1
|
Prazak L, Iwasaki Y, Kim AR, Kozlov K, King K, Gergen JP. A dual role for DNA binding by Runt in activation and repression of sloppy paired transcription. Mol Biol Cell 2021; 32:ar26. [PMID: 34432496 PMCID: PMC8693977 DOI: 10.1091/mbc.e20-08-0509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
This work investigates the role of DNA binding by Runt in regulating the sloppy paired 1 (slp1) gene and in particular two distinct cis-regulatory elements that mediate regulation by Runt and other pair-rule transcription factors during Drosophila segmentation. We find that a DNA-binding-defective form of Runt is ineffective at repressing both the distal (DESE) and proximal (PESE) early stripe elements of slp1 and is also compromised for DESE-dependent activation. The function of Runt-binding sites in DESE is further investigated using site-specific transgenesis and quantitative imaging techniques. When DESE is tested as an autonomous enhancer, mutagenesis of the Runt sites results in a clear loss of Runt-dependent repression but has little to no effect on Runt-dependent activation. Notably, mutagenesis of these same sites in the context of a reporter gene construct that also contains the PESE enhancer results in a significant reduction of DESE-dependent activation as well as the loss of repression observed for the autonomous mutant DESE enhancer. These results provide strong evidence that DNA binding by Runt directly contributes to the regulatory interplay of interactions between these two enhancers in the early embryo.
Collapse
Affiliation(s)
- Lisa Prazak
- Department of Biology, Farmingdale State College, Farmingdale, NY 11735-1021.,Department of Biochemistry and Cell Biology and Center for Developmental Genetics.,Graduate Program in Molecular and Cellular Biology, Stony Brook University, Stony Brook, NY 11794-5215
| | - Yasuno Iwasaki
- Department of Biochemistry and Cell Biology and Center for Developmental Genetics
| | - Ah-Ram Kim
- Graduate Program in Biochemistry and Structural Biology, and
| | - Konstantin Kozlov
- Department of Applied Mathematics, St. Petersburg State Polytechnical University, St. Petersburg, Russia 195251
| | - Kevin King
- Department of Biochemistry and Cell Biology and Center for Developmental Genetics.,Graduate Program in Molecular and Cellular Biology, Stony Brook University, Stony Brook, NY 11794-5215
| | - J Peter Gergen
- Department of Biochemistry and Cell Biology and Center for Developmental Genetics
| |
Collapse
|
2
|
Abstract
Motivation The universal expressibility assumption of Deep Neural Networks (DNNs) is the key motivation behind recent worksin the systems biology community to employDNNs to solve important problems in functional genomics and moleculargenetics. Typically, such investigations have taken a ‘black box’ approach in which the internal structure of themodel used is set purely by machine learning considerations with little consideration of representing the internalstructure of the biological system by the mathematical structure of the DNN. DNNs have not yet been applied to thedetailed modeling of transcriptional control in which mRNA production is controlled by the binding of specific transcriptionfactors to DNA, in part because such models are in part formulated in terms of specific chemical equationsthat appear different in form from those used in neural networks. Results In this paper, we give an example of a DNN whichcan model the detailed control of transcription in a precise and predictive manner. Its internal structure is fully interpretableand is faithful to underlying chemistry of transcription factor binding to DNA. We derive our DNN from asystems biology model that was not previously recognized as having a DNN structure. Although we apply our DNNto data from the early embryo of the fruit fly Drosophila, this system serves as a test bed for analysis of much larger datasets obtained by systems biology studies on a genomic scale. . Availability and implementation The implementation and data for the models used in this paper are in a zip file in the supplementary material. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Yi Liu
- Department of Statistics, Ecology and Evolution, Molecular Genetics & Cell Biology, Institute of Genomics and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - Kenneth Barr
- Department of Human Genetics, Ecology and Evolution, Molecular Genetics & Cell Biology, Institute of Genomics and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| | - John Reinitz
- Departments of Statistics, Ecology and Evolution, Molecular Genetics & Cell Biology, Institute of Genomics and Systems Biology, University of Chicago, Chicago, IL 60637, USA
| |
Collapse
|
3
|
Classification-Based Inference of Dynamical Models of Gene Regulatory Networks. G3-GENES GENOMES GENETICS 2019; 9:4183-4195. [PMID: 31624138 PMCID: PMC6893186 DOI: 10.1534/g3.119.400603] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
Cell-fate decisions during development are controlled by densely interconnected gene regulatory networks (GRNs) consisting of many genes. Inferring and predictively modeling these GRNs is crucial for understanding development and other physiological processes. Gene circuits, coupled differential equations that represent gene product synthesis with a switch-like function, provide a biologically realistic framework for modeling the time evolution of gene expression. However, their use has been limited to smaller networks due to the computational expense of inferring model parameters from gene expression data using global non-linear optimization. Here we show that the switch-like nature of gene regulation can be exploited to break the gene circuit inference problem into two simpler optimization problems that are amenable to computationally efficient supervised learning techniques. We present FIGR (Fast Inference of Gene Regulation), a novel classification-based inference approach to determining gene circuit parameters. We demonstrate FIGR’s effectiveness on synthetic data generated from random gene circuits of up to 50 genes as well as experimental data from the gap gene system of Drosophila melanogaster, a benchmark for inferring dynamical GRN models. FIGR is faster than global non-linear optimization by a factor of 600 and its computational complexity scales much better with GRN size. On a practical level, FIGR can accurately infer the biologically realistic gap gene network in under a minute on desktop-class hardware instead of requiring hours of parallel computing. We anticipate that FIGR would enable the inference of much larger biologically realistic GRNs than was possible before.
Collapse
|
4
|
Barr KA, Martinez C, Moran JR, Kim AR, Ramos AF, Reinitz J. Synthetic enhancer design by in silico compensatory evolution reveals flexibility and constraint in cis-regulation. BMC SYSTEMS BIOLOGY 2017; 11:116. [PMID: 29187214 PMCID: PMC5708098 DOI: 10.1186/s12918-017-0485-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Accepted: 11/09/2017] [Indexed: 11/12/2022]
Abstract
BACKGROUND Models that incorporate specific chemical mechanisms have been successful in describing the activity of Drosophila developmental enhancers as a function of underlying transcription factor binding motifs. Despite this, the minimum set of mechanisms required to reconstruct an enhancer from its constituent parts is not known. Synthetic biology offers the potential to test the sufficiency of known mechanisms to describe the activity of enhancers, as well as to uncover constraints on the number, order, and spacing of motifs. RESULTS Using a functional model and in silico compensatory evolution, we generated putative synthetic even-skipped stripe 2 enhancers with varying degrees of similarity to the natural enhancer. These elements represent the evolutionary trajectories of the natural stripe 2 enhancer towards two synthetic enhancers designed ab initio. In the first trajectory, spatially regulated expression was maintained, even after more than a third of binding sites were lost. In the second, sequences with high similarity to the natural element did not drive expression, but a highly diverged sequence about half the length of the minimal stripe 2 enhancer drove ten times greater expression. Additionally, homotypic clusters of Zelda or Stat92E motifs, but not Bicoid, drove expression in developing embryos. CONCLUSIONS Here, we present a functional model of gene regulation to test the degree to which the known transcription factors and their interactions explain the activity of the Drosophila even-skipped stripe 2 enhancer. Initial success in the first trajectory showed that the gene regulation model explains much of the function of the stripe 2 enhancer. Cases where expression deviated from prediction indicates that undescribed factors likely act to modulate expression. We also showed that activation driven Bicoid and Hunchback is highly sensitive to spatial organization of binding motifs. In contrast, Zelda and Stat92E drive expression from simple homotypic clusters, suggesting that activation driven by these factors is less constrained. Collectively, the 40 sequences generated in this work provides a powerful training set for building future models of gene regulation.
Collapse
Affiliation(s)
- Kenneth A Barr
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Zoology 111, 1101 E 57th St, Chicago, 60637, Illinois, USA.
- Department of Ecology and Evolution, The University of Chicago, Chicago, 60637, Illinois, USA.
| | - Carlos Martinez
- Department Biochemistry and Molecular Genetics, Northwestern University, Chicago, 60611, Illinois, USA
| | - Jennifer R Moran
- Department Human Genetics, The University of Chicago, Chicago, 60637, Illinois, USA
- Institute for Genomics & Systems Biology, The University of Chicago, Chicago, 60637, Illinois, USA
| | - Ah-Ram Kim
- School of Life Science, Handong Global University, Pohang, 37554, Gyeongbuk, South Korea
| | - Alexandre F Ramos
- Departamento de Radiologia - Faculdade de Medicina, Universidade de São Paulo & Instituto do Câncer do Estado de São Paulo, São Paulo, SP CEP, 05403-911, Brazil
- Escola de Artes, Ciências e Humanidades & Núcleo de Estudos Interdisciplinares em Sistemas Complexos, Universidade de São Paulo, Av. Arlindo Béttio, São Paulo, 1000 CEP 03828-000, SP, Brazil
| | - John Reinitz
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Zoology 111, 1101 E 57th St, Chicago, 60637, Illinois, USA
- Department of Ecology and Evolution, The University of Chicago, Chicago, 60637, Illinois, USA
- Institute for Genomics & Systems Biology, The University of Chicago, Chicago, 60637, Illinois, USA
- Department Statistics, The University of Chicago, 5747 S. Ellis Avenue Jones 312, Chicago, 60637, IL, USA
| |
Collapse
|
5
|
Barr KA, Reinitz J. A sequence level model of an intact locus predicts the location and function of nonadditive enhancers. PLoS One 2017; 12:e0180861. [PMID: 28715438 PMCID: PMC5513433 DOI: 10.1371/journal.pone.0180861] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Accepted: 06/22/2017] [Indexed: 01/24/2023] Open
Abstract
Metazoan gene expression is controlled through the action of long stretches of noncoding DNA that contain enhancers-shorter sequences responsible for controlling a single aspect of a gene's expression pattern. Models built on thermodynamics have shown how enhancers interpret protein concentration in order to determine specific levels of gene expression, but the emergent regulatory logic of a complete regulatory locus shows qualitative and quantitative differences from isolated enhancers. Such differences may arise from steric competition limiting the quantity of DNA that can simultaneously influence the transcription machinery. We incorporated this competition into a mechanistic model of gene regulation, generated efficient algorithms for this computation, and applied it to the regulation of Drosophila even-skipped (eve). This model finds the location of enhancers and identifies which factors control the boundaries of eve expression. This model predicts a new enhancer that, when assayed in vivo, drives expression in a non-eve pattern. Incorporation of chromatin accessibility eliminates this inconsistency.
