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Milocco L, Uller T. Utilizing developmental dynamics for evolutionary prediction and control. Proc Natl Acad Sci U S A 2024; 121:e2320413121. [PMID: 38530898 PMCID: PMC10998628 DOI: 10.1073/pnas.2320413121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 02/20/2024] [Indexed: 03/28/2024] Open
Abstract
Understanding, predicting, and controlling the phenotypic consequences of genetic and environmental change is essential to many areas of fundamental and applied biology. In evolutionary biology, the generative process of development is a major source of organismal evolvability that constrains or facilitates adaptive change by shaping the distribution of phenotypic variation that selection can act upon. While the complex interactions between genetic and environmental factors during development may appear to make it impossible to infer the consequences of perturbations, the persistent observation that many perturbations result in similar phenotypes indicates that there is a logic to what variation is generated. Here, we show that a general representation of development as a dynamical system can reveal this logic. We build a framework that allows predicting the phenotypic effects of perturbations, and conditions for when the effects of perturbations of different origins are concordant. We find that this concordance is explained by two generic features of development, namely the dynamical dependence of the phenotype on itself and the fact that all perturbations must affect the developmental process to have an effect on the phenotype. We apply our theoretical framework to classical models of development and show that it can be used to predict the evolutionary response to selection using information of plasticity and to accelerate evolution in a desired direction. The framework we introduce provides a way to quantitatively interchange perturbations, opening an avenue of perturbation design to control the generation of variation.
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Affiliation(s)
| | - Tobias Uller
- Department of Biology, Lund University, 223 62Lund, Sweden
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2
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Schmitt MS, Colen J, Sala S, Devany J, Seetharaman S, Caillier A, Gardel ML, Oakes PW, Vitelli V. Machine learning interpretable models of cell mechanics from protein images. Cell 2024; 187:481-494.e24. [PMID: 38194965 DOI: 10.1016/j.cell.2023.11.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Revised: 09/20/2023] [Accepted: 11/29/2023] [Indexed: 01/11/2024]
Abstract
Cellular form and function emerge from complex mechanochemical systems within the cytoplasm. Currently, no systematic strategy exists to infer large-scale physical properties of a cell from its molecular components. This is an obstacle to understanding processes such as cell adhesion and migration. Here, we develop a data-driven modeling pipeline to learn the mechanical behavior of adherent cells. We first train neural networks to predict cellular forces from images of cytoskeletal proteins. Strikingly, experimental images of a single focal adhesion (FA) protein, such as zyxin, are sufficient to predict forces and can generalize to unseen biological regimes. Using this observation, we develop two approaches-one constrained by physics and the other agnostic-to construct data-driven continuum models of cellular forces. Both reveal how cellular forces are encoded by two distinct length scales. Beyond adherent cell mechanics, our work serves as a case study for integrating neural networks into predictive models for cell biology.
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Affiliation(s)
- Matthew S Schmitt
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA; Department of Physics, University of Chicago, Chicago, IL 60637, USA; Kadanoff Center for Theoretical Physics, University of Chicago, Chicago, IL 60637, USA
| | - Jonathan Colen
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA; Department of Physics, University of Chicago, Chicago, IL 60637, USA; Kadanoff Center for Theoretical Physics, University of Chicago, Chicago, IL 60637, USA
| | - Stefano Sala
- Department of Cell & Molecular Physiology, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153, USA
| | - John Devany
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA; Department of Physics, University of Chicago, Chicago, IL 60637, USA
| | - Shailaja Seetharaman
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA; Department of Physics, University of Chicago, Chicago, IL 60637, USA
| | - Alexia Caillier
- Department of Cell & Molecular Physiology, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153, USA
| | - Margaret L Gardel
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA; Department of Physics, University of Chicago, Chicago, IL 60637, USA.
| | - Patrick W Oakes
- Department of Cell & Molecular Physiology, Stritch School of Medicine, Loyola University Chicago, Maywood, IL 60153, USA.
| | - Vincenzo Vitelli
- James Franck Institute, University of Chicago, Chicago, IL 60637, USA; Department of Physics, University of Chicago, Chicago, IL 60637, USA; Kadanoff Center for Theoretical Physics, University of Chicago, Chicago, IL 60637, USA.
