In pursuit of design principles of regulatory sequences

SMARCAL1, the annealing helicase and the transcriptional co-regulator

The ATP-dependent chromatin remodeling proteins play an important role in DNA repair. The energy released by ATP hydrolysis is used for myriad functions ranging from nucleosome repositioning and nucleosome eviction to histone variant exchange. In addition, the distant member of the family, SMARCAL1, uses the energy to reanneal stalled replication forks in response to DNA damage. Biophysical studies have shown that this protein has the unique ability to recognize and bind specifically to DNA structures possessing double-strand to single-strand transition regions. Mutations in SMARCAL1 have been linked to Schimke immuno-osseous dysplasia, an autosomal recessive disorder that exhibits variable penetrance and expressivity. It has long been hypothesized that the variable expressivity and pleiotropic phenotypes observed in the patients might be due to the ability of SMARCAL1 to co-regulate the expression of a subset of genes within the genome. Recently, the role of SMARCAL1 in regulating transcription has been delineated. In this review, we discuss the biophysical and functional properties of the protein that help it to transcriptionally co-regulate DNA damage response as well as to bind to the stalled replication fork and stabilize it, thus ensuring genomic stability. We also discuss the role of SMARCAL1 in cancer and the possibility of using this protein as a chemotherapeutic target.

Search and Capture: Disorder Rules Gene Promoter Selection

Intrinsically disordered regions (IDRs) are preponderant in transcription factors (TFs) and are evolutionarily less conserved vis-à-vis DNA-binding domains (DBDs). Unexpected findings from Barkai and colleagues, which demonstrate that promoter selectivity is determined by IDRs, should significantly enhance our understanding of gene expression regulation.

Design of orthogonal regulatory systems for modulating gene expression in plants

Agricultural biotechnology strategies often require the precise regulation of multiple genes to effectively modify complex plant traits. However, most efforts are hindered by a lack of characterized tools that allow for reliable and targeted expression of transgenes. We have successfully engineered a library of synthetic transcriptional regulators that modulate expression strength in planta. By leveraging orthogonal regulatory systems from Saccharomyces spp., we have developed a strategy for the design of synthetic activators, synthetic repressors, and synthetic promoters and have validated their use in Nicotiana benthamiana and Arabidopsis thaliana. This characterization of contributing genetic elements that dictate gene expression represents a foundation for the rational design of refined synthetic regulators. Our findings demonstrate that these tools provide variation in transcriptional output while enabling the concerted expression of multiple genes in a tissue-specific and environmentally responsive manner, providing a basis for generating complex genetic circuits that process endogenous and environmental stimuli.

A sequential methodology for the rapid identification and characterization of breast cancer-associated functional SNPs

GWAS cannot identify functional SNPs (fSNP) from disease-associated SNPs in linkage disequilibrium (LD). Here, we report developing three sequential methodologies including Reel-seq (Regulatory element-sequencing) to identify fSNPs in a high-throughput fashion, SDCP-MS (SNP-specific DNA competition pulldown-mass spectrometry) to identify fSNP-bound proteins and AIDP-Wb (allele-imbalanced DNA pulldown-Western blot) to detect allele-specific protein:fSNP binding. We first apply Reel-seq to screen a library containing 4316 breast cancer-associated SNPs and identify 521 candidate fSNPs. As proof of principle, we verify candidate fSNPs on three well-characterized loci: FGFR2, MAP3K1 and BABAM1. Next, using SDCP-MS and AIDP-Wb, we rapidly identify multiple regulatory factors that specifically bind in an allele-imbalanced manner to the fSNPs on the FGFR2 locus. We finally demonstrate that the factors identified by SDCP-MS can regulate risk gene expression. These data suggest that the sequential application of Reel-seq, SDCP-MS, and AIDP-Wb can greatly help to translate large sets of GWAS data into biologically relevant information.

New insights into the variability of lactic acid production in Lachancea thermotolerans at the phenotypic and genomic level

Non-conventional yeasts are increasingly applied in fermented beverage industry to obtain distinctive products with improved quality. Among these yeasts, Lachancea thermotolerans has multiple features of industrial relevance, especially the production of l(+)-lactic acid (LA), useful for the biological acidification of wine and beer. Since few information is available on this peculiar activity, the current study aimed to explore the physiological and genetic variability among L. thermotolerans strains. From a strain collection, mostly isolated from wine, a huge phenotypic diversity was acknowledged and allowed the selection of a high (SOL13) and a low (COLC27) LA producer. Comparative whole-genome sequencing of these two selected strains and the type strain CBS 6340^T showed a high similarity in terms of gene content and functional annotation. Notwithstanding, target gene-based analysis revealed variations between high and low producers in the key gene sequences related to LA accumulation. More in-depth investigation of the core promoters and expression analysis of the genes ldh, encoding lactate dehydrogenase, indicated the transcriptional regulation may be the principal cause behind phenotypic differences. These findings highlighted the usefulness of whole-genome sequencing coupled with expression analysis. They provided crucial genetic insights for a deeper investigation of the intraspecific variability in LA production pathway.

GTRD: a database on gene transcription regulation-2019 update

The current version of the Gene Transcription Regulation Database (GTRD; http://gtrd.biouml.org) contains information about: (i) transcription factor binding sites (TFBSs) and transcription coactivators identified by ChIP-seq experiments for Homo sapiens, Mus musculus, Rattus norvegicus, Danio rerio, Caenorhabditis elegans, Drosophila melanogaster, Saccharomyces cerevisiae, Schizosaccharomyces pombe and Arabidopsis thaliana; (ii) regions of open chromatin and TFBSs (DNase footprints) identified by DNase-seq; (iii) unmappable regions where TFBSs cannot be identified due to repeats; (iv) potential TFBSs for both human and mouse using position weight matrices from the HOCOMOCO database. Raw ChIP-seq and DNase-seq data were obtained from ENCODE and SRA, and uniformly processed. ChIP-seq peaks were called using four different methods: MACS, SISSRs, GEM and PICS. Moreover, peaks for the same factor and peak calling method, albeit using different experiment conditions (cell line, treatment, etc.), were merged into clusters. To reduce noise, such clusters for different peak calling methods were merged into meta-clusters; these were considered to be non-redundant TFBS sets. Moreover, extended quality control was applied to all ChIP-seq data. Web interface to access GTRD was developed using the BioUML platform. It provides browsing and displaying information, advanced search possibilities and an integrated genome browser.

