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      An incoherent feedforward loop facilitates adaptive tuning of gene expression

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          We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression.

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          Most cited references 34

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          Transcriptional regulatory networks in Saccharomyces cerevisiae.

           T Lee,  Ziv Bar-Joseph (2002)
          We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.
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            Network motifs in the transcriptional regulation network of Escherichia coli.

            Little is known about the design principles of transcriptional regulation networks that control gene expression in cells. Recent advances in data collection and analysis, however, are generating unprecedented amounts of information about gene regulation networks. To understand these complex wiring diagrams, we sought to break down such networks into basic building blocks. We generalize the notion of motifs, widely used for sequence analysis, to the level of networks. We define 'network motifs' as patterns of interconnections that recur in many different parts of a network at frequencies much higher than those found in randomized networks. We applied new algorithms for systematically detecting network motifs to one of the best-characterized regulation networks, that of direct transcriptional interactions in Escherichia coli. We find that much of the network is composed of repeated appearances of three highly significant motifs. Each network motif has a specific function in determining gene expression, such as generating temporal expression programs and governing the responses to fluctuating external signals. The motif structure also allows an easily interpretable view of the entire known transcriptional network of the organism. This approach may help define the basic computational elements of other biological networks.
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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.

                Author and article information

                Role: Reviewing Editor
                eLife Sciences Publications, Ltd
                05 April 2018
                : 7
                [1 ]deptDepartment of Biology, Center for Genomics and Systems Biology New York University New YorkUnited States
                [2 ]Memorial Sloan Kettering Cancer Center New YorkUnited States
                [3 ]deptBanting and Best Department of Medical Research, Donnelly Centre University of Toronto TorontoCanada
                Weizmann Institute of Science Israel
                Weizmann Institute of Science Israel
                © 2018, Hong et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: MCB1244219
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: R01GM107466
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Research Article
                Genomics and Evolutionary Biology
                Custom metadata
                The architecture of a gene regulatory network determines the effect of evolutionary changes in transcription factor binding.

                Life sciences

                transcription factors, experimental evolution, gene expression, s. cerevisiae


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