Analysis of homeodomain specificities allows the family-wide prediction of preferred recognition sites.

We describe the comprehensive characterization of homeodomain DNA-binding specificities from a metazoan genome. The analysis of all 84 independent homeodomains from D. melanogaster reveals the breadth of DNA sequences that can be specified by this recognition motif. The majority of these factors can be organized into 11 different specificity groups, where the preferred recognition sequence between these groups can differ at up to four of the six core recognition positions. Analysis of the recognition motifs within these groups led to a catalog of common specificity determinants that may cooperate or compete to define the binding site preference. With these recognition principles, a homeodomain can be reengineered to create factors where its specificity is altered at the majority of recognition positions. This resource also allows prediction of homeodomain specificities from other organisms, which is demonstrated by the prediction and analysis of human homeodomain specificities.

Editing out five Serpina1 paralogs to create a mouse model of genetic emphysema.

Chronic obstructive pulmonary disease affects 10% of the worldwide population, and the leading genetic cause is α-1 antitrypsin (AAT) deficiency. Due to the complexity of the murine locus, which includes up to six Serpina1 paralogs, no genetic animal model of the disease has been successfully generated until now. Here we create a quintuple Serpina1a-e knockout using CRISPR/Cas9-mediated genome editing. The phenotype recapitulates the human disease phenotype, i.e., absence of hepatic and circulating AAT translates functionally to a reduced capacity to inhibit neutrophil elastase. With age, Serpina1 null mice develop emphysema spontaneously, which can be induced in younger mice by a lipopolysaccharide challenge. This mouse models not only AAT deficiency but also emphysema and is a relevant genetic model and not one based on developmental impairment of alveolarization or elastase administration. We anticipate that this unique model will be highly relevant not only to the preclinical development of therapeutics for AAT deficiency, but also to emphysema and smoking research.

DNA-binding-domain fusions enhance the targeting range and precision of Cas9.

The CRISPR-Cas9 system is commonly used in biomedical research; however, the precision of Cas9 is suboptimal for applications that involve editing a large population of cells (for example, gene therapy). Variations on the standard Cas9 system have yielded improvements in the precision of targeted DNA cleavage, but they often restrict the range of targetable sequences. It remains unclear whether these variants can limit lesions to a single site in the human genome over a large cohort of treated cells. Here we show that by fusing a programmable DNA-binding domain (pDBD) to Cas9 and attenuating Cas9's inherent DNA-binding affinity, we were able to produce a Cas9-pDBD chimera with dramatically improved precision and an increased targeting range. Because the specificity and affinity of this framework can be easily tuned, Cas9-pDBDs provide a flexible system that can be tailored to achieve extremely precise genome editing at nearly any genomic locus.

Global analysis of Drosophila Cys2-His2 zinc finger proteins reveals a multitude of novel recognition motifs and binding determinants.

Cys2-His2 zinc finger proteins (ZFPs) are the largest group of transcription factors in higher metazoans. A complete characterization of these ZFPs and their associated target sequences is pivotal to fully annotate transcriptional regulatory networks in metazoan genomes. As a first step in this process, we have characterized the DNA-binding specificities of 129 zinc finger sets from Drosophila using a bacterial one-hybrid system. This data set contains the DNA-binding specificities for at least one encoded ZFP from 70 unique genes and 23 alternate splice isoforms representing the largest set of characterized ZFPs from any organism described to date. These recognition motifs can be used to predict genomic binding sites for these factors within the fruit fly genome. Subsets of fingers from these ZFPs were characterized to define their orientation and register on their recognition sequences, thereby allowing us to define the recognition diversity within this finger set. We find that the characterized fingers can specify 47 of the 64 possible DNA triplets. To confirm the utility of our finger recognition models, we employed subsets of Drosophila fingers in combination with an existing archive of artificial zinc finger modules to create ZFPs with novel DNA-binding specificity. These hybrids of natural and artificial fingers can be used to create functional zinc finger nucleases for editing vertebrate genomes.

An improved predictive recognition model for Cys(2)-His(2) zinc finger proteins.

