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Gupta P, Elser J, Hooks E, D’Eustachio P, Jaiswal P, Naithani S. Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis. Nucleic Acids Res 2024; 52:D1538-D1547. [PMID: 37986220 PMCID: PMC10767815 DOI: 10.1093/nar/gkad1052] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 10/20/2023] [Accepted: 10/23/2023] [Indexed: 11/22/2023] Open
Abstract
Plant Reactome (https://plantreactome.gramene.org) is a freely accessible, comprehensive plant pathway knowledgebase. It provides curated reference pathways from rice (Oryza sativa) and gene-orthology-based pathway projections to 129 additional species, spanning single-cell photoautotrophs, non-vascular plants, and higher plants, thus encompassing a wide-ranging taxonomic diversity. Currently, Plant Reactome houses a collection of 339 reference pathways, covering metabolic and transport pathways, hormone signaling, genetic regulations of developmental processes, and intricate transcriptional networks that orchestrate a plant's response to abiotic and biotic stimuli. Beyond being a mere repository, Plant Reactome serves as a dynamic data discovery platform. Users can analyze and visualize omics data, such as gene expression, gene-gene interaction, proteome, and metabolome data, all within the rich context of plant pathways. Plant Reactome is dedicated to fostering data interoperability, upholding global data standards, and embracing the tenets of the Findable, Accessible, Interoperable and Re-usable (FAIR) data policy.
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Affiliation(s)
- Parul Gupta
- Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Justin Elser
- Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Elizabeth Hooks
- Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | | | - Pankaj Jaiswal
- Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Sushma Naithani
- Department of Botany & Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
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Myers ZA, Wootan CM, Liang Z, Zhou P, Engelhorn J, Hartwig T, Nathan SM. Conserved and variable heat stress responses of the Heat Shock Factor transcription factor family in maize and Setaria viridis. Plant Direct 2023; 7:e489. [PMID: 37124872 PMCID: PMC10133983 DOI: 10.1002/pld3.489] [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] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Revised: 01/31/2023] [Accepted: 02/24/2023] [Indexed: 05/03/2023]
Abstract
The Heat Shock Factor (HSF) transcription factor family is a central and required component of plant heat stress responses and acquired thermotolerance. The HSF family has dramatically expanded in plant lineages, often including a repertoire of 20 or more genes. Here we assess and compare the composition, heat responsiveness, and chromatin profiles of the HSF families in maize and Setaria viridis (Setaria), two model C4 panicoid grasses. Both species encode a similar number of HSFs, and examples of both conserved and variable expression responses to a heat stress event were observed between the two species. Chromatin accessibility and genome-wide DNA-binding profiles were generated to assess the chromatin of HSF family members with distinct responses to heat stress. We observed significant variability for both chromatin accessibility and promoter occupancy within similarly regulated sets of HSFs between Setaria and maize, as well as between syntenic pairs of maize HSFs retained following its most recent genome duplication event. Additionally, we observed the widespread presence of TF binding at HSF promoters in control conditions, even at HSFs that are only expressed in response to heat stress. TF-binding peaks were typically near putative HSF-binding sites in HSFs upregulated in response to heat stress, but not in stable or not expressed HSFs. These observations collectively support a complex scenario of expansion and subfunctionalization within this transcription factor family and suggest that within-family HSF transcriptional regulation is a conserved, defining feature of the family.
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Affiliation(s)
- Zachary A. Myers
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
| | - Clair M. Wootan
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
| | - Zhikai Liang
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
| | - Peng Zhou
- Chinese Academy of Agricultural SciencesInstitute of Crop SciencesBeijingChina
| | - Julia Engelhorn
- Heinrich‐Heine UniversityDüsseldorfGermany
- Max Planck Institute for Plant Breeding ResearchCologneGermany
| | - Thomas Hartwig
- Heinrich‐Heine UniversityDüsseldorfGermany
- Max Planck Institute for Plant Breeding ResearchCologneGermany
| | - Springer M. Nathan
- Department of Plant and Microbial BiologyUniversity of MinnesotaMinneapolisMNUSA
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Burks DJ, Pusadkar V, Azad RK. POSMM: an efficient alignment-free metagenomic profiler that complements alignment-based profiling. Environ Microbiome 2023; 18:16. [PMID: 36890583 PMCID: PMC9993663 DOI: 10.1186/s40793-023-00476-y] [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] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 02/25/2023] [Indexed: 06/18/2023]
Abstract
We present here POSMM (pronounced 'Possum'), Python-Optimized Standard Markov Model classifier, which is a new incarnation of the Markov model approach to metagenomic sequence analysis. Built on the top of a rapid Markov model based classification algorithm SMM, POSMM reintroduces high sensitivity associated with alignment-free taxonomic classifiers to probe whole genome or metagenome datasets of increasingly prohibitive sizes. Logistic regression models generated and optimized using the Python sklearn library, transform Markov model probabilities to scores suitable for thresholding. Featuring a dynamic database-free approach, models are generated directly from genome fasta files per run, making POSMM a valuable accompaniment to many other programs. By combining POSMM with ultrafast classifiers such as Kraken2, their complementary strengths can be leveraged to produce higher overall accuracy in metagenomic sequence classification than by either as a standalone classifier. POSMM is a user-friendly and highly adaptable tool designed for broad use by the metagenome scientific community.
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Affiliation(s)
- David J Burks
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA
| | - Vaidehi Pusadkar
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA
| | - Rajeev K Azad
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA.
- Department of Mathematics, University of North Texas, Denton, TX, 76203, USA.
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Zargar SM, Mir RA, Ebinezer LB, Masi A, Hami A, Manzoor M, Salgotra RK, Sofi NR, Mushtaq R, Rohila JS, Rakwal R. Physiological and Multi-Omics Approaches for Explaining Drought Stress Tolerance and Supporting Sustainable Production of Rice. Front Plant Sci 2022; 12:803603. [PMID: 35154193 PMCID: PMC8829427 DOI: 10.3389/fpls.2021.803603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/14/2021] [Indexed: 05/12/2023]
Abstract
Drought differs from other natural disasters in several respects, largely because of the complexity of a crop's response to it and also because we have the least understanding of a crop's inductive mechanism for addressing drought tolerance among all abiotic stressors. Overall, the growth and productivity of crops at a global level is now thought to be an issue that is more severe and arises more frequently due to climatic change-induced drought stress. Among the major crops, rice is a frontline staple cereal crop of the developing world and is critical to sustaining populations on a daily basis. Worldwide, studies have reported a reduction in rice productivity over the years as a consequence of drought. Plants are evolutionarily primed to withstand a substantial number of environmental cues by undergoing a wide range of changes at the molecular level, involving gene, protein and metabolite interactions to protect the growing plant. Currently, an in-depth, precise and systemic understanding of fundamental biological and cellular mechanisms activated by crop plants during stress is accomplished by an umbrella of -omics technologies, such as transcriptomics, metabolomics and proteomics. This combination of multi-omics approaches provides a comprehensive understanding of cellular dynamics during drought or other stress conditions in comparison to a single -omics approach. Thus a greater need to utilize information (big-omics data) from various molecular pathways to develop drought-resilient crop varieties for cultivation in ever-changing climatic conditions. This review article is focused on assembling current peer-reviewed published knowledge on the use of multi-omics approaches toward expediting the development of drought-tolerant rice plants for sustainable rice production and realizing global food security.
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Affiliation(s)
- Sajad Majeed Zargar
- Proteomics Laboratory, Division of Plant Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Rakeeb Ahmad Mir
- Department of Biotechnology, School of Biosciences and Biotechnology, BGSB University, Rajouri, India
| | - Leonard Barnabas Ebinezer
- Department of Agronomy, Food, Natural Resources, Animals, and Environment, University of Padova, Padua, Italy
| | - Antonio Masi
- Department of Agronomy, Food, Natural Resources, Animals, and Environment, University of Padova, Padua, Italy
| | - Ammarah Hami
- Proteomics Laboratory, Division of Plant Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Madhiya Manzoor
- Proteomics Laboratory, Division of Plant Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Romesh K. Salgotra
- School of Biotechnology, Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu, Jammu, India
| | - Najeebul Rehman Sofi
- Division of Plant Breeding and Genetics, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
| | - Roohi Mushtaq
- Department of Biotechnology and Bioinformatics, SP College, Cluster University Srinagar, Srinagar, India
| | - Jai Singh Rohila
- Dale Bumpers National Rice Research Center, United States Department of Agriculture (USDA)-Agricultural Research Service (ARS), Stuttgart, AR, United States
| | - Randeep Rakwal
- Faculty of Health and Sport Sciences, University of Tsukuba, Ibaraki, Japan
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Alves Oliveira D, Tang JD, Warburton ML. Reference Gene Selection for RT-qPCR Analysis in Maize Kernels Inoculated with Aspergillus flavus. Toxins (Basel) 2021; 13:386. [PMID: 34071223 DOI: 10.3390/toxins13060386] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 05/18/2021] [Accepted: 05/25/2021] [Indexed: 11/22/2022] Open
Abstract
Resistance against infection by the fungus Aspergillus flavus Link in commercial maize (Zea mays L.) is the topic of many studies, but few studies have investigated the effects of A. flavus infection on gene expression levels in ear kernels. A crucial component of gene expression profiling by RT-qPCR is having a reliable set of reference genes that show relatively constant expression across the treatments and phenotypes under study. Currently, however, there is no published information on reference genes suitable for measuring changes in kernel gene expression levels after infection with A. flavus. Thus, in this study, six candidate reference genes (ACT1, β-Tub2, eIF4A2, TATA, EFIα, and GAPDH) were evaluated and ranked according to their expression stability. The genes were amplified from first-strand cDNA samples synthesized from kernels of two susceptible and two resistant maize lines that were either inoculated with A. flavus or water or not inoculated. Three software packages were used to calculate and rank the stability of expression for these genesgeNorm, NormFinder, and BestKeeper. The analysis revealed that the most stable genes to normalize expression levels from maize kernels responding to A. flavus inoculation and wounding were ACT1, EFIα, and eIF4A2.
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Hu Y, Colantonio V, Müller BSF, Leach KA, Nanni A, Finegan C, Wang B, Baseggio M, Newton CJ, Juhl EM, Hislop L, Gonzalez JM, Rios EF, Hannah LC, Swarts K, Gore MA, Hennen-Bierwagen TA, Myers AM, Settles AM, Tracy WF, Resende MFR Jr. Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn. Nat Commun 2021; 12:1227. [PMID: 33623026 DOI: 10.1038/s41467-021-21380-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 01/26/2021] [Indexed: 01/31/2023] Open
Abstract
Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92% of the total assembly and 99% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn.
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Ribeiro C, Hennen-Bierwagen TA, Myers AM, Cline K, Settles AM. Engineering 6-phosphogluconate dehydrogenase improves grain yield in heat-stressed maize. Proc Natl Acad Sci U S A 2020; 117:33177-33185. [PMID: 33323483 DOI: 10.1101/2020.05.21.108985] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/22/2023] Open
Abstract
Endosperm starch synthesis is a primary determinant of grain yield and is sensitive to high-temperature stress. The maize chloroplast-localized 6-phosphogluconate dehydrogenase (6PGDH), PGD3, is critical for endosperm starch accumulation. Maize also has two cytosolic isozymes, PGD1 and PGD2, that are not required for kernel development. We found that cytosolic PGD1 and PGD2 isozymes have heat-stable activity, while amyloplast-localized PGD3 activity is labile under heat stress conditions. We targeted heat-stable 6PGDH to endosperm amyloplasts by fusing the Waxy1 chloroplast targeting the peptide coding sequence to the Pgd1 and Pgd2 open reading frames (ORFs). These WPGD1 and WPGD2 fusion proteins import into isolated chloroplasts, demonstrating a functional targeting sequence. Transgenic maize plants expressing WPGD1 and WPGD2 with an endosperm-specific promoter increased 6PGDH activity with enhanced heat stability in vitro. WPGD1 and WPGD2 transgenes complement the pgd3-defective kernel phenotype, indicating the fusion proteins are targeted to the amyloplast. In the field, the WPGD1 and WPGD2 transgenes can mitigate grain yield losses in high-nighttime-temperature conditions by increasing kernel number. These results provide insight into the subcellular distribution of metabolic activities in the endosperm and suggest the amyloplast pentose phosphate pathway is a heat-sensitive step in maize kernel metabolism that contributes to yield loss during heat stress.
