Este trabalho foi financiado pelo Discovery das Crianças Instituto concessão MC-II-2006-1 (RDM e TED), o NIH Epigenetics Roteiro concessão [1R01DA025744-01 e 3R01DA025744-02S1] (RDM e FLMV), U01AG023746 (SC), o Saigh Foundation (FLMV e TED), 1K08CA140720-01A1 e Alex Lemonade Stand &quot;A&quot; apoio Award (TED). Agradecemos ao Centro do Genoma Acesso à Tecnologia do Departamento de Genética da Washington University School of Medicine de ajuda com a análise genômica. O Centro é parcialmente financiado pelo NCI Cancer Support Center Grant P30 CA91842 # para o Centro de Câncer Siteman e pela ICTS / CTSA Grant # UL1RR024992 do National Center for Research Resources (NCRR), um componente do National Institutes of Health (NIH), e NIH Roadmap for Medical Research. Esta publicação é da exclusiva responsabilidade dos autores e não representam necessariamente a posição oficial do NCRR ou NIH.

<ol>
	<li>Vallania, F. L. M., Druley, T. E., Ramos, E., Wang, J., Borecki, I., Province, M., Mitra, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+discovery+of+rare+insertions+and+deletions+in+large+cohorts.">High-throughput discovery of rare insertions and deletions in large cohorts.</a> Genome Research. 20, 1391-1397 (2010).</li><li>Shendure, J., Mitra, R., Varma, C., Church, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Advanced+Sequencing+Technologies:+Methods+and+Goals.">Advanced Sequencing Technologies: Methods and Goals.</a> Nature Reviews of Genetics. 5, 335-344 (2004).</li><li>The 1000 Genomes Project Consortium. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+map+of+human+genome+variation+from+population-scale+sequencing.">A map of human genome variation from population-scale sequencing.</a> Nature. 467, 1061-1073 (2010).</li><li>Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., McCarthy, M. I., Ramos, E. M., Cardon, L. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Finding+the+missing+heritability+of+complex+diseases.">Finding the missing heritability of complex diseases.</a> Nature. 461, 747-753 (2009).</li><li>Reich, D. E., Lander, E. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=On+the+allelic+spectrum+of+human+disease.">On the allelic spectrum of human disease.</a> Trends Genet. 17, 502-510 (2001).</li><li>Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., Hobbs, H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Multiple+rare+alleles+contribute+to+low+plasma+levels+of+HDL+cholesterol.">Multiple rare alleles contribute to low plasma levels of HDL cholesterol.</a> Science. 305, 869-872 (2004).</li><li>Ji, W., Foo, J. N., O'Roak, B. J., Zhao, H., Larson, M. G., Simon, D. B., Newton-Cheh, C., State, M. W., Levy, D., Lifton, R. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rare+independent+mutations+in+renal+salt+handling+genes+contribute+to+blood+pressure+variation.">Rare independent mutations in renal salt handling genes contribute to blood pressure variation.</a> Nat. Genet. 40, 592-599 (2008).</li><li>Ahituv, N., Kavaslar, N., Schackwitz, W., Ustaszewska, A., Martin, J., Hebert, S., Doelle, H., Ersoy, B., Kryukov, G., Schmidt, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Medical+sequencing+at+the+extremes+of+human+body+mass.">Medical sequencing at the extremes of human body mass.</a> Am. J. Hum. Genet. 80, 779-791 (2007).</li><li>Druley, T. E., Vallania, F. L., Wegner, D. J., Varley, K. E., Knowles, O. L., Bonds, J. A., Robison, S. W., Doniger, S. W., Hamvas, A., Cole, F. S., Fay, J. C., Mitra, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+rare+allelic+variants+from+pooled+genomic+DNA.">Quantification of rare allelic variants from pooled genomic DNA.</a> Nat. Methods. 6, 263-265 (2009).</li><li>Mitra, R. D., Butty, V., Shendure, J., Housman, D., Church, G. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Digital+Genotyping+and+Haplotyping+with+Polymerase+Colonies.">Digital Genotyping and Haplotyping with Polymerase Colonies.</a> Proc. Natl. Acad. Sci. 100, 5926-5931 (2003).</li></ol>

Não há conflitos de interesse declarados.

