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      Identification of central regulators related to abdominal fat deposition in chickens based on weighted gene co-expression network analysis

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          Abstract

          Abdominal fat ( AF) is one of the most important economic traits in chickens. Excessive AF in chickens will reduce feed utilization efficiency and negatively affect reproductive performance and disease resistance. However, the regulatory network of AF deposition needs to be further elucidated. In the present study, 300 one-day-old female Wannan chickens were reared to 17 wk of age, and 200 Wannan hens were selected to determine the abdominal fat percentage ( AFP). Twenty AF tissue samples with the lowest AFP were selected as the low abdominal fat group ( L-AFG), and 20 AF tissue samples with the highest AFP were selected as the high abdominal fat group ( H-AFG). Eleven samples from L-AFG and 14 samples from H-AFG were selected for RNA-seq and used for weighted gene co-expression network analysis ( WGCNA). Among the 25 RNA-seq samples, 5 samples with the lowest and highest AFP values were selected for differential expression gene analysis. Compared with the L-AFG, 225 and 101 genes were upregulated and downregulated in the H-AFG, respectively. A total of 20,503 genes were used to construct the WGCNA, and 44 co-expression gene modules were identified. Among these modules, 3 modules including turquoise, darkorange2, and floralwhite were identified as significantly associated with AFP traits. Furthermore, several genes including acyl-CoA oxidase 1 ( ACOX1 ), stearoyl-CoA desaturase ( SCD ), aldehyde dehydrogenase 6 family member A1 ( ALDH6A1 ), jun proto-oncogene, AP-1 transcription factor subunit ( JUN ), and fos proto-oncogene, AP-1 transcription factor subunit ( FOS ) involved in the “PPAR signaling pathway,” “fatty acid metabolism,” and “MAPK signaling pathway” were identified as central regulators that contribute to AF deposition. These results provide valuable information for further understanding of the gene expression and regulation of AF traits and contribute to future molecular breeding for AF in chickens.

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          Most cited references46

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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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            The Sequence Alignment/Map format and SAMtools

            Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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
                Poult Sci
                Poult Sci
                Poultry Science
                Elsevier
                0032-5791
                1525-3171
                05 January 2024
                March 2024
                05 January 2024
                : 103
                : 3
                : 103436
                Affiliations
                [0001]College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
                Author notes
                [1 ]Corresponding author: jiangrunshen@ 123456ahau.edu.cn
                Article
                S0032-5791(24)00015-4 103436
                10.1016/j.psj.2024.103436
                10828593
                38237326
                65a6637a-ff9c-49f5-9fb7-f48b873651ad
                © 2024 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 11 November 2023
                : 3 January 2024
                Categories
                GENETICS AND MOLECULAR BIOLOGY

                chicken,abdominal fat,weighted gene co-expression network analysis,central regulator

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