Regulatory SNP rs5743417 impairs constitutive expression of human β-defensin 1 and has high frequency in Africans and Afro-Americans

The prediction of regulatory single nucleotide polymorphisms (rSNPs) in proximal promoters of disease-related genes could be a useful tool for personalized medicine in both patient stratification and customized therapy. Using our previously reported method of rSNPs prediction (currently a software called SNPClinic v.1.0) as well as with PredictSNP tool, we performed in silico prediction of regulatory SNPs in the antimicrobial peptide human β-defensin 1 gene in three human cell lines from 1,000 Genomes Project (1kGP), namely A549 (epithelial cell line), HL-60 (neutrophils) and T_H 1 (lymphocytes). These predictions were run in a proximal pseudo-promoter comprising all common alleles on each polymorphic site according to the 1,000 Genomes Project data (1kGP: ALL). Plasmid vectors containing either the major or the minor allele of a putative rSNP rs5743417 (categorized as regulatory by SNPClinic and confirmed by PredictSNP) and a non-rSNP negative control were transfected to lung A549 human epithelial cell line. We assessed functionality of rSNPs by qPCR using the Pfaffl method. In A549 cells, minor allele of the SNP rs5743417 G→A showed a significant reduction in gene expression, diminishing DEFB1 transcription by 33% when compared with the G major allele (p-value = .03). SNP rs5743417 minor allele has high frequency in Gambians (8%, 1kGP population: GWD) and Afro-Americans (3.3%, 1kGP population: ASW). This SNP alters three transcription factors binding sites (TFBSs) comprising SREBP2 (sterols and haematopoietic pathways), CREB1 (cAMP, insulin and TNF pathways) and JUND (apoptosis, senescence and stress pathways) in the proximal promoter of DEFB1. Further in silico analysis reveals that this SNP also overlaps with GS1-24F4.2, a lincRNA gene complementary to the X Kell blood group related 5 (XKR5) mRNA. The potential clinical impact of the altered constitutive expression of DEFB1 caused by rSNP rs5743417 in DEFB1-associated diseases as tuberculosis, COPD, asthma, cystic fibrosis and cancer in African and Afro-American populations deserves further research.

Enhancer Features that Drive Formation of Transcriptional Condensates

Enhancers are DNA elements that are bound by transcription factors (TFs), which recruit coactivators and the transcriptional machinery to genes. Phase-separated condensates of TFs and coactivators have been implicated in assembling the transcription machinery at particular enhancers, yet the role of DNA sequence in this process has not been explored. We show that DNA sequences encoding TF binding site number, density, and affinity above sharply defined thresholds drive condensation of TFs and coactivators. A combination of specific structured (TF-DNA) and weak multivalent (TF-coactivator) interactions allows for condensates to form at particular genomic loci determined by the DNA sequence and the complement of expressed TFs. DNA features found to drive condensation promote enhancer activity and transcription in cells. Our study provides a framework to understand how the genome can scaffold transcriptional condensates at specific loci and how the universal phenomenon of phase separation might regulate this process.

The Bivalent Genome: Characterization, Structure, and Regulation

An intricate molecular machinery is at the core of gene expression regulation in every cell. During the initial stages of organismal development, the coordinated activation of diverse transcriptional programs is crucial and must be carefully executed to shape every organ and tissue. Bivalent promoters and poised enhancers are regulatory regions decorated with histone marks that are associated with both positive and negative transcriptional outcomes. These apparently contradictory signals are important for setting bivalent genes in a poised state, which is subsequently resolved during differentiation into either active or repressive states. We discuss the origins of bivalent promoters and the mechanisms implicated in their acquisition and maintenance. We further review how the presence of bivalent marks influences genome architecture. Finally, we highlight the potential link between bivalency and cancer which could drive biomedical research in disease etiology and treatment.

Promoter Activity Buffering Reduces the Fitness Cost of Misregulation

Organisms regulate gene expression through changes in the activity of transcription factors (TFs). In yeast, the response of genes to changes in TF activity is generally assumed to be encoded in the promoter. To directly test this assumption, we chose 42 genes and, for each, replaced the promoter with a synthetic inducible promoter and measured how protein expression changes as a function of TF activity. Most genes exhibited gene-specific TF dose-response curves not due to differences in mRNA stability, translation, or protein stability. Instead, most genes have an intrinsic ability to buffer the effects of promoter activity. This can be encoded in the open reading frame and the 3' end of genes and can be implemented by both autoregulatory feedback and by titration of limiting trans regulators. We show experimentally and computationally that, when misexpression of a gene is deleterious, this buffering insulates cells from fitness defects due to misregulation.

CRISPRa-mediated FOXP3 gene upregulation in mammalian cells

BACKGROUND

Forkhead box P3+ (FOXP3 +) regulatory T cells (Tregs) are a subset of lymphocytes, critical for the maintenance of immune homeostasis. Loss-of-function mutations of the FOXP3 gene in animal models and humans results in loss of differentiation potential into Treg cells and are responsible for several immune-mediated inflammatory diseases. Strategies of increasing FOXP3 expression represent a potential approach to increase the pool of Tregs within the lymphocyte population and may be employed in therapies of diverse autoimmune conditions. In the present study, a dCas9 CRISPR-based method was systematically employed to achieve upregulation and sustained high expression of endogenous FOXP3 in HEK293 and human Jurkat T cell lines through targeting of the core promotor, three known regulatory regions of the FOXP3 gene (CNS1-3), and two additional regions selected through extensive bioinformatics analysis (Cage1 and Cage2).

RESULTS

Using an activator-domain fusion based dCas9 transcription activator, robust upregulation of FOXP3 was achieved, and an optimal combination of single guide RNAs was selected, which exerted an additive effect on FOXP3 gene upregulation. Simultaneous targeting of FOXP3 and EOS, a transcription factor known to act in concert with FOXP3 in initiating a Treg phenotype, resulted in upregulation of FOXP3 downstream genes CD25 and TNFR2. When compared to ectopic expression of FOXP3 via plasmid electroporation, upregulation of endogenous FOXP3 via the Cas9-based method resulted in prolonged expression of FOXP3 in Jurkat cells.

