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Cagirici HB, Andorf CM, Sen TZ. Co-expression pan-network reveals genes involved in complex traits within maize pan-genome. BMC PLANT BIOLOGY 2022; 22:595. [PMID: 36529716 PMCID: PMC9762053 DOI: 10.1186/s12870-022-03985-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 12/07/2022] [Indexed: 06/17/2023]
Abstract
BACKGROUND With the advances in the high throughput next generation sequencing technologies, genome-wide association studies (GWAS) have identified a large set of variants associated with complex phenotypic traits at a very fine scale. Despite the progress in GWAS, identification of genotype-phenotype relationship remains challenging in maize due to its nature with dozens of variants controlling the same trait. As the causal variations results in the change in expression, gene expression analyses carry a pivotal role in unraveling the transcriptional regulatory mechanisms behind the phenotypes. RESULTS To address these challenges, we incorporated the gene expression and GWAS-driven traits to extend the knowledge of genotype-phenotype relationships and transcriptional regulatory mechanisms behind the phenotypes. We constructed a large collection of gene co-expression networks and identified more than 2 million co-expressing gene pairs in the GWAS-driven pan-network which contains all the gene-pairs in individual genomes of the nested association mapping (NAM) population. We defined four sub-categories for the pan-network: (1) core-network contains the highest represented ~ 1% of the gene-pairs, (2) near-core network contains the next highest represented 1-5% of the gene-pairs, (3) private-network contains ~ 50% of the gene pairs that are unique to individual genomes, and (4) the dispensable-network contains the remaining 50-95% of the gene-pairs in the maize pan-genome. Strikingly, the private-network contained almost all the genes in the pan-network but lacked half of the interactions. We performed gene ontology (GO) enrichment analysis for the pan-, core-, and private- networks and compared the contributions of variants overlapping with genes and promoters to the GWAS-driven pan-network. CONCLUSIONS Gene co-expression networks revealed meaningful information about groups of co-regulated genes that play a central role in regulatory processes. Pan-network approach enabled us to visualize the global view of the gene regulatory network for the studied system that could not be well inferred by the core-network alone.
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Affiliation(s)
- H Busra Cagirici
- US Department of Agriculture - Agricultural Research Service, Crop Improvement Genetics Research Unit, Western Regional Research Center, 800 Buchanan St, Albany, CA, 94710, USA
| | - Carson M Andorf
- US Department of Agriculture - Agricultural Research Service, Corn Insects and Crop Genetics Research Unit, Iowa State University, Ames, IA, 50011, USA.
- Department of Computer Science, Iowa State University, Ames, IA, 50011, USA.
| | - Taner Z Sen
- US Department of Agriculture - Agricultural Research Service, Crop Improvement Genetics Research Unit, Western Regional Research Center, 800 Buchanan St, Albany, CA, 94710, USA.
- Department of Bioengineering, University of California, Berkeley, CA, 94720, USA.
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The spatial transcriptomic landscape of non-small cell lung cancer brain metastasis. Nat Commun 2022; 13:5983. [PMID: 36216799 PMCID: PMC9551067 DOI: 10.1038/s41467-022-33365-y] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 09/14/2022] [Indexed: 11/30/2022] Open
Abstract
Brain metastases (BrMs) are a common occurrence in lung cancer with a dismal outcome. To understand the mechanism of metastasis to inform prognosis and treatment, here we analyze primary and metastasized tumor specimens from 44 non-small cell lung cancer patients by spatial RNA sequencing, affording a whole transcriptome map of metastasis resolved with morphological markers for the tumor core, tumor immune microenvironment (TIME), and tumor brain microenvironment (TBME). Our data indicate that the tumor microenvironment (TME) in the brain, including the TIME and TBME, undergoes extensive remodeling to create an immunosuppressive and fibrogenic niche for the BrMs. Specifically, the brain TME is characterized with reduced antigen presentation and B/T cell function, increased neutrophils and M2-type macrophages, immature microglia, and reactive astrocytes. Differential gene expression and network analysis identify fibrosis and immune regulation as the major functional modules disrupted in both the lung and brain TME. Besides providing systems-level insights into the mechanism of lung cancer brain metastasis, our study uncovers potential prognostic biomarkers and suggests that therapeutic strategies should be tailored to the immune and fibrosis status of the BrMs. Brain metastases (BrMs) in non-small cell lung cancer (NSCLC) are associated with dismal outcomes, and are possibly sustained by the brain microenvironment. Here, the authors analyse NSCLC BrMs using Digital Spatial Profiling and reveal fibrosis, immune suppression, and cell reprogramming in the BrM microenvironment.
