Opsin expression varies across larval development and taxa in pteriomorphian bivalves.

Introduction: Many marine organisms have a biphasic life cycle that transitions between a swimming larva with a more sedentary adult form. At the end of the first phase, larvae must identify suitable sites to settle and undergo a dramatic morphological change. Environmental factors, including photic and chemical cues, appear to influence settlement, but the sensory receptors involved are largely unknown. We targeted the protein receptor, opsin, which belongs to large superfamily of transmembrane receptors that detects environmental stimuli, hormones, and neurotransmitters. While opsins are well-known for light-sensing, including vision, a growing number of studies have demonstrated light-independent functions. We therefore examined opsin expression in the Pteriomorphia, a large, diverse clade of marine bivalves, that includes commercially important species, such as oysters, mussels, and scallops. Methods: Genomic annotations combined with phylogenetic analysis show great variation of opsin abundance among pteriomorphian bivalves, including surprisingly high genomic abundance in many species that are eyeless as adults, such as mussels. Therefore, we investigated the diversity of opsin expression from the perspective of larval development. We collected opsin gene expression in four families of Pteriomorphia, across three distinct larval stages, i.e., trochophore, veliger, and pediveliger, and compared those to adult tissues. Results: We found larvae express all opsin types in these bivalves, but opsin expression patterns are largely species-specific across development. Few opsins are expressed in the adult mantle, but many are highly expressed in adult eyes. Intriguingly, opsin genes such as retinochrome, xenopsins, and Go-opsins have higher levels of expression in the later larval stages when substrates for settlement are being tested, such as the pediveliger. Conclusion: Investigating opsin gene expression during larval development provides crucial insights into their intricate interactions with the surroundings, which may shed light on how opsin receptors of these organisms respond to various environmental cues that play a pivotal role in their settlement process.

Ocean state rising: Storm simulation and vulnerability mapping to predict hurricane impacts for Rhode Island's critical infrastructure.

Predicting the consequences of a major coastal storm is increasingly difficult as the result of global climate change and growing societal dependence on critical infrastructure (CI). Past storms are no longer a reliable predictor of future weather events, and the traditional approach to vulnerability assessment presents accumulated loss in largely quantitative terms that lack the specificity local emergency managers need to develop effective plans and mitigation strategies. The Rhode Island Coastal Hazards Modeling and Prediction (RI-CHAMP) system is a geographic information system (GIS)-based modeling tool that combines high-resolution storm simulations with geolocated vulnerability data to predict specific consequences based on local concerns about impacts to CI. This case study discusses implementing RI-CHAMP for the State of Rhode Island to predict impacts of wind and inundation on its CI during a hurricane, tropical storm, or nor'easter. This paper addresses the collection and field verification of vulnerability data, along with RI-CHAMP's process for integrating those data with storm models. The project deeply engaged end-users (emergency managers, facility managers, and other stakeholders) in developing RI-CHAMP's ArcGIS Online dashboard to ensure it provides specific, actionable data. The results of real and synthetic storm models are presented along with discussion of how the data in these simulations are being used by state and local emergency managers, facility owners, and others.

Molluscan Genomes Reveal Extensive Differences in Photopigment Evolution Across the Phylum.

In animals, opsins and cryptochromes are major protein families that transduce light signals when bound to light-absorbing chromophores. Opsins are involved in various light-dependent processes, like vision, and have been co-opted for light-independent sensory modalities. Cryptochromes are important photoreceptors in animals, generally regulating circadian rhythm, they belong to a larger protein family with photolyases, which repair UV-induced DNA damage. Mollusks are great animals to explore questions about light sensing as eyes have evolved multiple times across, and within, taxonomic classes. We used molluscan genome assemblies from 80 species to predict protein sequences and examine gene family evolution using phylogenetic approaches. We found extensive opsin family expansion and contraction, particularly in bivalve xenopsins and gastropod Go-opsins, while other opsins, like retinochrome, rarely duplicate. Bivalve and gastropod lineages exhibit fluctuations in opsin repertoire, with cephalopods having the fewest number of opsins and loss of at least 2 major opsin types. Interestingly, opsin expansions are not limited to eyed species, and the highest opsin content was seen in eyeless bivalves. The dynamic nature of opsin evolution is quite contrary to the general lack of diversification in mollusk cryptochromes, though some taxa, including cephalopods and terrestrial gastropods, have reduced repertoires of both protein families. We also found complete loss of opsins and cryptochromes in multiple, but not all, deep-sea species. These results help set the stage for connecting genomic changes, including opsin family expansion and contraction, with differences in environmental, and biological features across Mollusca.

