Integration of Orthogonal Signaling by the Notch and Dpp Pathways in <i>Drosophila</i>

Stroebele, Elizabeth; Erives, Albert

doi:10.1534/genetics.116.186791

Cited by 7 publications

(12 citation statements)

References 121 publications

(148 reference statements)

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“…On the ventral side, DL and Twist (TWI) activate but SNA represses the expression in the mesoderm [39,44]. Expression on the dorsal side is inhibited directly by Suppressor of hairless (Su(H)), which is the only known repressor of sim in the neuroectoderm [45], but is believed to have an activating influence on sim in the mesoderm region [45,48,49].…”

Section: Quantifying and Interpreting The Value Of Perturbation Expermentioning

confidence: 99%

An information theoretic treatment of sequence-to-expression modeling

Khajouei

Sinha

2018

Preprint

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Studying a gene's regulatory mechanisms is a tedious process that involves identification of candidate regulators by transcription factor (TF) knockout or over-expression experiments, delineation of enhancers by reporter assays, and demonstration of direct TF influence by site mutagenesis, among other approaches. Such experiments are often chosen based on the biologist's intuition, from several testable hypotheses. We pursue the goal of making this process systematic by using ideas from information theory to reason about experiments in gene regulation, in the hope of ultimately enabling rigorous experiment design strategies. For this, we make use of a state-of-the-art mathematical model of gene expression, which provides a way to formalize our current knowledge of cis-as well as trans-regulatory mechanisms of a gene. Ambiguities in such knowledge can be expressed as uncertainties in the model, which we capture formally by building an ensemble of plausible models that fit the existing data and defining a probability distribution over the ensemble. We then characterize the impact of a new experiment on our understanding of the gene's regulation based on how the ensemble of plausible models and its probability distribution changes when challenged with results from that experiment. This allows us to assess the 'value' of the experiment retroactively as the reduction in entropy of the distribution (information gain) resulting from the experiment's results. We fully formalize this novel approach to reasoning about gene regulation experiments and use it to evaluate a variety of perturbation experiments on two developmental genes of D. melanogaster. We also provide objective and 'biologist-friendly' descriptions of the information gained from each such experiment. The rigorously defined information theoretic approaches presented here can be used in the future to formulate systematic strategies for experiment design pertaining to studies of gene regulatory mechanisms.In-depth studies of gene regulatory mechanisms employ a variety of experimental approaches such as identifying a gene's enhancer(s) and testing its variants through reporter assays, followed by transcription factor mis-expression or knockouts, site mutagenesis, etc. The biologist is often faced with the challenging problem of selecting the ideal next experiment to perform so that its results provide novel mechanistic insights, and has to rely on their intuition about what is currently known on the topic and which experiments may add to that knowledge. We seek to make this intuition-based process more systematic, by borrowing ideas from the mature statistical field of experiment design. Towards this goal, we use the language of mathematical models to formally describe what is known about a gene's regulatory mechanisms, and how an experiment's results enhance that knowledge. We use information theoretic ideas to assign a 'value' to an experiment as well as explain objectively what is learned from that experiment. We demonstrate use of this novel approach on two...

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Section: Quantifying and Interpreting The Value Of Perturbation Expermentioning

confidence: 99%

An information theoretic treatment of sequence-to-expression modeling

Khajouei

Sinha

2018

Preprint

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“…Our first use of the 1344 SUH-RBs was to identify the SUH-RB with the densest cluster of Smad Dpp/BMP-effector, Apterous, and Zelda binding sites (Stroebele and Erives 2016). This led to the identification of the nab dorsal wing margin enhancer (DWME) Stroebele and Erives (2016). A single SUH-RB at Notch and one of the Delta SUH-RBs also contained a similar set of sites as the nab DWME.…”

Section: Su(h)-dependent Enhancers At Notch and Deltamentioning

confidence: 99%

“…In addition to the Notch and Delta WMEs, we cloned and tested 11 SUH-RBs and found that 10 of these drove distinct tissue-specific activities, which we show in this study and companion studies (nab DWME (Stroebele and Erives 2016) and 9 novel enhancers in the upper and bottom halves of Table 4, respectively). In a companion study on the regulation of nab developmental gene (Stroebele and Erives 2016), we found that a SUH-RB containing two Su(H) sites in the first intron on nab corresponds to a wing/haltere imaginal disc enhancer (DWME) and a larval brain enhancer (BrE) ( Table 4). The nab DWME is licensed by wing disc selectors to integrate Notch and Dpp/BMP signaling pathways and drive expression in the dorsal wing margin.…”