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3
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Jordan DJ, Miska EA. Canalisation and plasticity on the developmental manifold of Caenorhabditis elegans. Mol Syst Biol 2023; 19:e11835. [PMID: 37850520 PMCID: PMC10632735 DOI: 10.15252/msb.202311835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/26/2023] [Accepted: 10/05/2023] [Indexed: 10/19/2023] Open
Abstract
How do the same mechanisms that faithfully regenerate complex developmental programmes in spite of environmental and genetic perturbations also allow responsiveness to environmental signals, adaptation and genetic evolution? Using the nematode Caenorhabditis elegans as a model, we explore the phenotypic space of growth and development in various genetic and environmental contexts. Our data are growth curves and developmental parameters obtained by automated microscopy. Using these, we show that among the traits that make up the developmental space, correlations within a particular context are predictive of correlations among different contexts. Furthermore, we find that the developmental variability of this animal can be captured on a relatively low-dimensional phenotypic manifold and that on this manifold, genetic and environmental contributions to plasticity can be deconvolved independently. Our perspective offers a new way of understanding the relationship between robustness and flexibility in complex systems, suggesting that projection and concentration of dimension can naturally align these forces as complementary rather than competing.
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Affiliation(s)
- David J Jordan
- Department of BiochemistryUniversity of CambridgeCambridgeUK
| | - Eric A Miska
- Department of BiochemistryUniversity of CambridgeCambridgeUK
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Piccinali RV, Gaspe MS, Nattero J, Gürtler RE. Population structure and migration in Triatoma infestans (Hemiptera: Reduviidae) from the Argentine Chaco: An integration of genetic and morphometric data. Acta Trop 2023; 247:107010. [PMID: 37666351 DOI: 10.1016/j.actatropica.2023.107010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/25/2023] [Accepted: 08/28/2023] [Indexed: 09/06/2023]
Abstract
Genetic and morphological structure of vector populations are useful to identify panmictic groups, reinfestation sources and minimal units for control interventions. Currently, no studies have integrated genetic and morphometric data in Triatoma infestans (Hemiptera: Reduviidae), one of the main vectors of Trypanosoma cruzi. We characterized the genetic and phenotypic structure of T. infestans at a small spatial scale (2-8 km), identified potential migrants and compared flight-related traits among genetic groups and between migrant and non-migrant insects in a well-defined area without insecticide spraying in the previous 12 years. We obtained microsatellite genotypes (N = 303), wing shape and size (N = 164) and body weight-to-length ratios (N = 188) in T. infestans from 11 houses in Pampa del Indio, Argentine Chaco. The uppermost level of genetic structuring partially agreed with the morphological groups, showing high degrees of substructuring. The genetic structure showed a clear spatial pattern around Route 3 and one genetic group overlapped with an area of persistent infestation and insecticide resistance. Females harboured more microsatellite alleles than males, which showed signs of isolation-by-distance. Wing shape discriminant analyses of genetic groups revealed low reclassification scores whereas wing size differed among genetic groups for both sexes. Potential migrants (8%) did not differ from non-migrants in sex, ecotope, wing shape and size. However, male migrants had lower W/L than non-migrants suggesting poorer nutritional state. Our findings may contribute to the understanding of population characteristics, dispersal dynamics and ongoing elimination efforts of T. infestans.
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Affiliation(s)
- Romina V Piccinali
- Facultad de Ciencias Exactas y Naturales, Departamento de Ecología, Genética y Evolución. Laboratorio de Eco-Epidemiología. Intendente Güiraldes 2160, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina; CONICET-Universidad de Buenos Aires. Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Intendente Güiraldes 2160, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina.