Collapse
Affiliation(s)
- Kenneth A. Barr
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| | - John Reinitz
- Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Statistics, University of Chicago, Chicago, Illinois, United States of America
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Department of Molecular Genetics and Cell Biology, University of Chicago, Chicago, Illinois, United States of America
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| |
Collapse
|
6
|
Sayal R, Dresch JM, Pushel I, Taylor BR, Arnosti DN. Quantitative perturbation-based analysis of gene expression predicts enhancer activity in early Drosophila embryo. eLife 2016; 5. [PMID: 27152947 PMCID: PMC4859806 DOI: 10.7554/elife.08445] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Accepted: 04/04/2016] [Indexed: 01/02/2023] Open
Abstract
Enhancers constitute one of the major components of regulatory machinery of metazoans. Although several genome-wide studies have focused on finding and locating enhancers in the genomes, the fundamental principles governing their internal architecture and cis-regulatory grammar remain elusive. Here, we describe an extensive, quantitative perturbation analysis targeting the dorsal-ventral patterning gene regulatory network (GRN) controlled by Drosophila NF-κB homolog Dorsal. To understand transcription factor interactions on enhancers, we employed an ensemble of mathematical models, testing effects of cooperativity, repression, and factor potency. Models trained on the dataset correctly predict activity of evolutionarily divergent regulatory regions, providing insights into spatial relationships between repressor and activator binding sites. Importantly, the collective predictions of sets of models were effective at novel enhancer identification and characterization. Our study demonstrates how experimental dataset and modeling can be effectively combined to provide quantitative insights into cis-regulatory information on a genome-wide scale. DOI:http://dx.doi.org/10.7554/eLife.08445.001 DNA contains regions known as genes, which may be “transcribed” to produce the RNA molecules that act as templates for building proteins and regulate cell activity. Proteins called transcription factors can bind to specific sequences of DNA to influence whether nearby genes are transcribed. For example, so-called enhancer regions of DNA contain several binding sites for transcription factors, and this binding activates gene transcription. Little is known about how the transcription factor binding sites are organized in enhancer regions, which makes it difficult to use DNA sequence information alone to predict the regulation of genes. A transcription factor called Dorsal controls the activity of a network of genes that plays a crucial role in the development of fruit fly embryos. Dorsal binds to the enhancer region of a gene called rhomboid, which has been well studied and is known to be a fairly typical example of an enhancer region. To understand the regulatory information encoded in the DNA sequences of enhancers, Sayal, Dresch et al. have now used a technique called perturbation analysis to investigate the interactions that are likely to occur between Dorsal and other transcription factors as they bind to the rhomboid enhancer. This technique involves systematically mutating the enhancer to remove different combinations of transcription factor binding sites and quantitatively investigating the effect this has on gene activity. A large set of mathematical models were then trained using this data and shown to correctly predict the activity of a range of other gene regulatory regions. The collective predictions of the models identified new enhancer regions and revealed details about how different types of transcription factor binding sites are arranged within enhancers. As we enter an era where the DNA sequences of entire human populations are increasingly accessible, we would like to know the functional significance of changes in gene regulatory regions. Sayal, Dresch et al. show that the regulatory properties of specific control proteins are accessible by employing quantitative experiments and mathematical models. Similar studies will be required to learn how mutations found across the genome may alter gene expression, leading to better diagnosis and treatment of disease. DOI:http://dx.doi.org/10.7554/eLife.08445.002
Collapse
Affiliation(s)
- Rupinder Sayal
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, United States.,Department of Biochemistry, DAV University, Jalandhar, India
| | - Jacqueline M Dresch
- Department of Mathematics, Michigan State University, East Lansing, United States.,Department of Mathematics and Computer Science, Clark University, Worcester, United States
| | - Irina Pushel
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, United States.,Stowers Institute for Medical Research, Kansas City, United States
| | - Benjamin R Taylor
- Department of Computer Science and Engineering, Michigan State University, East Lansing, United States.,School of Computer Science, Georgia Institute of Technology, Atlanta, United States
| | - David N Arnosti
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, United States
| |
Collapse
|
7
|
|
8
|
Jiang P, Ludwig MZ, Kreitman M, Reinitz J. Natural variation of the expression pattern of the segmentation gene even-skipped in melanogaster. Dev Biol 2015; 405:173-81. [PMID: 26129990 PMCID: PMC4529771 DOI: 10.1016/j.ydbio.2015.06.019] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2014] [Revised: 06/23/2015] [Accepted: 06/24/2015] [Indexed: 11/28/2022]
Abstract
The evolution of canalized traits is a central question in evolutionary biology. Natural variation in highly conserved traits can provide clues about their evolutionary potential. Here we investigate natural variation in a conserved trait-even-skipped (eve) expression at the cellular blastoderm stage of embryonic development in Drosophila melanogaster. Expression of the pair-rule gene eve was quantitatively measured in three inbred lines derived from a natural population of D. melanogaster. One line showed marked differences in the spacing, amplitude and timing of formation of the characteristic seven-striped pattern over a 50-min period prior to the onset of gastrulation. Stripe 5 amplitude and the width of the interstripe between stripes 4 and 5 were both reduced in this line, while the interstripe distance between stripes 3 and 4 was increased. Engrailed expression in stage 10 embryos revealed a statistically significant increase in the length of parasegment 6 and a decrease in the length of parasegments 8 and 9. These changes are larger than those previously reported between D. melanogaster and D. pseudoobscura, two species that are thought to have diverged from a common ancestor over 25 million years ago. This line harbors a rare 448 bp deletion in the first intron of knirps (kni). This finding suggested that reduced Kni levels caused the deviant eve expression, and indeed we observed lower levels of Kni protein at early cycle 14A in L2 compared to the other two lines. A second of the three lines displayed an approximately 20% greater level of expression for all seven eve stripes. The three lines are each viable and fertile, and none display a segmentation defect as adults, suggesting that early-acting variation in eve expression is ameliorated by developmental buffering mechanisms acting later in development. Canalization of the segmentation pathway may reduce the fitness consequences of genetic variation, thus allowing the persistence of mutations with unexpectedly strong gene expression phenotypes.
Collapse
Affiliation(s)
- Pengyao Jiang
- Department of Ecology & Evolution, University of Chicago, IL 60637, USA.
| | - Michael Z Ludwig
- Department of Ecology & Evolution, University of Chicago, IL 60637, USA; Institute for Genomics & Systems Biology, Chicago, IL 60637, USA
| | - Martin Kreitman
- Department of Ecology & Evolution, University of Chicago, IL 60637, USA; Institute for Genomics & Systems Biology, Chicago, IL 60637, USA
| | - John Reinitz
- Department of Ecology & Evolution, University of Chicago, IL 60637, USA; Institute for Genomics & Systems Biology, Chicago, IL 60637, USA; Department of Statistics, University of Chicago, IL 60637, USA; Department of Molecular Genetics and Cell Biology, University of Chicago, IL 60637, USA
| |
Collapse
|
9
|
Janssens H, Siggens K, Cicin-Sain D, Jiménez-Guri E, Musy M, Akam M, Jaeger J. A quantitative atlas of Even-skipped and Hunchback expression in Clogmia albipunctata (Diptera: Psychodidae) blastoderm embryos. EvoDevo 2014; 5:1. [PMID: 24393251 PMCID: PMC3897886 DOI: 10.1186/2041-9139-5-1] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2013] [Accepted: 11/22/2013] [Indexed: 11/13/2022] Open
Abstract
Background Comparative studies of developmental processes are one of the main approaches to evolutionary developmental biology (evo-devo). Over recent years, there has been a shift of focus from the comparative study of particular regulatory genes to the level of whole gene networks. Reverse-engineering methods can be used to computationally reconstitute and analyze the function and dynamics of such networks. These methods require quantitative spatio-temporal expression data for model fitting. Obtaining such data in non-model organisms remains a major technical challenge, impeding the wider application of data-driven mathematical modeling to evo-devo. Results We have raised antibodies against four segmentation gene products in the moth midge Clogmia albipunctata, a non-drosophilid dipteran species. We have used these antibodies to create a quantitative atlas of protein expression patterns for the gap gene hunchback (hb), and the pair-rule gene even-skipped (eve). Our data reveal differences in the dynamics of Hb boundary positioning and Eve stripe formation between C. albipunctata and Drosophila melanogaster. Despite these differences, the overall relative spatial arrangement of Hb and Eve domains is remarkably conserved between these two distantly related dipteran species. Conclusions We provide a proof of principle that it is possible to acquire quantitative gene expression data at high accuracy and spatio-temporal resolution in non-model organisms. Our quantitative data extend earlier qualitative studies of segmentation gene expression in C. albipunctata, and provide a starting point for comparative reverse-engineering studies of the evolutionary and developmental dynamics of the segmentation gene system.
Collapse
Affiliation(s)
- Hilde Janssens
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica (CRG), and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Ken Siggens
- Department of Zoology, Downing Street, Cambridge CB2 3EJ UK
| | - Damjan Cicin-Sain
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica (CRG), and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Eva Jiménez-Guri
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica (CRG), and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Marco Musy
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica (CRG), and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Michael Akam
- Department of Zoology, Downing Street, Cambridge CB2 3EJ UK
| | - Johannes Jaeger
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica (CRG), and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| |
Collapse
|
10
|
Becker K, Balsa-Canto E, Cicin-Sain D, Hoermann A, Janssens H, Banga JR, Jaeger J. Reverse-engineering post-transcriptional regulation of gap genes in Drosophila melanogaster. PLoS Comput Biol 2013; 9:e1003281. [PMID: 24204230 PMCID: PMC3814631 DOI: 10.1371/journal.pcbi.1003281] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2013] [Accepted: 09/02/2013] [Indexed: 12/19/2022] Open
Abstract
Systems biology proceeds through repeated cycles of experiment and modeling. One way to implement this is reverse engineering, where models are fit to data to infer and analyse regulatory mechanisms. This requires rigorous methods to determine whether model parameters can be properly identified. Applying such methods in a complex biological context remains challenging. We use reverse engineering to study post-transcriptional regulation in pattern formation. As a case study, we analyse expression of the gap genes Krüppel, knirps, and giant in Drosophila melanogaster. We use detailed, quantitative datasets of gap gene mRNA and protein expression to solve and fit a model of post-transcriptional regulation, and establish its structural and practical identifiability. Our results demonstrate that post-transcriptional regulation is not required for patterning in this system, but is necessary for proper control of protein levels. Our work demonstrates that the uniqueness and specificity of a fitted model can be rigorously determined in the context of spatio-temporal pattern formation. This greatly increases the potential of reverse engineering for the study of development and other, similarly complex, biological processes. The analysis of pattern-forming gene networks is largely focussed on transcriptional regulation. However, post-transcriptional events, such as translation and regulation of protein stability also play important roles in the establishment of protein expression patterns and levels. In this study, we use a reverse-engineering approach—fitting mathematical models to quantitative expression data—to analyse post-transcriptional regulation of the Drosophila gap genes Krüppel, knirps and giant, involved in segment determination during early embryogenesis. Rigorous fitting requires us to establish whether our models provide a robust and unique solution. We demonstrate, for the first time, that this can be done in the context of a complex spatio-temporal regulatory system. This is an important methodological advance for reverse-engineering developmental processes. Our results indicate that post-transcriptional regulation is not required for pattern formation, but is necessary for proper regulation of gap protein levels. Specifically, we predict that translation rates must be tuned for rapid early accumulation, and protein stability must be increased for persistence of high protein levels at late stages of gap gene expression.