Existe uma evidência crescente que a incidência e resposta terapêutica de comuns, fenótipos complexos e doenças tais como a obesidade 8, hipercolesterolemia 4, hipertensão 7 e outros podem ser moderadas por perfis pessoais de variação rara. Identificar os genes e as vias onde essas variantes agregadas em populações afetadas terão profundas implicações diagnósticas e terapêuticas, mas analisando separadamente os indivíduos afetados pode ser o tempo e custo proibitivo. De base populacional análise oferece um método mais eficiente para o levantamento da variação genética em locos múltiplos. Apresentamos um novo reunidas DNA-protocolo sequenciação emparelhado com o pacote de software SPLINTER desenhados para identificar este tipo de variação genética através de populações. Demonstramos a precisão deste método na identificação e quantificação alelos menores dentro de uma grande população combinada de 947 indivíduos, incluindo as variantes raras que eramchamado de novo a partir da sequência reunidas e validado por pyrosequencing individual. A nossa estratégia principalmente difere de outros protocolos pela incorporação de um positivo e um controlo negativo dentro de cada experiência. Isso permite que SPLINTER para conseguir uma precisão muito maior e de energia em comparação com outras abordagens 1. A cobertura óptima de 25 vezes por alelo é fixado de forma independente do tamanho da piscina, tornando a análise de agrupamentos de grandes viável como este requisito apenas as escalas linearmente com o tamanho da piscina. A nossa abordagem é muito flexível e pode ser aplicado a qualquer fenótipo de interesse, mas também para amostras que são naturalmente heterogénea, tais como as populações de células mistas e biópsias de tumores. Dado o interesse cada vez maior na seqüência combinada de regiões-alvo de grande porte como o exome ou genoma, a nossa biblioteca de preparação e análise SPLINTER é compatível com o costume de captura e de todo o exome seqüenciamento, mas o utilitário de alinhamento no pacote SPLINTER não foi projetado para grandesequências de referências. Portanto, temos utilizado com sucesso o alinhador de programação dinâmica, Novoalign, para genome-wide alinhamentos seguido de variante ligando a amostra conjunta (Ramos et al., Submetido). Assim, nossa estratégia de seqüenciamento de pool pode escalar com sucesso para piscinas maiores, com quantidades crescentes de sequência alvo.

<table border="1"><tbody><tr><td> Nome do reagente </td><td> Companhia </td><td> Número de Catálogo </td><td> Seção </td></tr><tr><td> PfuUltra Alta Fidelidade </td><td> Agilent </td><td> 600384 </td><td> 1,4 </td></tr><tr><td> Betaína </td><td> SIGMA </td><td> B2629 </td><td> 1,4 </td></tr><tr><td> M13mp18 ssDNA vector </td><td> NEB </td><td> N4040S </td><td> 1,5 </td></tr><tr><td> pGEM-T Easy </td><td> Promega </td><td> A1360 </td><td> 1,5 </td></tr><tr><td> Quinase de polinucleótido T4 </td><td> NEB </td><td> M0201S </td><td> 2,2 </td></tr><tr><td> Ligase de T4 </td><td> NEB </td><td> M0202S </td><td> 2,2 </td></tr><tr><td> Polietileno Glicol 8000 MW </td><td> SIGMA </td><td> P5413 </td><td> 2,2 </td></tr><tr><td> Sonicador Bioruptor </td><td> Diagenode </td><td> UCD-200-TS</td><td> 2,3 </td></tr></tbody></table>

