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      Gonad transcriptome analysis reveals the differences in gene expression related to sex-biased and reproduction of clam Cyclina sinensis

      , , , , , ,
      Frontiers in Marine Science
      Frontiers Media SA

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          Abstract

          Sexual differentiation and gonad development are important biological processes for bivalve species. The clam Cyclina sinensis is an important cultured marine bivalve widely distributed along with the coastal areas of China. However, the information related to sexual determination/differentiation and gonadal development of C. sinensis almost has no reported. To study the molecular mechanisms of its sexual determination/differentiation and gonadal development, transcriptome analysis was performed in the gonad of C. sinensis, and the potential biological functions of reproduction-related gene were also investigated in this study. The results showed that 1 013 and 427 genes were differentially expressed in the ovary and testis, respectively. KEGG enrichment analysis showed that the DEGs in the gonad were significantly clustered in progesterone-mediated oocyte maturation, cell cycle and oocyte meiosis. Further analysis showed that 23 genes were mainly involved in sex determination/differentiation, including Dmrt1, Sox2/4/9, Foxl2, β-catenin and GATA-type zinc finger protein 1-like. Twenty key genes were mainly involved in the process of spermatogenesis, and five genes encode steroid biosynthesis and metabolism. Fifteen genes related to ovarian development were also identified in this study, such as Vitellogenin, MAM and LDL-receptor class A domain-containing protein 1 and Cell division cycle protein 20 homolog. Moreover, 50µg/L estradiol treatment significantly up-regulated the expression levels of CsVg in the ovary and hepatopancreas. These results highlight the genes involved in sexual determination/differentiation and gonadal development, which enhance our understanding for further studies of reproduction and breeding of C. sinensis and other marine bivalves.

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          fastp: an ultra-fast all-in-one FASTQ preprocessor

          Abstract Motivation Quality control and preprocessing of FASTQ files are essential to providing clean data for downstream analysis. Traditionally, a different tool is used for each operation, such as quality control, adapter trimming and quality filtering. These tools are often insufficiently fast as most are developed using high-level programming languages (e.g. Python and Java) and provide limited multi-threading support. Reading and loading data multiple times also renders preprocessing slow and I/O inefficient. Results We developed fastp as an ultra-fast FASTQ preprocessor with useful quality control and data-filtering features. It can perform quality control, adapter trimming, quality filtering, per-read quality pruning and many other operations with a single scan of the FASTQ data. This tool is developed in C++ and has multi-threading support. Based on our evaluation, fastp is 2–5 times faster than other FASTQ preprocessing tools such as Trimmomatic or Cutadapt despite performing far more operations than similar tools. Availability and implementation The open-source code and corresponding instructions are available at https://github.com/OpenGene/fastp.
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            Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

            Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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              Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

              High-throughput mRNA sequencing (RNA-Seq) holds the promise of simultaneous transcript discovery and abundance estimation 1-3 . We introduce an algorithm for transcript assembly coupled with a statistical model for RNA-Seq experiments that produces estimates of abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the time series revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development.
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                Author and article information

                Journal
                Frontiers in Marine Science
                Front. Mar. Sci.
                Frontiers Media SA
                2296-7745
                January 16 2023
                January 16 2023
                : 9
                Article
                10.3389/fmars.2022.1110587
                b26e34cd-b179-4b56-8299-50d5e7c47988
                © 2023

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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