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Affiliation(s)
- Camila Ribeiro
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611
- Plant Molecular and Cellular Biology Program, University of Florida, Gainesville, FL 32611
| | - Tracie A Hennen-Bierwagen
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011
| | - Alan M Myers
- Roy J. Carver Department of Biochemistry, Biophysics and Molecular Biology, Iowa State University, Ames, IA 50011
| | - Kenneth Cline
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611
- Plant Molecular and Cellular Biology Program, University of Florida, Gainesville, FL 32611
| | - A Mark Settles
- Horticultural Sciences Department, University of Florida, Gainesville, FL 32611
- Plant Molecular and Cellular Biology Program, University of Florida, Gainesville, FL 32611
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Ribeiro C, Hennen-Bierwagen TA, Myers AM, Cline K, Settles AM. Engineering 6-phosphogluconate dehydrogenase improves grain yield in heat-stressed maize. Proc Natl Acad Sci U S A 2020:202010179. [PMID: 33323483 DOI: 10.1073/pnas.2010179117] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023] Open
Abstract
Endosperm starch synthesis is a primary determinant of grain yield and is sensitive to high-temperature stress. The maize chloroplast-localized 6-phosphogluconate dehydrogenase (6PGDH), PGD3, is critical for endosperm starch accumulation. Maize also has two cytosolic isozymes, PGD1 and PGD2, that are not required for kernel development. We found that cytosolic PGD1 and PGD2 isozymes have heat-stable activity, while amyloplast-localized PGD3 activity is labile under heat stress conditions. We targeted heat-stable 6PGDH to endosperm amyloplasts by fusing the Waxy1 chloroplast targeting the peptide coding sequence to the Pgd1 and Pgd2 open reading frames (ORFs). These WPGD1 and WPGD2 fusion proteins import into isolated chloroplasts, demonstrating a functional targeting sequence. Transgenic maize plants expressing WPGD1 and WPGD2 with an endosperm-specific promoter increased 6PGDH activity with enhanced heat stability in vitro. WPGD1 and WPGD2 transgenes complement the pgd3-defective kernel phenotype, indicating the fusion proteins are targeted to the amyloplast. In the field, the WPGD1 and WPGD2 transgenes can mitigate grain yield losses in high-nighttime-temperature conditions by increasing kernel number. These results provide insight into the subcellular distribution of metabolic activities in the endosperm and suggest the amyloplast pentose phosphate pathway is a heat-sensitive step in maize kernel metabolism that contributes to yield loss during heat stress.
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Eseverri Á, Baysal C, Medina V, Capell T, Christou P, Rubio LM, Caro E. Transit Peptides From Photosynthesis-Related Proteins Mediate Import of a Marker Protein Into Different Plastid Types and Within Different Species. Front Plant Sci 2020; 11:560701. [PMID: 33101328 PMCID: PMC7545105 DOI: 10.3389/fpls.2020.560701] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 09/07/2020] [Indexed: 06/01/2023]
Abstract
Nucleus-encoded plastid proteins are synthesized as precursors with N-terminal targeting signals called transit peptides (TPs), which mediate interactions with the translocon complexes at the outer (TOC) and inner (TIC) plastid membranes. These complexes exist in multiple isoforms in higher plants and show differential specificity and tissue abundance. While some show specificity for photosynthesis-related precursor proteins, others distinctly recognize nonphotosynthetic and housekeeping precursor proteins. Here we used TPs from four Arabidopsis thaliana proteins, three related to photosynthesis (chlorophyll a/b binding protein, Rubisco activase) and photo-protection (tocopherol cyclase) and one involved in the assimilation of ammonium into amino-acids, and whose expression is most abundant in the root (ferredoxin dependent glutamate synthase 2), to determine whether they were able to mediate import of a nuclear-encoded marker protein into plastids of different tissues of a dicot and a monocot species. In A. thaliana, import and processing efficiency was high in all cases, while TP from the rice Rubisco small chain 1, drove very low import in Arabidopsis tissues. Noteworthy, our results show that Arabidopsis photosynthesis TPs also mediate plastid import in rice callus, and in leaf and root tissues with almost a 100% efficiency, providing new biotechnological tools for crop improvement strategies based on recombinant protein accumulation in plastids by the expression of nuclear-encoded transgenes.
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Affiliation(s)
- Álvaro Eseverri
- Centre for Plant Biotechnology and Genomics, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Pozuelo de Alarcón, Spain
- Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, Spain
| | - Can Baysal
- Department of Plant Production and Forestry Science, University of Lleida-Agrotecnio Center, Lleida, Spain
| | - Vicente Medina
- Department of Plant Production and Forestry Science, University of Lleida-Agrotecnio Center, Lleida, Spain
| | - Teresa Capell
- Department of Plant Production and Forestry Science, University of Lleida-Agrotecnio Center, Lleida, Spain
| | - Paul Christou
- Department of Plant Production and Forestry Science, University of Lleida-Agrotecnio Center, Lleida, Spain
- ICREA, Catalan Institute for Research and Advanced Studies, Barcelona, Spain
| | - Luis M. Rubio
- Centre for Plant Biotechnology and Genomics, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Pozuelo de Alarcón, Spain
- Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, Spain
| | - Elena Caro
- Centre for Plant Biotechnology and Genomics, Universidad Politécnica de Madrid (UPM) - Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Pozuelo de Alarcón, Spain
- Departamento de Biotecnología-Biología Vegetal, Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Madrid, Spain
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Mokhtar MM, Atia MAM. SSRome: an integrated database and pipelines for exploring microsatellites in all organisms. Nucleic Acids Res 2020; 47:D244-D252. [PMID: 30365025 PMCID: PMC6323889 DOI: 10.1093/nar/gky998] [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] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Accepted: 10/14/2018] [Indexed: 11/23/2022] Open
Abstract
Over the past decade, many databases focusing on microsatellite mining on a genomic scale were released online with at least one of the following major deficiencies: (i) lacking the classification of microsatellites as genic or non-genic, (ii) not comparing microsatellite motifs at both genic and non-genic levels in order to identify unique motifs for each class or (iii) missing SSR marker development. In this study, we have developed ‘SSRome’ as a web-based, user-friendly, comprehensive and dynamic database with pipelines for exploring microsatellites in 6533 organisms. In the SSRome database, 158 million microsatellite motifs are identified across all taxa, in addition to all the mitochondrial and chloroplast genomes and expressed sequence tags available from NCBI. Moreover, 45.1 million microsatellite markers were developed and classified as genic or non-genic. All the stored motif and marker datasets can be downloaded freely. In addition, SSRome provides three user-friendly tools to identify, classify and compare motifs on either a genome- or transcriptome-wide scale. With the implementation of PHP, HTML and JavaScript, users can upload their data for analysis via a user-friendly GUI. SSRome represents a powerful database and mega-tool that will assist researchers in developing and dissecting microsatellite markers on a high-throughput scale.
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Affiliation(s)
- Morad M Mokhtar
- Molecular Genetics and Genome Mapping Laboratory, Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), ARC, Giza, 12619, Egypt
| | - Mohamed A M Atia
- Molecular Genetics and Genome Mapping Laboratory, Genome Mapping Department, Agricultural Genetic Engineering Research Institute (AGERI), ARC, Giza, 12619, Egypt
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Kamboj R, Singh B, Mondal TK, Bisht DS. Current status of genomic resources on wild relatives of rice. Breed Sci 2020; 70:135-144. [PMID: 32523396 PMCID: PMC7272243 DOI: 10.1270/jsbbs.19064] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2019] [Accepted: 09/26/2019] [Indexed: 06/02/2023]
Abstract
Rice is a food crop of global importance, cultivated in diverse agro-climatic zones of the world. However, in the process of domestication many beneficial alleles have been eroded from the gene pool of the rice cultivated globally and eventually has made it vulnerable to a plethora of stresses. In contrast, the wild relatives of rice, despite being agronomically inferior, have inherited a potential of surviving in a range of geographical habitats. These adaptations enrich them with novel traits that upon introgression to modern cultivated varieties offer tremendous potential of increasing yield and adaptability. But, due to the unavailability of their genetic as well as genomic resources, identification and characterisation of these novel beneficial alleles has been a challenging task. Nevertheless, with the unprecedented surge in the area of conservation genomics, researchers have now shifted their focus towards these natural repositories of beneficial traits. Presently, there are several generic and specialized databases harboring genome-wide information on wild species of rice, and are acting as a useful resource for identification of novel genes and alleles, designing of molecular markers, comparative analysis and evolutionary biology studies. In this review, we introduce the key features of these databases focusing on their utility in rice breeding programs.
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Affiliation(s)
- Richa Kamboj
- National Institute for Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - Balwant Singh
- National Institute for Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - Tapan Kumar Mondal
- National Institute for Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
| | - Deepak Singh Bisht
- National Institute for Plant Biotechnology, LBS Building, Pusa Campus, New Delhi 110012, India
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Scheben A, Chan CKK, Mansueto L, Mauleon R, Larmande P, Alexandrov N, Wing RA, McNally KL, Quesneville H, Edwards D. Progress in single-access information systems for wheat and rice crop improvement. Brief Bioinform 2020; 20:565-571. [PMID: 29659709 DOI: 10.1093/bib/bby016] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Improving productivity of the staple crops wheat and rice is essential to feed the growing global population, particularly in the context of a changing climate. However, current rates of yield gain are insufficient to support the predicted population growth. New approaches are required to accelerate the breeding process, and many of these are driven by the application of large-scale crop data. To leverage the substantial volumes and types of data that can be applied for precision breeding, the wheat and rice research communities are working towards the development of integrated systems to access and standardize the dispersed, heterogeneous available data. Here, we outline the initiatives of the International Wheat Information System (WheatIS) and the International Rice Informatics Consortium (IRIC) to establish Web-based single-access systems and data mining tools to make the available resources more accessible, drive discovery and accelerate the production of new crop varieties. We discuss the progress of WheatIS and IRIC towards unifying specialized wheat and rice databases and building custom software platforms to manage and interrogate these data. Single-access crop information systems will strengthen scientific collaboration, optimize the use of public research funds and help achieve the required yield gains in the two most important global food crops.
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Affiliation(s)
- Armin Scheben
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, 6009 Perth, WA, Australia
| | - Chon-Kit Kenneth Chan
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, 6009 Perth, WA, Australia
| | - Locedie Mansueto
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | - Ramil Mauleon
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | - Pierre Larmande
- IRD, UMR DIADE (Plant Diversity Adaptation and Development Research unit) , 911 Avenue Agropolis, 34394 Montpellier, France
| | - Nickolai Alexandrov
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | - Rod A Wing
- Arizona Genomics Institute, University of Arizona, Tucson, Arizona, USA
| | - Kenneth L McNally
- International Rice Research Institute, DAPO Box 7777, Metro Manila 1301, The Philippines
| | | | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, 6009 Perth, WA, Australia
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13
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McDermaid A, Monier B, Zhao J, Liu B, Ma Q. Interpretation of differential gene expression results of RNA-seq data: review and integration. Brief Bioinform 2019; 20:2044-2054. [PMID: 30099484 PMCID: PMC6954399 DOI: 10.1093/bib/bby067] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 06/21/2018] [Accepted: 07/04/2018] [Indexed: 12/23/2022] Open
Abstract
Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many applications of RNA-seq data analysis. Interpretation of the DGE results can be nonintuitive and time consuming due to the variety of formats based on the tool of choice and the numerous pieces of information provided in these results files. Here we reviewed DGE results analysis from a functional point of view for various visualizations. We also provide an R/Bioconductor package, Visualization of Differential Gene Expression Results using R, which generates information-rich visualizations for the interpretation of DGE results from three widely used tools, Cuffdiff, DESeq2 and edgeR. The implemented functions are also tested on five real-world data sets, consisting of one human, one Malus domestica and three Vitis riparia data sets.
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Affiliation(s)
- Adam McDermaid
- Department of Mathematics and Statistics, South Dakota State University, Brookings, SD, USA
| | - Brandon Monier
- Department of Biology and Microbiology, South Dakota State University, SD, USA
| | - Jing Zhao
- Department of Internal Medicine, Sanford Research, University of South Dakota Sanford School of Medicine
| | | | - Qin Ma
- Department of Agronomy, Horticulture, and Plant Science, Bioinformatics and Mathematical Biosciences Lab, South Dakota State University
- Department of Mathematics and Statistics of SDSU, BioSNTR and Sanford Research, USA
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14
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Chen J, Jiao Y, Laza H, Payton P, Ware D, Xin Z. Identification of the First Nuclear Male Sterility Gene (Male-sterile 9) in Sorghum. Plant Genome 2019; 12:1-12. [PMID: 33016577 DOI: 10.3835/plantgenome2019.03.0020] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 05/03/2019] [Indexed: 06/11/2023]
Abstract
The male-sterile 9 (ms9) is a novel nuclear male-sterile mutant in sorghum. The Ms9 gene encodes a PHD-finger transcription factor critical for pollen development. The identification of the Ms9 gene provides a strategy to control male sterility in sorghum. Nuclear male sterility (NMS) is important for understanding microspore development and could facilitate the development of new strategies to control male sterility. Several NMS lines and mutants have been reported in sorghum [Sorghum bicolor (L.) Moench] previously. However, no male-sterile gene has been identified, hampering the utility of NMS in sorghum breeding. In this study, we characterized a new NMS mutant, male sterile 9 (ms9), which is distinct from all other reported NMS loci. The ms9 mutant is stable under a variety of environmental conditions. Homozygous ms9 plants produced normal ovaries but small pale-colored anthers that contained no pollen grains. Microscopic analyses revealed abnormal microspore development of ms9 at the midmicrospore stage, causing degeneration of microspore inside the anther lobes and male sterility of ms9 plants. Using MutMap, we identified the Ms9 gene as a plant homeotic domain (PHD)-finger transcription factor similar to Ms1 in Arabidopsis thaliana (L.) Heynh. and Ptc1 in rice (Oryza sativa L.). Ms9 is the first NMS gene identified in sorghum. Thus, the Ms9 gene and ms9 mutant provide new genetic tools for studying pollen development and controlling male sterility in sorghum.