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Fajardo TVM, Quecini V. Comparative transcriptome analyses between cultivated and wild grapes reveal conservation of expressed genes but extensive rewiring of co-expression networks. PLANT MOLECULAR BIOLOGY 2021; 106:1-20. [PMID: 33538951 DOI: 10.1007/s11103-021-01122-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 01/17/2021] [Indexed: 06/12/2023]
Abstract
The transcriptomes of wild and cultivated grapes consists of similar expressed genes but distinct wiring of co-expressed modules associated with environmental conditions. Grapevine is an important fruit crop worldwide, with high economic value and widespread distribution. Commercial production is based on Vitis vinifera, and, to a lesser extent, on hybrids with American grapes, such as V. labrusca. Wild grape relatives are important sources of resistance against biotic and abiotic factors; however, their global gene expression patterns remain poorly characterized. We associated genome-wide transcript profiling to phenotypic analyses to investigate the responses of cultivated and wild vines to vineyard conditions. The expressed genes in the Vitis reference transcriptome are largely shared by wild grapes, V. labrusca hybrids and vinifera cultivars. In contrast, significant differential regulation between wild and vinifera genotypes represents 80% of gene expression variation, regardless of the environment. In wild grapes, genes associated to regulatory processes are downregulated, whereas those involved in metabolic pathways are upregulated, in comparison to vinifera. Photosynthesis-related ontologies are overrepresented in the induced genes, in agreement with higher contents of chlorophyll in wild grapes. Co-regulated gene network analyses provide evidence of more complex transcriptome organization in vinifera. In wild grapes, genes involved in signaling pathways of stress-related hormones are overrepresented in modules associated with the environment. Consensus network analyses revealed high preservation within co-regulated gene modules between cultivated and wild grapes, but divergent relationships among the expression clusters. In conclusion, the distinct phenotypes of wild and cultivated grapes are underlain by differences in gene expression, but also by distinct higher-order organization of the transcriptome and contrasting association of co-expressed gene clusters with the environment.
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Affiliation(s)
- Thor V M Fajardo
- Embrapa Uva e Vinho (Brazilian Agricultural Research Corporation, Grape and Wine Research Center), Rua Livramento, 515, Bento Gonçalves, RS, 95701-008, Brazil
| | - Vera Quecini
- Embrapa Uva e Vinho (Brazilian Agricultural Research Corporation, Grape and Wine Research Center), Rua Livramento, 515, Bento Gonçalves, RS, 95701-008, Brazil.
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Jaemthaworn T, Kalapanulak S, Saithong T. Topological clustering of regulatory genes confers pathogenic tolerance to cassava brown streak virus (CBSV) in cassava. Sci Rep 2021; 11:7872. [PMID: 33846415 PMCID: PMC8041763 DOI: 10.1038/s41598-021-86806-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Accepted: 03/19/2021] [Indexed: 02/01/2023] Open
Abstract
Robustness, a naïve property of biological systems, enables organisms to maintain functions during perturbation and is crucial for improving the resilience of crops to prevailing stress conditions and diseases, guaranteeing food security. Most studies of robustness in crops have focused on genetic superiority based upon individual genes, overlooking the collaborative actions of multiple responsive genes and the regulatory network topology. This research aims to uncover patterns of gene cooperation leading to organismal robustness by studying the topology of gene co-expression networks (GCNs) of both CBSV virus resistant and susceptible cassava cultivars. The resulting GCNs show higher topological clustering of cooperative genes in the resistant cultivar, suggesting that the network architecture is central to attaining robustness. Despite a reduction in the number of hub genes in the resistant cultivar following the perturbation, essential biological functions contained in the network were maintained through neighboring genes that withstood the shock. The susceptible cultivar seemingly coped by inducing more gene actions in the network but could not maintain the functions required for plant growth. These findings underscore the importance of regulatory network architecture in ensuring phenotypic robustness and deepen our understanding of transcriptional regulation.
