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Jin DM, Morton JT, Bonneau R. Meta-analysis of the human gut microbiome uncovers shared and distinct microbial signatures between diseases. bioRxiv 2024:2024.02.27.582333. [PMID: 38464323 PMCID: PMC10925178 DOI: 10.1101/2024.02.27.582333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Microbiome studies have revealed gut microbiota's potential impact on complex diseases. However, many studies often focus on one disease per cohort. We developed a meta-analysis workflow for gut microbiome profiles and analyzed shotgun metagenomic data covering 11 diseases. Using interpretable machine learning and differential abundance analysis, our findings reinforce the generalization of binary classifiers for Crohn's disease (CD) and colorectal cancer (CRC) to hold-out cohorts and highlight the key microbes driving these classifications. We identified high microbial similarity in disease pairs like CD vs ulcerative colitis (UC), CD vs CRC, Parkinson's disease vs type 2 diabetes (T2D), and schizophrenia vs T2D. We also found strong inverse correlations in Alzheimer's disease vs CD and UC. These findings detected by our pipeline provide valuable insights into these diseases.
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Affiliation(s)
- Dong-Min Jin
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
| | - James T. Morton
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Richard Bonneau
- Center for Genomics and Systems Biology, New York University, New York, NY, USA
- Genentech, New York, NY, USA
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Morton JT, Jin DM, Mills RH, Shao Y, Rahman G, McDonald D, Zhu Q, Balaban M, Jiang Y, Cantrell K, Gonzalez A, Carmel J, Frankiensztajn LM, Martin-Brevet S, Berding K, Needham BD, Zurita MF, David M, Averina OV, Kovtun AS, Noto A, Mussap M, Wang M, Frank DN, Li E, Zhou W, Fanos V, Danilenko VN, Wall DP, Cárdenas P, Baldeón ME, Jacquemont S, Koren O, Elliott E, Xavier RJ, Mazmanian SK, Knight R, Gilbert JA, Donovan SM, Lawley TD, Carpenter B, Bonneau R, Taroncher-Oldenburg G. Multi-level analysis of the gut-brain axis shows autism spectrum disorder-associated molecular and microbial profiles. Nat Neurosci 2023:10.1038/s41593-023-01361-0. [PMID: 37365313 DOI: 10.1038/s41593-023-01361-0] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 05/13/2023] [Indexed: 06/28/2023]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.
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Affiliation(s)
- James T Morton
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
- Biostatistics & Bioinformatics Branch, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Dong-Min Jin
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, USA
| | | | - Yan Shao
- Host-Microbiota Interactions Laboratory, Wellcome Sanger Institute, Hinxton, UK
| | - Gibraan Rahman
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Qiyun Zhu
- School of Life Sciences, Arizona State University, Tempe, AZ, USA
- Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA
| | - Metin Balaban
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
| | - Yueyu Jiang
- Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Kalen Cantrell
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Antonio Gonzalez
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Julie Carmel
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel
| | | | - Sandra Martin-Brevet
- Laboratory for Research in Neuroimaging, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland
| | - Kirsten Berding
- Division of Nutritional Sciences, University of Illinois, Urbana, IL, USA
| | - Brittany D Needham
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Anatomy, Cell Biology and Physiology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - María Fernanda Zurita
- Microbiology Institute and Health Science College, Universidad San Francisco de Quito, Quito, Ecuador
| | - Maude David
- Departments of Microbiology & Pharmaceutical Sciences, Oregon State University, Corvallis, OR, USA
| | - Olga V Averina
- Vavilov Institute of General Genetics Russian Academy of Sciences, Moscow, Russia
| | - Alexey S Kovtun
- Vavilov Institute of General Genetics Russian Academy of Sciences, Moscow, Russia
- Skolkovo Institute of Science and Technology, Skolkovo, Russia
| | - Antonio Noto
- Department of Biomedical Sciences, School of Medicine, University of Cagliari, Cagliari, Italy
| | - Michele Mussap
- Laboratory Medicine, Department of Surgical Sciences, School of Medicine, University of Cagliari, Cagliari, Italy
| | - Mingbang Wang
- Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China
- Microbiome Therapy Center, South China Hospital, Health Science Center, Shenzhen University, Shenzhen, China
| | - Daniel N Frank
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ellen Li
- Department of Medicine, Division of Gastroenterology and Hepatology, Stony Brook University, Stony Brook, NY, USA
