151
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Santus L, Sopena-Rios M, García-Pérez R, Lin AE, Adams GC, Barnes KG, Siddle KJ, Wohl S, Reverter F, Rinn JL, Bennett RS, Hensley LE, Sabeti PC, Melé M. Single-cell profiling of lncRNA expression during Ebola virus infection in rhesus macaques. Nat Commun 2023; 14:3866. [PMID: 37391481 PMCID: PMC10313701 DOI: 10.1038/s41467-023-39627-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 06/19/2023] [Indexed: 07/02/2023] Open
Abstract
Long non-coding RNAs (lncRNAs) are involved in numerous biological processes and are pivotal mediators of the immune response, yet little is known about their properties at the single-cell level. Here, we generate a multi-tissue bulk RNAseq dataset from Ebola virus (EBOV) infected and not-infected rhesus macaques and identified 3979 novel lncRNAs. To profile lncRNA expression dynamics in immune circulating single-cells during EBOV infection, we design a metric, Upsilon, to estimate cell-type specificity. Our analysis reveals that lncRNAs are expressed in fewer cells than protein-coding genes, but they are not expressed at lower levels nor are they more cell-type specific when expressed in the same number of cells. In addition, we observe that lncRNAs exhibit similar changes in expression patterns to those of protein-coding genes during EBOV infection, and are often co-expressed with known immune regulators. A few lncRNAs change expression specifically upon EBOV entry in the cell. This study sheds light on the differential features of lncRNAs and protein-coding genes and paves the way for future single-cell lncRNA studies.
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Affiliation(s)
- Luisa Santus
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Catalonia, 08034, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
| | - Maria Sopena-Rios
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Catalonia, 08034, Spain
| | - Raquel García-Pérez
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Catalonia, 08034, Spain
| | - Aaron E Lin
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Harvard Program in Virology, Harvard Medical School, Boston, MA, 02115, USA
| | - Gordon C Adams
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Kayla G Barnes
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, 02115, USA
- Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK
| | - Katherine J Siddle
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Shirlee Wohl
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
- The Scripps Research Institute, Department of Immunology and Microbiology, La Jolla, CA, USA
| | - Ferran Reverter
- Department of Genetics, Microbiology and Statistics University of Barcelona, Barcelona, Spain
| | - John L Rinn
- Department of Biochemistry, University of Colorado Boulder, Boulder, 80303, USA
| | - Richard S Bennett
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD, 21702, USA
| | - Lisa E Hensley
- Integrated Research Facility, Division of Clinical Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Frederick, MD, 21702, USA.
| | - Pardis C Sabeti
- FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA.
- Harvard Program in Virology, Harvard Medical School, Boston, MA, 02115, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, 20815, USA.
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Catalonia, 08034, Spain.
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152
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Wang W, Bo T, Zhang G, Li J, Ma J, Ma L, Hu G, Tong H, Lv Q, Araujo DJ, Luo D, Chen Y, Wang M, Wang Z, Wang GZ. Noncoding transcripts are linked to brain resting-state activity in non-human primates. Cell Rep 2023; 42:112652. [PMID: 37335775 DOI: 10.1016/j.celrep.2023.112652] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 04/05/2023] [Accepted: 05/30/2023] [Indexed: 06/21/2023] Open
Abstract
Brain-derived transcriptomes are known to correlate with resting-state brain activity in humans. Whether this association holds in nonhuman primates remains uncertain. Here, we search for such molecular correlates by integrating 757 transcriptomes derived from 100 macaque cortical regions with resting-state activity in separate conspecifics. We observe that 150 noncoding genes explain variations in resting-state activity at a comparable level with protein-coding genes. In-depth analysis of these noncoding genes reveals that they are connected to the function of nonneuronal cells such as oligodendrocytes. Co-expression network analysis finds that the modules of noncoding genes are linked to both autism and schizophrenia risk genes. Moreover, genes associated with resting-state noncoding genes are highly enriched in human resting-state functional genes and memory-effect genes, and their links with resting-state functional magnetic resonance imaging (fMRI) signals are altered in the brains of patients with autism. Our results highlight the potential for noncoding RNAs to explain resting-state activity in the nonhuman primate brain.
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Affiliation(s)
- Wei Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Tingting Bo
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Clinical Neuroscience Center, Ruijin Hospital Luwan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ge Zhang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China
| | - Jie Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Liangxiao Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ganlu Hu
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Huige Tong
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qian Lv
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China
| | - Daniel J Araujo
- Center for Cancer Immunotherapy, La Jolla Institute for Immunology, La Jolla, CA, USA
| | - Dong Luo
- School of Biomedical Engineering, Hainan University, Haikou, Hainan, China
| | - Yuejun Chen
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China
| | - Meiyun Wang
- Department of Medical Imaging, Henan Provincial People's Hospital & the People's Hospital of Zhengzhou University, No. 7 Weiwu Road, Zhengzhou, Henan, China
| | - Zheng Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, China; School of Biomedical Engineering, Hainan University, Haikou, Hainan, China.
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
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153
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Peng J, Zhao L. The origin and structural evolution of de novo genes in Drosophila. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.13.532420. [PMID: 37425675 PMCID: PMC10326970 DOI: 10.1101/2023.03.13.532420] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Although previously thought to be unlikely, recent studies have shown that de novo gene origination from previously non-genic sequences is a relatively common mechanism for gene innovation in many species and taxa. These young genes provide a unique set of candidates to study the structural and functional origination of proteins. However, our understanding of their protein structures and how these structures originate and evolve are still limited, due to a lack of systematic studies. Here, we combined high-quality base-level whole genome alignments, bioinformatic analysis, and computational structure modeling to study the origination, evolution, and protein structure of lineage-specific de novo genes. We identified 555 de novo gene candidates in D. melanogaster that originated within the Drosophilinae lineage. We found a gradual shift in sequence composition, evolutionary rates, and expression patterns with their gene ages, which indicates possible gradual shifts or adaptations of their functions. Surprisingly, we found little overall protein structural changes for de novo genes in the Drosophilinae lineage. Using Alphafold2, ESMFold, and molecular dynamics, we identified a number of de novo gene candidates with protein products that are potentially well-folded, many of which are more likely to contain transmembrane and signal proteins compared to other annotated protein-coding genes. Using ancestral sequence reconstruction, we found that most potentially well-folded proteins are often born folded. Interestingly, we observed one case where disordered ancestral proteins become ordered within a relatively short evolutionary time. Single-cell RNA-seq analysis in testis showed that although most de novo genes are enriched in spermatocytes, several young de novo genes are biased in the early spermatogenesis stage, indicating potentially important but less emphasized roles of early germline cells in the de novo gene origination in testis. This study provides a systematic overview of the origin, evolution, and structural changes of Drosophilinae-specific de novo genes.
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Affiliation(s)
- Junhui Peng
- Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY 10065, USA
| | - Li Zhao
- Laboratory of Evolutionary Genetics and Genomics, The Rockefeller University, New York, NY 10065, USA
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154
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Xu X, Ma J, Li W, You Y, Jiang Q, Long P, Liu K, Mo T, Jiang J, Wang W, Lei Y, Diao T, Ruan S, Wang X, Guo H, Chen W, Wu T. Polycyclic aromatic hydrocarbons exposure and plasma lncRNA signature: A profile and functional analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 877:162932. [PMID: 36934921 DOI: 10.1016/j.scitotenv.2023.162932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Revised: 03/13/2023] [Accepted: 03/14/2023] [Indexed: 05/06/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental pollutants that pose detrimental effects on human health, and the exploration of the associations of PAHs exposure with long non-coding RNA (lncRNA) may provide novel clues to the underlying mechanisms. In the present study, we detected 10 urinary PAHs metabolites by GC-MS and plasma lncRNAs levels by Human LncRNA Array v4 among 230 participants from two panels (160 in the Shiyan panel and 70 in the Wuhan-Zhuhai panel). We applied linear regression models to assess the associations between PAHs metabolites and lncRNAs separately in each panel and combined the results using fixed-effect meta-analysis. To explore the potential origin of PAHs-related lncRNAs in plasma, we estimated their tissue-specificity and associations between lncRNAs levels in plasma and leukocytes. Leukocytes mRNA sequencing data and RNA binding proteins were utilized to explore implicated pathways of identified lncRNAs. We found that urinary 1-hydroxyphenanthrene (1-OH-Phe) was inversely associated with 8 lncRNAs and positively associated with 1 lncRNA, as well as 9-hydroxyphenanthrene (9-OH-Phe) was inversely associated with 11 lncRNAs (FDR < 0.1). Tissue specificity analysis using Genome Tissue Expression database suggested that several identified lncRNAs might specifically express in organs targeted by PAHs exposure (lung, liver, heart, kidney, and brain). Besides, plasma levels of 1-OH-Phe related ENSG00000260616 and 9-OH-Phe related STARD4-AS1 were inversely associated with their intra-leukocytes levels (P value < 0.05). Notably, STARD4-AS1 was positively associated with the expression levels of its neighboring protein-coding gene (CAMK4 and STARD4) in leukocytes and were involved in pathways related to cellular response to DNA damage, which we further confirmed using DNA damage biomarker, 8-hydroxydeoxyguanosine. Functional analysis also revealed vital pathways related to cytokine-mediated signaling and glucose homeostasis. Our findings provided novel insights into plausible biological mechanisms underlying the adverse effects of PAHs exposure.
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Affiliation(s)
- Xuedan Xu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jixuan Ma
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Wending Li
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yutong You
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qin Jiang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Pinpin Long
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Kang Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China; School of Public Health, Guangzhou Medical University, Guangzhou 511436, China
| | - Tingting Mo
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jing Jiang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Wei Wang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yanshou Lei
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Tingyue Diao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shuping Ruan
- Health Management Center, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan 442008, China
| | - Xiaozheng Wang
- Health Management Center, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan 442008, China
| | - Huan Guo
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Weihong Chen
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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155
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Esposito R, Lanzós A, Uroda T, Ramnarayanan S, Büchi I, Polidori T, Guillen-Ramirez H, Mihaljevic A, Merlin BM, Mela L, Zoni E, Hovhannisyan L, McCluggage F, Medo M, Basile G, Meise DF, Zwyssig S, Wenger C, Schwarz K, Vancura A, Bosch-Guiteras N, Andrades Á, Tham AM, Roemmele M, Medina PP, Ochsenbein AF, Riether C, Kruithof-de Julio M, Zimmer Y, Medová M, Stroka D, Fox A, Johnson R. Tumour mutations in long noncoding RNAs enhance cell fitness. Nat Commun 2023; 14:3342. [PMID: 37291246 PMCID: PMC10250536 DOI: 10.1038/s41467-023-39160-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 06/01/2023] [Indexed: 06/10/2023] Open
Abstract
Long noncoding RNAs (lncRNAs) are linked to cancer via pathogenic changes in their expression levels. Yet, it remains unclear whether lncRNAs can also impact tumour cell fitness via function-altering somatic "driver" mutations. To search for such driver-lncRNAs, we here perform a genome-wide analysis of fitness-altering single nucleotide variants (SNVs) across a cohort of 2583 primary and 3527 metastatic tumours. The resulting 54 mutated and positively-selected lncRNAs are significantly enriched for previously-reported cancer genes and a range of clinical and genomic features. A number of these lncRNAs promote tumour cell proliferation when overexpressed in in vitro models. Our results also highlight a dense SNV hotspot in the widely-studied NEAT1 oncogene. To directly evaluate the functional significance of NEAT1 SNVs, we use in cellulo mutagenesis to introduce tumour-like mutations in the gene and observe a significant and reproducible increase in cell fitness, both in vitro and in a mouse model. Mechanistic studies reveal that SNVs remodel the NEAT1 ribonucleoprotein and boost subnuclear paraspeckles. In summary, this work demonstrates the utility of driver analysis for mapping cancer-promoting lncRNAs, and provides experimental evidence that somatic mutations can act through lncRNAs to enhance pathological cancer cell fitness.
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Affiliation(s)
- Roberta Esposito
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland.
- Institute of Genetics and Biophysics "Adriano Buzzati-Traverso", CNR, 80131, Naples, Italy.
| | - Andrés Lanzós
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, 3012, Bern, Switzerland
| | - Tina Uroda
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Sunandini Ramnarayanan
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
- The SFI Centre for Research Training in Genomics Data Science, Dublin, Ireland
| | - Isabel Büchi
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Taisia Polidori
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Hugo Guillen-Ramirez
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Ante Mihaljevic
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Bernard Mefi Merlin
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Lia Mela
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Eugenio Zoni
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Urology, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Lusine Hovhannisyan
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Finn McCluggage
- School of Molecular Sciences, University of Western Australia, Crawley, WA, Australia
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Matúš Medo
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Giulia Basile
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Dominik F Meise
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Sandra Zwyssig
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Corina Wenger
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Kyriakos Schwarz
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Adrienne Vancura
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Núria Bosch-Guiteras
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Graduate School of Cellular and Biomedical Sciences, University of Bern, 3012, Bern, Switzerland
| | - Álvaro Andrades
- GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Granada, 18016, Spain
- Instituto de Investigación Biosanitaria, Granada, 18014, Spain
- Department of Biochemistry and Molecular Biology I, University of Granada, Granada, 18071, Spain
| | - Ai Ming Tham
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland
| | - Michaela Roemmele
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Pedro P Medina
- GENYO, Centre for Genomics and Oncological Research, Pfizer/University of Granada/Andalusian Regional Government, Granada, 18016, Spain
- Instituto de Investigación Biosanitaria, Granada, 18014, Spain
- Department of Biochemistry and Molecular Biology I, University of Granada, Granada, 18071, Spain
| | - Adrian F Ochsenbein
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Carsten Riether
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
| | - Marianna Kruithof-de Julio
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Urology, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Yitzhak Zimmer
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Michaela Medová
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Radiation Oncology, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Deborah Stroka
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland
- Department of Visceral Surgery and Medicine, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Archa Fox
- School of Molecular Sciences, University of Western Australia, Crawley, WA, Australia
- School of Human Sciences, University of Western Australia, Crawley, WA, Australia
| | - Rory Johnson
- Department of Medical Oncology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland.
- Department for BioMedical Research, University of Bern, 3008, Bern, Switzerland.
- School of Biology and Environmental Science, University College Dublin, Dublin, D04 V1W8, Ireland.
- Conway Institute for Biomolecular and Biomedical Research, University College Dublin, Dublin, D04 V1W8, Ireland.