detection of rare genomic variants from pooled sequencing using splinter

Como tecnologia de seqüenciamento de DNA foi marcadamente avançou nos últimos anos 2, tornou-se cada vez mais evidente que a quantidade de variação genética entre dois indivíduos é maior do que se pensava anteriormente 3. Em contraste, uma matriz baseada em genotipagem falhou para identificar uma contribuição significativa de variantes da sequência de comuns para a variabilidade fenotípica de doença comum 4,5. Tomados em conjunto, essas observações levaram à evolução da doença comum / variante rara hipótese sugerindo que a maioria da &quot;herdabilidade perdido&quot; em fenótipos comuns e complexas, em vez disso, devido ao perfil pessoal de um indivíduo de variantes raras de DNA ou privada 6-8 . No entanto, caracterizando como rara variação impacta fenótipos complexos requer a análise de muitos indivíduos afetados em muitos loci genômicos, e está idealmente comparado a uma pesquisa similar em uma coorte afetados. Apesar do poder de sequenciação oferecida pelas plataformas de hoje, umainquérito de base populacional de loci genômicos muitos e posterior análise computacional requerido continua proibitivo para muitos investigadores. Para atender a essa necessidade, desenvolvemos uma abordagem conjunta seqüenciamento 1,9 e um pacote de software para a detecção de um romance variante de alta precisão rara a partir dos dados resultantes. A capacidade de genomas piscina de populações inteiras de indivíduos afetados e levantamento do grau de variação genética em várias regiões-alvo em uma biblioteca de sequenciamento único proporciona excelentes economias em custo e tempo com a metodologia tradicional seqüenciamento amostra única. Com uma cobertura média por sequenciação do alelo de 25 vezes, o algoritmo personalizado, lasca, utiliza uma variante interna estratégia de controlo de chamada para chamar inserções, deleções e substituições até quatro pares de bases de comprimento, com elevada sensibilidade e especificidade de pools de até 1 alelo mutante em 500 indivíduos. Descrevemos aqui o método para a preparação do s reunidasequencing biblioteca seguido passo-a-passo sobre como usar o pacote SPLINTER para análise da sequenciação agrupada ( <a href="http://www.ibridgenetwork.org/wustl/splinter" target="_blank">http://www.ibridgenetwork.org/wustl/splinter</a> ). Nós mostramos uma comparação entre sequenciamento combinada de 947 indivíduos, os quais também foram submetidos genome-wide array, em mais de 20kb de seqüenciamento por pessoa. Concordância entre genotipagem de marcado e novas variantes chamadas na amostra composta foram excelentes. Este método pode ser facilmente dimensionada para qualquer número de loci genómicas e qualquer número de indivíduos. Ao incorporar os controles internos amplicon positivos e negativos em proporções que imitam a população em estudo, o algoritmo pode ser calibrado para um ótimo desempenho. Esta estratégia pode também ser modificados para utilização com captura de hibridação ou indivíduo específicos códigos de barras e pode ser aplicado para a sequenciação de amostras naturalmente heterogéneos, tais como o DNA do tumor.

Watch this Scientific Journal Video about Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER at JoVE.com

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Seqüenciamento de DNA pool é uma estratégia rápida e de custo eficaz para detectar variantes raras associadas com fenótipos complexos em grandes grupos. Aqui descrevemos a análise computacional de pool, o seqüenciamento da próxima geração de 32 genes relacionados ao câncer, utilizando o pacote de software SPLINTER. Este método é escalável, e aplicável a qualquer fenótipo de interesse.

Detecção de variantes raras genômico de Seqüenciamento combinados usando SPLINTER

As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any ...

detection-rare-genomic-variants-from-pooled-sequencing-using

Research

JoVE Journal

Biology

15.0K visualizações.  Washington University School of Medicine. Seqüenciamento de DNA pool é uma estratégia rápida e de custo eficaz para detectar variantes raras associadas com fenótipos complexos em grandes grupos. Aqui descrevemos a análise computacional de pool, o seqüenciamento da próxima geração de 32 genes relacionados ao câncer, utilizando o pacote de software SPLINTER. Este método é escalável, e aplicável a qualquer fenótipo de interesse.

Vídeo: Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Isolation of Genomic DNA from Mouse Tails

Isolamento de DNA genômico de Tails rato

Biologia

Extraction of High Molecular Weight Genomic DNA from Soils and Sediments

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with nutrient and energy flow within terrestrial ecosystems. Cultivation-independent environmental genomic, also known as metagenomic, approaches promise unprecedented access to this genetic information with respect to pathway reconstruction and functional screening for high value therapeutic and biomass conversion processes. However, the soil microbiome still remains a challenge largely due to the difficulty in obtaining high molecular weight DNA of sufficient quality for large insert library production. Here we introduce a protocol for extracting high molecular weight, microbial community genomic DNA from soils and sediments. The quality of isolated genomic DNA is ideal for constructing large insert environmental genomic libraries for downstream sequencing and screening applications. 
The procedure starts with cell lysis. Cell walls and membranes of microbes are lysed by both mechanical (grinding) and chemical forces (&beta;-mercaptoethanol). Genomic DNA is then isolated using extraction buffer, chloroform-isoamyl alcohol and isopropyl alcohol. The buffers employed for the lysis and extraction steps include guanidine isothiocyanate and hexadecyltrimethylammonium bromide (CTAB) to preserve the integrity of the high molecular weight genomic DNA. Depending on your downstream application, the isolated genomic DNA can be further purified using cesium chloride (CsCl) gradient ultracentrifugation, which reduces impurities including humic acids. The first procedure, extraction, takes approximately 8 hours, excluding DNA quantification step. The CsCl gradient ultracentrifugation, is a two days process. During the entire procedure, genomic DNA should be treated gently to prevent shearing, avoid severe vortexing, and repetitive harsh pipetting.

