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1.
Nat Methods ; 18(8): 965-974, 2021 08.
Artigo em Inglês | MEDLINE | ID: mdl-34341582

RESUMO

CRISPR-Cas9 technologies have dramatically increased the ease of targeting DNA sequences in the genomes of living systems. The fusion of chromatin-modifying domains to nuclease-deactivated Cas9 (dCas9) has enabled targeted epigenome editing in both cultured cells and animal models. However, delivering large dCas9 fusion proteins to target cells and tissues is an obstacle to the widespread adoption of these tools for in vivo studies. Here, we describe the generation and characterization of two conditional transgenic mouse lines for epigenome editing, Rosa26:LSL-dCas9-p300 for gene activation and Rosa26:LSL-dCas9-KRAB for gene repression. By targeting the guide RNAs to transcriptional start sites or distal enhancer elements, we demonstrate regulation of target genes and corresponding changes to epigenetic states and downstream phenotypes in the brain and liver in vivo, and in T cells and fibroblasts ex vivo. These mouse lines are convenient and valuable tools for facile, temporally controlled, and tissue-restricted epigenome editing and manipulation of gene expression in vivo.


Assuntos
Sistemas CRISPR-Cas , Epigênese Genética , Epigenoma , Edição de Genes/métodos , Regulação da Expressão Gênica , Animais , Encéfalo/metabolismo , Feminino , Fibroblastos/metabolismo , Humanos , Fígado/metabolismo , Masculino , Camundongos , Camundongos Transgênicos , Linfócitos T/metabolismo
2.
Am J Hum Genet ; 108(8): 1436-1449, 2021 08 05.
Artigo em Inglês | MEDLINE | ID: mdl-34216551

RESUMO

Despite widespread clinical genetic testing, many individuals with suspected genetic conditions lack a precise diagnosis, limiting their opportunity to take advantage of state-of-the-art treatments. In some cases, testing reveals difficult-to-evaluate structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted. We performed targeted long-read sequencing (T-LRS) using adaptive sampling on the Oxford Nanopore platform on 40 individuals, 10 of whom lacked a complete molecular diagnosis. We computationally targeted up to 151 Mbp of sequence per individual and searched for pathogenic substitutions, structural variants, and methylation differences using a single data source. We detected all genomic aberrations-including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences-identified by prior clinical testing. In 8/8 individuals with complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, leading to changes in clinical management in one case. In ten individuals with suspected Mendelian conditions lacking a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in six and variants of uncertain significance in two others. T-LRS accurately identifies pathogenic structural variants, resolves complex rearrangements, and identifies Mendelian variants not detected by other technologies. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority genes and regions or complex clinical testing results.


Assuntos
Aberrações Cromossômicas , Análise Citogenética/métodos , Doenças Genéticas Inatas/diagnóstico , Doenças Genéticas Inatas/genética , Predisposição Genética para Doença , Genoma Humano , Mutação , Variações do Número de Cópias de DNA , Feminino , Testes Genéticos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Cariotipagem , Masculino , Análise de Sequência de DNA
3.
J Cyst Fibros ; 2021 May 25.
Artigo em Inglês | MEDLINE | ID: mdl-34049825