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156
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Qian SH, Xiong YL, Chen L, Geng YJ, Tang XM, Chen ZX. Dynamic Spatial-temporal Expression Ratio of X Chromosome to Autosomes but Stable Dosage Compensation in Mammals. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:589-600. [PMID: 36031057 PMCID: PMC10787176 DOI: 10.1016/j.gpb.2022.08.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2021] [Revised: 08/03/2022] [Accepted: 08/22/2022] [Indexed: 06/15/2023]
Abstract
In the evolutionary model of dosage compensation, per-allele expression level of the X chromosome has been proposed to have twofold up-regulation to compensate its dose reduction in males (XY) compared to females (XX). However, the expression regulation of X-linked genes is still controversial, and comprehensive evaluations are still lacking. By integrating multi-omics datasets in mammals, we investigated the expression ratios including X to autosomes (X:AA ratio) and X to orthologs (X:XX ratio) at the transcriptome, translatome, and proteome levels. We revealed a dynamic spatial-temporal X:AA ratio during development in humans and mice. Meanwhile, by tracing the evolution of orthologous gene expression in chickens, platypuses, and opossums, we found a stable expression ratio of X-linked genes in humans to their autosomal orthologs in other species (X:XX ≈ 1) across tissues and developmental stages, demonstrating stable dosage compensation in mammals. We also found that different epigenetic regulations contributed to the high tissue specificity and stage specificity of X-linked gene expression, thus affecting X:AA ratios. It could be concluded that the dynamics of X:AA ratios were attributed to the different gene contents and expression preferences of the X chromosome, rather than the stable dosage compensation.
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Affiliation(s)
- Sheng Hu Qian
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Yu-Li Xiong
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Lu Chen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Ying-Jie Geng
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiao-Man Tang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Zhen-Xia Chen
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China; Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan 430070, China; Interdisciplinary Sciences Institute, Huazhong Agricultural University, Wuhan 430070, China.
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157
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Roberts M, Josephs EB. Weaker selection on genes with treatment-specific expression consistent with a limit on plasticity evolution in Arabidopsis thaliana. Genetics 2023; 224:iyad074. [PMID: 37094602 PMCID: PMC10484170 DOI: 10.1093/genetics/iyad074] [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: 03/06/2023] [Revised: 03/06/2023] [Accepted: 04/07/2023] [Indexed: 04/26/2023] Open
Abstract
Differential gene expression between environments often underlies phenotypic plasticity. However, environment-specific expression patterns are hypothesized to relax selection on genes, and thus limit plasticity evolution. We collated over 27 terabases of RNA-sequencing data on Arabidopsis thaliana from over 300 peer-reviewed studies and 200 treatment conditions to investigate this hypothesis. Consistent with relaxed selection, genes with more treatment-specific expression have higher levels of nucleotide diversity and divergence at nonsynonymous sites but lack stronger signals of positive selection. This result persisted even after controlling for expression level, gene length, GC content, the tissue specificity of expression, and technical variation between studies. Overall, our investigation supports the existence of a hypothesized trade-off between the environment specificity of a gene's expression and the strength of selection on said gene in A. thaliana. Future studies should leverage multiple genome-scale datasets to tease apart the contributions of many variables in limiting plasticity evolution.
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Affiliation(s)
- Miles Roberts
- Genetics and Genome Sciences Program, Michigan State University, East Lansing, MI 48824, USA
| | - Emily B Josephs
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
- Ecology, Evolution, and Behavior Program, Michigan State University, East Lansing, MI 48824, USA
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158
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Singh A, AT V, Gupta K, Sharma S, Kumar S. Long non-coding RNA and microRNA landscape of two major domesticated cotton species. Comput Struct Biotechnol J 2023; 21:3032-3044. [PMID: 37266406 PMCID: PMC10229759 DOI: 10.1016/j.csbj.2023.05.011] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 05/11/2023] [Accepted: 05/11/2023] [Indexed: 06/03/2023] Open
Abstract
Allotetraploid cotton plants Gossypium hirsutum and Gossypium barbadense have been widely cultivated for their natural, renewable textile fibres. Even though ncRNAs in domesticated cotton species have been extensively studied, systematic identification and annotation of lncRNAs and miRNAs expressed in various tissues and developmental stages under various biological contexts are limited. This influences the comprehension of their functions and future research on these cotton species. Here, we report high confidence lncRNAs and miRNA collection from G. hirsutum accession and G. barbadense accession using large-scale RNA-seq and small RNA-seq datasets incorporated into a user-friendly database, CoNCRAtlas. This database provides a wide range and depth of lncRNA and miRNA annotation based on the systematic integration of extensive annotations such as expression patterns derived from transcriptome data analysis in thousands of samples, as well as multi-omics annotations. We assume this comprehensive resource will accelerate evolutionary and functional studies in ncRNAs and inform future breeding programs for cotton improvement. CoNCRAtlas is accessible at http://www.nipgr.ac.in/CoNCRAtlas/.
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Affiliation(s)
- Ajeet Singh
- Bioinformatics Lab, National Institute of Plant Genome Research, New Delhi 110067, India
- Postdoctoral Associate, Ophthalmology, Baylor College of Medicine, Houston, TX, USA
| | - Vivek AT
- Bioinformatics Lab, National Institute of Plant Genome Research, New Delhi 110067, India
| | - Kanika Gupta
- Bioinformatics Lab, National Institute of Plant Genome Research, New Delhi 110067, India
| | - Shruti Sharma
- Bioinformatics Lab, National Institute of Plant Genome Research, New Delhi 110067, India
| | - Shailesh Kumar
- Bioinformatics Lab, National Institute of Plant Genome Research, New Delhi 110067, India
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159
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Yu D, Wu Y, Zhu L, Wang Y, Sheng D, Zhao X, Liang G, Gan L. The landscape of the long non-coding RNAs in developing mouse retinas. BMC Genomics 2023; 24:252. [PMID: 37165305 PMCID: PMC10173636 DOI: 10.1186/s12864-023-09354-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 05/03/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND The long non-coding RNAs (lncRNAs) are critical regulators of diverse biological processes. Nevertheless, a global view of its expression and function in the mouse retina, a crucial model for neurogenesis study, still needs to be made available. RESULTS Herein, by integrating the established gene models and the result from ab initio prediction using short- and long-read sequencing, we characterized 4,523 lncRNA genes (MRLGs) in developing mouse retinas (from the embryonic day of 12.5 to the neonatal day of P28), which was so far the most comprehensive collection of retinal lncRNAs. Next, derived from transcriptomics analyses of different tissues and developing retinas, we found that the MRLGs were highly spatiotemporal specific in expression and played essential roles in regulating the genesis and function of mouse retinas. In addition, we investigated the expression of MRLGs in some mouse mutants and revealed that 97 intergenic MRLGs might be involved in regulating differentiation and development of retinal neurons through Math5, Isl1, Brn3b, NRL, Onecut1, or Onecut2 mediated pathways. CONCLUSIONS In summary, this work significantly enhanced our knowledge of lncRNA genes in mouse retina development and provided valuable clues for future exploration of their biological roles.
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Affiliation(s)
- Dongliang Yu
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, 310018, China.
- Institute of Life Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, 310036, China.
| | - Yuqing Wu
- College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, Zhejiang, 310018, China
| | - Leilei Zhu
- Institute of Life Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, 310036, China
| | - Yuying Wang
- Institute of Life Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, 310036, China
| | - Donglai Sheng
- Institute of Life Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, 310036, China
| | - Xiaofeng Zhao
- Institute of Life Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, 310036, China
| | - Guoqing Liang
- Institute of Life Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, 310036, China.
| | - Lin Gan
- Department of Neuroscience & Regenerative Medicine, Medical College of Georgia, Augusta University, Augusta, GA, 30912, USA.
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160
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Zhao Y, Zheng Z, Zhang Z, Hillpot E, Lin YS, Zakusilo FT, Lu JY, Ablaeva J, Miller RA, Nevo E, Seluanov A, Gorbunova V. Evolution of High-Molecular-Mass Hyaluronic Acid is Associated with Subterranean Lifestyle. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.08.539764. [PMID: 37215017 PMCID: PMC10197608 DOI: 10.1101/2023.05.08.539764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Hyaluronic acid (HA) is a major component of extracellular matrix (ECM) which plays an important role in development, cellular response to injury and inflammation, cell migration, and cancer. The naked mole-rat (NMR, Heterocephalus glaber ) contains abundant high-molecular-mass HA (HMM-HA) in its tissues, which contributes to this species' cancer resistance and possibly longevity. Here we report that abundant HMM-HA is found in a wide range of subterranean mammalian species, but not in phylogenetically related aboveground species. These species accumulate abundant HMM-HA by regulating the expression of genes involved in HA degradation and synthesis and contain unique mutations in these genes. The abundant high molecular weight HA may benefit the adaptation to subterranean environment by increasing skin elasticity and protecting from oxidative stress due to hypoxic subterranean environment. HMM-HA may also be coopted to confer cancer resistance and longevity to subterranean mammals. Our work suggests that HMM-HA has evolved with subterranean lifestyle.
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161
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Cridland JM, Contino CE, Begun DJ. Selection and geography shape male reproductive tract transcriptomes in Drosophila melanogaster. Genetics 2023; 224:iyad034. [PMID: 36869688 PMCID: PMC10474930 DOI: 10.1093/genetics/iyad034] [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: 01/25/2023] [Revised: 01/25/2023] [Accepted: 02/20/2023] [Indexed: 03/05/2023] Open
Abstract
Transcriptome analysis of several animal clades suggests that male reproductive tract gene expression evolves quickly. However, the factors influencing the abundance and distribution of within-species variation, the ultimate source of interspecific divergence, are poorly known. Drosophila melanogaster, an ancestrally African species that has recently spread throughout the world and colonized the Americas in the last roughly 100 years, exhibits phenotypic and genetic latitudinal clines on multiple continents, consistent with a role for spatially varying selection in shaping its biology. Nevertheless, geographic expression variation in the Americas is poorly described, as is its relationship to African expression variation. Here, we investigate these issues through the analysis of two male reproductive tissue transcriptomes [testis and accessory gland (AG)] in samples from Maine (USA), Panama, and Zambia. We find dramatic differences between these tissues in differential expression between Maine and Panama, with the accessory glands exhibiting abundant expression differentiation and the testis exhibiting very little. Latitudinal expression differentiation appears to be influenced by the selection of Panama expression phenotypes. While the testis shows little latitudinal expression differentiation, it exhibits much greater differentiation than the accessory gland in Zambia vs American population comparisons. Expression differentiation for both tissues is non-randomly distributed across the genome on a chromosome arm scale. Interspecific expression divergence between D. melanogaster and D. simulans is discordant with rates of differentiation between D. melanogaster populations. Strongly heterogeneous expression differentiation across tissues and timescales suggests a complex evolutionary process involving major temporal changes in the way selection influences expression evolution in these organs.
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Affiliation(s)
- Julie M Cridland
- Department of Evolution and Ecology, University of California-Davis, Davis, CA 95616, USA
| | - Colin E Contino
- Department of Evolution and Ecology, University of California-Davis, Davis, CA 95616, USA
| | - David J Begun
- Department of Evolution and Ecology, University of California-Davis, Davis, CA 95616, USA
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162
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Pan Z, Wang Y, Wang M, Wang Y, Zhu X, Gu S, Zhong C, An L, Shan M, Damas J, Halstead MM, Guan D, Trakooljul N, Wimmers K, Bi Y, Wu S, Delany ME, Bai X, Cheng HH, Sun C, Yang N, Hu X, Lewin HA, Fang L, Zhou H. An atlas of regulatory elements in chicken: A resource for chicken genetics and genomics. SCIENCE ADVANCES 2023; 9:eade1204. [PMID: 37134160 PMCID: PMC10156120 DOI: 10.1126/sciadv.ade1204] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
A comprehensive characterization of regulatory elements in the chicken genome across tissues will have substantial impacts on both fundamental and applied research. Here, we systematically identified and characterized regulatory elements in the chicken genome by integrating 377 genome-wide sequencing datasets from 23 adult tissues. In total, we annotated 1.57 million regulatory elements, representing 15 distinct chromatin states, and predicted about 1.2 million enhancer-gene pairs and 7662 super-enhancers. This functional annotation of the chicken genome should have wide utility on identifying regulatory elements accounting for gene regulation underlying domestication, selection, and complex trait regulation, which we explored. In short, this comprehensive atlas of regulatory elements provides the scientific community with a valuable resource for chicken genetics and genomics.
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Affiliation(s)
- Zhangyuan Pan
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Ying Wang
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mingshan Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650000, China
| | - Yuzhe Wang
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100193, China
| | - Xiaoning Zhu
- State Key Laboratory for Agrobiotechnology, China Agricultural University, Beijing 100193, China
| | - Shenwen Gu
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Conghao Zhong
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Liqi An
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mingzhu Shan
- Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China
| | - Joana Damas
- The Genome Center, University of California, Davis, CA 95616, USA
| | - Michelle M Halstead
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Dailu Guan
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Nares Trakooljul
- Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
| | - Klaus Wimmers
- Research Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
- Faculty of Agricultural and Environmental Sciences, University Rostock, Rostock, Germany
| | - Ye Bi
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Shang Wu
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Mary E Delany
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Xuechen Bai
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
| | - Hans H Cheng
- USDA-ARS, Avian Disease and Oncology Laboratory, East Lansing, MI 48823, USA
| | - Congjiao Sun
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Ning Yang
- National Engineering Laboratory for Animal Breeding and Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, China Agricultural University, Beijing 100193, China
| | - Xiaoxiang Hu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650000, China
| | - Harris A Lewin
- The Genome Center, University of California, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, 8000, DK
- MRC Human Genetics Unit at the Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Huaijun Zhou
- Department of Animal Science, University of California, Davis, Davis 95616, CA, USA
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163
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Guillotin B, Rahni R, Passalacqua M, Mohammed MA, Xu X, Raju SK, Ramírez CO, Jackson D, Groen SC, Gillis J, Birnbaum KD. A pan-grass transcriptome reveals patterns of cellular divergence in crops. Nature 2023; 617:785-791. [PMID: 37165193 PMCID: PMC10657638 DOI: 10.1038/s41586-023-06053-0] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 04/05/2023] [Indexed: 05/12/2023]
Abstract
Different plant species within the grasses were parallel targets of domestication, giving rise to crops with distinct evolutionary histories and traits1. Key traits that distinguish these species are mediated by specialized cell types2. Here we compare the transcriptomes of root cells in three grass species-Zea mays, Sorghum bicolor and Setaria viridis. We show that single-cell and single-nucleus RNA sequencing provide complementary readouts of cell identity in dicots and monocots, warranting a combined analysis. Cell types were mapped across species to identify robust, orthologous marker genes. The comparative cellular analysis shows that the transcriptomes of some cell types diverged more rapidly than those of others-driven, in part, by recruitment of gene modules from other cell types. The data also show that a recent whole-genome duplication provides a rich source of new, highly localized gene expression domains that favour fast-evolving cell types. Together, the cell-by-cell comparative analysis shows how fine-scale cellular profiling can extract conserved modules from a pan transcriptome and provide insight on the evolution of cells that mediate key functions in crops.
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Affiliation(s)
- Bruno Guillotin
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- Center for Genomics and Systems Biology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Ramin Rahni
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | | | - Mohammed Ateequr Mohammed
- Center for Genomics and Systems Biology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Xiaosa Xu
- Cold Spring Harbor Laboratory, New York, NY, USA
| | - Sunil Kenchanmane Raju
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- Department of Plant Biology, Michigan State University, East Lansing, MI, USA
| | - Carlos Ortiz Ramírez
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- UGA-LANGEBIO Cinvestav, Guanajuato, México
| | | | - Simon C Groen
- Department of Nematology and Center for Plant Cell Biology, Institute for Integrative Genome Biology, University of California, Riverside, CA, USA
| | - Jesse Gillis
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Kenneth D Birnbaum
- Center for Genomics and Systems Biology, New York University, New York, NY, USA.