Collapse
Affiliation(s)
- Kolja Becker
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain
- Institute of Genetics, Johannes Gutenberg University, Mainz, Germany
| | | | - Damjan Cicin-Sain
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain
| | - Astrid Hoermann
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain
| | - Hilde Janssens
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain
| | | | - Johannes Jaeger
- EMBL/CRG Research Unit in Systems Biology, Centre de Regulació Genòmica, and Universitat Pombeu Fabra (UPF), Barcelona, Spain
- * E-mail:
| |
Collapse
|
11
|
Surkova S, Myasnikova E, Kozlov KN, Pisarev A, Reinitz J, Samsonova M. Quantitative imaging of gene expression in Drosophila embryos. Cold Spring Harb Protoc 2013; 2013:488-97. [PMID: 23734022 DOI: 10.1101/pdb.top075101] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Quantitative measurements derived using sophisticated microscopy techniques are essential for understanding the basic principles that control the behavior of biological systems. Here we describe a data pipeline developed to extract quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. The pipeline consists of image segmentation, background removal, temporal characterization of an embryo, data registration, and data averaging. This pipeline has been successfully applied to obtain quantitative gene expression data at cellular resolution in space and at 6.5-min resolution in time. It has also enabled the construction of a spatiotemporal atlas of segmentation gene expression. We describe the software used to construct a workflow for extracting quantitative data on segmentation gene expression and the BREReA package, which implements the methods for background removal and registration of segmentation gene expression patterns.
Collapse
|
12
|
Dresch JM, Richards M, Ay A. A primer on thermodynamic-based models for deciphering transcriptional regulatory logic. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2013; 1829:946-53. [PMID: 23643643 DOI: 10.1016/j.bbagrm.2013.04.011] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/26/2012] [Revised: 04/24/2013] [Accepted: 04/25/2013] [Indexed: 11/27/2022]
Abstract
A rigorous analysis of transcriptional regulation at the DNA level is crucial to the understanding of many biological systems. Mathematical modeling has offered researchers a new approach to understanding this central process. In particular, thermodynamic-based modeling represents the most biophysically informed approach aimed at connecting DNA level regulatory sequences to the expression of specific genes. The goal of this review is to give biologists a thorough description of the steps involved in building, analyzing, and implementing a thermodynamic-based model of transcriptional regulation. The data requirements for this modeling approach are described, the derivation for a specific regulatory region is shown, and the challenges and future directions for the quantitative modeling of gene regulation are discussed.
Collapse
|
13
|
Kim AR, Martinez C, Ionides J, Ramos AF, Ludwig MZ, Ogawa N, Sharp DH, Reinitz J. Rearrangements of 2.5 kilobases of noncoding DNA from the Drosophila even-skipped locus define predictive rules of genomic cis-regulatory logic. PLoS Genet 2013; 9:e1003243. [PMID: 23468638 PMCID: PMC3585115 DOI: 10.1371/journal.pgen.1003243] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 11/30/2012] [Indexed: 01/19/2023] Open
Abstract
Rearrangements of about 2.5 kilobases of regulatory DNA located 5' of the transcription start site of the Drosophila even-skipped locus generate large-scale changes in the expression of even-skipped stripes 2, 3, and 7. The most radical effects are generated by juxtaposing the minimal stripe enhancers MSE2 and MSE3 for stripes 2 and 3 with and without small "spacer" segments less than 360 bp in length. We placed these fusion constructs in a targeted transformation site and obtained quantitative expression data for these transformants together with their controlling transcription factors at cellular resolution. These data demonstrated that the rearrangements can alter expression levels in stripe 2 and the 2-3 interstripe by a factor of more than 10. We reasoned that this behavior would place tight constraints on possible rules of genomic cis-regulatory logic. To find these constraints, we confronted our new expression data together with previously obtained data on other constructs with a computational model. The model contained representations of thermodynamic protein-DNA interactions including steric interference and cooperative binding, short-range repression, direct repression, activation, and coactivation. The model was highly constrained by the training data, which it described within the limits of experimental error. The model, so constrained, was able to correctly predict expression patterns driven by enhancers for other Drosophila genes; even-skipped enhancers not included in the training set; stripe 2, 3, and 7 enhancers from various Drosophilid and Sepsid species; and long segments of even-skipped regulatory DNA that contain multiple enhancers. The model further demonstrated that elevated expression driven by a fusion of MSE2 and MSE3 was a consequence of the recruitment of a portion of MSE3 to become a functional component of MSE2, demonstrating that cis-regulatory "elements" are not elementary objects.
Collapse
Affiliation(s)
- Ah-Ram Kim
- Department of Ecology and Evolution, Chicago Center for Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, New York, United States of America
| | - Carlos Martinez
- Department of Ecology and Evolution, Chicago Center for Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| | - John Ionides
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
| | - Alexandre F. Ramos
- Escola de Artes, Ciências e Humanidades, Universidade de São Paulo, São Paulo, Brazil
| | - Michael Z. Ludwig
- Department of Ecology and Evolution, Chicago Center for Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| | - Nobuo Ogawa
- Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - David H. Sharp
- Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - John Reinitz
- Department of Ecology and Evolution, Chicago Center for Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Statistics, Department of Molecular Genetics and Cell Biology, and Institute of Genomics and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| |
Collapse
|
14
|
Abstract
The deleterious effects of different X-chromosome dosage in males and females are buffered by a process called dosage compensation, which in Drosophila is achieved through a doubling of X-linked transcription in males. The male-specific lethal complex mediates this process, but is known to act only after gastrulation. Recent work has shown that the transcription of X-linked genes is also upregulated in males prior to gastrulation; whether it results in functional dosage compensation is not known. Absent or partial early dosage compensation raises the possibility of sex-biased expression of key developmental genes, such as the segmentation genes controlling anteroposterior patterning. We assess the functional output of early dosage compensation by measuring the expression of even-skipped (eve) with high spatiotemporal resolution in male and female embryos. We show that eve has a sexually dimorphic pattern, suggesting an interaction with either X-chromosome dose or the sex determination system. By manipulating the gene copy number of an X-linked transcription factor, giant (gt), we traced sex-biased eve patterning to gt dose, indicating that early dosage compensation is functionally incomplete. Despite sex-biased eve expression, the gene networks downstream of eve are able to produce sex-independent segmentation, a point that we establish by measuring the proportions of segments in elongated germ-band embryos. Finally, we use a whole-locus eve transgene with modified cis regulation to demonstrate that segment proportions have a sex-dependent sensitivity to subtle changes in Eve expression. The sex independence of downstream segmentation despite this sensitivity to Eve expression implies that additional autosomal gene- or pathway-specific mechanisms are required to ameliorate the effects of partial early dosage compensation.
Collapse
|
15
|
Janssens H, Crombach A, Richard Wotton K, Cicin-Sain D, Surkova S, Lu Lim C, Samsonova M, Akam M, Jaeger J. Lack of tailless leads to an increase in expression variability in Drosophila embryos. Dev Biol 2013; 377:305-17. [PMID: 23333944 PMCID: PMC3635121 DOI: 10.1016/j.ydbio.2013.01.010] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2012] [Revised: 12/24/2012] [Accepted: 01/09/2013] [Indexed: 11/30/2022]
Abstract
Developmental processes are robust, or canalised: dynamic patterns of gene expression across space and time are regulated reliably and precisely in the presence of genetic and environmental perturbations. It remains unclear whether canalisation relies on specific regulatory factors (such as heat-shock proteins), or whether it is based on more general redundancy and distributed robustness at the network level. The latter explanation implies that mutations in many regulatory factors should exhibit loss of canalisation. Here, we present a quantitative characterisation of segmentation gene expression patterns in mutants of the terminal gap gene tailless (tll) in Drosophila melanogaster. Our analysis provides new insights into the dynamic mechanisms underlying gap gene regulation, and reveals significantly increased variability of gene expression in the mutant compared to the wild-type background. We show that both position and timing of posterior segmentation gene expression domains vary strongly from embryo-to-embryo in tll mutants. This variability must be caused by a vulnerability in the regulatory system which is hidden or buffered in the wild-type, but becomes uncovered by the deletion of tll. Our analysis provides evidence that loss of canalisation in mutants could be more widespread than previously thought.
Collapse
Affiliation(s)
- Hilde Janssens
- EMBL/CRG Research Unit in Systems Biology, CRG—Centre de Regulació Genòmica, and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Anton Crombach
- EMBL/CRG Research Unit in Systems Biology, CRG—Centre de Regulació Genòmica, and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Karl Richard Wotton
- EMBL/CRG Research Unit in Systems Biology, CRG—Centre de Regulació Genòmica, and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Damjan Cicin-Sain
- EMBL/CRG Research Unit in Systems Biology, CRG—Centre de Regulació Genòmica, and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Svetlana Surkova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg 195251, Russia
| | - Chea Lu Lim
- Department of Zoology, Downing Street, Cambridge CB2 3EJ, UK
| | - Maria Samsonova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg 195251, Russia
| | - Michael Akam
- Department of Zoology, Downing Street, Cambridge CB2 3EJ, UK
| | - Johannes Jaeger
- EMBL/CRG Research Unit in Systems Biology, CRG—Centre de Regulació Genòmica, and Universitat Pompeu Fabra (UPF), Dr. Aiguader 88, 08003 Barcelona, Spain
- Department of Zoology, Downing Street, Cambridge CB2 3EJ, UK
- Corresponding author at: Centre for Genomic Regulation (CRG), EMBL/CRG Research Unit in Systems Biology, Dr. Aiguader 88, 08003 Barcelona, Spain. Fax: +34 93 396 99 83.
| |
Collapse
|
16
|
Surkova S, Golubkova E, Manu, Panok L, Mamon L, Reinitz J, Samsonova M. Quantitative dynamics and increased variability of segmentation gene expression in the Drosophila Krüppel and knirps mutants. Dev Biol 2013; 376:99-112. [PMID: 23333947 DOI: 10.1016/j.ydbio.2013.01.008] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2012] [Revised: 12/30/2012] [Accepted: 01/09/2013] [Indexed: 11/28/2022]
Abstract
Here we characterize the response of the Drosophila segmentation system to mutations in two gap genes, Kr and kni, in the form of single or double homozygotes and single heterozygotes. Segmentation gene expression in these genotypes was quantitatively monitored with cellular resolution in space and 6.5 to 13min resolution in time. As is the case with wild type, we found that gene expression domains in the posterior portion of the embryo shift to the anterior over time. In certain cases, such as the gt posterior domain in Kr mutants, the shifts are significantly larger than is seen in wild type embryos. We also investigated the effects of Kr and kni on the variability of gene expression. Mutations often produce variable phenotypes, and it is well known that the cuticular phenotype of Kr mutants is variable. We sought to understand the molecular basis of this effect. We find that throughout cycle 14A the relative levels of eve and ftz expression in stripes 2 and 3 are variable among individual embryos. Moreover, in Kr and kni mutants, unlike wild type, the variability in positioning of the posterior Hb domain and eve stripe 7 is not decreased or filtered with time. The posterior Gt domain in Kr mutants is highly variable at early times, but this variability decreases when this domain shifts in the anterior direction to the position of the neighboring Kni domain. In contrast to these findings, positional variability throughout the embryo does not decrease over time in double Kr;kni mutants. In heterozygotes the early expression patterns of segmentation genes resemble patterns seen in homozygous mutants but by the onset of gastrulation they become similar to the wild type patterns. Finally, we note that gene expression levels are reduced in Kr and kni mutant embryos and have a tendency to decrease over time. This is a surprising result in view of the role that mutual repression is thought to play in the gap gene system.
