Agradecemos toda a vida Sigma Ciência Missão Alvo ID equipe de desenvolvimento da biblioteca, especialmente Kevin Gutshall para encontrar a tecnologia e negociar os termos de licença e Heather Holemon por seu apoio e participação nas discussões de problemas frutíferas. Agradecemos também a Dr. Joop Gäken de Faculdade Londres do rei para livremente compartilhar os resultados inéditos e sugestões, e Qazi Hamid RxBiosciences para a preparação de um lote grande de cDNA e sua persistência em consegui-lo clonado. Nós gostaríamos de agradecer Nan Lin e Scott Bahr de SAFC para a realização de arranjos de cDNA e análise de dados. MISSÃO é uma marca registrada da LP Biotecnologia Sigma-Aldrich

<ol>
	<li>Huang, Q., Gumireddy, K., Schrier, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+microRNAs+miR-373+and+miR-520c+promote+tumour+invasion+and+metastasis.">The microRNAs miR-373 and miR-520c promote tumour invasion and metastasis.</a> Nat. Cell Biol. 10 (2), 202-210 (2008).</li><li>Lichner, Z., Pall, E., Kerekes, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+miR-290-295+cluster+promotes+pluripotency+maintenance+by+regulating+cell+cycle+phase+distribution+in+mouse+embryonic+stem+cells.">The miR-290-295 cluster promotes pluripotency maintenance by regulating cell cycle phase distribution in mouse embryonic stem cells.</a> Differentiation. 81 (1), 11-24 (2011).</li><li>Subramanyam, D., Lamouille, S., Judson, R. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+targets+of+miR-302+and+miR-372+promote+reprogramming+of+human+fibroblasts+to+induced+pluripotent+stem+cells.">Multiple targets of miR-302 and miR-372 promote reprogramming of human fibroblasts to induced pluripotent stem cells.</a> Nat. Biotechnol. 29 (5), 443-448 (2001).</li><li>Lim, L. P., Lau, N. C., Garrett-Engele, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microarray+analysis+shows+that+some+microRNAs+downregulate+large+numbers+of+target+mRNAs.">Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs.</a> Nature. 433 (7027), 769-773 (2005).</li><li>Huntzinger, E., Izaurralde, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+silencing+by+microRNAs:+contributions+of+translational+repression+and+mRNA+decay.">Gene silencing by microRNAs: contributions of translational repression and mRNA decay.</a> Nat. Rev. Genet. 12 (2), 99-110 (2011).</li><li>Thomas, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Desperately+seeking+microRNA+targets.">Desperately seeking microRNA targets.</a> Nat. Struc. Mol. Biol. 17 (10), 1169-1174 (2010).</li><li>Baek, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+impact+of+microRNAs+on+protein+output.">The impact of microRNAs on protein output.</a> Nature. 455 (7209), 71-71 (2008).</li><li>Guo, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mammalian+microRNAs+predominantly+act+to+decrease+target+mRNA+levels.">Mammalian microRNAs predominantly act to decrease target mRNA levels.</a> Nature. 466 (3708), 835-840 (2010).</li><li>Ma, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tumour+invasion+and+metastasis+initiated+my+microRNA-10b+in+breast+cancer.">Tumour invasion and metastasis initiated my microRNA-10b in breast cancer.</a> Nature. 449 (7163), 682-688 (2007).</li><li>Visone, R., 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=MicroRNAs+miR-221+and+miR-222,+both+overexpressed+in+human+thyroid+papillary+carcinomas,+regulate+p27Kip1+protein+levels+and+cell+cycle.">MicroRNAs miR-221 and miR-222, both overexpressed in human thyroid papillary carcinomas, regulate p27Kip1 protein levels and cell cycle.</a> Endocrine-Related Cancer. 14 (3), 791-798 (2007).</li><li>Lu, Z., 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=MicroRNA-21+promotes+cell+transformation+by+targeting+the+programmed+cell+death+4+gene.">MicroRNA-21 promotes cell transformation by targeting the programmed cell death 4 gene.</a> Oncogene. 27 (31), 4373-4379 (2008).</li><li>Guo, 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=The+noncoding+RNA,+miR-126,+suppresses+the+growth+of+neoplastic+cells+by+targeting+phosphatidylinositol+3-kinase+signaling+and+is+frequently+lost+in+colon+cancers.">The noncoding RNA, miR-126, suppresses the growth of neoplastic cells by targeting phosphatidylinositol 3-kinase signaling and is frequently lost in colon cancers.</a> Genes Chrom. Cancer. 47 (11), 939-946 (2008).</li><li>Yamakuchi, M., 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=miR-34a+repression+of+SIRT1+regulates+apoptosis.">miR-34a repression of SIRT1 regulates apoptosis.</a> Proc. Natl. Acad. Sci. U.S.A. 105 (36), 13421-13426 (2008).</li><li>Wickramasinghe, N. S., 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=Estradiol+downregulates+miR-21+expression+and+increases+miR-21+target+gene+expression+in+MCF-7+breast+cancer+cells.">Estradiol downregulates miR-21 expression and increases miR-21 target gene expression in MCF-7 breast cancer cells.</a> Nucleic Acid Res. 37 (8), 2584-2595 .</li><li>Ciaudo, 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=Highly+dynamic+and+sex-specific+expression+of+microRNAs+during+early+ES+cell+differentiation.">Highly dynamic and sex-specific expression of microRNAs during early ES cell differentiation.</a> PLoS Genetics. 5, e1000620 (2009).</li><li>Vallejo, D. M., 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=Targeting+Notch+signaling+by+the+conserved+miR-8/200+microRNA+family+in+development+and+cancer+cells.">Targeting Notch signaling by the conserved miR-8/200 microRNA family in development and cancer cells.</a> EMBO J. 30 (4), 756-769 (2011).</li><li>Jafarifar, F., 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=Repression+of+VEGFA+by+CA-rich+element-binding+microRNAs+is+modulated+by+hnRNAP.">Repression of VEGFA by CA-rich element-binding microRNAs is modulated by hnRNAP.</a> L. EMBO J. 30 (7), 1324-1334 (2011).</li><li>Clancy, J. L., 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=mRNA+isoform+diversity+can+obscure+detection+of+miRNA-mediated+control+of+translation.">mRNA isoform diversity can obscure detection of miRNA-mediated control of translation.</a> RNA. 17 (6), 1025-1033 (2011).</li></ol>