- Center for Genomics and Systems Biology, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.
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164
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Marlétaz F, Timoshevskaya N, Timoshevskiy V, Simakov O, Parey E, Gavriouchkina D, Suzuki M, Kubokawa K, Brenner S, Smith J, Rokhsar DS. The hagfish genome and the evolution of vertebrates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.17.537254. [PMID: 37131617 PMCID: PMC10153176 DOI: 10.1101/2023.04.17.537254] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
As the only surviving lineages of jawless fishes, hagfishes and lampreys provide a critical window into early vertebrate evolution. Here, we investigate the complex history, timing, and functional role of genome-wide duplications in vertebrates in the light of a chromosome-scale genome of the brown hagfish Eptatretus atami. Using robust chromosome-scale (paralogon-based) phylogenetic methods, we confirm the monophyly of cyclostomes, document an auto-tetraploidization (1RV) that predated the origin of crown group vertebrates ~517 Mya, and establish the timing of subsequent independent duplications in the gnathostome and cyclostome lineages. Some 1RV gene duplications can be linked to key vertebrate innovations, suggesting that this early genomewide event contributed to the emergence of pan-vertebrate features such as neural crest. The hagfish karyotype is derived by numerous fusions relative to the ancestral cyclostome arrangement preserved by lampreys. These genomic changes were accompanied by the loss of genes essential for organ systems (eyes, osteoclast) that are absent in hagfish, accounting in part for the simplification of the hagfish body plan; other gene family expansions account for hagfishes' capacity to produce slime. Finally, we characterise programmed DNA elimination in somatic cells of hagfish, identifying protein-coding and repetitive elements that are deleted during development. As in lampreys, the elimination of these genes provides a mechanism for resolving genetic conflict between soma and germline by repressing germline/pluripotency functions. Reconstruction of the early genomic history of vertebrates provides a framework for further exploration of vertebrate novelties.
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Affiliation(s)
- Ferdinand Marlétaz
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, London, UK
- Molecular Genetics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
| | | | | | - Oleg Simakov
- Molecular Genetics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
- Department of Molecular Evolution and Development, University of Vienna, Vienna, Austria
| | - Elise Parey
- Centre for Life's Origins and Evolution, Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Daria Gavriouchkina
- Molecular Genetics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
- Present address: UK Dementia Research Institute, University College London, London, UK
| | - Masakazu Suzuki
- Department of Science, Graduate School of Integrated Science and Technology, Shizuoka University, Shizuoka, Japan
| | - Kaoru Kubokawa
- Ocean Research Institute, The University of Tokyo, Tokyo, Japan
| | - Sydney Brenner
- Comparative and Medical Genomics Laboratory, Institute of Molecular and Cell Biology, A*STAR, Biopolis, Singapore 138673, Singapore
- Deceased
| | - Jeramiah Smith
- Department of Biology, University of Kentucky, Lexington, KY, USA
| | - Daniel S Rokhsar
- Molecular Genetics Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, Japan
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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165
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Kenchanmane Raju SK, Ledford M, Niederhuth CE. DNA methylation signatures of duplicate gene evolution in angiosperms. PLANT PHYSIOLOGY 2023:kiad220. [PMID: 37061825 PMCID: PMC10400039 DOI: 10.1093/plphys/kiad220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 03/03/2023] [Accepted: 04/12/2023] [Indexed: 06/19/2023]
Abstract
Gene duplication is a source of evolutionary novelty. DNA methylation may play a role in the evolution of duplicate genes (paralogs) through its association with gene expression. While this relationship has been examined to varying extents in a few individual species, the generalizability of these results at either a broad phylogenetic scale with species of differing duplication histories or across a population remains unknown. We applied a comparative epigenomics approach to 43 angiosperm species across the phylogeny and a population of 928 Arabidopsis (Arabidopsis thaliana) accessions, examining the association of DNA methylation with paralog evolution. Genic DNA methylation was differentially associated with duplication type, the age of duplication, sequence evolution, and gene expression. Whole genome duplicates were typically enriched for CG-only gene-body methylated or unmethylated genes, while single-gene duplications were typically enriched for non-CG methylated or unmethylated genes. Non-CG methylation, in particular, was characteristic of more recent single-gene duplicates. Core angiosperm gene families differentiated into those which preferentially retain paralogs and 'duplication-resistant' families, which convergently reverted to singletons following duplication. Duplication-resistant families that still have paralogous copies were, uncharacteristically for core angiosperm genes, enriched for non-CG methylation. Non-CG methylated paralogs had higher rates of sequence evolution, higher frequency of presence-absence variation, and more limited expression. This suggests that silencing by non-CG methylation may be important to maintaining dosage following duplication and be a precursor to fractionation. Our results indicate that genic methylation marks differing evolutionary trajectories and fates between paralogous genes and have a role in maintaining dosage following duplication.
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Affiliation(s)
| | | | - Chad E Niederhuth
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
- AgBioResearch, Michigan State University, East Lansing, MI 48824, USA
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166
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Zhao F, Yan Y, Wang Y, Liu Y, Yang R. Splicing complexity as a pivotal feature of alternative exons in mammalian species. BMC Genomics 2023; 24:198. [PMID: 37046221 PMCID: PMC10099729 DOI: 10.1186/s12864-023-09247-y] [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: 01/09/2023] [Accepted: 03/14/2023] [Indexed: 04/14/2023] Open
Abstract
BACKGROUND As a significant process of post-transcriptional gene expression regulation in eukaryotic cells, alternative splicing (AS) of exons greatly contributes to the complexity of the transcriptome and indirectly enriches the protein repertoires. A large number of studies have focused on the splicing inclusion of alternative exons and have revealed the roles of AS in organ development and maturation. Notably, AS takes place through a change in the relative abundance of the transcript isoforms produced by a single gene, meaning that exons can have complex splicing patterns. However, the commonly used percent spliced-in (Ψ) values only define the usage rate of exons, but lose information about the complexity of exons' linkage pattern. To date, the extent and functional consequence of splicing complexity of alternative exons in development and evolution is poorly understood. RESULTS By comparing splicing complexity of exons in six tissues (brain, cerebellum, heart, liver, kidney, and testis) from six mammalian species (human, chimpanzee, gorilla, macaque, mouse, opossum) and an outgroup species (chicken), we revealed that exons with high splicing complexity are prevalent in mammals and are closely related to features of genes. Using traditional machine learning and deep learning methods, we found that the splicing complexity of exons can be moderately predicted with features derived from exons, among which length of flanking exons and splicing strength of downstream/upstream splice sites are top predictors. Comparative analysis among human, chimpanzee, gorilla, macaque, and mouse revealed that, alternative exons tend to evolve to an increased level of splicing complexity and higher tissue specificity in splicing complexity. During organ development, not only developmentally regulated exons, but also 10-15% of non-developmentally regulated exons show dynamic splicing complexity. CONCLUSIONS Our analysis revealed that splicing complexity is an important metric to characterize the splicing dynamics of alternative exons during the development and evolution of mammals.
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Affiliation(s)
- Feiyang Zhao
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Yubin Yan
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Yaxi Wang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Yuan Liu
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China
| | - Ruolin Yang
- College of Life Sciences, Northwest A&F University, Yangling, Shaanxi, China.
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167
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Jones BM, Rubin BER, Dudchenko O, Kingwell CJ, Traniello IM, Wang ZY, Kapheim KM, Wyman ES, Adastra PA, Liu W, Parsons LR, Jackson SR, Goodwin K, Davidson SM, McBride MJ, Webb AE, Omufwoko KS, Van Dorp N, Otárola MF, Pham M, Omer AD, Weisz D, Schraiber J, Villanea F, Wcislo WT, Paxton RJ, Hunt BG, Aiden EL, Kocher SD. Convergent and complementary selection shaped gains and losses of eusociality in sweat bees. Nat Ecol Evol 2023; 7:557-569. [PMID: 36941345 PMCID: PMC11610481 DOI: 10.1038/s41559-023-02001-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 01/18/2023] [Indexed: 03/23/2023]
Abstract
Sweat bees have repeatedly gained and lost eusociality, a transition from individual to group reproduction. Here we generate chromosome-length genome assemblies for 17 species and identify genomic signatures of evolutionary trade-offs associated with transitions between social and solitary living. Both young genes and regulatory regions show enrichment for these molecular patterns. We also identify loci that show evidence of complementary signals of positive and relaxed selection linked specifically to the convergent gains and losses of eusociality in sweat bees. This includes two pleiotropic proteins that bind and transport juvenile hormone (JH)-a key regulator of insect development and reproduction. We find that one of these proteins is primarily expressed in subperineurial glial cells that form the insect blood-brain barrier and that brain levels of JH vary by sociality. Our findings are consistent with a role of JH in modulating social behaviour and suggest that eusocial evolution was facilitated by alteration of the proteins that bind and transport JH, revealing how an ancestral developmental hormone may have been co-opted during one of life's major transitions. More broadly, our results highlight how evolutionary trade-offs have structured the molecular basis of eusociality in these bees and demonstrate how both directional selection and release from constraint can shape trait evolution.
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Affiliation(s)
- Beryl M Jones
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Benjamin E R Rubin
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Olga Dudchenko
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
| | - Callum J Kingwell
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
| | - Ian M Traniello
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Z Yan Wang
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Karen M Kapheim
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
- Department of Biology, Utah State University, Logan, UT, USA
| | - Eli S Wyman
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Per A Adastra
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Weijie Liu
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Lance R Parsons
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - S RaElle Jackson
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Katharine Goodwin
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Shawn M Davidson
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Matthew J McBride
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Department of Chemistry, Princeton University, Princeton, NJ, USA
| | - Andrew E Webb
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Kennedy S Omufwoko
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Nikki Van Dorp
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
| | - Mauricio Fernández Otárola
- Biodiversity and Tropical Ecology Research Center (CIBET) and School of Biology, University of Costa Rica, San José, Costa Rica
| | - Melanie Pham
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Arina D Omer
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - David Weisz
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Joshua Schraiber
- Department of Biology, Temple University, Philadelphia, PA, USA
- Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA, USA
| | - Fernando Villanea
- Department of Biology, Temple University, Philadelphia, PA, USA
- Department of Anthropology, University of Colorado Boulder, Boulder, CO, USA
| | - William T Wcislo
- Smithsonian Tropical Research Institute, Panama City, Republic of Panama
| | - Robert J Paxton
- Institute of Biology, Martin-Luther University Halle-Wittenberg, Halle, Germany
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany
| | - Brendan G Hunt
- Department of Entomology, University of Georgia, Athens, GA, USA
| | - Erez Lieberman Aiden
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
| | - Sarah D Kocher
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA.
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
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168
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Zeighami Y, Bakken TE, Nickl-Jockschat T, Peterson Z, Jegga AG, Miller JA, Schulkin J, Evans AC, Lein ES, Hawrylycz M. A comparison of anatomic and cellular transcriptome structures across 40 human brain diseases. PLoS Biol 2023; 21:e3002058. [PMID: 37079537 PMCID: PMC10118126 DOI: 10.1371/journal.pbio.3002058] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 03/02/2023] [Indexed: 04/21/2023] Open
Abstract
Genes associated with risk for brain disease exhibit characteristic expression patterns that reflect both anatomical and cell type relationships. Brain-wide transcriptomic patterns of disease risk genes provide a molecular-based signature, based on differential co-expression, that is often unique to that disease. Brain diseases can be compared and aggregated based on the similarity of their signatures which often associates diseases from diverse phenotypic classes. Analysis of 40 common human brain diseases identifies 5 major transcriptional patterns, representing tumor-related, neurodegenerative, psychiatric and substance abuse, and 2 mixed groups of diseases affecting basal ganglia and hypothalamus. Further, for diseases with enriched expression in cortex, single-nucleus data in the middle temporal gyrus (MTG) exhibits a cell type expression gradient separating neurodegenerative, psychiatric, and substance abuse diseases, with unique excitatory cell type expression differentiating psychiatric diseases. Through mapping of homologous cell types between mouse and human, most disease risk genes are found to act in common cell types, while having species-specific expression in those types and preserving similar phenotypic classification within species. These results describe structural and cellular transcriptomic relationships of disease risk genes in the adult brain and provide a molecular-based strategy for classifying and comparing diseases, potentially identifying novel disease relationships.
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Affiliation(s)
- Yashar Zeighami
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, Canada
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Trygve E. Bakken
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, Neuroscience and Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa, United States of America
| | - Zeru Peterson
- Department of Psychiatry, Neuroscience and Pharmacology, Iowa Neuroscience Institute, University of Iowa, Iowa City, Iowa, United States of America
| | - Anil G. Jegga
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, United States of America
- Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, United States of America
| | - Jeremy A. Miller
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Jay Schulkin
- Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington, United States of America
| | - Alan C. Evans
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Ed S. Lein
- Allen Institute for Brain Science, Seattle, Washington, United States of America
| | - Michael Hawrylycz
- Allen Institute for Brain Science, Seattle, Washington, United States of America
- University of Washington, Department of Genome Sciences, Seattle, Washington, United States of America
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169
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Zhang N, Zhang H, Liu Z, Dai Z, Wu W, Zhou R, Li S, Wang Z, Liang X, Wen J, Zhang X, Zhang B, Ouyang S, Zhang J, Luo P, Li X, Cheng Q. An artificial intelligence network-guided signature for predicting outcome and immunotherapy response in lung adenocarcinoma patients based on 26 machine learning algorithms. Cell Prolif 2023; 56:e13409. [PMID: 36822595 PMCID: PMC10068958 DOI: 10.1111/cpr.13409] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 12/27/2022] [Accepted: 01/12/2023] [Indexed: 02/25/2023] Open
Abstract
The immune cells play an increasingly vital role in influencing the proliferation, progression, and metastasis of lung adenocarcinoma (LUAD) cells. However, the potential of immune cells' specific genes-based model remains largely unknown. In the current study, by analysing single-cell RNA sequencing (scRNA-seq) data and bulk RNA sequencing data, the tumour-infiltrating immune cell (TIIC) associated signature was developed based on a total of 26 machine learning (ML) algorithms. As a result, the TIIC signature score could predict survival outcomes of LUAD patients across five independent datasets. The TIIC signature score showed superior performance to 168 previously established signatures in LUAD. Moreover, the TIIC signature score developed by the immunofluorescence staining of the tissue array of LUAD patients showed a prognostic value. Our research revealed a solid connection between TIIC signature score and tumour immunity as well as metabolism. Additionally, it has been discovered that the TIIC signature score can forecast genomic change, chemotherapeutic drug susceptibility, and-most significantly-immunotherapeutic response. As a newly demonstrated biomarker, the TIIC signature score facilitated the selection of the LUAD population who would benefit from future clinical stratification.
