A quantitative validated model reveals two phases of transcriptional regulation for the gap gene giant in Drosophila

Multifaceted effects on even-skipped transcriptional dynamics upon Krüppel dosage changes

Although fluctuations in transcription factor (TF) dosage are often well tolerated, TF dosage modulation can change the target gene expression dynamics and result in significant non-lethal developmental phenotypes. Using MS2/MCP-mediated quantitative live imaging in early Drosophila embryos, we analyzed how changing levels of the gap gene Krüppel (Kr) affects transcriptional dynamics of the pair-rule gene even-skipped (eve). Halving the Kr dosage leads to a transient posterior expansion of the eve stripe 2 and an anterior shift of stripe 5. Surprisingly, the most significant changes are observed in eve stripes 3 and 4, the enhancers of which do not contain Kr-binding sites. In Kr heterozygous embryos, both stripes 3 and 4 display narrower widths, anteriorly shifted boundaries and reduced mRNA production levels. We show that Kr dosage indirectly affects stripe 3 and 4 dynamics by modulating other gap gene dynamics. We quantitatively correlate moderate body segment phenotypes of Kr heterozygotes with spatiotemporal changes in eve expression. Our results indicate that nonlinear relationships between TF dosage and phenotypes underlie direct TF-DNA and indirect TF-TF interactions.

Optogenetic control of the Bicoid morphogen reveals fast and slow modes of gap gene regulation

Developmental patterning networks are regulated by multiple inputs and feedback connections that rapidly reshape gene expression, limiting the information that can be gained solely from slow genetic perturbations. Here we show that fast optogenetic stimuli, real-time transcriptional reporters, and a simplified genetic background can be combined to reveal the kinetics of gene expression downstream of a developmental transcription factor in vivo. We engineer light-controlled versions of the Bicoid transcription factor and study their effects on downstream gap genes in embryos. Our results recapitulate known relationships, including rapid Bicoid-dependent transcription of giant and hunchback and delayed repression of Krüppel. In addition, we find that the posterior pattern of knirps exhibits a quick but inverted response to Bicoid perturbation, suggesting a noncanonical role for Bicoid in directly suppressing knirps transcription. Acute modulation of transcription factor concentration while recording output gene activity represents a powerful approach for studying developmental gene networks in vivo.

Nonequilibrium model of short-range repression in gene transcription regulation

Transcription factors are proteins that regulate gene activity by activating or repressing gene transcription. A special class of transcriptional repressors operates via a short-range mechanism, making local DNA regions inaccessible to binding by activators, and thus providing an indirect repressive action on the target gene. This mechanism is commonly modeled assuming that repressors interact with DNA under thermodynamic equilibrium and neglecting some configurations of the gene regulatory region. We elaborate on a more general nonequilibrium model of short-range repression using the graph formalism for transitions between gene states, and we apply analytical calculations to compare it with the equilibrium model in terms of the repression strength and expression noise. In contrast to the equilibrium approach, the new model allows us to separate two basic mechanisms of short-range repression. The first mechanism is associated with the recruiting of factors that mediate chromatin condensation, and the second one concerns the blocking of factors that mediate chromatin loosening. The nonequilibrium model demonstrates better performance on previously published gene expression data obtained for transcription factors controlling Drosophila development, and furthermore it predicts that the first repression mechanism is the most favorable in this system. The presented approach can be scaled to larger gene networks and can be used to infer specific modes and parameters of transcriptional regulation from gene expression data.

Genetic Causation in Complex Regulatory Systems: An Integrative Dynamic Perspective

The logic of genetic discovery has changed little over time, but the focus of biology is shifting from simple genotype-phenotype relationships to complex metabolic, physiological, developmental, and behavioral traits. In light of this, the traditional reductionist view of individual genes as privileged difference-making causes of phenotypes is re-examined. The scope and nature of genetic effects in complex regulatory systems, in which dynamics are driven by regulatory feedback and hierarchical interactions across levels of organization are considered. This review argues that it is appropriate to treat genes as specific actual difference-makers for the molecular regulation of gene expression. However, they are often neither stable, proportional, nor specific as causes of the overall dynamic behavior of regulatory networks. Dynamical models, properly formulated and validated, provide the tools to probe cause-and-effect relationships in complex biological systems, allowing to go beyond the limitations of genetic reductionism to gain an integrative understanding of the causal processes underlying complex phenotypes.

