STARR prêmio fundação (MQZ), NIH concessão ES017166 (MQZ), NSF concessão DMS0906593 (HX).

1. Preparando os arquivos de entrada para o BCP Análise <ol><li> Alinhe o curta lê produzido a partir de seqüenciamento corridas (Chip e bibliotecas de entrada) para o genoma de referência apropriado, usando o software de alinhamento preferencial curto de leitura. Os locais mapeados devem ser convertidos para as 6 colunas de dados do navegador extensíveis (TCAP) formato 13 (UCSC navegador genoma, <a href="http://genome.ucsc.edu/" target="_blank">http://genome.ucsc.edu/</a> ), uma linha guia delimitada por mapeada ler indicando o cromossomo mapeada, a posição inicial (baseado em 0), posição final (semi-aberto), leia pontuação, nome (opcional), e vertente. </li></ol> 2a. Difundir Leia Perfis: Chip pré-processamento Leia Densidades para Detecção de Enriquecido Ilhas em Dados Difusos <ol><li> Estenda o chip e locais de entrada mapeado para um comprimento de fragmentos pré-determinado, ou seja. o tamanho do fragmento alvo durante a digestão enzimática ou sonicação do ADN, normalmente cerca de 200 pb. Contagens de fragmentos são, em seguida, a agregaçãoted em caixas adjacentes. Por padrão, o tamanho da caixa é definido como o comprimento do fragmento estimado de 200 pb. </li><li> Qualquer mudança de pontos possíveis em um conjunto de bandejas com idêntica contagem leitura irá mais provável queda nos limites mais exteriores. Consequentemente, é improvável que um ponto de mudança irá ocorrer a um limite interno entre duas caixas com as contagens de leitura mesmos. Então, escaninhos grupo adjacente, com idêntico leituras por bin, em um único bloco, ou seja. bedGraph formato 13. </li></ol> 2b. Puntiformes Perfis Leia: Chip pré-processamento e arquivos CAMA entrada para detecção de picos de Dados puntiformes <ol><li> Agregado sobreposição lê para Chip vertente mais e menos lê separadamente. As densidades vertente específica de leitura devem formar um perfil bimodal de picos de mais e de menos. Escolha pares mais / menos dos picos mais enriquecidos e usar a distância entre as suas cimeiras como uma estimativa do comprimento do fragmento de biblioteca. </li><li> Mudar o chip e entrada lê metade do fragmento length para o centro e recalcular a densidade de leitura do mais mudou e se fundiram e menos vertente lê. Esta metodologia para estimar o tamanho do fragmento foi adotada a partir de Zhang, et al. 3. Posições com contagens idênticas mesclagem deve ser agrupadas em blocos, semelhante ao passo 2A.2. </li></ol> 3. Estimar a média posterior Leia densidade de cada bloco usando nosso aproximação BCMIX <ol><li> A densidade de cada um dos blocos de leitura é modelado como uma distribuição de Poisson, Pois (θ t), com um parâmetro significativo na sequência de uma mistura de distribuições gama, Γ (α, β), e uma probabilidade anterior de um ponto de mudança ocorre a qualquer limite de bloco de p. Pois condicionado (θ t) em G (α, β) efectivamente torna o modelo de um HMM estado infinito. Estimar o hiper-parâmetros, α, β, e p, usando probabilidade posterior máxima. </li><li> Explicitamente calcular as estimativas de Bayes paracada bloco, t θ, como E (θ t | γ Z). Substituir o consumo mais tradicional, mas o tempo para a frente e para trás filtros usados ​​frequentemente em HMMs, com a aproximação mais eficiente computacionalmente Limitado Complexidade Mistura para estimar médias a posteriori, θ c. Os meios resultantes posteriores será &quot;suavizada&quot; em um perfil aproximado piecewise constante para blocos com idêntico, c θ, deve ser mais bloqueado juntamente com limite atualizados coordena. </li></ol> 4a. Difundir Leia Perfis: pós-processo médias a posteriori em segmentos de Enriquecimento difusa <ol><li> Utilizar o número de entrada de leituras por cada novo bloco c θ como a taxa de fundo, Pois (λ a) e determinar o enriquecimento com um teste de hipótese simples com base em se a média ChIP posterior, θ c, excede algum limiar δ. O 90 º &lt;/ Sup&gt; quantil é o padrão d e é apropriado na maioria dos casos. </li><li> Mesclar adjacente θ c blocos que excedem o enriquecimento em uma única região e relatório intercalar coordenadas em formato CAMA simples. Alternativamente, pode-se reportar o c θ para cada bloco em formato bedGraph para preservar os detalhes de alta-resolução das estimativas de densidade de leitura. </li></ol> 4b. Punctata Leia Perfis: pós-processo médias a posteriori para candidatos de pico <ol><li> Definir a taxa de fundo, Pois (λ a), como sendo a média de todos os pontos de leitura (γ 2) e identificar todos os blocos que ultrapassam o limiar, d. Desde picos puntiformes devem ser mais substancialmente enriquecido, o δ padrão é definido como o 99 º quantil de POIs (λ a). </li><li> Definir o bloco com o c máxima θ como a cimeira pico candidato e contíguo blocos de acompanhamento que compartilham um antro de leitura semelhantesidade (± 1 leia contar para permitir a pequena variação). Esta região adjacente é definido como um sítio de ligação candidato. </li><li> Calcular λ 2 como média das contagens de leitura no local candidato ChIP de ligação e de testes de hipóteses este fundo de entrada versus estavam a hipótese nula, H 0, que é uma λ ≥ λ 2 e rejeitar H 0 com base num limiar p-valor. Saída picos candidatos em formato CAMA. </li></ol>

