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      Gene coexpression networks reveal key drivers of phenotypic divergence in porcine muscle

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          Abstract

          Background

          Domestication of the wild pig has led to obese and lean phenotype breeds, and evolutionary genome research has sought to identify the regulatory mechanisms underlying this phenotypic diversity. However, revealing the molecular mechanisms underlying muscle phenotype variation based on differentially expressed genes has proved to be difficult. To characterize the mechanisms regulating muscle phenotype variation under artificial selection, we aimed to provide an integrated view of genome organization by weighted gene coexpression network analysis.

          Results

          Our analysis was based on 20 publicly available next-generation sequencing datasets of lean and obese pig muscle generated from 10 developmental stages. The evolution of the constructed coexpression modules was examined using the genome resequencing data of 37 domestic pigs and 11 wild boars. Our results showed the regulation of muscle development might be more complex than had been previously acknowledged, and is regulated by the coordinated action of muscle, nerve and immunity related genes. Breed-specific modules that regulated muscle phenotype divergence were identified, and hundreds of hub genes with major roles in muscle development were determined to be responsible for key functional distinctions between breeds. Our evolutionary analysis showed that the role of changes in the coding sequence under positive selection in muscle phenotype divergence was minor.

          Conclusions

          Muscle phenotype divergence was found to be regulated by the divergence of coexpression network modules under artificial selection, and not by changes in the coding sequence of genes. Our results present multiple lines of evidence suggesting links between modules and muscle phenotypes, and provide insights into the molecular bases of genome organization in muscle development and phenotype variation.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12864-015-1238-5) contains supplementary material, which is available to authorized users.

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          Most cited references81

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          Hierarchical organization of modularity in metabolic networks

          Spatially or chemically isolated functional modules composed of several cellular components and carrying discrete functions are considered fundamental building blocks of cellular organization, but their presence in highly integrated biochemical networks lacks quantitative support. Here we show that the metabolic networks of 43 distinct organisms are organized into many small, highly connected topologic modules that combine in a hierarchical manner into larger, less cohesive units, their number and degree of clustering following a power law. Within Escherichia coli the uncovered hierarchical modularity closely overlaps with known metabolic functions. The identified network architecture may be generic to system-level cellular organization.
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            The evolution of gene expression levels in mammalian organs.

            Changes in gene expression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of gene expression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of gene expression evolution varies among organs, lineages and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although gene expression evolution in mammals was strongly shaped by purifying selection, we identify numerous potentially selectively driven expression switches, which occurred at different rates across lineages and tissues and which probably contributed to the specific organ biology of various mammals.
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              Functional organization of the transcriptome in human brain.

              The enormous complexity of the human brain ultimately derives from a finite set of molecular instructions encoded in the human genome. These instructions can be directly studied by exploring the organization of the brain's transcriptome through systematic analysis of gene coexpression relationships. We analyzed gene coexpression relationships in microarray data generated from specific human brain regions and identified modules of coexpressed genes that correspond to neurons, oligodendrocytes, astrocytes and microglia. These modules provide an initial description of the transcriptional programs that distinguish the major cell classes of the human brain and indicate that cell type-specific information can be obtained from whole brain tissue without isolating homogeneous populations of cells. Other modules corresponded to additional cell types, organelles, synaptic function, gender differences and the subventricular neurogenic niche. We found that subventricular zone astrocytes, which are thought to function as neural stem cells in adults, have a distinct gene expression pattern relative to protoplasmic astrocytes. Our findings provide a new foundation for neurogenetic inquiries by revealing a robust and previously unrecognized organization to the human brain transcriptome.
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                Author and article information

                Contributors
                zhxicgz@gmail.com
                lzysdau@163.com
                liuqingxin@sdau.edu.cn
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central (London )
                1471-2164
                5 February 2015
                5 February 2015
                2015
                : 16
                : 1
                : 50
                Affiliations
                Laboratory of Developmental Genetics, Shandong Agricultural University, Tai’an, Shandong China
                Article
                1238
                10.1186/s12864-015-1238-5
                4328970
                25651817
                ee285413-e1c0-45c4-b350-284493268ca5
                © Zhao et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 26 September 2014
                : 12 January 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Genetics
                muscle,modules,weighted gene coexpression network analysis,phenotype variation,artificial selection

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