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Cultivation manipulating zeaxanthin-carotenoid production in Arthrospira (Spirulina) platensis under light and temperature stress

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Algal Research 2023年 76卷

作者： Mohammed, Ibrahim Ahmed Ruengjitchatchawalya, Marasri Paithoonrangsarid, Kalyanee Biotechnology Program School of Bioresources and Technology King Mongkut's University of Technology Thonburi (KMUTT Bang Khun Thian) Tha Kham Bang Khun Thian Bangkok 10150 Thailand Bioinformatics and Systems Biology Program School of Bioresources and Technology King Mongkut's University of Technology Thonburi (KMUTT Bang Khun Thian) Tha Kham Bang Khun Thian Bangkok 10150 Thailand Biochemical Engineering and Systems Biology Research Group National Center for Genetic Engineering and Biotechnology National Science and Technology Development Agency at King Mongkut's University of Technology Thonburi Tha Kham Bang Khun Thian Bangkok 10150 Thailand

Arthrospira (Spirulina) platensis is highly nutritious and most promising cyanobacterium for healthy compounds. In this study, the effect of light and temperature stress on zeaxanthin production in A. platensis C1 (PCC9438) were investigated. Under an optimal condition (35 °C, PPFD of 100 μmol photons m⁻² s⁻¹), the algal growth revealed a specific growth rate (μ) of 0.024 h⁻¹, with the carotenoid yield and content of 3.64 mg L⁻¹ and 4.66 mg g⁻¹, respectively, when cells were grown for 96 h. Whereas that of the isothermally grown under sub-optimal temperatures (16 °C, 20 °C, 37 °C, 39 °C and 43 °C), the growth rates and carotenoid yields were very low, ranging from 0.001 to 0.021 h⁻¹ of the specific growth rate, and varied from 0.17 to 3.05 mg L⁻¹ and 0.64 to 4.51 mg g⁻¹ of carotenoid yield and content, respectively. Nevertheless, employing a temperature shift strategy by transferring the algal culture to high temperature (42 °C) led to the increment of total carotenoids by about 12 % and zeaxanthin content and yield by 35.6 % and 22.1 %, respectively, compared to the control, which had a yield and content of 0.68 mg L⁻¹ and 0.87 mg g⁻¹, respectively, within 48 h. Furthermore, altering light intensities during the cultivation period, algal biomass significantly increased by 59 % under high light stress (1000 μmol photons m⁻² s⁻¹) compared to the control (0.78 g L⁻¹). Additionally, zeaxanthin yield and content increased by 104.4 % and 28.7 %, respectively, under 1000 μmol photons m⁻² s⁻¹. We therefore proposed that light/temperature stress shifting strategy for the cultivation of A. platensis C1 could be used to enhance its nutraceutical value. © 2023 Elsevier B.V.

关键词： Arthrospira platensis Carotenoid Light stress Temperature stress Zeaxanthin

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Development and Application of a Multi-Level Computational Approach for the Identification of Inhibitors of Mapk3 in Leishmania Martiniquensis and Leishmania Orientalis

SSRN

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SSRN 2024年

作者： Kiriwan, Duangnapa Vieira, Tatiana F. Kumsiri, Nutnaree Sousa, Sergio F. Choowongkomon, Kiattawee Associate Laboratory i4HB—Institute for Health and Bioeconomy Faculdade de Medicina Universidade do Porto Porto Portugal LAQV/REQUIMTE BioSIM - Departamento de Biomedicina Faculdade de Medicina Universidade do Porto Porto Portugal Genetic Engineering and Bioinformatics program Kasetsart University 50 Ngam Wong Wan Road Chatuchak Bangkok10900 Thailand Center for Advanced Studies in Nanotechnology for Chemical Food and Agricultural Industries KU Institute for Advanced Studies Kasetsart University Bangkok10900 Thailand Department of Biochemistry Faculty of Science Kasetsart University 50 Ngam Wong Wan Road Chatuchak Bangkok10900 Thailand