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	<li>Park, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=ChIP-seq:+advantages+and+challenges+of+a+maturing+technology.">ChIP-seq: advantages and challenges of a maturing technology.</a> Nat. Rev. Genet. 10, 669-680 (2009).</li><li>Barski, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-resolution+profiling+of+histone+methylations+in+the+human+genome.">High-resolution profiling of histone methylations in the human genome.</a> Cell. 129, 823-837 (2007).</li><li>Zhang, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Model-based+Analysis+of+ChIP-Seq+(MACS).">Model-based Analysis of ChIP-Seq (MACS).</a> Genome Biol. 9, R137 (2008).</li><li>Zang, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+clustering+approach+for+identification+of+enriched+domains+from+histone+modification+ChIP-Seq+data.">A clustering approach for identification of enriched domains from histone modification ChIP-Seq data.</a> Bioinformatics. 25, 1952-1958 (2009).</li><li>Jothi, R., Cuddapah, S., Barski, A., Cui, K., Zhao, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+identification+of+in+vivo+protein-DNA+binding+sites+from+ChIP-Seq+data.">Genome-wide identification of in vivo protein-DNA binding sites from ChIP-Seq data.</a> Nucleic Acids Res. 36, 5221-5231 (2008).</li><li>Qin, Z. 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Biotechnol. 28, 1045-1048 (2010).</li><li>Karolchik, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+UCSC+Table+Browser+data+retrieval+tool.">The UCSC Table Browser data retrieval tool.</a> Nucleic Acids Res. 32, 493-496 (2004).</li><li>Matys, V., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=TRANSFAC:+transcriptional+regulation,+from+patterns+to+profiles.">TRANSFAC: transcriptional regulation, from patterns to profiles.</a> Nucleic Acids Res. 31, 374-378 (2003).</li><li>Portales-Casamar, E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=JASPAR+2010:+the+greatly+expanded+open-access+database+of+transcription+factor+binding+profiles.">JASPAR 2010: the greatly expanded open-access database of transcription factor binding profiles.</a> Nucleic Acids Res. 38, D105-D110 (2010).</li></ol>

Não há conflitos de interesse declarados.

Nós nos propusemos a desenvolver um modelo de análise de dados que possam identificar ChIPseq ambas as estruturas puntiformes e difusos dados igualmente bem. Até agora, as regiões de enriquecimento, as regiões particularmente difusas, que refletem a expectativa pressuposto de tamanho grande ilha, têm sido difíceis de identificar. Para resolver esses problemas, foram utilizados os mais recentes avanços na tecnologia de HMM, que possuem muitas vantagens sobre os modelos heurísticos existentes e HMMs menos inovado...