Collapse
Affiliation(s)
- Svetlana Surkova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg 195251, Russia
| | | | | | | | | | | | | |
Collapse
|
17
|
Botman D, Kaandorp JA. Spatial gene expression quantification: a tool for analysis of in situ hybridizations in sea anemone Nematostella vectensis. BMC Res Notes 2012; 5:555. [PMID: 23039089 PMCID: PMC3532226 DOI: 10.1186/1756-0500-5-555] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 09/26/2012] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Spatial gene expression quantification is required for modeling gene regulation in developing organisms. The fruit fly Drosophila melanogaster is the model system most widely applied for spatial gene expression analysis due to its unique embryonic properties: the shape does not change significantly during its early cleavage cycles and most genes are differentially expressed along a straight axis. This system of development is quite exceptional in the animal kingdom.In the sea anemone Nematostella vectensis the embryo changes its shape during early development; there are cell divisions and cell movement, like in most other metazoans. Nematostella is an attractive case study for spatial gene expression since its transparent body wall makes it accessible to various imaging techniques. FINDINGS Our new quantification method produces standardized gene expression profiles from raw or annotated Nematostella in situ hybridizations by measuring the expression intensity along its cell layer. The procedure is based on digital morphologies derived from high-resolution fluorescence pictures. Additionally, complete descriptions of nonsymmetric expression patterns have been constructed by transforming the gene expression images into a three-dimensional representation. CONCLUSIONS We created a standard format for gene expression data, which enables quantitative analysis of in situ hybridizations from embryos with various shapes in different developmental stages. The obtained expression profiles are suitable as input for optimization of gene regulatory network models, and for correlation analysis of genes from dissimilar Nematostella morphologies. This approach is potentially applicable to many other metazoan model organisms and may also be suitable for processing data from three-dimensional imaging techniques.
Collapse
Affiliation(s)
- Daniel Botman
- Section Computational Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands
| | - Jaap A Kaandorp
- Section Computational Science, University of Amsterdam, Science Park 904, 1098 XH, Amsterdam, The Netherlands
| |
Collapse
|
18
|
Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains. PLoS One 2012; 7:e46658. [PMID: 23029561 PMCID: PMC3460907 DOI: 10.1371/journal.pone.0046658] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2012] [Accepted: 09/05/2012] [Indexed: 11/19/2022] Open
Abstract
Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, “medium-throughput” pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.
Collapse
|
19
|
Kozlov K, Surkova S, Myasnikova E, Reinitz J, Samsonova M. Modeling of gap gene expression in Drosophila Kruppel mutants. PLoS Comput Biol 2012; 8:e1002635. [PMID: 22927803 PMCID: PMC3426564 DOI: 10.1371/journal.pcbi.1002635] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2012] [Accepted: 06/25/2012] [Indexed: 12/24/2022] Open
Abstract
The segmentation gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of gene expression, which determines both the positions and the identities of body segments. The gap gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of gap gene Kruppel (Kr) on segmentation gene expression. We acquired a large dataset on the expression of gap genes in Kr null mutants and demonstrated that the expression levels of these genes are significantly reduced in the second half of cycle 14A. To explain this novel biological result we applied the gene circuit method which extracts regulatory information from spatial gene expression data. Previous attempts to use this formalism to correctly and quantitatively reproduce gap gene expression in mutants for a trunk gap gene failed, therefore here we constructed a revised model and showed that it correctly reproduces the expression patterns of gap genes in Kr null mutants. We found that the remarkable alteration of gap gene expression patterns in Kr mutants can be explained by the dynamic decrease of activating effect of Cad on a target gene and exclusion of Kr gene from the complex network of gap gene interactions, that makes it possible for other interactions, in particular, between hb and gt, to come into effect. The successful modeling of the quantitative aspects of gap gene expression in mutant for the trunk gap gene Kr is a significant achievement of this work. This result also clearly indicates that the oversimplified representation of transcriptional regulation in the previous models is one of the reasons for unsuccessful attempts of mutant simulations. Systems biology is aimed to develop an understanding of biological function or process as a system of interacting components. Here we apply the systems-level approach to understand how the blueprints for segments in the fruit fly Drosophila embryo arise. We obtain gene expression data and use the gene circuits method which allow us to reconstruct the segment determination process in the computer. To understand the system we need not only to describe it in detail, but also to comprehend what happens when certain stimuli or disruptions occur. Previous attempts to model segmentation gene expression patterns in a mutant for a trunk gap gene were unsuccessful. Here we describe the extension of the model that allows us to solve this problem in the context of Kruppel (Kr) gene. We show that remarkable alteration of gap gene expression patterns in Kr mutants can be explained by dynamic decrease of the activating effect of Cad on a target gene and exclusion of Kr from the complex network of gap gene interactions, that makes it possible for other interactions, in particular between hb and gt, to come into effect.
Collapse
Affiliation(s)
- Konstantin Kozlov
- Department of Computational Biology/Center for Advanced Studies, St. Petersburg State Polytechnical University, St. Petersburg, Russia
| | | | | | | | | |
Collapse
|
20
|
Lopes FJP, Spirov AV, Bisch PM. The role of Bicoid cooperative binding in the patterning of sharp borders in Drosophila melanogaster. Dev Biol 2012; 370:165-72. [PMID: 22841642 DOI: 10.1016/j.ydbio.2012.07.020] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2012] [Revised: 07/06/2012] [Accepted: 07/16/2012] [Indexed: 10/28/2022]
Abstract
In Drosophila embryonic development, the Bicoid (Bcd) protein establishes positional information of downstream developmental genes like hunchback (hb), which has a strong anterior expression and a sharp on-off boundary in the mid-embryo. The role of Bcd cooperative binding in the positioning of the Hb pattern has been previously demonstrated. However, there are discrepancies in the reported results about the role of this mechanism in the sharp Hb border. Here, we determined the Hill coefficient (nH) required for Bcd to generate the sharp border of Hb in wild-type (WT) embryos. We found that an n(H) of approximately 6.3 (s.d. 1.4) and 10.8 (s.d. 4.0) is required to account for Hb sharpness at early and late cycle 14A, respectively. Additional mechanisms are possibly required because the high nH is likely unachievable for Bcd binding to the hb promoter. To test this idea, we determined the nH required to pattern the Hb profile of 15 embryos expressing an hb14F allele that is defective in self-activation and found nH to be 3.0 (s.d. 1.0). This result indicates that in WT embryos, the hb self-activation is important for Hb sharpness. Corroborating our results, we also found a progressive increase in the required value of n(H) spanning from 4.0 to 9.2 by determining this coefficient from averaged profiles of eight temporal classes at cycle 14A (T1 to T8). Our results indicate that there is a transition in the mechanisms responsible for the sharp Hb border during cycle 14A: in early stages of this cycle, Bcd cooperative binding is primarily responsible for Hb sharpness; in late cycle 14A, hb self-activation becomes the dominant mechanism.
Collapse
Affiliation(s)
- Francisco J P Lopes
- Laboratório de Física-Biológica, Instituto de Biofúsica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil.
| | | | | |
Collapse
|
21
|
Efficient reverse-engineering of a developmental gene regulatory network. PLoS Comput Biol 2012; 8:e1002589. [PMID: 22807664 PMCID: PMC3395622 DOI: 10.1371/journal.pcbi.1002589] [Citation(s) in RCA: 72] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2012] [Accepted: 04/27/2012] [Indexed: 11/19/2022] Open
Abstract
Understanding the complex regulatory networks underlying development and evolution of multi-cellular organisms is a major problem in biology. Computational models can be used as tools to extract the regulatory structure and dynamics of such networks from gene expression data. This approach is called reverse engineering. It has been successfully applied to many gene networks in various biological systems. However, to reconstitute the structure and non-linear dynamics of a developmental gene network in its spatial context remains a considerable challenge. Here, we address this challenge using a case study: the gap gene network involved in segment determination during early development of Drosophila melanogaster. A major problem for reverse-engineering pattern-forming networks is the significant amount of time and effort required to acquire and quantify spatial gene expression data. We have developed a simplified data processing pipeline that considerably increases the throughput of the method, but results in data of reduced accuracy compared to those previously used for gap gene network inference. We demonstrate that we can infer the correct network structure using our reduced data set, and investigate minimal data requirements for successful reverse engineering. Our results show that timing and position of expression domain boundaries are the crucial features for determining regulatory network structure from data, while it is less important to precisely measure expression levels. Based on this, we define minimal data requirements for gap gene network inference. Our results demonstrate the feasibility of reverse-engineering with much reduced experimental effort. This enables more widespread use of the method in different developmental contexts and organisms. Such systematic application of data-driven models to real-world networks has enormous potential. Only the quantitative investigation of a large number of developmental gene regulatory networks will allow us to discover whether there are rules or regularities governing development and evolution of complex multi-cellular organisms.
Collapse
|
22
|
Measuring gene expression noise in early Drosophila embryos: nucleus-to-nucleus variability. ACTA ACUST UNITED AC 2012; 9:373-382. [PMID: 22723811 DOI: 10.1016/j.procs.2012.04.040] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
In recent years the analysis of noise in gene expression has widely attracted the attention of experimentalists and theoreticians. Experimentally, the approaches based on in vivo fluorescent reporters in single cells appear to be straightforward and effective tools for bacteria and yeast. However, transferring these approaches to multicellular organisms presents many methodological problems. Here we describe our approach to measure between-nucleus variability (noise) in the primary morphogenetic gradient of Bicoid (Bcd) in the precellular blastoderm stage of fruit fly (Drosophila) embryos. The approach is based on the comparison of results for fixed immunostained embryos with observations of live embryos carrying fluorescent Bcd (Bcd-GFP). We measure the noise using two-dimensional Singular Spectrum Analysis (2D SSA). We have found that the nucleus-to-nucleus noise in Bcd intensity, both for live (Bcd-GFP) and for fixed immunstained embryos, tends to be signal-independent. In addition, the character of the noise is sensitive to the nuclear masking technique used to extract quantitative intensities. Further, the method of decomposing the raw quantitative expression data into a signal (expression surface) and residual noise affects the character of the residual noise. We find that careful masking of confocal images and use of appropriate computational tools to decompose raw expression data into trend and noise makes it possible to extract and study the biological noise of gene expression.
