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      Comparative transcriptome sequencing analysis of female and male Decapterus macrosoma

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          Abstract

          Sexual growth dimorphism is a common phenomenon in teleost fish and has led to many reproductive strategies. Growth- and sex-related gene research in teleost fish would broaden our understanding of the process. In this study, transcriptome sequencing of shortfin scad Decapterus macrosoma was performed for the first time, and a high-quality reference transcriptome was constructed. After identification and assembly, a total of 58,475 nonredundant unigenes were obtained with an N50 length of 2,266 bp, and 28,174 unigenes were successfully annotated with multiple public databases. BUSCO analysis determined a level of 92.9% completeness for the assembled transcriptome. Gene expression analysis revealed 2,345 differentially expressed genes (DEGs) in the female and male D. macrosoma, 1,150 of which were female-biased DEGs, and 1,195 unigenes were male-biased DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that the DEGs were mainly involved in biological processes including protein synthesis, growth, rhythmic processes, immune defense, and vitellogenesis. Then, we identified many growth- and sex-related genes, including Igf, Fabps, EF-hand family genes, Zp3, Zp4 and Vg. In addition, a total of 19,573 simple sequence repeats (SSRs) were screened and identified from the transcriptome sequences. The results of this study can provide valuable information on growth- and sex-related genes and facilitate further exploration of the molecular mechanism of sexual growth dimorphism.

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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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            Trimmomatic: a flexible trimmer for Illumina sequence data

            Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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              RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

              Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                8 November 2022
                2022
                : 10
                : e14342
                Affiliations
                [1 ]Third Institute of Oceanography, Ministry of Natural Resources , Xiamen, China
                [2 ]Key Laboratory of Marine Ranching, Ministry of Agriculture and Rural Affairs , Guangzhou, China
                [3 ]Key Laboratory of Marine Ecological Conservation and Restoration, Ministry of Natural Resources , Xiamen, China
                Article
                14342
                10.7717/peerj.14342
                9651050
                b947c61f-4708-47aa-94dd-a787a5f6eb56
                © 2022 Cai et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 20 June 2022
                : 14 October 2022
                Funding
                Funded by: National Programme on Global Change and Air-Sea Interaction
                Award ID: GASI-02-SCS-YDsum
                This research was funded by the National Programme on Global Change and Air-Sea Interaction, grant number GASI-02-SCS-YDsum. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Aquaculture, Fisheries and Fish Science
                Bioinformatics
                Marine Biology
                Molecular Biology
                Zoology

                de novo assembly,decapterus macrosoma,transcriptome,growth-related genes,sex-related genes,differentially expressed genes

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