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      Evidences for increased expression variation of duplicate genes in budding yeast: from cis- to trans-regulation effects

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      1 , * , 1 , 2 , 1 , 2 , 3 , *
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          Duplicate genes tend to have a more variable expression program than singleton genes, which was thought to be an important way for the organism to respond and adapt to fluctuating environment. However, the underlying molecular mechanisms driving such expression variation remain largely unexplored. In this work, we first rigorously confirmed that duplicate genes indeed have higher gene expression variation than singleton genes in several aspects, i.e. responses to environmental perturbation, between-strain divergence, and expression noise. To investigate the underlying mechanism, we further analyzed a previously published expression dataset of yeast segregants produced from genetic crosses. We dissected the observed expression divergence between segregant strains into cis- and trans-variabilities, and demonstrated that trans-regulation effect can explain larger fraction of the expression variation than cis-regulation effect. This is true for both duplicate genes and singleton genes. In contrast, we found, between a pair of sister paralogs, cis-variability explains more of the expression divergence between the paralogs than trans-variability. We next investigated the presence of cis- and trans-features that are associated with elevated expression variations. For cis-acting regulation, duplicate genes have higher genetic diversity in their promoters and coding regions than singleton genes. For trans-acting regulation, duplicate and singleton genes are differentially regulated by chromatin regulators and transcription factors, and duplicate genes are more severely affected by the deletion of histone tails. These results showed that both cis-and trans-factors have great effect in causing the increased expression variation of duplicate genes, and explained the previously observed differences in transcription regulation between duplicate genes and singleton genes.

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          Most cited references44

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          Evolution by gene duplication: an update

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            Population genomics of domestic and wild yeasts

            Since the completion of the genome sequence of Saccharomyces cerevisiae in 19961,2, there has been an exponential increase in complete genome sequences accompanied by great advances in our understanding of genome evolution. Although little is known about the natural and life histories of yeasts in the wild, there are an increasing number of studies looking at ecological and geographic distributions3,4, population structure5-8, and sexual versus asexual reproduction9,10. Less well understood at the whole genome level are the evolutionary processes acting within populations and species leading to adaptation to different environments, phenotypic differences and reproductive isolation. Here we present one- to four-fold or more coverage of the genome sequences of over seventy isolates of the baker's yeast, S. cerevisiae, and its closest relative, S. paradoxus. We examine variation in gene content, SNPs, indels, copy numbers and transposable elements. We find that phenotypic variation broadly correlates with global genome-wide phylogenetic relationships. Interestingly, S. paradoxus populations are well delineated along geographic boundaries while the variation among worldwide S. cerevisiae isolates shows less differentiation and is comparable to a single S. paradoxus population. Rather than one or two domestication events leading to the extant baker's yeasts, the population structure of S. cerevisiae consists of a few well-defined geographically isolated lineages and many different mosaics of these lineages, supporting the idea that human influence provided the opportunity for cross-breeding and production of new combinations of pre-existing variation.
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              Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise.

              A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.
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                Author and article information

                Journal
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                February 2011
                February 2011
                8 October 2010
                8 October 2010
                : 39
                : 3
                : 837-847
                Affiliations
                1Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, 2Department of Molecular Genetics, University of Toronto, 1 King's College Circle, Toronto, ON M5S 1A8 and 3Banting and Best Department of Medical Research, University of Toronto, 112 College Street, Toronto, ON M5G 1L6, Canada
                Author notes
                *To whom correspondence should be addressed. Tel: (416) 946 0924; Fax: (416) 978 8287; Email: Zhaolei.Zhang@ 123456utoronto.ca
                Correspondence may also be addressed to Dong Dong. Email: dong.dong@ 123456utoronto.ca
                Article
                gkq874
                10.1093/nar/gkq874
                3035465
                20935054
                5c0b0cd9-9eed-4aa0-85b5-d53b7b9fdad4
                © The Author(s) 2010. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 May 2010
                : 30 August 2010
                : 16 September 2010
                Categories
                Computational Biology

                Genetics
                Genetics

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