| | - Wenhao Zhou
- Shanghai Key Laboratory of Birth Defects, Division of Neonatology, Children's Hospital of Fudan University, National Center for Children's Health, Shanghai, China
| | - Vassilios Fanos
- Neonatal Intensive Care Unit and Neonatal Pathology, Department of Surgical Sciences, School of Medicine, University of Cagliari, Cagliari, Italy
| | - Valery N Danilenko
- Vavilov Institute of General Genetics Russian Academy of Sciences, Moscow, Russia
| | - Dennis P Wall
- Pediatrics (Systems Medicine), Biomedical Data Science, and Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Paúl Cárdenas
- Institute of Microbiology, COCIBA, Universidad San Francisco de Quito, Quito, Ecuador
| | - Manuel E Baldeón
- Facultad de Ciencias Médicas, de la Salud y la Vida, Universidad Internacional del Ecuador, Quito, Ecuador
| | - Sébastien Jacquemont
- Sainte Justine Hospital Research Center, Montréal, QC, Canada
- Department of Pediatrics, Université de Montréal, Montréal, QC, Canada
| | - Omry Koren
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel
| | - Evan Elliott
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel
- The Leslie and Susan Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat Gan, Israel
| | - Ramnik J Xavier
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA, USA
- Center for the Study of Inflammatory Bowel Disease, Massachusetts General Hospital, Boston, MA, USA
| | - Sarkis K Mazmanian
- Division of Biology & Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, California, USA
| | - Jack A Gilbert
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA
| | - Sharon M Donovan
- Division of Nutritional Sciences, University of Illinois, Urbana, IL, USA
| | - Trevor D Lawley
- Host-Microbiota Interactions Laboratory, Wellcome Sanger Institute, Hinxton, UK
| | - Bob Carpenter
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Richard Bonneau
- Center for Computational Biology, Flatiron Institute, Simons Foundation, New York, NY, USA
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, USA
- Prescient Design, a Genentech Accelerator, New York, NY, USA
| | - Gaspar Taroncher-Oldenburg
- Gaspar Taroncher Consulting, Philadelphia, PA, USA.
- Simons Foundation Autism Research Initiative, Simons Foundation, New York, NY, USA.
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Zhang SY, Ruan JJ, Jin DM, Chen N, Xie WG, Ruan QF. [Pan-cancer analysis of ubiquitin-specific protease 7 and its expression changes in the carcinogenesis of scar ulcer]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:518-526. [PMID: 37805766 DOI: 10.3760/cma.j.cn501225-20230421-00137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/09/2023]
Abstract
Objective: To explore the biological role and clinical significance of ubiquitin-specific protease 7 (USP7) in the carcinogenesis of scar ulcer. Methods: A retrospective observational study combined with bioinformatics analysis was used. The RNA expression profile data of USP7 in tumor and/or its corresponding paracancular normal tissue were obtained from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus database, and the RNA sequencing data were transformed by log2. The variations of USP7 gene were analyzed by cBioPortal database. The USP7 mRNA expression in tumor and adjacent normal tissue in TCGA database were obtained by using the "Gene_DE" module in TIMER 2.0 database. The survival rates of patients with high and low USP7 expression in cutaneous melanoma (SKCM), cervical squamous cell carcinoma (CESC), lung squamous cell carcinoma (LUSC), and head and neck squamous cell carcinoma (HNSC) were analyzed using the Gene Expression Profile Interactive Analysis 2 (GEPIA2) database, and the Kaplan-Meier survival curves were drawn. Sangerbox database was used to analyze the correlation of USP7 expression in pan-cancer with microsatellite instability (MSI) or tumor mutation burden (TMB) pan-cancer. Through the "correlation analysis" module in the GEPIA2 database, the correlation of USP7 expression in pan-cancer with the expression levels of five DNA mismatch repair genes (MLH1, MSH2, MSH6, PMS2, and EPCAM) and three essential DNA methyltransferases (DNMT)--DNMT1, DNMT3A, and DNMT3B were evaluated. The USP7 expression in CESC, HNSC, LUSC, and SKCM and its correlation with infiltration of immune cells (B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, and dendritic cells) were analyzed by the "Immune-Gene" module in TIMER 2.0 database. The "Similar Genes Detection" module of GEPIA2 database was used to obtain the top 100 protein sets with similar expression patterns to USP7. Intersection analysis was performed between the aforementioned protein sets and the top 50 protein sets that were directly physically bound to USP7 obtained by using the STRING database. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis were performed for the two protein sets mentioned above using the DAVID database. The samples of normal skin, hypertrophic scar, scar ulcer, and scar carcinoma with corresponding clinicopathologic features were collected from the Department of Pathology of Tongren Hospital of Wuhan University & Wuhan Third Hospital from October 2018 to October 2022, and the USP7 expression in tissue was detected by immunohistochemical method, with the number of samples of 6. Data were statistically analyzed with Log-rank test, one-way analysis of variance, and Bonferroni test. Results: In pan-cancer, the main gene variations of USP7 were mutation and amplification, and the top 3 tumors with the highest variation frequency (>6%) were bladder urothelial carcinoma, SKCM, and endometrial carcinoma. The main mutation of USP7 gene in pan-cancer was missense mutation. In SKCM with the highest mutation frequency, the main type of mutation was missense mutation in USP7_ICP0_bdg domain. USP7 mRNA expression in breast invasive carcinoma, bile duct carcinoma, colon carcinoma, esophageal carcinoma, HNSC, renal chromophobe cell carcinoma, hepatocellular carcinoma, lung adenocarcinoma, LUSC, prostate carcinoma, and gastric carcinoma was significantly higher than that in corresponding paracancer normal tissue (P<0.05). USP7 mRNA expression in glioblastoma multiforme, renal clear cell carcinoma, renal papillary cell carcinoma, and thyroid carcinoma was significantly lower than that in corresponding paracancular normal tissue (P<0.05). In addition, USP7 mRNA expression in SKCM metastases was much higher than that in primary tumor tissue (P<0.05). Survival curves showed no significant difference in survival rate between patients with high USP7 expression and patients with low USP7 expression in CESC, HNSC, LUSC, and SKCM (Log-rank P>0.05, with hazard ratios of 1.00, 0.99, 1.00, and 1.30, respectively). USP7 expression in colon cancer, colorectal cancer, thymic cancer, and thyroid cancer was negatively correlated with TMB (with Pearson correlation coefficients of -0.26, -0.19, -0.19, and 0.11, respectively, P<0.05). USP7 expression in glioma, CESC, lung adenocarcinoma, mixed renal carcinoma, and LUSC was positively correlated with MSI expression (with Pearson correlation coefficients of 0.22, 0.14, 0.15, 0.08, and 0.14, respectively, P<0.05), and USP7 expression in colon cancer, colorectal cancer, invasive breast cancer, prostate cancer, HNSC, thyroid cancer, and diffuse large B-cell lymphoma were significantly negatively correlated with MSI expression (with Pearson correlation coefficients of -0.31, -0.27, -0.13, -0.19, -0.16, -0.18, and -0.53, respectively, P<0.05). The expression of USP7 in CESC was positively correlated with that of both MSH2 and MSH6 (with Spearman correlation coefficients of 0.51 and 0.44, respectively, P<0.05), and the expression of USP7 in HNSC was positively correlated with the expression of EPCAM, MLH1, MSH2, MSH6, and PMS2 (with Spearman correlation coefficients of 0.39, 0.14, 0.49, 0.54, and 0.41, respectively, P<0.05), and the expression of USP7 in LUSC was positively correlated with the expression of EPCAM, MSH2, MSH6, and PMS2 (with Spearman correlation coefficients of 0.20, 0.36, 0.40, and 0.34, respectively, P<0.05), and the expression of USP7 in SKCM was positively correlated with the expression of EPCAM, MLH1, MSH2, MSH6, and PMS2 (with Spearman correlation coefficients of 0.11, 0.33, 0.42, 0.55, and 0.34, respectively, P<0.05). The expression of USP7 in CESC, HNSC, LUSC, and SKCM was significantly positively correlated with the expression of DNMT1, DNMT3A, and DNMT3B (with Spearman correlation coefficients of 0.42, 0.34, 0.22, 0.45, 0.52, 0.22, 0.36, 0.36, 0.22, 0.38, 0.46, and 0.21, respectively, P<0.05). The expression of USP7 in CESC, HNSC, LUSC, and SKCM was positively correlated with CD4+ T cell infiltration (with Partial correlation coefficients of 0.14, 0.22, 0.13, and 0.16, respectively, P<0.05). Being similar to the pattern of USP7 expression and ranked among top 100 protein sets, the top 5 proteins were C16orf72, BCLAF1, UBN, GSPT1, ERI2 (with Spearman correlation coefficients of 0.83, 0.74, 0.73, and 0.72, respectively, all P values<0.05). The top 50 protein sets that directly physically bind to USP7 overlapped with the aforementioned protein set by only one protein, thyroid hormone receptor interaction factor 12. KEGG enrichment analysis showed that USP7 related genes were involved in cell cycle, spliceosome, cell senescence, and p53 signal pathway. GO enrichment analysis showed that USP7 related genes were involved in transcriptional regulation, protein ubiquitination, DNA repair, and cytoplasmic pattern recognition receptor signal pathways. Analysis of clinical samples showed that USP7 expression was significantly higher in hypertrophic scars (0.35±0.05), scar ulcers (0.43±0.04), and scar cancers (0.61±0.03) than in normal skin (0.18±0.04), P<0.05. Conclusions: USP7 may be a clinical biomarker for the progression of cicatricial ulcer cancer.
