This work examines how gene networks for bovine skeletal muscle can be inferred from expression data that spans a comprehensive number of experimental treatments in muscle and fat tissues. We use the example of myogenin (MYOG), a muscle-specific transcription factor essential for the development of skeletal muscle, and develop a network comprising 22 genes (or network nodes) that are connected by 33 significant associations. With this network, we simulate an evolutionary process based on digital organisms to address two fundamental questions: What global changes are required in the MYOG network to generate an extreme organism? And, what (re)configurations in the network can be expected that results in a minimal and maximal change in protein output after knocking out MYOG? Results revealed the existence of two distinct clusters of genes with coordinated expression within the network.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume , , 23.06, 2006
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