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Affiliation(s)
- Nan Zhang
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- College of Life Science and TechnologyHuazhong University of Science and TechnologyWuhanChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Hao Zhang
- Department of Neurosurgery, The Second Affiliated HospitalChongqing Medical UniversityChongqingChina
| | - Zaoqu Liu
- Department of Interventional RadiologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Wantao Wu
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
- Department of Oncology, Xiangya HospitalCentral South UniversityChangshaChina
| | - Ran Zhou
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and HealthUniversity of ManchesterManchesterUK
| | - Shuyu Li
- Department of Thyroid and Breast Surgery, Tongji HospitalTongji Medical College of Huazhong University of Science and TechnologyWuhanChina
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Xisong Liang
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Jie Wen
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Xun Zhang
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Bo Zhang
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Sirui Ouyang
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
| | - Jian Zhang
- Department of Oncology, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Peng Luo
- Department of Oncology, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Xizhe Li
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
- Department of Thoracic Surgery, Xiangya HospitalCentral South UniversityChangshaChina
- Hunan Engineering Research Center for Pulmonary Nodules Precise Diagnosis & TreatmentChangshaChina
| | - Quan Cheng
- Department of Neurosurgery, Xiangya HospitalCentral South UniversityChangshaChina
- National Clinical Research Center for Geriatric Disorders, Xiangya HospitalCentral South UniversityChangshaChina
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170
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Oh MR, Jung SJ, Chae SW, Park BH, Lee SO. Lycium chinense Miller fruit extract lowers liver enzyme levels in subjects with mild hepatic dysfunction: a randomized, double-blind, placebo-controlled clinical trial. Eur J Nutr 2023; 62:1415-1425. [PMID: 36629892 DOI: 10.1007/s00394-022-03075-8] [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: 08/09/2022] [Accepted: 12/12/2022] [Indexed: 01/12/2023]
Abstract
PURPOSE In our previous study, we showed that Lycium chinense Miller fruit extract (LFE) exerted hepatoprotective effects in mice. In the current study, we examined the effect of LFE on liver enzyme levels in subjects with mild hepatic dysfunction. METHODS A total of 90 subjects, aged 19 to 70 years old, with abnormal alanine aminotransferase (ALT) levels, were randomly placed into either an LFE (n = 45) treatment group or a placebo group (n = 45). During the 12-week clinical trial, subjects in each group received either LFE or placebo capsules, and were instructed to take four tablets per day (1760 mg/day). The primary outcome of the study was the changes of ALT and γ-glutamyltransferase (GGT) levels in each subject. The safety of LFE supplementation was assessed and adverse events were recorded. RESULTS LFE supplementation for 12 weeks resulted in a significant reduction of ALT (P = 0.0498) and GGT (P = 0.0368) levels in comparison to the placebo. No clinically significant changes were observed in any safety parameters. CONCLUSION These results suggest that LFE can be applied to subjects with mild hepatic dysfunction with no possible side effects. TRIAL REGISTRATION This study was registered at the Clinical Research Information Service (CRIS) as no. KCT0003985.
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Affiliation(s)
- Mi-Ra Oh
- Clinical Trial Center for Functional Foods, Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea
| | - Su-Jin Jung
- Clinical Trial Center for Functional Foods, Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea
- Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea
| | - Soo-Wan Chae
- Clinical Trial Center for Functional Foods, Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea
- Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea
| | - Byung-Hyun Park
- Department of Biochemistry and Research Institute for Endocrine Sciences, Jeonbuk National University Medical School, Jeonju, Jeonbuk, 54896, Republic of Korea.
| | - Seung-Ok Lee
- Clinical Trial Center for Functional Foods, Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea.
- Biomedical Research Institute of Jeonbuk National University Hospital, Jeonju, Jeonbuk, 54907, Republic of Korea.
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Jeonbuk National University Medical School, Jeonju, Jeonbuk, 54896, Republic of Korea.
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171
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SMRT and Illumina sequencing provide insights into mechanisms of lignin and terpenoids biosynthesis in Pinus massoniana Lamb. Int J Biol Macromol 2023; 232:123267. [PMID: 36657535 DOI: 10.1016/j.ijbiomac.2023.123267] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/28/2022] [Accepted: 01/10/2023] [Indexed: 01/18/2023]
Abstract
Wood and oleoresin are important industrial raw materials with high economic value; however, their molecular formation and biosynthesis mechanisms in different tissues of Pinus massoniana remain unexplored. Therefore, we used single-molecule real-time sequencing technology (SMRT) and Illumina RNA sequencing to establish a transcriptome dataset and explore the expression pattern of genes related to secondary metabolites involved in wood formation and oleoresin biosynthesis in six different P. massoniana tissues. In total, 63.58 Gb of polymerase reads were obtained, including 41,407 isoforms with an average length of 1822 bp. We identified 3939 and 8785 isoforms and 161 and 481 transcription factors with tissue expression specificity and in the reproductive and vegetative organs, respectively. Eighty isoforms were annotated as cellulose synthases and 224 isoforms involved in lignin biosynthesis were enriched. Additionally, we identified 217 isoforms involved in the terpenoid biosynthesis pathway, with needles having the most tissue-specific genes for terpenoid biosynthesis. Some isoforms related to lignin biosynthesis were highly expressed in the xylem, according to the results of transcriptome sequencing and real-time quantitative reverse-transcription polymerase chain reaction. Our research confirmed the advantages of SMRT sequencing and provided valuable information for the transcriptional annotation of P. massoniana, which will be beneficial for producing better raw wood and oleoresin materials.
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172
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Stevanovic M, Kovacevic-Grujicic N, Petrovic I, Drakulic D, Milivojevic M, Mojsin M. Crosstalk between SOX Genes and Long Non-Coding RNAs in Glioblastoma. Int J Mol Sci 2023; 24:ijms24076392. [PMID: 37047365 PMCID: PMC10094781 DOI: 10.3390/ijms24076392] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 03/17/2023] [Accepted: 03/23/2023] [Indexed: 03/31/2023] Open
Abstract
Glioblastoma (GBM) continues to be the most devastating primary brain malignancy. Despite significant advancements in understanding basic GBM biology and enormous efforts in developing new therapeutic approaches, the prognosis for most GBM patients remains poor with a median survival time of 15 months. Recently, the interplay between the SOX (SRY-related HMG-box) genes and lncRNAs (long non-coding RNAs) has become the focus of GBM research. Both classes of molecules have an aberrant expression in GBM and play essential roles in tumor initiation, progression, therapy resistance, and recurrence. In GBM, SOX and lncRNAs crosstalk through numerous functional axes, some of which are part of the complex transcriptional and epigenetic regulatory mechanisms. This review provides a systematic summary of current literature data on the complex interplay between SOX genes and lncRNAs and represents an effort to underscore the effects of SOX/lncRNA crosstalk on the malignant properties of GBM cells. Furthermore, we highlight the significance of this crosstalk in searching for new biomarkers and therapeutic approaches in GBM treatment.
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173
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Yao Z, van Velthoven CTJ, Kunst M, Zhang M, McMillen D, Lee C, Jung W, Goldy J, Abdelhak A, Baker P, Barkan E, Bertagnolli D, Campos J, Carey D, Casper T, Chakka AB, Chakrabarty R, Chavan S, Chen M, Clark M, Close J, Crichton K, Daniel S, Dolbeare T, Ellingwood L, Gee J, Glandon A, Gloe J, Gould J, Gray J, Guilford N, Guzman J, Hirschstein D, Ho W, Jin K, Kroll M, Lathia K, Leon A, Long B, Maltzer Z, Martin N, McCue R, Meyerdierks E, Nguyen TN, Pham T, Rimorin C, Ruiz A, Shapovalova N, Slaughterbeck C, Sulc J, Tieu M, Torkelson A, Tung H, Cuevas NV, Wadhwani K, Ward K, Levi B, Farrell C, Thompson CL, Mufti S, Pagan CM, Kruse L, Dee N, Sunkin SM, Esposito L, Hawrylycz MJ, Waters J, Ng L, Smith KA, Tasic B, Zhuang X, Zeng H. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.06.531121. [PMID: 37034735 PMCID: PMC10081189 DOI: 10.1101/2023.03.06.531121] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
The mammalian brain is composed of millions to billions of cells that are organized into numerous cell types with specific spatial distribution patterns and structural and functional properties. An essential step towards understanding brain function is to obtain a parts list, i.e., a catalog of cell types, of the brain. Here, we report a comprehensive and high-resolution transcriptomic and spatial cell type atlas for the whole adult mouse brain. The cell type atlas was created based on the combination of two single-cell-level, whole-brain-scale datasets: a single-cell RNA-sequencing (scRNA-seq) dataset of ~7 million cells profiled, and a spatially resolved transcriptomic dataset of ~4.3 million cells using MERFISH. The atlas is hierarchically organized into five nested levels of classification: 7 divisions, 32 classes, 306 subclasses, 1,045 supertypes and 5,200 clusters. We systematically analyzed the neuronal, non-neuronal, and immature neuronal cell types across the brain and identified a high degree of correspondence between transcriptomic identity and spatial specificity for each cell type. The results reveal unique features of cell type organization in different brain regions, in particular, a dichotomy between the dorsal and ventral parts of the brain: the dorsal part contains relatively fewer yet highly divergent neuronal types, whereas the ventral part contains more numerous neuronal types that are more closely related to each other. We also systematically characterized cell-type specific expression of neurotransmitters, neuropeptides, and transcription factors. The study uncovered extraordinary diversity and heterogeneity in neurotransmitter and neuropeptide expression and co-expression patterns in different cell types across the brain, suggesting they mediate a myriad of modes of intercellular communications. Finally, we found that transcription factors are major determinants of cell type classification in the adult mouse brain and identified a combinatorial transcription factor code that defines cell types across all parts of the brain. The whole-mouse-brain transcriptomic and spatial cell type atlas establishes a benchmark reference atlas and a foundational resource for deep and integrative investigations of cell type and circuit function, development, and evolution of the mammalian brain.
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Affiliation(s)
- Zizhen Yao
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Meng Zhang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | | | - Changkyu Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Won Jung
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Pamela Baker
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Eliza Barkan
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Daniel Carey
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Min Chen
- University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jennie Close
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Scott Daniel
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tim Dolbeare
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - James Gee
- University of Pennsylvania, Philadelphia, PA, USA
| | | | - Jessica Gloe
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - James Gray
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Windy Ho
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Kelly Jin
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Kanan Lathia
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Arielle Leon
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Brian Long
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Zoe Maltzer
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Naomi Martin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Rachel McCue
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | | | | | | | - Josef Sulc
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Herman Tung
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Katelyn Ward
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Boaz Levi
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Shoaib Mufti
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Lauren Kruse
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Jack Waters
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
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174
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Liu Z, Zhang Y, Weng S, Xu H, Han X. Implications of pseudogenes for the prognosis of hepatocellular carcinoma. Clin Transl Med 2023; 13:e1195. [PMID: 36750350 PMCID: PMC9905005 DOI: 10.1002/ctm2.1195] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 01/17/2023] [Accepted: 01/20/2023] [Indexed: 02/09/2023] Open
Affiliation(s)
- Zaoqu Liu
- Department of Interventional RadiologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Interventional Institute of Zhengzhou UniversityZhengzhouChina
- Interventional Treatment and Clinical Research Center of Henan ProvinceZhengzhouChina
| | - Yuyuan Zhang
- Department of Interventional RadiologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Siyuan Weng
- Department of Interventional RadiologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Hui Xu
- Department of Interventional RadiologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
| | - Xinwei Han
- Department of Interventional RadiologyThe First Affiliated Hospital of Zhengzhou UniversityZhengzhouChina
- Interventional Institute of Zhengzhou UniversityZhengzhouChina
- Interventional Treatment and Clinical Research Center of Henan ProvinceZhengzhouChina
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175
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Li J, Shen J, Wang R, Chen Y, Zhang T, Wang H, Guo C, Qi J. The nearly complete assembly of the Cercis chinensis genome and Fabaceae phylogenomic studies provide insights into new gene evolution. PLANT COMMUNICATIONS 2023; 4:100422. [PMID: 35957520 PMCID: PMC9860166 DOI: 10.1016/j.xplc.2022.100422] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 08/02/2022] [Accepted: 08/05/2022] [Indexed: 05/27/2023]
Abstract
Fabaceae is a large family of angiosperms with high biodiversity that contains a variety of economically important crops and model plants for the study of biological nitrogen fixation. Polyploidization events have been extensively studied in some Fabaceae plants, but the occurrence of new genes is still concealed, owing to a lack of genomic information on certain species of the basal clade of Fabaceae. Cercis chinensis (Cercidoideae) is one such species; it diverged earliest from Fabaceae and is essential for phylogenomic studies and new gene predictions in Fabaceae. To facilitate genomic studies on Fabaceae, we performed genome sequencing of C. chinensis and obtained a 352.84 Mb genome, which was further assembled into seven pseudochromosomes with 30 612 predicted protein-coding genes. Compared with other legume genomes, that of C. chinensis exhibits no lineage-specific polyploidization event. Further phylogenomic analyses of 22 legumes and 11 other angiosperms revealed that many gene families are lineage specific before and after the diversification of Fabaceae. Among them, dozens of genes are candidates for new genes that have evolved from intergenic regions and are thus regarded as de novo-originated genes. They differ significantly from established genes in coding sequence length, exon number, guanine-cytosine content, and expression patterns among tissues. Functional analysis revealed that many new genes are related to asparagine metabolism. This study represents an important advance in understanding the evolutionary pattern of new genes in legumes and provides a valuable resource for plant phylogenomic studies.
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Affiliation(s)
- Jinglong Li
- State Key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Jingting Shen
- State Key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Rui Wang
- State Key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Yamao Chen
- State Key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Taikui Zhang
- State Key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Haifeng Wang
- College of Agriculture, Guangxi University, Nanning 530004, China
| | - Chunce Guo
- Jiangxi Provincial Key Laboratory for Bamboo Germplasm Resources and Utilization, Forestry College, Jiangxi Agricultural University, Nanchang 330045, China
| | - Ji Qi
- State Key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China.
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176
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Jung SC, Zhou T, Ko EA. Age-dependent expression of ion channel genes in rat. THE KOREAN JOURNAL OF PHYSIOLOGY & PHARMACOLOGY : OFFICIAL JOURNAL OF THE KOREAN PHYSIOLOGICAL SOCIETY AND THE KOREAN SOCIETY OF PHARMACOLOGY 2023; 27:85-94. [PMID: 36575936 PMCID: PMC9806634 DOI: 10.4196/kjpp.2023.27.1.85] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 10/25/2022] [Accepted: 10/28/2022] [Indexed: 12/29/2022]
Abstract
Ion channels regulate a large number of cellular functions and their functional role in many diseases makes them potential therapeutic targets. Given their diverse distribution across multiple organs, the roles of ion channels, particularly in age-associated transcriptomic changes in specific organs, are yet to be fully revealed. Using RNA-seq data, we investigated the rat transcriptomic profiles of ion channel genes across 11 organs/tissues and 4 developmental stages in both sexes of Fischer 344 rats and identify tissue-specific and age-dependent changes in ion channel gene expression. Organ-enriched ion channel genes were identified. In particular, the brain showed higher tissue-specificity of ion channel genes, including Gabrd, Gabra6, Gabrg2, Grin2a, and Grin2b. Notably, age-dependent changes in ion channel gene expression were prominently observed in the thymus, including in Aqp1, Clcn4, Hvcn1, Itpr1, Kcng2, Kcnj11, Kcnn3, and Trpm2. Our comprehensive study of ion channel gene expression will serve as a primary resource for biological studies of aging-related diseases caused by abnormal ion channel functions.