Os autores declaram relações financeiras com entidades comerciais que tenham interesse no trabalho apresentado.

microRNAs são RNAs de 20-24 nucleotídeos que regulam a expressão gênica pós-transcricional pela tradução do mRNA inibição e, freqüentemente, desestabilizar o mRNA alvo (revisto em [6]). Um único miRNA pode regular várias centenas de mRNAs para controlar a resposta de uma célula a sinais ambientais e de desenvolvimento. Identificação e validação de mRNAs alvo é essencial para determinar o papel de um miRNA e função nestas vias. No entanto, a identificação do alvo não é simples porque, em animais, miRNAs e seus locais-alvo não são totalmente complementares. A &quot;semente&quot; região, baseia 2 a 7 a partir da extremidade 5 &#39;da miRNA, é geralmente complementar aos seus alvos. No entanto, existem muitas exceções à regra de sementes, ea jusante emparelhamento de bases pode compensar uma correspondência semente imperfeita. Um certo número de algoritmos de computador têm sido desenvolvidos para prever alvos miRNA baseado em correspondência de sementes e de compensação a jusante, uma estrutura alvoposição d, conservação da sequência, e vários outros parâmetros que têm sido observados para alvos validados experimentalmente (revisto em [7]). Enquanto in silico previsões são convenientes e se identificam muitos alvos miRNA válidos, a maioria previu genes falhar os testes de validação experimental, e muitos alvos reais não são previstos. Além disso, desde algoritmos de computador são baseados em características-alvo previamente determinados, eles não permitem a descoberta de alvos que se afastam do que já é conhecido. Um certo número de sistemas experimentais têm sido utilizados com sucesso para identificar ou descobrir alvos miRNA funcionais em células vivas. Estes métodos de rastreamento globais incluem microarrays e sequenciamento de RNA, RNA co-imunoprecipitação (RIP), e Rotulagem Isótopos Estáveis ​​com Aminoácidos em cultura de células (SILAC), um método de proteômica (revisto em [7]). Cada método tem vantagens e desvantagens. Uma vez que miRNA segmentação frequentemente desestabiliza um mRNA e leva a sua degradação, uma perdar ganho no nível de ARNm após a introdução de um miRNA imitar ou inibidor, respectivamente, podem identificar alvos miRNA. Esta perda ou ganho de mRNA é facilmente detectada por microarray ou sequenciação de profundidade. Enquanto os métodos de detecção de mRNA são mais simples e mais sensível do que os métodos de detecção de proteínas, detecção de mRNA vai perder todos os alvos do miRNA que não são degradados. Relatórios recentes do laboratório Bartell comparando os resultados da detecção de miRNA-alvo RNA com os de SILAC [8] ou perfil ribossoma [9] indicam que os miRNAs mamíferos predominantemente agir, reduzindo os níveis de mRNA alvo. No entanto, muitos outros laboratórios que trabalham com metas de miRNA individuais detectaram alteração na proteína, mas nenhuma mudança no nível de mRNA. Relatos de que parece ser translacional regulação sem perda mRNA detectável incluem: miR-10b em HOXD10 [10], miR221/222 em p27KIP1 mostrou [11], miR-21 em Pdcd4 [12], miR-126 em p85β [13] , miR-34 em SIRT1 [14], miR-21 em PTEN [15], miR-302D em Arid4b [16], miR-200c em JAG1 [17], e miR-299, 297, 567, umnd 609 em VEGFA [18]. Além disso, Clancy et al [19] relatou recentemente que a regulação traducional por let-7 só foi detectado quando isoformas de RNAm individuais que contêm o local de let-7-alvo foram detectados de forma selectiva. A segunda sugere que, pelo menos em alguns casos, a regulação de translação pode ser negligenciada