RESUMO

BACKGROUND: Mechanisms governing the diversity of CFTR gene expression throughout the body are complex. Multiple intronic and distal regulatory elements are responsible for regulating differential CFTR expression across tissues. METHODS: Drawing on published data, 18 high-priority genomic regions were identified and interrogated for CFTR-enhancer function using CRISPR/dCas9-based epigenome editing tools. Each region was evaluated by dCas9p300 and dCas9KRAB for its ability to enhance or repress CFTR expression, respectively. RESULTS: Multiple genomic regions were tested for enhancer activity using CRISPR/dCas9 epigenome editing. dCas9p300 mediates a significant increase in CFTR mRNA levels when targeted to the promoter and a region 44 kb upstream of the transcriptional start site in a CFTR-low expressing cell line. Multiple gRNAs targeting the promoter induced a robust increase in CFTR protein levels. In contrast, dCas9KRAB-mediated repression is much more robust with 10 of the 18 evaluated genomic regions inducing CFTR protein knockdown. To evaluate the therapeutic efficacy of modulating CFTR gene regulation, dCas9p300 was used to induce elevated levels of CFTR from the endogenous locus in ΔF508/ΔF508 human bronchial epithelial cells. Ussing chamber studies demonstrated a synergistic increase in ion transport in response to CRISPR-induced expression of ΔF508 CFTR mRNA along with VX809 treatment. CONCLUSIONS: CRISPR/dCas9-based epigenome-editing provides a previously unexplored tool for interrogating CFTR enhancer function. Here, we demonstrate that therapeutic interventions that increase the expression of CFTR may improve the efficacy of CFTR modulators. A better understanding CFTR regulatory mechanisms could uncover novel therapeutic interventions for the development of cystic fibrosis therapies.

4.
Genome Res ; 31(4): 538-550, 2021 04.
Artigo em Inglês | MEDLINE | ID: mdl-33674350

RESUMO

The AP-1 transcription factor (TF) dimer contributes to many biological processes and environmental responses. AP-1 can be composed of many interchangeable subunits. Unambiguously determining the binding locations of these subunits in the human genome is challenging because of variable antibody specificity and affinity. Here, we definitively establish the genome-wide binding patterns of five AP-1 subunits by using CRISPR to introduce a common antibody tag on each subunit. We find limited evidence for strong dimerization preferences between subunits at steady state and find that, under a stimulus, dimerization patterns reflect changes in the transcriptome. Further, our analysis suggests that canonical AP-1 motifs indiscriminately recruit all AP-1 subunits to genomic sites, which we term AP-1 hotspots. We find that AP-1 hotspots are predictive of cell type-specific gene expression and of genomic responses to glucocorticoid signaling (more so than super-enhancers) and are significantly enriched in disease-associated genetic variants. Together, these results support a model where promiscuous binding of many AP-1 subunits to the same genomic location play a key role in regulating cell type-specific gene expression and environmental responses.

5.
Genome Res ; 31(5): 877-889, 2021 May.
Artigo em Inglês | MEDLINE | ID: mdl-33722938

RESUMO

High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal.

6.
PLoS Comput Biol ; 17(1): e1008223, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33513136

RESUMO

Gene regulatory network inference is essential to uncover complex relationships among gene pathways and inform downstream experiments, ultimately enabling regulatory network re-engineering. Network inference from transcriptional time-series data requires accurate, interpretable, and efficient determination of causal relationships among thousands of genes. Here, we develop Bootstrap Elastic net regression from Time Series (BETS), a statistical framework based on Granger causality for the recovery of a directed gene network from transcriptional time-series data. BETS uses elastic net regression and stability selection from bootstrapped samples to infer causal relationships among genes. BETS is highly parallelized, enabling efficient analysis of large transcriptional data sets. We show competitive accuracy on a community benchmark, the DREAM4 100-gene network inference challenge, where BETS is one of the fastest among methods of similar performance and additionally infers whether causal effects are activating or inhibitory. We apply BETS to transcriptional time-series data of differentially-expressed genes from A549 cells exposed to glucocorticoids over a period of 12 hours. We identify a network of 2768 genes and 31,945 directed edges (FDR ≤ 0.2). We validate inferred causal network edges using two external data sources: Overexpression experiments on the same glucocorticoid system, and genetic variants associated with inferred edges in primary lung tissue in the Genotype-Tissue Expression (GTEx) v6 project. BETS is available as an open source software package at https://github.com/lujonathanh/BETS.


