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Carballo-Pacoret P, Carracedo A, Rodriguez-Fontenla C. Unraveling the three-dimensional (3D) genome architecture in Neurodevelopmental Disorders (NDDs). Neurogenetics 2024:10.1007/s10048-024-00774-8. [PMID: 39190242 DOI: 10.1007/s10048-024-00774-8] [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: 05/30/2024] [Accepted: 07/17/2024] [Indexed: 08/28/2024]
Abstract
The human genome, comprising millions of pairs of bases, serves as the blueprint of life, encoding instructions for cellular processes. However, genomes are not merely linear sequences; rather, the complex of DNA and histones, known as chromatin, exhibits complex organization across various levels, which profoundly influence gene expression and cellular function. Central to understanding genome organization is the emerging field of three-dimensional (3D) genome studies. Utilizing advanced techniques such as Hi-C, researchers have unveiled non-random dispositions of genomic elements, highlighting their importance in transcriptional regulation and disease mechanisms. Topologically Associating Domains (TADs), that demarcate regions of chromatin with preferential internal interactions, play crucial roles in gene regulation and are increasingly implicated in various diseases such as cancer and schizophrenia. However, their role in Neurodevelopmental Disorders (NDDs) remains poorly understood. Here, we focus on TADs and 3D conservation across the evolution and between cell types in NDDs. The investigation into genome organization and its impact on disease has led to significant breakthroughs in understanding NDDs etiology such ASD (Autism Spectrum Disorder). By elucidating the wide spectrum of ASD manifestations, researchers aim to uncover the underlying genetic and epigenetic factors contributing to its heterogeneity. Moreover, studies linking TAD disruption to NDDs underscore the importance of spatial genome organization in maintaining proper brain development and function. In summary, this review highlights the intricate interplay between genome organization, transcriptional control, and disease pathology, shedding light on fundamental biological processes and offering insights into the mechanisms underlying NDDs like ASD.
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Affiliation(s)
- P Carballo-Pacoret
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Av Barcelona 31, Santiago de Compostela A Coruña, 15706, Spain
- Grupo de Medicina Xenómica, Facultad de Medicina, Universidad de Santiago de Compostela, San Francisco s/n., Santiago de Compostela, 15782, Spain
| | - A Carracedo
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Av Barcelona 31, Santiago de Compostela A Coruña, 15706, Spain
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain
- Grupo de Medicina Xenómica, Facultad de Medicina, Universidad de Santiago de Compostela, San Francisco s/n., Santiago de Compostela, 15782, Spain
| | - C Rodriguez-Fontenla
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Universidad de Santiago de Compostela, Av Barcelona 31, Santiago de Compostela A Coruña, 15706, Spain.
- Grupo de Medicina Xenómica, Center for Research in Molecular Medicine and Chronic Diseases (CiMUS), Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Universidad de Santiago de Compostela, Santiago de Compostela, Spain.
- Grupo de Medicina Xenómica, Facultad de Medicina, Universidad de Santiago de Compostela, San Francisco s/n., Santiago de Compostela, 15782, Spain.
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2
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Bittner N, Shi C, Zhao D, Ding J, Southam L, Swift D, Kreitmaier P, Tutino M, Stergiou O, Cheung JTS, Katsoula G, Hankinson J, Wilkinson JM, Orozco G, Zeggini E. Primary osteoarthritis chondrocyte map of chromatin conformation reveals novel candidate effector genes. Ann Rheum Dis 2024; 83:1048-1059. [PMID: 38479789 PMCID: PMC11287644 DOI: 10.1136/ard-2023-224945] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Accepted: 02/29/2024] [Indexed: 07/17/2024]
Abstract
OBJECTIVES Osteoarthritis is a complex disease with a huge public health burden. Genome-wide association studies (GWAS) have identified hundreds of osteoarthritis-associated sequence variants, but the effector genes underpinning these signals remain largely elusive. Understanding chromosome organisation in three-dimensional (3D) space is essential for identifying long-range contacts between distant genomic features (e.g., between genes and regulatory elements), in a tissue-specific manner. Here, we generate the first whole genome chromosome conformation analysis (Hi-C) map of primary osteoarthritis chondrocytes and identify novel candidate effector genes for the disease. METHODS Primary chondrocytes collected from 8 patients with knee osteoarthritis underwent Hi-C analysis to link chromosomal structure to genomic sequence. The identified loops were then combined with osteoarthritis GWAS results and epigenomic data from primary knee osteoarthritis chondrocytes to identify variants involved in gene regulation via enhancer-promoter interactions. RESULTS We identified 345 genetic variants residing within chromatin loop anchors that are associated with 77 osteoarthritis GWAS signals. Ten of these variants reside directly in enhancer regions of 10 newly described active enhancer-promoter loops, identified with multiomics analysis of publicly available chromatin immunoprecipitation sequencing (ChIP-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) data from primary knee chondrocyte cells, pointing to two new candidate effector genes SPRY4 and PAPPA (pregnancy-associated plasma protein A) as well as further support for the gene SLC44A2 known to be involved in osteoarthritis. For example, PAPPA is directly associated with the turnover of insulin-like growth factor 1 (IGF-1) proteins, and IGF-1 is an important factor in the repair of damaged chondrocytes. CONCLUSIONS We have constructed the first Hi-C map of primary human chondrocytes and have made it available as a resource for the scientific community. By integrating 3D genomics with large-scale genetic association and epigenetic data, we identify novel candidate effector genes for osteoarthritis, which enhance our understanding of disease and can serve as putative high-value novel drug targets.
