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      Overexpression of vesicle-associated membrane protein PttVAP27-17 as a tool to improve biomass production and the overall saccharification yields in Populus trees

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          Abstract

          Background

          Bioconversion of wood into bioproducts and biofuels is hindered by the recalcitrance of woody raw material to bioprocesses such as enzymatic saccharification. Targeted modification of the chemical composition of the feedstock can improve saccharification but this gain is often abrogated by concomitant reduction in tree growth.

          Results

          In this study, we report on transgenic hybrid aspen ( Populus tremula × tremuloides) lines that showed potential to increase biomass production both in the greenhouse and after 5 years of growth in the field. The transgenic lines carried an overexpression construct for Populus tremula × tremuloides vesicle-associated membrane protein (VAMP)-associated protein PttVAP27-17 that was selected from a gene-mining program for novel regulators of wood formation. Analytical-scale enzymatic saccharification without any pretreatment revealed for all greenhouse-grown transgenic lines, compared to the wild type, a 20–44% increase in the glucose yield per dry weight after enzymatic saccharification, even though it was statistically significant only for one line. The glucose yield after enzymatic saccharification with a prior hydrothermal pretreatment step with sulfuric acid was not increased in the greenhouse-grown transgenic trees on a dry-weight basis, but increased by 26–50% when calculated on a whole biomass basis in comparison to the wild-type control. Tendencies to increased glucose yields by up to 24% were present on a whole tree biomass basis after acidic pretreatment and enzymatic saccharification also in the transgenic trees grown for 5 years on the field when compared to the wild-type control.

          Conclusions

          The results demonstrate the usefulness of gene-mining programs to identify novel genes with the potential to improve biofuel production in tree biotechnology programs. Furthermore, multi-omic analyses, including transcriptomic, proteomic and metabolomic analyses, performed here provide a toolbox for future studies on the function of VAP27 proteins in plants.

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          Most cited references61

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            STAR: ultrafast universal RNA-seq aligner.

            Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. To align our large (>80 billon reads) ENCODE Transcriptome RNA-seq dataset, we developed the Spliced Transcripts Alignment to a Reference (STAR) software based on a previously undescribed RNA-seq alignment algorithm that uses sequential maximum mappable seed search in uncompressed suffix arrays followed by seed clustering and stitching procedure. STAR outperforms other aligners by a factor of >50 in mapping speed, aligning to the human genome 550 million 2 × 76 bp paired-end reads per hour on a modest 12-core server, while at the same time improving alignment sensitivity and precision. In addition to unbiased de novo detection of canonical junctions, STAR can discover non-canonical splices and chimeric (fusion) transcripts, and is also capable of mapping full-length RNA sequences. Using Roche 454 sequencing of reverse transcription polymerase chain reaction amplicons, we experimentally validated 1960 novel intergenic splice junctions with an 80-90% success rate, corroborating the high precision of the STAR mapping strategy. STAR is implemented as a standalone C++ code. STAR is free open source software distributed under GPLv3 license and can be downloaded from http://code.google.com/p/rna-star/.
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              The PRIDE database and related tools and resources in 2019: improving support for quantification data

              Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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                Author and article information

                Contributors
                hannele.tuominen@slu.se
                Journal
                Biotechnol Biofuels
                Biotechnol Biofuels
                Biotechnology for Biofuels
                BioMed Central (London )
                1754-6834
                16 February 2021
                16 February 2021
                2021
                : 14
                : 43
                Affiliations
                [1 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Department of Chemistry, , Umeå University, ; 901 87, Umeå, Sweden
                [2 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Umeå Plant Science Centre, Department of Plant Physiology, , Umeå University, ; 901 87 Umeå, Sweden
                [3 ]GRID grid.6341.0, ISNI 0000 0000 8578 2742, Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, , Swedish University of Agricultural Sciences, ; 901 83 Umeå, Sweden
                [4 ]GRID grid.438270.a, SweTree Technologies, ; PO Box 7981, 907 19 Umeå, Sweden
                [5 ]GRID grid.19477.3c, ISNI 0000 0004 0607 975X, Present Address: Faculty of Chemistry, Biotechnology and Food Science, , Norwegian University of Life Sciences, ; 1432 Ås, Norway
                [6 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Computational Life Science Cluster (CLiC), Department of Chemistry, , Umeå University, ; Umeå, Sweden
                [7 ]GRID grid.8761.8, ISNI 0000 0000 9919 9582, Present Address: Department of Microbiology and Immunology, Institute of Biomedicine, , University of Gothenburg, ; 40530 Gothenburg, Sweden
                [8 ]GRID grid.6341.0, ISNI 0000 0000 8578 2742, Present Address: Umeå Plant Science Centre, Department of Forest Genetics and Plant Physiology, , Swedish University of Agricultural Sciences, ; 901 83 Umeå, Sweden
                Author information
                http://orcid.org/0000-0002-4949-3702
                Article
                1895
                10.1186/s13068-021-01895-0
                7885582
                33593413
                a95fddcd-ecc0-4300-bbd3-49e05b29ab4c
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 23 October 2020
                : 4 February 2021
                Funding
                Funded by: Swedish Research Council FORMAS
                Award ID: 232–2009-1698
                Funded by: Swedish Foundation for Strategic Research
                Award ID: RBP14–0011
                Funded by: the Swedish Governmental Agency for Innovation Systems Vinnova
                Award ID: 2015–02290
                Funded by: the KAW Foundation
                Award ID: 2016-0341
                Funded by: the strategic research environment Bio4Energy, and the Swedish Energy Agency
                Award ID: P47516-1
                Funded by: Swedish University of Agricultural Sciences
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Biotechnology
                populus,vesicle-associated membrane protein,vamp,vamp-associated protein,vap27,growth,bioprocessing,transcriptomics,proteomics,metabolomics

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