Leishmania martiniquensis and Leishmania orientalis are two major species of parasites, associated to health problems in Thailand. Here, we focused on in silico strategies for the identification of inhibitors of the protein mitogen active protein kinase3 (MAPK3) in these two species. MAPK3 is a Ser/Thr protein kinase that plays an important role in the differentiation of amastigotes to promastigotes. This study describes a multi-level computational method for discovering new MAPK3 inhibitors with high potency. This approach involves creating 3D models of these protein targets through homology modelling, refined with molecular dynamics (MD) simulations, followed by protein-ligand docking validation for protocol validation, virtual screening of large molecular databases, followed by MD simulations on most promising protein-ligand complexes, and binding free energy calculations. This approach was applied to screen an in-house library of 8,000 tripeptides. The structure-based virtual screening results suggested nine tripeptides as promising inhibitors of MAPK3 for all the leishmania species considered. Four tripeptides were validated as very promising binders by the MD simulations and free energy calculations. Subsequent MAP Kinase 3 inhibition assay was performed. Our in vitro kinase assay demonstrated that the peptide WSY exhibited a significantly higher effectiveness in inhibiting MAPK3 compared to WHW at a concentration of 3.33 µM with percentages of 89.97±9.28% and 27.97±14.45%, *** optimized multi-level protocol can now be applied to other types of molecular databases to identify promising candidates targeting proteins LmrMAPK3 and LoMAPK3. © 2024, The Authors. All rights reserved.

关键词： Molecular dynamics

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Correction: Resistance QTLs controlling leaf and neck blast disease identified in a doubled haploid rice population

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Euphytica 2023年第7期219卷 1-1页

作者： Korinsak, Siripar Sriprakhon, Saengchai Sirithunya, Kanyanat Sriwongchai, Tanee Wongsaprom, Chanakarn Plabpla, Anucha Vanavichit, Apichart Toojinda, Theerayut National Center for Genetic Engineering and Biotechnology (BIOTEC) National Science and Technology Development Agency (NSTDA) Khlong Luang Thailand Faculty of Science and Agricultural Technology Rajamangala University of Technology Lanna Chiangmai Thailand Department of Agronomy Faculty of Agriculture Kasetsart University Bangkok Thailand Interdisciplinary Graduate Program in Genetic Engineering and Bioinformatics Kasetsart University Bangkok Thailand Department of Agronomy Faculty of Agriculture at Kamphaeng Saen Kasetsart University Nakhon Pathom Thailand Rice Science Center Kasetsart University Nakhon Pathom Thailand

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Nitrogen assimilation in cassava: implications for carbon metabolism and biomass synthesis

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Journal of Physics: Conference Series 2019年第1期1232卷

作者： W Siriwat V Muhardina C Thammarongtham S Kalapanulak T Saithong Systems Biology and Bioinformatics Research Laboratory Pilot Plant Development and Training Institute King Mongkut's University of Technology Thonburi Bang Khun Thian Bangkok 10150 Thailand Department of Agricultural Industrial Technology Faculty of Agricultural Technology University of SerambiMekkah Jl. TeungkuImumLueng Bata Batoh Banda Aceh Aceh 23245 Indonesia Biochemical Engineering and Pilot Plant Research and Development Unit National Center for Genetic Engineering and Biotechnology at King Mongkut's University of Technology Thonburi Bang KhunThian Bangkok 10150 Thailand Bioinformatics and Systems Biology Program School of Bioresources and Technology King Mongkut's University of Technology Thonburi Bang KhunThian Bangkok 10150 Thailand

