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      Dynamic Expression and Gene Regulation of MicroRNAs During Bighead Carp ( Hypophthalmichthys nobilis) Early Development

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          Abstract

          The early development of fish is regulated through dynamic and complex mechanisms involving the regulation of various genes. Many genes are subjected to post-transcriptional regulation by microRNAs (miRNAs). In the Chinese aquaculture industry, the native species bighead carp ( Hypophthalmichthys nobilis) is important. However, the genetic regulation related to the early development of bighead carp is unknown. Here, we generated developmental profiles by miRNA sequencing to study the dynamic regulation of miRNAs during bighead carp early development. This study identified 1 046 miRNAs, comprising 312 known miRNAs and 734 uncharacterized miRNAs. Changes in miRNA expression were identified in the six early development stages. An obviously increased expression trend was detected during the development process, with the main burst of activity occurring after the earliest stage (early blastula, DS1). Investigations revealed that several miRNAs were dominantly expressed during the development process, especially in the later stages (e.g., miR-10b-5p, miR-21, miR-92a-3p, miR-206-3p, and miR-430a-3p), suggesting that these miRNAs exerted important functions during embryonic development. The differentially expressed miRNAs (DEMs) and time-serial analysis (profiles) of DEMs were analyzed. A total of 372 miRNAs were identified as DEMs (fold-change >2, and false discovery rate <0.05), and three expression profiles of the DEMs were detected to have co-expression patterns ( r > 0.7, and p < 0.05). The broad negative regulation of target genes by miRNAs was speculated, and many development-related biological processes and pathways were enriched for the targets of the DEMs, which might be associated with maternal genome degradation and embryogenesis processes. In conclusion, we revealed the repertoire of miRNAs that are active during early development of bighead carp. These findings will increase our understanding of the regulatory mechanisms of early development of fish.

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          Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

          The two most commonly used methods to analyze data from real-time, quantitative PCR experiments are absolute quantification and relative quantification. Absolute quantification determines the input copy number, usually by relating the PCR signal to a standard curve. Relative quantification relates the PCR signal of the target transcript in a treatment group to that of another sample such as an untreated control. The 2(-Delta Delta C(T)) method is a convenient way to analyze the relative changes in gene expression from real-time quantitative PCR experiments. The purpose of this report is to present the derivation, assumptions, and applications of the 2(-Delta Delta C(T)) method. In addition, we present the derivation and applications of two variations of the 2(-Delta Delta C(T)) method that may be useful in the analysis of real-time, quantitative PCR data. Copyright 2001 Elsevier Science (USA).
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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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              Cytoscape: a software environment for integrated models of biomolecular interaction networks.

              Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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                Author and article information

                Contributors
                Journal
                Front Genet
                Front Genet
                Front. Genet.
                Frontiers in Genetics
                Frontiers Media S.A.
                1664-8021
                19 January 2022
                2021
                : 12
                : 821403
                Affiliations
                [1] 1 Key Laboratory of Freshwater Fisheries and Germplasm Resources Utilization , Ministry of Agriculture and Rural Affairs , Freshwater Fisheries Research Center of Chinese Academy of Fishery Sciences , Wuxi, China
                [2] 2 Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources , Ministry of Education , Shanghai Ocean University , Shanghai, China
                [3] 3 Wuxi Fisheries College , Nanjing Agricultural University , Wuxi, China
                Author notes

                Edited by: Andrea Erika Münsterberg, University of East Anglia, United Kingdom

                Reviewed by: Min Tao, Hunan Normal University, China

                Amanda Oliveira Ribeiro, São Paulo State University, Brazil

                Ioannis Kanakis, University of Chester, United Kingdom

                *Correspondence: Zaijie Dong, dongzj@ 123456ffrc.cn , dongzaijie@ 123456ffrc.cn

                This article was submitted to RNA, a section of the journal Frontiers in Genetics

                Article
                821403
                10.3389/fgene.2021.821403
                8809360
                35126475
                6c1297f6-0b92-4487-9854-3de27b0661ef
                Copyright © 2022 Fu, Zhu, Wang, Luo, Jiang and Dong.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 November 2021
                : 30 December 2021
                Funding
                Funded by: Central Public-interest Scientific Institution Basal Research Fund, Chinese Academy of Fishery Sciences , doi 10.13039/501100012428;
                Funded by: Earmarked Fund for China Agriculture Research System , doi 10.13039/501100010038;
                Categories
                Genetics
                Original Research

                Genetics
                bighead carp,embryo,larva,development,microrna,dynamic regulation
                Genetics
                bighead carp, embryo, larva, development, microrna, dynamic regulation

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