CONCLUSIONS

Transfection of both HEK293 and Jurkat cells with dCas9-activators showed that regulatory regions downstream and upstream of FOXP3 promoter can be very potent transcription inducers in comparison to targeting the core promoter. While introduction of genes by conventional methods of gene therapy may involve a risk of insertional mutagenesis due to viral integration into the genome, transient up- or down-regulation of transcription by a CRISPR-dCas9 approach may resolve this safety concern. dCas9-based systems provide great promise in DNA footprint-free phenotype perturbations (perturbation without the risk of DNA damage) to drive development of transcription modulation-based therapies.

Modulating transcription through development of semi-synthetic yeast core promoters

Altering gene expression regulation by promoter engineering is a very effective way to fine-tune heterologous pathways in eukaryotic hosts. Typically, pathway building approaches in yeast still use a limited set of long, native promoters. With the today’s introduction of longer and more complex pathways, an expansion of this synthetic biology toolbox is necessary. In this study we elucidated the core promoter structure of the well-characterized yeast TEF1 promoter and determined the minimal length needed for sufficient protein expression. Furthermore, this minimal core promoter sequence was used for the creation of a promoter library covering different expression strengths. This resulted in a group of short, 69 bp promoters with an 8.0-fold expression range. One exemplar had a two and four times higher expression compared to the native CYC1 and ADH1 promoter, respectively. Additionally, as it was described that the protein expression range could be broadened by upstream activating sequences (UASs), we integrated earlier described single and multiple short, synthetic UASs in front of the strongest yeast core promoter. This approach resulted to further variation in protein expression and an overall promoter library spanning a 20-fold activity range and covering a length from 69 bp to maximally 129 bp. Furthermore, the robustness of this library was assessed on three alternative carbon sources besides glucose. As such, the suitability of short yeast core promoters for metabolic engineering applications on different media, either in an individual context or combined with UAS elements, was demonstrated.

Clock-controlled rhythmic transcription: is the clock enough and how does it work?

Circadian clocks regulate the rhythmic expression of thousands of genes underlying the daily oscillations of biological functions. Here, we discuss recent findings showing that circadian clock rhythmic transcriptional outputs rely on additional mechanisms than just clock gene DNA binding, which may ultimately contribute to the plasticity of circadian transcriptional programs.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

What functional genomics has taught us about transcriptional regulation in malaria parasites

Malaria parasites are characterized by a complex life cycle that is accompanied by dynamic gene expression patterns. The factors and mechanisms that regulate gene expression in these parasites have been searched for even before the advent of next generation sequencing technologies. Functional genomics approaches have substantially boosted this area of research and have yielded significant insights into the interplay between epigenetic, transcriptional and post-transcriptional mechanisms. Recently, considerable progress has been made in identifying sequence-specific transcription factors and DNA-encoded regulatory elements. Here, we review the insights obtained from these efforts including the characterization of core promoters, the involvement of sequence-specific transcription factors in life cycle progression and the mapping of gene regulatory elements. Furthermore, we discuss recent developments in the field of functional genomics and how they might contribute to further characterization of this complex gene regulatory network.

Profiling DNA methylation patterns of zebrafish liver associated with parental high dietary arachidonic acid

Diet has been shown to influence epigenetic key players, such as DNA methylation, which can regulate the gene expression potential in both parents and offspring. Diets enriched in omega-6 and deficient in omega-3 PUFAs (low dietary omega-3/omega-6 PUFA ratio), have been associated with the promotion of pathogenesis of diseases in humans and other mammals. In this study, we investigated the impact of increased dietary intake of arachidonic acid (ARA), a physiologically important omega-6 PUFA, on 2 generations of zebrafish. Parental fish were fed either a low or a high ARA diet, while the progeny of both groups were fed the low ARA diet. We screened for DNA methylation on single base-pair resolution using reduced representation bisulfite sequencing (RRBS). The DNA methylation profiling revealed significant differences between the dietary groups in both parents and offspring. The majority of differentially methylated loci associated with high dietary ARA were found in introns and intergenic regions for both generations. Common loci between the identified differentially methylated loci in F0 and F1 livers were reported. We described overlapping gene annotations of identified methylation changes with differential expression, but based on a small number of overlaps. The present study describes the diet-associated methylation profiles across genomic regions, and it demonstrates that parental high dietary ARA modulates DNA methylation patterns in zebrafish liver.

Saturation mutagenesis of twenty disease-associated regulatory elements at single base-pair resolution

The majority of common variants associated with common diseases, as well as an unknown proportion of causal mutations for rare diseases, fall in noncoding regions of the genome. Although catalogs of noncoding regulatory elements are steadily improving, we have a limited understanding of the functional effects of mutations within them. Here, we perform saturation mutagenesis in conjunction with massively parallel reporter assays on 20 disease-associated gene promoters and enhancers, generating functional measurements for over 30,000 single nucleotide substitutions and deletions. We find that the density of putative transcription factor binding sites varies widely between regulatory elements, as does the extent to which evolutionary conservation or integrative scores predict functional effects. These data provide a powerful resource for interpreting the pathogenicity of clinically observed mutations in these disease-associated regulatory elements, and comprise a rich dataset for the further development of algorithms that aim to predict the regulatory effects of noncoding mutations.

Transcriptional Enhancers in the FOXP2 Locus Underwent Accelerated Evolution in the Human Lineage

Unique human features such as complex language are the result of molecular evolutionary changes that modified developmental programs of our brain. The human-specific evolution of the forkhead box P2 (FOXP2) gene coding region has been linked to the emergence of speech and language in the human kind. However, little is known about how the expression of FOXP2 is regulated and if its regulatory machinery evolved in a lineage-specific manner in humans. In order to identify FOXP2 regulatory regions containing human-specific changes we used databases of human accelerated non-coding sequences or HARs. We found that the topologically associating domain (TAD) determined using developing human cerebral cortex containing the FOXP2 locus includes two clusters of 12 HARs, placing the locus occupied by FOXP2 among the top regions showing fast acceleration rates in non-coding regions in the human genome. Using in vivo enhancer assays in zebrafish, we found that at least five FOXP2-HARs behave as transcriptional enhancers throughout different developmental stages. In addition, we found that at least two FOXP2-HARs direct the expression of the reporter gene EGFP to foxP2 expressing regions and cells. Moreover, we uncovered two FOXP2-HARs showing reporter expression gain of function in the nervous system when compared with the chimpanzee ortholog sequences. Our results indicate that regulatory sequences in the FOXP2 locus underwent a human-specific evolutionary process suggesting that the transcriptional machinery controlling this gene could have also evolved differentially in the human lineage.