The nitrogen assimilation pathway in cassava was reconstructed by comparative genomics approach to understand the underlying metabolism as well as the interaction between carbon and nitrogen assimilation towards the synthesis of metabolic phenotype. First, theproteins of cassava were annotated via sequence similarity search against genes of 11 template plants obtained from KEGG and PMN databases, employing reciprocal BLASTp(E-value ≤ 1x10−10, identity percentage ≥ 60, and coverage percentage ≥ 80). The template plants comprised well-known plant, starchy crops, nitrogen-fixing crops and crops that are evolutionarily related to cassava and includedArabidopsis thaliana, Oryzasativa, Zea mays, Ricinuscommunis, Solanumtuberosum, Brassica rapa, Cicerarietinum, Jatrophacurcas, Medicagotruncatula, Phaseolus vulgaris and Glycine *** pathway was then curatedwith reactions obtained from the CassavaCyc database to ensure full pathway *** was subsequently validated with cloned sequence of cassava from the GenBank and cassava transcriptome data from literature. The resulting N-assimilation pathway, covering the conversion of nitrate to amino acids (glutamine and glutamate),consists of 14 biochemical reactions corresponding to 59 genes, 73 proteins and 2 transport reactions. At least 92 percent of the identified proteins in the pathway were supported by the transcriptome data. In addition, the proposed N-assimilation pathway contains four additional enzymes, including glutamate synthase, nitrilase, formamidase and carbamoyl phosphate synthasecompared to the existing N-assimilation pathway in CassavaCyc database. Taken together, the N-assimilation pathway herein proposed identified reactions involved in N-assimilation and represents a forward step towards understanding metabolic basis for cassava yield as well as its phenotypic plasticity and adaptation to stress.

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Comprehensive functional annotation of susceptibility variants identifies genetic heterogeneity between lung adenocarcinoma and squamous cell carcinoma

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Frontiers of Medicine 2021年第2期15卷 275-291页

作者： Na Qin Yuancheng Li Cheng Wang Meng Zhu Juncheng Dai Tongtong Hong Demetrius Albanes Stephen Lam Adonina Tardon Chu Chen Gary Goodman Stig EBojesen Maria Teresa Landi Mattias Johansson Angela Risch H-Erich Wichmann Heike Bickeboller Gadi Rennert Susanne Arnold Paul Brennan John KField Sanjay Shete Loic Le Marchand Olle Melander Hans Brunnstrom Geoffrey Liu Rayjean JHung Angeline Andrew Lambertus AKiemeney Shan Zienolddiny Kjell Grankvist Mikael Johansson Neil Caporaso Penella Woll Philip Lazarus Matthew BSchabath Melinda CAldrich Victoria LStevens Guangfu Jin David CChristiani Zhibin Hu Christopher IAmos Hongxia Ma Hongbing Shen Department of Epidemiology Center for Global HealthSchool of Public HealthNanjing Medical UniversityNanjing 211166China State Key Laboratory of Reproductive Medicine Center for Global HealthNanjing Medical UniversityNanjing 211166China Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China Jiangsu Key Lab of Cancer Biomarkers Prevention and TreatmentCollaborative Innovation Center for Cancer MedicineNanjing Medical UniversityNanjing 211166China China International Cooperation Center for Environment and Human Health School of Public HealthNanjing Medical UniversityNanjing 211166China Division of Cancer Epidemiology and Genetics National Cancer InstituteBethesdaMD 20892-9304USA Department of Integrative Oncology British Columbia Cancer AgencyVancouverBC V5Z 1L3Canada Faculty of Medicine University of Oviedo and CIBERESPOviedo 33006Spain Program in Epidemiology Public Health Sciences DivisionFred Hutchinson Cancer Research CenterSeattleWA 98109-1024USA Public Health Sciences Division Swedish Cancer InstituteSeattleWA 98026USA Department of Clinical Biochemistry Copenhagen University HospitalCopenhagen DK-1017Denmark National Cancer Institute BethesdaMD 20892-9304USA Genetic Epidemiology Group International Agency for Research on CancerLyon 69372France Cancer Center Cluster Salzburg at PLUS Department of Molecular BiologyUniversity of SalzburgHeidelberg 5020Austria Institute of Medical Informatics Biometry and EpidemiologyChair of EpidemiologyLudwig Maximilians UniversityMunichBavaria 80539Germany Department of Genetic Epidemiology University Medical Center GoettingenGoettingen 37075Germany Technion Faculty of Medicine Carmel Medical CenterHaifa 3448516Israel Markey Cancer Center University of KentuckyLexingtonKY 40506-0054USA Department of Molecular and Clinical Cancer Medicine Roy Castle Lung Cancer Research ProgrammeThe University of Liverpool Institute of Translational MedicineLiverpool L697Z

Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer(NSCLC)risk,biological mechanisms of these variants remain largely *** integrating a large-scale genotype data of 15581 lung adenocarcinoma(AD)cases,8350 squamous cell carcinoma(SqCC)cases,and 27355 controls,as well as multiple transcriptome and epigenomic databases,we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility *** identified 3064 credible risk variants for NSCLC,which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive *** factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was *** annotation and genebased analysis implicated 894 target genes,including 274 specifics for AD and 123 for SqCC,which were overrepresented in somatic driver genes(ER=1.95,P=0.005).Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways,while SqCC genes were homologous recombination deficiency *** results illustrate the molecular basis of both wellstudied and new susceptibility loci of NSCLC,providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.