| | - M Sol Gaspe
- Facultad de Ciencias Exactas y Naturales, Departamento de Ecología, Genética y Evolución. Laboratorio de Eco-Epidemiología. Intendente Güiraldes 2160, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina; CONICET-Universidad de Buenos Aires. Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Intendente Güiraldes 2160, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina
| | - Julieta Nattero
- Facultad de Ciencias Exactas y Naturales, Departamento de Ecología, Genética y Evolución. Laboratorio de Eco-Epidemiología. Intendente Güiraldes 2160, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina; CONICET-Universidad de Buenos Aires. Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Intendente Güiraldes 2160, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina
| | - Ricardo E Gürtler
- Facultad de Ciencias Exactas y Naturales, Departamento de Ecología, Genética y Evolución. Laboratorio de Eco-Epidemiología. Intendente Güiraldes 2160, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina; CONICET-Universidad de Buenos Aires. Instituto de Ecología, Genética y Evolución de Buenos Aires (IEGEBA), Intendente Güiraldes 2160, Ciudad Universitaria, Pabellón 2, Ciudad Autónoma de Buenos Aires C1428EGA, Argentina
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5
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Machado FA, Mongle CS, Slater G, Penna A, Wisniewski A, Soffin A, Dutra V, Uyeda JC. Rules of teeth development align microevolution with macroevolution in extant and extinct primates. Nat Ecol Evol 2023; 7:1729-1739. [PMID: 37652997 DOI: 10.1038/s41559-023-02167-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 07/17/2023] [Indexed: 09/02/2023]
Abstract
Macroevolutionary biologists have classically rejected the notion that higher-level patterns of divergence arise through microevolutionary processes acting within populations. For morphology, this consensus partly derives from the inability of quantitative genetics models to correctly predict the behaviour of evolutionary processes at the scale of millions of years. Developmental studies (evo-devo) have been proposed to reconcile micro- and macroevolution. However, there has been little progress in establishing a formal framework to apply evo-devo models of phenotypic diversification. Here we reframe this issue by asking whether using evo-devo models to quantify biological variation can improve the explanatory power of comparative models, thus helping us bridge the gap between micro- and macroevolution. We test this prediction by evaluating the evolution of primate lower molars in a comprehensive dataset densely sampled across living and extinct taxa. Our results suggest that biologically informed morphospaces alongside quantitative genetics models allow a seamless transition between the micro- and macroscales, whereas biologically uninformed spaces do not. We show that the adaptive landscape for primate teeth is corridor like, with changes in morphology within the corridor being nearly neutral. Overall, our framework provides a basis for integrating evo-devo into the modern synthesis, allowing an operational way to evaluate the ultimate causes of macroevolution.
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Affiliation(s)
- Fabio A Machado
- Department of Integrative Biology, Oklahoma State University, Stillwater, OK, USA.
| | - Carrie S Mongle
- Department of Anthropology, Stony Brook University, Stony Brook, NY, USA
- Turkana Basin Institute, Stony Brook University, Stony Brook, NY, USA
| | - Graham Slater
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Anna Penna
- Department of Anthropology, University of Texas at San Antonio, San Antonio, TX, USA
| | - Anna Wisniewski
- Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA
| | - Anna Soffin
- Department of Biology, Virginia Tech, Blacksburg, VA, USA
| | - Vitor Dutra
- Department of Anthropology, Florida Atlantic University, Boca Raton, FL, USA
| | - Josef C Uyeda
- Department of Biology, Virginia Tech, Blacksburg, VA, USA
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Skinner DJ, Jeckel H, Martin AC, Drescher K, Dunkel J. Topological packing statistics of living and nonliving matter. SCIENCE ADVANCES 2023; 9:eadg1261. [PMID: 37672580 PMCID: PMC10482333 DOI: 10.1126/sciadv.adg1261] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 07/27/2023] [Indexed: 09/08/2023]
Abstract
Complex disordered matter is of central importance to a wide range of disciplines, from bacterial colonies and embryonic tissues in biology to foams and granular media in materials science to stellar configurations in astrophysics. Because of the vast differences in composition and scale, comparing structural features across such disparate systems remains challenging. Here, by using the statistical properties of Delaunay tessellations, we introduce a mathematical framework for measuring topological distances between general three-dimensional point clouds. The resulting system-agnostic metric reveals subtle structural differences between bacterial biofilms as well as between zebrafish brain regions, and it recovers temporal ordering of embryonic development. We apply the metric to construct a universal topological atlas encompassing bacterial biofilms, snowflake yeast, plant shoots, zebrafish brain matter, organoids, and embryonic tissues as well as foams, colloidal packings, glassy materials, and stellar configurations. Living systems localize within a bounded island-like region of the atlas, reflecting that biological growth mechanisms result in characteristic topological properties.
