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Tino Polen - One of the best experts on this subject based on the ideXlab platform.
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RNAseq analysis of α-proteobacterium Gluconobacter oxydans 621H
BMC Genomics, 2018Co-Authors: Angela Kranz, Tobias Busche, Alexander Vogel, Björn Usadel, Jörn Kalinowski, Michael Bott, Tino PolenAbstract:Background The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its Transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary Transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole Transcriptomes were sequenced to identify expressed genes and operon structures. Results Sequencing of primary Transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis -regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole Transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). Conclusions This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive Transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans . The corrections of start codons further improve the high quality genome reference and support future proteome analysis.
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rnaseq analysis of α proteobacterium gluconobacter oxydans 621h
BMC Genomics, 2018Co-Authors: Angela Kranz, Tobias Busche, Alexander Vogel, Björn Usadel, Jörn Kalinowski, Michael Bott, Tino PolenAbstract:The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its Transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary Transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole Transcriptomes were sequenced to identify expressed genes and operon structures. Sequencing of primary Transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis-regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole Transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive Transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans. The corrections of start codons further improve the high quality genome reference and support future proteome analysis.
Rosario Carmona - One of the best experts on this subject based on the ideXlab platform.
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TransFlow: a modular framework for assembling and assessing accurate de novo Transcriptomes in non-model organisms
BMC, 2018Co-Authors: Pedro Seoane, Marina Espigares, Rosario Carmona, Álvaro Polonio, Julia Quintana, Enrico Cretazzo, Josefina Bota, Alejandro Pérez-garcía, Juan De Dios Alché, Luis GómezAbstract:Abstract Background The advances in high-throughput sequencing technologies are allowing more and more de novo assembling of Transcriptomes from many new organisms. Some degree of automation and evaluation is required to warrant reproducibility, repetitivity and the selection of the best possible Transcriptome. Workflows and pipelines are becoming an absolute requirement for such a purpose, but the issue of assembling evaluation for de novo Transcriptomes in organisms lacking a sequenced genome remains unsolved. An automated, reproducible and flexible framework called TransFlow to accomplish this task is described. Results TransFlow with its five independent modules was designed to build different workflows depending on the nature of the original reads. This architecture enables different combinations of Illumina and Roche/454 sequencing data, and can be extended to other sequencing platforms. Its capabilities are illustrated with the selection of reliable plant reference Transcriptomes and the assembling six Transcriptomes (three case studies for grapevine leaves, olive tree pollen, and chestnut stem, and other three for haustorium, epiphytic structures and their combination for the phytopathogenic fungus Podosphaera xanthii). Arabidopsis and poplar Transcriptomes revealed to be the best references. A common result regarding de novo assemblies is that Illumina paired-end reads of 100 nt in length assembled with OASES can provide reliable Transcriptomes, while the contribution of longer reads is noticeable only when they complement a set of short, single-reads. Conclusions TransFlow can handle up to 181 different assembling strategies. Evaluation based on principal component analyses allows its self-adaptation to different sets of reads to provide a suitable Transcriptome for each combination of reads and assemblers. As a result, each case study has its own behaviour, prioritises evaluation parameters, and gives an objective and automated way for detecting the best Transcriptome within a pool of them. Sequencing data type and quantity (preferably several hundred millions of 2×100 nt or longer), assemblers (OASES for Illumina, MIRA4 and EULER-SR reconciled with CAP3 for Roche/454) and strategy (preferably scaffolding with OASES, and probably merging with Roche/454 when available) arise as the most impacting factors
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reprolive a database with linked data for the olive tree olea europaea l reproductive Transcriptome
