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      Differentially Expressed lncRNAs Related to the Development of Abdominal Fat in Gushi Chickens and Their Interaction Regulatory Network

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          Abstract

          Chickens are one of the most important sources of meat worldwide, and the growth status of abdominal fat is closely related to production efficiency. Long noncoding RNAs (lncRNAs) play an important role in lipid metabolism and deposition regulation. However, research on the expression profile of lncRNAs related to the development of abdominal fat in chickens after hatching and their interaction regulatory networks is still lacking. To characterize the lncRNA expression profile during the development of chicken abdominal fat, abdominal adipose tissues from 6-, 14-, 22-, and 30-week-old Chinese Gushi chickens were herein used to construct 12 cDNA libraries, and a total of 3,827 new lncRNAs and 5,466 previously annotated lncRNAs were revealed. At the same time, based on the comparative analysis of five combinations, 276 differentially expressed lncRNAs (DE-lncRNAs) were screened. Functional enrichment analysis showed that the predicted target genes of these DE-lncRNAs were significantly enriched in pathways related to the posttranscriptional regulation of gene expression, negative regulation of cell proliferation, cell adhesion and other biological processes, glycosphingolipid biosynthesis, PPAR signaling, fatty acid degradation, fatty acid synthesis and others. In addition, association analysis of the lncRNA transcriptome profile was performed, and DE-lncRNA-related lncRNA-mRNA, lncRNA-miRNA and lncRNA-miRNA-mRNA interaction regulatory networks were constructed. The results showed that DE-lncRNA formed a complex network with PPAR pathway components, including PPARD, ACOX1, ADIPOQ, CPT1A, FABP5, ASBG2, LPL, PLIN2 and related miRNAs, including mir-200b-3p, mir-130b-3p, mir-215-5p, mir-122-5p, mir-223 and mir-125b-5p, and played an important regulatory role in biological processes such as lipid metabolism, adipocyte proliferation and differentiation. This study described the dynamic expression profile of lncRNAs in the abdominal fat of Gushi chickens for the first time and constructed the DE-lncRNA interaction regulatory network. The results expand the number of known lncRNAs in chicken abdominal fat and provide valuable resources for further elucidating the posttranscriptional regulatory mechanism of chicken abdominal fat development or deposition.

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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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            clusterProfiler: an R package for comparing biological themes among gene clusters.

            Increasing quantitative data generated from transcriptomics and proteomics require integrative strategies for analysis. Here, we present an R package, clusterProfiler that automates the process of biological-term classification and the enrichment analysis of gene clusters. The analysis module and visualization module were combined into a reusable workflow. Currently, clusterProfiler supports three species, including humans, mice, and yeast. Methods provided in this package can be easily extended to other species and ontologies. The clusterProfiler package is released under Artistic-2.0 License within Bioconductor project. The source code and vignette are freely available at http://bioconductor.org/packages/release/bioc/html/clusterProfiler.html.
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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
                24 December 2021
                2021
                : 12
                : 802857
                Affiliations
                [1] 1 College of Animal Science and Technology, Henan Agricultural University , Zhengzhou, China
                [2] 2 College of Biological Engineering, Henan University of Technology , Zhengzhou, China
                [3] 3 Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources , Zhengzhou, China
                Author notes

                Edited by: Kui Li, Institute of Animal Sciences (CAAS), China

                Reviewed by: Hui Li, Northeast Agricultural University, China

                Sayed Haidar Abbas Raza, Northwest A and F University, China

                *Correspondence: Guoxi Li, liguoxi0914@ 123456126.com
                [ † ]

                These authors have contributed equally to this work

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

                Article
                802857
                10.3389/fgene.2021.802857
                8740130
                b45f240e-c208-4d9e-b10b-b0daa6670636
                Copyright © 2021 Zhai, Zhao, Fan, Yuan, Li, Li, Li, Zhang, Huang, Li, Kang and Li.

                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
                : 27 October 2021
                : 29 November 2021
                Funding
                Funded by: National Natural Science Foundation of China , doi 10.13039/501100001809;
                Award ID: 32072692 31572356
                Categories
                Genetics
                Original Research

                Genetics
                gushi chicken,abdominal fat,long noncoding rna,regulatory network,cerna
                Genetics
                gushi chicken, abdominal fat, long noncoding rna, regulatory network, cerna

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