Section: Identification Of Novel Suh-rb Enhancers From Different Stagesmentioning

confidence: 99%

Genomic dimensions of Su(H)-targeted regulatory belts inDrosophila

Stroebele

Fuqua

Warren

et al. 2016

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Asymmetric Notch signaling promotes divergent fates in select cells throughout metazoan development. In the receiving cell, signaling results in cleavage of the Notch intracellular domain and its import into the nucleus, where it binds Suppressor of Hairless [Su(H)] to promote gene expression in conjunction with contextual cues in the surrounding DNA sequence. To investigate the nature of this contextual logic, we identify 1344 Su(H)-site containing regulatory belts that are conserved across the Drosophila genus. Each Su(H)-type regulatory belt (SUH-RB) is a 0.6-1.0 kb chain of conservation peaks consistent with a transcriptional enhancer or core promoter. These regulatory belts contain one or more canonical binding sites for Su(H) along with ∼15-30 other binding sites. SUH-RBs are densely clustered in certain chromosomal regions such as the E(spl)-complex, the Wnt gene complex, and genes encoding Notch receptor ligands (Delta and Serrate). SUH-RBs overlap most known Su(H)/Notch-target enhancers and others, including non-embryonic enhancers that are not identified by embryonic ChIP-seq peaks. Thus, SUH-RBs overcome the stage-specific nature of embryonic ChIP-seq peaks and suggest a pervasive role for contextual tissue-specific pioneer and/or enhancer-licensing factors. SUH-RBs also delineate false positive ChIP-seq peaks, which do not overlap SUH-RBs, are missing even the weakest Su(H)-binding sequences, and have the shortest ChIP peak widths. Last, we characterize several novel enhancers including Su(H)-dependent enhancers at Notch and Delta, intestinal enhancers at A2bp1 and hedgehog, and distinct enhancers at roughest, E2f1, and escargot.

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“…The smallest possible scale to ascribe such homology is that of individual nucleotide positions ("site positional homology"). Of course this is possible only in the context of homological inference based on multiple nucleotide positions in a sequence.By studying the function and evolution of regulatory DNA sequences (transcriptional enhancers in Ciona and Drosophila), which are not constrained by rigid, protein-coding, triplet reading frames (Erives et al Brittain et al 2014;Stroebele and Erives 2016), I conclude that site positional homology is incorrectly handled by gapped alignment (GA). GA was originally adopted by necessity in order to compare protein sequences of divergent lengths (Braunitzer's gappy comparisons of α-and β-hemoglobin…”

mentioning

confidence: 99%

“…This issue is exacerbated to great extremes in the regulatory DNAs of the speciose Hawaiian Drosophila (Brittain et al 2014;O'Grady and DeSalle 2018). Nonetheless, this issue also is seen for the sequences encoding many important regulator proteins enriched in polyglutamine content and other repeats, including the Notch intracellular domain and sub-units of the Mediator complex (Tóth-Petróczy et al 2008;Fuxreiter et al 2008;Rice et al 2015;Stroebele and Erives 2016;Erives 2017). As a related consequence, repeat alleles at these loci are not being accurately genotyped by modern genome assembly despite evidence of profound phenotypic effects (Rice et al 2015;Chandler et al 2017;Press and Queitsch 2017;Press et al 2019).…”

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confidence: 99%

Maximal homology alignment: A new method based on two-dimensional homology

Erives

2019

Preprint

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Maximal homology alignment is a new biologically-relevant approach to DNA sequence alignment that embraces microparalogy. It departs from the current method of gapped alignment, which uses a simple, binary state model of nucleotide position. In gapped alignment nucleotide positions have either no relationship (1-to-None) or else orthological relationship (1-to-1) with nucleotides in other sequences. Maximal homology alignment, however, allows additional states such as 1-to-Many and Many-to-Many, thus modeling both orthological and paralogical relationships, which together comprise the main homology types. Maximal homology alignment collects dispersed microparalogy into the same alignment columns on multiple rows, and thereby generates a two-dimensional representation of a single sequence. Sequence alignment then proceeds as the alignment of two-dimensional topological objects. The operations of producing and aligning two dimensional auto-alignments motivate a need for tests of two dimensional homological integrity that are both necessary and sufficient. Here, I work out and implement basic principles for computationally handling the two dimensions of positional homology, which are inherent to biological sequences due to replication slippage and related errors. I then show that maximal homology alignment is more suited and more informative than gapped alignment for modeling the evolution of genetic sequences, which harbor large numbers of small insertions and deletions originating as local microparalogy. These results show that both conserved and non-conserved genomic sequences are imbued with a signature of replication slippage that is absent from their random permutations. KEYWORDS dimensionality; DNA microfoam; Drosophila; enhancer DNAs; gapped alignment (GA); maximal homology alignment (MHA); positional homology; replication slippage; tandem repeats S equences of covalently-linked nucleotides and their evolutionary relationships are the basis of gene homology. The smallest possible scale to ascribe such homology is that of individual nucleotide positions ("site positional homology"). Of course this is possible only in the context of homological inference based on multiple nucleotide positions in a sequence.By studying the function and evolution of regulatory DNA sequences (transcriptional enhancers in Ciona and Drosophila), which are not constrained by rigid, protein-coding, triplet reading frames (Erives et al. Brittain et al. 2014;Stroebele and Erives 2016), I conclude that site positional homology is incorrectly handled by gapped alignment (GA). GA was originally adopted by necessity in order to compare protein sequences of divergent lengths (Braunitzer's gappy comparisons of α-and β-hemoglobin

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Integration of Orthogonal Signaling by the Notch and Dpp Pathways in Drosophila

Cited by 7 publications

References 121 publications

An information theoretic treatment of sequence-to-expression modeling

An information theoretic treatment of sequence-to-expression modeling

Genomic dimensions of Su(H)-targeted regulatory belts inDrosophila

Maximal homology alignment: A new method based on two-dimensional homology

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