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Affiliation(s)
- Junping Chen
- Plant Stress and Germplasm Development Unit, USDA-ARS, Lubbock, TX, 79415
| | | | - Haydee Laza
- Plant Stress and Germplasm Development Unit, USDA-ARS, Lubbock, TX, 79415
| | - Paxton Payton
- Plant Stress and Germplasm Development Unit, USDA-ARS, Lubbock, TX, 79415
| | - Doreen Ware
- Cold Spring Harbor Lab., Cold Spring Harbor, NY
- Soil and Nutrition Lab. Research Unit, USDA-ARS, Cornell Univ., Ithaca, NY
| | - Zhanguo Xin
- Plant Stress and Germplasm Development Unit, USDA-ARS, Lubbock, TX, 79415
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15
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Tello-Ruiz MK, Naithani S, Stein JC, Gupta P, Campbell M, Olson A, Wei S, Preece J, Geniza MJ, Jiao Y, Lee YK, Wang B, Mulvaney J, Chougule K, Elser J, Al-Bader N, Kumari S, Thomason J, Kumar V, Bolser DM, Naamati G, Tapanari E, Fonseca N, Huerta L, Iqbal H, Keays M, Munoz-Pomer Fuentes A, Tang A, Fabregat A, D'Eustachio P, Weiser J, Stein LD, Petryszak R, Papatheodorou I, Kersey PJ, Lockhart P, Taylor C, Jaiswal P, Ware D. Gramene 2018: unifying comparative genomics and pathway resources for plant research. Nucleic Acids Res 2019; 46:D1181-D1189. [PMID: 29165610 PMCID: PMC5753211 DOI: 10.1093/nar/gkx1111] [Citation(s) in RCA: 91] [Impact Index Per Article: 18.2] [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] [Received: 09/15/2017] [Accepted: 10/25/2017] [Indexed: 12/24/2022] Open
Abstract
Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.
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Affiliation(s)
| | - Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Joshua C Stein
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Parul Gupta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Michael Campbell
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Sharon Wei
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Justin Preece
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Matthew J Geniza
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Yinping Jiao
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Young Koung Lee
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.,Division of Biological Sciences and Institute for Basic Science, Wonkwang University, Iksan 54538, Korea
| | - Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Joseph Mulvaney
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Kapeel Chougule
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Noor Al-Bader
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Sunita Kumari
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - James Thomason
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Vivek Kumar
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Daniel M Bolser
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Guy Naamati
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Electra Tapanari
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Nuno Fonseca
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Laura Huerta
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Haider Iqbal
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Maria Keays
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | | | - Amy Tang
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Antonio Fabregat
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Peter D'Eustachio
- Department of Biochemistry & Molecular Pharmacology, NYU School of Medicine, New York, NY 10016, USA
| | - Joel Weiser
- Informatics and Bio-computing Program, Ontario Institute of Cancer Research, Toronto, M5G 1L7, Canada
| | - Lincoln D Stein
- Adaptive Oncology Program, Ontario Institute for Cancer Research, Toronto M5G 0A3, Canada
| | - Robert Petryszak
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Irene Papatheodorou
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Paul J Kersey
- EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SD, UK
| | - Patti Lockhart
- American Society of Plant Biologists, 15501 Monona Drive, Rockville, MD 20855-2768, USA
| | - Crispin Taylor
- American Society of Plant Biologists, 15501 Monona Drive, Rockville, MD 20855-2768, USA
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA.,USDA ARS NAA Robert W. Holley Center for Agriculture and Health, Agricultural Research Service, Ithaca, NY 14853, USA
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16
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Lee T, Lee S, Yang S, Lee I. MaizeNet: a co-functional network for network-assisted systems genetics in Zea mays. Plant J 2019; 99:571-582. [PMID: 31006149 DOI: 10.1111/tpj.14341] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 03/21/2019] [Accepted: 03/28/2019] [Indexed: 05/27/2023]
Abstract
Maize (Zea mays) has multiple uses in human food, animal fodder, starch and sweetener production and as a biofuel, and is accordingly the most extensively cultivated cereal worldwide. To enhance maize production, genetic factors underlying important agricultural traits, including stress tolerance and flowering, have been explored through forward and reverse genetics approaches. Co-functional gene networks are systems biology resources useful in identifying trait-associated genes in plants by prioritizing candidate genes. Here, we present MaizeNet (http://www.inetbio.org/maizenet/), a genome-scale co-functional network of Z. mays genes, and a companion web server for network-assisted systems genetics. We describe the validation of MaizeNet network quality and its ability to functionally predict molecular pathways and complex traits in maize. Furthermore, we demonstrate that MaizeNet-based prioritization of candidate genes can facilitate the identification of cell wall biosynthesis genes and detect network communities associated with flowering-time candidate genes derived from genome-wide association studies. The demonstrated gene prioritization and subnetwork analysis can be conducted by simply submitting maize gene models based on the commonly used B73 RefGen_v3 and the latest B73 RefGen_v4 reference genomes on the MaizeNet web server. MaizeNet-based network-assisted systems genetics will substantially accelerate the discovery of trait-associated genes for crop improvement.
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Affiliation(s)
- Tak Lee
- Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, 03722, Korea
| | - Sungho Lee
- Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, 03722, Korea
| | - Sunmo Yang
- Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, 03722, Korea
| | - Insuk Lee
- Department of Biotechnology, College of Life Sciences and Biotechnology, Yonsei University, Seoul, 03722, Korea
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17
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Tian T, Liu Y, Yan H, You Q, Yi X, Du Z, Xu W, Su Z. agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update. Nucleic Acids Res 2019; 45:W122-W129. [PMID: 28472432 PMCID: PMC5793732 DOI: 10.1093/nar/gkx382] [Citation(s) in RCA: 1302] [Impact Index Per Article: 260.4] [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] [Received: 01/14/2017] [Accepted: 04/25/2017] [Indexed: 01/30/2023] Open
Abstract
The agriGO platform, which has been serving the scientific community for >10 years, specifically focuses on gene ontology (GO) enrichment analyses of plant and agricultural species. We continuously maintain and update the databases and accommodate the various requests of our global users. Here, we present our updated agriGO that has a largely expanded number of supporting species (394) and datatypes (865). In addition, a larger number of species have been classified into groups covering crops, vegetables, fish, birds and insects closely related to the agricultural community. We further improved the computational efficiency, including the batch analysis and P-value distribution (PVD), and the user-friendliness of the web pages. More visualization features were added to the platform, including SEACOMPARE (cross comparison of singular enrichment analysis), direct acyclic graph (DAG) and Scatter Plots, which can be merged by choosing any significant GO term. The updated platform agriGO v2.0 is now publicly accessible at http://systemsbiology.cau.edu.cn/agriGOv2/.
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Affiliation(s)
- Tian Tian
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Yue Liu
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Hengyu Yan
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Qi You
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Xin Yi
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Zhou Du
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Wenying Xu
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Zhen Su
- State Key Laboratory of Plant Physiology and Biochemistry, College of Biological Sciences, China Agricultural University, Beijing 100193, China
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18
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Jimmy JL, Babu S. Variations in the Structure and Evolution of Rice WRKY Genes in Indica and Japonica Genotypes and their Co-expression Network in Mediating Disease Resistance. Evol Bioinform Online 2019; 15:1176934319857720. [PMID: 31236008 PMCID: PMC6572876 DOI: 10.1177/1176934319857720] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [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: 05/16/2019] [Accepted: 05/17/2019] [Indexed: 11/26/2022] Open
Abstract
WRKY transcription factor (TF) family regulates many functions in plant growth and development and also during biotic and abiotic stress. In this study, 101 WRKY TF gene models in indica and japonica rice were used to conduct evolutionary analysis, gene structure analysis, and motif composition. Co-expression analysis was carried out first by selecting the differentially expressing genes that showed a significant change in response to the pathogens from Rice Oligonucleotide Array Database (ROAD). About 82 genes showed responses to infection by Magnaporthe oryzae or Xanthomonas oryzae pv. oryzae. Co-expression gene network was constructed using direct neighborhood and context associated inbuilt mode in RiceNetv2 tool. Only 41 genes showed interaction with 2299 non-WRKY genes. Variations exist in the structure and evolution of WRKY genes among indica and japonica genotypes which have important implications in their differential roles including disease resistance. WRKY genes mediate a complex networking and co-express along with other WRKY and non-WRKY genes to mediate resistance against fungal and bacterial pathogens in rice.
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Affiliation(s)
- John Lilly Jimmy
- School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, India
| | - Subramanian Babu
- School of Bio Sciences and Technology, Vellore Institute of Technology, Vellore, India
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19
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Muthuramalingam P, Jeyasri R, Bharathi RKAS, Suba V, Pandian STK, Ramesh M. Global integrated omics expression analyses of abiotic stress signaling HSF transcription factor genes in Oryza sativa L.: An in silico approach. Genomics 2019; 112:908-918. [PMID: 31175978 DOI: 10.1016/j.ygeno.2019.06.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2019] [Accepted: 06/04/2019] [Indexed: 11/18/2022]
Abstract
Among the significant transcription factors (TFs), HSF proteins play pivotal roles in the regulation of hormonal signal transduction and different abiotic stress (AbS) responses. Hence considering its importance, global omics expression analysis of HSF candidates was performed in rice (OsHSF). The current study identified 25 HSF family members and physically plotted them against the rice genome. These proteins were systematically analyzed for their physicochemical features, organization and expression signatures. Further, heatmap of both spatio-temporal and global plant hormones revealed the developmental tissues and hormone specific expression profiling of these genes respectively. Comparative genome mapping between OsHSF players in interrelated C4 grass species revealed the chromosome level synteny. Signalome analysis revealed the protein - protein interactions of OsHSF. Expression profiling of key players in response to stresses exhibited the new involvement in combined AbS (CAbS) responses. Our results are significantly valuable to decipher their functional analysis of CAbS tolerant in rice.
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Affiliation(s)
- Pandiyan Muthuramalingam
- Department of Biotechnology, Science Campus, Alagappa University, Karaikudi 630003, Tamil Nadu, India
| | - Rajendran Jeyasri
- Department of Biotechnology, Science Campus, Alagappa University, Karaikudi 630003, Tamil Nadu, India
| | | | - Vellaichami Suba
- Department of Biotechnology, Science Campus, Alagappa University, Karaikudi 630003, Tamil Nadu, India
| | | | - Manikandan Ramesh
- Department of Biotechnology, Science Campus, Alagappa University, Karaikudi 630003, Tamil Nadu, India.
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20
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Walls RL, Cooper L, Elser J, Gandolfo MA, Mungall CJ, Smith B, Stevenson DW, Jaiswal P. The Plant Ontology Facilitates Comparisons of Plant Development Stages Across Species. Front Plant Sci 2019; 10:631. [PMID: 31214208 PMCID: PMC6558174 DOI: 10.3389/fpls.2019.00631] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 04/26/2019] [Indexed: 06/09/2023]
Abstract
The Plant Ontology (PO) is a community resource consisting of standardized terms, definitions, and logical relations describing plant structures and development stages, augmented by a large database of annotations from genomic and phenomic studies. This paper describes the structure of the ontology and the design principles we used in constructing PO terms for plant development stages. It also provides details of the methodology and rationale behind our revision and expansion of the PO to cover development stages for all plants, particularly the land plants (bryophytes through angiosperms). As a case study to illustrate the general approach, we examine variation in gene expression across embryo development stages in Arabidopsis and maize, demonstrating how the PO can be used to compare patterns of expression across stages and in developmentally different species. Although many genes appear to be active throughout embryo development, we identified a small set of uniquely expressed genes for each stage of embryo development and also between the two species. Evaluating the different sets of genes expressed during embryo development in Arabidopsis or maize may inform future studies of the divergent developmental pathways observed in monocotyledonous versus dicotyledonous species. The PO and its annotation database (http://www.planteome.org) make plant data for any species more discoverable and accessible through common formats, thus providing support for applications in plant pathology, image analysis, and comparative development and evolution.
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Affiliation(s)
- Ramona L. Walls
- CyVerse, Bio5 Institute, The University of Arizona, Tucson, AZ, United States
| | - Laurel Cooper
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Justin Elser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Maria Alejandra Gandolfo
- Liberty Hyde Bailey Hortorium, Plant Biology Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, United States
| | - Christopher J. Mungall
- Environmental Genomics and Systems Biology, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
| | - Barry Smith
- Department of Philosophy, University at Buffalo, Buffalo, NY, United States
| | | | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
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21
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Ngangkham U, Dash S, Parida M, Samantaray S, Nongthombam D, Yadav MK, Kumar A, Chidambaranathan P, Katara JL, Patra BC, Bose LK. The potentiality of rice microsatellite markers in assessment of cross-species transferability and genetic diversity of rice and its wild relatives. 3 Biotech 2019; 9:217. [PMID: 31114741 DOI: 10.1007/s13205-019-1757-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2018] [Accepted: 05/11/2019] [Indexed: 10/26/2022] Open
Abstract
The main aim of this study is to assess the potentiality of SSR markers for the identification of the cross-species transferability frequency in a large set of the diverse genome types of wild relative rice along with cultivated rice. Here, we used 18 different rice genotypes representing nine different genome types with 70 SSR markers to investigate the potentiality of cross-species transferability rate. The overall cross-species transferability of SSR markers across the 18 rice genotypes ranged from 38.9% (RM280 and RM447) to 100% (RM490, RM318, RM279, RM18877 and RM20033, RM19303) with an average of 76.58%. Also, cross-species transferability across chromosome ranged from 54.4% (chromosome 4) to 86.5% (chromosome 2) with an average of 74.35%. The polymorphism information content of the markers varied from 0.198 (RM263) to 0.868 (RM510) with a mean of 0.549 ± 0.153, showing high discriminatory power. The highest rate of cross-transferability was observed in O. rufipogon (97%), The highest rate of cross-species transferability was in O. rufipogon (97.00%), followed by O. glaberrima (94.20%), O. nivara (92.80%), Swarna (92.80%), O. longistaminata (91.40%), O. eichingeri (90%), O. barthii (88.50%), O. alta (82.80%), O. australiensis (77.10%), O. grandiglumis (74.20%), O. officinalis (74.20%), Zizania latifolia (70.00%), O. latifolia (68.50%), O. brachyantha (62.80%), Leersia perrieri (57.10%) and O. ridleyi (41.40%) with least in O. coarctata (28.50%). A total of 341 alleles from 70 loci were detected with the number of alleles per locus ranged from 2 to 12. Based on dendrogram analysis, the AA genome groups was separated as distinct group from the rest of the genome types. Similarly, principal coordinate analysis and structure analysis clearly separated the AA genome type from the rest of the genome types. Through the analysis of molecular variance, more variance (51%) was observed among the individual, whereas less (14%) was observed among the population. Thus, our findings may offer a valuable resource for studying the genetic diversity and relationship to facilitate the understanding of the complex mechanism of the origin and evolutionary processes of different Oryza species and wild relative rice.