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Affiliation(s)
- S Y Zhang
- Institute of Burns, Tongren Hospital of Wuhan University & Wuhan Third Hospital, Wuhan 430060, China
| | - J J Ruan
- Institute of Burns, Tongren Hospital of Wuhan University & Wuhan Third Hospital, Wuhan 430060, China
| | - D M Jin
- Department of Pathology, Tongren Hospital of Wuhan University & Wuhan Third Hospital, Wuhan 430060, China
| | - N Chen
- Institute of Burns, Tongren Hospital of Wuhan University & Wuhan Third Hospital, Wuhan 430060, China
| | - W G Xie
- Institute of Burns, Tongren Hospital of Wuhan University & Wuhan Third Hospital, Wuhan 430060, China
| | - Q F Ruan
- Institute of Burns, Tongren Hospital of Wuhan University & Wuhan Third Hospital, Wuhan 430060, China
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Jin DM, Wicke S, Gan L, Yang JB, Jin JJ, Yi TS. The Loss of the Inverted Repeat in the Putranjivoid Clade of Malpighiales. Front Plant Sci 2020; 11:942. [PMID: 32670335 PMCID: PMC7332575 DOI: 10.3389/fpls.2020.00942] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Accepted: 06/10/2020] [Indexed: 05/19/2023]
Abstract
The typical plastid genome (plastome) of photosynthetic angiosperms comprises a pair of Inverted Repeat regions (IRs), which separate a Large Single Copy region (LSC) from a Small Single Copy region (SSC). The independent losses of IRs have been documented in only a few distinct plant lineages. The majority of these taxa show uncommonly high levels of plastome structural variations, while a few have otherwise conserved plastomes. For a better understanding of the function of IRs in stabilizing plastome structure, more taxa that have lost IRs need to be investigated. We analyzed the plastomes of eight species from two genera of the putranjivoid clade of Malpighiales using Illumina paired-end sequencing, the de novo assembly strategy GetOrganelle, as well as a combination of two annotation methods. We found that all eight plastomes of the putranjivoid clade have lost their IRB, representing the fifth case of IR loss within autotrophic angiosperms. Coinciding with the loss of the IR, plastomes of the putranjivoid clade have experienced significant structural variations including gene and intron losses, multiple large inversions, as well as the translocation and duplication of plastome segments. However, Balanopaceae, one of the close relatives of the putranjivoid clade, exhibit a relatively conserved plastome organization with canonical IRs. Our results corroborate earlier reports that the IR loss and additional structural reorganizations are closely linked, hinting at a shared mechanism that underpins structural disturbances.