<table border="1"><tbody><tr><td> Nome do reagente </td><td> Companhia </td><td> Número de catálogo </td><td> Comentários (opcional) </td></tr><tr><td> Baseado em Linux estação de trabalho </td><td></td><td></td><td></td></tr></tbody></table>

a novel bayesian change-point algorithm for genome-wide analysis of diverse chipseq data types

ChIPseq é uma técnica amplamente utilizada para investigar interacções DNA-proteína. Ler a densidade perfis são gerados usando a próxima sequência de ADN ligado à proteína e alinhando a curto leituras para um genoma de referência. Regiões enriquecidas são revelados como picos, o que muitas vezes diferem dramaticamente de forma, dependendo da proteína alvo 1. Por exemplo, factores de transcrição ligam frequentemente em um local e modo específico da sequência e tendem a produzir picos puntiformes, enquanto que modificações de histonas são mais difusas e caracterizam-se por grandes difusas, ilhas de enriquecimento 2. Confiável identificação dessas regiões foi o foco do nosso trabalho. Algoritmos de análise de dados ChIPseq empregaram várias metodologias, de heurísticas 3-5 aos mais rigorosos modelos estatísticos, por exemplo, modelos ocultos de Markov (HMM) 6-8. Nós procuramos uma solução que minimizasse a necessidade de difíceis de definir, parâmetros ad hoc, que muitas vezescomprometer resolução e diminuir a possibilidade de utilização intuitiva da ferramenta. Com relação aos métodos baseados em HMM, buscamos reduzir os procedimentos de estimação e de parâmetros simples, classificações de estado finito que são frequentemente utilizados. Além disso, a análise de dados convencional ChIPseq envolve categorização do esperado ler perfis de densidade como quer punctata ou difusa seguido de posterior aplicação da ferramenta apropriada. Nós ainda como objetivo substituir a necessidade de estes dois modelos distintos com um único modelo mais versátil, que pode competentemente abordar todo o espectro de tipos de dados. Para atingir estes objectivos, o primeiro construído um quadro estatístico que naturalmente modelados estruturas ChIPseq de dados usando um avanço de ponta em HMMs 9, que utiliza apenas fórmulas explícitas-uma inovação crucial para suas vantagens de desempenho. Modelos mais sofisticados, em seguida, heurísticas, nossa HMM acomoda infinitos estados ocultos através de umModelo Bayesian. Nós aplicamos a identificação de pontos de mudança razoável na densidade de ler, que ainda definir segmentos de enriquecimento. Nossa análise revelou como nosso Bayesiana mudar o ponto algoritmo (BCP) teve uma complexidade computacional reduzido evidenciado por um tempo de execução abreviada e consumo de memória. O algoritmo BCP foi aplicado com sucesso tanto o pico punctata e identificação ilha difusa com precisão robusto e limitados parâmetros definidos pelo usuário. Isto ilustrado tanto a sua versatilidade e facilidade de uso. Conseqüentemente, acreditamos que pode ser implementada facilmente em intervalos amplos de tipos de dados e usuários finais de uma forma que pode ser facilmente comparados e contrastados, tornando-se uma grande ferramenta para ChIPseq análise de dados que pode ajudar na colaboração e corroboração entre grupos de pesquisa. Aqui, demonstramos a aplicação do factor de transcrição de BCP existente 10,11 e 12 epigenéticas dados para ilustrar a sua utilidade.

BCP destaca em identificação de regiões de enriquecimento amplo em dados de modificação de histonas. Como ponto de referência, que anteriormente comparação dos nossos resultados aos de SICER 3, uma ferramenta já existente que tem demonstrado forte desempenho. Para ilustrar melhor as vantagens do BCP, examinamos uma modificação de histonas que tinha sido bem estudado para estabelecer uma base para avaliar as taxas de sucesso. Com isto em mente, é então analisada H3K36me3, uma vez que tem sido demo...

Watch this Scientific Journal Video about A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types at JoVE.com

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Nosso ponto de mudança Bayesiana (BCP) algoritmo baseia-se no estado-da-arte avanços em modelagem de mudanças de pontos através de modelos ocultos de Markov e os aplica a cromatina imunoprecipitação seqüenciamento (ChIPseq) análise de dados. BCP executa bem em tipos de dados ampla e pontuada, mas supera em identificar com precisão robustos, ilhas reproduzíveis de enriquecimento histona difusa.

A Novel Bayesiana Algoritmo de Mudança-ponto para Genome-wide Análise de tipos de dados ChIPseq Diversos

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of ...