关键词： lung cancer genome-wide association study function annotation immune homologous recombination repair deficiency genetic heterogeneity

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Gene expression experiment reveals negative enrichment of immune system related pathways in interictal migraineurs

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Neuroscience Applied 2022年 1卷

作者： S. Kumar K. Gecse T. Nagy D. Baksa G. Bagdy G. Juhasz P. Petschner 1Faculty of Pharmacy - Semmelweis University Department of Pharmacodynamics Budapest Hungary 2Hungarian Brain Research Program- Semmelweis University SE-NAP2 Genetic Brain Imaging Migraine Research Group Budapest Hungary 3Faculty of Electrical Engineering and Informatics - Budapest University of Technology and Economics Department of Measurement and Information Systems Budapest Hungary 4Hungarian Academy of Sciences - Semmelweis University MTA-SE Neuropsychopharmacology and Neurochemistry Research Group Budapest Hungary 5Hungarian Brain Research Program - Semmelweis University NAP-2-SE New Antidepressant Target Research Group Budapest Hungary 6Institute for Chemical Research - Kyoto University Bioinformatics Center Uji- Kyoto Japan

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Whole-genome and Transcriptome Sequencing of Prostate Cancer Identify New genetic Alterations Driving Disease Progression

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European urology 2018年第3期73卷 322-339页

作者： Shancheng Ren Gong-Hong Wei Dongbing Liu Liguo Wang Yong Hou Shida Zhu Lihua Peng Qin Zhang Yanbing Cheng Hong Su Xiuqing Zhou Jibin Zhang Fuqiang Li Hancheng Zheng Zhikun Zhao Changjun Yin Zengquan He Xin Gao Haiyen E Zhau Chia-Yi Chu Jason Boyang Wu Colin Collins Stanislav V Volik Robert Bell Jiaoti Huang Kui Wu Danfeng Xu Dingwei Ye Yongwei Yu Lianhui Zhu Meng Qiao Hang-Mao Lee Yuehong Yang Yasheng Zhu Xiaolei Shi Rui Chen Yang Wang Weidong Xu Yanqiong Cheng Chuanliang Xu Xu Gao Tie Zhou Bo Yang Jianguo Hou Li Liu Zhensheng Zhang Yao Zhu Chao Qin Pengfei Shao Jun Pang Leland W K Chung Jianfeng Xu Chin-Lee Wu Weide Zhong Xun Xu Yingrui Li Xiuqing Zhang Jian Wang Huanming Yang Jun Wang Haojie Huang Yinghao Sun Department of Urology Shanghai Changhai Hospital Second Military Medical University Shanghai China. Biocenter Oulu Faculty of Biochemistry and Molecular Medicine University of Oulu Oulu Finland. BGI-Shenzhen Shenzhen China China National GeneBank-Shenzhen BGI-Shenzhen Shenzhen China. Division of Biomedical Statistics and Informatics Mayo Clinic College of Medicine Rochester MN USA. China National GeneBank-Shenzhen BGI-Shenzhen Shenzhen China State Key Laboratory of Genetic Engineering School of Life Sciences Fudan University Shanghai China. Division of Genomics and Bioinformatics CUHK-BGI Innovation Institute of Trans-Omics The Chinese University of Hong Kong Hong Kong China. BGI Education Center University of Chinese Academy of Sciences Shenzhen China. BGI-Shenzhen Shenzhen China. School of Biological Science and Medical Engineering Southeast University Nanjing China State Key Laboratory of Bioelectronics Southeast University Nanjing China. Department of Urology The First Affiliated Hospital of Nanjing Medical University Nanjing China. Department of Urology The Third Affiliated Hospital of Sun Yat-Sen University Guangzhou China. Uro-Oncology Research Program Department of Medicine Samuel Oschin Comprehensive Cancer Institute Cedars-Sinai Medical Center Los Angeles CA USA. Vancouver Prostate Centre and Department of Urologic Sciences University of British Columbia Vancouver BC Canada. Department of Pathology and Laboratory Medicine David Geffen School of Medicine University of California Los Angeles CA USA. Department of Urology Changzheng Hospital Second Military Medical University Shanghai China. Department of Urology Fudan University Shanghai Cancer Center Shanghai China. Department of Pathology Shanghai Changhai Hospital Second Military Medical University Shanghai China. State Key Laboratory of Genetic Engineering School of Life Sciences Fudan University Shanghai China Program for Personalized Cancer Care NorthShore University HealthS

