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      ForageGrassBase: molecular resource for the forage grass meadow fescue ( Festuca pratensis Huds.)

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          Abstract

          Meadow fescue ( Festuca pratensis Huds.) is one of the most important forage grasses in temperate regions. It is a diploid (2n = 14) outbreeding species that belongs to the genus Festuca. Together with Lolium perenne, they are the most important genera of forage grasses. Meadow fescue has very high quality of yield with good winter survival and persistency. However, extensive genomic resources for meadow fescue have not become available so far. To address this lack of comprehensive publicly available datasets, we have developed functionally annotated draft genome sequences of two meadow fescue genotypes, ‘HF7/2’ and ‘B14/16’, and constructed the platform ForageGrassBase, available at http://foragegrass.org/, for data visualization, download and querying. This is the first open-access platform that provides extensive genomic resources related to this forage grass species. The current database provides the most up-to-date draft genome sequence along with structural and functional annotations for genes that can be accessed using Genome Browser (GBrowse), along with comparative genomic alignments to Arabidopsis, L. perenne, barley, rice, Brachypodium and maize genomes. We have integrated homologous search tool BLAST also for the users to analyze their data. Combined, GBrowse, BLAST and downloadable data gives a user-friendly access to meadow fescue genomic resources. To our knowledge, ForageGrassBase is the first genome database dedicated to forage grasses. The current forage grass database provides valuable resources for a range of research fields related to meadow fescue and other forage crop species, as well as for plant research communities in general. The genome database can be accessed at http://foragegrass.org.

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          Magic-BLAST, an accurate RNA-seq aligner for long and short reads

          Background Next-generation sequencing technologies can produce tens of millions of reads, often paired-end, from transcripts or genomes. But few programs can align RNA on the genome and accurately discover introns, especially with long reads. We introduce Magic-BLAST, a new aligner based on ideas from the Magic pipeline. Results Magic-BLAST uses innovative techniques that include the optimization of a spliced alignment score and selective masking during seed selection. We evaluate the performance of Magic-BLAST to accurately map short or long sequences and its ability to discover introns on real RNA-seq data sets from PacBio, Roche and Illumina runs, and on six benchmarks, and compare it to other popular aligners. Additionally, we look at alignments of human idealized RefSeq mRNA sequences perfectly matching the genome. Conclusions We show that Magic-BLAST is the best at intron discovery over a wide range of conditions and the best at mapping reads longer than 250 bases, from any platform. It is versatile and robust to high levels of mismatches or extreme base composition, and reasonably fast. It can align reads to a BLAST database or a FASTA file. It can accept a FASTQ file as input or automatically retrieve an accession from the SRA repository at the NCBI. Electronic supplementary material The online version of this article (10.1186/s12859-019-2996-x) contains supplementary material, which is available to authorized users.
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            A synteny-based draft genome sequence of the forage grass Lolium perenne.

            Here we report the draft genome sequence of perennial ryegrass (Lolium perenne), an economically important forage and turf grass species that is widely cultivated in temperate regions worldwide. It is classified along with wheat, barley, oats and Brachypodium distachyon in the Pooideae sub-family of the grass family (Poaceae). Transcriptome data was used to identify 28,455 gene models, and we utilized macro-co-linearity between perennial ryegrass and barley, and synteny within the grass family, to establish a synteny-based linear gene order. The gametophytic self-incompatibility mechanism enables the pistil of a plant to reject self-pollen and therefore promote out-crossing. We have used the sequence assembly to characterize transcriptional changes in the stigma during pollination with both compatible and incompatible pollen. Characterization of the pollen transcriptome identified homologs to pollen allergens from a range of species, many of which were expressed to very high levels in mature pollen grains, and are potentially involved in the self-incompatibility mechanism. The genome sequence provides a valuable resource for future breeding efforts based on genomic prediction, and will accelerate the development of new varieties for more productive grasslands.
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              Using the Generic Genome Browser (GBrowse).

              A genome browser is software that allows users to visualize DNA, protein, or other sequence features within the context of a reference sequence, such as a chromosome or contig. The Generic Genome Browser (GBrowse) is an open-source browser developed as part of the Generic Model Organism Database project (Stein et al., 2002). GBrowse can be configured to display genomic sequence features for any organism and is the browser used for the model organisms Drosophila melanogaster (Grumbling and Strelets, 2006) and Caenorhabditis elegans (Schwarz et al., 2006), among others. The software package can be downloaded from the Web and run on a Windows, Mac OS X, or Unix-type system. Version 1.64, as described in the original protocol, was released in November 2005, but the software is under active development and new versions are released about every six months. This update includes instructions on updating existing data sources with new files from NCBI.
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                Author and article information

                Journal
                Database (Oxford)
                Database (Oxford)
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2020
                15 June 2020
                15 June 2020
                : 2020
                : baaa046
                Affiliations
                [1]Department of Plant Sciences (IPV), Faculty of Biosciences (BIOVIT), Norwegian University of Life Sciences (NMBU) , Ås, Akershus 1432, Norway
                Author notes
                Corresponding author: Tel: +47-40566127; Email: mallikarjuna.rao.kovi@ 123456nmbu.no
                Article
                baaa046
                10.1093/database/baaa046
                7294657
                32539086
                f115310f-5e2f-4340-aab8-104128cdfde8
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 3 July 2019
                : 24 December 2019
                : 21 May 2020
                Page count
                Pages: 5
                Funding
                Funded by: Research Council of Norway 10.13039/501100005416
                Award ID: 208481
                Award ID: 255428
                Award ID: 199664/I10
                Categories
                Original Article

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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