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Biology

11.2K visualizações.  Stony Brook University. Nosso ponto de mudança Bayesiana (BCP) algoritmo baseia-se no estado-da-arte avanços em modelagem de mudanças de pontos através de modelos ocultos de Markov e os aplica a cromatina imunoprecipitação seqüenciamento (ChIPseq) análise de dados. BCP executa bem em tipos de dados ampla e pontuada, mas supera em identificar com precisão robustos, ilhas reproduzíveis de enriquecimento histona difusa.

Vídeo: A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Neuronal and Astrocyte Co-Culture Assay for High Content Analysis of Neurotoxicity

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing measurement of multiple cellular phenotypes within a single assay. In this study, we utilized HCA to develop a novel assay for neurotoxicity. Neurotoxicity assessment represents an important part of drug safety evaluation, as well as being a significant focus of environmental protection efforts. Additionally, neurotoxicity is also a well-accepted in vitro marker of the development of neurodegenerative diseases such as Alzheimer's and Parkinson's diseases. Recently, the application of HCA to neuronal screening has been reported. By labeling neuronal cells with &beta;III-tubulin, HCA assays can provide high-throughput, non-subjective, quantitative measurements of parameters such as neuronal number, neurite count and neurite length, all of which can indicate neurotoxic effects. However, the role of astrocytes remains unexplored in these models. Astrocytes have an integral role in the maintenance of central nervous system (CNS) homeostasis, and are associated with both neuroprotection and neurodegradation when they are activated in response to toxic substances or disease states. GFAP is an intermediate filament protein expressed predominantly in the astrocytes of the CNS. Astrocytic activation (gliosis) leads to the upregulation of GFAP, commonly accompanied by astrocyte proliferation and hypertrophy. This process of reactive gliosis has been proposed as an early marker of damage to the nervous system. The traditional method for GFAP quantitation is by immunoassay. This approach is limited by an inability to provide information on cellular localization, morphology and cell number. We determined that HCA could be used to overcome these limitations and to simultaneously measure multiple features associated with gliosis - changes in GFAP expression, astrocyte hypertrophy, and astrocyte proliferation - within a single assay. In co-culture studies, astrocytes have been shown to protect neurons against several types of toxic insult and to critically influence neuronal survival. Recent studies have suggested that the use of astrocytes in an in vitro neurotoxicity test system may prove more relevant to human CNS structure and function than neuronal cells alone. Accordingly, we have developed an HCA assay for co-culture of neurons and astrocytes, comprised of protocols and validated, target-specific detection reagents for profiling &beta;III-tubulin and glial fibrillary acidic protein (GFAP). This assay enables simultaneous analysis of neurotoxicity, neurite outgrowth, gliosis, neuronal and astrocytic morphology and neuronal and astrocytic development in a wide variety of cellular models, representing a novel, non-subjective, high-throughput assay for neurotoxicity assessment. The assay holds great potential for enhanced detection of neurotoxicity and improved productivity in neuroscience research and drug discovery.

This article describes a novel protocol and reagent set designed for sensitive measurement of neurotoxic effects of compounds and treatments on co-cultures of neurons and astrocytes using high content analysis. Results demonstrate that high content analysis represents an exciting novel technology for neurotoxicity assessment.

A Neuronal e astrocitária Ensaio Co-Cultura de Análise de Conteúdo de Alta de neurotoxicidade

High Content Analysis (HCA) assays combine cells and detection reagents with automated imaging and powerful image analysis algorithms, allowing ...

Biologia

Genome-wide Analysis of Aminoacylation (Charging) Levels of tRNA Using Microarrays

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both prokaryotic and eukaryotic cells lead to translational regulation which is a major cellular mechanism of stress response. Familiar examples are the stringent response in E. coli and the Gcn2 stress response pathway in yeast ([2-6]). Recent work in E. coli and S. cerevisiae have shown that tRNA charging patterns are highly dynamic and depends on the type of stress experienced by cells [1, 6, 7]. The highly dynamic, variable nature of tRNA charging makes it essential to determine changes in tRNA charging levels at the genomic scale, in order to fully elucidate cellular response to environmental variations. In this review we present a method for simultaneously measuring the relative charging levels of all tRNAs in S. cerevisiae . While the protocol presented here is for yeast, this protocol has been successfully applied for determining relative charging levels in a wide variety of organisms including E. coli and human cell cultures[7, 8].

