33
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Functional mapping of yeast genomes by saturated transposition

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Yeast is a powerful model for systems genetics. We present a versatile, time- and labor-efficient method to functionally explore the Saccharomyces cerevisiae genome using saturated transposon mutagenesis coupled to high-throughput sequencing. SAturated Transposon Analysis in Yeast (SATAY) allows one-step mapping of all genetic loci in which transposons can insert without disrupting essential functions. SATAY is particularly suited to discover loci important for growth under various conditions. SATAY (1) reveals positive and negative genetic interactions in single and multiple mutant strains, (2) can identify drug targets, (3) detects not only essential genes, but also essential protein domains, (4) generates both null and other informative alleles. In a SATAY screen for rapamycin-resistant mutants, we identify Pib2 (PhosphoInositide-Binding 2) as a master regulator of TORC1. We describe two antagonistic TORC1-activating and -inhibiting activities located on opposite ends of Pib2. Thus, SATAY allows to easily explore the yeast genome at unprecedented resolution and throughput.

          DOI: http://dx.doi.org/10.7554/eLife.23570.001

          eLife digest

          Genes are stretches of DNA that carry the instructions to build and maintain cells. Many studies in genetics involve inactivating one or more genes and observing the consequences. If the loss of a gene kills the cell, that gene is likely to be vital for life. If it does not, the gene may not be essential, or a similar gene may be able to take over its role.

          Baker’s yeast is a simple organism that shares many characteristics with human cells. Many yeast genes have a counterpart among human genes, and so studying baker’s yeast can reveal clues about our own genetics. Michel et al. report an adaptation for baker’s yeast of a technique called “Transposon sequencing”, which had been used in other single-celled organisms to study the effects of interrupting genes. Briefly, a virus-like piece of DNA, called a transposon, inserts randomly into the genetic material and switches off individual genes. The DNA is then sequenced to reveal every gene that can be disrupted without killing the cell, and remaining genes are inferred to be essential for life.

          The approach, named SATAY (which is short for “saturated transposon analysis in yeast”), uses this strategy to create millions of baker’s yeast cells, each with a different gene switched off. Because the number of cells generated this way vastly exceeds the number of genes, every gene will be switched off by several independent transposons. Therefore the technique allows all yeast genes to be inactivated several times in one single experiment. The cells can be grown in varying conditions during the experiment, revealing the genes needed for survival in different situations. Non-essential genes can also be inactivated beforehand to uncover if any genes might be compensating for their absence.

          In the future, this technique may be used to better understand human diseases, such as cancer, since many disease-causing genes in humans have counterparts in yeast.

          DOI: http://dx.doi.org/10.7554/eLife.23570.002

          Related collections

          Most cited references45

          • Record: found
          • Abstract: found
          • Article: not found

          The genetic landscape of a cell.

          A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            An ER-mitochondria tethering complex revealed by a synthetic biology screen.

            Communication between organelles is an important feature of all eukaryotic cells. To uncover components involved in mitochondria/endoplasmic reticulum (ER) junctions, we screened for mutants that could be complemented by a synthetic protein designed to artificially tether the two organelles. We identified the Mmm1/Mdm10/Mdm12/Mdm34 complex as a molecular tether between ER and mitochondria. The tethering complex was composed of proteins resident of both ER and mitochondria. With the use of genome-wide mapping of genetic interactions, we showed that the components of the tethering complex were functionally connected to phospholipid biosynthesis and calcium-signaling genes. In mutant cells, phospholipid biosynthesis was impaired. The tethering complex localized to discrete foci, suggesting that discrete sites of close apposition between ER and mitochondria facilitate interorganelle calcium and phospholipid exchange.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Tn-seq; high-throughput parallel sequencing for fitness and genetic interaction studies in microorganisms

              Biological pathways are structured in complex networks of interacting genes. Solving the architecture of such networks may provide valuable information, such as how microorganisms cause disease. Here we present a method (Tn-seq) for accurately determining quantitative genetic interactions on a genome-wide scale in microorganisms. Tn-seq is based on the assembly of a saturated Mariner transposon insertion library. After library selection, changes in frequency of each insertion mutant are determined by sequencing of the flanking regions en masse. These changes are used to calculate each mutant’s fitness. Fitness was determined for each gene of the gram-positive bacterium Streptococcus pneumoniae, a causative agent of pneumonia and meningitis. A genome-wide screen for genetic interactions identified both alleviating and aggravating interactions that could be further divided into seven distinct categories. Due to the wide activity of the Mariner transposon, Tn-seq has the potential to contribute to the exploration of complex pathways across many different species.
                Bookmark

                Author and article information

                Contributors
                Role: Reviewing editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                08 May 2017
                2017
                : 6
                : e23570
                Affiliations
                [1 ]deptInstitute of Biochemistry , ETH Zurich , Zurich, Switzerland
                [2 ]deptDepartment of Biology , University of Fribourg , Fribourg, Switzerland
                California Institute of Technology , United States
                California Institute of Technology , United States
                Author notes
                Author information
                http://orcid.org/0000-0002-2160-6824
                http://orcid.org/0000-0002-3754-3709
                http://orcid.org/0000-0002-6030-8555
                Article
                23570
                10.7554/eLife.23570
                5466422
                28481201
                bdf7400b-720b-4ca1-81f1-8e26f07eff36
                © 2017, Michel 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.

                History
                : 23 November 2016
                : 06 May 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000780, European Commission;
                Award ID: 337906-OrgaNet
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: PP00P3_13365
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000854, Human Frontier Science Program;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 310030_166474
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 31003A_153058
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 155823
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Tools and Resources
                Cell Biology
                Computational and Systems Biology
                Custom metadata
                2.5
                A new method maps functional and structural features of yeast genomes with unprecedented ease and throughput, which allows identification of protein domains at the genome scale.

                Life sciences
                transposon,yeast,genetic interaction,pharmacogenomics,protein domains,torc1,pib2,prp45,s. cerevisiae
                Life sciences
                transposon, yeast, genetic interaction, pharmacogenomics, protein domains, torc1, pib2, prp45, s. cerevisiae

                Comments

                Comment on this article