Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo
Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene exp...
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| Autor*in: |
Fakhouri, Walid D [verfasserIn] Ay, Ahmet [verfasserIn] Sayal, Rupinder [verfasserIn] Dresch, Jacqueline [verfasserIn] Dayringer, Evan [verfasserIn] Arnosti, David N [verfasserIn] |
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E-Artikel |
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Englisch |
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2010 |
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| Anmerkung: |
© EMBO and Macmillan Publishers Limited 2010 |
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| Übergeordnetes Werk: |
Enthalten in: Molecular Systems Biology - Nature Publishing Group UK, 2023, 6(2010), 1 vom: 19. Jan. |
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| Übergeordnetes Werk: |
volume:6 ; year:2010 ; number:1 ; day:19 ; month:01 |
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| DOI / URN: |
10.1038/msb.2009.97 |
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SPR058179747 |
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| 245 | 1 | 0 | |a Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo |
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| 520 | |a Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. | ||
| 520 | |a Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. | ||
| 520 | |a Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. | ||
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| 700 | 1 | |a Arnosti, David N |e verfasserin |4 aut | |
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10.1038/msb.2009.97 doi (DE-627)SPR058179747 (SPR)msb.2009.97-e DE-627 ger DE-627 rakwb eng Fakhouri, Walid D verfasserin aut Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © EMBO and Macmillan Publishers Limited 2010 Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. enhancer (dpeaa)DE-He213 modeling (dpeaa)DE-He213 repression (dpeaa)DE-He213 transcription (dpeaa)DE-He213 Ay, Ahmet verfasserin aut Sayal, Rupinder verfasserin aut Dresch, Jacqueline verfasserin aut Dayringer, Evan verfasserin aut Arnosti, David N verfasserin aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 6(2010), 1 vom: 19. Jan. (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:6 year:2010 number:1 day:19 month:01 https://dx.doi.org/10.1038/msb.2009.97 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 6 2010 1 19 01 |
| spelling |
10.1038/msb.2009.97 doi (DE-627)SPR058179747 (SPR)msb.2009.97-e DE-627 ger DE-627 rakwb eng Fakhouri, Walid D verfasserin aut Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © EMBO and Macmillan Publishers Limited 2010 Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. enhancer (dpeaa)DE-He213 modeling (dpeaa)DE-He213 repression (dpeaa)DE-He213 transcription (dpeaa)DE-He213 Ay, Ahmet verfasserin aut Sayal, Rupinder verfasserin aut Dresch, Jacqueline verfasserin aut Dayringer, Evan verfasserin aut Arnosti, David N verfasserin aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 6(2010), 1 vom: 19. Jan. (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:6 year:2010 number:1 day:19 month:01 https://dx.doi.org/10.1038/msb.2009.97 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 6 2010 1 19 01 |
| allfields_unstemmed |
10.1038/msb.2009.97 doi (DE-627)SPR058179747 (SPR)msb.2009.97-e DE-627 ger DE-627 rakwb eng Fakhouri, Walid D verfasserin aut Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © EMBO and Macmillan Publishers Limited 2010 Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. enhancer (dpeaa)DE-He213 modeling (dpeaa)DE-He213 repression (dpeaa)DE-He213 transcription (dpeaa)DE-He213 Ay, Ahmet verfasserin aut Sayal, Rupinder verfasserin aut Dresch, Jacqueline verfasserin aut Dayringer, Evan verfasserin aut Arnosti, David N verfasserin aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 6(2010), 1 vom: 19. Jan. (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:6 year:2010 number:1 day:19 month:01 https://dx.doi.org/10.1038/msb.2009.97 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 6 2010 1 19 01 |
| allfieldsGer |
10.1038/msb.2009.97 doi (DE-627)SPR058179747 (SPR)msb.2009.97-e DE-627 ger DE-627 rakwb eng Fakhouri, Walid D verfasserin aut Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © EMBO and Macmillan Publishers Limited 2010 Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. enhancer (dpeaa)DE-He213 modeling (dpeaa)DE-He213 repression (dpeaa)DE-He213 transcription (dpeaa)DE-He213 Ay, Ahmet verfasserin aut Sayal, Rupinder verfasserin aut Dresch, Jacqueline verfasserin aut Dayringer, Evan verfasserin aut Arnosti, David N verfasserin aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 6(2010), 1 vom: 19. Jan. (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:6 year:2010 number:1 day:19 month:01 https://dx.doi.org/10.1038/msb.2009.97 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 6 2010 1 19 01 |
| allfieldsSound |