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Affiliation(s)
- Norbert Bittner
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | - Chenfu Shi
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Danyun Zhao
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - James Ding
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Lorraine Southam
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | - Diane Swift
- Department of Oncology and Metabolism, The University of Sheffield, Sheffield, UK
| | - Peter Kreitmaier
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
- Graduate School of Experimental Medicine, Technical University of Munich, München, Germany
- TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, München, Germany
| | - Mauro Tutino
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | - Odysseas Stergiou
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | | | - Georgia Katsoula
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
- Graduate School of Experimental Medicine, Technical University of Munich, München, Germany
- TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, München, Germany
| | - Jenny Hankinson
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
| | | | - Gisela Orozco
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Eleftheria Zeggini
- Institute of Translational Genomics, Helmholtz Zentrum München Deutsches Forschungszentrum für Gesundheit und Umwelt, Neuherberg, Germany
- TUM School of Medicine and Health, Technical University of Munich and Klinikum Rechts der Isar, München, Germany
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Jaso-Vera ME, Takaoka S, Patel I, Ruan X. Integrative regulation of hLMR1 by dietary and genetic factors in nonalcoholic fatty liver disease and hyperlipidemia. Hum Genet 2024; 143:897-906. [PMID: 38493444 DOI: 10.1007/s00439-024-02654-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 02/05/2024] [Indexed: 03/19/2024]
Abstract
Long non-coding RNA (lncRNA) genes represent a large class of transcripts that are widely expressed across species. As most human lncRNAs are non-conserved, we recently employed a unique humanized liver mouse model to study lncRNAs expressed in human livers. We identified a human hepatocyte-specific lncRNA, hLMR1 (human lncRNA metabolic regulator 1), which is induced by feeding and promotes hepatic cholesterol synthesis. Recent genome-wide association studies (GWAS) found that several single-nucleotide polymorphisms (SNPs) from the hLMR1 gene locus are associated with blood lipids and markers of liver damage. These results suggest that dietary and genetic factors may regulate hLMR1 to affect disease progression. In this study, we first screened for nutritional/hormonal factors and found that hLMR1 was robustly induced by insulin/glucose in cultured human hepatocytes, and this induction is dependent on the transcription factor SREBP1. We then tested if GWAS SNPs genetically linked to hLMR1 could regulate hLMR1 expression. We found that DNA sequences flanking rs9653945, a SNP from the last exon of the hLMR1 gene, functions as an enhancer that can be robustly activated by SREBP1c depending on the presence of rs9653945 major allele (G). We further performed CRISPR base editing in human HepG2 cells and found that rs9653945 major (G) to minor (A) allele modification resulted in blunted insulin/glucose-induced expression of hLMR1. Finally, we performed genotyping and gene expression analyses using a published human NAFLD RNA-seq dataset and found that individuals homozygous for rs9653945-G have a higher expression of hLMR1 and risk of NAFLD. Taken together, our data support a model that rs9653945-G predisposes individuals to insulin/glucose-induced hLMR1, contributing to the development of hyperlipidemia and NAFLD.
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Affiliation(s)
- Marcos E Jaso-Vera
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Institute for Fundamental Biomedical Research, Johns Hopkins All Childrens Hospital, 600 Fifth Street S., St. Petersburg, FL, 33701, USA
| | - Shohei Takaoka
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Institute for Fundamental Biomedical Research, Johns Hopkins All Childrens Hospital, 600 Fifth Street S., St. Petersburg, FL, 33701, USA
| | - Ishika Patel
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Institute for Fundamental Biomedical Research, Johns Hopkins All Childrens Hospital, 600 Fifth Street S., St. Petersburg, FL, 33701, USA
| | - Xiangbo Ruan
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- Institute for Fundamental Biomedical Research, Johns Hopkins All Childrens Hospital, 600 Fifth Street S., St. Petersburg, FL, 33701, USA.
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Reyna J, Fetter K, Ignacio R, Marandi CCA, Rao N, Jiang Z, Figueroa DS, Bhattacharyya S, Ay F. Loop Catalog: a comprehensive HiChIP database of human and mouse samples. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.26.591349. [PMID: 38746164 PMCID: PMC11092438 DOI: 10.1101/2024.04.26.591349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
HiChIP enables cost-effective and high-resolution profiling of regulatory and structural loops. To leverage the increasing number of publicly available HiChIP datasets from diverse cell lines and primary cells, we developed the Loop Catalog (https://loopcatalog.lji.org), a web-based database featuring HiChIP loop calls for 1319 samples across 133 studies and 44 high-resolution Hi-C loop calls. We demonstrate its utility in interpreting fine-mapped GWAS variants (SNP-to-gene linking), in identifying enriched sequence motifs and motif pairs at loop anchors, and in network-level analysis of loops connecting regulatory elements (community detection). Our comprehensive catalog, spanning over 4M unique 5kb loops, along with the accompanying analysis modalities constitutes an important resource for studies in gene regulation and genome organization.