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Affiliation(s)
- Dong-Min Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Susann Wicke
- Institute for Evolution and Biodiversity, University of Münster, Münster, Germany
| | - Lu Gan
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jun-Bo Yang
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Jian-Jun Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Ting-Shuang Yi
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
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Abstract
The clusioid clade of Malpighiales is comprised of five families: Bonnetiaceae, Calophyllaceae, Clusiaceae, Hypericaceae and Podostemaceae. Recent studies have found the plastome structure of Garcinia mangostana L. from Clusiaceae was conserved, while plastomes of five riverweed species from Podostemaceae showed significant structural variations. The diversification pattern of plastome structure of the clusioid clade worth a thorough investigation. Here we determined five complete plastomes representing four families of the clusioid clade. Our results found that the plastomes of the early diverged three families (Clusiaceae, Bonnetiaceae and Calophyllaceae) in the clusioid clade are relatively conserved, while the plastomes of the other two families show significant variations. The Inverted Repeat (IR) regions of Tristicha trifaria and Marathrum foeniculaceum (Podostemaceae) are greatly reduced following the loss of the ycf1 and ycf2 genes. An inversion over 50 kb spanning from trnK-UUU to rbcL in the LSC region is shared by Cratoxylum cochinchinense (Hypericaceae), T. trifaria and Ma. foeniculaceum (Podostemaceae). The large inversed colinear block in Hypericaceae and Podostemaceae contains all the genes in the 50-kb inversed colinear block in a clade of Papilionoideae, with two extra genes (trnK-UUU and matK) at one end. Another endpoint of both inversions in the two clusioids families and Papilionoideae is located between rbcL and accD. This study greatly helped to clarify the plastome evolution in the clusioid clade.
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Affiliation(s)
- Dong-Min Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jian-Jun Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Ting-Shuang Yi
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
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Wang ZX, Jin DM, Wang GD, Yi TS. The complete plastome of Ctenolophon englerianus Mildbr. (Ctenolophonaceae). Mitochondrial DNA B Resour 2019; 4:3379-3380. [PMID: 33366002 PMCID: PMC7707312 DOI: 10.1080/23802359.2019.1673684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2019] [Accepted: 09/23/2019] [Indexed: 11/26/2022] Open
Abstract
Ctenolophon englerianus Mildbr. is endemic to West Africa. The wood of this species is very strong, and is widely used as building material in local regions. In this study, we determined its complete plastome sequence. This is the first reported complete plastome sequence in the family Ctenolophonaceae. The plastome of C. englerianus was found to possess a total length of 161,553 bp containing two inverted repeats (IRs) of 27,469 bp, a large single copy (LSC) region of 89,386 bp, and a small single copy (SSC) region of 17,229 bp. The plastome contains 110 unique genes, consisting of 76 protein-coding genes, 30 tRNA genes and 4 rRNA genes. The rpl32, rps16 and infA genes were lost. To validate the phylogenetic relationships of C. englerianus in Malpighiales, we have selected seven representative families from three major clades of Malpighiales to construct phylogenetic tree. According to the phylogenetic topologies, C. englerianus has a close relationship with Erythroxylum novogranatence.
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Affiliation(s)
- Zi-Xun Wang
- Key Laboratory of Ministry of Education for Medicinal Plant Resource and Natural Pharmaceutical Chemistry, National Engineering Laboratory for Resource Developing of Endangered Chinese Crude Drugs in Northwest of China, College of Life Sciences, Shaanxi Normal University, Xi'an, China
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Dong-Min Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Guo-Dong Wang
- Key Laboratory of Ministry of Education for Medicinal Plant Resource and Natural Pharmaceutical Chemistry, National Engineering Laboratory for Resource Developing of Endangered Chinese Crude Drugs in Northwest of China, College of Life Sciences, Shaanxi Normal University, Xi'an, China
| | - Ting-Shuang Yi
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
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Jin DM, Gan L, Jin JJ, Yi TS. The plastid genome of Klainedoxa gabonensis Pierre ex Engl. (Malpighiales). Mitochondrial DNA B Resour 2019; 4:2541-2542. [PMID: 33365617 PMCID: PMC7687570 DOI: 10.1080/23802359.2019.1639557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
Klainedoxa gabonensis Pierre ex Engl. is an important tropical tree species. In this study, its complete plastome sequence was determined. This is the first reported complete plastome sequence in the family Irvingiaceae. The plastome is totally 160,118 bp in length, containing a pair of 26,963-bp-long inverted repeat regions (IRs), a large single copy region of 88,157 bp, and a small single copy region of 18,035 bp. A total of 112 unique genes were identified in K. gabonensis plastome, of which 78 are protein-coding genes, 30 are tRNA genes, and four are rRNA genes. Phylogenetic analysis confirmed the close relationship between K. gabonensis and Irvingia malayana.