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Affiliation(s)
- Thanakorn Jaemthaworn
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology, School of Information Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand
| | - Saowalak Kalapanulak
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology, School of Information Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand.
- Center for Agricultural Systems Biology, Systems Biology and Bioinformatics Research Group, Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand.
| | - Treenut Saithong
- Bioinformatics and Systems Biology Program, School of Bioresources and Technology, School of Information Technology, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand.
- Center for Agricultural Systems Biology, Systems Biology and Bioinformatics Research Group, Pilot Plant Development and Training Institute, King Mongkut's University of Technology Thonburi, Bangkok, 10150, Thailand.
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Chen J, Li JM, Tang YJ, Ma K, Li B, Zeng X, Liu XB, Li Y, Yang ZL, Xu WN, Xie BG, Liu HW, Guo SX. Genome-wide analysis and prediction of genes involved in the biosynthesis of polysaccharides and bioactive secondary metabolites in high-temperature-tolerant wild Flammulina filiformis. BMC Genomics 2020; 21:719. [PMID: 33069230 PMCID: PMC7568368 DOI: 10.1186/s12864-020-07108-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 09/28/2020] [Indexed: 11/28/2022] Open
Abstract
Background Flammulina filiformis (previously known as Asian F. velutipes) is a popular commercial edible mushroom. Many bioactive compounds with medicinal effects, such as polysaccharides and sesquiterpenoids, have been isolated and identified from F. filiformis, but their biosynthesis and regulation at the molecular level remains unclear. In this study, we sequenced the genome of the wild strain F. filiformis Liu355, predicted its biosynthetic gene clusters (BGCs) and profiled the expression of these genes in wild and cultivar strains and in different developmental stages of the wild F. filiformis strain by a comparative transcriptomic analysis. Results We found that the genome of the F. filiformis was 35.01 Mb in length and harbored 10,396 gene models. Thirteen putative terpenoid gene clusters were predicted and 12 sesquiterpene synthase genes belonging to four different groups and two type I polyketide synthase gene clusters were identified in the F. filiformis genome. The number of genes related to terpenoid biosynthesis was higher in the wild strain (119 genes) than in the cultivar strain (81 genes). Most terpenoid biosynthesis genes were upregulated in the primordium and fruiting body of the wild strain, while the polyketide synthase genes were generally upregulated in the mycelium of the wild strain. Moreover, genes encoding UDP-glucose pyrophosphorylase and UDP-glucose dehydrogenase, which are involved in polysaccharide biosynthesis, had relatively high transcript levels both in the mycelium and fruiting body of the wild F. filiformis strain. Conclusions F. filiformis is enriched in a number of gene clusters involved in the biosynthesis of polysaccharides and terpenoid bioactive compounds and these genes usually display differential expression between wild and cultivar strains, even in different developmental stages. This study expands our knowledge of the biology of F. filiformis and provides valuable data for elucidating the regulation of secondary metabolites in this unique F. filiformis strain.
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Affiliation(s)
- Juan Chen
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China.
| | - Jia-Mei Li
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China
| | - Yan-Jing Tang
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China
| | - Ke Ma
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Bing Li
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China
| | - Xu Zeng
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China
| | - Xiao-Bin Liu
- Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, P. R. China
| | - Yang Li
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China
| | - Zhu-Liang Yang
- Key Laboratory for Plant Diversity and Biogeography of East Asia, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, P. R. China
| | - Wei-Nan Xu
- Mycological Research Center, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, P. R. China
| | - Bao-Gui Xie
- Mycological Research Center, College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou, P. R. China
| | - Hong-Wei Liu
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China
| | - Shun-Xing Guo
- Key Laboratory of Bioactive Substances and Resource Utilization of Chinese Herbal Medicine, Ministry of Education, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, P. R. China.
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Gupta P, Singh SK. Gene Regulatory Networks: Current Updates and Applications in Plant Biology. ENERGY, ENVIRONMENT, AND SUSTAINABILITY 2019. [DOI: 10.1007/978-981-15-0690-1_18] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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