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Affiliation(s)
- Dominic J Skinner
- Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
- NSF-Simons Center for Quantitative Biology, Northwestern University, 2205 Tech Drive, Evanston, IL 60208, USA
| | - Hannah Jeckel
- Department of Physics, Philipps-Universität Marburg, Renthof 6, 35032 Marburg, Germany
- Biozentrum, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland
| | - Adam C Martin
- Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Ave., Cambridge, MA 02139, USA
| | - Knut Drescher
- Biozentrum, University of Basel, Spitalstrasse 41, 4056 Basel, Switzerland
| | - Jörn Dunkel
- Department of Mathematics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
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Mongle CS, Nesbitt A, Machado FA, Smaers JB, Turner AH, Grine FE, Uyeda JC. A common mechanism drives the alignment between the micro- and macroevolution of primate molars. Evolution 2022; 76:2975-2985. [PMID: 36005286 DOI: 10.1111/evo.14600] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/25/2022] [Accepted: 08/01/2022] [Indexed: 01/22/2023]
Abstract
A central challenge for biology is to reveal how different levels of biological variation interact and shape diversity. However, recent experimental studies have indicated that prevailing models of evolution cannot readily explain the link between micro- and macroevolution at deep timescales. Here, we suggest that this paradox could be the result of a common mechanism driving a correlated pattern of evolution. We examine the proportionality between genetic variance and patterns of trait evolution in a system whose developmental processes are well understood to gain insight into how such alignment between morphological divergence and genetic variation might be maintained over macroevolutionary time. Primate molars present a model system by which to link developmental processes to evolutionary dynamics because of the biased pattern of variation that results from the developmental architecture regulating their formation. We consider how this biased variation is expressed at the population level, and how it manifests through evolution across primates. There is a strong correspondence between the macroevolutionary rates of primate molar divergence and their genetic variation. This suggests a model of evolution in which selection is closely aligned with the direction of genetic variance, phenotypic variance, and the underlying developmental architecture of anatomical traits.
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Affiliation(s)
- Carrie S Mongle
- Department of Anthropology, Stony Brook University, Stony Brook, New York, 11794.,Division of Anthropology, American Museum of Natural History, New York, New York, 10024.,Turkana Basin Institute, Stony Brook University, Stony Brook, New York, 11794
| | - Allison Nesbitt
- Department of Pathology and Anatomical Sciences, University of Missouri, Columbia, Missouri, 65212
| | - Fabio A Machado
- Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061
| | - Jeroen B Smaers
- Department of Anthropology, Stony Brook University, Stony Brook, New York, 11794
| | - Alan H Turner
- Department of Anatomical Sciences, Stony Brook University, Stony Brook, New York, 11794
| | - Frederick E Grine
- Department of Anthropology, Stony Brook University, Stony Brook, New York, 11794.,Department of Anatomical Sciences, Stony Brook University, Stony Brook, New York, 11794
| | - Josef C Uyeda
- Department of Biological Sciences, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, 24061
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8
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Walker RF. A Mechanistic Theory of Development-Aging Continuity in Humans and Other Mammals. Cells 2022; 11:cells11050917. [PMID: 35269539 PMCID: PMC8909351 DOI: 10.3390/cells11050917] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 02/26/2022] [Accepted: 02/28/2022] [Indexed: 12/29/2022] Open
Abstract
There is consensus among biogerontologists that aging occurs either as the result of a purposeful genome-based, evolved program or due to spontaneous, randomly occurring, maladaptive events. Neither concept has yet identified a specific mechanism to explain aging’s emergence and acceleration during mid-life and beyond. Presented herein is a novel, unifying mechanism with empirical evidence that describes how aging becomes continuous with development. It assumes that aging emerges from deterioration of a regulatory process that directs morphogenesis and morphostasis. The regulatory system consists of a genome-wide “backbone” within which its specific genes are differentially expressed by the local epigenetic landscapes of cells and tissues within which they reside, thereby explaining its holistic nature. Morphostasis evolved in humans to ensure the nurturing of dependent offspring during the first decade of young adulthood when peak parental vitality prevails in the absence of aging. The strict redundancy of each morphostasis regulatory cycle requires sensitive dependence upon initial conditions to avoid initiating deterministic chaos behavior. However, when natural selection declines as midlife approaches, persistent, progressive, and specific DNA damage and misrepair changes the initial conditions of the regulatory process, thereby compromising morphostasis regulatory redundancy, instigating chaos, initiating senescence, and accelerating aging thereafter.