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22
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Kausch AP, Nelson-Vasilchik K, Hague J, Mookkan M, Quemada H, Dellaporta S, Fragoso C, Zhang ZJ. Edit at will: Genotype independent plant transformation in the era of advanced genomics and genome editing. Plant Sci 2019; 281:186-205. [PMID: 30824051 DOI: 10.1016/j.plantsci.2019.01.006] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Revised: 12/07/2018] [Accepted: 01/10/2019] [Indexed: 05/21/2023]
Abstract
The combination of advanced genomics, genome editing and plant transformation biology presents a powerful platform for basic plant research and crop improvement. Together these advances provide the tools to identify genes as targets for direct editing as single base pair changes, deletions, insertions and site specific homologous recombination. Recent breakthrough technologies using morphogenic regulators in plant transformation creates the ability to introduce reagents specific toward their identified targets and recover stably transformed and/or edited plants which are genotype independent. These technologies enable the possibility to alter a trait in any variety, without genetic disruption which would require subsequent extensive breeding, but rather to deliver the same variety with one trait changed. Regulatory issues regarding this technology will predicate how broadly these technologies will be implemented. In addition, education will play a crucial role for positive public acceptance. Taken together these technologies comprise a platform for advanced breeding which is an imperative for future world food security.
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Affiliation(s)
- Albert P Kausch
- Department of Cell and Molecular Biology, University of Rhode Island, RI 02892, USA.
| | | | - Joel Hague
- Department of Cell and Molecular Biology, University of Rhode Island, RI 02892, USA
| | - Muruganantham Mookkan
- Plant Transformation Core Facility, Division of Plant Sciences, University of Missouri, Columbia, MO 65211, USA
| | | | - Stephen Dellaporta
- Yale University, New Haven, CT 06520, USA; Verinomics Inc., New Haven, CT 06520, USA
| | | | - Zhanyuan J Zhang
- Plant Transformation Core Facility, Division of Plant Sciences, University of Missouri, Columbia, MO 65211, USA
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23
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Naidoo S, Slippers B, Plett JM, Coles D, Oates CN. The Road to Resistance in Forest Trees. Front Plant Sci 2019; 10:273. [PMID: 31001287 PMCID: PMC6455082 DOI: 10.3389/fpls.2019.00273] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 02/19/2019] [Indexed: 05/09/2023]
Abstract
In recent years, forests have been exposed to an unprecedented rise in pests and pathogens. This, coupled with the added challenge of climate change, renders forest plantation stock vulnerable to attack and severely limits productivity. Genotypes resistant to such biotic challenges are desired in plantation forestry to reduce losses. Conventional breeding has been a main avenue to obtain resistant genotypes. More recently, genetic engineering has become a viable approach to develop resistance against pests and pathogens in forest trees. Tree genomic resources have contributed to advancements in both these approaches. Genome-wide association studies and genomic selection in tree populations have accelerated breeding tools while integration of various levels of omics information facilitates the selection of candidate genes for genetic engineering. Furthermore, tree associations with non-pathogenic endophytic and subterranean microbes play a critical role in plant health and may be engineered in forest trees to improve resistance in the future. We look at recent studies in forest trees describing defense mechanisms using such approaches and propose the way forward to developing superior genotypes with enhanced resistance against biotic stress.
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Affiliation(s)
- Sanushka Naidoo
- Division of Genetics, Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - Bernard Slippers
- Division of Genetics, Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
| | - Jonathan M. Plett
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, Australia
| | - Donovin Coles
- Hawkesbury Institute for the Environment, Western Sydney University, Richmond, NSW, Australia
| | - Caryn N. Oates
- Division of Genetics, Department of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute (FABI), University of Pretoria, Pretoria, South Africa
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Naithani S, Gupta P, Preece J, Garg P, Fraser V, Padgitt-Cobb LK, Martin M, Vining K, Jaiswal P. Involving community in genes and pathway curation. Database (Oxford) 2019; 2019:5289625. [PMID: 30649295 PMCID: PMC6334007 DOI: 10.1093/database/bay146] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/08/2018] [Accepted: 12/11/2018] [Indexed: 12/25/2022]
Abstract
Biocuration plays a crucial role in building databases and complex systems-level platforms required for processing, annotating and analyzing ‘Big Data’ in biology. However, biocuration efforts cannot keep pace with a dramatic increase in the production of omics data; this presents one of the bottlenecks in genomics. In two pathway curation jamborees, Plant Reactome curators tested strategies for introducing researchers to pathway curation tools, harnessing biologists’ expertise in curating plant pathways and developing a network of community biocurators. We summarize the strategy, workflow and outcomes of these exercises, and discuss the role of community biocuration in advancing databases and genomic resources.
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Affiliation(s)
- Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Parul Gupta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Justin Preece
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Priyanka Garg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Valerie Fraser
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA.,Molecular and Cellular Biology Graduate Program, Oregon State University, Corvallis, OR, USA
| | | | - Matthew Martin
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
| | - Kelly Vining
- Department of Horticulture, Oregon State University, Corvallis, OR, USA
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, USA
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25
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Ambrosino L, Ruggieri V, Bostan H, Miralto M, Vitulo N, Zouine M, Barone A, Bouzayen M, Frusciante L, Pezzotti M, Valle G, Chiusano ML. Multilevel comparative bioinformatics to investigate evolutionary relationships and specificities in gene annotations: an example for tomato and grapevine. BMC Bioinformatics 2018; 19:435. [PMID: 30497367 PMCID: PMC6266932 DOI: 10.1186/s12859-018-2420-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [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] [Indexed: 12/01/2022] Open
Abstract
Background “Omics” approaches may provide useful information for a deeper understanding of speciation events, diversification and function innovation. This can be achieved by investigating the molecular similarities at sequence level between species, allowing the definition of ortholog and paralog genes. However, the spreading of sequenced genome, often endowed with still preliminary annotations, requires suitable bioinformatics to be appropriately exploited in this framework. Results We presented here a multilevel comparative approach to investigate on genome evolutionary relationships and peculiarities of two fleshy fruit species of relevant agronomic interest, Solanum lycopersicum (tomato) and Vitis vinifera (grapevine). We defined 17,823 orthology relationships between tomato and grapevine reference gene annotations. The resulting orthologs are associated with the detected paralogs in each species, permitting the definition of gene networks, useful to investigate the different relationships. The reconciliation of the compared collections in terms of an updating of the functional descriptions was also exploited. All the results were made accessible in ComParaLogs, a dedicated bioinformatics platform available at http://biosrv.cab.unina.it/comparalogs/gene/search. Conclusions The aim of the work was to suggest a reliable approach to detect all similarities of gene loci between two species based on the integration of results from different levels of information, such as the gene, the transcript and the protein sequences, overcoming possible limits due to exclusive protein versus protein comparisons. This to define reliable ortholog and paralog genes, as well as species specific gene loci in the two species, overcoming limits due to the possible draft nature of preliminary gene annotations. Moreover, reconciled functional descriptions, as well as common or peculiar enzymatic classes and protein domains from tomato and grapevine, together with the definition of species-specific gene sets after the pairwise comparisons, contributed a comprehensive set of information useful to comparatively exploit the two species gene annotations and investigate on differences between species with climacteric and non-climacteric fruits. In addition, the definition of networks of ortholog genes and of associated paralogs, and the organization of web-based interfaces for the exploration of the results, defined a friendly computational bench-work in support of comparative analyses between two species. Electronic supplementary material The online version of this article (10.1186/s12859-018-2420-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Luca Ambrosino
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy.,Current address: Research Infrastructures for Marine Biological Resources, Stazione Zoologica Anton Dohrn, Naples, Italy
| | - Valentino Ruggieri
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy.,Current address: Center for Research in Agricultural Genomics, Cerdanyola, Barcelona, Spain
| | - Hamed Bostan
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy.,Current address: Plants for Human Health Institute, North Carolina State University, Kannapolis, NC, USA
| | - Marco Miralto
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy.,Current address: Research Infrastructures for Marine Biological Resources, Stazione Zoologica Anton Dohrn, Naples, Italy
| | - Nicola Vitulo
- Department of Biotechnology, University of Verona, Verona, Italy
| | - Mohamed Zouine
- Génomique et Biotechnologie des Fruits, UMR990 INRA / INP-Toulouse, Université de Toulouse, Castanet-Tolosan, France
| | - Amalia Barone
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy
| | - Mondher Bouzayen
- Génomique et Biotechnologie des Fruits, UMR990 INRA / INP-Toulouse, Université de Toulouse, Castanet-Tolosan, France
| | - Luigi Frusciante
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy
| | - Mario Pezzotti
- Department of Biotechnology, University of Verona, Verona, Italy
| | - Giorgio Valle
- CRIBI Biotechnology Centre, University of Padova, Padova, Italy
| | - Maria Luisa Chiusano
- Department of Agriculture, University of Naples "Federico II,", Portici, Naples, Italy. .,Research Infrastructures for Marine Biological Resources, Stazione Zoologica Anton Dohrn, Naples, Italy.
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26
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Oney-Birol S, Fitz-Gibbon S, Chen JM, Gugger PF, Sork VL. Assessment of shared alleles in drought-associated candidate genes among southern California white oak species (Quercus sect. Quercus). BMC Genet 2018; 19:88. [PMID: 30285631 PMCID: PMC6167808 DOI: 10.1186/s12863-018-0677-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [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: 03/29/2018] [Accepted: 09/19/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Hybridization and introgression are common phenomena among oak species. These processes can be beneficial by introducing favorable genetic variants across species (adaptive introgression). Given that drought is an important stress, impacting physiological and morphological variation and limiting distributions, our goal was to identify drought-related genes that might exhibit patterns of introgression influenced by natural selection. Using RNAseq, we sequenced whole transcriptomes of 24 individuals from three oaks in southern California: (Quercus engelmannii, Quercus berberidifolia, Quercus cornelius-mulleri) and identified genetic variants to estimate admixture rates of all variants and those in drought genes. RESULTS We found 398,042 variants across all loci and 4352 variants in 139 drought candidate genes. STRUCTURE analysis of all variants revealed the majority of our samples were assignable to a single species, but with several highly admixed individuals. When using drought-associated variants, the same individuals exhibited less admixture and their allele frequencies were more polarized between Engelmann and scrub oaks than when using the total gene set. These findings are consistent with the hypothesis that selection may act differently on functional genes, such as drought-associated genes, and point to candidate genes that are suggestive of divergent selection among species maintaining adaptive differences. For example, the drought genes that showed the strongest bias against engelmannii-fixed oak variants in scrub oaks were related to sugar transporter, coumarate-coA ligases, glutathione S-conjugation, and stress response. CONCLUSION This pilot study illustrates that whole transcriptomes of individuals will provide useful data for identifying functional genes that contribute to adaptive divergence among hybridizing species.