Collapse
|
23
|
Roth S. Mathematics and biology: a Kantian view on the history of pattern formation theory. Dev Genes Evol 2011; 221:255-79. [PMID: 22086125 PMCID: PMC3234355 DOI: 10.1007/s00427-011-0378-0] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2011] [Accepted: 10/19/2011] [Indexed: 12/20/2022]
Abstract
Driesch's statement, made around 1900, that the physics and chemistry of his day were unable to explain self-regulation during embryogenesis was correct and could be extended until the year 1972. The emergence of theories of self-organisation required progress in several areas including chemistry, physics, computing and cybernetics. Two parallel lines of development can be distinguished which both culminated in the early 1970s. Firstly, physicochemical theories of self-organisation arose from theoretical (Lotka 1910-1920) and experimental work (Bray 1920; Belousov 1951) on chemical oscillations. However, this research area gained broader acceptance only after thermodynamics was extended to systems far from equilibrium (1922-1967) and the mechanism of the prime example for a chemical oscillator, the Belousov-Zhabotinski reaction, was deciphered in the early 1970s. Secondly, biological theories of self-organisation were rooted in the intellectual environment of artificial intelligence and cybernetics. Turing wrote his The chemical basis of morphogenesis (1952) after working on the construction of one of the first electronic computers. Likewise, Gierer and Meinhardt's theory of local activation and lateral inhibition (1972) was influenced by ideas from cybernetics. The Gierer-Meinhardt theory provided an explanation for the first time of both spontaneous formation of spatial order and of self-regulation that proved to be extremely successful in elucidating a wide range of patterning processes. With the advent of developmental genetics in the 1980s, detailed molecular and functional data became available for complex developmental processes, allowing a new generation of data-driven theoretical approaches. Three examples of such approaches will be discussed. The successes and limitations of mathematical pattern formation theory throughout its history suggest a picture of the organism, which has structural similarity to views of the organic world held by the philosopher Immanuel Kant at the end of the eighteenth century.
Collapse
Affiliation(s)
- Siegfried Roth
- Institute of Developmental Biology, University of Cologne, Biowissenschaftliches Zentrum, Zülpicher Strasse 47b, 50674 Cologne, Germany.
| |
Collapse
|
24
|
Ludwig MZ, Manu, Kittler R, White KP, Kreitman M. Consequences of eukaryotic enhancer architecture for gene expression dynamics, development, and fitness. PLoS Genet 2011; 7:e1002364. [PMID: 22102826 PMCID: PMC3213169 DOI: 10.1371/journal.pgen.1002364] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2011] [Accepted: 09/14/2011] [Indexed: 12/13/2022] Open
Abstract
The regulatory logic of time- and tissue-specific gene expression has mostly been dissected in the context of the smallest DNA fragments that, when isolated, recapitulate native expression in reporter assays. It is not known if the genomic sequences surrounding such fragments, often evolutionarily conserved, have any biological function or not. Using an enhancer of the even-skipped gene of Drosophila as a model, we investigate the functional significance of the genomic sequences surrounding empirically identified enhancers. A 480 bp long "minimal stripe element" is able to drive even-skipped expression in the second of seven stripes but is embedded in a larger region of 800 bp containing evolutionarily conserved binding sites for required transcription factors. To assess the overall fitness contribution made by these binding sites in the native genomic context, we employed a gene-replacement strategy in which whole-locus transgenes, capable of rescuing even-skipped(-) lethality to adulthood, were substituted for the native gene. The molecular phenotypes were characterized by tagging Even-skipped with a fluorescent protein and monitoring gene expression dynamics in living embryos. We used recombineering to excise the sequences surrounding the minimal enhancer and site-specific transgenesis to create co-isogenic strains differing only in their stripe 2 sequences. Remarkably, the flanking sequences were dispensable for viability, proving the sufficiency of the minimal element for biological function under normal conditions. These sequences are required for robustness to genetic and environmental perturbation instead. The mutant enhancers had measurable sex- and dose-dependent effects on viability. At the molecular level, the mutants showed a destabilization of stripe placement and improper activation of downstream genes. Finally, we demonstrate through live measurements that the peripheral sequences are required for temperature compensation. These results imply that seemingly redundant regulatory sequences beyond the minimal enhancer are necessary for robust gene expression and that "robustness" itself must be an evolved characteristic of the wild-type enhancer.
Collapse
Affiliation(s)
- Michael Z. Ludwig
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| | - Manu
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
| | - Ralf Kittler
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Kevin P. White
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Martin Kreitman
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, United States of America
- Institute for Genomics and Systems Biology, University of Chicago, Chicago, Illinois, United States of America
| |
Collapse
|
25
|
Kanodia JS, Kim Y, Tomer R, Khan Z, Chung K, Storey JD, Lu H, Keller PJ, Shvartsman SY. A computational statistics approach for estimating the spatial range of morphogen gradients. Development 2011; 138:4867-74. [PMID: 22007136 DOI: 10.1242/dev.071571] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
A crucial issue in studies of morphogen gradients relates to their range: the distance over which they can act as direct regulators of cell signaling, gene expression and cell differentiation. To address this, we present a straightforward statistical framework that can be used in multiple developmental systems. We illustrate the developed approach by providing a point estimate and confidence interval for the spatial range of the graded distribution of nuclear Dorsal, a transcription factor that controls the dorsoventral pattern of the Drosophila embryo.
Collapse
Affiliation(s)
- Jitendra S Kanodia
- Department of Chemical and Biological Engineering and Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
| | | | | | | | | | | | | | | | | |
Collapse
|
26
|
Myasnikova E, Surkova S, Stein G, Pisarev A, Samsonova M. A regression system for estimation of errors introduced by confocal imaging into gene expression data in situ. BMC Bioinformatics 2011; 12:320. [PMID: 21816093 PMCID: PMC3169536 DOI: 10.1186/1471-2105-12-320] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2011] [Accepted: 08/04/2011] [Indexed: 11/10/2022] Open
Abstract
Background Accuracy of the data extracted from two-dimensional confocal images is limited due to experimental errors that arise in course of confocal scanning. The common way to reduce the noise in images is sequential scanning of the same specimen several times with the subsequent averaging of multiple frames. Attempts to increase the dynamical range of an image by setting too high values of microscope PMT parameters may cause clipping of single frames and introduce errors into the data extracted from the averaged images. For the estimation and correction of this kind of errors a method based on censoring technique (Myasnikova et al., 2009) is used. However, the method requires the availability of all the confocal scans along with the averaged image, which is normally not provided by the standard scanning procedure. Results To predict error size in the data extracted from the averaged image we developed a regression system. The system is trained on the learning sample composed of images obtained from three different microscopes at different combinations of PMT parameters, and for each image all the scans are saved. The system demonstrates high prediction accuracy and was applied for correction of errors in the data on segmentation gene expression in Drosophila blastoderm stored in the FlyEx database (http://urchin.spbcas.ru/flyex/, http://flyex.uchicago.edu/flyex/). The prediction method is realized as a software tool CorrectPattern freely available at http://urchin.spbcas.ru/asp/2011/emm/. Conclusions We created a regression system and software to predict the magnitude of errors in the data obtained from a confocal image based on information about microscope parameters used for the image acquisition. An important advantage of the developed prediction system is the possibility to accurately correct the errors in data obtained from strongly clipped images, thereby allowing to obtain images of the higher dynamical range and thus to extract more detailed quantitative information from them.
Collapse
Affiliation(s)
- Ekaterina Myasnikova
- Department of Computational Biology, Center for Advanced Studies, St.Petersburg State Polytechnical University, St.Petersburg, 195251, Russia.
| | | | | | | | | |
Collapse
|
27
|
Surkova SY, Gurskiy VV, Reinitz J, Samsonova MG. Study of stability mechanisms of embryonic development in fruit fly Drosophila. Russ J Dev Biol 2011. [DOI: 10.1134/s1062360411010115] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
28
|
Holloway DM, Lopes FJP, da Fontoura Costa L, Travençolo BAN, Golyandina N, Usevich K, Spirov AV. Gene expression noise in spatial patterning: hunchback promoter structure affects noise amplitude and distribution in Drosophila segmentation. PLoS Comput Biol 2011; 7:e1001069. [PMID: 21304932 PMCID: PMC3033364 DOI: 10.1371/journal.pcbi.1001069] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2010] [Accepted: 12/28/2010] [Indexed: 01/08/2023] Open
Abstract
Positional information in developing embryos is specified by spatial gradients of transcriptional regulators. One of the classic systems for studying this is the activation of the hunchback (hb) gene in early fruit fly (Drosophila) segmentation by the maternally-derived gradient of the Bicoid (Bcd) protein. Gene regulation is subject to intrinsic noise which can produce variable expression. This variability must be constrained in the highly reproducible and coordinated events of development. We identify means by which noise is controlled during gene expression by characterizing the dependence of hb mRNA and protein output noise on hb promoter structure and transcriptional dynamics. We use a stochastic model of the hb promoter in which the number and strength of Bcd and Hb (self-regulatory) binding sites can be varied. Model parameters are fit to data from WT embryos, the self-regulation mutant hb(14F), and lacZ reporter constructs using different portions of the hb promoter. We have corroborated model noise predictions experimentally. The results indicate that WT (self-regulatory) Hb output noise is predominantly dependent on the transcription and translation dynamics of its own expression, rather than on Bcd fluctuations. The constructs and mutant, which lack self-regulation, indicate that the multiple Bcd binding sites in the hb promoter (and their strengths) also play a role in buffering noise. The model is robust to the variation in Bcd binding site number across a number of fly species. This study identifies particular ways in which promoter structure and regulatory dynamics reduce hb output noise. Insofar as many of these are common features of genes (e.g. multiple regulatory sites, cooperativity, self-feedback), the current results contribute to the general understanding of the reproducibility and determinacy of spatial patterning in early development.
Collapse
Affiliation(s)
- David M Holloway
- Mathematics Department, British Columbia Institute of Technology, Burnaby, British Columbia, Canada.
| | | | | | | | | | | | | |
Collapse
|
29
|
Prazak L, Fujioka M, Gergen JP. Non-additive interactions involving two distinct elements mediate sloppy-paired regulation by pair-rule transcription factors. Dev Biol 2010; 344:1048-59. [PMID: 20435028 DOI: 10.1016/j.ydbio.2010.04.026] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2009] [Revised: 04/08/2010] [Accepted: 04/23/2010] [Indexed: 11/18/2022]
Abstract
The relatively simple combinatorial rules responsible for establishing the initial metameric expression of sloppy-paired-1 (slp1) in the Drosophila blastoderm embryo make this system an attractive model for investigating the mechanism of regulation by pair-rule transcription factors. This investigation of slp1 cis-regulatory architecture identifies two distinct elements, a proximal early stripe element (PESE) and a distal early stripe element (DESE) located from -3.1kb to -2.5kb and from -8.1kb to -7.1kb upstream of the slp1 promoter, respectively, that mediate this early regulation. The proximal element expresses only even-numbered stripes and mediates repression by Even-skipped (Eve) as well as by the combination of Runt and Fushi-tarazu (Ftz). A 272 basepair sub-element of PESE retains an Eve-dependent repression, but is expressed throughout the even-numbered parasegments due to the loss of repression by Runt and Ftz. In contrast, the distal element expresses both odd and even-numbered stripes and also drives inappropriate expression in the anterior half of the odd-numbered parasegments due to an inability to respond to repression by Eve. Importantly, a composite reporter gene containing both early stripe elements recapitulates pair-rule gene-dependent regulation in a manner beyond what is expected from combining their individual patterns. These results indicate that interactions involving distinct cis-elements contribute to the proper integration of pair-rule regulatory information. A model fully accounting for these results proposes that metameric slp1 expression is achieved through the Runt-dependent regulation of interactions between these two pair-rule response elements and the slp1 promoter.