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Affiliation(s)
- Sung-Cherl Jung
- Department of Physiology, School of Medicine, Jeju National University, Jeju 63243, Korea
| | - Tong Zhou
- Department of Physiology and Cell Biology, University of Nevada, Reno School of Medicine, Reno, NV 89557, USA
| | - Eun-A Ko
- Department of Physiology, School of Medicine, Jeju National University, Jeju 63243, Korea,Correspondence Eun-A Ko, E-mail:
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177
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Tao W, Li R, Li T, Li Z, Li Y, Cui L. The evolutionary patterns, expression profiles, and genetic diversity of expanded genes in barley. FRONTIERS IN PLANT SCIENCE 2023; 14:1168124. [PMID: 37180392 PMCID: PMC10171312 DOI: 10.3389/fpls.2023.1168124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/28/2023] [Indexed: 05/16/2023]
Abstract
Gene duplication resulting from whole-genome duplication (WGD), small-scale duplication (SSD), or unequal hybridization plays an important role in the expansion of gene families. Gene family expansion can also mediate species formation and adaptive evolution. Barley (Hordeum vulgare) is the world's fourth largest cereal crop, and it contains valuable genetic resources due to its ability to tolerate various types of environmental stress. In this study, 27,438 orthogroups in the genomes of seven Poaceae were identified, and 214 of them were significantly expanded in barley. The evolutionary rates, gene properties, expression profiles, and nucleotide diversity between expanded and non-expanded genes were compared. Expanded genes evolved more rapidly and experienced lower negative selection. Expanded genes, including their exons and introns, were shorter, they had fewer exons, their GC content was lower, and their first exons were longer compared with non-expanded genes. Codon usage bias was also lower for expanded genes than for non-expanded genes; the expression levels of expanded genes were lower than those of non-expanded genes, and the expression of expanded genes showed higher tissue specificity than that of non-expanded genes. Several stress-response-related genes/gene families were identified, and these genes could be used to breed barley plants with greater resistance to environmental stress. Overall, our analysis revealed evolutionary, structural, and functional differences between expanded and non-expanded genes in barley. Additional studies are needed to clarify the functions of the candidate genes identified in our study and evaluate their utility for breeding barley plants with greater stress resistance.
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Affiliation(s)
- Wenjing Tao
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi, China
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, Fujian, China
| | - Ruiying Li
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi, China
| | - Tingting Li
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi, China
| | - Zhimin Li
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi, China
| | - Yihan Li
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi, China
- *Correspondence: Yihan Li, ; Licao Cui,
| | - Licao Cui
- College of Bioscience and Engineering, Jiangxi Agricultural University, Nanchang, Jiangxi, China
- *Correspondence: Yihan Li, ; Licao Cui,
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178
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The sheep miRNAome: Characterization and distribution of miRNAs in 21 tissues. Gene X 2023; 851:146998. [DOI: 10.1016/j.gene.2022.146998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 10/10/2022] [Accepted: 10/18/2022] [Indexed: 11/06/2022] Open
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179
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Detecting macroevolutionary genotype-phenotype associations using error-corrected rates of protein convergence. Nat Ecol Evol 2023; 7:155-170. [PMID: 36604553 PMCID: PMC9834058 DOI: 10.1038/s41559-022-01932-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 10/12/2022] [Indexed: 01/07/2023]
Abstract
On macroevolutionary timescales, extensive mutations and phylogenetic uncertainty mask the signals of genotype-phenotype associations underlying convergent evolution. To overcome this problem, we extended the widely used framework of non-synonymous to synonymous substitution rate ratios and developed the novel metric ωC, which measures the error-corrected convergence rate of protein evolution. While ωC distinguishes natural selection from genetic noise and phylogenetic errors in simulation and real examples, its accuracy allows an exploratory genome-wide search of adaptive molecular convergence without phenotypic hypothesis or candidate genes. Using gene expression data, we explored over 20 million branch combinations in vertebrate genes and identified the joint convergence of expression patterns and protein sequences with amino acid substitutions in functionally important sites, providing hypotheses on undiscovered phenotypes. We further extended our method with a heuristic algorithm to detect highly repetitive convergence among computationally non-trivial higher-order phylogenetic combinations. Our approach allows bidirectional searches for genotype-phenotype associations, even in lineages that diverged for hundreds of millions of years.
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180
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Long X, Charlesworth D, Qi J, Wu R, Chen M, Wang Z, Xu L, Fu H, Zhang X, Chen X, He L, Zheng L, Huang Z, Zhou Q. Independent Evolution of Sex Chromosomes and Male Pregnancy-Related Genes in Two Seahorse Species. Mol Biol Evol 2022; 40:6964685. [PMID: 36578180 PMCID: PMC9851323 DOI: 10.1093/molbev/msac279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 10/14/2022] [Accepted: 12/22/2022] [Indexed: 12/30/2022] Open
Abstract
Unlike birds and mammals, many teleosts have homomorphic sex chromosomes, and changes in the chromosome carrying the sex-determining locus, termed "turnovers", are common. Recent turnovers allow studies of several interesting questions. One question is whether the new sex-determining regions evolve to become completely non-recombining, and if so, how and why. Another is whether (as predicted) evolutionary changes that benefit one sex accumulate in the newly sex-linked region. To study these questions, we analyzed the genome sequences of two seahorse species of the Syngnathidae, a fish group in which many species evolved a unique structure, the male brood pouch. We find that both seahorse species have XY sex chromosome systems, but their sex chromosome pairs are not homologs, implying that at least one turnover event has occurred. The Y-linked regions occupy 63.9% and 95.1% of the entire sex chromosome of the two species and do not exhibit extensive sequence divergence with their X-linked homologs. We find evidence for occasional recombination between the extant sex chromosomes that may account for their homomorphism. We argue that these Y-linked regions did not evolve by recombination suppression after the turnover, but by the ancestral nature of the low crossover rates in these chromosome regions. With such an ancestral crossover landscape, a turnover can instantly create an extensive Y-linked region. Finally, we test for adaptive evolution of male pouch-related genes after they became Y-linked in the seahorse.
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Affiliation(s)
- Xin Long
- MOE Laboratory of Biosystems Homeostasis and Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou 310058, China,Research Center for Intelligent Computing Platforms, Zhejiang Lab, Hangzhou 311100, China
| | - Deborah Charlesworth
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, West Mains Road, Edinburgh EH9 3LF, UK
| | - Jianfei Qi
- Department of Aquaculture, Fisheries Research Institute of Fujian, Xiamen 361013, China
| | - Ruiqiong Wu
- Fujian Key Laboratory of Developmental and Neural Biology & Southern Center for Biomedical Research, College of Life Sciences, Fujian Normal University, Fuzhou, Fujian, China
| | - Meiling Chen
- Fujian Key Laboratory of Developmental and Neural Biology & Southern Center for Biomedical Research, College of Life Sciences, Fujian Normal University, Fuzhou, Fujian, China
| | - Zongji Wang
- MOE Laboratory of Biosystems Homeostasis and Protection and Zhejiang Provincial Key Laboratory for Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou 310058, China
| | - Luohao Xu
- MOE Key Laboratory of Freshwater Fish Reproduction and Development, Key Laboratory of Aquatic Science of Chongqing, School of Life Sciences, Southwest University, Chongqing 400715, China
| | - Honggao Fu
- Fujian Key Laboratory of Developmental and Neural Biology & Southern Center for Biomedical Research, College of Life Sciences, Fujian Normal University, Fuzhou, Fujian, China
| | - Xueping Zhang
- Fujian Key Laboratory of Developmental and Neural Biology & Southern Center for Biomedical Research, College of Life Sciences, Fujian Normal University, Fuzhou, Fujian, China
| | - Xinxin Chen
- Department of Aquaculture, Fisheries Research Institute of Fujian, Xiamen 361013, China
| | - Libin He
- Department of Aquaculture, Fisheries Research Institute of Fujian, Xiamen 361013, China
| | | | | | - Qi Zhou
- Corresponding authors: E-mails: ; ;
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181
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Wu S, Zhang Q, Zhang W, Huang W, Kong Q, Liu Q, Li W, Zou X, Liu CM, Yan S. Linolenic Acid-Derived Oxylipins Inhibit Aflatoxin Biosynthesis in Aspergillus flavus through Activation of Imizoquin Biosynthesis. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2022; 70:15928-15944. [PMID: 36508213 PMCID: PMC9785051 DOI: 10.1021/acs.jafc.2c06230] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/24/2022] [Accepted: 11/30/2022] [Indexed: 06/17/2023]
Abstract
Oxylipins play important signaling roles in aflatoxin (AF) biosynthesis in Aspergillus flavus. We previously showed that exogenous supply of autoxidated linolenic acid (AL) inhibited AF biosynthesis in A. flavus via oxylipins, but the molecular mechanism is still unknown. Here, we performed multiomics analyses of A. flavus grown in media with or without AL. Targeted metabolite analyses and quantitative reverse transcription (qRT)-polymerase chain reaction (PCR) showed that the imizoquin (IMQ) biosynthetic pathway was distinctly upregulated in the presence of AL. 13C-glucose labeling confirmed in parallel that the tricarboxylic acid cycle was also enhanced by AL, consistent with observed increases in mycelial growth. Moreover, we integrated thermal proteome profiling and molecular dynamics simulations to identify a potential receptor of AL; AL was found to interact with a transporter (ImqJ) located in the IMQ gene cluster, primarily through hydrophobic interactions. Further analyses of strains with an IMQ pathway transcription factor overexpressed or knocked out confirmed that this pathway was critical for AL-mediated inhibition of AF biosynthesis. Comparison of 22 assembled A. flavus and Aspergillus oryzae genomes showed that genes involved in the IMQ pathway were positively selected in A. oryzae. Taken together, the results of our study provide novel insights into oxylipin-mediated regulation of AF biosynthesis and suggest potential methods for preventing AF contamination of crops.
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Affiliation(s)
- Shaowen Wu
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Qunjie Zhang
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
- Institution
of Genomics and Bioinformatics, South China
Agricultural University, Guangzhou510642, China
| | - Wenyang Zhang
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Wenjie Huang
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Qian Kong
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Qinjian Liu
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Wenyan Li
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Xinlu Zou
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
| | - Chun-Ming Liu
- Key
Laboratory of Plant Molecular Physiology, Institute of Botany, Chinese Academy of Sciences, 20 Nanxincun, Fragrant Hill, Beijing100093, China
| | - Shijuan Yan
- Guangdong
Key Laboratory for Crop Germplasm Resources Preservation and Utilization,
Agro-biological Gene Research Center, Guangdong
Academy of Agricultural Sciences, Guangzhou510640, China
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182
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Metivier JC, Chain FJJ. Diversity in Expression Biases of Lineage-Specific Genes During Development and Anhydrobiosis Among Tardigrade Species. Evol Bioinform Online 2022; 18:11769343221140277. [PMID: 36578471 PMCID: PMC9791283 DOI: 10.1177/11769343221140277] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 10/27/2022] [Indexed: 12/24/2022] Open
Abstract
Lineage-specific genes can contribute to the emergence and evolution of novel traits and adaptations. Tardigrades are animals that have adapted to tolerate extreme conditions by undergoing a form of cryptobiosis called anhydrobiosis, a physical transformation to an inactive desiccated state. While studies to understand the genetics underlying the interspecies diversity in anhydrobiotic transitions have identified tardigrade-specific genes and family expansions involved in this process, the contributions of species-specific genes to the variation in tardigrade development and cryptobiosis are less clear. We used previously published transcriptomes throughout development and anhydrobiosis (5 embryonic stages, 7 juvenile stages, active adults, and tun adults) to assess the transcriptional biases of different classes of genes between 2 tardigrade species, Hypsibius exemplaris and Ramazzottius varieornatus. We also used the transcriptomes of 2 other tardigrades, Echiniscoides sigismundi and Richtersius coronifer, and data from 3 non-tardigrade species (Adenita vaga, Drosophila melanogaster, and Caenorhabditis elegans) to help identify lineage-specific genes. We found that lineage-specific genes have generally low and narrow expression but are enriched among biased genes in different stages of development depending on the species. Biased genes tend to be specific to early and late development, but there is little overlap in functional enrichment of biased genes between species. Gene expansions in the 2 tardigrades also involve families with different functions despite homologous genes being expressed during anhydrobiosis in both species. Our results demonstrate the interspecific variation in transcriptional contributions and biases of lineage-specific genes during development and anhydrobiosis in 2 tardigrades.
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Affiliation(s)
| | - Frédéric J J Chain
- Frédéric J J Chain, Department of Biological Sciences, University of Massachusetts Lowell, One University Ave, Lowell, MA 01854, USA.
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183
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Li S, Zhang J, Zhang L, Fang X, Luo J, An H, Zhang X. Genome-wide identification and comprehensive analysis reveal potential roles of long non-coding RNAs in fruit development of southern highbush blueberry ( Vaccinium corymbosum L.). FRONTIERS IN PLANT SCIENCE 2022; 13:1078085. [PMID: 36582646 PMCID: PMC9792668 DOI: 10.3389/fpls.2022.1078085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 11/21/2022] [Indexed: 06/17/2023]
Abstract
Introduction Blueberries have a high antioxidant content and are produced as healthy food worldwide. Long non-coding RNAs (lncRNAs) are a type of regulatory RNAs that play a variety of roles in plants. Nonetheless, information on lncRNAs and their functions during blueberry fruit development is scarce in public databases. Methods In the present study, we performed genome-wide identification of lncRNAs in a southern highbush blueberry using strand-specific RNA sequencing (ssRNA-Seq). Differentially expressed lncRNAs (DE-lncRNAs) and their potential target genes were analyzed at four stages of fruit development. Cis-regulatory DE-lncRNAs were predicted using co-localization analysis. Results These findings included a total of 25,036 lncRNAs from 17,801 loci. Blueberry lncRNAs had shorter transcript lengths, smaller open reading frame (ORF) sizes, fewer exons, and fewer isoforms than protein-coding RNAs, as well as lower expression levels and higher stage-specificity during fruit development. A total of 105 DE-lncRNAs were identified among the comparison group of PAD vs. CUP, 443 DE-lncRNAs were detected when comparing CUP with PINK fruits, and 285 DE-lncRNAs were revealed when comparing PINK and BLUE fruits. According to Kyoto Encyclopedia of Genes and Genomes annotation, target genes of DE-lncRNAs were primarily enriched in the "Autophagy-other", "DNA replication", "Endocytosis", 'photosynthesis' and 'chlorophyll metabolism' pathways, suggesting that lncRNAs may pay potential roles in fruit expansion and ripening. Moreover, several lncRNAs have been proposed as cis-regulators of the key genes involved in flavonoid biosynthesis. MSTRG.107242.6, and its putative target gene, BTB/POZ and TAZ domain-containing protein, might play critical roles in anthocyanin accumulation in blueberries. Discussion These findings highlight the regulatory function of lncRNAs and aid in elucidating the molecular mechanism underlying blueberry fruit growth.
