Literature DB >> 19158363

High-resolution DNA-binding specificity analysis of yeast transcription factors.

Cong Zhu1, Kelsey J R P Byers, Rachel Patton McCord, Zhenwei Shi, Michael F Berger, Daniel E Newburger, Katrina Saulrieta, Zachary Smith, Mita V Shah, Mathangi Radhakrishnan, Anthony A Philippakis, Yanhui Hu, Federico De Masi, Marcin Pacek, Andreas Rolfs, Tal Murthy, Joshua Labaer, Martha L Bulyk.   

Abstract

Transcription factors (TFs) regulate the expression of genes through sequence-specific interactions with DNA-binding sites. However, despite recent progress in identifying in vivo TF binding sites by microarray readout of chromatin immunoprecipitation (ChIP-chip), nearly half of all known yeast TFs are of unknown DNA-binding specificities, and many additional predicted TFs remain uncharacterized. To address these gaps in our knowledge of yeast TFs and their cis regulatory sequences, we have determined high-resolution binding profiles for 89 known and predicted yeast TFs, over more than 2.3 million gapped and ungapped 8-bp sequences ("k-mers"). We report 50 new or significantly different direct DNA-binding site motifs for yeast DNA-binding proteins and motifs for eight proteins for which only a consensus sequence was previously known; in total, this corresponds to over a 50% increase in the number of yeast DNA-binding proteins with experimentally determined DNA-binding specificities. Among other novel regulators, we discovered proteins that bind the PAC (Polymerase A and C) motif (GATGAG) and regulate ribosomal RNA (rRNA) transcription and processing, core cellular processes that are constituent to ribosome biogenesis. In contrast to earlier data types, these comprehensive k-mer binding data permit us to consider the regulatory potential of genomic sequence at the individual word level. These k-mer data allowed us to reannotate in vivo TF binding targets as direct or indirect and to examine TFs' potential effects on gene expression in approximately 1,700 environmental and cellular conditions. These approaches could be adapted to identify TFs and cis regulatory elements in higher eukaryotes.

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Year:  2009        PMID: 19158363      PMCID: PMC2665775          DOI: 10.1101/gr.090233.108

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  57 in total

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3.  Genomic binding sites of the yeast cell-cycle transcription factors SBF and MBF.

Authors:  V R Iyer; C E Horak; C S Scafe; D Botstein; M Snyder; P O Brown
Journal:  Nature       Date:  2001-01-25       Impact factor: 49.962

4.  Functional discovery via a compendium of expression profiles.

Authors:  T R Hughes; M J Marton; A R Jones; C J Roberts; R Stoughton; C D Armour; H A Bennett; E Coffey; H Dai; Y D He; M J Kidd; A M King; M R Meyer; D Slade; P Y Lum; S B Stepaniants; D D Shoemaker; D Gachotte; K Chakraburtty; J Simon; M Bard; S H Friend
Journal:  Cell       Date:  2000-07-07       Impact factor: 41.582

5.  Exploring the DNA-binding specificities of zinc fingers with DNA microarrays.

Authors:  M L Bulyk; X Huang; Y Choo; G M Church
Journal:  Proc Natl Acad Sci U S A       Date:  2001-06-12       Impact factor: 11.205

6.  Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

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8.  Genomic expression programs in the response of yeast cells to environmental changes.

Authors:  A P Gasch; P T Spellman; C M Kao; O Carmel-Harel; M B Eisen; G Storz; D Botstein; P O Brown
Journal:  Mol Biol Cell       Date:  2000-12       Impact factor: 4.138

9.  A Rsc3/Rsc30 zinc cluster dimer reveals novel roles for the chromatin remodeler RSC in gene expression and cell cycle control.

Authors:  M L Angus-Hill; A Schlichter; D Roberts; H Erdjument-Bromage; P Tempst; B R Cairns
Journal:  Mol Cell       Date:  2001-04       Impact factor: 17.970

10.  Remodeling of yeast genome expression in response to environmental changes.

Authors:  H C Causton; B Ren; S S Koh; C T Harbison; E Kanin; E G Jennings; T I Lee; H L True; E S Lander; R A Young
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  231 in total

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2.  Construction of regulatory networks using expression time-series data of a genotyped population.

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Authors:  Angela Taddei; Heiko Schober; Susan M Gasser
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Review 7.  Systematic characterization of protein-DNA interactions.

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Journal:  Cell Mol Life Sci       Date:  2011-01-05       Impact factor: 9.261

Review 8.  Determining the specificity of protein-DNA interactions.

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9.  Toward single-molecule optical mapping of the epigenome.

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10.  Msn2 coordinates a stoichiometric gene expression program.

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Journal:  Curr Biol       Date:  2013-11-07       Impact factor: 10.834

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