Biophysics and population size constrains speciation in an evolutionary model of developmental system drift

Developmental system drift is a likely mechanism for the origin of hybrid incompatibilities between closely related species. We examine here the detailed mechanistic basis of hybrid incompatibilities between two allopatric lineages, for a genotype-phenotype map of developmental system drift under stabilising selection, where an organismal phenotype is conserved, but the underlying molecular phenotypes and genotype can drift. This leads to number of emergent phenomenon not obtainable by modelling genotype or phenotype alone. Our results show that: 1) speciation is more rapid at smaller population sizes with a characteristic, Orr-like, power law, but at large population sizes slow, characterised by a sub-diffusive growth law; 2) the molecular phenotypes under weakest selection contribute to the earliest incompatibilities; and 3) pair-wise incompatibilities dominate over higher order, contrary to previous predictions that the latter should dominate. The population size effect we find is consistent with previous results on allopatric divergence of transcription factor-DNA binding, where smaller populations have common ancestors with a larger drift load because genetic drift favours phenotypes which have a larger number of genotypes (higher sequence entropy) over more fit phenotypes which have far fewer genotypes; this means less substitutions are required in either lineage before incompatibilities arise. Overall, our results indicate that biophysics and population size provide a much stronger constraint to speciation than suggested by previous models, and point to a general mechanistic principle of how incompatibilities arise the under stabilising selection for an organismal phenotype.

The process of speciation is of fundamental importance to the field of evolution as it is intimately connected to understanding the immense bio-diversity of life. There is still relatively little understanding of the underlying genetic mechanisms that give rise to hybrid incompatibilities with results suggesting that divergence in transcription factor DNA binding and gene expression play an important role. A key finding from the field of evo-devo is that organismal phenotypes show developmental system drift, where species maintain the same phenotype, but diverge in developmental pathways; this is an important potential source of hybrid incompatibilities. Here, we explore a theoretical framework to understand how incompatibilities arise due to developmental system drift, using a tractable biophysically inspired genotype-phenotype for spatial gene expression. Modelling the evolution of phenotypes in this way has the key advantage that it mirrors how selection works in nature, i.e. that selection acts on phenotypes, but variation (mutation) arise at the level of genotypes. This results, as we demonstrate, in a number of non-trivial and testable predictions concerning speciation due to developmental system drift, which would not be obtainable by modelling evolution of genotypes or phenotypes alone.

Stable enhancers are active in development, and fragile enhancers are associated with evolutionary adaptation

Background

Despite continual progress in the identification and characterization of trait- and disease-associated variants that disrupt transcription factor (TF)-DNA binding, little is known about the distribution of TF binding deactivating mutations (deMs) in enhancer sequences. Here, we focus on elucidating the mechanism underlying the different densities of deMs in human enhancers.

Results

We identify two classes of enhancers based on the density of nucleotides prone to deMs. Firstly, fragile enhancers with abundant deM nucleotides are associated with the immune system and regular cellular maintenance. Secondly, stable enhancers with only a few deM nucleotides are associated with the development and regulation of TFs and are evolutionarily conserved. These two classes of enhancers feature different regulatory programs: the binding sites of pioneer TFs of FOX family are specifically enriched in stable enhancers, while tissue-specific TFs are enriched in fragile enhancers. Moreover, stable enhancers are more tolerant of deMs due to their dominant employment of homotypic TF binding site (TFBS) clusters, as opposed to the larger-extent usage of heterotypic TFBS clusters in fragile enhancers. Notably, the sequence environment and chromatin context of the cognate motif, other than the motif itself, contribute more to the susceptibility to deMs of TF binding.

Conclusions

This dichotomy of enhancer activity is conserved across different tissues, has a specific footprint in epigenetic profiles, and argues for a bimodal evolution of gene regulatory programs in vertebrates. Specifically encoded stable enhancers are evolutionarily conserved and associated with development, while differently encoded fragile enhancers are associated with the adaptation of species.

Electronic supplementary material

The online version of this article (10.1186/s13059-019-1750-z) contains supplementary material, which is available to authorized users.

Optimized PCR conditions minimizing the formation of chimeric DNA molecules from MPRA plasmid libraries

Background

Massively parallel reporter assays (MPRAs) enable high-throughput functional evaluation of various DNA regulatory elements and their mutant variants. The assays are based on construction of highly diverse plasmid libraries containing two variable fragments, a region of interest (a sequence under study; ROI) and a barcode (BC) used to uniquely tag each ROI, which are separated by a constant spacer sequence. The sequences of BC–ROI combinations present in the libraries may be either known a priori or not. In the latter case, it is necessary to identify these combinations before performing functional experiments. Typically, this is done by PCR amplification of the BC–ROI regions with flanking primers, followed by next-generation sequencing (NGS) of the products. However, chimeric DNA molecules formed on templates with identical spacer fragment during the amplification process may substantially hamper the identification of genuine BC–ROI combinations, and as a result lower the performance of the assays.

Results

To identify settings that minimize formation of chimeric products we tested a number of PCR amplification parameters, such as conventional and emulsion types of PCR, one- or two-round amplification strategies, amount of DNA template, number of PCR cycles, and the duration of the extension step. Using specific MPRA libraries as templates, we found that the two-round amplification of the BC–ROI regions with a very low initial template amount, an elongated extension step, and a specific number of PCR cycles result in as low as 0.30 and 0.32% of chimeric products for emulsion and conventional PCR approaches, respectively.

Conclusions

We have identified PCR parameters that ensure synthesis of specific (non-chimeric) products from highly diverse MPRA plasmid libraries. In addition, we found that there is a negligible difference in performance of emulsion and conventional PCR approaches performed with the identified settings.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5847-2) contains supplementary material, which is available to authorized users.

A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS)

Cell state-specific promoters constitute essential tools for basic research and biotechnology because they activate gene expression only under certain biological conditions. Synthetic Promoters with Enhanced Cell-State Specificity (SPECS) can be superior to native ones, but the design of such promoters is challenging and frequently requires gene regulation or transcriptome knowledge that is not readily available. Here, to overcome this challenge, we use a next-generation sequencing approach combined with machine learning to screen a synthetic promoter library with 6107 designs for high-performance SPECS for potentially any cell state. We demonstrate the identification of multiple SPECS that exhibit distinct spatiotemporal activity during the programmed differentiation of induced pluripotent stem cells (iPSCs), as well as SPECS for breast cancer and glioblastoma stem-like cells. We anticipate that this approach could be used to create SPECS for gene therapies that are activated in specific cell states, as well as to study natural transcriptional regulatory networks.

