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      Translational compensation of gene copy number alterations by aneuploidy in Drosophila melanogaster

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      Nucleic Acids Research
      Oxford University Press

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          Abstract

          Chromosomal or segmental aneuploidy—the gain or loss of whole or partial chromosomes—is typically deleterious for organisms, a hallmark of cancers, and only occasionally adaptive. To understand the cellular and organismal consequences of aneuploidy, it is important to determine how altered gene doses impact gene expression. Previous studies show that, for some Drosophila cell lines but not others, the dose effect of segmental aneuploidy can be moderately compensated at the mRNA level – aneuploid gene expression is shifted towards wild-type levels. Here, by analyzing genome-wide translation efficiency estimated with ribosome footprint data from the aneuploid Drosophila S2 cell line, we report that the dose effect of aneuploidy can be further compensated at the translational level. Intriguingly, we find no comparable translational compensation in the aneuploid Kc167 cell line. Comparing the properties of aneuploid genes from the two cell lines suggests that selective constraint on gene expression, but neither sequence features nor functions, may partly explain why the two cell lines differ in translational compensation. Our results, together with previous observations that compensation at the mRNA level also varies among Drosophila cell lines and yeast strains, suggest that dosage compensation of aneuploidy is not general but contingent on genotypic and/or developmental context.

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          Most cited references27

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          GtRNAdb: a database of transfer RNA genes detected in genomic sequence

          Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb), currently including over 74 000 tRNA genes predicted from 740 species. The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. The database is publicly available at http://gtrnadb.ucsc.edu.
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            UNAFold: software for nucleic acid folding and hybridization.

            The UNAFold software package is an integrated collection of programs that simulate folding, hybridization, and melting pathways for one or two single-stranded nucleic acid sequences. The name is derived from "Unified Nucleic Acid Folding." Folding (secondary structure) prediction for single-stranded RNA or DNA combines free energy minimization, partition function calculations and stochastic sampling. For melting simulations, the package computes entire melting profiles, not just melting temperatures. UV absorbance at 260 nm, heat capacity change (C(p)), and mole fractions of different molecular species are computed as a function of temperature. The package installs and runs on all Unix and Linux platforms that we have looked at, including Mac OS X. Images of secondary structures, hybridizations, and dot plots may be computed using common formats. Similarly, a variety of melting profile plots is created when appropriate. These latter plots include experimental results if they are provided. The package is "command line" driven. Underlying compiled programs may be used individually, or in special combinations through the use of a variety of Perl scripts. Users are encouraged to create their own scripts to supplement what comes with the package. This evolving software is available for download at http://www.bioinfo.rpi.edu/applications/hybrid/download.php .
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              Aneuploidy confers quantitative proteome changes and phenotypic variation in budding yeast

              Aneuploidy, referring here to genome contents characterized by abnormal numbers of chromosomes, has been associated with developmental defects, cancer, and adaptive evolution in experimental organisms1–9. However, it remains unresolved how aneuploidy impacts gene expression and whether aneuploidy could directly bring phenotypic variation and improved fitness over that of euploid counterparts. In this work, we designed a novel scheme to generate, through random meiotic segregation, 38 stable and fully isogenic aneuploid yeast strains with distinct karyotypes and genome contents between 1N and 3N without involving any genetic selection. Through phenotypic profiling under various growth conditions or in the presence of a panel of chemotherapeutic or antifungal drugs, we found that aneuploid strains exhibited diverse growth phenotypes, and some aneuploid strains grew better than euploid control strains under conditions suboptimal for the latter. Using quantitative mass spectrometry-based proteomics, we show that the levels of protein expression largely scale with chromosome copy numbers, following the same trend observed for the transcriptome. These results provide strong evidence that aneuploidy directly impacts gene expression at both the transcriptome and proteome levels and can generate significant phenotypic variation that could bring about fitness gains under diverse conditions. Our findings suggest that the fitness ranking between euploid and aneuploid cells is context- and karyotype-dependent, providing the basis for the notion that aneuploidy can directly underlie phenotypic evolution and cellular adaptation.
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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
                07 April 2017
                13 February 2017
                13 February 2017
                : 45
                : 6
                : 2986-2993
                Affiliations
                Department of Biology, University of Rochester, Rochester, NY 14627, USA
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +1 585 276 2183; Fax: +1 585 275 2070; Email: zhangz.sci@ 123456gmail.com
                Article
                gkx106
                10.1093/nar/gkx106
                5389667
                28199687
                ed49e62c-5985-4382-9c3a-b2ed2182148d
                © The Author(s) 2017. 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 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
                : 06 February 2017
                : 31 January 2017
                : 27 September 2016
                Page count
                Pages: 8
                Categories
                Computational Biology

                Genetics
                Genetics

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