Assuntos
Glucocorticoides/farmacologia , Modelos Estatísticos , Transcriptoma/efeitos dos fármacos , Células A549 , Algoritmos , Biologia Computacional , Humanos , Pulmão/química , Pulmão/metabolismo , Aprendizado de Máquina , Software , Transcriptoma/genética
7.
Cell Rep ; 33(9): 108460, 2020 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-33264623

RESUMO

Technologies to reprogram cell-type specification have revolutionized the fields of regenerative medicine and disease modeling. Currently, the selection of fate-determining factors for cell reprogramming applications is typically a laborious and low-throughput process. Therefore, we use high-throughput pooled CRISPR activation (CRISPRa) screens to systematically map human neuronal cell fate regulators. We utilize deactivated Cas9 (dCas9)-based gene activation to target 1,496 putative transcription factors (TFs) in the human genome. Using a reporter of neuronal commitment, we profile the neurogenic activity of these factors in human pluripotent stem cells (PSCs), leading to a curated set of pro-neuronal factors. Activation of pairs of TFs reveals neuronal cofactors, including E2F7, RUNX3, and LHX8, that improve conversion efficiency, subtype specificity, and maturation of neuronal cell types. Finally, using multiplexed gene regulation with orthogonal CRISPR systems, we demonstrate improved neuronal differentiation with concurrent activation and repression of target genes, underscoring the power of CRISPR-based gene regulation for programming complex cellular phenotypes.

8.
Sci Adv ; 6(49)2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33268355

RESUMO

While a genetic component of preterm birth (PTB) has long been recognized and recently mapped by genome-wide association studies (GWASs), the molecular determinants underlying PTB remain elusive. This stems in part from an incomplete availability of functional genomic annotations in human cell types relevant to pregnancy and PTB. We generated transcriptome (RNA-seq), epigenome (ChIP-seq of H3K27ac, H3K4me1, and H3K4me3 histone modifications), open chromatin (ATAC-seq), and chromatin interaction (promoter capture Hi-C) annotations of cultured primary decidua-derived mesenchymal stromal/stem cells and in vitro differentiated decidual stromal cells and developed a computational framework to integrate these functional annotations with results from a GWAS of gestational duration in 56,384 women. Using these resources, we uncovered additional loci associated with gestational duration and target genes of associated loci. Our strategy illustrates how functional annotations in pregnancy-relevant cell types aid in the experimental follow-up of GWAS for PTB and, likely, other pregnancy-related conditions.

9.
Front Physiol ; 11: 687, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32655414

RESUMO

Premature preterm rupture of membranes (PPROM), rupture of fetal membranes before 37 weeks of gestation, is the leading identifiable cause of spontaneous preterm births. Often there is no obvious cause that is identified in a patient who presents with PPROM. Identifying the upstream molecular events that lead to fetal membrane weakening presents potentially actionable mechanisms which could lead to the identification of at-risk patients and to the development of new therapeutic interventions. Functional genomic studies have transformed understanding of the role of gene regulation in diverse cells and tissues involved health and disease. Here, we review the results of those studies in the context of fetal membranes. We will highlight relevant results from major coordinated functional genomics efforts and from targeted studies focused on individual cell or tissue models. Studies comparing gene expression and DNA methylation between healthy and pathological fetal membranes have found differential regulation between labor and quiescent tissue as well as in preterm births, preeclampsia, and recurrent pregnancy loss. Whole genome and exome sequencing studies have identified common and rare fetal variants associated with preterm births. However, few fetal membrane tissue studies have modeled the response to stimuli relevant to pregnancy. Fetal membranes are readily adaptable to cell culture and relevant cellular phenotypes are readily observable. For these reasons, this is now an unrealized opportunity for genomic studies isolating the effect of cell signaling cascades and mapping the fetal membrane responses that lead to PPROM and other pregnancy complications.