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Affiliation(s)
- Dong-Min Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Lu Gan
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jian-Jun Jin
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
| | - Ting-Shuang Yi
- Germplasm Bank of Wild Species, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China
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Yang DE, Jin DM, Wang B, Zhang DS, Nguyen HT, Zhang CL, Chen SJ. Characterization and mapping of Rpi1, a gene that confers dominant resistance to stalk rot in maize. Mol Genet Genomics 2005; 274:229-34. [PMID: 16133168 DOI: 10.1007/s00438-005-0016-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2005] [Accepted: 05/31/2005] [Indexed: 10/25/2022]
Abstract
The maize inbred lines 1145 (resistant) and Y331 (susceptible), and the F(1), F(2) and BC(1)F(1) populations derived from them were inoculated with the pathogen Pythium inflatum Matthews, which causes stalk rot in Zea mays. Field data revealed that the ratio of resistant to susceptible plants was 3:1 in the F(2) population, and 1:1 in the BC(1)F(1)population, indicating that the resistance to P. inflatum Matthews was controlled by a single dominant gene in the 1145xY331 cross. The gene that confers resistance to P. inflatum Matthews was designated Rpi1 for resistance to P. inflatum) according to the standard nomenclature for plant disease resistance genes. Fifty SSR markers from 10 chromosomes were first screened in the F(2) population to find markers linked to the Rpi1 gene. The results indicated that umc1702 and mmc0371 were both linked to Rpi1, placing the resistance gene on chromosome 4. RAPD (randomly amplified polymorphic DNA) markers were then tested in the F(2)population using bulked segregant analysis (BSA). Four RAPD products were found to show linkage to the Rpi1 gene. Then 27 SSR markers and 8 RFLP markers in the region encompassing Rpi1 were used for fine-scale mapping of the resistance gene. Two SSR markers and four RFLP markers were linked to the Rpi1 gene. Finally, the Rpi1 gene was mapped between the SSR markers bnlg1937 and agrr286 on chromosome 4, 1.6 cM away from the former and 4.1 cM distant from the latter. This is the first time that a dominant gene for resistance to maize stalk rot caused by P. inflatum Matthews has been mapped with molecular marker techniques.
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Affiliation(s)
- D E Yang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, PR China
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Chen CX, Wang ZL, Yang DE, Ye CJ, Zhao YB, Jin DM, Weng ML, Wang B. Molecular tagging and genetic mapping of the disease resistance gene RppQ to southern corn rust. Theor Appl Genet 2004; 108:945-950. [PMID: 14624338 DOI: 10.1007/s00122-003-1506-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2003] [Accepted: 09/10/2003] [Indexed: 05/24/2023]
Abstract
Southern corn rust (SCR), Puccinia polysora Underw, is a destructive disease in maize ( Zea mays L.). Inbred line Qi319 is highly resistant to SCR. Results from the inoculation test and genetic analysis of SCR in five F(2) populations and five BC(1)F(1 )populations derived from resistant parent Qi319 clearly indicate that the resistance to SCR in Qi319 is controlled by a single dominant resistant gene, which was named RppQ. Simple sequence repeat (SSR) analysis was carried out in an F(2) population derived from the cross "Qi319x340". Twenty SSR primer pairs evenly distributed on chromosome10 were screened at first. Out of them, two primer pairs, phi118 and phi 041, showed linkage with SCR resistance. Based on this result, eight new SSR primer pairs surrounding the region of primers phi118 and phi 041 were selected and further tested regarding their linkage relation with RppQ. Results indicated that SSR markers umc1,318 and umc 2,018 were linked to RppQ with a genetic distance of 4.76 and 14.59 cM, respectively. On the other side of RppQ, beyond SSR markers phi 041 and phi118, another SSR marker umc1,293 was linked to RppQ with a genetic distance of 3.78 cM. Because the five linkage SSR markers (phi118, phi 041, umc1,318, umc 2,018 and umc1,293) are all located on chromosome 10, the RppQ gene should also be located on chromosome 10. In order to fine map the RppQ gene, AFLP (amplified fragment length polymorphism) analysis was carried out. A total 54 AFLP primer combinations were analyzed; one AFLP marker, AF1, from the amplification products of primer combination E-AGC/M-CAA, showed linkage with the RppQ gene in a genetic distance of 3.34 cM. Finally the RppQ gene was mapped on the short arm of chromosome 10 between SSR markers phi 041 and AFLP marker AF1 with a genetic distance of 2.45 and 3.34 cM respectively.
