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      Comparison of Metabolic Network between Muscle and Intramuscular Adipose Tissues in Hanwoo Beef Cattle Using a Systems Biology Approach

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          Abstract

          The interrelationship between muscle and adipose tissues plays a major role in determining the quality of carcass traits. The objective of this study was to compare metabolic differences between muscle and intramuscular adipose (IMA) tissues in the longissimus dorsi (LD) of Hanwoo ( Bos taurus coreanae) using the RNA-seq technology and a systems biology approach. The LD sections between the 6th and 7th ribs were removed from nine (each of three cows, steers, and bulls) Hanwoo beef cattle (carcass weight of 430.2 ± 40.66 kg) immediately after slaughter. The total mRNA from muscle, IMA, and subcutaneous adipose and omental adipose tissues were isolated and sequenced. The reads that passed quality control were mapped onto the bovine reference genome (build bosTau6), and differentially expressed genes across tissues were identified. The KEGG pathway enrichment tests revealed the opposite direction of metabolic regulation between muscle and IMA. Metabolic gene network analysis clearly indicated that oxidative metabolism was upregulated in muscle and downregulated in IMA. Interestingly, pathways for regulating cell adhesion, structure, and integrity and chemokine signaling pathway were upregulated in IMA and downregulated in muscle. It is thus inferred that IMA may play an important role in the regulation of development and structure of the LD tissues and muscle/adipose communication.

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          Count-based differential expression analysis of RNA sequencing data using R and Bioconductor

          , , … (2013)
          RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in many areas of biology, including studies into gene regulation, development and disease. Of particular interest is the discovery of differentially expressed genes across different conditions (e.g., tissues, perturbations), while optionally adjusting for other systematic factors that affect the data collection process. There are a number of subtle yet critical aspects of these analyses, such as read counting, appropriate treatment of biological variability, quality control checks and appropriate setup of statistical modeling. Several variations have been presented in the literature, and there is a need for guidance on current best practices. This protocol presents a "state-of-the-art" computational and statistical RNA-seq differential expression analysis workflow largely based on the free open-source R language and Bioconductor software and in particular, two widely-used tools DESeq and edgeR. Hands-on time for typical small experiments (e.g., 4-10 samples) can be <1 hour, with computation time <1 day using a standard desktop PC.
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            The functional landscape of mouse gene expression

            Wen-Wen Zhang, Quaid Morris, RICHARD CHANG … (2004)
            Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.
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              Depot-specific differences in adipogenic progenitor abundance and proliferative response to high-fat diet.

              Aaron Joe, Fabio Rossi, A. Wayne Vogl … (2009)
              White adipose tissue (fat) is the primary organ for energy storage and its regulation has serious implications on human health. Excess fat tissue causes significant morbidity, and adipose tissue dysfunction caused by excessive adipocyte hypertrophy has been proposed to play a significant role in the pathogenesis of metabolic disease. Studies in both humans and animal models show that metabolic dysfunction is more closely associated with visceral than subcutaneous fat accumulation. Here, we show that in mice fed a high-fat diet, visceral fat (VAT) grows mostly by hypertrophy and subcutaneous fat (SAT) by hyperplasia, providing a rationale for the different effects of specific adipose depots on metabolic health. To address whether depot expansion is controlled at the level of stem/progenitor cells, we developed a strategy to prospectively identify adipogenic progenitors (APs) from both depots. Clonogenic assays and in vivo bromodeoxyuridine (BrdU) studies show that APs are eightfold more abundant in SAT than VAT, and that AP proliferation is significantly increased in SAT but not VAT in response to high-fat diet. Our results suggest that depot-specific differences in AP abundance and proliferation underlie whether a fat depot expands by hypertrophy or hyperplasia, and thus may have important implications on the development of metabolic disease. In addition, we provide the first evidence that dietary inputs can modulate the proliferation of adipogenic progenitors in adults.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Int J Genomics
                Journal ID (iso-abbrev): Int J Genomics
                Journal ID (publisher-id): IJG
                Title: International Journal of Genomics
                Publisher: Hindawi Publishing Corporation
                ISSN (Print): 2314-436X
                ISSN (Electronic): 2314-4378
                Publication date (Print): 2014
                Publication date (Electronic): 13 November 2014
                Volume: 2014
                Electronic Location Identifier: 679437
                Affiliations
                1Division of Animal Genomics and Bioinformatics, National Institute of Animal Science, Rural Development Administration, Suwon 441-706, Republic of Korea
                2Department of Animal Biosystem Sciences, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 305-764, Republic of Korea
                3Department of Animal Science, Kyungpook National University, Sangju 742-170, Republic of Korea
                Author notes
                *Seongwon Seo: swseo@ 123456cnu.kr

                Academic Editor: Graziano Pesole

                Author information
                http://orcid.org/0000-0002-4131-0545
                Article
                DOI: 10.1155/2014/679437
                PMC ID: 4247929
                PubMed ID: 25478565
                SO-VID: eb78573a-83ac-4e81-8203-6273917f7c64
                Copyright © Copyright © 2014 Hyun-Jeong Lee et al.
                License:

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                Date received : 21 July 2014
                Date revision received : 7 October 2014
                Date accepted : 30 October 2014
                Categories
                Subject: Research Article

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