10.
J Exp Med ; 217(1)2020 01 06.
Artigo em Inglês | MEDLINE | ID: mdl-31570496

RESUMO

CCR6- group 3 innate lymphoid cells (ILC3s) are mediators of intestinal immunity and barrier function that possess the capacity to acquire type 1 effector features and fully convert into ILC1s. The molecular mechanisms governing such plasticity are undefined. Here, we identified c-Maf as an essential regulator of ILC3 homeostasis and plasticity that limits physiological ILC1 conversion. Phenotypic analysis of effector status in Maf-deficient CCR6- ILC3s, coupled with evaluation of global changes in transcriptome, chromatin accessibility, and transcription factor motif enrichment, revealed that c-Maf enforces ILC3 identity. c-Maf promoted ILC3 accessibility and supported RORγt activity and expression of type 3 effector genes. Conversely, c-Maf antagonized type 1 programming, largely through restraint of T-bet expression and function. Mapping of the dynamic changes in chromatin landscape accompanying CCR6- ILC3 development and ILC1 conversion solidified c-Maf as a gatekeeper of type 1 regulatory transformation and a controller of ILC3 fate.


Assuntos
Imunidade Inata/imunologia , Linfócitos/imunologia , Proteínas Proto-Oncogênicas c-maf/imunologia , Animais , Linhagem da Célula/imunologia , Cromatina/imunologia , Regulação da Expressão Gênica/imunologia , Homeostase/imunologia , Camundongos , Camundongos Endogâmicos C57BL , Membro 3 do Grupo F da Subfamília 1 de Receptores Nucleares/imunologia , Fatores de Transcrição/imunologia , Transcriptoma/imunologia
11.
Bioinformatics ; 36(2): 331-338, 2020 01 15.
Artigo em Inglês | MEDLINE | ID: mdl-31368479

RESUMO

MOTIVATION: High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA. RESULTS: We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters. AVAILABILITY AND IMPLEMENTATION: The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.


Assuntos
Software , Alelos , Teorema de Bayes , Frequência do Gene , Humanos , Desequilíbrio de Ligação
12.
Nat Biotechnol ; 37(12): 1493-1501, 2019 12.
Artigo em Inglês | MEDLINE | ID: mdl-31548729

RESUMO

Class 2 CRISPR-Cas systems, such as Cas9 and Cas12, have been widely used to target DNA sequences in eukaryotic genomes. However, class 1 CRISPR-Cas systems, which represent about 90% of all CRISPR systems in nature, remain largely unexplored for genome engineering applications. Here, we show that class 1 CRISPR-Cas systems can be expressed in mammalian cells and used for DNA targeting and transcriptional control. We repurpose type I variants of class 1 CRISPR-Cas systems from Escherichia coli and Listeria monocytogenes, which target DNA via a multi-component RNA-guided complex termed Cascade. We validate Cascade expression, complex formation and nuclear localization in human cells, and demonstrate programmable CRISPR RNA (crRNA)-mediated targeting of specific loci in the human genome. By tethering activation and repression domains to Cascade, we modulate the expression of targeted endogenous genes in human cells. This study demonstrates the use of Cascade as a CRISPR-based technology for targeted eukaryotic gene regulation, highlighting class 1 CRISPR-Cas systems for further exploration.


Assuntos
Sistemas CRISPR-Cas/genética , Engenharia Genética/métodos , Transcrição Genética/genética , Escherichia coli/genética , Células HEK293 , Humanos , Listeria monocytogenes/genética , RNA Guia/genética
13.
Elife ; 72018 12 21.
Artigo em Inglês | MEDLINE | ID: mdl-30575519

RESUMO

Changes in DNA methylation are involved in development, disease, and the response to environmental conditions. However, not all regulatory elements are functionally methylation-dependent (MD). Here, we report a method, mSTARR-seq, that assesses the causal effects of DNA methylation on regulatory activity at hundreds of thousands of fragments (millions of CpG sites) simultaneously. Using mSTARR-seq, we identify thousands of MD regulatory elements in the human genome. MD activity is partially predictable using sequence and chromatin state information, and distinct transcription factors are associated with higher activity in unmethylated versus methylated DNA. Further, pioneer TFs linked to higher activity in the methylated state appear to drive demethylation of experimentally methylated sites. MD regulatory elements also predict methylation-gene expression relationships across individuals, where they are 1.6x enriched among sites with strong negative correlations. mSTARR-seq thus provides a map of MD regulatory activity in the human genome and facilitates interpretation of differential methylation studies.