Cys(2)-His(2) zinc finger proteins (ZFPs) are the largest family of transcription factors in higher metazoans. They also represent the most diverse family with regards to the composition of their recognition sequences. Although there are a number of ZFPs with characterized DNA-binding preferences, the specificity of the vast majority of ZFPs is unknown and cannot be directly inferred by homology due to the diversity of recognition residues present within individual fingers. Given the large number of unique zinc fingers and assemblies present across eukaryotes, a comprehensive predictive recognition model that could accurately estimate the DNA-binding specificity of any ZFP based on its amino acid sequence would have great utility. Toward this goal, we have used the DNA-binding specificities of 678 two-finger modules from both natural and artificial sources to construct a random forest-based predictive model for ZFP recognition. We find that our recognition model outperforms previously described determinant-based recognition models for ZFPs, and can successfully estimate the specificity of naturally occurring ZFPs with previously defined specificities.

Computational identification of diverse mechanisms underlying transcription factor-DNA occupancy.

ChIP-based genome-wide assays of transcription factor (TF) occupancy have emerged as a powerful, high-throughput method to understand transcriptional regulation, especially on a global scale. This has led to great interest in the underlying biochemical mechanisms that direct TF-DNA binding, with the ultimate goal of computationally predicting a TF's occupancy profile in any cellular condition. In this study, we examined the influence of various potential determinants of TF-DNA binding on a much larger scale than previously undertaken. We used a thermodynamics-based model of TF-DNA binding, called "STAP," to analyze 45 TF-ChIP data sets from Drosophila embryonic development. We built a cross-validation framework that compares a baseline model, based on the ChIP'ed ("primary") TF's motif, to more complex models where binding by secondary TFs is hypothesized to influence the primary TF's occupancy. Candidates interacting TFs were chosen based on RNA-SEQ expression data from the time point of the ChIP experiment. We found widespread evidence of both cooperative and antagonistic effects by secondary TFs, and explicitly quantified these effects. We were able to identify multiple classes of interactions, including (1) long-range interactions between primary and secondary motifs (separated by ≤150 bp), suggestive of indirect effects such as chromatin remodeling, (2) short-range interactions with specific inter-site spacing biases, suggestive of direct physical interactions, and (3) overlapping binding sites suggesting competitive binding. Furthermore, by factoring out the previously reported strong correlation between TF occupancy and DNA accessibility, we were able to categorize the effects into those that are likely to be mediated by the secondary TF's effect on local accessibility and those that utilize accessibility-independent mechanisms. Finally, we conducted in vitro pull-down assays to test model-based predictions of short-range cooperative interactions, and found that seven of the eight TF pairs tested physically interact and that some of these interactions mediate cooperative binding to DNA.

Simulations of enhancer evolution provide mechanistic insights into gene regulation.

There is growing interest in models of regulatory sequence evolution. However, existing models specifically designed for regulatory sequences consider the independent evolution of individual transcription factor (TF)-binding sites, ignoring that the function and evolution of a binding site depends on its context, typically the cis-regulatory module (CRM) in which the site is located. Moreover, existing models do not account for the gene-specific roles of TF-binding sites, primarily because their roles often are not well understood. We introduce two models of regulatory sequence evolution that address some of the shortcomings of existing models and implement simulation frameworks based on them. One model simulates the evolution of an individual binding site in the context of a CRM, while the other evolves an entire CRM. Both models use a state-of-the art sequence-to-expression model to predict the effects of mutations on the regulatory output of the CRM and determine the strength of selection. We use the new framework to simulate the evolution of TF-binding sites in 37 well-studied CRMs belonging to the anterior-posterior patterning system in Drosophila embryos. We show that these simulations provide accurate fits to evolutionary data from 12 Drosophila genomes, which includes statistics of binding site conservation on relatively short evolutionary scales and site loss across larger divergence times. The new framework allows us, for the first time, to test hypotheses regarding the underlying cis-regulatory code by directly comparing the evolutionary implications of the hypothesis with the observed evolutionary dynamics of binding sites. Using this capability, we find that explicitly modeling self-cooperative DNA binding by the TF Caudal (CAD) provides significantly better fits than an otherwise identical evolutionary simulation that lacks this mechanistic aspect. This hypothesis is further supported by a statistical analysis of the distribution of intersite spacing between adjacent CAD sites. Experimental tests confirm direct homodimeric interaction between CAD molecules as well as self-cooperative DNA binding by CAD. We note that computational modeling of the D. melanogaster CRMs alone did not yield significant evidence to support CAD self-cooperativity. We thus demonstrate how specific mechanistic details encoded in CRMs can be revealed by modeling their evolution and fitting such models to multispecies data.