Frontiers in Plant Science, 2015Co-Authors: Pedro Seoane, Antonio J. De Castro, Francisco M Canovas, Adoración Zafra, Dario Guerrerofernandez, Rosario Carmona, Trinidad Castillocastillo, Ana Medinagarcia, Jose F AldanamontesAbstract:Plant reproductive Transcriptomes have been analysed in different species due to the agronomical and biotechnological importance of plant reproduction. Here we presented an olive tree reproductive Transcriptome database with samples from pollen and pistil at different developmental stages, and leaf and root as control vegetative tissues (http://reprolive.eez.csic.es). It was developed from 2,077,309 raw reads and 1,549 Sanger sequences. Using a pre-defined workflow based on open-source tools, sequences were pre-processed, assembled, mapped and annotated with expression data, descriptions, GO terms, InterPro signatures, EC numbers, KEGG pathways, ORFs, and SSRs. Tentative transcripts were also annotated with the corresponding orthologues in Arabidopsis thaliana from TAIR and RefSeq databases to enable Linked Data integration. It results in a reproductive Transcriptome comprising 72,846 contigs with average length of 686 bp, of which 63,965 (87.8%) included at least one functional annotation, and 55,356 (75.9%) had an orthologue. A minimum of 23,568 different tentative transcripts was identified and 5,835 of them contain a complete ORF. The representative reproductive Transcriptome can be reduced to 28,972 tentative transcripts for further gene expression studies. Partial Transcriptomes from pollen, pistil and vegetative tissues as control were also constructed. ReprOlive provides free access and download capability to these results. Retrieval mechanisms for sequences and transcript annotations are provided. Graphical localisation of annotated enzymes into KEGG pathways is also possible. Finally, ReprOlive has included a semantic conceptualisation by means of a Resource Description Framework (RDF) allowing a Linked Data search for extracting the most updated information related to enzymes, interactions, allergens, structures and reactive oxygen species.
Johan Decelle - One of the best experts on this subject based on the ideXlab platform.
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a de novo approach to disentangle partner identity and function in holobiont systems
Microbiome, 2018Co-Authors: Arnaud Meng, Camille Marchet, Erwan Corre, Pierre Peterlongo, Adriana Alberti, Corinne Da Silva, Patrick Wincker, Eric Pelletier, Ian Probert, Johan DecelleAbstract:Study of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges. The production of chimeric sequences and our inability to distinguish the taxonomic origins of the sequences produced are inherent and recurrent difficulties in de novo assembly analyses. As the study of holobiont meta-Transcriptomes is affected by challenges invoked above, we propose an innovative bioinformatic approach to tackle such difficulties and tested it on marine models as a proof of concept. We considered three holobiont models, of which two Transcriptomes were previously published and a yet unpublished Transcriptome, to analyze and sort their raw reads using Short Read Connector, a k-mer based similarity method. Before assembly, we thus defined four distinct categories for each holobiont meta-Transcriptome: host reads, symbiont reads, shared reads, and unassigned reads. Afterwards, we observed that independent de novo assemblies for each category led to a diminution of the number of chimeras compared to classical assembly methods. Moreover, the separation of each partner’s Transcriptome offered the independent and comparative exploration of their functional diversity in the holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts (a Cnidaria-Dinophyta, a Porifera-Bacteria) and a first meta-Transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is considerably limited. In contrast to classical assembly approaches, our bioinformatic strategy generates less de novo assembled chimera and allows biologists to study separately host and symbiont data from a holobiont mixture. The pre-assembly separation of reads using an efficient tool as Short Read Connector is an effective way to tackle meta-transcriptomic challenges and offers bright perpectives to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages and ultimately expand our knowledge about these associations.
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A de novo approach to disentangle partner identity and function in holobiont systems
Microbiome, 2018Co-Authors: Arnaud Meng, Camille Marchet, Erwan Corre, Pierre Peterlongo, Adriana Alberti, Corinne Da Silva, Patrick Wincker, Eric Pelletier, Ian Probert, Johan DecelleAbstract:Background: Study of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges. The production of chimeric sequences and our inability to distinguish the taxonomic origins of the sequences produced are inherent and recurrent difficulties in de novo assembly analyses. As the study of holobiont meta-Transcriptomes is affected by challenges invoked above, we propose an innovative bioinformatic approach to tackle such difficulties and tested it on marine models as a proof of concept. Results: We considered three holobiont models, of which two Transcriptomes were previously published and a yet unpublished Transcriptome, to analyze and sort their raw reads using Short Read Connector, a k-mer based similarity method. Before assembly, we thus defined four distinct categories for each holobiont meta-Transcriptome: host reads, symbiont reads, shared reads, and unassigned reads. Afterwards, we observed that independent de novo assemblies for each category led to a diminution of the number of chimeras compared to classical assembly methods. Moreover, the separation of each partner’ s Transcriptome offered the independent and comparative exploration of their functional diversity in the holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts (a Cnidaria-Dinophyta, a Porifera-Bacteria) and a first meta-Transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is considerably limited. Conclusions: In contrast to classical assembly approaches, our bioinformatic strategy generates less de novo assembled chimera and allows biologists to study separately host and symbiont data from a holobiont mixture. The pre-assembly separation of reads using an efficient tool as Short Read Connector is an effective way to tackle meta-transcriptomic challenges and offers bright perpectives to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages and ultimately expand our knowledge about these associations.