Assuntos
Cromatina/metabolismo , Metilação de DNA , Epigênese Genética , Genoma Humano , Análise de Sequência de DNA/estatística & dados numéricos , Fatores de Transcrição/genética , Cromatina/química , Biologia Computacional/métodos , Ilhas de CpG , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Células K562 , Sequências Reguladoras de Ácido Nucleico , Análise de Sequência de DNA/métodos , Fatores de Transcrição/metabolismo
14.
Nat Commun ; 9(1): 5317, 2018 12 21.
Artigo em Inglês | MEDLINE | ID: mdl-30575722

RESUMO

Environmental stimuli commonly act via changes in gene regulation. Human-genome-scale assays to measure such responses are indirect or require knowledge of the transcription factors (TFs) involved. Here, we present the use of human genome-wide high-throughput reporter assays to measure environmentally-responsive regulatory element activity. We focus on responses to glucocorticoids (GCs), an important class of pharmaceuticals and a paradigmatic genomic response model. We assay GC-responsive regulatory activity across >108 unique DNA fragments, covering the human genome at >50×. Those assays directly detected thousands of GC-responsive regulatory elements genome-wide. We then validate those findings with measurements of transcription factor occupancy, histone modifications, chromatin accessibility, and gene expression. We also detect allele-specific environmental responses. Notably, the assays did not require knowledge of GC response mechanisms. Thus, this technology can be used to agnostically quantify genomic responses for which the underlying mechanism remains unknown.


Assuntos
Regulação da Expressão Gênica/efeitos dos fármacos , Genoma Humano , Glucocorticoides/farmacologia , Elementos Reguladores de Transcrição/efeitos dos fármacos , Interação Gene-Ambiente , Ensaios de Triagem em Larga Escala , Humanos
15.
Genome Res ; 28(9): 1272-1284, 2018 09.
Artigo em Inglês | MEDLINE | ID: mdl-30097539

RESUMO

Glucocorticoids are potent steroid hormones that regulate immunity and metabolism by activating the transcription factor (TF) activity of glucocorticoid receptor (GR). Previous models have proposed that DNA binding motifs and sites of chromatin accessibility predetermine GR binding and activity. However, there are vast excesses of both features relative to the number of GR binding sites. Thus, these features alone are unlikely to account for the specificity of GR binding and activity. To identify genomic and epigenetic contributions to GR binding specificity and the downstream changes resultant from GR binding, we performed hundreds of genome-wide measurements of TF binding, epigenetic state, and gene expression across a 12-h time course of glucocorticoid exposure. We found that glucocorticoid treatment induces GR to bind to nearly all pre-established enhancers within minutes. However, GR binds to only a small fraction of the set of accessible sites that lack enhancer marks. Once GR is bound to enhancers, a combination of enhancer motif composition and interactions between enhancers then determines the strength and persistence of GR binding, which consequently correlates with dramatic shifts in enhancer activation. Over the course of several hours, highly coordinated changes in TF binding and histone modification occupancy occur specifically within enhancers, and these changes correlate with changes in the expression of nearby genes. Following GR binding, changes in the binding of other TFs precede changes in chromatin accessibility, suggesting that other TFs are also sensitive to genomic features beyond that of accessibility.