Single-molecule Sequencing of an Animal Mitochondrial Genome Reveals Chloroplast-like Architecture and Repeat-mediated Recombination.

Recent advances in long-read sequencing technology have allowed for single-molecule sequencing of entire mitochondrial genomes, opening the door for direct investigation of the mitochondrial genome architecture and recombination. We used PacBio sequencing to reassemble mitochondrial genomes from two species of New Zealand freshwater snails, Potamopyrgus antipodarum and Potamopyrgus estuarinus. These assemblies revealed a ∼1.7 kb structure within the mitochondrial genomes of both species that was previously undetected by an assembly of short reads and likely corresponding to a large noncoding region commonly present in the mitochondrial genomes. The overall architecture of these Potamopyrgus mitochondrial genomes is reminiscent of the chloroplast genomes of land plants, harboring a large single-copy (LSC) region and a small single-copy (SSC) region separated by a pair of inverted repeats (IRa and IRb). Individual sequencing reads that spanned across the Potamopyrgus IRa-SSC-IRb structure revealed the occurrence of a "flip-flop" recombination. We also detected evidence for two distinct IR haplotypes and recombination between them in wild-caught P. estuarinus, as well as extensive intermolecular recombination between single-nucleotide polymorphisms in the LSC region. The chloroplast-like architecture and repeat-mediated mitochondrial recombination we describe here raise fundamental questions regarding the origins and commonness of inverted repeats in cytoplasmic genomes and their role in mitochondrial genome evolution.

Lineage abundance estimation for SARS-CoV-2 in wastewater using transcriptome quantification techniques.

Effectively monitoring the spread of SARS-CoV-2 mutants is essential to efforts to counter the ongoing pandemic. Predicting lineage abundance from wastewater, however, is technically challenging. We show that by sequencing SARS-CoV-2 RNA in wastewater and applying algorithms initially used for transcriptome quantification, we can estimate lineage abundance in wastewater samples. We find high variability in signal among individual samples, but the overall trends match those observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in mutant prevalence in situations where clinical sequencing is unavailable.

Nationwide Trends in COVID-19 Cases and SARS-CoV-2 RNA Wastewater Concentrations in the United States.

Wastewater-based epidemiology has emerged as a promising technology for population-level surveillance of COVID-19. In this study, we present results of a large nationwide SARS-CoV-2 wastewater monitoring system in the United States. We profile 55 locations with at least six months of sampling from April 2020 to May 2021. These locations represent more than 12 million individuals across 19 states. Samples were collected approximately weekly by wastewater treatment utilities as part of a regular wastewater surveillance service and analyzed for SARS-CoV-2 RNA concentrations. SARS-CoV-2 RNA concentrations were normalized to pepper mild mottle virus, an indicator of fecal matter in wastewater. We show that wastewater data reflect temporal and geographic trends in clinical COVID-19 cases and investigate the impact of normalization on correlations with case data within and across locations. We also provide key lessons learned from our broad-scale implementation of wastewater-based epidemiology, which can be used to inform wastewater-based epidemiology approaches for future emerging diseases. This work demonstrates that wastewater surveillance is a feasible approach for nationwide population-level monitoring of COVID-19 disease. With an evolving epidemic and effective vaccines against SARS-CoV-2, wastewater-based epidemiology can serve as a passive surveillance approach for detecting changing dynamics or resurgences of the virus.

Additive and epistatic effects influence spectral tuning in molluscan retinochrome opsin.

The relationship between genotype and phenotype is non-trivial because of the often complex molecular pathways that make it difficult to unambiguously relate phenotypes to specific genotypes. Photopigments, comprising an opsin apoprotein bound to a light-absorbing chromophore, present an opportunity to directly relate the amino acid sequence to an absorbance peak phenotype (λmax). We examined this relationship by conducting a series of site-directed mutagenesis experiments of retinochrome, a non-visual opsin, from two closely related species: the common bay scallop, Argopecten irradians, and the king scallop, Pecten maximus. Using protein folding models, we identified three amino acid sites of likely functional importance and expressed mutated retinochrome proteins in vitro. Our results show that the mutation of amino acids lining the opsin binding pocket is responsible for fine spectral tuning, or small changes in the λmax of these light-sensitive proteins. Mutations resulted in a blue or red shift as predicted, but with dissimilar magnitudes. Shifts ranged from a 16 nm blue shift to a 12 nm red shift from the wild-type λmax. These mutations do not show an additive effect, but rather suggest the presence of epistatic interactions. This work highlights the importance of binding pocket shape in the evolution of spectral tuning and builds on our ability to relate genotypic changes to phenotypes in an emerging model for opsin functional analysis.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification.

Effectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020.

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. We collected 24-hour composite wastewater samples from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and measured SARS-CoV-2 RNA concentrations using RT-qPCR. We show that the relationship between wastewater viral titers and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater viral titers and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. We find that the WC ratio increases after key events, providing insight into the balance between disease spread and public health response. We also find that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity. These three metrics could complement a framework for integrating wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Asexuality Associated with Marked Genomic Expansion of Tandemly Repeated rRNA and Histone Genes.

How does asexual reproduction influence genome evolution? Although is it clear that genomic structural variation is common and important in natural populations, we know very little about how one of the most fundamental of eukaryotic traits-mode of genomic inheritance-influences genome structure. We address this question with the New Zealand freshwater snail Potamopyrgus antipodarum, which features multiple separately derived obligately asexual lineages that coexist and compete with otherwise similar sexual lineages. We used whole-genome sequencing reads from a diverse set of sexual and asexual individuals to analyze genomic abundance of a critically important gene family, rDNA (the genes encoding rRNAs), that is notable for dynamic and variable copy number. Our genomic survey of rDNA in P. antipodarum revealed two striking results. First, the core histone and 5S rRNA genes occur between tandem copies of the 18S-5.8S-28S gene cluster, a unique architecture for these crucial gene families. Second, asexual P. antipodarum harbor dramatically more rDNA-histone copies than sexuals, which we validated through molecular and cytogenetic analysis. The repeated expansion of this genomic region in asexual P. antipodarum lineages following distinct transitions to asexuality represents a dramatic genome structural change associated with asexual reproduction-with potential functional consequences related to the loss of sexual reproduction.

Wastewater Surveillance of SARS-CoV-2 across 40 U.S. states.

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

SARS-CoV-2 titers in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we use longitudinal wastewater analysis to track SARS-CoV-2 dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. Viral titers in wastewater increased exponentially from mid-March to mid-April, after which they began to decline. Viral titers in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral titers as a convolution of back-dated new clinical cases with the viral shedding function of an individual. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. Finally, we found that wastewater viral titers at the neighborhood level correlate better with demographic variables than with population size. This work suggests that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and may shed light on infection characteristics that are difficult to capture in clinical investigations, such as early viral shedding dynamics.

The Epithelial adhesin 1 tandem repeat region mediates protein display through multiple mechanisms.

The pathogenic yeast Candida glabrata is reliant on a suite of cell surface adhesins that play a variety of roles necessary for transmission, establishment and proliferation during infection. One particular adhesin, Epithelial Adhesin 1 [Epa1p], is responsible for binding to host tissue, a process which is essential for fungal propagation. Epa1p structure consists of three domains: an N-terminal intercellular binding domain responsible for epithelial cell binding, a C-terminal GPI anchor for cell wall linkage and a serine/threonine-rich linker domain connecting these terminal domains. The linker domain contains a 40-amino acid tandem repeat region, which we have found to be variable in repeat copy number between isolates from clinical sources. We hypothesized that natural variation in Epa1p repeat copy may modulate protein function. To test this, we recombinantly expressed Epa1p with various repeat copy numbers in S. cerevisiae to determine how differences in repeat copy number affect Epa1p expression, surface display and binding to human epithelial cells. Our data suggest that repeat copy number variation has pleiotropic effects, influencing gene expression, protein surface display and shedding from the cell surface of the Epa1p adhesin. This study serves to demonstrate repeat copy number variation can modulate protein function through a number of mechanisms in order to contribute to pathogenicity of C. glabrata.

Genome of the Parasitoid Wasp Diachasma alloeum, an Emerging Model for Ecological Speciation and Transitions to Asexual Reproduction.

Parasitoid wasps are among the most speciose animals, yet have relatively few available genomic resources. We report a draft genome assembly of the wasp Diachasma alloeum (Hymenoptera: Braconidae), a host-specific parasitoid of the apple maggot fly Rhagoletis pomonella (Diptera: Tephritidae), and a developing model for understanding how ecological speciation can "cascade" across trophic levels. Identification of gene content confirmed the overall quality of the draft genome, and we manually annotated ∼400 genes as part of this study, including those involved in oxidative phosphorylation, chemosensation, and reproduction. Through comparisons to model hymenopterans such as the European honeybee Apis mellifera and parasitoid wasp Nasonia vitripennis, as well as a more closely related braconid parasitoid Microplitis demolitor, we identified a proliferation of transposable elements in the genome, an expansion of chemosensory genes in parasitoid wasps, and the maintenance of several key genes with known roles in sexual reproduction and sex determination. The D. alloeum genome will provide a valuable resource for comparative genomics studies in Hymenoptera as well as specific investigations into the genomic changes associated with ecological speciation and transitions to asexuality.

