TY - JOUR T1 - Modeling Co-Expression across Species for Complex Traits: Insights to the Difference of Human and Mouse Embryonic Stem Cells A1 - Cai, Jun A1 - Xie, Dan A1 - Fan, Zhewen A1 - Chipperfield, Hiram A1 - Marden, John A1 - Wong, Wing H. A1 - Zhong, Sheng Y1 - 2010/03/12 N2 - Author Summary A major goal in biology is to understand the evolution of complex traits, such as the development of multicellular body plans. To a certain extent, complex traits are governed by regulated gene expression. The comparison expression data between species requires extra considerations than sequence comparison, because gene expression is not static and the level of expression is influenced by external conditions. Considering that co-expression patterns are often comparable across species, we developed a statistical model for cross-species clustering analysis. The model allows each species to create its own clusters of the genes but also encourages the species to borrow strength from each others' clusters of orthologous genes. The result is a pairing of clusters, one from each species, where the paired clusters share many but not necessarily all orthologous genes. The model-based approach not only reduces subjective influence but also enables effective use of evolutionary dependence. Applying this model to analyze human and mouse embryonic stem (ES) cell data, we identified the transcription factors and the signaling proteins that are specifically expressed in either human or mouse ES cells. These results suggest that the pluripotent cell identity can be established and maintained through more than one gene regulatory network. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 6 IS - 3 UR - https://doi.org/10.1371/journal.pcbi.1000707 SP - e1000707 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1000707 ER -