BACKGROUND:Global disparities in prostate cancer (PCa) incidence highlight the urgent need to identify genomic abnormalities in prostate tumors in different ethnic populations including Asian men. OBJECTIVE:To systematically explore the genomic complexity and define disease-driven genetic alterations in PCa. DESIGN, SETTING, AND PARTICIPANTS:The study sequenced whole-genome and transcriptome of tumor-benign paired tissues from 65 treatment-naive Chinese PCa patients. Subsequent targeted deep sequencing of 293 PCa-relevant genes was performed in another cohort of 145 prostate tumors. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS:The genomic alteration landscape in PCa was analyzed using an integrated computational pipeline. Relationships with PCa progression and survival were analyzed using nonparametric test, log-rank, and multivariable Cox regression analyses. RESULTS AND LIMITATIONS:We demonstrated an association of high frequency of CHD1 deletion with a low rate of TMPRSS2-ERG fusion and relatively high percentage of mutations in androgen receptor upstream activator genes in Chinese patients. We identified five putative clustered deleted tumor suppressor genes and provided experimental and clinical evidence that PCDH9, deleted/loss in approximately 23% of tumors, functions as a novel tumor suppressor gene with prognostic potential in PCa. Furthermore, axon guidance pathway genes were frequently deregulated, including gain/amplification of PLXNA1 gene in approximately 17% of tumors. Functional and clinical data analyses showed that increased expression of PLXNA1 promoted prostate tumor growth and independently predicted prostate tumor biochemical recurrence, metastasis, and poor survival in multi-institutional cohorts of patients with PCa. A limitation of this study is that other genetic alterations were not experimentally investigated. CONCLUSIONS:There are shared and salient genetic characteristics of PCa in Chinese and Caucasian men. Novel genetic alterations i

关键词： AR coactivator mutation Axon guidance pathway CHD1 deletion Chinese prostate cancer Clustered deleted tumor suppressor genes Personalized medicine Prognosis RNA-seq TMPRSS2-ERG fusion Whole genome sequencing

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GREGoR: Accelerating Genomics for Rare Diseases

arXiv

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arXiv 2024年

作者： Dawood, Moez Heavner, Ben Wheeler, Marsha M. Ungar, Rachel A. LoTempio, Jonathan Wiel, Laurens Berger, Seth Bernstein, Jonathan A. Chong, Jessica X. Délot, Emmanuèle C. Eichler, Evan E. Gibbs, Richard A. Lupski, James R. Shojaie, Ali Talkowski, Michael E. Wagner, Alex H. Wei, Chia-Lin Wellington, Christopher Wheeler, Matthew T. Carvalho, Claudia M.B. Gifford, Casey A. May, Susanne Miller, Danny E. Rehm, Heidi L. Sedlazeck, Fritz J. Vilain, Eric O'Donnell-Luria, Anne Posey, Jennifer E. Chadwick, Lisa H. Bamshad, Michael J. Montgomery, Stephen B. Human Genome Sequencing Center Baylor College of Medicine HoustonTX United States Department of Molecular and Human Genetics Baylor College of Medicine HoustonTX United States Medical Scientist Training Program Baylor College of Medicine HoustonTX United States Department of Biostatistics University of Washington SeattleWA United States Department of Genetics School of Medicine Stanford University StanfordCA United States Department of Pathology School of Medicine Stanford University Stanford CA United States Stanford Center for Biomedical Ethics School of Medicine Stanford University Stanford CA United States Institute for Clinical and Translational Science University of California IrvineCA United States Division of Cardiovascular Medicine School of Medicine Stanford University Stanford CA United States Division of Genetics and Metabolism Children’s National Rare Disease Institute WashingtonDC United States Center for Genetic Medicine Research Children’s National Rare Disease Institute WashingtonDC United States Department of Genomics and Precision Medicine George Washington University WashingtonDC United States Department of Pediatrics School of Medicine Stanford University Stanford CA United States Department of Pediatrics Dvision of Genetic Medicine University of Washington SeattleWA United States Brotman Baty Institute for Precision Medicine University of Washington SeattleWA United States Department of Genome Sciences University of Washington SeattleWA United States Howard Hughes Medical Institute University of Washington SeattleWA United States Department of Pediatrics Baylor College of Medicine HoustonTX United States Center for Genomic Medicine Massachusetts General Hospital BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard BostonMA United States Department of Neurology Massachusetts General Hospital Harvard Medical School BostonMA United States Stanley Center for

Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://***/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics. © 2024, CC BY.

关键词： Genome

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Data integration of bulk and single-cell transcriptomics from cerebral organoids and post-mortem brains to identify cell types and cell type specific driver genes in autism

Research Square

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Research Square 2020年

作者： Lim, Elaine T. Chan, Yingleong Burns, Mannix J. Guo, Xiaoge Erdin, Serkan Tai, Derek J.C. Reichert, Julia M. Chan, Ying Kai Chiang, Jessica J. Meyers, Katharina Zhang, Xiaochang Walsh, Christopher A. Yankner, Bruce A. Raychaudhuri, Soumya Hirschhorn, Joel N. Gusella, James F. Talkowski, Michael E. Church, George M. DZNE Germany Program in Bioinformatics and Integrative Biology Departments of Neurology and Molecular Cell and Cancer Biology University of Massachusetts Medical School WorcesterMA01605 United States Department of Genetics Harvard Medical School BostonMA02115 United States Wyss Institute for Biologically Inspired Engineering Harvard University BostonMA02115 United States Stanley Center for Psychiatric Research Broad Institute of MIT and Harvard CambridgeMA02115 United States Center for Genomic Medicine Massachusetts General Hospital BostonMA02115 United States Department of Neurology Massachusetts General Hospital BostonMA02115 United States Department of Human Genetics The Grossman Institute for Neuroscience Quantitative Biology and Human Behavior The University of Chicago ChicagoIL60637 United States Division of Genetics and Genomics Manton Center for Orphan Disease Research Howard Hughes Medical Institute Boston Children’s Hospital BostonMA02115 United States Departments of Pediatrics and Neurology Harvard Medical School BostonMA02115 United States Divisions of Genetics and Rheumatology Brigham and Women's Hospital Harvard Medical School BostonMA02115 United States Partners Center for Personalized Genetic Medicine BostonMA02115 United States Faculty of Medical and Human Sciences University of Manchester ManchesterM13 9PL United Kingdom Division of Endocrinology Boston Children's Hospital BostonMA02115 United States Center for Basic and Translational Obesity Research Boston Children's Hospital BostonMA02115 United States

Human-derived cerebral organoids demonstrate great promise for identifying cell types and cell type specific molecular processes perturbed by genetic variants associated with neuropsychiatric and neurodevelopmental disorders, which are notoriously challenging to study using animal models. However, considerable challenges remain in achieving robust, scalable and generalizable phenotyping of organoids to discover cell types and cell type specific genes. We perform RNA sequencing on 71 samples comprising 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to integrate bulk RNA and single-cell RNA sequence data from human post-mortem brains and cerebral organoids, for the identification of cell types and cell type specific individual genes. We apply Orgo-Seq for two autism-associated loci: 16p11.2 deletions and 15q11-13 duplications, and identify neuroepithelial cells as critical cell types for 16p11.2 deletions, and discover novel and previously reported cell type specific driver genes. Finally, we validated our results that mutations in the KCTD13 gene in the 16p11.2 locus lead to imbalances in the proportion of neuroepithelial cells, using CRISPR/Cas9-edited mosaic organoids. Our work presents a quantitative technological framework to integrate multiple transcriptomics datasets to identify cell types and cell type specific driver genes associated with complex diseases using cerebral organoids. © 2020, CC BY.