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

We describe a method for microarray analysis to determine relative aminoacylation levels of all tRNAs from S. cerivisiae.

Análise do genoma de Aminoacylation (carregamento) Níveis de tRNA Usando Microarrays

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both ...

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the protein domains that bind to specific histone modifications. One such domain is the plant homeodomain (PHD), found in several chromatin-binding proteins. The epigenetic factor RBP2 has multiple PHD domains, however, they have different functions (Figure 4). In particular, the C-terminal PHD domain, found in a RBP2 oncogenic fusion in human leukemia, binds to trimethylated lysine 4 in histone H3 (H3K4me3)1. The transcript corresponding to the RBP2 isoform containing the C-terminal PHD accumulates during differentiation of promonocytic, lymphoma-derived, U937 cells into monocytes2. Consistent with both sets of data, genome-wide analysis showed that in differentiated U937 cells, the RBP2 protein gets localized to genomic regions highly enriched for H3K4me33. Localization of RBP2 to its targets correlates with a decrease in H3K4me3 due to RBP2 histone demethylase activity and a decrease in transcriptional activity. In contrast, two other PHDs of RBP2 are unable to bind H3K4me3. Notably, the C-terminal domain PHD of RBP2 is absent in the smaller RBP2 isoform4. It is conceivable that the small isoform of RBP2, which lacks interaction with H3K4me3, differs from the larger isoform in genomic location. The difference in genomic location of RBP2 isoforms may account for the observed diversity in RBP2 function. Specifically, RBP2 is a critical player in cellular differentiation mediated by the retinoblastoma protein (pRB). Consistent with these data, previous genome-wide analysis, without distinction between isoforms, identified two distinct groups of RBP2 target genes: 1) genes bound by RBP2 in a manner that is independent of differentiation; 2) genes bound by RBP2 in a differentiation-dependent manner.
To identify differences in localization between the isoforms we performed genome-wide location analysis by ChIP-Seq. Using antibodies that detect both RBP2 isoforms we have located all RBP2 targets. Additionally we have antibodies that only bind large, and not small RBP2 isoform (Figure 4). After identifying the large isoform targets, one can then subtract them from all RBP2 targets to reveal the targets of small isoform. These data show the contribution of chromatin-interacting domain in protein recruitment to its binding sites in the genome.

Here we are presenting a chromatin immunoprecipitation (ChIP) procedure for genome-wide location analysis of protein isoforms that differ in a histone-binding domain. We are applying it to ChIP-Seq analysis to identify the targets of the KDM5A/JARID1A/RBP2 histone demethylase.

Análise do genoma usando chip para identificar alvos isoforma específica Gene

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the ...

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, genome-wide cDNA library cloned into the 3'UTR downstream from the dual-selection fusion protein, thymidine kinase-zeocin (TKzeo). The first round of selection is for stable transformants, followed with introduction of a miRNA of interest, and finally, selecting for cDNAs containing the miRNA's target. Selected cDNAs are identified by sequencing (see Figure 1-3 for Target ID Library Workflow and details).
To ensure broad coverage of the human transcriptome, Target ID Library cDNAs were generated via oligo-dT priming using a pool of total RNA prepared from multiple human tissues and cell lines. Resulting cDNA range from 0.5 to 4 kb, with an average size of 1.2 kb, and were cloned into the p3&#900;TKzeo dual-selection plasmid (see Figure 4 for plasmid map). The gene targets represented in the library can be found on the Sigma-Aldrich webpage. Results from Illumina sequencing (Table 3), show that the library includes 16,922 of the 21,518 unique genes in UCSC RefGene (79%), or 14,000 genes with 10 or more reads (66%).

The Target ID Library is a plasmid-based, genome-wide collection of cloned cDNA used to identify miRNA targets. Here we demonstrate its use and application.

Genome-wide tela de Metas de miRNA Usando a missão Biblioteca ID Alvo

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, ...

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene 1. While the creation of libraries of RNAi clones covering most of the C. elegans genome 2,3 opened the way for true functional genomic studies (see for example 4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens 8. The approach relies on microscopic imaging and image analysis. 
	Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture.
	We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing9. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

We describe a protocol using C. elegans and RNAi feeding libraries that allows automated measurement of multiple parameters such as fluorescence, size and opacity of individual worms in a population. We give one example of a screen to identify genes involved in anti-fungal innate immunity in C. elegans.