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Affiliation(s)
- Signem Oney-Birol
- Department of Molecular Biology and Genetics, Faculty of Arts and Sciences, Burdur Mehmet Akif Ersoy University, 15030, Burdur, Turkey.
| | - Sorel Fitz-Gibbon
- Institute of Genomics and Proteomics, University of California, Los Angeles, CA, 90095, USA
| | - Jin-Ming Chen
- Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, 430074, Hubei, China
| | - Paul F Gugger
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095-7239, USA.,Appalachian Laboratory, University of Maryland Center for Environmental Science, Frostburg, MD, 21532, USA
| | - Victoria L Sork
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095-7239, USA.,Institute of the Environment and Sustainability, University of California, Los Angeles, CA, 90095-1496, USA
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27
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Chen S, Saito N, Encabo JR, Yamada K, Choi IR, Kishima Y. Ancient Endogenous Pararetroviruses in Oryza Genomes Provide Insights into the Heterogeneity of Viral Gene Macroevolution. Genome Biol Evol 2018; 10:2686-2696. [PMID: 30239708 PMCID: PMC6179347 DOI: 10.1093/gbe/evy207] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/16/2018] [Indexed: 12/13/2022] Open
Abstract
Endogenous viral sequences in eukaryotic genomes, such as those derived from plant pararetroviruses (PRVs), can serve as genomic fossils to study viral macroevolution. Many aspects of viral evolutionary rates are heterogeneous, including substitution rate differences between genes. However, the evolutionary dynamics of this viral gene rate heterogeneity (GRH) have been rarely examined. Characterizing such GRH may help to elucidate viral adaptive evolution. In this study, based on robust phylogenetic analysis, we determined an ancient endogenous PRV group in Oryza genomes in the range of being 2.41-15.00 Myr old. We subsequently used this ancient endogenous PRV group and three younger groups to estimate the GRH of PRVs. Long-term substitution rates for the most conserved gene and a divergent gene were 2.69 × 10-8 to 8.07 × 10-8 and 4.72 × 10-8 to 1.42 × 10-7 substitutions/site/year, respectively. On the basis of a direct comparison, a long-term GRH of 1.83-fold was identified between these two genes, which is unexpectedly low and lower than the short-term GRH (>3.40-fold) of PRVs calculated using published data. The lower long-term GRH of PRVs was due to the slightly faster rate decay of divergent genes than of conserved genes during evolution. To the best of our knowledge, we quantified for the first time the long-term GRH of viral genes using paleovirological analyses, and proposed that the GRH of PRVs might be heterogeneous on time scales (time-dependent GRH). Our findings provide special insights into viral gene macroevolution and should encourage a more detailed examination of the viral GRH.
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Affiliation(s)
- Sunlu Chen
- Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, China
| | - Nozomi Saito
- Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
| | - Jaymee R Encabo
- Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
- Rice Breeding Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
- Microbiology Division, Institute of Biological Sciences, University of the Philippines Los Baños, Los Baños, Laguna, Philippines
| | - Kanae Yamada
- Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
| | - Il-Ryong Choi
- Rice Breeding Platform, International Rice Research Institute, Los Baños, Laguna, Philippines
| | - Yuji Kishima
- Laboratory of Plant Breeding, Research Faculty of Agriculture, Hokkaido University, Sapporo, Japan
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28
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Mohamad-Matrol AA, Chang SW, Abu A. Plant data visualisation using network graphs. PeerJ 2018; 6:e5579. [PMID: 30186704 PMCID: PMC6120445 DOI: 10.7717/peerj.5579] [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: 03/30/2018] [Accepted: 08/12/2018] [Indexed: 11/20/2022] Open
Abstract
Background The amount of plant data such as taxonomical classification, morphological characteristics, ecological attributes and geological distribution in textual and image forms has increased rapidly due to emerging research and technologies. Therefore, it is crucial for experts as well as the public to discern meaningful relationships from this vast amount of data using appropriate methods. The data are often presented in lengthy texts and tables, which make gaining new insights difficult. The study proposes a visual-based representation to display data to users in a meaningful way. This method emphasises the relationships between different data sets. Method This study involves four main steps which translate text-based results from Extensible Markup Language (XML) serialisation format into graphs. The four steps include: (1) conversion of ontological dataset as graph model data; (2) query from graph model data; (3) transformation of text-based results in XML serialisation format into a graphical form; and (4) display of results to the user via a graphical user interface (GUI). Ontological data for plants and samples of trees and shrubs were used as the dataset to demonstrate how plant-based data could be integrated into the proposed data visualisation. Results A visualisation system named plant visualisation system was developed. This system provides a GUI that enables users to perform the query process, as well as a graphical viewer to display the results of the query in the form of a network graph. The efficiency of the developed visualisation system was measured by performing two types of user evaluations: a usability heuristics evaluation, and a query and visualisation evaluation. Discussion The relationships between the data were visualised, enabling the users to easily infer the knowledge and correlations between data. The results from the user evaluation show that the proposed visualisation system is suitable for both expert and novice users, with or without computer skills. This technique demonstrates the practicability of using a computer assisted-tool by providing cognitive analysis for understanding relationships between data. Therefore, the results benefit not only botanists, but also novice users, especially those that are interested to know more about plants.
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Affiliation(s)
| | - Siow-Wee Chang
- Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
| | - Arpah Abu
- Institute of Biological Sciences, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia.,Centre of Research for Computational Sciences and Informatics for Biology, Bioindustry, Environment, Agriculture and Healthcare, University of Malaya, Kuala Lumpur, Malaysia
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29
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Chowrasia S, Panda AK, Rawal HC, Kaur H, Mondal TK. Identification of jumonjiC domain containing gene family among the Oryza species and their expression analysis in FL478, a salt tolerant rice genotype. Plant Physiol Biochem 2018; 130:43-53. [PMID: 29960182 DOI: 10.1016/j.plaphy.2018.06.031] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Revised: 06/20/2018] [Accepted: 06/21/2018] [Indexed: 05/26/2023]
Abstract
The jumonji (JMJ)-C domain containing proteins belong to histone demethylases family with the ability to demethylate the tri-methylated histone residues. They act as chromatin regulators to regulate many physiological functions in plants. The present study deals with the characterization of JMJ-C gene family members in wild as well as cultivated rice species and their expression analysis in salt tolerant rice genotype, FL478. The genome wide study identified 151 members belonging to JMJ-C gene family in 11 different Oryza species. We also studied their structure, genomic location, gene duplication events, phylogenetic relationship, in silico expression analysis and identified cis elements in their promoters. We also found a few JMJ-C gene family members in rice which underwent duplication before the whole genome duplication event of the rice. The qRT-PCR based expression profiling revealed that out of the total 15 rice JMJ-C members, two were highly expressed in the flag leaf stage of FL478 under salt treatment. These two candidate JMJ-C members were also found to render salinity tolerance when over-expressed in yeast cells. Thus, the present study helps in further structural as well as functional characterization of JMJ-C genes under salinity stress in Oryza species.
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Affiliation(s)
- Soni Chowrasia
- ICAR-National Research Centre on Plant Biotechnology, Lal-Bahadur Shastri Centre, IARI, Pusa, New Delhi, 110012, India
| | - Alok Kumar Panda
- ICAR-National Research Centre on Plant Biotechnology, Lal-Bahadur Shastri Centre, IARI, Pusa, New Delhi, 110012, India
| | - Hukam C Rawal
- ICAR-National Research Centre on Plant Biotechnology, Lal-Bahadur Shastri Centre, IARI, Pusa, New Delhi, 110012, India
| | - Harmeet Kaur
- ICAR-National Research Centre on Plant Biotechnology, Lal-Bahadur Shastri Centre, IARI, Pusa, New Delhi, 110012, India
| | - Tapan Kumar Mondal
- ICAR-National Research Centre on Plant Biotechnology, Lal-Bahadur Shastri Centre, IARI, Pusa, New Delhi, 110012, India.
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30
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Alaux M, Rogers J, Letellier T, Flores R, Alfama F, Pommier C, Mohellibi N, Durand S, Kimmel E, Michotey C, Guerche C, Loaec M, Lainé M, Steinbach D, Choulet F, Rimbert H, Leroy P, Guilhot N, Salse J, Feuillet C, Paux E, Eversole K, Adam-Blondon AF, Quesneville H. Linking the International Wheat Genome Sequencing Consortium bread wheat reference genome sequence to wheat genetic and phenomic data. Genome Biol 2018; 19:111. [PMID: 30115101 PMCID: PMC6097284 DOI: 10.1186/s13059-018-1491-4] [Citation(s) in RCA: 134] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Accepted: 07/23/2018] [Indexed: 01/24/2023] Open
Abstract
The Wheat@URGI portal has been developed to provide the international community of researchers and breeders with access to the bread wheat reference genome sequence produced by the International Wheat Genome Sequencing Consortium. Genome browsers, BLAST, and InterMine tools have been established for in-depth exploration of the genome sequence together with additional linked datasets including physical maps, sequence variations, gene expression, and genetic and phenomic data from other international collaborative projects already stored in the GnpIS information system. The portal provides enhanced search and browser features that will facilitate the deployment of the latest genomics resources in wheat improvement.
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Affiliation(s)
- Michael Alaux
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France.
| | - Jane Rogers
- International Wheat Genome Sequencing Consortium (IWGSC), 18 High Street, Little Eversden, Cambridge, CB23 1HE, UK
| | | | - Raphaël Flores
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | | | - Cyril Pommier
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Nacer Mohellibi
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Sophie Durand
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Erik Kimmel
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Célia Michotey
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Claire Guerche
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Mikaël Loaec
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Mathilde Lainé
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
| | - Delphine Steinbach
- URGI, INRA, Université Paris-Saclay, 78026, Versailles, France
- Present address: GQE-Le Moulon UMR 320, INRA, Université Paris-Sud, Université Paris-Saclay, CNRS, AgroParisTech, Ferme du Moulon, 91190, Gif-sur-Yvette, France
| | - Frédéric Choulet
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Hélène Rimbert
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Philippe Leroy
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Nicolas Guilhot
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Jérôme Salse
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Catherine Feuillet
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
- Present address: Inari Agriculture, 200 Sydney Street, Cambridge, MA, 02139, USA
| | - Etienne Paux
- GDEC, INRA, Université Clermont Auvergne, 63000, Clermont-Ferrand, France
| | - Kellye Eversole
- International Wheat Genome Sequencing Consortium (IWGSC), 5207 Wyoming Road, Bethesda, Maryland, 20816, USA
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Qi H, Jiang Z, Zhang K, Yang S, He F, Zhang Z. PlaD: A Transcriptomics Database for Plant Defense Responses to Pathogens, Providing New Insights into Plant Immune System. Genomics Proteomics Bioinformatics 2018; 16:283-293. [PMID: 30266409 PMCID: PMC6205082 DOI: 10.1016/j.gpb.2018.08.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2018] [Revised: 07/02/2018] [Accepted: 08/13/2018] [Indexed: 01/01/2023]
Abstract
High-throughput transcriptomics technologies have been widely used to study plant transcriptional reprogramming during the process of plant defense responses, and a large quantity of gene expression data have been accumulated in public repositories. However, utilization of these data is often hampered by the lack of standard metadata annotation. In this study, we curated 2444 public pathogenesis-related gene expression samples from the model plant Arabidopsis and three major crops (maize, rice, and wheat). We organized the data into a user-friendly database termed as PlaD. Currently, PlaD contains three key features. First, it provides large-scale curated data related to plant defense responses, including gene expression and gene functional annotation data. Second, it provides the visualization of condition-specific expression profiles. Third, it allows users to search co-regulated genes under the infections of various pathogens. Using PlaD, we conducted a large-scale transcriptome analysis to explore the global landscape of gene expression in the curated data. We found that only a small fraction of genes were differentially expressed under multiple conditions, which might be explained by their tendency of having more network connections and shorter network distances in gene networks. Collectively, we hope that PlaD can serve as an important and comprehensive knowledgebase to the community of plant sciences, providing insightful clues to better understand the molecular mechanisms underlying plant immune responses. PlaD is freely available at http://systbio.cau.edu.cn/plad/index.php or http://zzdlab.com/plad/index.php.
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Affiliation(s)
- Huan Qi
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Zhenhong Jiang
- Jiangxi Key Laboratory of Molecular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, China
| | - Kang Zhang
- Department of Plant Pathology and the Ministry of Agriculture Key Laboratory for Plant Pathology, China Agricultural University, Beijing 100193, China
| | - Shiping Yang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China
| | - Fei He
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China; Biology Department, Brookhaven National Lab, Upton, NY 11967, USA.
| | - Ziding Zhang
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing 100193, China.
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Sun S, Zhou Y, Chen J, Shi J, Zhao H, Zhao H, Song W, Zhang M, Cui Y, Dong X, Liu H, Ma X, Jiao Y, Wang B, Wei X, Stein JC, Glaubitz JC, Lu F, Yu G, Liang C, Fengler K, Li B, Rafalski A, Schnable PS, Ware DH, Buckler ES, Lai J. Extensive intraspecific gene order and gene structural variations between Mo17 and other maize genomes. Nat Genet 2018; 50:1289-95. [PMID: 30061735 DOI: 10.1038/s41588-018-0182-0] [Citation(s) in RCA: 224] [Impact Index Per Article: 37.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2017] [Accepted: 06/05/2018] [Indexed: 12/24/2022]
Abstract
Maize is an important crop with a high level of genome diversity and heterosis. The genome sequence of a typical female line, B73, was previously released. Here, we report a de novo genome assembly of a corresponding male representative line, Mo17. More than 96.4% of the 2,183 Mb assembled genome can be accounted for by 362 scaffolds in ten pseudochromosomes with 38,620 annotated protein-coding genes. Comparative analysis revealed large gene-order and gene structural variations: approximately 10% of the annotated genes were mutually nonsyntenic, and more than 20% of the predicted genes had either large-effect mutations or large structural variations, which might cause considerable protein divergence between the two inbred lines. Our study provides a high-quality reference-genome sequence of an important maize germplasm, and the intraspecific gene order and gene structural variations identified should have implications for heterosis and genome evolution.