Massively Parallel Assays and Quantitative Sequence-Function Relationships

Over the last decade, a rich variety of massively parallel assays have revolutionized our understanding of how biological sequences encode quantitative molecular phenotypes. These assays include deep mutational scanning, high-throughput SELEX, and massively parallel reporter assays. Here, we review these experimental methods and how the data they produce can be used to quantitatively model sequence-function relationships. In doing so, we touch on a diverse range of topics, including the identification of clinically relevant genomic variants, the modeling of transcription factor binding to DNA, the functional and evolutionary landscapes of proteins, and cis-regulatory mechanisms in both transcription and mRNA splicing. We further describe a unified conceptual framework and a core set of mathematical modeling strategies that studies in these diverse areas can make use of. Finally, we highlight key aspects of experimental design and mathematical modeling that are important for the results of such studies to be interpretable and reproducible.

100 Years of evolving gene-disease complexities and scientific debutants

It's been over 100 years since the word `gene' is around and progressively evolving in several scientific directions. Time-to-time technological advancements have heavily revolutionized the field of genomics, especially when it's about, e.g. triple code development, gene number proposition, genetic mapping, data banks, gene-disease maps, catalogs of human genes and genetic disorders, CRISPR/Cas9, big data and next generation sequencing, etc. In this manuscript, we present the progress of genomics from pea plant genetics to the human genome project and highlight the molecular, technical and computational developments. Studying genome and epigenome led to the fundamentals of development and progression of human diseases, which includes chromosomal, monogenic, multifactorial and mitochondrial diseases. World Health Organization has classified, standardized and maintained all human diseases, when many academic and commercial online systems are sharing information about genes and linking to associated diseases. To efficiently fathom the wealth of this biological data, there is a crucial need to generate appropriate gene annotation repositories and resources. Our focus has been how many gene-disease databases are available worldwide and which sources are authentic, timely updated and recommended for research and clinical purposes. In this manuscript, we have discussed and compared 43 such databases and bioinformatics applications, which enable users to connect, explore and, if possible, download gene-disease data.

Differential transcriptional regulation by alternatively designed mechanisms: A mathematical modeling approach

Cells maintain cellular homeostasis employing different regulatory mechanisms to respond external stimuli. We study two groups of signal-dependent transcriptional regulatory mechanisms. In the first group, we assume that repressor and activator proteins compete for binding to the same regulatory site on DNA (competitive mechanisms). In the second group, they can bind to different regulatory regions in a noncompetitive fashion (noncompetitive mechanisms). For both competitive and noncompetitive mechanisms, we studied the gene expression dynamics by increasing the repressor or decreasing the activator abundance (inhibition mechanisms), or by decreasing the repressor or increasing the activator abundance (activation mechanisms). We employed delay differential equation models. Our simulation results show that the competitive and noncompetitive inhibition mechanisms exhibit comparable repression effectiveness. However, response time is fastest in the noncompetitive inhibition mechanism due to increased repressor abundance, and slowest in the competitive inhibition mechanism by increased repressor level. The competitive and noncompetitive inhibition mechanisms through decreased activator abundance show comparable and moderate response times, while the competitive and noncompetitive activation mechanisms by increased activator protein level display more effective and faster response. Our study exemplifies the importance of mathematical modeling and computer simulation in the analysis of gene expression dynamics.

Inference of Transcription Factor Regulation Patterns Using Gene Expression Covariation in Natural Populations of Drosophila melanogaster

Gene regulatory networks control the complex programs that drive development. Deciphering the connections between transcription factors (TFs) and target genes is challenging, in part because TFs bind to thousands of places in the genome but control expression through a subset of these binding events. We hypothesize that we can combine natural variation of expression levels and predictions of TF binding sites to identify TF targets. We gather RNA-seq data from 71 genetically distinct F1 Drosophila melanogaster embryos and calculate the correlations between TF and potential target genes' expression levels, which we call "regulatory strength." To separate direct and indirect TF targets, we hypothesize that direct TF targets will have a preponderance of binding sites in their upstream regions. Using 14 TFs active during embryogenesis, we find that 12 TFs showed a significant correlation between their binding strength and regulatory strength on downstream targets, and 10 TFs showed a significant correlation between the number of binding sites and the regulatory effect on target genes. The general roles, e.g. bicoid's role as an activator, and the particular interactions we observed between our TFs, e.g. twist's role as a repressor of sloppy paired and odd paired, generally coincide with the literature.

Measuring cis-regulatory energetics in living cells using allelic manifolds

Gene expression in all organisms is controlled by cooperative interactions between DNA-bound transcription factors (TFs), but quantitatively measuring TF-DNA and TF-TF interactions remains difficult. Here we introduce a strategy for precisely measuring the Gibbs free energy of such interactions in living cells. This strategy centers on the measurement and modeling of ‘allelic manifolds’, a multidimensional generalization of the classical genetics concept of allelic series. Allelic manifolds are measured using reporter assays performed on strategically designed cis-regulatory sequences. Quantitative biophysical models are then fit to the resulting data. We used this strategy to study regulation by two Escherichia coli TFs, CRP and σ70 RNA polymerase. Doing so, we consistently obtained energetic measurements precise to ∼0.1 kcal/mol. We also obtained multiple results that deviate from the prior literature. Our strategy is compatible with massively parallel reporter assays in both prokaryotes and eukaryotes, and should therefore be highly scalable and broadly applicable.

Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that minor issues remain unresolved (see decision letter).

Flexibility and structure of flanking DNA impact transcription factor affinity for its core motif

Spatial and temporal expression of genes is essential for maintaining phenotype integrity. Transcription factors (TFs) modulate expression patterns by binding to specific DNA sequences in the genome. Along with the core binding motif, the flanking sequence context can play a role in DNA-TF recognition. Here, we employ high-throughput in vitro and in silico analyses to understand the influence of sequences flanking the cognate sites in binding of three most prevalent eukaryotic TF families (zinc finger, homeodomain and bZIP). In vitro binding preferences of each TF toward the entire DNA sequence space were correlated with a wide range of DNA structural parameters, including DNA flexibility. Results demonstrate that conformational plasticity of flanking regions modulates binding affinity of certain TF families. DNA duplex stability and minor groove width also play an important role in DNA-TF recognition but differ in how exactly they influence the binding in each specific case. Our analyses further reveal that the structural features of preferred flanking sequences are not universal, as similar DNA-binding folds can employ distinct DNA recognition modes.

