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      Evolutionary Analysis of the B56 Gene Family of PP2A Regulatory Subunits

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          Abstract

          Protein phosphatase 2A (PP2A) is an abundant serine/threonine phosphatase that functions as a tumor suppressor in numerous cell-cell signaling pathways, including Wnt, myc, and ras. The B56 subunit of PP2A regulates its activity, and is encoded by five genes in humans. B56 proteins share a central core domain, but have divergent amino- and carboxy-termini, which are thought to provide isoform specificity. We performed phylogenetic analyses to better understand the evolution of the B56 gene family. We found that B56 was present as a single gene in eukaryotes prior to the divergence of animals, fungi, protists, and plants, and that B56 gene duplication prior to the divergence of protostomes and deuterostomes led to the origin of two B56 subfamilies, B56αβε and B56γδ. Further duplications led to three B56αβε genes and two B56γδ in vertebrates. Several nonvertebrate B56 gene names are based on distinct vertebrate isoform names, and would best be renamed. B56 subfamily genes lack significant divergence within primitive chordates, but each became distinct in complex vertebrates. Two vertebrate lineages have undergone B56 gene loss, Xenopus and Aves. In Xenopus, B56δ function may be compensated for by an alternatively spliced transcript, B56δ/γ, encoding a B56δ-like amino-terminal region and a B56γ core.

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          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            The amphioxus genome and the evolution of the chordate karyotype.

            Lancelets ('amphioxus') are the modern survivors of an ancient chordate lineage, with a fossil record dating back to the Cambrian period. Here we describe the structure and gene content of the highly polymorphic approximately 520-megabase genome of the Florida lancelet Branchiostoma floridae, and analyse it in the context of chordate evolution. Whole-genome comparisons illuminate the murky relationships among the three chordate groups (tunicates, lancelets and vertebrates), and allow not only reconstruction of the gene complement of the last common chordate ancestor but also partial reconstruction of its genomic organization, as well as a description of two genome-wide duplications and subsequent reorganizations in the vertebrate lineage. These genome-scale events shaped the vertebrate genome and provided additional genetic variation for exploitation during vertebrate evolution.
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              Estimating maximum likelihood phylogenies with PhyML.

              Our understanding of the origins, the functions and/or the structures of biological sequences strongly depends on our ability to decipher the mechanisms of molecular evolution. These complex processes can be described through the comparison of homologous sequences in a phylogenetic framework. Moreover, phylogenetic inference provides sound statistical tools to exhibit the main features of molecular evolution from the analysis of actual sequences. This chapter focuses on phylogenetic tree estimation under the maximum likelihood (ML) principle. Phylogenies inferred under this probabilistic criterion are usually reliable and important biological hypotheses can be tested through the comparison of different models. Estimating ML phylogenies is computationally demanding, and careful examination of the results is warranted. This chapter focuses on PhyML, a software that implements recent ML phylogenetic methods and algorithms. We illustrate the strengths and pitfalls of this program through the analysis of a real data set. PhyML v3.0 is available from (http://atgc_montpellier.fr/phyml/).
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                05 May 2015
                May 2015
                : 16
                : 5
                : 10134-10157
                Affiliations
                [1 ]Department of Biological Sciences, Sam Houston State University, Huntsville, TX 77341, USA; E-Mails: lms047@ 123456shsu.edu (L.M.S.); mxc017@ 123456shsu.edu (M.C.)
                [2 ]Department of Computer Science, Sam Houston State University, Huntsville, TX 77341, USA; E-Mail: hxc005@ 123456shsu.edu
                Author notes
                [* ]Author to whom correspondence should be addressed; E-Mail: jms120@ 123456shsu.edu ; Tel.: +1-936-294-1537; Fax: +1-936-294-3940.
                Article
                ijms-16-10134
                10.3390/ijms160510134
                4463637
                25950761
                5605a394-6de5-4089-9241-ef48ac27fae3
                © 2015 by the authors; licensee MDPI, Basel, Switzerland.

                This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 March 2015
                : 24 April 2015
                Categories
                Article

                Molecular biology
                protein phosphatase 2a,b56 regulatory subunit,molecular phylogeny
                Molecular biology
                protein phosphatase 2a, b56 regulatory subunit, molecular phylogeny

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