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Springer NM, Anderson SN, Andorf CM, Ahern KR, Bai F, Barad O, Barbazuk WB, Bass HW, Baruch K, Ben-Zvi G, Buckler ES, Bukowski R, Campbell MS, Cannon EKS, Chomet P, Dawe RK, Davenport R, Dooner HK, Du LH, Du C, Easterling KA, Gault C, Guan JC, Hunter CT, Jander G, Jiao Y, Koch KE, Kol G, Köllner TG, Kudo T, Li Q, Lu F, Mayfield-Jones D, Mei W, McCarty DR, Noshay JM, Portwood JL 2nd, Ronen G, Settles AM, Shem-Tov D, Shi J, Soifer I, Stein JC, Stitzer MC, Suzuki M, Vera DL, Vollbrecht E, Vrebalov JT, Ware D, Wei S, Wimalanathan K, Woodhouse MR, Xiong W, Brutnell TP. The maize W22 genome provides a foundation for functional genomics and transposon biology. Nat Genet 2018; 50:1282-8. [PMID: 30061736 DOI: 10.1038/s41588-018-0158-0] [Citation(s) in RCA: 114] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 05/17/2018] [Indexed: 11/08/2022]
Abstract
The maize W22 inbred has served as a platform for maize genetics since the mid twentieth century. To streamline maize genome analyses, we have sequenced and de novo assembled a W22 reference genome using short-read sequencing technologies. We show that significant structural heterogeneity exists in comparison to the B73 reference genome at multiple scales, from transposon composition and copy number variation to single-nucleotide polymorphisms. The generation of this reference genome enables accurate placement of thousands of Mutator (Mu) and Dissociation (Ds) transposable element insertions for reverse and forward genetics studies. Annotation of the genome has been achieved using RNA-seq analysis, differential nuclease sensitivity profiling and bisulfite sequencing to map open reading frames, open chromatin sites and DNA methylation profiles, respectively. Collectively, the resources developed here integrate W22 as a community reference genome for functional genomics and provide a foundation for the maize pan-genome.
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Buti M, Pasquariello M, Ronga D, Milc JA, Pecchioni N, Ho VT, Pucciariello C, Perata P, Francia E. Transcriptome profiling of short-term response to chilling stress in tolerant and sensitive Oryza sativa ssp. Japonica seedlings. Funct Integr Genomics 2018; 18:627-644. [PMID: 29876699 DOI: 10.1007/s10142-018-0615-y] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 03/07/2018] [Accepted: 05/23/2018] [Indexed: 12/26/2022]
Abstract
Low temperature is a major factor limiting rice growth and yield, and seedling is one of the developmental stages at which sensitivity to chilling stress is higher. Tolerance to chilling is a complex quantitative trait, so one of the most effective approaches to identify genes and pathways involved is to compare the stress-induced expression changes between tolerant and sensitive genotypes. Phenotypic responses to chilling of 13 Japonica cultivars were evaluated, and Thaibonnet and Volano were selected as sensitive and tolerant genotypes, respectively. To thoroughly profile the short-term response of the two cultivars to chilling, RNA-Seq was performed on Thaibonnet and Volano seedlings after 0 (not stressed), 2, and 10 h at 10 °C. Differential expression analysis revealed that the ICE-DREB1/CBF pathway plays a primary role in chilling tolerance, mainly due to some important transcription factors involved (some of which had never been reported before). Moreover, the expression trends of some genes that were radically different between Thaibonnet and Volano (i.e., calcium-dependent protein kinases OsCDPK21 and OsCDPK23, cytochrome P450 monooxygenase CYP76M8, etc.) suggest their involvement in low temperature tolerance too. Density of differentially expressed genes along rice genome was determined and linked to the position of known QTLs: remarkable co-locations were reported, delivering an overview of genomic regions determinant for low temperature response at seedling stage. Our study contributes to a better understanding of the molecular mechanisms underlying rice response to chilling and provides a solid background for development of low temperature-tolerant germplasm.
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Affiliation(s)
- Matteo Buti
- BIOGEST-SITEIA, University of Modena and Reggio Emilia, Via Amendola, 2 - Pad. Besta, 42122, Reggio Emilia, Italy.
| | | | - Domenico Ronga
- BIOGEST-SITEIA, University of Modena and Reggio Emilia, Via Amendola, 2 - Pad. Besta, 42122, Reggio Emilia, Italy
| | - Justyna Anna Milc
- BIOGEST-SITEIA, University of Modena and Reggio Emilia, Via Amendola, 2 - Pad. Besta, 42122, Reggio Emilia, Italy
- Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy
| | - Nicola Pecchioni
- Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy
- Cereal Research Centre, Council for Agricultural Research and Economics, Foggia, Italy
| | - Viet The Ho
- PlantLab, Scuola Superiore Sant'Anna, Pisa, Italy
- Ho Chi Minh City University of Food Industry, Ho Chi Minh, Vietnam
| | | | | | - Enrico Francia
- BIOGEST-SITEIA, University of Modena and Reggio Emilia, Via Amendola, 2 - Pad. Besta, 42122, Reggio Emilia, Italy
- Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy
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Gazquez A, Vilas JM, Colman Lerner JE, Maiale SJ, Calzadilla PI, Menéndez AB, Rodríguez AA. Rice tolerance to suboptimal low temperatures relies on the maintenance of the photosynthetic capacity. Plant Physiol Biochem 2018; 127:537-552. [PMID: 29723825 DOI: 10.1016/j.plaphy.2018.04.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Revised: 04/12/2018] [Accepted: 04/25/2018] [Indexed: 06/08/2023]
Abstract
The purpose of this research was to identify differences between two contrasting rice cultivars in their response to suboptimal low temperatures stress. A transcriptomic analysis of the seedlings was performed and results were complemented with biochemical and physiological analyses. The microarray analysis showed downregulation of many genes related with PSII and particularly with the oxygen evolving complex in the sensitive cultivar IR50. Complementary studies indicated that the PSII performance, the degree of oxygen evolving complex coupling with the PSII core and net photosynthetic rate diminished in this cultivar in response to the stress. However, the tolerant cultivar Koshihikari was able to maintain its energy equilibrium by sustaining the photosynthetic capacity. The increase of oleic acid in Koshihikari could be related with membrane remodelling of the chloroplasts and hence contribute to tolerance. Overall, these results work as a ground for future analyses that look forward to characterize possible mechanisms to tolerate this stress.
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Affiliation(s)
- Ayelén Gazquez
- Laboratorio de Fisiología de Estrés Abiótico en Plantas, Unidad de Biotecnología 1, IIB-INTECH, CONICET, UNSAM, Chascomús, Argentina
| | - Juan Manuel Vilas
- Laboratorio de Fisiología de Estrés Abiótico en Plantas, Unidad de Biotecnología 1, IIB-INTECH, CONICET, UNSAM, Chascomús, Argentina
| | | | - Santiago Javier Maiale
- Laboratorio de Fisiología de Estrés Abiótico en Plantas, Unidad de Biotecnología 1, IIB-INTECH, CONICET, UNSAM, Chascomús, Argentina
| | - Pablo Ignacio Calzadilla
- Laboratorio de Fisiología de Estrés Abiótico en Plantas, Unidad de Biotecnología 1, IIB-INTECH, CONICET, UNSAM, Chascomús, Argentina
| | - Ana Bernardina Menéndez
- Departamento de Biodiversidad y Biología Experimental, FCEyN - UBA, INMIBO-CONICET, Buenos Aires, Argentina
| | - Andrés Alberto Rodríguez
- Laboratorio de Fisiología de Estrés Abiótico en Plantas, Unidad de Biotecnología 1, IIB-INTECH, CONICET, UNSAM, Chascomús, Argentina.
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Orozco-Arias S, Liu J, Tabares-Soto R, Ceballos D, Silva Domingues D, Garavito A, Ming R, Guyot R. Inpactor, Integrated and Parallel Analyzer and Classifier of LTR Retrotransposons and Its Application for Pineapple LTR Retrotransposons Diversity and Dynamics. Biology (Basel) 2018; 7:E32. [PMID: 29799487 DOI: 10.3390/biology7020032] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Revised: 05/16/2018] [Accepted: 05/22/2018] [Indexed: 12/22/2022]
Abstract
One particular class of Transposable Elements (TEs), called Long Terminal Repeats (LTRs), retrotransposons, comprises the most abundant mobile elements in plant genomes. Their copy number can vary from several hundreds to up to a few million copies per genome, deeply affecting genome organization and function. The detailed classification of LTR retrotransposons is an essential step to precisely understand their effect at the genome level, but remains challenging in large-sized genomes, requiring the use of optimized bioinformatics tools that can take advantage of supercomputers. Here, we propose a new tool: Inpactor, a parallel and scalable pipeline designed to classify LTR retrotransposons, to identify autonomous and non-autonomous elements, to perform RT-based phylogenetic trees and to analyze their insertion times using High Performance Computing (HPC) techniques. Inpactor was tested on the classification and annotation of LTR retrotransposons in pineapple, a recently-sequenced genome. The pineapple genome assembly comprises 44% of transposable elements, of which 23% were classified as LTR retrotransposons. Exceptionally, 16.4% of the pineapple genome assembly corresponded to only one lineage of the Gypsy superfamily: Del, suggesting that this particular lineage has undergone a significant increase in its copy numbers. As demonstrated for the pineapple genome, Inpactor provides comprehensive data of LTR retrotransposons’ classification and dynamics, allowing a fine understanding of their contribution to genome structure and evolution. Inpactor is available at https://github.com/simonorozcoarias/Inpactor.
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Liao P, Li S, Cui X, Zheng Y. A comprehensive review of web-based resources of non-coding RNAs for plant science research. Int J Biol Sci 2018; 14:819-832. [PMID: 29989090 PMCID: PMC6036741 DOI: 10.7150/ijbs.24593] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2017] [Accepted: 03/14/2018] [Indexed: 01/06/2023] Open
Abstract
Non-coding RNAs (ncRNAs) are transcribed from genome but not translated into proteins. Many ncRNAs are key regulators of plants growth and development, metabolism and stress tolerance. In order to make the web-based ncRNA resources for plant science research be more easily accessible and understandable, we made a comprehensive review for 83 web-based resources of three types, including genome databases containing ncRNA data, microRNA (miRNA) databases and long non-coding RNA (lncRNA) databases. To facilitate effective usage of these resources, we also suggested some preferred resources of miRNAs and lncRNAs for performing meaningful analysis.
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Affiliation(s)
- Peiran Liao
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, 650500,China
| | - Shipeng Li
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, 650500,China
| | - Xiuming Cui
- Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan, 650500,China
- Yunnan key laboratory of Panax notoginseng, Kunming, Yunnan, 650500, China
| | - Yun Zheng
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan, 650500, China
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Lee YK, Rhee JY, Lee SH, Chung GC, Park SJ, Segami S, Maeshima M, Choi G. Functionally redundant LNG3 and LNG4 genes regulate turgor-driven polar cell elongation through activation of XTH17 and XTH24. Plant Mol Biol 2018; 97:23-36. [PMID: 29616436 DOI: 10.1007/s11103-018-0722-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2017] [Accepted: 03/25/2018] [Indexed: 05/03/2023]
Abstract
In this work, we genetically characterized the function of Arabidopsis thaliana, LONGIFOLIA (LNG1), LNG2, LNG3, LNG4, their contribution to regulate vegetative architecture in plant. We used molecular and biophysical approaches to elucidate a gene function that regulates vegetative architecture, as revealed by the leaf phenotype and later effects on flowering patterns in Arabidopsis loss-of-function mutants. As a result, LNG genes play an important role in polar cell elongation by turgor pressure controlling the activation of XTH17 and XTH24. Plant vegetative architecture is related to important traits that later influence the floral architecture involved in seed production. Leaf morphology is the primary key trait to compose plant vegetative architecture. However, molecular mechanism on leaf shape determination is not fully understood even in the model plant A. thaliana. We previously showed that LONGIFOLIA (LNG1) and LONGIFOLIA2 (LNG2) genes regulate leaf morphology by promoting longitudinal cell elongation in Arabidopsis. In this study, we further characterized two homologs of LNG1, LNG3, and LNG4, using genetic, biophysical, and molecular approaches. Single loss-of-function mutants, lng3 and lng4, do not show any phenotypic difference, but mutants of lng quadruple (lngq), and lng1/2/3 and lng1/2/4 triples, display reduced leaf length, compared to wild type. Using the paradermal analysis, we conclude that the reduced leaf size of lngq is due to decreased cell elongation in the direction of longitudinal leaf growth, and not decreased cell proliferation. This data indicate that LNG1/2/3/4 are functionally redundant, and are involved in polar cell elongation in Arabidopsis leaf. Using a biophysical approach, we show that the LNGs contribute to maintain high turgor pressure, thus regulating turgor pressure-dependent polar cell elongation. In addition, gene expression analysis showed that LNGs positively regulate the expression of the cell wall modifying enzyme encoded by a multi-gene family, xyloglucan endotransglucosylase/hydrolase (XTH). Taking all of these together, we propose that LNG related genes play an important role in polar cell elongation by changing turgor pressure and controlling the activation of XTH17 and XTH24.
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Affiliation(s)
- Young Koung Lee
- Department of Biological Sciences, KAIST, Daejeon, 34141, South Korea.