Quantitativos e automatizada de alto rendimento de todo o genoma Telas de RNAi em C. elegans</em

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. ...

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Transposon mutagenesis and single-gene deletion are two methods applied in genome-wide gene knockout in bacteria 1,2. Although transposon mutagenesis is less time consuming, less costly, and does not require completed genome information, there are two weaknesses in this method: (1) the possibility of a disparate mutants in the mixed mutant library that counter-selects mutants with decreased competition; and (2) the possibility of partial gene inactivation whereby genes do not entirely lose their function following the insertion of a transposon. Single-gene deletion analysis may compensate for the drawbacks associated with transposon mutagenesis. To improve the efficiency of genome-wide single gene deletion, we attempt to establish a high-throughput technique for genome-wide single gene deletion using Streptococcus sanguinis as a model organism. Each gene deletion construct in S. sanguinis genome is designed to comprise 1-kb upstream of the targeted gene, the aphA-3 gene, encoding kanamycin resistance protein, and 1-kb downstream of the targeted gene. Three sets of primers F1/R1, F2/R2, and F3/R3, respectively, are designed and synthesized in a 96-well plate format for PCR-amplifications of those three components of each deletion construct. Primers R1 and F3 contain 25-bp sequences that are complementary to regions of the aphA-3 gene at their 5' end. A large scale PCR amplification of the aphA-3 gene is performed once for creating all single-gene deletion constructs. The promoter of aphA-3 gene is initially excluded to minimize the potential polar effect of kanamycin cassette. To create the gene deletion constructs, high-throughput PCR amplification and purification are performed in a 96-well plate format. A linear recombinant PCR amplicon for each gene deletion will be made up through four PCR reactions using high-fidelity DNA polymerase. The initial exponential growth phase of S. sanguinis cultured in Todd Hewitt broth supplemented with 2.5% inactivated horse serum is used to increase competence for the transformation of PCR-recombinant constructs. Under this condition, up to 20% of S. sanguinis cells can be transformed using ~50 ng of DNA. Based on this approach, 2,048 mutants with single-gene deletion were ultimately obtained from the 2,270 genes in S. sanguinis excluding four gene ORFs contained entirely within other ORFs in S. sanguinis SK36 and 218 potential essential genes. The technique on creating gene deletion constructs is high throughput and could be easy to use in genome-wide single gene deletions for any transformable bacteria.

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

An efficient genome-wide single gene mutation method has been established using Streptococcus sanguinis as a model organism. This method has achieved via high throughput recombinant PCRs and transformations.

Do genoma deleções de genes em<em&gt; Streptococcus sanguinis</em&gt; Por PCR de Alto Rendimento

Transposon  mutagenesis and single-gene deletion are two methods applied in genome-wide  gene knockout in bacteria 1,2. Although transposon mutagenesis is ...

Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale

mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed &#8220;anota&#8221; algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.

Ribosomes play a central role in protein synthesis. Polyribosome (polysome) fractionation by sucrose density gradient centrifugation allows direct determination of translation efficiencies of individual mRNAs on a genome-wide scale. In addition, this method can be used for biochemical analysis of ribosome- and polysome-associated factors such as chaperones and signaling molecules.

Polysome Fracionamento e Análise de mamíferos Translatomes em uma escala genômica

mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. ...

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC (Crosslinking of Small Molecules to Isolate Chromatin)

The genome is the target of some of the most effective chemotherapeutics, but most of these drugs lack DNA sequence specificity, which leads to dose-limiting toxicity and many adverse side effects. Targeting the genome with sequence-specific small molecules may enable molecules with increased therapeutic index and fewer off-target effects. N-methylpyrrole/N-methylimidazole polyamides are molecules that can be rationally designed to target specific DNA sequences with exquisite precision. And unlike most natural transcription factors, polyamides can bind to methylated and chromatinized DNA without a loss in affinity. The sequence specificity of polyamides has been extensively studied in vitro with cognate site identification (CSI) and with traditional biochemical and biophysical approaches, but the study of polyamide binding to genomic targets in cells remains elusive. Here we report a method, the crosslinking of small molecules to isolate chromatin (COSMIC), that identifies polyamide binding sites across the genome. COSMIC is similar to chromatin immunoprecipitation (ChIP), but differs in two important ways: (1) a photocrosslinker is employed to enable selective, temporally-controlled capture of polyamide binding events, and (2) the biotin affinity handle is used to purify polyamide&#8211;DNA conjugates under semi-denaturing conditions to decrease DNA that is non-covalently bound. COSMIC is a general strategy that can be used to reveal the genome-wide binding events of polyamides and other genome-targeting chemotherapeutic agents.