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Affiliation(s)
- C X Chen
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, 100101, Beijing, China
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Yang DE, Zhang CL, Zhang DS, Jin DM, Weng ML, Chen SJ, Nguyen H, Wang B. Genetic analysis and molecular mapping of maize (Zea mays L.) stalk rot resistant gene Rfg1. Theor Appl Genet 2004; 108:706-711. [PMID: 14647897 DOI: 10.1007/s00122-003-1466-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2003] [Accepted: 08/20/2003] [Indexed: 05/24/2023]
Abstract
One single pathogen Fusarium graminearum Schw. was inoculated to maize inbred lines 1,145 (Resistant) and Y331 (Susceptive), and their progenies of F(1), F(2) and BC(1)F(1) populations. Field statistical data revealed that all of the F(1) individuals were resistant to the disease and that the ratio of resistant plants to susceptive plants was 3:1 in the F(2) population, and 1:1 in the BC(1)F(1 )population. The results revealed that a single dominant gene controls the resistance to F. graminearum Schw. The resistant gene to F. graminearum Schw. was denominated as Rfg1 according to the standard principle of the nomenclature of the plant disease resistant genes. RAPD (randomly amplified polymorphic DNA) combined with BSA (bulked segregant analysis) analysis was carried out in the developed F(2) and BC(1)F(1 )populations, respectively. Three RAPD products screened from the RAPD analysis with 820 Operon 10-mer primers showed the linkage relation with the resistant gene Rfg1. The three RAPD amplification products (OPD-20(1000), OPA-04(1100) and OPY-04(900)) were cloned and their copy numbers were determined. The results indicated that only OPY-04(900) was a single-copy sequence. Then, OPY-04(900) was used as a probe to map the Rfg1 gene with a RIL F(7) mapping population provided by Henry Nguyen, which was developed from the cross "S3xMo17". Rfg1 was primarily mapped on chromosome 6 between the two linked markers OPY-04(900) and umc21 (Bin 6.04-6.05). In order to confirm the primary mapping result, 25 SSR (simple sequence repeat) markers and six RFLP (restriction fragment length polymorphism) markers in the Rfg1 gene-encompassing region were selected, and their linkage relation with Rfg1 was analyzed in our F(2) population. Results indicated that SSR marker mmc0241 and RFLP marker bnl3.03 are flanking the Rfg1 gene with a genetic distance of 3.0 cM and 2.0 cM, respectively. This is the first time to name and to map a single resistant gene of maize stalk rot through a single pathogen inoculation and molecular marker analysis.
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Affiliation(s)
- D E Yang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, 100101 Beijing, China
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Xing QH, Ru ZG, Zhou CJ, Xue X, Liang CY, Yang DE, Jin DM, Wang B. Genetic analysis, molecular tagging and mapping of the thermo-sensitive genic male-sterile gene (wtms1) in wheat. Theor Appl Genet 2003; 107:1500-1504. [PMID: 12928780 DOI: 10.1007/s00122-003-1385-y] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2003] [Accepted: 06/26/2003] [Indexed: 05/24/2023]
Abstract
A thermo-sensitive genic male-sterile (TGMS) wheat line ( Triticum aestivum L.) BNY-S was obtained from the spontaneous mutant of BNY-F. Its fertility was decided by the temperature during the differentiation stage of the spikelets. BNY-S was completely sterile when the temperature was lower than 10 degrees C during the differentiation stage of the spikelets, but fertile when the temperature was higher than 10 degrees C. Genetic analysis indicated that the sterility of BNY-S was controlled by a single recessive gene, which was named as wtms1. An F(2) population, consisting of 3,000 individuals from the cross between BNY-S and Lankao 52-24, was used for genetic analysis and statistical analysis of the TGMS and, out of them, 158 sterile and 93 fertile extremes were present for molecular tagging and mapping of the wtms1 gene. SSR (simple sequence repeat) and AFLP (amplified fragment length polymorphism) techniques combined with BSA (bulked segregant analysis) were used to screen markers linked to the target gene. As a result, wtms1 was preliminarily mapped on chromosome 2B according to SSR analysis. In AFLP analysis, 14 polymorphic AFLP loci were identified with a linkage relation to the wtms1 gene. Then linkage analysis using the F(2) population showed that three of them, E: AAG/M: CTA(163), E: AGG/M: CTC(220) and E: ACA/M: CTA(160), were linked to the wtms1 gene relatively close to a genetic distance of 6.9 cM, 6.9 cM and 13.9 cM, respectively. Finally, the wtms1 gene was mapped between the SSR marker Xgwm 374 and the AFLP marker E: AAG/M: CTA(163) with the distance of 4.8 cM and 6.9 cM, respectively. A partial linkage map was constructed according the SSR and AFLP data.