- Division of Biological Sciences and Institute for Basic Science/Division of Biological Sciences and Research Institute for Glycoscience, Wonkwang University, Iksan, 54538, South Korea.
| | - Ji Ye Rhee
- Department of Plant Biotechnology, Agricultural Plant Stress Research Center, College of Agriculture and Life Sciences, Chonnam National University, Gwangju, 61186, South Korea
| | - Seong Hee Lee
- Department of Renewable Resources, University of Alberta, Edmonton, AB, T6G 2E3, Canada
| | - Gap Chae Chung
- Department of Plant Biotechnology, Agricultural Plant Stress Research Center, College of Agriculture and Life Sciences, Chonnam National University, Gwangju, 61186, South Korea
| | - Soon Ju Park
- Division of Biological Sciences and Institute for Basic Science/Division of Biological Sciences and Research Institute for Glycoscience, Wonkwang University, Iksan, 54538, South Korea
| | - Shoji Segami
- Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan
| | - Masayohi Maeshima
- Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya, 464-8601, Japan
| | - Giltsu Choi
- Department of Biological Sciences, KAIST, Daejeon, 34141, South Korea
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Bolger ME, Arsova B, Usadel B. Plant genome and transcriptome annotations: from misconceptions to simple solutions. Brief Bioinform 2018; 19:437-449. [PMID: 28062412 PMCID: PMC5952960 DOI: 10.1093/bib/bbw135] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Revised: 11/29/2016] [Indexed: 12/14/2022] Open
Abstract
Next-generation sequencing has triggered an explosion of available genomic and transcriptomic resources in the plant sciences. Although genome and transcriptome sequencing has become orders of magnitudes cheaper and more efficient, often the functional annotation process is lagging behind. This might be hampered by the lack of a comprehensive enumeration of simple-to-use tools available to the plant researcher. In this comprehensive review, we present (i) typical ontologies to be used in the plant sciences, (ii) useful databases and resources used for functional annotation, (iii) what to expect from an annotated plant genome, (iv) an automated annotation pipeline and (v) a recipe and reference chart outlining typical steps used to annotate plant genomes/transcriptomes using publicly available resources.
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Affiliation(s)
- Marie E Bolger
- Forschungszentrum Jülich, Wilhelm Johnen Str, Jülich, Germany
| | - Borjana Arsova
- Forschungszentrum Jülich, Wilhelm Johnen Str, Jülich, Germany
- FRS-FNRS Chargé de Recherches, Functional Genomics and Plant Molecular Imaging Center for Protein Engineering (CIP), Dpt of Life Sciences, University of Liège, Quartier de la Vallée, 1, Chemin de la Vallée, 4 - Bât B22, 4000 LIEGE, Belgium
| | - Björn Usadel
- Forschungszentrum Jülich, Wilhelm Johnen Str, Jülich, Germany
- RWTH Aachen University, Institute for Biology I Botany, BioSC, Worringer Weg 3, Aachen, Germany
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Sørensen JL, Benfield AH, Wollenberg RD, Westphal K, Wimmer R, Nielsen MR, Nielsen KF, Carere J, Covarelli L, Beccari G, Powell J, Yamashino T, Kogler H, Sondergaard TE, Gardiner DM. The cereal pathogen Fusarium pseudograminearum produces a new class of active cytokinins during infection. Mol Plant Pathol 2018; 19:1140-1154. [PMID: 28802024 PMCID: PMC6638160 DOI: 10.1111/mpp.12593] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2017] [Revised: 08/08/2017] [Accepted: 08/10/2017] [Indexed: 05/02/2023]
Abstract
The fungal pathogen Fusarium pseudograminearum causes important diseases of wheat and barley. During a survey of secondary metabolites produced by this fungus, a novel class of cytokinins, herein termed Fusarium cytokinins, was discovered. Cytokinins are known for their growth-promoting and anti-senescence activities, and the production of a cytokinin mimic by what was once considered as a necrotrophic pathogen that promotes cell death and senescence challenges the simple view that this pathogen invades its hosts by employing a barrage of lytic enzymes and toxins. Through genome mining, a gene cluster in the F. pseudograminearum genome for the production of Fusarium cytokinins was identified and the biosynthetic pathway was established using gene knockouts. The Fusarium cytokinins could activate plant cytokinin signalling, demonstrating their genuine hormone mimicry. In planta analysis of the transcriptional response to one Fusarium cytokinin suggests extensive reprogramming of the host environment by these molecules, possibly through crosstalk with defence hormone signalling pathways.
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Affiliation(s)
- Jens Laurids Sørensen
- Department of Chemistry and BioscienceAalborg UniversityAalborg9220, Denmark
- Department of Chemistry and BioscienceAalborg UniversityEsbjerg6700, Denmark
| | - Aurelie H. Benfield
- Queensland Bioscience PrecinctCommonwealth Scientific and Industrial Research Organization (CSIRO) Agriculture and FoodBrisbane4067, Australia
| | | | - Klaus Westphal
- Department of Chemistry and BioscienceAalborg UniversityAalborg9220, Denmark
| | - Reinhard Wimmer
- Department of Chemistry and BioscienceAalborg UniversityAalborg9220, Denmark
| | - Mikkel Rank Nielsen
- Department of Chemistry and BioscienceAalborg UniversityEsbjerg6700, Denmark
| | - Kristian Fog Nielsen
- Department of Biotechnology and BiomedicineTechnical University of DenmarkKgs. Lyngby2800, Denmark
| | - Jason Carere
- Queensland Bioscience PrecinctCommonwealth Scientific and Industrial Research Organization (CSIRO) Agriculture and FoodBrisbane4067, Australia
| | - Lorenzo Covarelli
- Department of Agricultural, Food and Environmental SciencesUniversity of PerugiaPerugia06121, Italy
| | - Giovanni Beccari
- Department of Agricultural, Food and Environmental SciencesUniversity of PerugiaPerugia06121, Italy
| | - Jonathan Powell
- Queensland Bioscience PrecinctCommonwealth Scientific and Industrial Research Organization (CSIRO) Agriculture and FoodBrisbane4067, Australia
| | - Takafumi Yamashino
- Laboratory of Molecular Microbiology, School of AgricultureNagoya University, Furocho, Chikusa‐kuNagoya464‐8601, Japan
| | - Herbert Kogler
- Institute for Biological Interfaces 4, Magnetic Resonance, Karlsruhe Institute of TechnologyKarlsruhe76021, Germany
| | | | - Donald Max Gardiner
- Queensland Bioscience PrecinctCommonwealth Scientific and Industrial Research Organization (CSIRO) Agriculture and FoodBrisbane4067, Australia
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Wang B, Regulski M, Tseng E, Olson A, Goodwin S, McCombie WR, Ware D. A comparative transcriptional landscape of maize and sorghum obtained by single-molecule sequencing. Genome Res 2018; 28:921-932. [PMID: 29712755 PMCID: PMC5991521 DOI: 10.1101/gr.227462.117] [Citation(s) in RCA: 69] [Impact Index Per Article: 11.5] [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] [Received: 07/11/2017] [Accepted: 04/12/2018] [Indexed: 12/15/2022]
Abstract
Maize and sorghum are both important crops with similar overall plant architectures, but they have key differences, especially in regard to their inflorescences. To better understand these two organisms at the molecular level, we compared expression profiles of both protein-coding and noncoding transcripts in 11 matched tissues using single-molecule, long-read, deep RNA sequencing. This comparative analysis revealed large numbers of novel isoforms in both species. Evolutionarily young genes were likely to be generated in reproductive tissues and usually had fewer isoforms than old genes. We also observed similarities and differences in alternative splicing patterns and activities, both among tissues and between species. The maize subgenomes exhibited no bias in isoform generation; however, genes in the B genome were more highly expressed in pollen tissue, whereas genes in the A genome were more highly expressed in endosperm. We also identified a number of splicing events conserved between maize and sorghum. In addition, we generated comprehensive and high-resolution maps of poly(A) sites, revealing similarities and differences in mRNA cleavage between the two species. Overall, our results reveal considerable splicing and expression diversity between sorghum and maize, well beyond what was reported in previous studies, likely reflecting the differences in architecture between these two species.
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Affiliation(s)
- Bo Wang
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Michael Regulski
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | | | - Andrew Olson
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | - Sara Goodwin
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA
| | | | - Doreen Ware
- Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA.,USDA ARS NEA Robert W. Holley Center for Agriculture and Health, Cornell University, Ithaca, New York 14853, USA
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42
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Wimalanathan K, Friedberg I, Andorf CM, Lawrence‐Dill CJ. Maize GO Annotation-Methods, Evaluation, and Review (maize-GAMER). Plant Direct 2018; 2:e00052. [PMID: 31245718 PMCID: PMC6508527 DOI: 10.1002/pld3.52] [Citation(s) in RCA: 61] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 01/25/2018] [Accepted: 02/17/2018] [Indexed: 05/20/2023]
Abstract
We created a new high-coverage, robust, and reproducible functional annotation of maize protein-coding genes based on Gene Ontology (GO) term assignments. Whereas the existing Phytozome and Gramene maize GO annotation sets only cover 41% and 56% of maize protein-coding genes, respectively, this study provides annotations for 100% of the genes. We also compared the quality of our newly derived annotations with the existing Gramene and Phytozome functional annotation sets by comparing all three to a manually annotated gold standard set of 1,619 genes where annotations were primarily inferred from direct assay or mutant phenotype. Evaluations based on the gold standard indicate that our new annotation set is measurably more accurate than those from Phytozome and Gramene. To derive this new high-coverage, high-confidence annotation set, we used sequence similarity and protein domain presence methods as well as mixed-method pipelines that were developed for the Critical Assessment of Function Annotation (CAFA) challenge. Our project to improve maize annotations is called maize-GAMER (GO Annotation Method, Evaluation, and Review), and the newly derived annotations are accessible via MaizeGDB (http://download.maizegdb.org/maize-GAMER) and CyVerse (B73 RefGen_v3 5b+ at doi.org/10.7946/P2S62P and B73 RefGen_v4 Zm00001d.2 at doi.org/10.7946/P2M925).
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Affiliation(s)
- Kokulapalan Wimalanathan
- Bioinformatics and Computational BiologyIowa State UniversityAmesIAUSA
- Department of Genetics Development and Cell BiologyIowa State UniversityAmesIAUSA
| | - Iddo Friedberg
- Bioinformatics and Computational BiologyIowa State UniversityAmesIAUSA
- Department of Veterinary Microbiology and Preventive MedicineIowa State UniversityAmesIAUSA
| | - Carson M. Andorf
- USDA‐ARS Corn Insects and Crop Genetics Research UnitIowa State UniversityAmesIAUSA
- Department of Computer ScienceIowa State UniversityAmesIAUSA
| | - Carolyn J. Lawrence‐Dill
- Bioinformatics and Computational BiologyIowa State UniversityAmesIAUSA
- Department of Genetics Development and Cell BiologyIowa State UniversityAmesIAUSA
- Department of AgronomyIowa State UniversityAmesIAUSA
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43
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Wang Y, Ledet RJ, Imberg-Kazdan K, Logan SK, Garabedian MJ. Dynein axonemal heavy chain 8 promotes androgen receptor activity and associates with prostate cancer progression. Oncotarget 2016; 7:49268-80. [PMID: 27363033 DOI: 10.18632/oncotarget.10284] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 05/28/2016] [Indexed: 01/06/2023] Open
Abstract
To gain insight into cellular factors regulating AR action that could promote castration resistant prostate cancer (CRPC), we performed a genome-wide RNAi screen for factors that promote ligand-independent AR transcriptional activity and integrated clinical databases for candidate genes that are positively associated with prostate cancer metastasis and recurrence. From this analysis, we identified Dynein Axonemal Heavy Chain 8 (DNAH8) as an AR regulator that displayed higher mRNA expression in metastatic than in primary tumors, and showed high expression in patients with poor prognosis. Axonemal dyneins function in cellular motility, but the function of DNAH8 in prostate cancer or other cell types has not been reported. DNAH8 is on chromosome 6q21.2, a cancer-associated amplicon, and is primarily expressed in prostate and testis. Its expression is higher in primary tumors compared to normal prostate, and is further increased in metastatic prostate cancers. Patients expressing high levels of DNAH8 have a greater risk of relapse and a poor prognosis after prostatectomy. Depletion of DNAH8 in prostate cancer cells suppressed AR transcriptional activity and proliferation. Androgen treatment increased DNAH8 mRNA expression, and AR bound the DNAH8 promoter sequence indicating DNAH8 is an AR target gene. Thus, DNAH8 is a new regulator of AR associated with metastatic tumors and poor prognosis.
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Papatheodorou I, Fonseca NA, Keays M, Tang Y, Barrera E, Bazant W, Burke M, Füllgrabe A, Fuentes AMP, George N, Huerta L, Koskinen S, Mohammed S, Geniza M, Preece J, Jaiswal P, Jarnuczak AF, Huber W, Stegle O, Vizcaino JA, Brazma A, Petryszak R. Expression Atlas: gene and protein expression across multiple studies and organisms. Nucleic Acids Res 2018; 46:D246-D251. [PMID: 29165655 PMCID: PMC5753389 DOI: 10.1093/nar/gkx1158] [Citation(s) in RCA: 246] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 10/26/2017] [Accepted: 11/06/2017] [Indexed: 12/31/2022] Open
Abstract
Expression Atlas (http://www.ebi.ac.uk/gxa) is an added value database that provides information about gene and protein expression in different species and contexts, such as tissue, developmental stage, disease or cell type. The available public and controlled access data sets from different sources are curated and re-analysed using standardized, open source pipelines and made available for queries, download and visualization. As of August 2017, Expression Atlas holds data from 3,126 studies across 33 different species, including 731 from plants. Data from large-scale RNA sequencing studies including Blueprint, PCAWG, ENCODE, GTEx and HipSci can be visualized next to each other. In Expression Atlas, users can query genes or gene-sets of interest and explore their expression across or within species, tissues, developmental stages in a constitutive or differential context, representing the effects of diseases, conditions or experimental interventions. All processed data matrices are available for direct download in tab-delimited format or as R-data. In addition to the web interface, data sets can now be searched and downloaded through the Expression Atlas R package. Novel features and visualizations include the on-the-fly analysis of gene set overlaps and the option to view gene co-expression in experiments investigating constitutive gene expression across tissues or other conditions.
