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      Gene expression atlas of fruit ripening and transcriptome assembly from RNA-seq data in octoploid strawberry ( Fragaria ×  ananassa)

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          Abstract

          RNA-seq has been used to perform global expression analysis of the achene and the receptacle at four stages of fruit ripening, and of the roots and leaves of strawberry ( Fragaria ×  ananassa). About 967 million reads and 191 Gb of sequence were produced, using Illumina sequencing. Mapping the reads in the related genome of the wild diploid Fragaria vesca revealed differences between the achene and receptacle development program, and reinforced the role played by ethylene in the ripening receptacle. For the strawberry transcriptome assembly, a de novo strategy was followed, generating separate assemblies for each of the ten tissues and stages sampled. The Trinity program was used for these assemblies, resulting in over 1.4 M isoforms. Filtering by a threshold of 0.3 FPKM, and doing Blastx (E-value < 1 e-30) against the UniProt database of plants reduced the number to 472,476 isoforms. Their assembly with the MIRA program (90% homology) resulted in 26,087 contigs. From these, 91.34 percent showed high homology to Fragaria vesca genes and 87.30 percent Fragaria iinumae (BlastN E-value < 1 e-100). Mapping back the reads on the MIRA contigs identified polymorphisms at nucleotide level, using FREEBAYES, as well as estimate their relative abundance in each sample.

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          TopHat: discovering splice junctions with RNA-Seq

          Motivation: A new protocol for sequencing the messenger RNA in a cell, known as RNA-Seq, generates millions of short sequence fragments in a single run. These fragments, or ‘reads’, can be used to measure levels of gene expression and to identify novel splice variants of genes. However, current software for aligning RNA-Seq data to a genome relies on known splice junctions and cannot identify novel ones. TopHat is an efficient read-mapping algorithm designed to align reads from an RNA-Seq experiment to a reference genome without relying on known splice sites. Results: We mapped the RNA-Seq reads from a recent mammalian RNA-Seq experiment and recovered more than 72% of the splice junctions reported by the annotation-based software from that study, along with nearly 20 000 previously unreported junctions. The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer. We describe several challenges unique to ab initio splice site discovery from RNA-Seq reads that will require further algorithm development. Availability: TopHat is free, open-source software available from http://tophat.cbcb.umd.edu Contact: cole@cs.umd.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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            Genome-wide analysis of the ERF gene family in Arabidopsis and rice.

            Genes in the ERF family encode transcriptional regulators with a variety of functions involved in the developmental and physiological processes in plants. In this study, a comprehensive computational analysis identified 122 and 139 ERF family genes in Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa L. subsp. japonica), respectively. A complete overview of this gene family in Arabidopsis is presented, including the gene structures, phylogeny, chromosome locations, and conserved motifs. In addition, a comparative analysis between these genes in Arabidopsis and rice was performed. As a result of these analyses, the ERF families in Arabidopsis and rice were divided into 12 and 15 groups, respectively, and several of these groups were further divided into subgroups. Based on the observation that 11 of these groups were present in both Arabidopsis and rice, it was concluded that the major functional diversification within the ERF family predated the monocot/dicot divergence. In contrast, some groups/subgroups are species specific. We discuss the relationship between the structure and function of the ERF family proteins based on these results and published information. It was further concluded that the expansion of the ERF family in plants might have been due to chromosomal/segmental duplication and tandem duplication, as well as more ancient transposition and homing. These results will be useful for future functional analyses of the ERF family genes.
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              Next-generation transcriptome assembly.

              Transcriptomics studies often rely on partial reference transcriptomes that fail to capture the full catalogue of transcripts and their variations. Recent advances in sequencing technologies and assembly algorithms have facilitated the reconstruction of the entire transcriptome by deep RNA sequencing (RNA-seq), even without a reference genome. However, transcriptome assembly from billions of RNA-seq reads, which are often very short, poses a significant informatics challenge. This Review summarizes the recent developments in transcriptome assembly approaches - reference-based, de novo and combined strategies - along with some perspectives on transcriptome assembly in the near future.
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                Author and article information

                Contributors
                iraida.amaya@juntadeandalucia.es
                valpuesta@uma.es
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                23 October 2017
                23 October 2017
                2017
                : 7
                : 13737
                Affiliations
                [1 ]Instituto Andaluz de Investigación y Formación Agraria y Pesquera (IFAPA), Centro de Churriana, Málaga, Spain
                [2 ]ISNI 0000 0001 2183 4846, GRID grid.4711.3, Departamento de Biología Molecular y Bioquímica, Instituto de Hortofruticultura Subtropical y Mediterranea (IHSM), Universidad de Málaga-Consejo Superior de Investigaciones Científicas, ; Málaga, Spain
                [3 ]ISNI 0000 0001 0694 4940, GRID grid.438526.e, Department of Horticulture, Virginia Tech, ; 24060 Blacksburg, VA USA
                Author information
                http://orcid.org/0000-0001-6257-8914
                Article
                14239
                10.1038/s41598-017-14239-6
                5653846
                29062051
                62bdef17-122f-4728-9bf7-26f474f396d7
                © The Author(s) 2017

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 13 July 2017
                : 6 October 2017
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