Differential analysis of chromatin accessibility and histone modifications for predicting mouse developmental enhancers

Enhancers are distal cis-regulatory elements that modulate gene expression. They are depleted of nucleosomes and enriched in specific histone modifications; thus, calling DNase-seq and histone mark ChIP-seq peaks can predict enhancers. We evaluated nine peak-calling algorithms for predicting enhancers validated by transgenic mouse assays. DNase and H3K27ac peaks were consistently more predictive than H3K4me1/2/3 and H3K9ac peaks. DFilter and Hotspot2 were the best DNase peak callers, while HOMER, MUSIC, MACS2, DFilter and F-seq were the best H3K27ac peak callers. We observed that the differential DNase or H3K27ac signals between two distant tissues increased the area under the precision-recall curve (PR-AUC) of DNase peaks by 17.5-166.7% and that of H3K27ac peaks by 7.1-22.2%. We further improved this differential signal method using multiple contrast tissues. Evaluated using a blind test, the differential H3K27ac signal method substantially improved PR-AUC from 0.48 to 0.75 for predicting heart enhancers. We further validated our approach using postnatal retina and cerebral cortex enhancers identified by massively parallel reporter assays, and observed improvements for both tissues. In summary, we compared nine peak callers and devised a superior method for predicting tissue-specific mouse developmental enhancers by reranking the called peaks.

A cancer tissue-specific FAM72 expression profile defines a novel glioblastoma multiform (GBM) gene-mutation signature

INTRODUCTION

Glioblastoma multiform (GBM) is a neural stem cell (NSC)-derived malignant brain tumor with complex genetic alterations challenging clinical treatments. FAM72 is a NSC-specific protein comprised of four paralogous genes (FAM72 A-D) in the human genome, but its functional tumorigenic significance is unclear.

METHODS

We conducted an in-depth expression and somatic mutation data analysis of FAM72 (A-D) in GBM using the comprehensive human clinical cancer study database cBioPortal [including The Cancer Genome Atlas (TCGA)].

RESULTS

We established a FAM72 transcription profile across TCGA correlated with the expression of the proliferative marker MKI67 and a tissue-specific gene-mutation signature represented by pivotal genes involved in driving the cell cycle. FAM72 paralogs are overexpressed in cancer cells, specifically correlating with the mitotic cell cycle genes ASPM, KIF14, KIF23, CENPE, CENPE, CEP55, SGO1, and BUB1, thereby contributing to centrosome and mitotic spindle formation. FAM72 expression correlation identifies a novel GBM-specific gene set (SCN9A, MXRA5, ADAM29, KDR, LRP1B, and PIK3C2G) in the de novo pathway of primary GBM predestined as viable targets for therapeutics.

CONCLUSION

Our newly identified primary GBM-specific gene-mutation signature, along with FAM72, could thus provide a new basis for prognostic biomarkers for diagnostics of GBM and could serve as potential therapeutic targets.

Global role for coactivator complexes in RNA polymerase II transcription

SAGA and TFIID are related transcription complexes, which were proposed to alternatively deliver TBP at different promoter classes. Recent genome-wide studies in yeast revealed that both complexes are required for the transcription of a vast majority of genes by RNA polymerase II raising new questions about the role of coactivators.

Mutational analysis of a Drosophila neuroblast enhancer governing nubbin expression during CNS development

While developmental studies of Drosophila neural stem cell lineages have identified transcription factors (TFs) important to cell identity decisions, currently only an incomplete understanding exists of the cis‐regulatory elements that control the dynamic expression of these TFs. Our previous studies have identified multiple enhancers that regulate the POU‐domain TF paralogs nubbin and pdm‐2 genes. Evolutionary comparative analysis of these enhancers reveals that they each contain multiple conserved sequence blocks (CSBs) that span TF DNA‐binding sites for known regulators of neuroblast (NB) gene expression in addition to novel sequences. This study functionally analyzes the conserved DNA sequence elements within a NB enhancer located within the nubbin gene and highlights a high level of complexity underlying enhancer structure. Mutational analysis has revealed CSBs that are important for enhancer activation and silencing in the developing CNS. We have also observed that adjusting the number and relative positions of the TF binding sites within these CSBs alters enhancer function.

Toward a Universal Structural and Energetic Model for Prokaryotic Promoters

With almost no consensus promoter sequence in prokaryotes, recruitment of RNA polymerase (RNAP) to precise transcriptional start sites (TSSs) has remained an unsolved puzzle. Uncovering the underlying mechanism is critical for understanding the principle of gene regulation. We attempted to search the hidden code in ∼16,500 promoters of 12 prokaryotes representing two kingdoms in their structure and energetics. Twenty-eight fundamental parameters of DNA structure including backbone angles, basepair axis, and interbasepair and intrabasepair parameters were used, and information was extracted from x-ray crystallography data. Three parameters (solvation energy, hydrogen-bond energy, and stacking energy) were selected for creating energetics profiles using in-house programs. DNA of promoter regions was found to be inherently designed to undergo a change in every parameter undertaken for the study, in all prokaryotes. The change starts from some distance upstream of TSSs and continues past some distance from TSS, hence giving a signature state to promoter regions. These signature states might be the universal hidden codes recognized by RNAP. This observation was reiterated when randomly selected promoter sequences (with little sequence conservation) were subjected to structure generation; all developed into very similar three-dimensional structures quite distinct from those of conventional B-DNA and coding sequences. Fine structural details at important motifs (viz. -11, -35, and -75 positions relative to TSS) of promoters reveal novel to our knowledge and pointed insights for RNAP interaction at these locations; it could be correlated with how some particular structural changes at the -11 region may allow insertion of RNAP amino acids in interbasepair space as well as facilitate the flipping out of bases from the DNA duplex.

