scholarly journals Nasoniasegmentation is regulated by an ancestral insect segmentation regulatory network also present in flies

2021 ◽  
Author(s):  
S E Taylor ◽  
P K Dearden
Keyword(s):  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Single Gene ◽  
Genetic Regulation ◽  
Nasonia Vitripennis ◽  
Genetic Changes ◽  
Parasteatoda Tepidariorum ◽  
Simulation Based ◽  
Gene Regulatory ◽  
Pair Rule

AbstractInsect segmentation is a well-studied and tractable system with which to investigate the genetic regulation of development. Though insects segment their germband using a variety of methods, modelling work implies that a single gene regulatory network can underpin the two main types of insect segmentation. This means limited genetic changes are required to explain significant differences in segmentation mode between different insects. Evidence for this idea is limited toDrosophila melanogaster, Tribolium castaneum, and the spiderParasteatoda tepidariorum, and the nature of the gene regulatory network (GRN) underlying this model has not been tested. Some insects, for exampleNasonia vitripennisandApis melliferasegment progressively, a pattern not examined in studies of this segmentation model, producing stripes at different times throughout the embryo, but not from a segment addition zone.Here we aim to understand the GRNs patterningNasoniausing a simulation-based approach. We found that an existing model ofDrosophilasegmentation (Clark, 2017) can be used to recapitulateNasonia’s progressive segmentation, if provided with altered inputs in the form of expression of the timer genesNν-caudalandNν-odd paired. We also predict limited topological changes to the pair rule network. Together this implies that very limited changes to theDrosophilanetwork are required to simulateNasoniasegmentation, despite the differences in segmentation modes, implying thatNasoniause a very similar version of an ancestral GRN also used byDrosophila.

scholarly journals Odd-paired controls frequency doubling in Drosophila segmentation by altering the pair-rule gene regulatory network

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Erik Clark ◽  
Michael Akam
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Frequency Doubling ◽  
Drosophila Embryo ◽  
Anteroposterior Patterning ◽  
Regulatory Interactions ◽  
Pair Rule Gene ◽  
Gene Regulatory ◽  
Pair Rule

The Drosophila embryo transiently exhibits a double-segment periodicity, defined by the expression of seven 'pair-rule' genes, each in a pattern of seven stripes. At gastrulation, interactions between the pair-rule genes lead to frequency doubling and the patterning of 14 parasegment boundaries. In contrast to earlier stages of Drosophila anteroposterior patterning, this transition is not well understood. By carefully analysing the spatiotemporal dynamics of pair-rule gene expression, we demonstrate that frequency-doubling is precipitated by multiple coordinated changes to the network of regulatory interactions between the pair-rule genes. We identify the broadly expressed but temporally patterned transcription factor, Odd-paired (Opa/Zic), as the cause of these changes, and show that the patterning of the even-numbered parasegment boundaries relies on Opa-dependent regulatory interactions. Our findings indicate that the pair-rule gene regulatory network has a temporally modulated topology, permitting the pair-rule genes to play stage-specific patterning roles.

scholarly journals Odd-paired controls frequency doubling in Drosophila segmentation by altering the pair-rule gene regulatory network

2016 ◽  
Author(s):  
Erik Clark ◽  
Michael Akam
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Frequency Doubling ◽  
Anteroposterior Patterning ◽  
Regulatory Interactions ◽  
Pair Rule Gene ◽  
Gene Regulatory ◽  
Pair Rule

ABSTRACTThe Drosophila embryo transiently exhibits a double segment periodicity, defined by the expression of seven “pair-rule” genes, each in a pattern of seven stripes. At gastrulation, interactions between the pair-rule genes lead to frequency doubling and the patterning of fourteen parasegment boundaries. In contrast to earlier stages of Drosophila anteroposterior patterning, this transition is not well understood. By carefully analysing the spatiotemporal dynamics of pair-rule gene expression, we demonstrate that frequency-doubling is precipitated by multiple coordinated changes to the network of regulatory interactions between the pair-rule genes. We identify the broadly expressed but temporally patterned transcription factor, Odd-paired (Opa/Zic), as the cause of these changes, and show that the patterning of the even-numbered parasegment boundaries relies on Opa-dependent regulatory interactions. Our findings indicate that the pair-rule gene regulatory network has a temporally-modulated topology, permitting the pair-rule genes to play stage-specific patterning roles.

scholarly journals Heterosis Related to Fitness and Phenotypic Variance in the Evolution of Diploid Gene Regulatory Network

2021 ◽  
Author(s):  
Kenji Okubo ◽  
Kunihiko Kaneko
Keyword(s):  
Gene Expression ◽  
Gene Regulatory Network ◽  
Regulatory Network ◽  
Single Gene ◽  
Gene Expression Pattern ◽  
Quantitative Agreement ◽  
Hybrid Population ◽  
Noise Robustness ◽  
Phenotypic Variance ◽  
Gene Regulatory

Heterosis describes the phenomenon whereby a hybrid population has higher fitness than an inbred population, and has previously been explained by either Mendelian dominance or overdominance, where it is generally assumed that one gene controls one trait. However, recent studies have demonstrated that genes interact through a complex gene regulatory network (GRN). Furthermore, phenotypic variance due to noise is reportedly lower for heterozygotes, whereas the origin of such variance-related heterosis remains elusive. Therefore, a theoretical analysis linking heterosis to GRN evolution and stochastic gene expression dynamics is required. Here, we investigate heterosis related to fitness and phenotypic variance in a system with interacting genes, by numerically evolving diploid GRNs. According to the results, the heterozygote population exhibited higher fitness than the homozygote population, that is, fitness-related heterosis resulting from evolution. In addition, the heterozygote population expressed lower noise-related phenotypic variance in expression levels than the homozygous population, implying that the heterozygote population is more robust to noise. Furthermore, the distribution of the ratio of heterozygote phenotypic variance to homozygote phenotypic variance exhibited quantitative agreement with previous experimental results. By applying dominance and overdominance to the gene expression pattern rather than only a single gene expression, we confirmed the correlation between heterosis and overdominance. We explain our results by proposing that the convex high-fitness region is evolutionarily shaped in the genetic space to gain noise robustness under genetic mixing through sexual reproduction.

scholarly journals Two different modes of oscillation in a gene transcription regulatory network with interlinked positive and negative feedback loops

2016 ◽  
Vol 27 (05) ◽  
pp. 1650056 ◽  
Author(s):  
Rajesh Karmakar
Keyword(s):  
Gene Regulatory Network ◽  
Negative Feedback ◽  
Regulatory Network ◽  
Single Gene ◽  
Oscillatory Behavior ◽  
Feedback Loops ◽  
Additional Advantage ◽  
Wide Range ◽  
Positive And Negative Feedback ◽  
Gene Regulatory

We study the oscillatory behavior of a gene regulatory network with interlinked positive and negative feedback loop. The frequency and amplitude are two important properties of oscillation. The studied network produces two different modes of oscillation. In one mode (mode-I), frequency of oscillation remains constant over a wide range of amplitude and in the other mode (mode-II) the amplitude of oscillation remains constant over a wide range of frequency. Our study reproduces both features of oscillations in a single gene regulatory network and shows that the negative plus positive feedback loops in gene regulatory network offer additional advantage. We identified the key parameters/variables responsible for different modes of oscillation. The network is flexible in switching between different modes by choosing appropriately the required parameters/variables.

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