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Gap gene regulatory dynamics evolve along a genotype network

View ORCID ProfileAnton Crombach, View ORCID ProfileKarl R. Wotton, View ORCID ProfileEva Jiménez-Guri, View ORCID ProfileJohannes Jaeger
doi: https://doi.org/10.1101/024471
Anton Crombach
1EMBL/CRG Research Unit in Systems Biology, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona, Spain
2Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
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  • For correspondence: anton.crombach@crg.eu yogi.jaeger@crg.eu
Karl R. Wotton
1EMBL/CRG Research Unit in Systems Biology, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona, Spain
2Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
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Eva Jiménez-Guri
1EMBL/CRG Research Unit in Systems Biology, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona, Spain
2Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
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Johannes Jaeger
1EMBL/CRG Research Unit in Systems Biology, Centre for Genomic Regulation (CRG), Dr. Aiguader 88, 08003 Barcelona, Spain
2Universitat Pompeu Fabra (UPF), 08002 Barcelona, Spain
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  • For correspondence: anton.crombach@crg.eu yogi.jaeger@crg.eu
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Abstract

Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift”. System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the non-model scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them to an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability).

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Posted August 12, 2015.
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Gap gene regulatory dynamics evolve along a genotype network
Anton Crombach, Karl R. Wotton, Eva Jiménez-Guri, Johannes Jaeger
bioRxiv 024471; doi: https://doi.org/10.1101/024471
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Gap gene regulatory dynamics evolve along a genotype network
Anton Crombach, Karl R. Wotton, Eva Jiménez-Guri, Johannes Jaeger
bioRxiv 024471; doi: https://doi.org/10.1101/024471

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