关键词： Genes

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The generation challenge programme platform: Semantic standards and workbench for crop science

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International Journal of Plant Genomics 2008年第unknown期2008卷 369601页

作者： Bruskiewich, Richard Senger, Martin Davenport, Guy Ruiz, Manuel Rouard, Mathieu Hazekamp, Tom Takeya, Masaru Doi, Koji Satoh, Kouji Costa, Marcos Simon, Reinhard Balaji, Jayashree Akintunde, Akinnola Mauleon, Ramil Wanchana, Samart Shah, Trushar Anacleto, Mylah Portugal, Arllet Ulat, Victor Jun Thongjuea, Supat Braak, Kyle Ritter, Sebastian Dereeper, Alexis Skofic, Milko Rojas, Edwin Martins, Natalia Pappas, Georgios Alamban, Ryan Almodiel, Roque Barboza, Lord Hendrix Detras, Jeffrey Manansala, Kevin Mendoza, Michael Jonathan Morales, Jeffrey Peralta, Barry Valerio, Rowena Zhang, Yi Gregorio, Sergio Hermocilla, Joseph Echavez, Michael Yap, Jan Michael Farmer, Andrew Schiltz, Gary Lee, Jennifer Casstevens, Terry Jaiswal, Pankaj Meintjes, Ayton Wilkinson, Mark Good, Benjamin Wagner, James Morris, Jane Marshall, David Collins, Anthony Kikuchi, Shoshi Metz, Thomas McLaren, Graham Van Hintum, Theo Crop Research Informatics Laboratory International Rice Research Institute (IRRI) DAPO Box 7777 Metro Manila Philippines Crop Research Informatics Laboratory International Maize and Wheat Improvement Center (CIMMYT) DF 06600 Mexico Apdo. Postal 6-641 Mexico Centre International de Recherche Agronomique Pour le Développement (CIRAD) 34398 Montpellier Cedex 5 Avenue Agropolis France Bioversity International 00057 Maccarese (Fiumicino) Rome Via dei Tre Denari 472/a Italy National Institute for Agrobiological Sciences (NIAS) Tsukuba Ibaraki 305-8602 Kannondai 2-1-2 Japan Empresa Brasileira de Pesquisa Agropecuaria (EMBRAPA) Brasilia DF 70770-900 Parque Estaçao Biologia Final W5 Norte Brazil Centro Internacional de la Papa (CIP) Lima 12 Avenida La Molina 1895 La Molina Peru International Crops Research Institute for the Semi-Arid Tropics Patancheru Andhra Pradesh 502324 India International Center for Agricultural Research in the Dry Areas Aleppo P.O. Box 5466 Syrian Arab Republic National Center for Genetic Engineering and Biotechnology 113 Thailand Science Park Klong Luang Pathumthani 12120 Phahonyothin Road Klong 1 Thailand Institute of Computer Science College of Arts and Sciences University of the Philippines Los Banos Laguna 4031 Philippines Department of Computer Science University of the Philippines Melchor Hall Diliman Quezon City 1101 Philippines National Center for Genome Resources Santa Fe NM 87505 2935 Rodeo Park Drive East United States Scottish Crop Research Institute Invergowrie Dundee DD2 5DA United Kingdom Department of Plant Breeding Cornell University Ithaca NY 14853 United States African Centre for Gene Technologies Lynnwood Ridge 0040 P.O. Box 75011 South Africa Department of Medical Genetics Faculty of Medicine University of British Columbia Vancouver BC V6T 1Z3 Canada School of Computing Science Simon Fraser Universtiy Burnaby BC V5A 1S6 8888 University Drive Canada Bioinformatics Graduate Program Genome Sciences Centre BC

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform;(ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data;(iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.

关键词： GENOMICS GERMPLASM resources PLANT breeding PLANT genetics COMPUTERS in biology bioinformatics -- Software

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