Tobias Busche - One of the best experts on this subject based on the ideXlab platform.
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RNAseq analysis of α-proteobacterium Gluconobacter oxydans 621H
BMC Genomics, 2018Co-Authors: Angela Kranz, Tobias Busche, Alexander Vogel, Björn Usadel, Jörn Kalinowski, Michael Bott, Tino PolenAbstract:Background The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its Transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary Transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole Transcriptomes were sequenced to identify expressed genes and operon structures. Results Sequencing of primary Transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis -regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole Transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). Conclusions This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive Transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans . The corrections of start codons further improve the high quality genome reference and support future proteome analysis.
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rnaseq analysis of α proteobacterium gluconobacter oxydans 621h
BMC Genomics, 2018Co-Authors: Angela Kranz, Tobias Busche, Alexander Vogel, Björn Usadel, Jörn Kalinowski, Michael Bott, Tino PolenAbstract:The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its Transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary Transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole Transcriptomes were sequenced to identify expressed genes and operon structures. Sequencing of primary Transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis-regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole Transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive Transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans. The corrections of start codons further improve the high quality genome reference and support future proteome analysis.
Alexander Vogel - One of the best experts on this subject based on the ideXlab platform.
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RNAseq analysis of α-proteobacterium Gluconobacter oxydans 621H
BMC Genomics, 2018Co-Authors: Angela Kranz, Tobias Busche, Alexander Vogel, Björn Usadel, Jörn Kalinowski, Michael Bott, Tino PolenAbstract:Background The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its Transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary Transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole Transcriptomes were sequenced to identify expressed genes and operon structures. Results Sequencing of primary Transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis -regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole Transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). Conclusions This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive Transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans . The corrections of start codons further improve the high quality genome reference and support future proteome analysis.
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rnaseq analysis of α proteobacterium gluconobacter oxydans 621h
BMC Genomics, 2018Co-Authors: Angela Kranz, Tobias Busche, Alexander Vogel, Björn Usadel, Jörn Kalinowski, Michael Bott, Tino PolenAbstract:The acetic acid bacterium Gluconobacter oxydans 621H is characterized by its exceptional ability to incompletely oxidize a great variety of carbohydrates in the periplasm. The metabolism of this α-proteobacterium has been characterized to some extent, yet little is known about its Transcriptomes and related data. In this study, we applied two different RNAseq approaches. Primary Transcriptomes enriched for 5′-ends of transcripts were sequenced to detect transcription start sites, which allow subsequent analysis of promoter motifs, ribosome binding sites, and 5´-UTRs. Whole Transcriptomes were sequenced to identify expressed genes and operon structures. Sequencing of primary Transcriptomes of G. oxydans revealed 2449 TSSs, which were classified according to their genomic context followed by identification of promoter and ribosome binding site motifs, analysis of 5´-UTRs including validation of predicted cis-regulatory elements and correction of start codons. 1144 (41%) of all genes were found to be expressed monocistronically, whereas 1634 genes were organized in 571 operons. Together, TSSs and whole Transcriptome data were also used to identify novel intergenic (18), intragenic (328), and antisense transcripts (313). This study provides deep insights into the transcriptional landscapes of G. oxydans. The comprehensive Transcriptome data, which we made publicly available, facilitate further analysis of promoters and other regulatory elements. This will support future approaches for rational strain development and targeted gene expression in G. oxydans. The corrections of start codons further improve the high quality genome reference and support future proteome analysis.