Widespread evidence of cooperative DNA binding by transcription factors in Drosophila development.

Regulation of eukaryotic gene transcription is often combinatorial in nature, with multiple transcription factors (TFs) regulating common target genes, often through direct or indirect mutual interactions. Many individual examples of cooperative binding by directly interacting TFs have been identified, but it remains unclear how pervasive this mechanism is during animal development. Cooperative TF binding should be manifest in genomic sequences as biased arrangements of TF-binding sites. Here, we explore the extent and diversity of such arrangements related to gene regulation during Drosophila embryogenesis. We used the DNA-binding specificities of 322 TFs along with chromatin accessibility information to identify enriched spacing and orientation patterns of TF-binding site pairs. We developed a new statistical approach for this task, specifically designed to accurately assess inter-site spacing biases while accounting for the phenomenon of homotypic site clustering commonly observed in developmental regulatory regions. We observed a large number of short-range distance preferences between TF-binding site pairs, including examples where the preference depends on the relative orientation of the binding sites. To test whether these binding site patterns reflect physical interactions between the corresponding TFs, we analyzed 27 TF pairs whose binding sites exhibited short distance preferences. In vitro protein-protein binding experiments revealed that >65% of these TF pairs can directly interact with each other. For five pairs, we further demonstrate that they bind cooperatively to DNA if both sites are present with the preferred spacing. This study demonstrates how DNA-binding motifs can be used to produce a comprehensive map of sequence signatures for different mechanisms of combinatorial TF action.

Three structure-selective endonucleases are essential in the absence of BLM helicase in Drosophila.

DNA repair mechanisms in mitotically proliferating cells avoid generating crossovers, which can contribute to genome instability. Most models for the production of crossovers involve an intermediate with one or more four-stranded Holliday junctions (HJs), which are resolved into duplex molecules through cleavage by specialized endonucleases. In vitro studies have implicated three nuclear enzymes in HJ resolution: MUS81-EME1/Mms4, GEN1/Yen1, and SLX4-SLX1. The Bloom syndrome helicase, BLM, plays key roles in preventing mitotic crossover, either by blocking the formation of HJ intermediates or by removing HJs without cleavage. Saccharomyces cerevisiae mutants that lack Sgs1 (the BLM ortholog) and either Mus81-Mms4 or Slx4-Slx1 are inviable, but mutants that lack Sgs1 and Yen1 are viable. The current view is that Yen1 serves primarily as a backup to Mus81-Mms4. Previous studies with Drosophila melanogaster showed that, as in yeast, loss of both DmBLM and MUS81 or MUS312 (the ortholog of SLX4) is lethal. We have now recovered and analyzed mutations in Drosophila Gen. As in yeast, there is some redundancy between Gen and mus81; however, in contrast to the case in yeast, GEN plays a more predominant role in responding to DNA damage than MUS81-MMS4. Furthermore, loss of DmBLM and GEN leads to lethality early in development. We present a comparison of phenotypes occurring in double mutants that lack DmBLM and either MUS81, GEN, or MUS312, including chromosome instability and deficiencies in cell proliferation. Our studies of synthetic lethality provide insights into the multiple functions of DmBLM and how various endonucleases may function when DmBLM is absent.

Recognition models to predict DNA-binding specificities of homeodomain proteins.