High-throughput identification of noncoding functional SNPs via type IIS enzyme restriction

Genome-wide association studies (GWAS) have identified many disease-associated noncoding variants, but cannot distinguish functional single-nucleotide polymorphisms (fSNPs) from others that reside incidentally within risk loci. To address this challenge, we developed an unbiased high-throughput screen that employs type IIS enzymatic restriction to identify fSNPs that allelically modulate the binding of regulatory proteins. We coupled this approach, termed SNP-seq, with flanking restriction enhanced pulldown (FREP) to identify regulation of CD40 by three disease-associated fSNPs via four regulatory proteins, RBPJ, RSRC2 and FUBP-1/TRAP150. Applying this approach across 27 loci associated with juvenile idiopathic arthritis, we identified 148 candidate fSNPs, including two that regulate STAT4 via the regulatory proteins SATB2 and H1.2. Together, these findings establish the utility of tandem SNP-seq/FREP to bridge the gap between GWAS and disease mechanism.

A novel method for improved accuracy of transcription factor binding site prediction

Identifying transcription factor (TF) binding sites (TFBSs) is important in the computational inference of gene regulation. Widely used computational methods of TFBS prediction based on position weight matrices (PWMs) usually have high false positive rates. Moreover, computational studies of transcription regulation in eukaryotes frequently require numerous PWM models of TFBSs due to a large number of TFs involved. To overcome these problems we developed DRAF, a novel method for TFBS prediction that requires only 14 prediction models for 232 human TFs, while at the same time significantly improves prediction accuracy. DRAF models use more features than PWM models, as they combine information from TFBS sequences and physicochemical properties of TF DNA-binding domains into machine learning models. Evaluation of DRAF on 98 human ChIP-seq datasets shows on average 1.54-, 1.96- and 5.19-fold reduction of false positives at the same sensitivities compared to models from HOCOMOCO, TRANSFAC and DeepBind, respectively. This observation suggests that one can efficiently replace the PWM models for TFBS prediction by a small number of DRAF models that significantly improve prediction accuracy. The DRAF method is implemented in a web tool and in a stand-alone software freely available at http://cbrc.kaust.edu.sa/DRAF.

DeFine: deep convolutional neural networks accurately quantify intensities of transcription factor-DNA binding and facilitate evaluation of functional non-coding variants

The complex system of gene expression is regulated by the cell type-specific binding of transcription factors (TFs) to regulatory elements. Identifying variants that disrupt TF binding and lead to human diseases remains a great challenge. To address this, we implement sequence-based deep learning models that accurately predict the TF binding intensities to given DNA sequences. In addition to accurately classifying TF-DNA binding or unbinding, our models are capable of accurately predicting real-valued TF binding intensities by leveraging large-scale TF ChIP-seq data. The changes in the TF binding intensities between the altered sequence and the reference sequence reflect the degree of functional impact for the variant. This enables us to develop the tool DeFine (Deep learning based Functional impact of non-coding variants evaluator, http://define.cbi.pku.edu.cn) with improved performance for assessing the functional impact of non-coding variants including SNPs and indels. DeFine accurately identifies the causal functional non-coding variants from disease-associated variants in GWAS. DeFine is an effective and easy-to-use tool that facilities systematic prioritization of functional non-coding variants.

A novel k-mer set memory (KSM) motif representation improves regulatory variant prediction

The representation and discovery of transcription factor (TF) sequence binding specificities is critical for understanding gene regulatory networks and interpreting the impact of disease-associated noncoding genetic variants. We present a novel TF binding motif representation, the k-mer set memory (KSM), which consists of a set of aligned k-mers that are overrepresented at TF binding sites, and a new method called KMAC for de novo discovery of KSMs. We find that KSMs more accurately predict in vivo binding sites than position weight matrix (PWM) models and other more complex motif models across a large set of ChIP-seq experiments. Furthermore, KSMs outperform PWMs and more complex motif models in predicting in vitro binding sites. KMAC also identifies correct motifs in more experiments than five state-of-the-art motif discovery methods. In addition, KSM-derived features outperform both PWM and deep learning model derived sequence features in predicting differential regulatory activities of expression quantitative trait loci (eQTL) alleles. Finally, we have applied KMAC to 1600 ENCODE TF ChIP-seq data sets and created a public resource of KSM and PWM motifs. We expect that the KSM representation and KMAC method will be valuable in characterizing TF binding specificities and in interpreting the effects of noncoding genetic variations.

Timing of gene expression in a cell-fate decision system

During development, morphogens provide extracellular cues allowing cells to select a specific fate by inducing complex transcriptional programs. The mating pathway in budding yeast offers simplified settings to understand this process. Pheromone secreted by the mating partner triggers the activity of a MAPK pathway, which results in the expression of hundreds of genes. Using a dynamic expression reporter, we quantified the kinetics of gene expression in single cells upon exogenous pheromone stimulation and in the physiological context of mating. In both conditions, we observed striking differences in the timing of induction of mating‐responsive promoters. Biochemical analyses and generation of synthetic promoter variants demonstrated how the interplay between transcription factor binding and nucleosomes contributes to determine the kinetics of transcription in a simplified cell‐fate decision system.

Chromatin Accessibility-Based Characterization of the Gene Regulatory Network Underlying Plasmodium falciparum Blood-Stage Development

Underlying the development of malaria parasites within erythrocytes and the resulting pathogenicity is a hardwired program that secures proper timing of gene transcription and production of functionally relevant proteins. How stage-specific gene expression is orchestrated in vivo remains unclear. Here, using the assay for transposase accessible chromatin sequencing (ATAC-seq), we identified ∼4,000 regulatory regions in P. falciparum intraerythrocytic stages. The vast majority of these sites are located within 2 kb upstream of transcribed genes and their chromatin accessibility pattern correlates positively with abundance of the respective mRNA transcript. Importantly, these regions are sufficient to drive stage-specific reporter gene expression and DNA motifs enriched in stage-specific sets of regulatory regions interact with members of the P. falciparum AP2 transcription factor family. Collectively, this study provides initial insights into the in vivo gene regulatory network of P. falciparum intraerythrocytic stages and should serve as a valuable resource for future studies.