em um perfil compósito - isto é, quando todas as isoformas de mRNA são detectadas como uma mRNA - como obtido com microarray muitos e análise de sequências. Co-imunoprecipitação de miRNA mRNA complexos através Argonaute (geralmente ago2) ou outra proteína associada (RNA imunoprecipitação, ou RIP) vai isolar alvos miRNA independentemente do mecanismo de regulação. Além disso, RIP detecta endógena, e presumivelmente biologicamente relevantes, interacções. No entanto, não se sabe se todas as interacções miRNA de mRNA-são funcionais, e RIP perderia todos os objectivos de ARNm que se associam apenas transitoriamente ou são rapidamente degradados. Além disso, miRNA específicos de mRNA-parceiros deve ser inferida bioinformaticamente porque todos os pares de mRNA miRNA-co-precipitado em conjunto. Finalmente, SILAC directamente identifica o produto final de regulação miRNA, a própria proteína, mas é insensível e, portanto, perde proteínas raras e as pequenas alterações vezes nos níveis de proteína. À luz das limitações com os actuais métodos de identificação de miRNA-alvo, sentimos um ensaio adicional global para identificar alvos miRNA funcionais por um mecanismo alternativo foi necessário. Para suprir essa necessidade, que licenciou uma tecnologia inventada por Joop Gaken e Mohamedali Azim de Faculdade Londres do rei. A invenção é uma proteína de fusão dupla selecção, especificamente, uma timidina-quinase de fusão zeocin, regulada por uma biblioteca de cDNA de sequências de miRNA potenciais alvo na sua 3&#39;UTR. Células estavelmente transfectadas com e expressando TKzeo-cDNA construções podem ser seleccionados com zeocin, conforme ilustrado na Fig. 2. Depois de expressar um miRNA de interesse, as metas que miRNA pode ser selecionado with ganciclovir, como ilustrado na Fig. 3. Ganciclovir mata as células expressando timidina-quinase, ou seja, as células expressando TKzeo-cDNA falta um alvo para a miRNA de interesse. Targeted cDNA pode ser isolado por amplificação por PCR de DNA a partir de células que sobrevivem ganciclovir iniciadores utilizando que flanqueiam os produtos de cDNA, e PCR podem ser sequenciados para identificar alvos. Temos desenvolvido tecnologia da Kings College em uma nova ferramenta para a identificação global e descoberta de metas funcionais miRNA humanos - a MISSÃO Biblioteca ID Target. Com a biblioteca de ID do alvo, os utilizadores podem isolar alvos miRNA por uma série de transfecção das células de mamíferos cultura e os passos de selecção de drogas. A Biblioteca é abrangente, e contém 66-79% de genes humanos. Os resultados iniciais indicam que tanto a descoberto anteriormente, bem como novos alvos podem ser isolados a partir da biblioteca ID MISSÃO alvo. Embora o protocolo é de alguma extensão,uso da Biblioteca identificação de destino exige técnicas padrão de laboratório molecular - cultura de células de mamíferos, transfecção, a seleção de drogas, PCR, e seqüenciamento - e, portanto, deve ser bem no meio da maioria dos biólogos. Sugerimos que a atenção suficiente ser pago ao delineamento experimental adequado, otimizando as condições de cultura e, mais importante, pré-teste de cada novo tipo de célula para determinar os níveis ótimos de drogas para as etapas de seleção (matar-curvas) para garantir o sucesso com a Biblioteca ID Target. Tal como acontece com todos os métodos de identificação de miRNA alvo, é altamente recomendável que os alvos identificados pela triagem da biblioteca ID do alvo ser validado com um segundo método, tal como microarray, qRT-PCR, o ensaio de repórter (isto é, luciferase), ou análise de Western.