MOTIVATION: Recognition models for protein-DNA interactions, which allow the prediction of specificity for a DNA-binding domain based only on its sequence or the alteration of specificity through rational design, have long been a goal of computational biology. There has been some progress in constructing useful models, especially for C(2)H(2) zinc finger proteins, but it remains a challenging problem with ample room for improvement. For most families of transcription factors the best available methods utilize k-nearest neighbor (KNN) algorithms to make specificity predictions based on the average of the specificities of the k most similar proteins with defined specificities. Homeodomain (HD) proteins are the second most abundant family of transcription factors, after zinc fingers, in most metazoan genomes, and as a consequence an effective recognition model for this family would facilitate predictive models of many transcriptional regulatory networks within these genomes. RESULTS: Using extensive experimental data, we have tested several machine learning approaches and find that both support vector machines and random forests (RFs) can produce recognition models for HD proteins that are significant improvements over KNN-based methods. Cross-validation analyses show that the resulting models are capable of predicting specificities with high accuracy. We have produced a web-based prediction tool, PreMoTF (Predicted Motifs for Transcription Factors) (http://stormo.wustl.edu/PreMoTF), for predicting position frequency matrices from protein sequence using a RF-based model.

Quantitative analysis of the Drosophila segmentation regulatory network using pattern generating potentials.

Cis-regulatory modules that drive precise spatial-temporal patterns of gene expression are central to the process of metazoan development. We describe a new computational strategy to annotate genomic sequences based on their "pattern generating potential" and to produce quantitative descriptions of transcriptional regulatory networks at the level of individual protein-module interactions. We use this approach to convert the qualitative understanding of interactions that regulate Drosophila segmentation into a network model in which a confidence value is associated with each transcription factor-module interaction. Sequence information from multiple Drosophila species is integrated with transcription factor binding specificities to determine conserved binding site frequencies across the genome. These binding site profiles are combined with transcription factor expression information to create a model to predict module activity patterns. This model is used to scan genomic sequences for the potential to generate all or part of the expression pattern of a nearby gene, obtained from available gene expression databases. Interactions between individual transcription factors and modules are inferred by a statistical method to quantify a factor's contribution to the module's pattern generating potential. We use these pattern generating potentials to systematically describe the location and function of known and novel cis-regulatory modules in the segmentation network, identifying many examples of modules predicted to have overlapping expression activities. Surprisingly, conserved transcription factor binding site frequencies were as effective as experimental measurements of occupancy in predicting module expression patterns or factor-module interactions. Thus, unlike previous module prediction methods, this method predicts not only the location of modules but also their spatial activity pattern and the factors that directly determine this pattern. As databases of transcription factor specificities and in vivo gene expression patterns grow, analysis of pattern generating potentials provides a general method to decode transcriptional regulatory sequences and networks.

Genome Surveyor 2.0: cis-regulatory analysis in Drosophila.

Genome Surveyor 2.0 is a web-based tool for discovery and analysis of cis-regulatory elements in Drosophila, built on top of the GBrowse genome browser for convenient visualization. Genome Surveyor was developed as a tool for predicting transcription factor (TF) binding targets and cis-regulatory modules (CRMs/enhancers), based on motifs representing experimentally determined DNA binding specificities. Since its first publication, we have added substantial new functionality (e.g. phylogenetic averaging of motif scores from multiple species, and a novel CRM discovery technique), increased the number of supported motifs about 4-fold (from ∼100 to ∼400), added provisions for evolutionary comparison across many more Drosophila species (from 2 to 12), and improved the user-interface. The server is free and open to all users, and there is no login requirement. Address: http://veda.cs.uiuc.edu/gs.

FlyFactorSurvey: a database of Drosophila transcription factor binding specificities determined using the bacterial one-hybrid system.

FlyFactorSurvey (http://pgfe.umassmed.edu/TFDBS/) is a database of DNA binding specificities for Drosophila transcription factors (TFs) primarily determined using the bacterial one-hybrid system. The database provides community access to over 400 recognition motifs and position weight matrices for over 200 TFs, including many unpublished motifs. Search tools and flat file downloads are provided to retrieve binding site information (as sequences, matrices and sequence logos) for individual TFs, groups of TFs or for all TFs with characterized binding specificities. Linked analysis tools allow users to identify motifs within our database that share similarity to a query matrix or to view the distribution of occurrences of an individual motif throughout the Drosophila genome. Together, this database and its associated tools provide computational and experimental biologists with resources to predict interactions between Drosophila TFs and target cis-regulatory sequences.