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Affiliation(s)
- Shuigen Li
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Jiaying Zhang
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Liqing Zhang
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Xianping Fang
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Jun Luo
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Haishan An
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Xueying Zhang
- Forest and Fruit Tree Research Institute, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Shanghai Key Lab of Protected Horticultural Technology, Shanghai Academy of Agricultural Sciences, Shanghai, China
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184
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Xu R, Martelossi J, Smits M, Iannello M, Peruzza L, Babbucci M, Milan M, Dunham JP, Breton S, Milani L, Nuzhdin SV, Bargelloni L, Passamonti M, Ghiselli F. Multi-tissue RNA-Seq Analysis and Long-read-based Genome Assembly Reveal Complex Sex-specific Gene Regulation and Molecular Evolution in the Manila Clam. Genome Biol Evol 2022; 14:6889380. [PMID: 36508337 PMCID: PMC9803972 DOI: 10.1093/gbe/evac171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 11/26/2022] [Accepted: 11/30/2022] [Indexed: 12/14/2022] Open
Abstract
The molecular factors and gene regulation involved in sex determination and gonad differentiation in bivalve molluscs are unknown. It has been suggested that doubly uniparental inheritance (DUI) of mitochondria may be involved in these processes in species such as the ubiquitous and commercially relevant Manila clam, Ruditapes philippinarum. We present the first long-read-based de novo genome assembly of a Manila clam, and a RNA-Seq multi-tissue analysis of 15 females and 15 males. The highly contiguous genome assembly was used as reference to investigate gene expression, alternative splicing, sequence evolution, tissue-specific co-expression networks, and sexual contrasting SNPs. Differential expression (DE) and differential splicing (DS) analyses revealed sex-specific transcriptional regulation in gonads, but not in somatic tissues. Co-expression networks revealed complex gene regulation in gonads, and genes in gonad-associated modules showed high tissue specificity. However, male gonad-associated modules showed contrasting patterns of sequence evolution and tissue specificity. One gene set was related to the structural organization of male gametes and presented slow sequence evolution but high pleiotropy, whereas another gene set was enriched in reproduction-related processes and characterized by fast sequence evolution and tissue specificity. Sexual contrasting SNPs were found in genes overrepresented in mitochondrial-related functions, providing new candidates for investigating the relationship between mitochondria and sex in DUI species. Together, these results increase our understanding of the role of DE, DS, and sequence evolution of sex-specific genes in an understudied taxon. We also provide resourceful genomic data for studies regarding sex diagnosis and breeding in bivalves.
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Affiliation(s)
- Ran Xu
- Corresponding authors: E-mail: (R.X.); E-mail: (F.G.)
| | | | | | | | - Luca Peruzza
- Department of Comparative Biomedicine and Food Science, University of Padova, Padova, Italy
| | - Massimiliano Babbucci
- Department of Comparative Biomedicine and Food Science, University of Padova, Padova, Italy
| | - Massimo Milan
- Department of Comparative Biomedicine and Food Science, University of Padova, Padova, Italy
| | - Joseph P Dunham
- Program in Molecular and Computational Biology, University of Southern California, Los Angeles, CA, USA,SeqOnce Biosciences Inc., Pasadena, CA, USA
| | - Sophie Breton
- Department of Biological Sciences, University of Montreal, Montreal, Canada
| | - Liliana Milani
- Department of Biological, Geological, and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Sergey V Nuzhdin
- Program in Molecular and Computational Biology, University of Southern California, Los Angeles, CA, USA
| | - Luca Bargelloni
- Department of Comparative Biomedicine and Food Science, University of Padova, Padova, Italy
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185
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Lüleci HB, Yılmaz A. Robust and rigorous identification of tissue-specific genes by statistically extending tau score. BioData Min 2022; 15:31. [PMID: 36494766 PMCID: PMC9733102 DOI: 10.1186/s13040-022-00315-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 11/11/2022] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVES In this study, we aimed to identify tissue-specific genes for various human tissues/organs more robustly and rigorously by extending the tau score algorithm. INTRODUCTION Tissue-specific genes are a class of genes whose functions and expressions are preferred in one or several tissues restrictedly. Identification of tissue-specific genes is essential for discovering multi-cellular biological processes such as tissue-specific molecular regulations, tissue development, physiology, and the pathogenesis of tissue-associated diseases. MATERIALS AND METHODS Gene expression data derived from five large RNA sequencing (RNA-seq) projects, spanning 96 different human tissues, were retrieved from ArrayExpress and ExpressionAtlas. The first step is categorizing genes using significant filters and tau score as a specificity index. After calculating tau for each gene in all datasets separately, statistical distance from the maximum expression level was estimated using a new meaningful procedure. Specific expression of a gene in one or several tissues was calculated after the integration of tau and statistical distance estimation, which is called as extended tau approach. Obtained tissue-specific genes for 96 different human tissues were functionally annotated, and some comparisons were carried out to show the effectiveness of the extended tau method. RESULTS AND DISCUSSION Categorization of genes based on expression level and identification of tissue-specific genes for a large number of tissues/organs were executed. Genes were successfully assigned to multiple tissues by generating the extended tau approach as opposed to the original tau score, which can assign tissue specificity to single tissue only.
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Affiliation(s)
- Hatice Büşra Lüleci
- grid.448834.70000 0004 0595 7127Department of Bioengineering, Gebze Technical University, Kocaeli, Turkey
| | - Alper Yılmaz
- grid.38575.3c0000 0001 2337 3561Department of Bioengineering, Yildiz Technical University, Istanbul, Turkey
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186
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Ma C, Li C, Ma H, Yu D, Zhang Y, Zhang D, Su T, Wu J, Wang X, Zhang L, Chen CL, Zhang YE. Pan-cancer surveys indicate cell cycle-related roles of primate-specific genes in tumors and embryonic cerebrum. Genome Biol 2022; 23:251. [PMID: 36474250 PMCID: PMC9724437 DOI: 10.1186/s13059-022-02821-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 11/24/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Despite having been extensively studied, it remains largely unclear why humans bear a particularly high risk of cancer. The antagonistic pleiotropy hypothesis predicts that primate-specific genes (PSGs) tend to promote tumorigenesis, while the molecular atavism hypothesis predicts that PSGs involved in tumors may represent recently derived duplicates of unicellular genes. However, these predictions have not been tested. RESULTS By taking advantage of pan-cancer genomic data, we find the upregulation of PSGs across 13 cancer types, which is facilitated by copy-number gain and promoter hypomethylation. Meta-analyses indicate that upregulated PSGs (uPSGs) tend to promote tumorigenesis and to play cell cycle-related roles. The cell cycle-related uPSGs predominantly represent derived duplicates of unicellular genes. We prioritize 15 uPSGs and perform an in-depth analysis of one unicellular gene-derived duplicate involved in the cell cycle, DDX11. Genome-wide screening data and knockdown experiments demonstrate that DDX11 is broadly essential across cancer cell lines. Importantly, non-neutral amino acid substitution patterns and increased expression indicate that DDX11 has been under positive selection. Finally, we find that cell cycle-related uPSGs are also preferentially upregulated in the highly proliferative embryonic cerebrum. CONCLUSIONS Consistent with the predictions of the atavism and antagonistic pleiotropy hypotheses, primate-specific genes, especially those PSGs derived from cell cycle-related genes that emerged in unicellular ancestors, contribute to the early proliferation of the human cerebrum at the cost of hitchhiking by similarly highly proliferative cancer cells.
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Affiliation(s)
- Chenyu Ma
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chunyan Li
- School of Engineering Medicine, Key Laboratory of Big Data-Based Precision Medicine (Ministry of Industry and Information Technology), and Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, 100191, China
| | - Huijing Ma
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Daqi Yu
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yufei Zhang
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- School of Life Sciences, Nanjing University, Nanjing, 210093, China
| | - Dan Zhang
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Tianhan Su
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jianmin Wu
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Center for Cancer Bioinformatics, Peking University Cancer Hospital & Institute, Beijing, 100142, China
| | - Xiaoyue Wang
- State Key Laboratory of Medical Molecular Biology, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing, China
| | - Li Zhang
- Chinese Institute for Brain Research, Beijing, 102206, China
| | - Chun-Long Chen
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR3244, Dynamics of Genetic Information, 75005, Paris, France
| | - Yong E Zhang
- Key Laboratory of Zoological Systematics and Evolution & State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
- CAS Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
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187
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Raina P, Guinea R, Chatsirisupachai K, Lopes I, Farooq Z, Guinea C, Solyom CA, de Magalhães JP. GeneFriends: gene co-expression databases and tools for humans and model organisms. Nucleic Acids Res 2022; 51:D145-D158. [PMID: 36454018 PMCID: PMC9825523 DOI: 10.1093/nar/gkac1031] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 12/05/2022] Open
Abstract
Gene co-expression analysis has emerged as a powerful method to provide insights into gene function and regulation. The rapid growth of publicly available RNA-sequencing (RNA-seq) data has created opportunities for researchers to employ this abundant data to help decipher the complexity and biology of genomes. Co-expression networks have proven effective for inferring the relationship between the genes, for gene prioritization and for assigning function to poorly annotated genes based on their co-expressed partners. To facilitate such analyses we created previously an online co-expression tool for humans and mice entitled GeneFriends. To continue providing a valuable tool to the scientific community, we have now updated the GeneFriends database and website. Here, we present the new version of GeneFriends, which includes gene and transcript co-expression networks based on RNA-seq data from 46 475 human and 34 322 mouse samples. The new database also encompasses tissue-specific gene co-expression networks for 20 human and 21 mouse tissues, dataset-specific gene co-expression maps based on TCGA and GTEx projects and gene co-expression networks for additional seven model organisms (fruit fly, zebrafish, worm, rat, yeast, cow and chicken). GeneFriends is freely available at http://www.genefriends.org/.
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Affiliation(s)
- Priyanka Raina
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Rodrigo Guinea
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Kasit Chatsirisupachai
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Inês Lopes
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Zoya Farooq
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
| | - Cristina Guinea
- UCAL - Universidad de Ciencias y Artes de América Latina, Faculty of Design, Lima 15026, Perú
| | - Csaba-Attila Solyom
- Integrative Genomics of Ageing Group, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool L7 8TX, UK
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188
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Comparative transcriptomics reveals commonalities and differences in the genetic underpinnings of a floral dimorphism. Sci Rep 2022; 12:20771. [PMID: 36456708 PMCID: PMC9715534 DOI: 10.1038/s41598-022-25132-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Accepted: 11/25/2022] [Indexed: 12/05/2022] Open
Abstract
Distyly, a floral dimorphism associated with heteromorphic self-incompatibility and controlled by the S-locus supergene, evolved independently multiple times. Comparative analyses of the first transcriptome atlas for the main distyly model, Primula veris, with other distylous species produced the following findings. A set of 53 constitutively expressed genes in P. veris did not include any of the housekeeping genes commonly used to normalize gene expression in qPCR experiments. The S-locus gene CYPT acquired its role in controlling style elongation via a change in expression profile. Comparison of genes differentially expressed between floral morphs revealed that brassinosteroids and auxin are the main hormones controlling style elongation in P. veris and Fagopyrum esculentum, respectively. Furthermore, shared biochemical pathways might underlie the expression of distyly in the distantly related P. veris, F. esculentum and Turnera subulata, suggesting a degree of correspondence between evolutionary convergence at phenotypic and molecular levels. Finally, we provide the first evidence supporting the previously proposed hypothesis that distyly supergenes of distantly related species evolved via the recruitment of genes related to the phytochrome-interacting factor (PIF) signaling network. To conclude, this is the first study that discovered homologous genes involved in the control of distyly in distantly related taxa.
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189
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Zhang H, Zhang N, Wu W, Zhou R, Li S, Wang Z, Dai Z, Zhang L, Liu Z, Zhang J, Luo P, Liu Z, Cheng Q. Machine learning-based tumor-infiltrating immune cell-associated lncRNAs for predicting prognosis and immunotherapy response in patients with glioblastoma. Brief Bioinform 2022; 23:bbac386. [PMID: 36136350 DOI: 10.1093/bib/bbac386] [Citation(s) in RCA: 54] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 07/29/2022] [Accepted: 08/10/2022] [Indexed: 12/14/2022] Open
Abstract
Long noncoding ribonucleic acids (RNAs; lncRNAs) have been associated with cancer immunity regulation. However, the roles of immune cell-specific lncRNAs in glioblastoma (GBM) remain largely unknown. In this study, a novel computational framework was constructed to screen the tumor-infiltrating immune cell-associated lncRNAs (TIIClnc) for developing TIIClnc signature by integratively analyzing the transcriptome data of purified immune cells, GBM cell lines and bulk GBM tissues using six machine learning algorithms. As a result, TIIClnc signature could distinguish survival outcomes of GBM patients across four independent datasets, including the Xiangya in-house dataset, and more importantly, showed superior performance than 95 previously established signatures in gliomas. TIIClnc signature was revealed to be an indicator of the infiltration level of immune cells and predicted the response outcomes of immunotherapy. The positive correlation between TIIClnc signature and CD8, PD-1 and PD-L1 was verified in the Xiangya in-house dataset. As a newly demonstrated predictive biomarker, the TIIClnc signature enabled a more precise selection of the GBM population who would benefit from immunotherapy and should be validated and applied in the near future.