Genome-wide Mapping of Drug-DNA Interactions in Cells with COSMIC Crosslinking of Small Molecules to Isolate Chromatin

Identifying the direct targets of genome-targeting molecules remains a major challenge. To understand how DNA-binding molecules engage the genome, we developed a method that relies on crosslinking of small molecules to isolate chromatin (COSMIC).

Mapeamento de todo o genoma de DNA Interações medicamentosas-em células com COSMIC (reticulação de moléculas pequenas para isolar Chromatin)

The genome is the target of some of the most effective chemotherapeutics, but most of these drugs lack DNA sequence specificity, which leads to ...

Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells

Extrachromosomal circular DNAs (eccDNAs) are common genetic elements in Saccharomyces cerevisiae and are reported in other eukaryotes as well. EccDNAs contribute to genetic variation among somatic cells in multicellular organisms and to evolution of unicellular eukaryotes. Sensitive methods for detecting eccDNA are needed to clarify how these elements affect genome stability and how environmental and biological factors&#160;induce their formation in eukaryotic cells. This video presents a sensitive eccDNA-purification method called Circle-Seq. The method encompasses column purification of circular DNA, removal of remaining linear chromosomal DNA, rolling-circle amplification of eccDNA, deep sequencing, and mapping. Extensive exonuclease treatment&#160;was&#160;required for sufficient linear chromosomal DNA degradation. The rolling-circle amplification step by &#966;29 polymerase enriched for circular DNA over linear DNA. Validation of the Circle-Seq method on three S. cerevisiae CEN.PK populations of 1010 cells detected hundreds of eccDNA profiles in sizes larger than 1 kilobase. Repeated findings of ASP3-1, COS111, CUP1, RSC30,&#160;HXT6, HXT7 genes on circular DNA in both S288c and CEN.PK suggests that DNA circularization is conserved between strains at these loci. In sum, the Circle-Seq method has broad applicability for genome-scale screening for eccDNA in eukaryotes as well as for detecting specific eccDNA types.

This paper presents a sensitive method called Circle-Seq for purifying extrachromosomal circular DNA (eccDNA). The method encompasses column purification, removal of remaining linear chromosomal DNA, rolling-circle amplification and high-throughput sequencing. Circle-Seq is applicable to genome-scale screening of eukaryotic eccDNA and studying genome instability and copy-number variation.

A purificação de todo o genoma de DNA circular Extracromossômica de células eucarióticas

Extrachromosomal circular DNAs (eccDNAs) are common genetic elements in Saccharomyces cerevisiae and are reported in other eukaryotes as well. EccDNAs ...

Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine

Classification and nomenclature of genes in a family can significantly contribute to the description of the diversity of encoded proteins and to the prediction of family functions based on several features, such as the presence of sequence motifs or of particular sites for post-translational modification and the expression profile of family members in different conditions. This work describes a detailed protocol for gene family characterization. Here, the procedure is applied to the characterization of the Arabidopsis T&#243;xicos in Levadura (ATL) E3 ubiquitin ligase family in grapevine. The methods include the genome-wide identification of family members, the characterization of gene localization, structure, and duplication, the analysis of conserved protein motifs, the prediction of protein localization and phosphorylation sites as well as gene expression profiling across the family in different datasets. Such procedure, which could be extended to further analyses depending on experimental purposes, could be applied to any gene family in any plant species for which genomic data are available, and it provides valuable information to identify interesting candidates for functional studies, giving insights into the molecular mechanisms of plant adaptation to their environment.

This article describes the procedure for the identification and characterization of a gene family in grapevine applied to the family of Arabidopsis T&#243;xicos in Levadura (ATL) E3 ubiquitin ligases.

Fluxo de trabalho abrangente para a identificação de todo o genoma e Meta-análise da expressão da ATL E3 ubiquitina Ligase Gene família em videira

Classification and nomenclature of genes in a family can significantly contribute to the description of the diversity of encoded proteins and to the ...