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      Evolutionary rates of mammalian telomere-stability genes correlate with karyotype features and female germline expression

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          Abstract

          Telomeres protect the ends of eukaryotic chromosomes and are essential for cell viability. In mammals, telomere dynamics vary with life history traits (e.g. body mass and longevity), suggesting differential selection depending on physiological characteristics. Telomeres, in analogy to centromeric regions, also represent candidate meiotic drivers and subtelomeric DNA evolves rapidly. We analyzed the evolutionary history of mammalian genes implicated in telomere homeostasis (TEL genes). We detected widespread positive selection and we tested two alternative hypotheses: (i) fast evolution is driven by changes in life history traits; (ii) a conflict with selfish DNA elements at the female meiosis represents the underlying selective pressure. By accounting for the phylogenetic relationships among mammalian species, we show that life history traits do not contribute to shape diversity of TEL genes. Conversely, the evolutionary rate of TEL genes correlates with expression levels during meiosis and episodes of positive selection across mammalian species are associated with karyotype features (number of chromosome arms). We thus propose a telomere drive hypothesis, whereby (sub)telomeres and telomere-binding proteins are engaged in an intra-genomic conflict similar to the one described for centromeres.

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          The delayed rise of present-day mammals.

          Did the end-Cretaceous mass extinction event, by eliminating non-avian dinosaurs and most of the existing fauna, trigger the evolutionary radiation of present-day mammals? Here we construct, date and analyse a species-level phylogeny of nearly all extant Mammalia to bring a new perspective to this question. Our analyses of how extant lineages accumulated through time show that net per-lineage diversification rates barely changed across the Cretaceous/Tertiary boundary. Instead, these rates spiked significantly with the origins of the currently recognized placental superorders and orders approximately 93 million years ago, before falling and remaining low until accelerating again throughout the Eocene and Oligocene epochs. Our results show that the phylogenetic 'fuses' leading to the explosion of extant placental orders are not only very much longer than suspected previously, but also challenge the hypothesis that the end-Cretaceous mass extinction event had a major, direct influence on the diversification of today's mammals.
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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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              Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites.

              The parsimony method of Suzuki and Gojobori (1999) and the maximum likelihood method developed from the work of Nielsen and Yang (1998) are two widely used methods for detecting positive selection in homologous protein coding sequences. Both methods consider an excess of nonsynonymous (replacement) substitutions as evidence for positive selection. Previously published simulation studies comparing the performance of the two methods show contradictory results. Here we conduct a more thorough simulation study to cover and extend the parameter space used in previous studies. We also reanalyzed an HLA data set that was previously proposed to cause problems when analyzed using the maximum likelihood method. Our new simulations and a reanalysis of the HLA data demonstrate that the maximum likelihood method has good power and accuracy in detecting positive selection over a wide range of parameter values. Previous studies reporting poor performance of the method appear to be due to numerical problems in the optimization algorithms and did not reflect the true performance of the method. The parsimony method has a very low rate of false positives but very little power for detecting positive selection or identifying positively selected sites.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                21 August 2018
                11 June 2018
                11 June 2018
                : 46
                : 14
                : 7153-7168
                Affiliations
                [1 ]Bioinformatics, Scientific Institute IRCCS E. MEDEA, 23842 Bosisio Parini, Italy
                [2 ]Department of Physiopathology and Transplantation, University of Milan, 20090 Milan, Italy
                [3 ]Don C. Gnocchi Foundation ONLUS, IRCCS, 20148 Milan, Italy
                Author notes
                To whom correspondence should be addressed. Tel: +39 031877826; Fax:+39 031877499; Email: chiara.pontremoli@ 123456bp.lnf.it
                Article
                gky494
                10.1093/nar/gky494
                6101625
                29893967
                2814c9b7-8dba-419a-a7e8-f02c89770d89
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@ 123456oup.com

                History
                : 22 May 2018
                : 17 May 2018
                : 30 January 2018
                Page count
                Pages: 16
                Categories
                Genome Integrity, Repair and Replication

                Genetics
                Genetics

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