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Affiliation(s)
- Joaquin Reyna
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Kyra Fetter
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093 USA
| | - Romeo Ignacio
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
| | - Cemil Can Ali Marandi
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Nikhil Rao
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA 92093 USA
| | - Zichen Jiang
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Department of Mathematics, University of California San Diego, La Jolla, CA 92093 USA
| | - Daniela Salgado Figueroa
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
| | - Sourya Bhattacharyya
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
| | - Ferhat Ay
- Centers for Cancer Immunotherapy and Autoimmunity, La Jolla Institute for Immunology, La Jolla, CA 92037 USA
- Bioinformatics and Systems Biology Graduate Program University of California, San Diego, La Jolla, CA 92093 USA
- Department of Pediatrics, University of California San Diego, La Jolla, CA 92093 USA
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Zhigulev A, Norberg Z, Cordier J, Spalinskas R, Bassereh H, Björn N, Pradhananga S, Gréen H, Sahlén P. Enhancer mutations modulate the severity of chemotherapy-induced myelosuppression. Life Sci Alliance 2024; 7:e202302244. [PMID: 38228368 PMCID: PMC10796589 DOI: 10.26508/lsa.202302244] [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: 06/30/2023] [Revised: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 01/18/2024] Open
Abstract
Non-small cell lung cancer is often diagnosed at advanced stages, and many patients are still treated with classical chemotherapy. The unselective nature of chemotherapy often results in severe myelosuppression. Previous studies showed that protein-coding mutations could not fully explain the predisposition to myelosuppression. Here, we investigate the possible role of enhancer mutations in myelosuppression susceptibility. We produced transcriptome and promoter-interaction maps (using HiCap) of three blood stem-like cell lines treated with carboplatin or gemcitabine. Taking advantage of publicly available enhancer datasets, we validated HiCap results in silico and in living cells using epigenetic CRISPR technology. We also developed a network approach for interactome analysis and detection of differentially interacting genes. Differential interaction analysis provided additional information on relevant genes and pathways for myelosuppression compared with differential gene expression analysis at the bulk level. Moreover, we showed that enhancers of differentially interacting genes are highly enriched for variants associated with differing levels of myelosuppression. Altogether, our work represents a prominent example of integrative transcriptome and gene regulatory datasets analysis for the functional annotation of noncoding mutations.
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Affiliation(s)
- Artemy Zhigulev
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Zandra Norberg
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Julie Cordier
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Rapolas Spalinskas
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Hassan Bassereh
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Niclas Björn
- Division of Clinical Chemistry and Pharmacology, Department of Biomedical and Clinical Sciences, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden
| | - Sailendra Pradhananga
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
| | - Henrik Gréen
- Division of Clinical Chemistry and Pharmacology, Department of Biomedical and Clinical Sciences, Faculty of Medicine and Health Sciences, Linköping University, Linköping, Sweden
- Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden
| | - Pelin Sahlén
- https://ror.org/026vcq606 Royal Institute of Technology - KTH, School of Chemistry, Biotechnology and Health, Science for Life Laboratory, Stockholm, Sweden
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Li K, Zhang P, Wang Z, Shen W, Sun W, Xu J, Wen Z, Li L. iEnhance: a multi-scale spatial projection encoding network for enhancing chromatin interaction data resolution. Brief Bioinform 2023; 24:bbad245. [PMID: 37381618 DOI: 10.1093/bib/bbad245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 06/06/2023] [Accepted: 06/12/2023] [Indexed: 06/30/2023] Open
Abstract
Although sequencing-based high-throughput chromatin interaction data are widely used to uncover genome-wide three-dimensional chromatin architecture, their sparseness and high signal-noise-ratio greatly restrict the precision of the obtained structural elements. To improve data quality, we here present iEnhance (chromatin interaction data resolution enhancement), a multi-scale spatial projection and encoding network, to predict high-resolution chromatin interaction matrices from low-resolution and noisy input data. Specifically, iEnhance projects the input data into matrix spaces to extract multi-scale global and local feature sets, then hierarchically fused these features by attention mechanism. After that, dense channel encoding and residual channel decoding are used to effectively infer robust chromatin interaction maps. iEnhance outperforms state-of-the-art Hi-C resolution enhancement tools in both visual and quantitative evaluation. Comprehensive analysis shows that unlike other tools, iEnhance can recover both short-range structural elements and long-range interaction patterns precisely. More importantly, iEnhance can be transferred to data enhancement of other tissues or cell lines of unknown resolution. Furthermore, iEnhance performs robustly in enhancement of diverse chromatin interaction data including those from single-cell Hi-C and Micro-C experiments.
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Affiliation(s)
- Kai Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Ping Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zilin Wang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Shen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Weicheng Sun
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Jinsheng Xu
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Zi Wen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
| | - Li Li
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, China
- Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
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