Relationship between histone modifications and transcription factor binding is protein family specific

The very small fraction of putative binding sites (BSs) that are occupied by transcription factors (TFs) in vivo can be highly variable across different cell types. This observation has been partly attributed to changes in chromatin accessibility and histone modification (HM) patterns surrounding BSs. Previous studies focusing on BSs within DNA regulatory regions found correlations between HM patterns and TF binding specificities. However, a mechanistic understanding of TF-DNA binding specificity determinants is still not available. The ability to predict in vivo TF binding on a genome-wide scale requires the identification of features that determine TF binding based on evolutionary relationships of DNA binding proteins. To reveal protein family-dependent mechanisms of TF binding, we conducted comprehensive comparisons of HM patterns surrounding BSs and non-BSs with exactly matched core motifs for TFs in three cell lines: 33 TFs in GM12878, 37 TFs in K562, and 18 TFs in H1-hESC. These TFs displayed protein family-specific preferences for HM patterns surrounding BSs, with high agreement among cell lines. Moreover, compared to models based on DNA sequence and shape at flanking regions of BSs, HM-augmented quantitative machine-learning methods resulted in increased performance in a TF family-specific manner. Analysis of the relative importance of features in these models indicated that TFs, displaying larger HM pattern differences between BSs and non-BSs, bound DNA in an HM-specific manner on a protein family-specific basis. We propose that TF family-specific HM preferences reveal distinct mechanisms that assist in guiding TFs to their cognate BSs by altering chromatin structure and accessibility.

Thrombopoietin signaling to chromatin elicits rapid and pervasive epigenome remodeling within poised chromatin architectures

Thrombopoietin (TPO) is a critical cytokine regulating hematopoietic stem cell maintenance and differentiation into the megakaryocytic lineage. However, the transcriptional and chromatin dynamics elicited by TPO signaling are poorly understood. Here, we study the immediate early transcriptional and cis-regulatory responses to TPO in hematopoietic stem/progenitor cells (HSPCs) and use this paradigm of cytokine signaling to chromatin to dissect the relationship between cis-regulatory activity and chromatin architecture. We show that TPO profoundly alters the transcriptome of HSPCs, with key hematopoietic regulators being transcriptionally repressed within 30 min of TPO. By examining cis-regulatory dynamics and chromatin architectures, we demonstrate that these changes are accompanied by rapid and extensive epigenome remodeling of cis-regulatory landscapes that is spatially coordinated within topologically associating domains (TADs). Moreover, TPO-responsive enhancers are spatially clustered and engage in preferential homotypic intra- and inter-TAD interactions that are largely refractory to TPO signaling. By further examining the link between cis-regulatory dynamics and chromatin looping, we show that rapid modulation of cis-regulatory activity is largely independent of chromatin looping dynamics. Finally, we show that, although activated and repressed cis-regulatory elements share remarkably similar DNA sequence compositions, transcription factor binding patterns accurately predict rapid cis-regulatory responses to TPO.

Systems analysis of dilated cardiomyopathy in the next generation sequencing era

Dilated cardiomyopathy (DCM) is a form of severe failure of cardiac muscle caused by a long list of etiologies ranging from myocardial infarction, DNA mutations in cardiac genes, to toxics. Systems analysis integrating next-generation sequencing (NGS)-based omics approaches, such as the sequencing of DNA, RNA, and chromatin, provide valuable insights into DCM mechanisms. The outcome and interpretation of NGS methods can be affected by the localization of cardiac biopsy, level of tissue degradation, and variable ratios of different cell populations, especially in the presence of fibrosis. Heart tissue composition may even differ between sexes, or siblings carrying the same disease causing mutation. Therefore, before planning any experiments, it is important to fully appreciate the complexities of DCM, and the selection of samples suitable for given research question should be an interdisciplinary effort involving clinicians and biologists. The list of NGS omics datasets in DCM to date is short. More studies have to be performed to contribute to public data repositories and facilitate systems analysis. In addition, proper data integration is a difficult task requiring complex computational approaches. Despite these complications, there are multiple promising implications of systems analysis in DCM. By combining various types of datasets, for example, RNA-seq, ChIP-seq, or 4C, deep insights into cardiac biology, and possible biomarkers and treatment targets, can be gained. Systems analysis can also facilitate the annotation of noncoding mutations in cardiac-specific DNA regulatory regions that play a substantial role in maintaining the tissue- and cell-specific transcriptional programs in the heart. This article is categorized under: Physiology > Mammalian Physiology in Health and Disease Laboratory Methods and Technologies > Genetic/Genomic Methods Laboratory Methods and Technologies > RNA Methods.

Expanding the repertoire of DNA shape features for genome-scale studies of transcription factor binding

Uncovering the mechanisms that affect the binding specificity of transcription factors (TFs) is critical for understanding the principles of gene regulation. Although sequence-based models have been used successfully to predict TF binding specificities, we found that including DNA shape information in these models improved their accuracy and interpretability. Previously, we developed a method for modeling DNA binding specificities based on DNA shape features extracted from Monte Carlo (MC) simulations. Prediction accuracies of our models, however, have not yet been compared to accuracies of models incorporating DNA shape information extracted from X-ray crystallography (XRC) data or Molecular Dynamics (MD) simulations. Here, we integrated DNA shape information extracted from MC or MD simulations and XRC data into predictive models of TF binding and compared their performance. Models that incorporated structural information consistently showed improved performance over sequence-based models regardless of data source. Furthermore, we derived and validated nine additional DNA shape features beyond our original set of four features. The expanded repertoire of 13 distinct DNA shape features, including six intra-base pair and six inter-base pair parameters and minor groove width, is available in our R/Bioconductor package DNAshapeR and enables a comprehensive structural description of the double helix on a genome-wide scale.

Targeting and silencing of rhodopsin by ectopic expression of the transcription factor KLF15

The genome-wide activity of transcription factors (TFs) on multiple regulatory elements precludes their use as gene-specific regulators. Here we show that ectopic expression of a TF in a cell-specific context can be used to silence the expression of a specific gene as a therapeutic approach to regulate gene expression in human disease. We selected the TF Krüppel-like factor 15 (KLF15) based on its putative ability to recognize a specific DNA sequence motif present in the rhodopsin (RHO) promoter and its lack of expression in terminally differentiated rod photoreceptors (the RHO-expressing cells). Adeno-associated virus (AAV) vector-mediated ectopic expression of KLF15 in rod photoreceptors of pigs enables Rho silencing with limited genome-wide transcriptional perturbations. Suppression of a RHO mutant allele by KLF15 corrects the phenotype of a mouse model of retinitis pigmentosa with no observed toxicity. Cell-specific-context conditioning of TF activity may prove a novel mode for somatic gene-targeted manipulation.