Assuntos
Elementos Facilitadores Genéticos , Código das Histonas , Motivos de Nucleotídeos , Receptores de Glucocorticoides/metabolismo , Ativação Transcricional , Linhagem Celular Tumoral , Epigênese Genética , Humanos , Ligação Proteica , Fatores de Transcrição/metabolismo
16.
Nat Commun ; 9(1): 3121, 2018 08 07.
Artigo em Inglês | MEDLINE | ID: mdl-30087329

RESUMO

Schizophrenia genome-wide association studies have identified >150 regions of the genome associated with disease risk, yet there is little evidence that coding mutations contribute to this disorder. To explore the mechanism of non-coding regulatory elements in schizophrenia, we performed ATAC-seq on adult prefrontal cortex brain samples from 135 individuals with schizophrenia and 137 controls, and identified 118,152 ATAC-seq peaks. These accessible chromatin regions in the brain are highly enriched for schizophrenia SNP heritability. Accessible chromatin regions that overlap evolutionarily conserved regions exhibit an even higher heritability enrichment, indicating that sequence conservation can further refine functional risk variants. We identify few differences in chromatin accessibility between cases and controls, in contrast to thousands of age-related differential accessible chromatin regions. Altogether, we characterize chromatin accessibility in the human prefrontal cortex, the effect of schizophrenia and age on chromatin accessibility, and provide evidence that our dataset will allow for fine mapping of risk variants.


Assuntos
Cromatina/química , Estudo de Associação Genômica Ampla , Córtex Pré-Frontal/metabolismo , Locos de Características Quantitativas , Esquizofrenia/genética , Esquizofrenia/metabolismo , Idoso , Idoso de 80 Anos ou mais , Encéfalo/fisiopatologia , Feminino , Perfilação da Expressão Gênica , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , Risco , Análise de Sequência de DNA
17.
Cell Syst ; 7(2): 146-160.e7, 2018 08 22.
Artigo em Inglês | MEDLINE | ID: mdl-30031775

RESUMO

The glucocorticoid receptor (GR) is a hormone-inducible transcription factor involved in metabolic and anti-inflammatory gene expression responses. To investigate what controls interactions between GR binding sites and their target genes, we used in situ Hi-C to generate high-resolution, genome-wide maps of chromatin interactions before and after glucocorticoid treatment. We found that GR binding to the genome typically does not cause new chromatin interactions to target genes but instead acts through chromatin interactions that already exist prior to hormone treatment. Both glucocorticoid-induced and glucocorticoid-repressed genes increased interactions with distal GR binding sites. In addition, while glucocorticoid-induced genes increased interactions with transcriptionally active chromosome compartments, glucocorticoid-repressed genes increased interactions with transcriptionally silent compartments. Lastly, while the architectural DNA-binding proteins CTCF and RAD21 were bound to most chromatin interactions, we found that glucocorticoid-responsive chromatin interactions were depleted for CTCF binding but enriched for RAD21. Together, these findings offer new insights into the mechanisms underlying GC-mediated gene activation and repression.


Assuntos
Cromatina/metabolismo , Regulação da Expressão Gênica , Glucocorticoides/metabolismo , Receptores de Glucocorticoides/metabolismo , Sítios de Ligação , Fator de Ligação a CCCTC/metabolismo , Proteínas de Ciclo Celular , Linhagem Celular , Cromatina/genética , Proteínas de Ligação a DNA , Genoma Humano , Humanos , Proteínas Nucleares/metabolismo , Fosfoproteínas/metabolismo , Ligação Proteica
18.
Bioinformatics ; 34(21): 3616-3623, 2018 11 01.
Artigo em Inglês | MEDLINE | ID: mdl-29701825