<table border="1" ><tbody><tr><td> Nome do reagente </td><td> Companhia </td><td> Número de Catálogo </td><td> Comentários </td></tr><tr><td> JumpStart REDTaq Readymix </td><td> Sigma-Aldrich </td><td> P0982 </td><td></td></tr><tr><td> Ganciclovir </td><td> Sigma-Aldrich </td><td> G2536 </td><td></td></tr><tr><td> G418 </td><td> Sigma-Aldrich </td><td> G8168 </td><td></td></tr><tr><td> Puromicina </td><td> Sigma-Aldrich </td><td> P9620 </td><td></td></tr><tr><td> Topo TA </td><td> Invitrogen </td><td> KNM4500-01 </td><td></td></tr><tr><td> GenElute mamíferos Genomic DNA Miniprep Kit </td><td> Sigma-Aldrich </td><td> G1N10 </td><td></td></tr><tr><td> Célula k Nucleofection específicaele </td><td> Lonza </td><td></td><td></td></tr><tr><td> Nucleofector </td><td> Lonza </td><td> AAD-1001 </td><td></td></tr><tr><td> Zeocin </td><td> Invitrogen </td><td> <a href="http://products.invitrogen.com/ivgn/en/US/adirect/invitrogen?cmd=catProductDetail&amp;productID=R25001">R250-01</a> </td><td></td></tr><tr><td height="1"> Identificação do destino Biblioteca </td><td> Sigma-Aldrich </td><td> MREH01 </td><td></td></tr></tbody></table>

genome-wide screen for mirna targets using the mission target id library

A Biblioteca de ID Alvo é projetado para ajudar nas metas de descoberta e identificação de microRNA (miRNA). A biblioteca de ID do alvo é um plasmídeo baseado em biblioteca de todo o genoma de cDNA clonado a jusante 3&#39;UTR a partir da proteína de fusão de selecção de dupla, timidina-quinase zeocin (TKzeo). A primeira rodada de seleção é para transformantes estáveis, seguido com a introdução de um miRNA de interesse, e, finalmente, a seleção de cDNAs contendo a meta de miRNA. CDNAs selecionados são identificados por seqüenciamento (ver Figura 1-3 Fluxo de Trabalho para a Target Biblioteca ID e detalhes). Para garantir uma ampla cobertura do transcriptoma humano, Target ID Biblioteca cDNAs foram gerados através de oligo-dT priming usando um pool de ARN total preparado a partir de vários tecidos humanos e linhas celulares. Resultando gama de cDNA de 0,5 a 4 kb, com um tamanho médio de 1,2 kb, e foram clonados no dupla-selecção p3TKzeo plasmídeo (ver Figura 4 para o mapa do plasmídeo). Os alvos de genes representados na library podem ser encontradas no site da Sigma-Aldrich. Os resultados de sequenciação Illumina (Tabela 3), mostram que a biblioteca inclui 16.922 dos 21,518 genes únicos em UCSC RefGene (79%), ou 14.000 genes com 10 ou mais lê (66%).

Watch this Scientific Journal Video about Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library at JoVE.com

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

A Biblioteca de ID de destino é um plasmídeo baseado em coleta de todo o genoma de cDNA clonado usado para identificar alvos miRNA. Aqui nós demonstrar o seu uso e aplicação.

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, ...

genome-wide-screen-for-mirna-targets-using-mission-target-id

Research

JoVE Journal

Biology

17.5K visualizações.  Sigma-Aldrich. A Biblioteca de ID de destino é um plasmídeo baseado em coleta de todo o genoma de cDNA clonado usado para identificar alvos miRNA. Aqui nós demonstrar o seu uso e aplicação.

