Functional annotation of novel lineage-specific genes using co-expression and promoter analysis
1 Department of Animal Sciences, University of Illinois at Urbana-Champaign, 210 Edward R Madigan Laboratory, 1201 W Gregory Dr, Urbana, IL 61801, USA
2 Institute for Genomic Biology, University of Illinois at Urbana-Champaign, 1206 West Gregory Drive, Room 1608, Urbana, IL 61801, USA
3 Current address: SEQUENOM, Inc, 3595 John Hopkins Court, San Diego, CA 92121, USA
Citation and License
BMC Genomics 2010, 11:161 doi:10.1186/1471-2164-11-161Published: 9 March 2010
The diversity of placental architectures within and among mammalian orders is believed to be the result of adaptive evolution. Although, the genetic basis for these differences is unknown, some may arise from rapidly diverging and lineage-specific genes. Previously, we identified 91 novel lineage-specific transcripts (LSTs) from a cow term-placenta cDNA library, which are excellent candidates for adaptive placental functions acquired by the ruminant lineage. The aim of the present study was to infer functions of previously uncharacterized lineage-specific genes (LSGs) using co-expression, promoter, pathway and network analysis.
Clusters of co-expressed genes preferentially expressed in liver, placenta and thymus were found using 49 previously uncharacterized LSTs as seeds. Over-represented composite transcription factor binding sites (TFBS) in promoters of clustered LSGs and known genes were then identified computationally. Functions were inferred for nine previously uncharacterized LSGs using co-expression analysis and pathway analysis tools. Our results predict that these LSGs may function in cell signaling, glycerophospholipid/fatty acid metabolism, protein trafficking, regulatory processes in the nucleus, and processes that initiate parturition and immune system development.
The placenta is a rich source of lineage-specific genes that function in the adaptive evolution of placental architecture and functions. We have shown that co-expression, promoter, and gene network analyses are useful methods to infer functions of LSGs with heretofore unknown functions. Our results indicate that many LSGs are involved in cellular recognition and developmental processes. Furthermore, they provide guidance for experimental approaches to validate the functions of LSGs and to study their evolution.