Tunable Superconducting Cavity using Superconducting Quantum Interference Device Metamaterials.

Here we consider a tunable superconducting cavity that can be used either as a tunable coupler to a qubit inside the cavity or as a tunable low noise, low temperature, RF filter. Our design consists of an array of radio-frequency superconducting quantum interference devices (rf SQUIDs) inside a superconducting cavity. This forms a tunable metamaterial structure which couples to the cavity through its magnetic plasma frequency. By tuning the resonant frequency of the metamaterial through an applied magnetic flux, one can tune the cavity mode profile. This allows us to detune the cavity initially centered at 5.593 GHz by over 200 MHz. The maximum quality factor approaches that of the empty cavity, which is 4.5 × 106. The metamaterial electromagnetic response is controlled via a low-frequency or dc magnetic flux bias, and we present a control line architecture that is capable of applying sufficient magnetic flux bias with minimal parasitic coupling. Together this design allows for an in-situ tunable cavity which enables low-temperature quantum control applications.

Adaptive phenotypic plasticity in a clonal invader.

Organisms featuring wide trait variability and occurring in a wide range of habitats, such as the ovoviviparous New Zealand freshwater snail Potamopyrgus antipodarum, are ideal models to study adaptation. Since the mid-19th century, P. antipodarum, characterized by extremely variable shell morphology, has successfully invaded aquatic areas on four continents. Because these obligately and wholly asexual invasive populations harbor low genetic diversity compared to mixed sexual/asexual populations in the native range, we hypothesized that (1) this phenotypic variation in the invasive range might be adaptive with respect to colonization of novel habitats, and (2) that at least some of the variation might be caused by phenotypic plasticity. We surveyed 425 snails from 21 localities across northwest Europe to attempt to disentangle genetic and environmental effects on shell morphology. We analyzed brood size as proxy for fitness and shell geometric morphometrics, while controlling for genetic background. Our survey revealed 10 SNP genotypes nested into two mtDNA haplotypes and indicated that mainly lineage drove variation in shell shape but not size. Physicochemical parameters affected both shell shape and size and the interaction of these traits with brood size. In particular, stronger stream flow rates were associated with larger shells. Our measurements of brood size suggested that relatively larger slender snails with relatively large apertures were better adapted to strong flow than counterparts with broader shells and relatively small apertures. In conclusion, the apparent potential to modify shell morphology plays likely a key role in the invasive success of P. antipodarum; the two main components of shell morphology, namely shape and size, being differentially controlled, the former mainly genetically and the latter predominantly by phenotypic plasticity.

Bivalent complexes of PRC1 with orthologs of BRD4 and MOZ/MORF target developmental genes in Drosophila.

Regulatory decisions in Drosophila require Polycomb group (PcG) proteins to maintain the silent state and Trithorax group (TrxG) proteins to oppose silencing. Since PcG and TrxG are ubiquitous and lack apparent sequence specificity, a long-standing model is that targeting occurs via protein interactions; for instance, between repressors and PcG proteins. Instead, we found that Pc-repressive complex 1 (PRC1) purifies with coactivators Fs(1)h [female sterile (1) homeotic] and Enok/Br140 during embryogenesis. Fs(1)h is a TrxG member and the ortholog of BRD4, a bromodomain protein that binds to acetylated histones and is a key transcriptional coactivator in mammals. Enok and Br140, another bromodomain protein, are orthologous to subunits of a mammalian MOZ/MORF acetyltransferase complex. Here we confirm PRC1-Br140 and PRC1-Fs(1)h interactions and identify their genomic binding sites. PRC1-Br140 bind developmental genes in fly embryos, with analogous co-occupancy of PRC1 and a Br140 ortholog, BRD1, at bivalent loci in human embryonic stem (ES) cells. We propose that identification of PRC1-Br140 "bivalent complexes" in fly embryos supports and extends the bivalency model posited in mammalian cells, in which the coexistence of H3K4me3 and H3K27me3 at developmental promoters represents a poised transcriptional state. We further speculate that local competition between acetylation and deacetylation may play a critical role in the resolution of bivalent protein complexes during development.