Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic

Kim, Ah-Ram; Martínez, Carlos A.; Ionides, John; Ramos, Alexandre F.; Ludwig, Michael; Ogawa, Norio; Sharp, David H.; Reinitz, John

doi:10.1371/journal.pgen.1003243

Cited by 68 publications

(139 citation statements)

References 82 publications

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“…One hypothesis is that other TFs bound nearby convert Hb from a repressor into an activator, as is the case for Dorsal (9-13). There is genetic evidence for activator synergy between Bcd and Hb (19,48), and activator synergy between Hb and Caudal has been proposed by computational work (30). Another hypothesis is that Hb monomers are activators but DNA-bound Hb dimers are repressors (25,49).…”

Section: Discussionmentioning

confidence: 95%

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Shadow enhancers enable Hunchback bifunctionality in the Drosophila embryo

Staller

Vincent

Bragdon

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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Hunchback (Hb) is a bifunctional transcription factor that activates and represses distinct enhancers. Here, we investigate the hypothesis that Hb can activate and repress the same enhancer. Computational models predicted that Hb bifunctionally regulates the even-skipped (eve) stripe 3+7 enhancer (eve3+7) in Drosophila blastoderm embryos. We measured and modeled eve expression at cellular resolution under multiple genetic perturbations and found that the eve3+7 enhancer could not explain endogenous eve stripe 7 behavior. Instead, we found that eve stripe 7 is controlled by two enhancers: the canonical eve3+7 and a sequence encompassing the minimal eve stripe 2 enhancer (eve2+7). Hb bifunctionally regulates eve stripe 7, but it executes these two activities on different pieces of regulatory DNA-it activates the eve2+7 enhancer and represses the eve3+7 enhancer. These two "shadow enhancers" use different regulatory logic to create the same pattern.enhancer | computational model | bifunctional transcription factor | Drosophila development | Hunchback T ranscription factors (TFs) are typically categorized as activators or repressors, but many TFs can act bifunctionally by both activating and repressing target genes (1-4). Changes in TF activity can result from posttranslational modifications, protein cleavage, or translocation of cofactors into the nucleus (5-7). However, in cases where a TF activates and represses genes in the same cells, bifunctionality is controlled by enhancer sequences, which are responsible for tissue-specific gene expression (8). For example, in Drosophila, Dorsal activates genes when it binds to enhancers alone or near Twist (9, 10) but represses genes when it binds near other TFs (11-13). The DNA sequence of a TF's binding site can also alter TF activity [e.g., the glucocorticoid receptor (14, 15)]. Identifying how the activity of bifunctional TFs is controlled will be critical for inferring accurate gene regulatory networks from genomic data (16).Here, we investigate how TF bifunctionality is controlled using a classic example: the Drosophila gene hunchback (hb) (1, 17, 18). Hb both activates and represses even-skipped (eve) by acting on multiple enhancers. Hb activates eve stripes 1 and 2 and represses stripes 4, 5, and 6 (19-22). Computational models from us and others support the hypothesis that Hb both activates and represses the enhancer that controls eve stripes 3 and 7 (eve3+7) (Fig. 1) (22-25).In contrast to others, our computational models of eve3+7 activity do not include regulatory DNA sequence (26-30). Instead, our modeling approach uses regression to identify the activators and repressors that control a given pattern; we refer to the identity and role of the regulators as "regulatory logic." Modeling regulatory logic without including DNA sequence enables a powerful strategy to dissect gene regulation in a complex locus. We can compare the regulatory logic of an enhancer reporter pattern to that of the corresponding portion of the endogenous pattern to determine whether the an...

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Section: Discussionmentioning

confidence: 95%

“…In contrast to others, our computational models of eve3+7 activity do not include regulatory DNA sequence (26)(27)(28)(29)(30). Instead, our modeling approach uses regression to identify the activators and repressors that control a given pattern; we refer to the identity and role of the regulators as "regulatory logic."…”

mentioning

confidence: 99%

Shadow enhancers enable Hunchback bifunctionality in the Drosophila embryo

Staller

Vincent

Bragdon

et al. 2015

Proc. Natl. Acad. Sci. U.S.A.

