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BioMed Research International
Volume 2015, Article ID 269150, 6 pages
http://dx.doi.org/10.1155/2015/269150
Research Article

Genepleio Software for Effective Estimation of Gene Pleiotropy from Protein Sequences

1College of Mathematics & Information Science, Wenzhou University, Wenzhou, China
2State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai 200433, China
3College of Life & Environmental Science, Wenzhou University, Wenzhou 325035, China
4Shanghai Stem Cell Institute, Institutes of Medical Sciences, School of Medicine, Shanghai Jiao Tong University, Shanghai 200240, China
5Department of Genetics, Developmental and Cell Biology, Iowa State University, Ames, IA 50011, USA

Received 3 June 2014; Revised 15 July 2014; Accepted 26 July 2014

Academic Editor: Siyuan Zheng

Copyright © 2015 Wenhai Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Though pleiotropy, which refers to the phenomenon of a gene affecting multiple traits, has long played a central role in genetics, development, and evolution, estimation of the number of pleiotropy components remains a hard mission to accomplish. In this paper, we report a newly developed software package, Genepleio, to estimate the effective gene pleiotropy from phylogenetic analysis of protein sequences. Since this estimate can be interpreted as the minimum pleiotropy of a gene, it is used to play a role of reference for many empirical pleiotropy measures. This work would facilitate our understanding of how gene pleiotropy affects the pattern of genotype-phenotype map and the consequence of organismal evolution.