RESUMO

Motivation: Genetic variation that disrupts gene function by altering gene splicing between individuals can substantially influence traits and disease. In those cases, accurately predicting the effects of genetic variation on splicing can be highly valuable for investigating the mechanisms underlying those traits and diseases. While methods have been developed to generate high quality computational predictions of gene structures in reference genomes, the same methods perform poorly when used to predict the potentially deleterious effects of genetic changes that alter gene splicing between individuals. Underlying that discrepancy in predictive ability are the common assumptions by reference gene finding algorithms that genes are conserved, well-formed and produce functional proteins. Results: We describe a probabilistic approach for predicting recent changes to gene structure that may or may not conserve function. The model is applicable to both coding and non-coding genes, and can be trained on existing gene annotations without requiring curated examples of aberrant splicing. We apply this model to the problem of predicting altered splicing patterns in the genomes of individual humans, and we demonstrate that performing gene-structure prediction without relying on conserved coding features is feasible. The model predicts an unexpected abundance of variants that create de novo splice sites, an observation supported by both simulations and empirical data from RNA-seq experiments. While these de novo splice variants are commonly misinterpreted by other tools as coding or non-coding variants of little or no effect, we find that in some cases they can have large effects on splicing activity and protein products and we propose that they may commonly act as cryptic factors in disease. Availability and implementation: The software is available from geneprediction.org/SGRF. Supplementary information: Supplementary information is available at Bioinformatics online.


Assuntos
Éxons , Splicing de RNA , Software , Humanos , Anotação de Sequência Molecular , Análise de Sequência de RNA
19.
Methods Mol Biol ; 1767: 447-480, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29524151

RESUMO

Genomic regulatory elements that control gene expression play an important role in many traits and diseases. Identifying the regulatory elements associated with each gene or phenotype and understanding the function of that element remain a significant challenge. To address this technological need, we developed CRISPR/Cas9-based epigenomic regulatory element screening (CERES) for improved high-throughput screening of regulatory element activity in the native genomic context. This protocol includes detailed instructions for design and cloning of gRNA libraries, construction of endogenous reporter cell lines via CRISPR/Cas9-mediated knock-in of fluorescent proteins, overall screen design, and recovery of the gRNA library for enrichment analysis. This protocol will be generally useful for implementing genome engineering technologies for high-throughput functional annotation of putative regulatory elements in their native chromosomal context.


Assuntos
Sistemas CRISPR-Cas , Epigênese Genética , Edição de Genes/métodos , RNA Guia/genética , Clonagem Molecular/métodos , Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Perfilação da Expressão Gênica/métodos , Técnicas de Introdução de Genes/métodos , Biblioteca Gênica , Células HEK293 , Ensaios de Triagem em Larga Escala/métodos , Humanos , Células K562 , Proteínas Luminescentes/genética , Sequências Reguladoras de Ácido Nucleico
20.
PLoS Comput Biol ; 14(1): e1005896, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29337990

RESUMO

Transcriptome-wide time series expression profiling is used to characterize the cellular response to environmental perturbations. The first step to analyzing transcriptional response data is often to cluster genes with similar responses. Here, we present a nonparametric model-based method, Dirichlet process Gaussian process mixture model (DPGP), which jointly models data clusters with a Dirichlet process and temporal dependencies with Gaussian processes. We demonstrate the accuracy of DPGP in comparison to state-of-the-art approaches using hundreds of simulated data sets. To further test our method, we apply DPGP to published microarray data from a microbial model organism exposed to stress and to novel RNA-seq data from a human cell line exposed to the glucocorticoid dexamethasone. We validate our clusters by examining local transcription factor binding and histone modifications. Our results demonstrate that jointly modeling cluster number and temporal dependencies can reveal shared regulatory mechanisms. DPGP software is freely available online at https://github.com/PrincetonUniversity/DP_GP_cluster.


Assuntos
Análise por Conglomerados , Regulação Neoplásica da Expressão Gênica , Neoplasias Pulmonares/genética , Células A549 , Algoritmos , Linhagem Celular Tumoral , Biologia Computacional , Simulação por Computador , Dexametasona/química , Perfilação da Expressão Gênica , Glucocorticoides/química , Histonas/química , Humanos , Ligação de Hidrogênio , Peróxido de Hidrogênio/química , Neoplasias Pulmonares/tratamento farmacológico , Modelos Biológicos , Distribuição Normal , Análise de Sequência com Séries de Oligonucleotídeos , Análise de Sequência de RNA , Fatores de Tempo , Fatores de Transcrição/química
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