Though the problem of pattern formation in biological systems has been studied for more than sixty years, it is from the beginning of this century that the synergy between theoretical and experimental researchers are depicting the ins and outs of this problem . In the present work we are deciphering the bases of the pattern for the ocellar complex formation in Drosophila melanogaster fly. We have modeled the Gene Regulatory Network (GRN ) that drives the development of this visual system pruning this network to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of an activator-repressor feedback loop fed by a morphogenetic gradient  in a French flag problem fashion. We determine that this pattern is robust agains perturbations in the structure of the equations used to describe the system. Moreover, a Boolean modeling of the GRN confirms the robustness in the patterning mechanism  for different network complexity levels. Interestingly, the Boolean networks analysis reveals a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli  .
URLanogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of URLanisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species . In the present work we analyze the robustness of the patterning for the ocellar complex formation in Drosophila melanogaster fly. We have systematically pruned the GRN that drives the development of this visual system to obtain the minimum pathway able to satisfy this pattern. We found that the mechanism underlying the patterning obeys to the dynamics of a 3-nodes network motif with a double negative feedback loop fed by a morphogenetic gradient that triggers the inhibition in a French flag problem fashion. A Boolean modeling of the GRN confirms robustness in the patterning mechanism showing the same result for different network complexity levels. Interestingly, the network provides a steady state solution in the interocellar part of the patterning and an oscillatory regime in the ocelli . This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation .
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Though the problem of pattern formation in biological systems has been studied for more than sixty years, it is from the beginning of this century that the synergy between theoretical and experimental researchers are depicting the ins and outs of this problem
URLanogenesis, developmental programs governed by Gene Regulatory Networks (GRN) define the functionality, size and shape of the different constituents of URLanisms. Robustness, thus, is an essential characteristic that GRNs need to fulfill in order to maintain viability and reproducibility in a species
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are deciphering the bases of the pattern
analyze the robustness of the patterning
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modeled the Gene Regulatory Network (GRN )
systematically pruned the GRN
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pruning this network
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an activator-repressor
a 3-nodes network motif with a double negative
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that triggers the inhibition
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We determine that this pattern is robust agains perturbations in the structure of the equations used to describe the system. Moreover, a
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the
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showing the same result
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Boolean networks analysis reveals
network provides
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. This theoretical result predicts that the ocellar pattern may underlie oscillatory dynamics in its genetic regulation