DocumentCode
3227426
Title
Co-expression and evolutionary constraint on protein complexes
Author
Pang, Kaifang ; Liang, Guanqun ; Siror, Joseph ; Sheng, Huanye
Author_Institution
Dept. of Comput. Sci. & Eng., Shanghai Jiao Tong Univ., Shanghai, China
fYear
2010
fDate
23-26 Sept. 2010
Firstpage
1159
Lastpage
1163
Abstract
Protein complexes play a critical role in many cellular processes, but the extent to which they need co-expression among their subunits is still unclear. Intuitively, functional modularity and co-expression may be important factors that contribute to evolutionary constraint on protein complexes; however, their exact contributions are not clear. Here, we collected two high confidence yeast protein complex datasets and ten gene expression datasets. Then, we constructed ten gene co-expression networks and proposed a complex co-expressed density (CCD) measure, which is defined as the percentage of interactions within a complex that show significant co-expression. As a result, we found that about sixty percent of protein complexes in the MIPS dataset and about fifty percent of protein complexes in the CYC2008 dataset tend to be significantly co-expressed. Subsequently, we found that co-expression of a protein complex does not depend on its size. Furthermore, we found that co-expression is an important constraint that not only keeps proteins within complexes evolving at lower rates but also keeps protein pairs within complexes evolving at more similar rates. On the other hand, we found that functional modularity without co-expression does not have such a property. In summary, our study gave a clearer relationship between protein complexes and co-expression, and underscored co-expression as an important constraint on protein complex evolution.
Keywords
biology; evolution (biological); proteins; cellular process; coexpressed density measure; evolutionary constraint; functional modularity; gene coexpression networks; protein complex; Bioinformatics; Genomics; Manuals;
fLanguage
English
Publisher
ieee
Conference_Titel
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location
Changsha
Print_ISBN
978-1-4244-6437-1
Type
conf
DOI
10.1109/BICTA.2010.5645088
Filename
5645088
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