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Affiliation(s)
- Hao Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
- Department of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, China
| | - Nan Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- One-third Lab, College of Bioinformatics Science and Technology, Harbin Medical University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Wantao Wu
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- Department of Oncology, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Ran Zhou
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, University of Manchester, UK
| | - Shuyu Li
- Department of Thyroid and Breast Surgery, Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, China
| | - Zeyu Wang
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Ziyu Dai
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Liyang Zhang
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Zaoqu Liu
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou, China
| | - Jian Zhang
- Department of Oncology, Zhujiang Hospital, Southern Medical University, China
| | - Peng Luo
- Department of Oncology, Zhujiang Hospital, Southern Medical University, China
| | - Zhixiong Liu
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
| | - Quan Cheng
- Department of Neurosurgery, Xiangya Hospital, Central South University, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, China
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190
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Brasó-Vives M, Marlétaz F, Echchiki A, Mantica F, Acemel RD, Gómez-Skarmeta JL, Hartasánchez DA, Le Targa L, Pontarotti P, Tena JJ, Maeso I, Escriva H, Irimia M, Robinson-Rechavi M. Parallel evolution of amphioxus and vertebrate small-scale gene duplications. Genome Biol 2022; 23:243. [PMID: 36401278 PMCID: PMC9673378 DOI: 10.1186/s13059-022-02808-6] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 10/31/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Amphioxus are non-vertebrate chordates characterized by a slow morphological and molecular evolution. They share the basic chordate body-plan and genome organization with vertebrates but lack their 2R whole-genome duplications and their developmental complexity. For these reasons, amphioxus are frequently used as an outgroup to study vertebrate genome evolution and Evo-Devo. Aside from whole-genome duplications, genes continuously duplicate on a smaller scale. Small-scale duplicated genes can be found in both amphioxus and vertebrate genomes, while only the vertebrate genomes have duplicated genes product of their 2R whole-genome duplications. Here, we explore the history of small-scale gene duplications in the amphioxus lineage and compare it to small- and large-scale gene duplication history in vertebrates. RESULTS We present a study of the European amphioxus (Branchiostoma lanceolatum) gene duplications thanks to a new, high-quality genome reference. We find that, despite its overall slow molecular evolution, the amphioxus lineage has had a history of small-scale duplications similar to the one observed in vertebrates. We find parallel gene duplication profiles between amphioxus and vertebrates and conserved functional constraints in gene duplication. Moreover, amphioxus gene duplicates show levels of expression and patterns of functional specialization similar to the ones observed in vertebrate duplicated genes. We also find strong conservation of gene synteny between two distant amphioxus species, B. lanceolatum and B. floridae, with two major chromosomal rearrangements. CONCLUSIONS In contrast to their slower molecular and morphological evolution, amphioxus' small-scale gene duplication history resembles that of the vertebrate lineage both in quantitative and in functional terms.
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Affiliation(s)
- Marina Brasó-Vives
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
| | - Ferdinand Marlétaz
- Department of Genetics, Evolution and Environment (GEE), University College London, London, UK
| | - Amina Echchiki
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Federica Mantica
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Rafael D Acemel
- Andalusian Centre for Developmental Biology (CABD), CSIC-Pablo Olavide University, Sevilla, Spain
| | - José L Gómez-Skarmeta
- Andalusian Centre for Developmental Biology (CABD), CSIC-Pablo Olavide University, Sevilla, Spain
| | - Diego A Hartasánchez
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Lorlane Le Targa
- IRD, APHM, MEPHI, Aix Marseille Université, Marseille, France
- IHU-Méditerranée Infection, Marseille, France
| | - Pierre Pontarotti
- IRD, APHM, MEPHI, Aix Marseille Université, Marseille, France
- IHU-Méditerranée Infection, Marseille, France
- CNRS, Paris, France
| | - Juan J Tena
- Andalusian Centre for Developmental Biology (CABD), CSIC-Pablo Olavide University, Sevilla, Spain
| | - Ignacio Maeso
- Andalusian Centre for Developmental Biology (CABD), CSIC-Pablo Olavide University, Sevilla, Spain
- Department of Genetics, Microbiology and Statistics, University of Barcelona, Barcelona, Spain
| | - Hector Escriva
- Biologie Intégrative des Organismes Marins, BIOM, CNRS-Sorbonne University, Banyuls-sur-Mer, France
| | - Manuel Irimia
- Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
- Pompeu Fabra University (UPF), Barcelona, Spain
- ICREA, Barcelona, Spain
| | - Marc Robinson-Rechavi
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland.
- Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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191
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Qian SH, Chen L, Xiong YL, Chen ZX. Evolution and function of developmentally dynamic pseudogenes in mammals. Genome Biol 2022; 23:235. [PMID: 36348461 PMCID: PMC9641868 DOI: 10.1186/s13059-022-02802-y] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 10/23/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Pseudogenes are excellent markers for genome evolution, which are emerging as crucial regulators of development and disease, especially cancer. However, systematic functional characterization and evolution of pseudogenes remain largely unexplored. RESULTS To systematically characterize pseudogenes, we date the origin of human and mouse pseudogenes across vertebrates and observe a burst of pseudogene gain in these two lineages. Based on a hybrid sequencing dataset combining full-length PacBio sequencing, sample-matched Illumina sequencing, and public time-course transcriptome data, we observe that abundant mammalian pseudogenes could be transcribed, which contribute to the establishment of organ identity. Our analyses reveal that developmentally dynamic pseudogenes are evolutionarily conserved and show an increasing weight during development. Besides, they are involved in complex transcriptional and post-transcriptional modulation, exhibiting the signatures of functional enrichment. Coding potential evaluation suggests that 19% of human pseudogenes could be translated, thus serving as a new way for protein innovation. Moreover, pseudogenes carry disease-associated SNPs and conduce to cancer transcriptome perturbation. CONCLUSIONS Our discovery reveals an unexpectedly high abundance of mammalian pseudogenes that can be transcribed and translated, and these pseudogenes represent a novel regulatory layer. Our study also prioritizes developmentally dynamic pseudogenes with signatures of functional enrichment and provides a hybrid sequencing dataset for further unraveling their biological mechanisms in organ development and carcinogenesis in the future.
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Affiliation(s)
- Sheng Hu Qian
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
| | - Lu Chen
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
| | - Yu-Li Xiong
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
| | - Zhen-Xia Chen
- Hubei Hongshan Laboratory, College of Biomedicine and Health, Huazhong Agricultural University, Wuhan, 430070 PR China
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Life Science and Technology, Huazhong Agricultural University, Wuhan, 430070 PR China
- Interdisciplinary Sciences Institute, Huazhong Agricultural University, Wuhan, 430070 PR China
- Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Shenzhen, 518124 PR China
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124 PR China
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192
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Leitão E, Schröder C, Parenti I, Dalle C, Rastetter A, Kühnel T, Kuechler A, Kaya S, Gérard B, Schaefer E, Nava C, Drouot N, Engel C, Piard J, Duban-Bedu B, Villard L, Stegmann APA, Vanhoutte EK, Verdonschot JAJ, Kaiser FJ, Tran Mau-Them F, Scala M, Striano P, Frints SGM, Argilli E, Sherr EH, Elder F, Buratti J, Keren B, Mignot C, Héron D, Mandel JL, Gecz J, Kalscheuer VM, Horsthemke B, Piton A, Depienne C. Systematic analysis and prediction of genes associated with monogenic disorders on human chromosome X. Nat Commun 2022; 13:6570. [PMID: 36323681 PMCID: PMC9630267 DOI: 10.1038/s41467-022-34264-y] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 10/19/2022] [Indexed: 11/06/2022] Open
Abstract
Disease gene discovery on chromosome (chr) X is challenging owing to its unique modes of inheritance. We undertook a systematic analysis of human chrX genes. We observe a higher proportion of disorder-associated genes and an enrichment of genes involved in cognition, language, and seizures on chrX compared to autosomes. We analyze gene constraints, exon and promoter conservation, expression, and paralogues, and report 127 genes sharing one or more attributes with known chrX disorder genes. Using machine learning classifiers trained to distinguish disease-associated from dispensable genes, we classify 247 genes, including 115 of the 127, as having high probability of being disease-associated. We provide evidence of an excess of variants in predicted genes in existing databases. Finally, we report damaging variants in CDK16 and TRPC5 in patients with intellectual disability or autism spectrum disorders. This study predicts large-scale gene-disease associations that could be used for prioritization of X-linked pathogenic variants.
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Affiliation(s)
- Elsa Leitão
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Christopher Schröder
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Ilaria Parenti
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Carine Dalle
- Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225, F-75013, Paris, France
| | - Agnès Rastetter
- Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225, F-75013, Paris, France
| | - Theresa Kühnel
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Alma Kuechler
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Sabine Kaya
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Bénédicte Gérard
- Unité de Génétique Moléculaire, IGMA, Hôpitaux Universitaire de Strasbourg, Strasbourg, France
| | - Elise Schaefer
- Service de Génétique Médicale, IGMA, Hôpitaux Universitaires de Strasbourg, Strasbourg, France
| | - Caroline Nava
- Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225, F-75013, Paris, France
| | - Nathalie Drouot
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, 67400, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, 67400, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, 67400, France
- Université de Strasbourg, Illkirch, 67400, France
| | - Camille Engel
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, 67400, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, 67400, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, 67400, France
- Université de Strasbourg, Illkirch, 67400, France
| | - Juliette Piard
- Centre de Génétique Humaine, CHU Besançon, Besançon, France
- INSERM UMR1231, Equipe Génétique des Anomalies du Développement, Université de Bourgogne-Franche-Comté, Dijon, France
| | | | - Laurent Villard
- Aix-Marseille University, INSERM, MMG, UMR-S 1251, Faculté de médecine, Marseille, France
- Département de Génétique Médicale, APHM, Hôpital d'Enfants de La Timone, Marseille, France
| | - Alexander P A Stegmann
- Department of Human Genetics, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands
- Department of Clinical Genetics, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Els K Vanhoutte
- Department of Clinical Genetics, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Job A J Verdonschot
- Department of Clinical Genetics, Maastricht University Medical Center+, Maastricht, The Netherlands
- Cardiovascular Research Institute (CARIM), Departments of Cardiology, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Frank J Kaiser
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Frédéric Tran Mau-Them
- INSERM UMR1231, Equipe Génétique des Anomalies du Développement, Université de Bourgogne-Franche-Comté, Dijon, France
- Unité Fonctionnelle Innovation en Diagnostic génomique des maladies rares, CHU Dijon Bourgogne, Dijon, France
| | - Marcello Scala
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132, Genoa, Italy
- Pediatric Neurology and Muscular Diseases Unit, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Pasquale Striano
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16132, Genoa, Italy
- Pediatric Neurology and Muscular Diseases Unit, IRCCS Istituto Giannina Gaslini, 16147, Genoa, Italy
| | - Suzanna G M Frints
- Department of Clinical Genetics, Maastricht University Medical Center+, Maastricht, The Netherlands
- Department of Genetics and Cell Biology, Faculty of Health Medicine Life Sciences, Maastricht University Medical Center+, Maastricht University, Maastricht, The Netherlands
| | - Emanuela Argilli
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Elliott H Sherr
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
- Institute of Human Genetics and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Fikret Elder
- UF de Génomique du Développement, Département de Génétique, Groupe Hospitalier Pitié-Salpêtrière, APHP-Sorbonne Université, Paris, France
| | - Julien Buratti
- UF de Génomique du Développement, Département de Génétique, Groupe Hospitalier Pitié-Salpêtrière, APHP-Sorbonne Université, Paris, France
| | - Boris Keren
- UF de Génomique du Développement, Département de Génétique, Groupe Hospitalier Pitié-Salpêtrière, APHP-Sorbonne Université, Paris, France
| | - Cyril Mignot
- Institut du Cerveau et de la Moelle épinière (ICM), Sorbonne Université, UMR S 1127, Inserm U1127, CNRS UMR 7225, F-75013, Paris, France
- APHP, Sorbonne Université, Département de Génétique, Centre de Référence Déficiences Intellectuelles de Causes Rares, Groupe Hospitalier Pitié-Salpêtrière and Hôpital Trousseau, Paris, France
| | - Delphine Héron
- APHP, Sorbonne Université, Département de Génétique, Centre de Référence Déficiences Intellectuelles de Causes Rares, Groupe Hospitalier Pitié-Salpêtrière and Hôpital Trousseau, Paris, France
| | - Jean-Louis Mandel
- Unité de Génétique Moléculaire, IGMA, Hôpitaux Universitaire de Strasbourg, Strasbourg, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, 67400, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, 67400, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, 67400, France
- Université de Strasbourg, Illkirch, 67400, France
| | - Jozef Gecz
- School of Medicine, The University of Adelaide, Adelaide, 5005, SA, Australia
- Robinson Research Institute, The University of Adelaide, Adelaide, SA, 5006, Australia
- South Australian Health and Medical Research Institute, The University of Adelaide, Adelaide, 5005, SA, Australia
| | - Vera M Kalscheuer
- Research Group Development and Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany
| | - Bernhard Horsthemke
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany
| | - Amélie Piton
- Unité de Génétique Moléculaire, IGMA, Hôpitaux Universitaire de Strasbourg, Strasbourg, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, 67400, France
- Centre National de la Recherche Scientifique, UMR7104, Illkirch, 67400, France
- Institut National de la Santé et de la Recherche Médicale, U964, Illkirch, 67400, France
- Université de Strasbourg, Illkirch, 67400, France
| | - Christel Depienne
- Institute of Human Genetics, University Hospital Essen, University Duisburg-Essen, Essen, Germany.
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193
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Huang J, Liu W, Zhang D, Lin B, Li B. TMEM158 expression is negatively regulated by AR signaling and associated with favorite survival outcomes in prostate cancers. Front Oncol 2022; 12:1023455. [PMID: 36387246 PMCID: PMC9663988 DOI: 10.3389/fonc.2022.1023455] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 10/18/2022] [Indexed: 08/30/2023] Open
Abstract
BACKGROUND Membrane protein TMEM158 was initially reported as a Ras-induced gene during senescence and has been implicated as either an oncogenic factor or tumor suppressor, depending on tumor types. It is unknown if TMEM158 expression is altered in prostate cancers. METHODS Multiple public gene expression datasets from RNA-seq and cDNA microarray assays were utilized to analyze candidate gene expression profiles. TMEM158 protein expression was assessed using an immunohistochemistry approach on a tissue section array from benign and malignant prostate tissues. Comparisons of gene expression profiles were conducted using the bioinformatics software R package. RESULTS COX regression-based screening identified the membrane protein TMEM158 gene as negatively associated with disease-specific and progression-free survival in prostate cancer patients. Gene expression at the mRNA and protein levels revealed that TMEM158 expression was significantly reduced in malignant tissues compared to benign compartments. Meanwhile, TMEM158 downregulation was strongly correlated with advanced clinicopathological features, including late-stage diseases, lymph node invasion, higher PSA levels, residual tumors after surgery, and adverse Gleason scores. In castration-resistant prostate cancers, TMEM158 expression was negatively correlated with AR signaling activity but positively correlated with neuroendocrinal progression index. Consistently, in cell culture models, androgen treatment reduced TMEM158 expression, while androgen deprivation led to upregulation of TMEM158 expression. Correlation analysis showed a tight correlation of TMEM158 expression with the level of R-Ras gene expression, which was also significantly downregulated in prostate cancers. Tumor immune infiltration profiling analysis discovered a strong association of TMEM158 expression with NK cell and Mast cell enrichment. CONCLUSION The membrane protein TMEM158 is significantly downregulated in prostate cancer and is tightly associated with disease progression, anti-tumor immune infiltration, and patient survival outcome.