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Affiliation(s)
- Q H Xing
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, 100101 Beijing, China
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Che KP, Zhan QC, Xing QH, Wang ZP, Jin DM, He DJ, Wang B. Tagging and mapping of rice sheath blight resistant gene. Theor Appl Genet 2003; 106:293-7. [PMID: 12582854 DOI: 10.1007/s00122-002-1001-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2002] [Accepted: 05/06/2002] [Indexed: 05/20/2023]
Abstract
Sheath blight (Rhizoctonia solani Kühn) is one of the severe rice diseases worldwide. In this study, an F(2) population from a cross between "4011" and "Xiangzaoxian19" is used to identify molecular markers linked with the resistant trait. "4011" was a transgenic rice cultivar carrying a resistant gene to sheath blight, while "Xiangzaoxian19" is a highly susceptible one. As a result, five molecular markers, including three RFLP markers converted from RAPD and AFLP markers, and two SSR markers were identified to link with the sheath blight resistant gene. This dominant resistant gene was named as R sb 1 and mapped on rice chromosome 5. The linkage distance between the markers (E-AT:M-CAC(120), E-AT:M-CTA(230), OPN-16(2000), RM164(320) and RM39(300)) and R sb 1 was 1.6 cM, 9.9 cM, 1.6 cM, 15.2 cM and 1.6 cM, respectively.
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Affiliation(s)
- K P Che
- Plant Biotechnology Laboratory, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
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Yang DE, Wang YG, Jin DM, Chen CX, Wang B. [Application of isonucleus and isocytoplasmic lines in the study of maize CMS]. Yi Chuan Xue Bao 2001; 28:663-7. [PMID: 11480179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 02/20/2023]
Abstract
Between wild fertile type (F) and its sterile mutant (cms), if their nucleus and cytoplasm are the same, this wild fertile type (F) and its sterile mutant (cms) are called isonucleus and isocytoplasmic lines. The maize mtDNAs of isonucleus and isocytoplasmic lines (I), wild fertile type 478(F) and its sterile mutant 478-cms, were analyzed by RAPD. 94 primers were screened, 3 polymorphic products, OPZ-19(420), OPAA-15(600) and OPS-01(400), were amplified between 478(F) and 478-cms. The results showed that mtDNAs in isonucleus and isocytoplasmic lines were more homologous than that in others. There is minor mtDNA difference between the fertile type (F) and its sterile type (cms) in a pair of isonucleus and isocytoplasmic lines. The polymorphism detected in isonucleus and isocytoplasmic lines may be more closely linked with the gene of fertility. Therefore, isonucleus and isocytoplasmic line is an excellent system in the study of CMS. Sister isonucleus and isocytoplasmic lines are consisted of 2 groups of isonucleus and isocytoplasmic lines in which their nucleus are not all the same but closely related, their cytoplasm are the same. Using sister isonucleus and isocytoplasmic lines is equal to determining the change of fertility by transferring one cytoplasm into the isonucleus. Isonucleus and isocytoplasmic lines (II) are consisted of Su478(F) and Su478-cms. Isonucleus and isocytoplasmic lines (I) and (II) are sister isonucleus and isocytoplasmic lines. The polymorphic products, OPZ-19(420) and OPAA-15(600), can also be obtained in isonucleus and isocytoplasmic lines (II). The 2 polymorphic products OPZ-19(420) and OPAA-15(600) are existed in both of the isonucleus and isocytoplasmic lines. This showed that isonucleus and isocytoplasmic lines are practicable in the study of CMS, and that common polymorphism in isonucleus and isocytoplasmic lines may be related more directly to fertility.
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Affiliation(s)
- D E Yang
- Institute of Genetics, Chinese Academy of Sciences, Beijing 100101, China
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