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“…We might also anticipate finding some of these variants to be common in populations if they co-occur with compensatory mutations. The continued development of models of transcription, such as [Kim et al, 2013], will be useful for predicting the effects of natural variation on gene expression.…”

Section: Discussionmentioning

confidence: 99%

“…The individual enhancers of eve are very well characterized in terms of function [Harding et al, 1989, Goto et al, 1989, Small et al, 1992, 1993, 1996, Arnosti et al, 1996, Fujioka et al, 1999, Janssens et al, 2006, Kim et al, 2013]. A 15kb segment of DNA (−6.4kb to +8.6kb of eve ) can provide a normal segmentation phenotype and rescue an eve null mutant to hatching [Fujioka et al, 1999, 2002].…”

Section: Introductionmentioning

confidence: 99%

Natural variation of the expression pattern of the segmentation gene even-skipped in melanogaster

Jiang

Ludwig

Kreitman

et al. 2015

Developmental Biology

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The evolution of canalized traits is a central question in evolutionary biology. Natural variation in highly conserved traits can provide clues about their evolutionary potential. Here we investigate natural variation in a conserved trait—even-skipped (eve) expression at the cellular blastoderm stage of embryonic development in Drosophila melanogaster. Expression of the pair-rule gene eve was quantitatively measured in three inbred lines derived from a natural population of D. melanogaster. One line showed marked differences in the spacing, amplitude and timing of formation of the characteristic seven-striped pattern over a fifty-minute period prior to the onset of gastrulation. Stripe 5 amplitude and the width of the interstripe between stripes 4 and 5 were both reduced in this line, while the interstripe distance between stripes 3 and 4 was increased. Engrailed expression in stage 10 embryos revealed a statistically significant increase in the length of parasegment 6 and a decrease in the length of parasegments 8 and 9. These changes are larger than those previously reported between D. melanogaster and D. pseudoobscura, two species that are thought to have diverged from a common ancestor over 25 million years ago. This line harbors a rare 448bp deletion in the first intron of knirps (kni). This finding suggested that reduced Kni levels caused the deviant eve expression, and indeed we observed lower levels of Kni protein at early cycle 14A in L2 compared to the other two lines. A second of the three lines displayed an approximately 20% greater level of expression for all seven eve stripes. The three lines are each viable and fertile, and none display a segmentation defect as adults, suggesting that early-acting variation in eve expression is ameliorated by developmental buffering mechanisms acting later in development. Canalization of the segmentation pathway may reduce the fitness consequences of genetic variation, thus allowing the persistence of mutations with unexpectedly strong gene expression phenotypes.

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“…Certain applications in developmental biology and systems biology rely heavily on this particular method of optimization [2, 3, 4, 5, 6]. It mimics the physical process of annealing by treating the cost function as an “energy” E and sampling the value of E according to the Boltzmann distribution at some artificial temperature T using the Metropolis algorithm [7].…”

Section: Introductionmentioning

confidence: 99%

Parallel simulated annealing using an adaptive resampling interval

Lou

Reinitz

2016

Parallel Computing

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This paper presents a parallel simulated annealing algorithm that is able to achieve 90% parallel efficiency in iteration on up to 192 processors and up to 40% parallel efficiency in time when applied to a 5000-dimension Rastrigin function. Our algorithm breaks scalability barriers in the method of Chu et al. (1999) by abandoning adaptive cooling based on variance. The resulting gains in parallel efficiency are much larger than the loss of serial efficiency from lack of adaptive cooling. Our algorithm resamples the states across processors periodically. The resampling interval is tuned according to the success rate for each specific number of processors. We further present an adaptive method to determine the resampling interval based on the adoption rate. This adaptive method is able to achieve nearly identical parallel efficiency but higher success rates compared to the fixed interval one using the best interval found.

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Rearrangements of 2.5 Kilobases of Noncoding DNA from the Drosophila even-skipped Locus Define Predictive Rules of Genomic cis-Regulatory Logic

Cited by 68 publications

References 82 publications

Shadow enhancers enable Hunchback bifunctionality in the Drosophila embryo

Shadow enhancers enable Hunchback bifunctionality in the Drosophila embryo

Natural variation of the expression pattern of the segmentation gene even-skipped in melanogaster

Parallel simulated annealing using an adaptive resampling interval

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