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      Genome-Wide Analysis of lncRNA and mRNA Expression During Differentiation of Abdominal Preadipocytes in the Chicken

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          Abstract

          Long noncoding RNAs (lncRNAs) regulate adipogenesis and other processes associated with metabolic tissue development and function. However, little is known about the function and profile of lncRNAs during preadipocyte differentiation in the chicken ( Gallus gallus). Herein, lncRNA and mRNA expression in preadipocytes at different stages of differentiation were analyzed using RNA sequencing. A total of 1,300,074,528 clean reads and 27,023 novel lncRNAs were obtained from 12 samples. The number of genes (1336 lncRNAs and 1759 mRNAs; 3095 in total) differentially expressed across various stages declined as differentiation progressed. Differentially expressed genes were found to be involved in several pathways related to preadipocyte differentiation that have been extensively studied, including glycerolipid metabolism, and the mammalian target of rapamycin, peroxisome proliferator-activated receptor, and mitogen-activated protein kinase signaling pathways. To our knowledge, some pathways are being reported for the first time, including the propanoate metabolism, fatty acid metabolism, and oxidative phosphorylation pathways. Furthermore, 3095 differentially expressed genes were clustered into eight clusters, and their expression patterns were determined through K-means clustering. Genes involved in the K2 cluster likely play important roles in preadipocyte differentiation. Six stage-specific modules related to A0 (day 0), A2 (day 2), and A6 (day 6) stages were identified, using weighted coexpression network analysis. Nine central, highly connected .genes in stage-specific modules were subsequently identified, including XLOC_068731, XLOC_022661, XLOC_045161, XLOC_070302, CHD6, LLGL1, NEURL1B, KLHL38, and ACTR6. This study provides a valuable resource for further study of chicken lncRNA and facilitates a better understanding of preadipocyte differentiation in the chicken

          Most cited references41

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          Identification of novel transcripts in annotated genomes using RNA-Seq.

          We describe a new 'reference annotation based transcript assembly' problem for RNA-Seq data that involves assembling novel transcripts in the context of an existing annotation. This problem arises in the analysis of expression in model organisms, where it is desirable to leverage existing annotations for discovering novel transcripts. We present an algorithm for reference annotation-based transcript assembly and show how it can be used to rapidly investigate novel transcripts revealed by RNA-Seq in comparison with a reference annotation. The methods described in this article are implemented in the Cufflinks suite of software for RNA-Seq, freely available from http://bio.math.berkeley.edu/cufflinks. The software is released under the BOOST license. cole@broadinstitute.org; lpachter@math.berkeley.edu Supplementary data are available at Bioinformatics online.
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            Gene connectivity, function, and sequence conservation: predictions from modular yeast co-expression networks

            Background Genes and proteins are organized into functional modular networks in which the network context of a gene or protein has implications for cellular function. Highly connected hub proteins, largely responsible for maintaining network connectivity, have been found to be much more likely to be essential for yeast survival. Results Here we investigate the properties of weighted gene co-expression networks formed from multiple microarray datasets. The constructed networks approximate scale-free topology, but this is not universal across all datasets. We show strong positive correlations between gene connectivity within the whole network and gene essentiality as well as gene sequence conservation. We demonstrate the preservation of a modular structure of the networks formed, and demonstrate that, within some of these modules, it is possible to observe a strong correlation between connectivity and essentiality or between connectivity and conservation within the modules particularly within modules containing larger numbers of essential genes. Conclusion Application of these techniques can allow a finer scale prediction of relative gene importance for a particular process within a group of similarly expressed genes.
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              De Novo Reconstruction of Adipose Tissue Transcriptomes Reveals Long Non-coding RNA Regulators of Brown Adipocyte Development.

              Brown adipose tissue (BAT) protects against obesity by promoting energy expenditure via uncoupled respiration. To uncover BAT-specific long non-coding RNAs (lncRNAs), we used RNA-seq to reconstruct de novo transcriptomes of mouse brown, inguinal white, and epididymal white fat and identified ∼1,500 lncRNAs, including 127 BAT-restricted loci induced during differentiation and often targeted by key regulators PPARγ, C/EBPα, and C/EBPβ. One of them, lnc-BATE1, is required for establishment and maintenance of BAT identity and thermogenic capacity. lnc-BATE1 inhibition impairs concurrent activation of brown fat and repression of white fat genes and is partially rescued by exogenous lnc-BATE1 with mutated siRNA-targeting sites, demonstrating a function in trans. We show that lnc-BATE1 binds heterogeneous nuclear ribonucleoprotein U and that both are required for brown adipogenesis. Our work provides an annotated catalog for the study of fat depot-selective lncRNAs and establishes lnc-BATE1 as a regulator of BAT development and physiology.
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                Author and article information

                Journal
                G3 (Bethesda)
                Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                20 January 2017
                March 2017
                : 7
                : 3
                : 953-966
                Affiliations
                [1]College of Animal Science and Technology, Yangzhou University, Yangzhou, 225009 Jiangsu, China
                Author notes
                [1 ]Corresponding author: College of Animal Science and Technology, Yangzhou University, 48 East Wenhui Rd., Yangzhou, 225009 Jiangsu, China. E-mail: jywang@ 123456yzu.edu.cn
                Author information
                http://orcid.org/0000-0002-5706-0624
                Article
                GGG_037069
                10.1534/g3.116.037069
                5345725
                28108554
                e1b3be40-e648-4489-860f-2993d05ebf61
                Copyright © 2017 Zhang et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 08 November 2016
                : 16 January 2017
                Page count
                Figures: 9, Tables: 2, Equations: 0, References: 62, Pages: 14
                Categories
                Genomic Selection

                Genetics
                preadipocyte differentiation,rna-sequencing,stage-specific module,chicken,genpred,shared data resources,genomic selection

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