Up-regulation of cholesterol synthesis pathways and limited neurodegeneration in a knock-in Sod1 mutant mouse model of ALS.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disorder affecting brain and spinal cord motor neurons. Mutations in the copper/zinc superoxide dismutase gene ( SOD1 ) are associated with ∼20% of inherited and 1-2% of sporadic ALS cases. Much has been learned from mice expressing transgenic copies of mutant SOD1, which typically involve high-level transgene expression, thereby differing from ALS patients expressing one mutant gene copy. To generate a model that more closely represents patient gene expression, we created a knock-in point mutation (G85R, a human ALS-causing mutation) in the endogenous mouse Sod1 gene, leading to mutant SOD1 G85R protein expression. Heterozygous Sod1 G85R mutant mice resemble wild type, whereas homozygous mutants have reduced body weight and lifespan, a mild neurodegenerative phenotype, and express very low mutant SOD1 protein levels with no detectable SOD1 activity. Homozygous mutants exhibit partial neuromuscular junction denervation at 3-4 months of age. Spinal cord motor neuron transcriptome analyses of homozygous Sod1 G85R mice revealed up-regulation of cholesterol synthesis pathway genes compared to wild type. Transcriptome and phenotypic features of these mice are similar to Sod1 knock-out mice, suggesting the Sod1 G85R phenotype is largely driven by loss of SOD1 function. By contrast, cholesterol synthesis genes are down-regulated in severely affected human TgSOD1 G93A transgenic mice at 4 months. Our analyses implicate dysregulation of cholesterol or related lipid pathway genes in ALS pathogenesis. The Sod1 G85R knock-in mouse is a useful ALS model to examine the importance of SOD1 activity in control of cholesterol homeostasis and motor neuron survival. SIGNIFICANCE STATEMENT: Amyotrophic lateral sclerosis is a devastating disease involving the progressive loss of motor neurons and motor function for which there is currently no cure. Understanding biological mechanisms leading to motor neuron death is critical for developing new treatments. Using a new knock-in mutant mouse model carrying a Sod1 mutation that causes ALS in patients, and in the mouse, causes a limited neurodegenerative phenotype similar to Sod1 loss-of-function, we show that cholesterol synthesis pathway genes are up-regulated in mutant motor neurons, whereas the same genes are down-regulated in transgenic SOD1 mice with a severe phenotype. Our data implicate dysregulation of cholesterol or other related lipid genes in ALS pathogenesis and provide new insights that could contribute to strategies for disease intervention.

Cell-nonautonomous function of ceramidase in photoreceptor homeostasis.

Neutral ceramidase, a key enzyme of sphingolipid metabolism, hydrolyzes ceramide to sphingosine. These sphingolipids are critical structural components of cell membranes and act as second messengers in diverse signal transduction cascades. Here, we have isolated and characterized functional null mutants of Drosophila ceramidase. We show that secreted ceramidase functions in a cell-nonautonomous manner to maintain photoreceptor homeostasis. In the absence of ceramidase, photoreceptors degenerate in a light-dependent manner, are defective in normal endocytic turnover of rhodopsin, and do not respond to light stimulus. Consistent with a cell-nonautonomous function, overexpression of ceramidase in tissues distant from photoreceptors suppresses photoreceptor degeneration in an arrestin mutant and facilitates membrane turnover in a rhodopsin null mutant. Furthermore, our results show that secreted ceramidase is internalized and localizes to endosomes. Our findings establish a role for a secreted sphingolipid enzyme in the regulation of photoreceptor structure and function.

p53 represses class switch recombination to IgG2a through its antioxidant function.

Ig class switch recombination (CSR) occurs in activated mature B cells, and causes an exchange of the IgM isotype for IgG, IgE, or IgA isotypes, which increases the effectiveness of the humoral immune response. DNA ds breaks in recombining switch (S) regions, where CSR occurs, are required for recombination. Activation-induced cytidine deaminase initiates DNA ds break formation by deamination of cytosines in S regions. This reaction requires reactive oxygen species (ROS) intermediates, such as hydroxyl radicals. In this study we show that the ROS scavenger N-acetylcysteine inhibits CSR. We also demonstrate that IFN-gamma treatment, which is used to induce IgG2a switching, increases intracellular ROS levels, and activates p53 in switching B cells, and show that p53 inhibits IgG2a class switching through its antioxidant-regulating function. Finally, we show that p53 inhibits DNA breaks and mutations in S regions in B cells undergoing CSR, suggesting that p53 inhibits the activity of activation-induced cytidine deaminase.

