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      Evolution After Whole-Genome Duplication: A Network Perspective

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          Abstract

          Gene duplication plays an important role in the evolution of genomes and interactomes. Elucidating how evolution after gene duplication interplays at the sequence and network level is of great interest. In this work, we analyze a data set of gene pairs that arose through whole-genome duplication (WGD) in yeast. All these pairs have the same duplication time, making them ideal for evolutionary investigation. We investigated the interplay between evolution after WGD at the sequence and network levels and correlated these two levels of divergence with gene expression and fitness data. We find that molecular interactions involving WGD genes evolve at rates that are three orders of magnitude slower than the rates of evolution of the corresponding sequences. Furthermore, we find that divergence of WGD pairs correlates strongly with gene expression and fitness data. Because of the role of gene duplication in determining redundancy in biological systems and particularly at the network level, we investigated the role of interaction networks in elucidating the evolutionary fate of duplicated genes. We find that gene neighborhoods in interaction networks provide a mechanism for inferring these fates, and we developed an algorithm for achieving this task. Further epistasis analysis of WGD pairs categorized by their inferred evolutionary fates demonstrated the utility of these techniques. Finally, we find that WGD pairs and other pairs of paralogous genes of small-scale duplication origin share similar properties, giving good support for generalizing our results from WGD pairs to evolution after gene duplication in general.

          Most cited references19

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          Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization.

          We sought to create a comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle. To this end, we used DNA microarrays and samples from yeast cultures synchronized by three independent methods: alpha factor arrest, elutriation, and arrest of a cdc15 temperature-sensitive mutant. Using periodicity and correlation algorithms, we identified 800 genes that meet an objective minimum criterion for cell cycle regulation. In separate experiments, designed to examine the effects of inducing either the G1 cyclin Cln3p or the B-type cyclin Clb2p, we found that the mRNA levels of more than half of these 800 genes respond to one or both of these cyclins. Furthermore, we analyzed our set of cell cycle-regulated genes for known and new promoter elements and show that several known elements (or variations thereof) contain information predictive of cell cycle regulation. A full description and complete data sets are available at http://cellcycle-www.stanford.edu
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            DIP: the database of interacting proteins.

            The Database of Interacting Proteins (DIP; http://dip.doe-mbi.ucla.edu) is a database that documents experimentally determined protein-protein interactions. This database is intended to provide the scientific community with a comprehensive and integrated tool for browsing and efficiently extracting information about protein interactions and interaction networks in biological processes. Beyond cataloging details of protein-protein interactions, the DIP is useful for understanding protein function and protein-protein relationships, studying the properties of networks of interacting proteins, benchmarking predictions of protein-protein interactions, and studying the evolution of protein-protein interactions.
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              Rapid subfunctionalization accompanied by prolonged and substantial neofunctionalization in duplicate gene evolution.

              Gene duplication is the primary source of new genes. Duplicate genes that are stably preserved in genomes usually have divergent functions. The general rules governing the functional divergence, however, are not well understood and are controversial. The neofunctionalization (NF) hypothesis asserts that after duplication one daughter gene retains the ancestral function while the other acquires new functions. In contrast, the subfunctionalization (SF) hypothesis argues that duplicate genes experience degenerate mutations that reduce their joint levels and patterns of activity to that of the single ancestral gene. We here show that neither NF nor SF alone adequately explains the genome-wide patterns of yeast protein interaction and human gene expression for duplicate genes. Instead, our analysis reveals rapid SF, accompanied by prolonged and substantial NF in a large proportion of duplicate genes, suggesting a new model termed subneofunctionalization (SNF). Our results demonstrate that enormous numbers of new functions have originated via gene duplication.
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                Author and article information

                Journal
                G3 (Bethesda)
                Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                1 November 2013
                November 2013
                : 3
                : 11
                : 2049-2057
                Affiliations
                [* ]Department of Computer Science, Rice University, Houston, Texas 77005
                []Department of Ecology and Evolutionary Biology, Rice University, Houston, Texas 77005
                Author notes
                [1 ]Corresponding author: Department of Computer Science, Rice University, Houston, TX 77251. E-mail: nakhleh@ 123456rice.edu
                Article
                GGG_008458
                10.1534/g3.113.008458
                3815064
                24048644
                aeb92090-990f-4e6f-acce-fdb069f5a62e
                Copyright © 2013 Zhu et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 07 September 2013
                : 10 September 2013
                Page count
                Pages: 9
                Categories
                6th Annual RECOMB/ISCB Conference on Regulatory & Systems Genomics
                Custom metadata
                v1

                Genetics
                whole-genome duplication,protein networks,yeast,duplication rate
                Genetics
                whole-genome duplication, protein networks, yeast, duplication rate

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