De novo recruitment of Polycomb-group proteins in Drosophila embryos

Polycomb-group (PcG)-mediated transcriptional repression of target genes can be delineated into two phases. First, following initial repression of target genes by gene-specific transcription factors, PcG proteins recognize the repressed state and assume control of the genes' repression. Second, once the silenced state is established, PcG proteins may maintain repression through an indefinite number of cell cycles. Little is understood about how PcG proteins initially recognize the repressed state of target genes and the steps leading to de novo establishment of PcG-mediated repression. We describe a genetic system in which a Drosophila PcG target gene, giant (gt), is ubiquitously repressed during early embryogenesis by a maternally expressed transcription factor, and show the temporal recruitment of components of three PcG protein complexes: PhoRC, PRC1 and PRC2. We show that de novo PcG recruitment follows a temporal hierarchy in which PhoRC stably localizes at the target gene at least 1 h before stable recruitment of PRC2 and concurrent trimethylation of histone H3 at lysine 27 (H3K27me3). The presence of PRC2 and increased levels of H3K27me3 are found to precede stable binding by PRC1.

Speed regulation of genetic cascades allows for evolvability in the body plan specification of insects

During the anterior-posterior fate specification of insects, anterior fates arise in a nonelongating tissue (called the "blastoderm"), and posterior fates arise in an elongating tissue (called the "germband"). However, insects differ widely in the extent to which anterior-posterior fates are specified in the blastoderm versus the germband. Here we present a model in which patterning in both the blastoderm and germband of the beetle Tribolium castaneum is based on the same flexible mechanism: a gradient that modulates the speed of a genetic cascade of gap genes, resulting in the induction of sequential kinematic waves of gap gene expression. The mechanism is flexible and capable of patterning both elongating and nonelongating tissues, and hence converting blastodermal to germband fates and vice versa. Using RNAi perturbations, we found that blastodermal fates could be shifted to the germband, and germband fates could be generated in a blastoderm-like morphology. We also suggest a molecular mechanism underlying our model, in which gradient levels regulate the switch between two enhancers: One enhancer is responsible for sequential gene activation, and the other is responsible for freezing temporal rhythms into spatial patterns. This model is consistent with findings in Drosophila melanogaster, where gap genes were found to be regulated by two nonredundant "shadow" enhancers.

Translating natural genetic variation to gene expression in a computational model of the Drosophila gap gene regulatory network

Annotating the genotype-phenotype relationship, and developing a proper quantitative description of the relationship, requires understanding the impact of natural genomic variation on gene expression. We apply a sequence-level model of gap gene expression in the early development of Drosophila to analyze single nucleotide polymorphisms (SNPs) in a panel of natural sequenced D. melanogaster lines. Using a thermodynamic modeling framework, we provide both analytical and computational descriptions of how single-nucleotide variants affect gene expression. The analysis reveals that the sequence variants increase (decrease) gene expression if located within binding sites of repressors (activators). We show that the sign of SNP influence (activation or repression) may change in time and space and elucidate the origin of this change in specific examples. The thermodynamic modeling approach predicts non-local and non-linear effects arising from SNPs, and combinations of SNPs, in individual fly genotypes. Simulation of individual fly genotypes using our model reveals that this non-linearity reduces to almost additive inputs from multiple SNPs. Further, we see signatures of the action of purifying selection in the gap gene regulatory regions. To infer the specific targets of purifying selection, we analyze the patterns of polymorphism in the data at two phenotypic levels: the strengths of binding and expression. We find that combinations of SNPs show evidence of being under selective pressure, while individual SNPs do not. The model predicts that SNPs appear to accumulate in the genotypes of the natural population in a way biased towards small increases in activating action on the expression pattern. Taken together, these results provide a systems-level view of how genetic variation translates to the level of gene regulatory networks via combinatorial SNP effects.

An Enhancer's Length and Composition Are Shaped by Its Regulatory Task

Enhancers drive the gene expression patterns required for virtually every process in metazoans. We propose that enhancer length and transcription factor (TF) binding site composition—the number and identity of TF binding sites—reflect the complexity of the enhancer's regulatory task. In development, we define regulatory task complexity as the number of fates specified in a set of cells at once. We hypothesize that enhancers with more complex regulatory tasks will be longer, with more, but less specific, TF binding sites. Larger numbers of binding sites can be arranged in more ways, allowing enhancers to drive many distinct expression patterns, and therefore cell fates, using a finite number of TF inputs. We compare ~100 enhancers patterning the more complex anterior-posterior (AP) axis and the simpler dorsal-ventral (DV) axis in Drosophila and find that the AP enhancers are longer with more, but less specific binding sites than the (DV) enhancers. Using a set of ~3,500 enhancers, we find enhancer length and TF binding site number again increase with increasing regulatory task complexity. Therefore, to be broadly applicable, computational tools to study enhancers must account for differences in regulatory task.