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

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 ...

Biologia

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 ...

MISSION LentiPlex Pooled shRNA Library Screening in Mammalian Cells

RNA interference (RNAi) is an intrinsic cellular mechanism for the regulation of gene expression. Harnessing the innate power of this system enables us to knockdown gene expression levels in loss of gene function studies.
There are two main methods for performing RNAi. The first is the use of small interfering RNAs (siRNAs) that are chemically synthesized, and the second utilizes short-hairpin RNAs (shRNAs) encoded within plasmids 1. The latter can be transfected into cells directly or packaged into replication incompetent lentiviral particles. The main advantages of using lentiviral shRNAs is the ease of introduction into a wide variety of cell types, their ability to stably integrate into the genome for long term gene knockdown and selection, and their efficacy in conducting high-throughput loss of function screens. To facilitate this we have created the LentiPlex pooled shRNA library.
The MISSION LentiPlex Human shRNA Pooled Library is a genome-wide lentiviral pool produced using a proprietary process. The library consists of over 75,000 shRNA constructs from the TRC collection targeting 15,000+ human genes 2. Each library is tested for shRNA representation before product release to ensure robust library coverage. The library is provided in a ready-to-use lentiviral format at titers of at least 5 x 108 TU/ml via p24 assay and is pre-divided into ten subpools of approximately 8,000 shRNA constructs each. Amplification and sequencing primers are also provided for downstream target identification.
Previous studies established a synergistic antitumor activity of TRAIL when combined with Paclitaxel in A549 cells, a human lung carcinoma cell line 3, 4. In this study we demonstrate the application of a pooled LentiPlex shRNA library to rapidly conduct a positive selection screen for genes involved in the cytotoxicity of A549 cells when exposed to TRAIL and Paclitaxel. One barrier often encountered with high-throughput screens is the cost and difficulty in deconvolution; we also detail a cost-effective polyclonal approach utilizing traditional sequencing.

Here we use a human LentiPlex pooled library and traditional sequencing methods to identify gene targets promoting cell survival. We demonstrate how to set up and deconvolute a LentiPlex screen and validate the results.

LentiPlex MISSÃO Pooled shRNA Screening Biblioteca em células de mamíferos

RNA interference (RNAi) is an intrinsic cellular mechanism for the regulation of gene expression. Harnessing the innate power of this system enables us to ...

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. ...

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

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work.
Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized.
Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types.
To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.

Our Bayesian Change Point (BCP) algorithm builds on state-of-the-art advances in modeling change-points via Hidden Markov Models and applies them to chromatin immunoprecipitation sequencing (ChIPseq) data analysis. BCP performs well in both broad and punctate data types, but excels in accurately identifying robust, reproducible islands of diffuse histone enrichment.

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 ...

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 ...

Detection of miRNA Targets in High-throughput Using the 3'LIFE Assay

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an array of hundreds of queried 3&#8217;UTRs. Target identification is based on the dual-luciferase assay, which detects binding at the mRNA level by measuring translational output, giving a functional readout of miRNA targeting. 3&#8217;LIFE uses non-proprietary buffers and reagents, and publically available reporter libraries, making genome-wide screens feasible and cost-effective. 3&#8217;LIFE can be performed either in a standard lab setting or scaled up using liquid handling robots and other high-throughput instrumentation. We illustrate the approach using a dataset of human 3&#8217;UTRs cloned in 96-well plates, and two test miRNAs, let-7c and miR-10b. We demonstrate how to perform DNA preparation, transfection, cell culture and luciferase assays in 96-well format, and provide tools for data analysis. In conclusion 3&#39;LIFE is highly reproducible, rapid, systematic, and identifies high confidence targets.

Detection of miRNA Targets in High-throughput Using the 3&#039;LIFE Assay

Luminescent identification of functional elements in 3&#8217; untranslated regions (3&#8217;UTRs) (3&#8217;LIFE) is a technique to identify functional regulation in 3&#8217;UTRs by miRNAs or other regulatory factors. This protocol utilizes high-throughput methodology such as 96-well transfection and luciferase assays to screen hundreds of putative interactions for functional repression.

Detecção de alvos miRNA em métodos de alta capacidade utilizando o ensaio 3&#39;LIFE

Luminescent Identification of Functional Elements in 3&#8217;UTRs (3&#8217;LIFE) allows the rapid identification of targets of specific miRNAs within an ...

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 ...