Collapse
Affiliation(s)
- Lisa Prazak
- Department of Biochemistry and Cell Biology and the Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-5215, USA
| | | | | |
Collapse
|
30
|
Challenges for modeling global gene regulatory networks during development: Insights from Drosophila. Dev Biol 2010; 340:161-9. [DOI: 10.1016/j.ydbio.2009.10.032] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2009] [Revised: 10/14/2009] [Accepted: 10/21/2009] [Indexed: 12/26/2022]
|
31
|
Mace DL, Varnado N, Zhang W, Frise E, Ohler U. Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images. ACTA ACUST UNITED AC 2009; 26:761-9. [PMID: 19942587 DOI: 10.1093/bioinformatics/btp658] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
MOTIVATION Recent advancements in high-throughput imaging have created new large datasets with tens of thousands of gene expression images. Methods for capturing these spatial and/or temporal expression patterns include in situ hybridization or fluorescent reporter constructs or tags, and results are still frequently assessed by subjective qualitative comparisons. In order to deal with available large datasets, fully automated analysis methods must be developed to properly normalize and model spatial expression patterns. RESULTS We have developed image segmentation and registration methods to identify and extract spatial gene expression patterns from RNA in situ hybridization experiments of Drosophila embryos. These methods allow us to normalize and extract expression information for 78,621 images from 3724 genes across six time stages. The similarity between gene expression patterns is computed using four scoring metrics: mean squared error, Haar wavelet distance, mutual information and spatial mutual information (SMI). We additionally propose a strategy to calculate the significance of the similarity between two expression images, by generating surrogate datasets with similar spatial expression patterns using a Monte Carlo swap sampler. On data from an early development time stage, we show that SMI provides the most biologically relevant metric of comparison, and that our significance testing generalizes metrics to achieve similar performance. We exemplify the application of spatial metrics on the well-known Drosophila segmentation network. AVAILABILITY A Java webstart application to register and compare patterns, as well as all source code, are available from: http://tools.genome.duke.edu/generegulation/image_analysis/insitu CONTACT uwe.ohler@duke.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Daniel L Mace
- Computational Biology and Bioinformatics Graduate Program, Duke University, Durham, NC 27708, USA
| | | | | | | | | |
Collapse
|
32
|
Zamparo L, Perkins TJ. Statistical lower bounds on protein copy number from fluorescence expression images. Bioinformatics 2009; 25:2670-6. [PMID: 19574287 PMCID: PMC2759547 DOI: 10.1093/bioinformatics/btp415] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2009] [Revised: 06/11/2009] [Accepted: 06/28/2009] [Indexed: 01/10/2023] Open
Abstract
MOTIVATION Fluorescence imaging has become a commonplace for quantitatively measuring mRNA or protein expression in cells and tissues. However, such expression data are usually relative-absolute concentrations or molecular copy numbers are typically not known. While this is satisfactory for many applications, for certain kinds of quantitative network modeling and analysis of expression noise, absolute measures of expression are necessary. RESULTS We propose two methods for estimating molecular copy numbers from single uncalibrated expression images of tissues. These methods rely on expression variability between cells, due either to steady-state fluctuations or unequal distribution of molecules during cell division, to make their estimates. We apply these methods to 152 protein fluorescence expression images of Drosophila melanogaster embryos during early development, generating copy number estimates for 14 genes in the segmentation network. We also analyze the effects of noise on our estimators and compare with empirical findings. Finally, we confirm an observation of Bar-Even et al., made in the much different setting of Saccharomyces cerevisiae, that steady-state expression variance tends to scale with mean expression. AVAILABILITY The data are all drawn from FlyEx (explained within), and is available at http://flyex.ams.sunysb.edu/FlyEx/.
Collapse
Affiliation(s)
- Lee Zamparo
- Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada
| | | |
Collapse
|
33
|
Ashyraliyev M, Siggens K, Janssens H, Blom J, Akam M, Jaeger J. Gene circuit analysis of the terminal gap gene huckebein. PLoS Comput Biol 2009; 5:e1000548. [PMID: 19876378 PMCID: PMC2760955 DOI: 10.1371/journal.pcbi.1000548] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2009] [Accepted: 09/28/2009] [Indexed: 12/24/2022] Open
Abstract
The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.
Collapse
Affiliation(s)
- Maksat Ashyraliyev
- Center for Mathematics and Computer Science, Centrum Wiskunde and Informatica, Amsterdam, The Netherlands
| | - Ken Siggens
- Laboratory for Development and Evolution, University Museum of Zoology, Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Hilde Janssens
- EMBL/CRG Research Unit in Systems Biology, CRG–Centre de Regulació Genòmica, Universitat Pompeu Fabra, Barcelona, Spain
| | - Joke Blom
- Center for Mathematics and Computer Science, Centrum Wiskunde and Informatica, Amsterdam, The Netherlands
| | - Michael Akam
- Laboratory for Development and Evolution, University Museum of Zoology, Department of Zoology, University of Cambridge, Cambridge, United Kingdom
| | - Johannes Jaeger
- Laboratory for Development and Evolution, University Museum of Zoology, Department of Zoology, University of Cambridge, Cambridge, United Kingdom
- EMBL/CRG Research Unit in Systems Biology, CRG–Centre de Regulació Genòmica, Universitat Pompeu Fabra, Barcelona, Spain
| |
Collapse
|
34
|
Kozlov KN, Myasnikova E, Samsonova AA, Surkova S, Reinitz J, Samsonova M. GCPReg package for registration of the segmentation gene expression data in Drosophila. Fly (Austin) 2009; 3:151-6. [PMID: 19550114 DOI: 10.4161/fly.8599] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
In modern functional genomics registration techniques areused to construct reference gene expression patterns and createa spatiotemporal atlas of the expression of all the genes in anetwork. In this paper we present a software package calledGCPReg, which can be used to register the expression patterns ofsegmentation genes in the early Drosophila embryo. The key task,which this package performs, is the extraction of spatially localizedcharacteristic features of expression patterns. To facilitatethis task, we have developed an easy-to-use interactive graphicalinterface. We describe GCPReg usage and demonstrate how thispackage can be applied to register gene expression patterns inwild type and mutants. GCPReg has been designed to operate ona UNIX platform and is freely available via the Internet at http://urchin.spbcas.ru/downloads/GCPReg/GCPReg.htm.
Collapse
Affiliation(s)
- Konstantin N Kozlov
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, St. Petersburg, Russia
| | | | | | | | | | | |
Collapse
|
35
|
Canalization of gene expression in the Drosophila blastoderm by gap gene cross regulation. PLoS Biol 2009; 7:e1000049. [PMID: 19750121 PMCID: PMC2653557 DOI: 10.1371/journal.pbio.1000049] [Citation(s) in RCA: 232] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2008] [Accepted: 01/14/2009] [Indexed: 11/18/2022] Open
Abstract
Developing embryos exhibit a robust capability to reduce phenotypic variations that occur naturally or as a result of experimental manipulation. This reduction in variation occurs by an epigenetic mechanism called canalization, a phenomenon which has resisted understanding because of a lack of necessary molecular data and of appropriate gene regulation models. In recent years, quantitative gene expression data have become available for the segment determination process in the Drosophila blastoderm, revealing a specific instance of canalization. These data show that the variation of the zygotic segmentation gene expression patterns is markedly reduced compared to earlier levels by the time gastrulation begins, and this variation is significantly lower than the variation of the maternal protein gradient Bicoid. We used a predictive dynamical model of gene regulation to study the effect of Bicoid variation on the downstream gap genes. The model correctly predicts the reduced variation of the gap gene expression patterns and allows the characterization of the canalizing mechanism. We show that the canalization is the result of specific regulatory interactions among the zygotic gap genes. We demonstrate the validity of this explanation by showing that variation is increased in embryos mutant for two gap genes, Krüppel and knirps, disproving competing proposals that canalization is due to an undiscovered morphogen, or that it does not take place at all. In an accompanying article in PLoS Computational Biology (doi:10.1371/journal.pcbi.1000303), we show that cross regulation between the gap genes causes their expression to approach dynamical attractors, reducing initial variation and providing a robust output. These results demonstrate that the Bicoid gradient is not sufficient to produce gap gene borders having the low variance observed, and instead this low variance is generated by gap gene cross regulation. More generally, we show that the complex multigenic phenomenon of canalization can be understood at a quantitative and predictive level by the application of a precise dynamical model. Animals have an astonishing ability to develop reliably in spite of variable conditions during embryogenesis. More than 60 years ago, it was proposed that this property of development, called canalization, results from genetic interactions that adjust biochemical reactions so as to bring about reliable outcomes. Since then, a great deal of progress has been made in understanding the buffering of genotypic and environmental variation, and individual mutations that reveal variation have been identified. However, the mechanisms by which genetic interactions produce canalization are not yet well understood, because this requires molecular data on multiple developmental determinants and models that correctly predict complex interactions. We make use of gene expression data at both high spatial and temporal resolution for the gap genes involved in the segmentation of Drosophila. We also apply a mathematical model to show that cross regulation among the gap genes is responsible for canalization in this system. Furthermore, the model predicted specific interactions that cause canalization, and the prediction was validated experimentally. Our results show that groups of genes can act on one another to reduce variation and highlights the importance of genetic networks in generating robust development. DuringDrosophila development, the expression patterns of gap genes are much less variable than the Bicoid morphogen gradient. Modeling and experiments show that this specific instance of canalization or developmental robustness occurs by gap gene cross regulation.
Collapse
|
36
|
Myasnikova E, Surkova S, Panok L, Samsonova M, Reinitz J. Estimation of errors introduced by confocal imaging into the data on segmentation gene expression in Drosophila. Bioinformatics 2009; 25:346-52. [PMID: 19052059 PMCID: PMC2639076 DOI: 10.1093/bioinformatics/btn620] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2008] [Revised: 11/25/2008] [Accepted: 11/27/2008] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Currently the confocal scanning microscopy of fluorescently tagged molecules is extensively employed to acquire quantitative data on gene expression at cellular resolution. Following this approach, we generated a large dataset on the expression of segmentation genes in the Drosophila blastoderm, that is widely used in systems biology studies. As data accuracy is of critical importance for the success of studies in this field, we took a shot to evaluate possible errors introduced in the data by acquisition and processing methods. This article deals with errors introduced by confocal microscope. RESULTS In confocal imaging, the inevitable photon noise is commonly reduced by the averaging of multiple frames. The averaging may introduce errors into the data, if single frames are clipped by microscope hardware. A method based on censoring technique is used to estimate and correct this type of errors. Additional source of errors is the quantification of blurred images. To estimate and correct these errors, the Richardson-Lucy deconvolution method was modified to provide the higher accuracy of data read off from blurred images of the Drosophila blastoderm. We have found that the sizes of errors introduced by confocal imaging make up approximately 5-7% of the mean intensity values and do not disguise the dynamic behavior and characteristic features of gene expression patterns. We also defined a range of microscope parameters for the acquisition of sufficiently accurate data. AVAILABILITY http://urchin.spbcas.ru/downloads/step/step.htm
Collapse
|
37
|
Ay A, Fakhouri WD, Chiu C, Arnosti DN. Image processing and analysis for quantifying gene expression from early Drosophila embryos. Tissue Eng Part A 2009; 14:1517-26. [PMID: 18687054 DOI: 10.1089/ten.tea.2008.0202] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Correlation of quantities of transcriptional activators and repressors with the mRNA output of target genes is a central issue for modeling gene regulation. In multicellular organisms, both spatial and temporal differences in gene expression must be taken into account; this can be achieved by use of in situ hybridization followed by confocal laser scanning microscopy (CLSM). Here we present a method to correlate the protein levels of the short-range repressor Giant with lacZ mRNA produced by reporter genes using images of Drosophila blastoderm embryos taken by CLSM. The image stacks from CLSM are processed using a semiautomatic algorithm to produce correlations between the repressor levels and lacZ mRNA reporter genes. We show that signals derived from CLSM are proportional to actual mRNA levels. Our analysis reveals that a suggested parabolic form of the background fluorescence in confocal images of early Drosophila embryos is evident most prominently in flattened specimens, with intact embryos exhibiting a more linear background. The data extraction described in this paper is primarily conceived for analysis of synthetic reporter genes that are designed to decipher cis-regulatory grammar, but the techniques are generalizable for quantitative analysis of other engineered or endogenous genes in embryos.