10.1038/msb.2009.97 doi (DE-627)SPR058179747 (SPR)msb.2009.97-e DE-627 ger DE-627 rakwb eng Fakhouri, Walid D verfasserin aut Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © EMBO and Macmillan Publishers Limited 2010 Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. enhancer (dpeaa)DE-He213 modeling (dpeaa)DE-He213 repression (dpeaa)DE-He213 transcription (dpeaa)DE-He213 Ay, Ahmet verfasserin aut Sayal, Rupinder verfasserin aut Dresch, Jacqueline verfasserin aut Dayringer, Evan verfasserin aut Arnosti, David N verfasserin aut Enthalten in Molecular Systems Biology Nature Publishing Group UK, 2023 6(2010), 1 vom: 19. Jan. (DE-627)490536905 (DE-600)2193510-5 1744-4292 nnns volume:6 year:2010 number:1 day:19 month:01 https://dx.doi.org/10.1038/msb.2009.97 X:SPRINGER Resolving-System kostenfrei Volltext SYSFLAG_0 GBV_SPRINGER GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_72 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_636 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2118 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4116 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4155 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4311 GBV_ILN_4313 GBV_ILN_4314 GBV_ILN_4315 GBV_ILN_4317 GBV_ILN_4318 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4598 GBV_ILN_4700 AR 6 2010 1 19 01 |
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Enthalten in Molecular Systems Biology 6(2010), 1 vom: 19. Jan. volume:6 year:2010 number:1 day:19 month:01 |
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Enthalten in Molecular Systems Biology 6(2010), 1 vom: 19. Jan. volume:6 year:2010 number:1 day:19 month:01 |
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Fakhouri, Walid D @@aut@@ Ay, Ahmet @@aut@@ Sayal, Rupinder @@aut@@ Dresch, Jacqueline @@aut@@ Dayringer, Evan @@aut@@ Arnosti, David N @@aut@@ |
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SPR058179747 |
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englisch |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000naa a22002652 4500</leader><controlfield tag="001">SPR058179747</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20241030065022.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">241030s2010 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1038/msb.2009.97</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)SPR058179747</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(SPR)msb.2009.97-e</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Fakhouri, Walid D</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© EMBO and Macmillan Publishers Limited 2010</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">enhancer</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modeling</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">repression</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">transcription</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ay, Ahmet</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Sayal, Rupinder</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dresch, Jacqueline</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dayringer, Evan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Arnosti, David N</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Molecular Systems Biology</subfield><subfield code="d">Nature Publishing Group UK, 2023</subfield><subfield code="g">6(2010), 1 vom: 19. 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Fakhouri, Walid D |
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Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo enhancer (dpeaa)DE-He213 modeling (dpeaa)DE-He213 repression (dpeaa)DE-He213 transcription (dpeaa)DE-He213 |
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deciphering a transcriptional regulatory code: modeling short‐range repression in the drosophila embryo |
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Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo |
| abstract |
Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. © EMBO and Macmillan Publishers Limited 2010 |
| abstractGer |
Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. © EMBO and Macmillan Publishers Limited 2010 |
| abstract_unstemmed |
Abstract Systems biology seeks a genomic‐level interpretation of transcriptional regulatory information represented by patterns of protein‐binding sites. Obtaining this information without direct experimentation is challenging; minor alterations in binding sites can have profound effects on gene expression, and underlie important aspects of disease and evolution. Quantitative modeling offers an alternative path to develop a global understanding of the transcriptional regulatory code. Recent studies have focused on endogenous regulatory sequences; however, distinct enhancers differ in many features, making it difficult to generalize to other cis‐regulatory elements. We applied a systematic approach to simpler elements and present here the first quantitative analysis of short‐range transcriptional repressors, which have central functions in metazoan development. Our fractional occupancy‐based modeling uncovered unexpected features of these proteins’ activity that allow accurate predictions of regulation by the Giant, Knirps, Krüppel, and Snail repressors, including modeling of an endogenous enhancer. This study provides essential elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Synopsis Transcriptional regulatory information, represented by patterns of protein‐binding sites on DNA, comprises an important portion of genetic coding. Despite the abundance of genomic sequences now available, identifying and characterizing this information remain a major challenge. Minor changes in protein‐binding sites can have profound effects on gene expression, and such changes have been shown to underlie important aspects of disease and evolution. Thus, an important aim in contemporary systems biology is to develop a global understanding of the transcriptional regulatory code, allowing prediction of gene output based on DNA sequence information. Recent studies have focused on endogenous transcriptional regulatory sequences (Janssens et al, 2006; Zinzen et al, 2006; Segal et al, 2008); however, distinct enhancers differ in many features, including transcription factor activity, spacing, and cooperativity, making it difficult to learn the effects of individual features and generalize them to other cis‐regulatory elements. We have pursued a bottom up approach to understand the mechanistic processing of regulatory elements by the transcriptional machinery, using a well‐defined and characterized set of repressors and activators in Drosophila blastoderm embryos. The study focuses on the Giant, Krüppel, Knirps, and Snail proteins, which have been characterized as short‐range repressors, able to act locally to interfere with activator function (quenching) (Gray et al, 1994; Arnosti et al, 1996a). Such repressors have central functions in development. The aim our study was to enable ab initio predictions of enhancer function, given defined quantities of regulatory proteins and the sequence of the enhancer (Figure 1). We have generated a large quantitative data set using fluorescent confocal laser scanning microscopy to determine the inputs (Giant, Krüppel, and Knirps protein levels) and outputs (lacZ mRNA levels) of the regulatory elements introduced into Drosophila by transgenesis. We analyzed the effect of altering specific features of a set of related gene modules, designed to uncover critical aspects of repression, including quenching distance, cooperativity, and overall factor potency. We generated specific descriptions for each regulatory element using fractional occupancy‐based modeling and identified quantitative values for parameters affecting transcriptional regulation in vivo, and these parameters were used to build and test the model. Through this process, we uncovered earlier unknown features that allow correct predictions of regulation by short‐range repressors, including a non‐monotonic distance function for quenching, which implicates possible phasing effects, a modest contribution for repressor–repressor cooperativity, and similarity in repression of disparate activators. By applying these parameters to a model of the endogenous rhomboid enhancer, we uncovered novel insights into the architecture of this enhancer (Figure 8). Our study provides essential quantitative elements of a transcriptional regulatory code that will allow extensive analysis of genomic information in Drosophila melanogaster and related organisms. Extension of these predictive models should facilitate the development of more sophisticated computational algorithms for the identification and functional characterization of novel regulatory elements. The development of such quantitative modeling tools will change our understanding of the genome from essentially a parts list to a dynamically regulated system, and will greatly facilitate studies in disease, population genetics, and evolutionary biology. Abstract A well‐defined set of transcriptional regulatory modules was created and analyzed in the Drosophila embryo.Fractional occupancy‐based models were developed to explain the interaction of short range transcriptional repressors with endogenous activators by using quantitative data from these modules.Our fractional occupancy‐based modeling uncovered specific quantitative features of short‐range repressors; a complex nonlinear quenching relationship, similar quenching efficiencies for different activators, and modest levels of cooperativityThe extension of the study to endogenous enhancers highlighted several features of enhancer architecture design in Drosophila embryos. © EMBO and Macmillan Publishers Limited 2010 |
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Deciphering a transcriptional regulatory code: modeling short‐range repression in the Drosophila embryo |
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Ay, Ahmet Sayal, Rupinder Dresch, Jacqueline Dayringer, Evan Arnosti, David N |
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10.1038/msb.2009.97 |
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2024-10-30T14:10:59.905Z |
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| score |
7.402364 |