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Affiliation(s)
- Jian Huang
- Center for Pathological Diagnosis and Research, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Wang Liu
- Department of Urology, The University of Kansas Medical Center, Kansas City, KS, United States
| | - Da Zhang
- Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, KS, United States
| | - Biyun Lin
- Center for Pathological Diagnosis and Research, The Affiliated Hospital of Guangdong Medical University, Zhanjiang, China
| | - Benyi Li
- Department of Urology, The University of Kansas Medical Center, Kansas City, KS, United States
- Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, KS, United States
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194
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Tang K, Tang J, Zeng J, Shen W, Zou M, Zhang C, Sun Q, Ye X, Li C, Sun C, Liu S, Jiang G, Du X. A network view of human immune system and virus-human interaction. Front Immunol 2022; 13:997851. [PMID: 36389817 PMCID: PMC9643829 DOI: 10.3389/fimmu.2022.997851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 10/11/2022] [Indexed: 11/30/2022] Open
Abstract
The immune system is highly networked and complex, which is continuously changing as encountering old and new pathogens. However, reductionism-based researches do not give a systematic understanding of the molecular mechanism of the immune response and viral pathogenesis. Here, we present HUMPPI-2022, a high-quality human protein-protein interaction (PPI) network, containing > 11,000 protein-coding genes with > 78,000 interactions. The network topology and functional characteristics analyses of the immune-related genes (IRGs) reveal that IRGs are mostly located in the center of the network and link genes of diverse biological processes, which may reflect the gene pleiotropy phenomenon. Moreover, the virus-human interactions reveal that pan-viral targets are mostly hubs, located in the center of the network and enriched in fundamental biological processes, but not for coronavirus. Finally, gene age effect was analyzed from the view of the host network for IRGs and virally-targeted genes (VTGs) during evolution, with IRGs gradually became hubs and integrated into host network through bridging functionally differentiated modules. Briefly, HUMPPI-2022 serves as a valuable resource for gaining a better understanding of the composition and evolution of human immune system, as well as the pathogenesis of viruses.
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Affiliation(s)
- Kang Tang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Jing Tang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Jinfeng Zeng
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Wei Shen
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
- Department of Rheumatology and Immunology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Min Zou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Chi Zhang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Qianru Sun
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Xiaoyan Ye
- Department of Otolaryngology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Chunwei Li
- Department of Otolaryngology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Caijun Sun
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Guozhi Jiang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Xiangjun Du
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
- Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Xiangjun Du,
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195
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Zhang B, Fei Y, Feng J, Zhu X, Wang R, Xiao H, Zhang H, Huang J. RiceNCexp: a rice non-coding RNA co-expression atlas based on massive RNA-seq and small-RNA seq data. JOURNAL OF EXPERIMENTAL BOTANY 2022; 73:6068-6077. [PMID: 35762882 DOI: 10.1093/jxb/erac285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 06/25/2022] [Indexed: 06/15/2023]
Abstract
Non-coding RNAs (ncRNAs) play important roles in regulating expression of protein-coding genes. Although gene expression databases have emerged in a timely manner, a comprehensive expression database for ncRNAs is still lacking. Herein, we constructed a rice ncRNA co-expression atlas (RiceNCexp), based on 491 RNA-seq and 274 small RNA (sRNA)-seq datasets. RiceNCexp hosts four types of ncRNAs, namely lncRNAs, PHAS genes, miRNAs, and phasiRNAs. RiceNCexp provides comprehensive expression information for rice ncRNAs in 22 tissues/organs, an efficient tau-based mining tool for tissue-specific ncRNAs, and the robust co-expression analysis among ncRNAs or between ncRNAs and protein-coding genes, based on 116 pairs of RNA-seq and sRNA-seq libraries from the same experiments. In summary, RiceNCexp is a user-friendly and comprehensive rice ncRNA co-expression atlas and can be freely accessed at https://cbi.njau.edu.cn/RiceNCexp/.
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Affiliation(s)
- Baoyi Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Province Engineering Research Center of Seed Industry Science and Technology, Nanjing 210095, China
| | - Yuhan Fei
- MOE Key Laboratory of Bioinformatics, Beijing Advanced Innovation Center for Structural Biology & Frontier Research Center for Biological Structure, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jiejie Feng
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Province Engineering Research Center of Seed Industry Science and Technology, Nanjing 210095, China
| | - Xueai Zhu
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Province Engineering Research Center of Seed Industry Science and Technology, Nanjing 210095, China
| | - Rui Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Province Engineering Research Center of Seed Industry Science and Technology, Nanjing 210095, China
| | - Hanqing Xiao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
| | - Hongsheng Zhang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Province Engineering Research Center of Seed Industry Science and Technology, Nanjing 210095, China
| | - Ji Huang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China
- Jiangsu Province Engineering Research Center of Seed Industry Science and Technology, Nanjing 210095, China
- Jiangsu Key Laboratory for Information Agriculture, Nanjing 210095, China
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196
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Aparicio-Puerta E, Hirsch P, Schmartz GP, Fehlmann T, Keller V, Engel A, Kern F, Hackenberg M, Keller A. isomiRdb: microRNA expression at isoform resolution. Nucleic Acids Res 2022; 51:D179-D185. [PMID: 36243964 PMCID: PMC9825445 DOI: 10.1093/nar/gkac884] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 09/19/2022] [Accepted: 09/30/2022] [Indexed: 01/29/2023] Open
Abstract
A significant fraction of mature miRNA transcripts carries sequence and/or length variations, termed isomiRs. IsomiRs are differentially abundant in cell types, tissues, body fluids or patients' samples. Not surprisingly, multiple studies describe a physiological and pathophysiological role. Despite their importance, systematically collected and annotated isomiR information available in databases remains limited. We thus developed isomiRdb, a comprehensive resource that compiles miRNA expression data at isomiR resolution from various sources. We processed 42 499 human miRNA-seq datasets (5.9 × 1011 sequencing reads) and consistently analyzed them using miRMaster and sRNAbench. Our database provides online access to the 90 483 most abundant isomiRs (>1 RPM in at least 1% of the samples) from 52 tissues and 188 cell types. Additionally, the full set of over 3 million detected isomiRs is available for download. Our resource can be queried at the sample, miRNA or isomiR level so users can quickly answer common questions about the presence/absence of a particular miRNA/isomiR in tissues of interest. Further, the database facilitates to identify whether a potentially interesting new isoform has been detected before and its frequency. In addition to expression tables, isomiRdb can generate multiple interactive visualisations including violin plots and heatmaps. isomiRdb is free to use and publicly available at: https://www.ccb.uni-saarland.de/isomirdb.
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Affiliation(s)
| | | | - Georges P Schmartz
- Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
| | - Tobias Fehlmann
- Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany,Rejuvenome, Astera Institute, Berkeley, CA 94705, USA
| | - Verena Keller
- Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany,Department for Internal Medicine II, Saarland University Hospital, 66421 Homburg, Germany
| | - Annika Engel
- Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
| | - Fabian Kern
- Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany,Helmholtz Institute for Pharmaceutical Research Saarland (HIPS)–Helmholtz Centre for Infection Research (HZI), Saarland University Campus, 66123 Saarbrücken, Germany
| | - Michael Hackenberg
- Genetics Department, Faculty of Science, Universidad de Granada, 18071 Granada, Spain
| | - Andreas Keller
- To whom correspondence should be addressed. Tel: +49 681 30268611; Fax: +49 681 30268610;
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197
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Abstract
In order to maintain global food security, it will be necessary to increase yields of the cereal crops that provide most of the calories and protein for the world's population, which includes common wheat (Triticum aestivum L.). An important wheat yield component is the number of grain-holding spikelets which form on the spike during inflorescence development. Characterizing the gene regulatory networks controlling the timing and rate of inflorescence development will facilitate the selection of natural and induced gene variants that contribute to increased spikelet number and yield. In the current study, co-expression and gene regulatory networks were assembled from a temporal wheat spike transcriptome dataset, revealing the dynamic expression profiles associated with the progression from vegetative meristem to terminal spikelet formation. Consensus co-expression networks revealed enrichment of several transcription factor families at specific developmental stages including the sequential activation of different classes of MIKC-MADS box genes. This gene regulatory network highlighted interactions among a small number of regulatory hub genes active during terminal spikelet formation. Finally, the CLAVATA and WUSCHEL gene families were investigated, revealing potential roles for TtCLE13, TtWOX2, and TtWOX7 in wheat meristem development. The hypotheses generated from these datasets and networks further our understanding of wheat inflorescence development.
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198
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Song H, Fu X, Li J, Niu T, Shen J, Wang X, Li Y, Hou Q, Liu A. Phylogenetic analysis and expression profiles of jasmonate ZIM-domain gene family provide insight into abiotic stress resistance in sunflower. FRONTIERS IN PLANT SCIENCE 2022; 13:1010404. [PMID: 36275559 PMCID: PMC9580003 DOI: 10.3389/fpls.2022.1010404] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 08/24/2022] [Indexed: 06/16/2023]
Abstract
Jasmonate ZIM-domain (JAZ) proteins act as inhibitory factors of the jasmonic acid (JA) pathway, which is involved in regulating plant development and defense responses. However, there are no extensive studies available on JAZ genes in sunflower (Helianthus annuus L.). In this study, the phylogenetic analysis of 139 putative JAZ genes from eight plants demonstrated that these JAZs could be divided into five groups (Groups I-V), and the 27 sunflower JAZs (HaJAZs) were classified into these five groups. All groups contained genes from both monocotyledons and dicotyledons, indicating that the emergence of JAZ genes predates the differentiation of monocotyledons and dicotyledons. Both segmental and tandem duplications contributed greatly to this gene family's expansion in sunflower, especially in Group II. Moreover, the expression profiles of HaJAZ genes under normal conditions, hormone treatments or abiotic stresses were analyzed based on RNA-seq data. HaJAZ2 may be undergoing pseudogenization as a nonfunctional gene because it was not expressed in any tissue. Many HaJAZ genes in roots upregulated their expression when involved in responding to exogenous hormones, especially methyl-jasmonate. The abiotic stress treatments of sunflower showed that HaJAZ5, HaJAZ15, HaJAZ17, HaJAZ20, and HaJAZ21 tend to be sensitive to certain abiotic stresses. HaJAZs from different groups may share similar functions but also exercise their unique functions when responding to abiotic stresses. We speculated that this gene family was conserved in sequence but varied in its expression among duplicated HaJAZ genes, which implies that they may confer neofunctionalization in the adaptation to abiotic stresses; this work provides insight into the resistance of sunflowers and their adaptation to diverse environmental conditions.
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Affiliation(s)
- Huifang Song
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Xinxuan Fu
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Juan Li
- Key Laboratory of State Forestry and Grassland Administration on Tropical Forestry Research, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou, China
| | - Tianzeng Niu
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Jie Shen
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Xi Wang
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Yunling Li
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Qinwen Hou
- Department of Life Sciences, Changzhi University, Changzhi, China
| | - Ake Liu
- Department of Life Sciences, Changzhi University, Changzhi, China
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199
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Yamamoto R, Chung R, Vazquez JM, Sheng H, Steinberg PL, Ioannidis NM, Sudmant PH. Tissue-specific impacts of aging and genetics on gene expression patterns in humans. Nat Commun 2022; 13:5803. [PMID: 36192477 PMCID: PMC9530233 DOI: 10.1038/s41467-022-33509-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 09/21/2022] [Indexed: 11/09/2022] Open
Abstract
Age is the primary risk factor for many common human diseases. Here, we quantify the relative contributions of genetics and aging to gene expression patterns across 27 tissues from 948 humans. We show that the predictive power of expression quantitative trait loci is impacted by age in many tissues. Jointly modelling the contributions of age and genetics to transcript level variation we find expression heritability (h2) is consistent among tissues while the contribution of aging varies by >20-fold with [Formula: see text] in 5 tissues. We find that while the force of purifying selection is stronger on genes expressed early versus late in life (Medawar's hypothesis), several highly proliferative tissues exhibit the opposite pattern. These non-Medawarian tissues exhibit high rates of cancer and age-of-expression-associated somatic mutations. In contrast, genes under genetic control are under relaxed constraint. Together, we demonstrate the distinct roles of aging and genetics on expression phenotypes.
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Affiliation(s)
- Ryo Yamamoto
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
- Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, USA
| | - Ryan Chung
- Center for Computational Biology, University of California Berkeley, Berkeley, USA
| | - Juan Manuel Vazquez
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | - Huanjie Sheng
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | - Philippa L Steinberg
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA
| | - Nilah M Ioannidis
- Center for Computational Biology, University of California Berkeley, Berkeley, USA.
- Department of Electrical Engineering and Computer Sciences, University of California Berkeley, Berkeley, USA.
| | - Peter H Sudmant
- Department of Integrative Biology, University of California Berkeley, Berkeley, USA.
- Center for Computational Biology, University of California Berkeley, Berkeley, USA.
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200
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Laloum D, Robinson-Rechavi M. Rhythmicity is linked to expression cost at the protein level but to expression precision at the mRNA level. PLoS Comput Biol 2022; 18:e1010399. [PMID: 36095022 PMCID: PMC9518874 DOI: 10.1371/journal.pcbi.1010399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 09/28/2022] [Accepted: 07/17/2022] [Indexed: 11/18/2022] Open
Abstract
Many genes have nycthemeral rhythms of expression, i.e. a 24-hours periodic variation, at either mRNA or protein level or both, and most rhythmic genes are tissue-specific. Here, we investigate and discuss the evolutionary origins of rhythms in gene expression. Our results suggest that rhythmicity of protein expression could have been favored by selection to minimize costs. Trends are consistent in bacteria, plants and animals, and are also supported by tissue-specific patterns in mouse. Unlike for protein level, cost cannot explain rhythm at the RNA level. We suggest that instead it allows to periodically reduce expression noise. Noise control had the strongest support in mouse, with limited evidence in other species. We have also found that genes under stronger purifying selection are rhythmically expressed at the mRNA level, and we propose that this is because they are noise sensitive genes. Finally, the adaptive role of rhythmic expression is supported by rhythmic genes being highly expressed yet tissue-specific. This provides a good evolutionary explanation for the observation that nycthemeral rhythms are often tissue-specific. For many genes, their expression, i.e. the production of RNA and proteins, is rhythmic with a 24-hour period. Here, we study and discuss the evolutionary origins of these rhythms. Our analyses of data from different species suggest that the rhythmicity of protein level may have been favored by selection for cost minimization. Furthermore, we have shown that cost cannot explain the rhythmic variations in RNA levels. Instead, we suggest that it periodically reduces the stochasticity of gene expression. We also found that genes under stronger purifying selection are rhythmically expressed at the mRNA level, and propose that this is because they are noise-sensitive genes. Finally, rhythmic expression involves genes that are often highly expressed and tissue-specific. This provides a good evolutionary explanation for the tissue-specificity of these rhythms.
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Affiliation(s)
- David Laloum
- Department of Ecology and Evolution, Batiment Biophore, Quartier UNIL-Sorge, Université de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Batiment Génopode, Quartier UNIL-Sorge, Université de Lausanne, Lausanne, Switzerland
| | - Marc Robinson-Rechavi
- Department of Ecology and Evolution, Batiment Biophore, Quartier UNIL-Sorge, Université de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Batiment Génopode, Quartier UNIL-Sorge, Université de Lausanne, Lausanne, Switzerland
- * E-mail:
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