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Affiliation(s)
- Irene Papatheodorou
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Nuno A Fonseca
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Maria Keays
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Y Amy Tang
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Elisabet Barrera
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Wojciech Bazant
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Melissa Burke
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Anja Füllgrabe
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | | | - Nancy George
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Laura Huerta
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Satu Koskinen
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Suhaib Mohammed
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | | | | | | | - Andrew F Jarnuczak
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Wolfgang Huber
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Oliver Stegle
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Juan Antonio Vizcaino
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Alvis Brazma
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
| | - Robert Petryszak
- European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK
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Kersey PJ, Allen JE, Allot A, Barba M, Boddu S, Bolt BJ, Carvalho-Silva D, Christensen M, Davis P, Grabmueller C, Kumar N, Liu Z, Maurel T, Moore B, McDowall MD, Maheswari U, Naamati G, Newman V, Ong CK, Paulini M, Pedro H, Perry E, Russell M, Sparrow H, Tapanari E, Taylor K, Vullo A, Williams G, Zadissia A, Olson A, Stein J, Wei S, Tello-Ruiz M, Ware D, Luciani A, Potter S, Finn RD, Urban M, Hammond-Kosack KE, Bolser DM, De Silva N, Howe KL, Langridge N, Maslen G, Staines DM, Yates A. Ensembl Genomes 2018: an integrated omics infrastructure for non-vertebrate species. Nucleic Acids Res 2018; 46:D802-D808. [PMID: 29092050 PMCID: PMC5753204 DOI: 10.1093/nar/gkx1011] [Citation(s) in RCA: 306] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2017] [Revised: 10/06/2017] [Accepted: 10/24/2017] [Indexed: 02/06/2023] Open
Abstract
Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including genome sequence, gene models, transcript sequence, genetic variation, and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments and expansions. These include the incorporation of almost 20 000 additional genome sequences and over 35 000 tracks of RNA-Seq data, which have been aligned to genomic sequence and made available for visualization. Other advances since 2015 include the release of the database in Resource Description Framework (RDF) format, a large increase in community-derived curation, a new high-performance protein sequence search, additional cross-references, improved annotation of non-protein-coding genes, and the launch of pre-release and archival sites. Collectively, these changes are part of a continuing response to the increasing quantity of publicly-available genome-scale data, and the consequent need to archive, integrate, annotate and disseminate these using automated, scalable methods.
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Affiliation(s)
- Paul Julian Kersey
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - James E Allen
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Alexis Allot
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Matthieu Barba
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Sanjay Boddu
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Bruce J Bolt
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Denise Carvalho-Silva
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Mikkel Christensen
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Paul Davis
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Christoph Grabmueller
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Navin Kumar
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Zicheng Liu
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Thomas Maurel
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Ben Moore
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Mark D McDowall
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Uma Maheswari
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Guy Naamati
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Victoria Newman
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Chuang Kee Ong
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Michael Paulini
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Helder Pedro
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Emily Perry
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Matthew Russell
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Helen Sparrow
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Electra Tapanari
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Kieron Taylor
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Alessandro Vullo
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Gareth Williams
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Amonida Zadissia
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Andrew Olson
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
| | - Joshua Stein
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
| | - Sharon Wei
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
| | - Marcela Tello-Ruiz
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
| | - Doreen Ware
- Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
- USDA-ARS NAA Plant, Soil and Nutrition Laboratory Research Unit, Cornell University, Ithaca, NY 14853, USA
| | - Aurelien Luciani
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Simon Potter
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Robert D Finn
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Martin Urban
- Rothamsted Research, Department of Biointeractions and Crop Protection, Harpenden, Hertfordshire, AL5 2JQ, UK
| | - Kim E Hammond-Kosack
- Rothamsted Research, Department of Biointeractions and Crop Protection, Harpenden, Hertfordshire, AL5 2JQ, UK
| | - Dan M Bolser
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Nishadi De Silva
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Kevin L Howe
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Nicholas Langridge
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Gareth Maslen
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Daniel Michael Staines
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
| | - Andrew Yates
- The European Molecular Biology Laboratory, The European Bioinformatics Institute, The Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK
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Abstract
Epigenomics is represented by the high-throughput investigations of genome-wide epigenetic alterations, which ultimately dictate genomic, transcriptomic, proteomic and metabolomic dynamism. Rice has been accepted as the global staple crop. As a result, this model crop deserves significant importance in the rapidly emerging field of plant epigenomics. A large number of recently available data reveal the immense flexibility and potential of variable epigenomic landscapes. Such epigenomic impacts and variability are determined by a number of epigenetic regulators and several crucial inheritable epialleles, respectively. This article highlights the correlation of the epigenomic landscape with growth, flowering, reproduction, non-coding RNA-mediated post-transcriptional regulation, transposon mobility and even heterosis in rice. We have also discussed the drastic epigenetic alterations which are reported in rice plants grown from seeds exposed to the extraterrestrial environment. Such abiotic conditions impose stress on the plants leading to epigenomic modifications in a genotype-specific manner. Some significant bioinformatic databases and in silico approaches have also been explained in this article. These softwares provide important interfaces for comparative epigenomics. The discussion concludes with a unified goal of developing epigenome editing to promote biological hacking of the rice epigenome. Such a cutting-edge technology if properly standardized, can integrate genomics and epigenomics together with the generation of high-yielding trait in several cultivars of rice.
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Affiliation(s)
- Aditya Banerjee
- Department of Biotechnology, St. Xavier's College (Autonomous), 30, Mother Teresa Sarani, Kolkata, 700016, West Bengal, India
| | - Aryadeep Roychoudhury
- Department of Biotechnology, St. Xavier's College (Autonomous), 30, Mother Teresa Sarani, Kolkata, 700016, West Bengal, India.
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47
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Abstract
Medicago truncatula emerged in 1990 as a model for legumes, comprising the third largest land plant family. Most legumes form symbiotic nitrogen-fixing root nodules with compatible soil bacteria and thus are important contributors to the global nitrogen cycle and sustainable agriculture. Legumes and legume products are important sources for human and animal protein as well as for edible and industrial oils. In the years since M. truncatula was chosen as a legume model, many genetic, genomic, and molecular resources have become available, including reference quality genome sequences for two widely used genotypes. Accessibility of genomic data is important for many different types of studies with M. truncatula as well as for research involving crop and forage legumes. In this chapter, we discuss strategies to obtain archived M. truncatula genomic data originally deposited into custom databases that are no longer maintained but are now accessible in general databases. We also review key current genomic databases that are specific to M. truncatula as well as those that contain M. truncatula data in addition to data from other plants.
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Affiliation(s)
- David Burks
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, USA
| | - Rajeev Azad
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, USA.,Department of Mathematics, University of North Texas, Denton, TX, USA
| | | | - Rebecca Dickstein
- Department of Biological Sciences and BioDiscovery Institute, University of North Texas, Denton, TX, USA.
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48
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Chen F, Dong W, Zhang J, Guo X, Chen J, Wang Z, Lin Z, Tang H, Zhang L. The Sequenced Angiosperm Genomes and Genome Databases. Front Plant Sci 2018; 9:418. [PMID: 29706973 PMCID: PMC5909171 DOI: 10.3389/fpls.2018.00418] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Accepted: 03/15/2018] [Indexed: 05/18/2023]
Abstract
Angiosperms, the flowering plants, provide the essential resources for human life, such as food, energy, oxygen, and materials. They also promoted the evolution of human, animals, and the planet earth. Despite the numerous advances in genome reports or sequencing technologies, no review covers all the released angiosperm genomes and the genome databases for data sharing. Based on the rapid advances and innovations in the database reconstruction in the last few years, here we provide a comprehensive review for three major types of angiosperm genome databases, including databases for a single species, for a specific angiosperm clade, and for multiple angiosperm species. The scope, tools, and data of each type of databases and their features are concisely discussed. The genome databases for a single species or a clade of species are especially popular for specific group of researchers, while a timely-updated comprehensive database is more powerful for address of major scientific mysteries at the genome scale. Considering the low coverage of flowering plants in any available database, we propose construction of a comprehensive database to facilitate large-scale comparative studies of angiosperm genomes and to promote the collaborative studies of important questions in plant biology.
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Affiliation(s)
- Fei Chen
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Ministry of Education Key Laboratory of Genetics, Breeding and Multiple Utilization of Corps, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Wei Dong
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Ministry of Education Key Laboratory of Genetics, Breeding and Multiple Utilization of Corps, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jiawei Zhang
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Ministry of Education Key Laboratory of Genetics, Breeding and Multiple Utilization of Corps, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Xinyue Guo
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Ministry of Education Key Laboratory of Genetics, Breeding and Multiple Utilization of Corps, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Junhao Chen
- State Key Laboratory of Subtropical Silviculture, School of Forestry and Biotechnology, Zhejiang Agriculture and Forestry University, Hangzhou, China
| | - Zhengjia Wang
- State Key Laboratory of Subtropical Silviculture, School of Forestry and Biotechnology, Zhejiang Agriculture and Forestry University, Hangzhou, China
| | - Zhenguo Lin
- Department of Biology, Saint Louis University, St. Louis, MO, United States
| | - Haibao Tang
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Ministry of Education Key Laboratory of Genetics, Breeding and Multiple Utilization of Corps, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Liangsheng Zhang
- State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops, College of Life Sciences, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Ministry of Education Key Laboratory of Genetics, Breeding and Multiple Utilization of Corps, Fujian Agriculture and Forestry University, Fuzhou, China
- *Correspondence: Liangsheng Zhang
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49
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Zaini PA, Nascimento R, Gouran H, Cantu D, Chakraborty S, Phu M, Goulart LR, Dandekar AM. Molecular Profiling of Pierce's Disease Outlines the Response Circuitry of Vitis vinifera to Xylella fastidiosa Infection. Front Plant Sci 2018; 9:771. [PMID: 29937771 PMCID: PMC6002507 DOI: 10.3389/fpls.2018.00771] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2018] [Accepted: 05/18/2018] [Indexed: 05/19/2023]
Abstract
Pierce's disease is a major threat to grapevines caused by the bacterium Xylella fastidiosa. Although devoid of a type 3 secretion system commonly employed by bacterial pathogens to deliver effectors inside host cells, this pathogen is able to influence host parenchymal cells from the xylem lumen by secreting a battery of hydrolytic enzymes. Defining the cellular and biochemical changes induced during disease can foster the development of novel therapeutic strategies aimed at reducing the pathogen fitness and increasing plant health. To this end, we investigated the transcriptional, proteomic, and metabolomic responses of diseased Vitis vinifera compared to healthy plants. We found that several antioxidant strategies were induced, including the accumulation of gamma-aminobutyric acid (GABA) and polyamine metabolism, as well as iron and copper chelation, but these were insufficient to protect the plant from chronic oxidative stress and disease symptom development. Notable upregulation of phytoalexins, pathogenesis-related proteins, and various aromatic acid metabolites was part of the host responses observed. Moreover, upregulation of various cell wall modification enzymes followed the proliferation of the pathogen within xylem vessels, consistent with the intensive thickening of vessels' secondary walls observed by magnetic resonance imaging. By interpreting the molecular profile changes taking place in symptomatic tissues, we report a set of molecular markers that can be further explored to aid in disease detection, breeding for resistance, and developing therapeutics.
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Affiliation(s)
- Paulo A. Zaini
- Department of Plant Sciences, University of California, Davis, Davis, CA, United States
| | - Rafael Nascimento
- Institute of Genetics and Biochemistry, Federal University of Uberlândia, Uberlândia, Brazil
| | - Hossein Gouran
- Department of Plant Sciences, University of California, Davis, Davis, CA, United States
| | - Dario Cantu
- Department of Viticulture and Enology, University of California, Davis, Davis, CA, United States
| | - Sandeep Chakraborty
- Department of Plant Sciences, University of California, Davis, Davis, CA, United States
| | - My Phu
- Department of Plant Sciences, University of California, Davis, Davis, CA, United States
| | - Luiz R. Goulart
- Institute of Genetics and Biochemistry, Federal University of Uberlândia, Uberlândia, Brazil
| | - Abhaya M. Dandekar
- Department of Plant Sciences, University of California, Davis, Davis, CA, United States
- *Correspondence: Abhaya M. Dandekar,
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50
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Mlecnik B, Galon J, Bindea G. Comprehensive functional analysis of large lists of genes and proteins. J Proteomics 2018; 171:2-10. [DOI: 10.1016/j.jprot.2017.03.016] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Revised: 03/13/2017] [Accepted: 03/19/2017] [Indexed: 01/16/2023]
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