressed to Xiaolei Liu.
| | - Shuhong Zhao
- To whom correspondence should be addressed. Tel: +86 27 87387480;
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11
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Gao Y, Jiang G, Yang W, Jin W, Gong J, Xu X, Niu X. Animal-SNPAtlas: a comprehensive SNP database for multiple animals. Nucleic Acids Res 2022; 51:D816-D826. [PMID: 36300636 PMCID: PMC9825464 DOI: 10.1093/nar/gkac954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 10/06/2022] [Accepted: 10/26/2022] [Indexed: 01/30/2023] Open
Abstract
Single-nucleotide polymorphisms (SNPs) as the most important type of genetic variation are widely used in describing population characteristics and play vital roles in animal genetics and breeding. Large amounts of population genetic variation resources and tools have been developed in human, which provided solid support for human genetic studies. However, compared with human, the development of animal genetic variation databases was relatively slow, which limits the genetic researches in these animals. To fill this gap, we systematically identified ∼ 499 million high-quality SNPs from 4784 samples of 20 types of animals. On that basis, we annotated the functions of SNPs, constructed high-density reference panels and calculated genome-wide linkage disequilibrium (LD) matrixes. We further developed Animal-SNPAtlas, a user-friendly database (http://gong_lab.hzau.edu.cn/Animal_SNPAtlas/) which includes high-quality SNP datasets and several support tools for multiple animals. In Animal-SNPAtlas, users can search the functional annotation of SNPs, perform online genotype imputation, explore and visualize LD information, browse variant information using the genome browser and download SNP datasets for each species. With the massive SNP datasets and useful tools, Animal-SNPAtlas will be an important fundamental resource for the animal genomics, genetics and breeding community.
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Affiliation(s)
| | | | - Wenqian Yang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P. R. China
| | - Weiwei Jin
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P. R. China
| | - Jing Gong
- To whom correspondence should be addressed. Tel: +86 27 87285085; Fax: +86 27 87285085;
| | - Xuewen Xu
- Correspondence may also be addressed to Xuewen Xu. Tel: +86 27 87285085; Fax: +86 27 87285085;
| | - Xiaohui Niu
- Correspondence may also be addressed to Xiaohui Niu. Tel: +86 27 87285085; Fax: +86 27 87285085;
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12
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Hu X, Wu L, Yao Y, Ma J, Li X, Shen H, Liu L, Dai H, Wang W, Chu X, Sheng C, Yang M, Zheng H, Song F, Chen K, Liu B. The integrated landscape of eRNA in gastric cancer reveals distinct immune subtypes with prognostic and therapeutic relevance. iScience 2022; 25:105075. [PMID: 36157578 PMCID: PMC9490034 DOI: 10.1016/j.isci.2022.105075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 06/09/2022] [Accepted: 08/31/2022] [Indexed: 12/24/2022] Open
Abstract
The comprehensive regulation effect of eRNA on tumor immune cell infiltration and the outcome remains obscure. We comprehensively identify the eRNA-mediated immune infiltration patterns of gastric cancer (GC) samples. We creatively proposed a random forest machine-learning (ML) algorithm to map eRNA to mRNA expression patterns. The eRNA score was constructed using principal component analysis algorithms and validated in an independent cohort. Three subtypes with distinct eRNA expression patterns were determined in GC. There were significant differences between the three subtypes in the overall survival rate, immune cell infiltration characteristics, and immunotherapy response indicators. The patients in the high eRNA score group have a higher overall survival rate and might benefit from immunotherapy. This work revealed that eRNA regulation might be a new prognostic index and might offer a potential biomarker in the response of immunotherapy. Evaluating the eRNA regulation manner of GC will contribute to guiding more effective immunotherapy strategies.
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Affiliation(s)
- Xin Hu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Liuxing Wu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Yanxin Yao
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Junfu Ma
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Xiangchun Li
- Tianjin Cancer Institute, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China
| | - Hongru Shen
- Tianjin Cancer Institute, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China
| | - Luyang Liu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Xinlei Chu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Chao Sheng
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Meng Yang
- Tianjin Cancer Institute, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University, Tianjin, China
| | - Hong Zheng
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
| | - Ben Liu
- Department of Epidemiology and Biostatistics, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Molecular Cancer Epidemiology, Tianjin 300060, China
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