Cell-Type-Specific Circadian Bioluminescence Rhythms in Dbp Reporter Mice.

Circadian rhythms are endogenously generated physiological and molecular rhythms with a cycle length of about 24 h. Bioluminescent reporters have been exceptionally useful for studying circadian rhythms in numerous species. Here, we report development of a reporter mouse generated by modification of a widely expressed and highly rhythmic gene encoding D-site albumin promoter binding protein (Dbp). In this line of mice, firefly luciferase is expressed from the Dbp locus in a Cre recombinase-dependent manner, allowing assessment of bioluminescence rhythms in specific cellular populations. A mouse line in which luciferase expression was Cre-independent was also generated. The Dbp reporter alleles do not alter Dbp gene expression rhythms in liver or circadian locomotor activity rhythms. In vivo and ex vivo studies show the utility of the reporter alleles for monitoring rhythmicity. Our studies reveal cell-type-specific characteristics of rhythms among neuronal populations within the suprachiasmatic nuclei ex vivo. In vivo studies show Dbp-driven bioluminescence rhythms in the liver of Albumin-Cre;DbpKI/+ "liver reporter" mice. After a shift of the lighting schedule, locomotor activity achieved the proper phase relationship with the new lighting cycle more rapidly than hepatic bioluminescence did. As previously shown, restricting food access to the daytime altered the phase of hepatic rhythmicity. Our model allowed assessment of the rate of recovery from misalignment once animals were provided with food ad libitum. These studies confirm the previously demonstrated circadian misalignment following environmental perturbations and reveal the utility of this model for minimally invasive, longitudinal monitoring of rhythmicity from specific mouse tissues.

Allele-Specific Knockdown of Mutant Huntingtin Protein via Editing at Coding Region Single Nucleotide Polymorphism Heterozygosities.

Huntington's disease (HD) is a devastating, autosomal dominant neurodegenerative disease caused by a trinucleotide repeat expansion in the huntingtin (HTT) gene. Inactivation of the mutant allele by clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 based gene editing offers a possible therapeutic approach for this disease, but permanent disruption of normal HTT function might compromise adult neuronal function. Here, we use a novel HD mouse model to examine allele-specific editing of mutant HTT (mHTT), with a BAC97 transgene expressing mHTT and a YAC18 transgene expressing normal HTT. We achieve allele-specific inactivation of HTT by targeting a protein coding sequence containing a common, heterozygous single nucleotide polymorphism (SNP). The outcome is a marked and allele-selective reduction of mHTT protein in a mouse model of HD. Expression of a single CRISPR-Cas9 nuclease in neurons generated a high frequency of mutations in the targeted HD allele that included both small insertion/deletion (InDel) mutations and viral vector insertions. Thus, allele-specific targeting of InDel and insertion mutations to heterozygous coding region SNPs provides a feasible approach to inactivate autosomal dominant mutations that cause genetic disease.

CRISPR/Cas9-mediated excision of ALS/FTD-causing hexanucleotide repeat expansion in C9ORF72 rescues major disease mechanisms in vivo and in vitro.

A GGGGCC24+ hexanucleotide repeat expansion (HRE) in the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), fatal neurodegenerative diseases with no cure or approved treatments that substantially slow disease progression or extend survival. Mechanistic underpinnings of neuronal death include C9ORF72 haploinsufficiency, sequestration of RNA-binding proteins in the nucleus, and production of dipeptide repeat proteins. Here, we used an adeno-associated viral vector system to deliver CRISPR/Cas9 gene-editing machineries to effectuate the removal of the HRE from the C9ORF72 genomic locus. We demonstrate successful excision of the HRE in primary cortical neurons and brains of three mouse models containing the expansion (500-600 repeats) as well as in patient-derived iPSC motor neurons and brain organoids (450 repeats). This resulted in a reduction of RNA foci, poly-dipeptides and haploinsufficiency, major hallmarks of C9-ALS/FTD, making this a promising therapeutic approach to these diseases.