Collapse
Affiliation(s)
- Ahmet Ay
- Department of Mathematics, Michigan State University, East Lansing, Michigan, USA
| | | | | | | |
Collapse
|
38
|
Pisarev A, Poustelnikova E, Samsonova M, Reinitz J. FlyEx, the quantitative atlas on segmentation gene expression at cellular resolution. Nucleic Acids Res 2009; 37:D560-6. [PMID: 18953041 PMCID: PMC2686593 DOI: 10.1093/nar/gkn717] [Citation(s) in RCA: 110] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2008] [Revised: 09/29/2008] [Accepted: 09/30/2008] [Indexed: 11/13/2022] Open
Abstract
The datasets on gene expression are the valuable source of information about the functional state of an organism. Recently, we have acquired the large dataset on expression of segmentation genes in the Drosophila blastoderm. To provide efficient access to the data, we have developed the FlyEx database (http://urchin.spbcas.ru/flyex). FlyEx contains 4716 images of 14 segmentation gene expression patterns obtained from 1579 embryos and 9,500,000 quantitative data records. Reference data are available for all segmentation genes in cycles 11-13 and all temporal classes of cycle 14A. FlyEx supports operations on images of gene expression patterns. The database can be used to examine the quality of data, analyze the dynamics of formation of segmentation gene expression domains, as well as to estimate the variability of gene expression patterns. Currently, a user is able to monitor and analyze the dynamics of formation of segmentation gene expression domains over the whole period of segment determination, that amounts to 1.5 h of development. FlyEx supports the data downloads and construction of personal reference datasets, that makes it possible to more effectively use and analyze data.
Collapse
Affiliation(s)
- Andrei Pisarev
- Department of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg 195251, Russia and Department of Applied Mathematics and Statistics and Center for Developmental Genetics, Stony Brook University, NY 11794-3600, USA
| | - Ekaterina Poustelnikova
- Department of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg 195251, Russia and Department of Applied Mathematics and Statistics and Center for Developmental Genetics, Stony Brook University, NY 11794-3600, USA
| | - Maria Samsonova
- Department of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg 195251, Russia and Department of Applied Mathematics and Statistics and Center for Developmental Genetics, Stony Brook University, NY 11794-3600, USA
| | - John Reinitz
- Department of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg 195251, Russia and Department of Applied Mathematics and Statistics and Center for Developmental Genetics, Stony Brook University, NY 11794-3600, USA
| |
Collapse
|
39
|
Surkova SY, Myasnikova EM, Reinitz J, Samsonova MG. Dynamic filtration of the expression pattern variability of Drosophila zygotic segmentation genes. Biophysics (Nagoya-shi) 2008. [DOI: 10.1134/s0006350908030093] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
|
40
|
Spatial bistability generates hunchback expression sharpness in the Drosophila embryo. PLoS Comput Biol 2008; 4:e1000184. [PMID: 18818726 PMCID: PMC2527687 DOI: 10.1371/journal.pcbi.1000184] [Citation(s) in RCA: 60] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2007] [Accepted: 08/13/2008] [Indexed: 11/19/2022] Open
Abstract
During embryonic development, the positional information provided by concentration gradients of maternal factors directs pattern formation by providing spatially dependent cues for gene expression. In the fruit fly, Drosophila melanogaster, a classic example of this is the sharp on-off activation of the hunchback (hb) gene at midembryo, in response to local concentrations of the smooth anterior-posterior Bicoid (Bcd) gradient. The regulatory region for hb contains multiple binding sites for the Bcd protein as well as multiple binding sites for the Hb protein. Some previous studies have suggested that Bcd is sufficient for properly sharpened Hb expression, yet other evidence suggests a need for additional regulation. We experimentally quantified the dynamics of hb gene expression in flies that were wild-type, were mutant for hb self-regulation or Bcd binding, or contained an artificial promoter construct consisting of six Bcd and two Hb sites. In addition to these experiments, we developed a reaction-diffusion model of hb transcription, with Bcd cooperative binding and hb self-regulation, and used Zero Eigenvalue Analysis to look for multiple stationary states in the reaction network. Our model reproduces the hb developmental dynamics and correctly predicts the mutant patterns. Analysis of our model indicates that the Hb sharpness can be produced by spatial bistability, in which hb self-regulation produces two stable levels of expression. In the absence of self-regulation, the bistable behavior vanishes and Hb sharpness is disrupted. Bcd cooperative binding affects the position where bistability occurs but is not itself sufficient for a sharp Hb pattern. Our results show that the control of Hb sharpness and positioning, by hb self-regulation and Bcd cooperativity, respectively, are separate processes that can be altered independently. Our model, which matches the changes in Hb position and sharpness observed in different experiments, provides a theoretical framework for understanding the data and in particular indicates that spatial bistability can play a central role in threshold-dependent reading mechanisms of positional information.
Collapse
|
41
|
Surkova SY, Myasnikova EM, Kozlov KN, Samsonova AA, Reinitz J, Samsonova MG. Methods for Acquisition of Quantitative Data from Confocal Images of Gene Expression in situ. CELL AND TISSUE BIOLOGY 2008; 2:200-215. [PMID: 19343098 PMCID: PMC2630218 DOI: 10.1134/s1990519x08020156] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
In this review, we summarize original methods for the extraction of quantitative information from confocal images of gene-expression patterns. These methods include image segmentation, the extraction of quantitative numerical data on gene expression, and the removal of background signal and spatial registration. Finally, it is possible to construct a spatiotemporal atlas of gene expression from individual images recorded at each developmental stage. Initially all methods were developed to extract quantitative numerical information from confocal images of segmentation gene expression in Drosophila melanogaster. The application of these methods to Drosophila images makes it possible to reveal new mechanisms in the formation of segmentation gene expression domains, as well as to construct a quantitative atlas of segmentation gene expression. Most image processing procedures can be easily adapted to process a wide range of biological images.
Collapse
Affiliation(s)
- S. Yu. Surkova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, St. Petersburg, Russia
| | - E. M. Myasnikova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, St. Petersburg, Russia
| | - K. N. Kozlov
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, St. Petersburg, Russia
| | | | - J. Reinitz
- Department of Applied Mathematics and Statistics and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY
| | - M. G. Samsonova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, St. Petersburg, Russia
| |
Collapse
|
42
|
Surkova S, Myasnikova E, Janssens H, Kozlov KN, Samsonova AA, Reinitz J, Samsonova M. Pipeline for acquisition of quantitative data on segmentation gene expression from confocal images. Fly (Austin) 2008; 2:58-66. [PMID: 18820476 PMCID: PMC2803333 DOI: 10.4161/fly.6060] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
We describe a data pipeline developed to extract the quantitative data on segmentation gene expression from confocal images of gene expression patterns in Drosophila. The pipeline consists of five steps: image segmentation, background removal, temporal characterization of an embryo, data registration and data averaging. This pipeline was successfully applied to obtain quantitative gene expression data at cellular resolution in space and at the 6.5-minute resolution in time, as well as to construct a spatiotemporal atlas of segmentation gene expression. Each data pipeline step can be easily adapted to process a wide range of images of gene expression patterns.
Collapse
Affiliation(s)
- Svetlana Surkova
- Department of Computational Biology; Center for Advanced Studies; St. Petersburg State Polytechnical University; St. Petersburg, Russia
| | - Ekaterina Myasnikova
- Department of Computational Biology; Center for Advanced Studies; St. Petersburg State Polytechnical University; St. Petersburg, Russia
| | - Hilde Janssens
- FlyMine; Department of Genetics; University of Cambridge; Cambridge, United Kingdom
| | - Konstantin N. Kozlov
- Department of Computational Biology; Center for Advanced Studies; St. Petersburg State Polytechnical University; St. Petersburg, Russia
| | | | - John Reinitz
- Department of Applied Mathematics and Statistics and Center for Developmental Genetics; Stony Brook University; Stony Brook, New York USA
| | - Maria Samsonova
- Department of Computational Biology; Center for Advanced Studies; St. Petersburg State Polytechnical University; St. Petersburg, Russia
| |
Collapse
|
43
|
Surkova S, Kosman D, Kozlov K, Manu, Myasnikova E, Samsonova AA, Spirov A, Vanario-Alonso CE, Samsonova M, Reinitz J. Characterization of the Drosophila segment determination morphome. Dev Biol 2008; 313:844-62. [PMID: 18067886 PMCID: PMC2254320 DOI: 10.1016/j.ydbio.2007.10.037] [Citation(s) in RCA: 175] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2007] [Revised: 08/27/2007] [Accepted: 10/18/2007] [Indexed: 11/24/2022]
Abstract
Here we characterize the expression of the full system of genes which control the segmentation morphogenetic field of Drosophila at the protein level in one dimension. The data used for this characterization are quantitative with cellular resolution in space and about 6 min in time. We present the full quantitative profiles of all 14 segmentation genes which act before the onset of gastrulation. The expression patterns of these genes are first characterized in terms of their average or typical behavior. At this level, the expression of all of the genes has been integrated into a single atlas of gene expression in which the expression levels of all genes in each cell are specified. We show that expression domains do not arise synchronously, but rather each domain has its own specific dynamics of formation. Moreover, we show that the expression domains shift position in the direction of the cephalic furrow, such that domains in the anlage of the segmented germ band shift anteriorly while those in the presumptive head shift posteriorly. The expression atlas of integrated data is very close to the expression profiles of individual embryos during the latter part of the blastoderm stage. At earlier times gap gene domains show considerable variation in amplitude, and significant positional variability. Nevertheless, an average early gap domain is close to that of a median individual. In contrast, we show that there is a diversity of developmental trajectories among pair-rule genes at a variety of levels, including the order of domain formation and positional accuracy. We further show that this variation is dynamically reduced, or canalized, over time. As the first quantitatively characterized morphogenetic field, this system and its behavior constitute an extraordinarily rich set of materials for the study of canalization and embryonic regulation at the molecular level.