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Gopalakrishnappa C, Gowda K, Prabhakara KH, Kuehn S. An ensemble approach to the structure-function problem in microbial communities. iScience 2022; 25:103761. [PMID: 35141504 PMCID: PMC8810406 DOI: 10.1016/j.isci.2022.103761] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
The metabolic activity of microbial communities plays a primary role in the flow of essential nutrients throughout the biosphere. Molecular genetics has revealed the metabolic pathways that model organisms utilize to generate energy and biomass, but we understand little about how the metabolism of diverse, natural communities emerges from the collective action of its constituents. We propose that quantifying and mapping metabolic fluxes to sequencing measurements of genomic, taxonomic, or transcriptional variation across an ensemble of diverse communities, either in the laboratory or in the wild, can reveal low-dimensional descriptions of community structure that can explain or predict their emergent metabolic activity. We survey the types of communities for which this approach might be best suited, review the analytical techniques available for quantifying metabolite fluxes in communities, and discuss what types of data analysis approaches might be lucrative for learning the structure-function mapping in communities from these data.
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Affiliation(s)
| | - Karna Gowda
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA
- Center for the Physics of Evolving Systems, University of Chicago, Chicago, IL 60637, USA
| | - Kaumudi H. Prabhakara
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA
- Center for the Physics of Evolving Systems, University of Chicago, Chicago, IL 60637, USA
| | - Seppe Kuehn
- Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA
- Center for the Physics of Evolving Systems, University of Chicago, Chicago, IL 60637, USA
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Alba V, Carthew JE, Carthew RW, Mani M. Global constraints within the developmental program of the Drosophila wing. eLife 2021; 10:66750. [PMID: 34180394 PMCID: PMC8257256 DOI: 10.7554/elife.66750] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 06/25/2021] [Indexed: 12/23/2022] Open
Abstract
Organismal development is a complex process, involving a vast number of molecular constituents interacting on multiple spatio-temporal scales in the formation of intricate body structures. Despite this complexity, development is remarkably reproducible and displays tolerance to both genetic and environmental perturbations. This robustness implies the existence of hidden simplicities in developmental programs. Here, using the Drosophila wing as a model system, we develop a new quantitative strategy that enables a robust description of biologically salient phenotypic variation. Analyzing natural phenotypic variation across a highly outbred population and variation generated by weak perturbations in genetic and environmental conditions, we observe a highly constrained set of wing phenotypes. Remarkably, the phenotypic variants can be described by a single integrated mode that corresponds to a non-intuitive combination of structural variations across the wing. This work demonstrates the presence of constraints that funnel environmental inputs and genetic variation into phenotypes stretched along a single axis in morphological space. Our results provide quantitative insights into the nature of robustness in complex forms while yet accommodating the potential for evolutionary variations. Methodologically, we introduce a general strategy for finding such invariances in other developmental contexts.
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Affiliation(s)
- Vasyl Alba
- Department of Engineering Sciences and Applied Mathematics, Northwestern UniversityEvanstonUnited States,NSF-Simons Center for Quantitative Biology, Northwestern UniversityEvanstonUnited States
| | - James E Carthew
- Department of Engineering Sciences and Applied Mathematics, Northwestern UniversityEvanstonUnited States
| | - Richard W Carthew
- NSF-Simons Center for Quantitative Biology, Northwestern UniversityEvanstonUnited States,Department of Molecular Biosciences, Northwestern UniversityEvanstonUnited States
| | - Madhav Mani
- Department of Engineering Sciences and Applied Mathematics, Northwestern UniversityEvanstonUnited States,NSF-Simons Center for Quantitative Biology, Northwestern UniversityEvanstonUnited States,Department of Molecular Biosciences, Northwestern UniversityEvanstonUnited States
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