Collapse
Affiliation(s)
- Svetlana Surkova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg, 195251, Russia
| | - David Kosman
- Division of Biological Sciences, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0349, USA
| | - Konstantin Kozlov
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg, 195251, Russia
| | - Manu
- Department of Applied Mathematics and Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-3600, USA
| | - Ekaterina Myasnikova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg, 195251, Russia
| | - Anastasia A. Samsonova
- Department of Genetics, Harvard Medical School, 77 Avenue Louis Pasteur, Boston, MA 02115, USA
| | - Alexander Spirov
- Department of Applied Mathematics and Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-3600, USA
| | - Carlos E. Vanario-Alonso
- Instituto de Biofisica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Ave Brigadeiro Trompowsky, CCS BL-G, Rio de Janeiro, RJ 21949, Brazil
| | - Maria Samsonova
- Department of Computational Biology, Center for Advanced Studies, St. Petersburg State Polytechnical University, 29 Polytehnicheskaya Street, St. Petersburg, 195251, Russia
| | - John Reinitz
- Department of Applied Mathematics and Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-3600, USA
| |
Collapse
|
44
|
Wu YF, Myasnikova E, Reinitz J. Master equation simulation analysis of immunostained Bicoid morphogen gradient. BMC SYSTEMS BIOLOGY 2007; 1:52. [PMID: 18021413 PMCID: PMC2212647 DOI: 10.1186/1752-0509-1-52] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2007] [Accepted: 11/16/2007] [Indexed: 11/10/2022]
Abstract
Background The concentration gradient of Bicoid protein which determines the developmental pathways in early Drosophila embryo is the best characterized morphogen gradient at the molecular level. Because different developmental fates can be elicited by different concentrations of Bicoid, it is important to probe the limits of this specification by analyzing intrinsic fluctuations of the Bicoid gradient arising from small molecular number. Stochastic simulations can be applied to further the understanding of the dynamics of Bicoid morphogen gradient formation at the molecular number level, and determine the source of the nucleus-to-nucleus expression variation (noise) observed in the Bicoid gradient. Results We compared quantitative observations of Bicoid levels in immunostained Drosophila embryos with a spatially extended Master Equation model which represents diffusion, decay, and anterior synthesis. We show that the intrinsic noise of an autonomous reaction-diffusion gradient is Poisson distributed. We demonstrate how experimental noise can be identified in the logarithm domain from single embryo analysis, and then separated from intrinsic noise in the normalized variance domain of an ensemble statistical analysis. We show how measurement sensitivity affects our observations, and how small amounts of rescaling noise can perturb the noise strength (Fano factor) observed. We demonstrate that the biological noise level in data can serve as a physical constraint for restricting the model's parameter space, and for predicting the Bicoid molecular number and variation range. An estimate based on a low variance ensemble of embryos suggests that the steady-state Bicoid molecular number in a nucleus should be larger than 300 in the middle of the embryo, and hence the gradient should extend to the posterior end of the embryo, beyond the previously assumed background limit. We exhibit the predicted molecular number gradient together with measurement effects, and make a comparison between conditions of higher and lower variance respectively. Conclusion Quantitative comparison of Master Equation simulations with immunostained data enabled us to determine narrow ranges for key biophysical parameters, which for this system can be independently validated. Intrinsic noise is clearly detectable as well, although the staining process introduces certain limits in resolution.
Collapse
Affiliation(s)
- Yu Feng Wu
- Department of Applied Mathematics and Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-3600, USA.
| | | | | |
Collapse
|
45
|
PERKINS TJ. The Gap Gene System of Drosophila melanogaster: Model-Fitting and Validation. Ann N Y Acad Sci 2007; 1115:116-31. [DOI: 10.1196/annals.1407.015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
|
46
|
Luengo Hendriks CL, Keränen SVE, Fowlkes CC, Simirenko L, Weber GH, DePace AH, Henriquez C, Kaszuba DW, Hamann B, Eisen MB, Malik J, Sudar D, Biggin MD, Knowles DW. Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline. Genome Biol 2007; 7:R123. [PMID: 17184546 PMCID: PMC1794436 DOI: 10.1186/gb-2006-7-12-r123] [Citation(s) in RCA: 110] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2006] [Revised: 11/17/2006] [Accepted: 12/21/2006] [Indexed: 11/10/2022] Open
Abstract
A suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology with cellular resolution in whole Drosophila embryos is described. Background To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. Results Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. Conclusion The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks.
Collapse
Affiliation(s)
- Cris L Luengo Hendriks
- Berkeley Drosophila Transcription Network Project, Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Soile VE Keränen
- Berkeley Drosophila Transcription Network Project, Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Charless C Fowlkes
- Berkeley Drosophila Transcription Network Project, Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA
| | - Lisa Simirenko
- Berkeley Drosophila Transcription Network Project, Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Gunther H Weber
- Berkeley Drosophila Transcription Network Project, Institute for Data Analysis and Visualization, University of California, Davis, CA 95616, USA
| | - Angela H DePace
- Berkeley Drosophila Transcription Network Project, Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Clara Henriquez
- Berkeley Drosophila Transcription Network Project, Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - David W Kaszuba
- Berkeley Drosophila Transcription Network Project, Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Bernd Hamann
- Berkeley Drosophila Transcription Network Project, Institute for Data Analysis and Visualization, University of California, Davis, CA 95616, USA
| | - Michael B Eisen
- Berkeley Drosophila Transcription Network Project, Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Jitendra Malik
- Berkeley Drosophila Transcription Network Project, Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA 94720, USA
| | - Damir Sudar
- Berkeley Drosophila Transcription Network Project, Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - Mark D Biggin
- Berkeley Drosophila Transcription Network Project, Genomics Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| | - David W Knowles
- Berkeley Drosophila Transcription Network Project, Life Sciences Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA
| |
Collapse
|
47
|
Abstract
Morphogenetic fields are among the most fundamental concepts of embryology. However, they are also among the most ill-defined, since they consist of dynamic regulatory processes whose exact nature remains elusive. In order to achieve a more rigorous definition of a developmental field, Lewis Wolpert introduced the concept of positional information illustrated by his French Flag model. Here we argue that Wolpert's positional information - a static coordinate system defining a field - lacks essential properties of the original field concept. We show how data-driven mathematical modeling approaches now enable us to study regulatory processes in a way that is qualitatively different from our previous level of understanding. As an example, we review our recent analysis of segmentation gene expression in the blastoderm embryo of the fruit fly Drosophila melanogaster. Based on this analysis, we propose a revised French Flag, which incorporates the dynamic, feedback-driven nature of pattern formation in the Drosophila blastoderm.
Collapse
Affiliation(s)
- Johannes Jaeger
- Laboratory of Development and Evolution, Department of Zoology, University of Cambridge, Downing Street, Cambridge CB2 3EJ, UK.
| | | |
Collapse
|
48
|
Johannes J, Sharp DH, Reinitz J. Known maternal gradients are not sufficient for the establishment of gap domains in Drosophila melanogaster. Mech Dev 2006; 124:108-28. [PMID: 17196796 PMCID: PMC1992814 DOI: 10.1016/j.mod.2006.11.001] [Citation(s) in RCA: 59] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2006] [Revised: 11/06/2006] [Accepted: 11/08/2006] [Indexed: 12/22/2022]
Abstract
Gap genes are among the first transcriptional targets of maternal morphogen gradients in the early Drosophila embryo. However, it remains unclear whether these gradients are indeed sufficient to establish the boundaries of localized gap gene expression patterns. In this study, we address this question using gap gene circuits, which are data-driven mathematical tools for extracting regulatory information from quantitative wild-type gene expression data. We present new, quantitative data on the mRNA expression patterns for the gap genes Krüppel (Kr), knirps (kni) and giant (gt) during the early blastoderm stage of Drosophila development. This data set shows significant differences in timing of gap gene expression compared to previous observations, and reveals that early gap gene expression is highly variable in both space and time. Gene circuit models fit to this data set were used for a detailed regulatory analysis of early gap gene expression. Our analysis shows that the proper balance of maternal repression and activation is essential for the correct positioning of gap domains, and that such balance can only be achieved for early expression of kni. In contrast, our results suggest that early expression of gt requires local neutralization of repressive input in the anterior region of the embryo, and that known maternal gradients are completely insufficient to position the boundaries of the early central Kr domain, or in fact any Kr-like domain in the central region of the blastoderm embryo. Based on this, we propose that unknown additional regulators must be involved in early gap gene regulation.
Collapse
Affiliation(s)
- Jaeger Johannes
- Department of Applied Mathematics & Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-3600, USA
| | - David H. Sharp
- Chief Science Office, Los Alamos National Laboratory, Los Alamos, NM 87545, USA
| | - John Reinitz
- Department of Applied Mathematics & Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, NY 11794-3600, USA
- Corresponding author. Tel.: + 1 646 361 0821; Fax: +1 631 632 8490. Email address: (John Reinitz)
| |
Collapse
|
49
|
Holloway DM, Harrison LG, Kosman D, Vanario-Alonso CE, Spirov AV. Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products. Dev Dyn 2006; 235:2949-60. [PMID: 16960857 PMCID: PMC2254309 DOI: 10.1002/dvdy.20940] [Citation(s) in RCA: 49] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
We analyze the relation between maternal gradients and segmentation in Drosophila, by quantifying spatial precision in protein patterns. Segmentation is first seen in the striped expression patterns of the pair-rule genes, such as even-skipped (eve). We compare positional precision between Eve and the maternal gradients of Bicoid (Bcd) and Caudal (Cad) proteins, showing that Eve position could be initially specified by the maternal protein concentrations but that these do not have the precision to specify the mature striped pattern of Eve. By using spatial trends, we avoid possible complications in measuring single boundary precision (e.g., gap gene patterns) and can follow how precision changes in time. During nuclear cleavage cycles 13 and 14, we find that Eve becomes increasingly correlated with egg length, whereas Bcd does not. This finding suggests that the change in precision is part of a separation of segmentation from an absolute spatial measure, established by the maternal gradients, to one precise in relative (percent egg length) units.
Collapse
Affiliation(s)
- David M Holloway
- Mathematics Department, British Columbia Institute of Technology, Burnaby, BC, Canada.
| | | | | | | | | |
Collapse
|
50
|
Janssens H, Hou S, Jaeger J, Kim AR, Myasnikova E, Sharp D, Reinitz J. Quantitative and predictive model of transcriptional control of the Drosophila melanogaster even skipped gene. Nat Genet 2006; 38:1159-65. [PMID: 16980977 DOI: 10.1038/ng1886] [Citation(s) in RCA: 162] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2006] [Accepted: 08/17/2006] [Indexed: 01/21/2023]
Abstract
Here we present a quantitative and predictive model of the transcriptional readout of the proximal 1.7 kb of the control region of the Drosophila melanogaster gene even skipped (eve). The model is based on the positions and sequence of individual binding sites on the DNA and quantitative, time-resolved expression data at cellular resolution. These data demonstrated new expression features, first reported here. The model correctly predicts the expression patterns of mutations in trans, as well as point mutations, insertions and deletions in cis. It also shows that the nonclassical expression of stripe 7 driven by this fragment is activated by the protein Caudal (Cad), and repressed by the proteins Tailless (Tll) and Giant (Gt).
Collapse
Affiliation(s)
- Hilde Janssens
- Department of Applied Mathematics and Statistics, and Center for Developmental Genetics, Stony Brook University, Stony Brook, New York 11794-3600, USA
| | | | | | | | | | | | | |
Collapse
|