A methodology to isolate high molecular weight and high quality genomic DNA from soil microbial community is described.

Extração de DNA genômico de alto peso molecular de solos e sedimentos

The soil microbiome is a vast and relatively unexplored reservoir of genomic diversity and metabolic innovation that is intimately associated with ...

Competitive Genomic Screens of Barcoded Yeast Libraries

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment.

We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

Competitiva Screens Genomic de Bibliotecas Yeast Barcoded

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

Selective Capture of 5-hydroxymethylcytosine from Genomic DNA

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene expression, maintenance of genome integrity, parental imprinting, X-chromosome inactivation, regulation of development, aging, and cancer1. Recently, the presence of an oxidized 5-mC, 5-hydroxymethylcytosine (5-hmC), was discovered in mammalian cells, in particular in embryonic stem (ES) cells and neuronal cells2-4. 5-hmC is generated by oxidation of 5-mC catalyzed by TET family iron (II)/&alpha;-ketoglutarate-dependent dioxygenases2, 3. 5-hmC is proposed to be involved in the maintenance of embryonic stem (mES) cell, normal hematopoiesis and malignancies, and zygote development2, 5-10. To better understand the function of 5-hmC, a reliable and straightforward sequencing system is essential. Traditional bisulfite sequencing cannot distinguish 5-hmC from 5-mC11. To unravel the biology of 5-hmC, we have developed a highly efficient and selective chemical approach to label and capture 5-hmC, taking advantage of a bacteriophage enzyme that adds a glucose moiety to 5-hmC specifically12.
Here we describe a straightforward two-step procedure for selective chemical labeling of 5-hmC. In the first labeling step, 5-hmC in genomic DNA is labeled with a 6-azide-glucose catalyzed by &beta;-GT, a glucosyltransferase from T4 bacteriophage, in a way that transfers the 6-azide-glucose to 5-hmC from the modified cofactor, UDP-6-N3-Glc (6-N3UDPG). In the second step, biotinylation, a disulfide biotin linker is attached to the azide group by click chemistry. Both steps are highly specific and efficient, leading to complete labeling regardless of the abundance of 5-hmC in genomic regions and giving extremely low background. Following biotinylation of 5-hmC, the 5-hmC-containing DNA fragments are then selectively captured using streptavidin beads in a density-independent manner. The resulting 5-hmC-enriched DNA fragments could be used for downstream analyses, including next-generation sequencing.
Our selective labeling and capture protocol confers high sensitivity, applicable to any source of genomic DNA with variable/diverse 5-hmC abundances. Although the main purpose of this protocol is its downstream application (i.e., next-generation sequencing to map out the 5-hmC distribution in genome), it is compatible with single-molecule, real-time SMRT (DNA) sequencing, which is capable of delivering single-base resolution sequencing of 5-hmC.

Described is a two-step labeling process using &beta;-glucosyltransferase (&beta;-GT) to transfer an azide-glucose to 5-hmC, followed by click chemistry to transfer a biotin linker for easy and density-independent enrichment. This efficient and specific labeling method enables enrichment of 5-hmC with extremely low background and high-throughput epigenomic mapping via next-generation sequencing.

Captura selectivo de 5-hydroxymethylcytosine a partir de DNA genómico

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene ...

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a clinical diagnostic service laboratory. DNA extracted from a patient&#8217;s sample (blood, saliva or other tissue types) is labeled with a fluorochrome (either cyanine 5 or cyanine 3). A reference DNA sample is labeled with the opposite fluorochrome. There follows a cleanup step to remove unincorporated nucleotides before the labeled DNAs are mixed and resuspended in a hybridization buffer and applied to an array comprising ~60,000 oligonucleotide probes from loci across the genome, with high probe density in clinically important areas. Following hybridization, the arrays are washed, then scanned and the resulting images are analyzed to measure the red and green fluorescence for each probe. Software is used to assess the quality of each probe measurement, calculate the ratio of red to green fluorescence and detect potential copy number variants.

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a diagnostic service laboratory.

Matriz Hibridização Genômica Comparativa (Array CGH) para a detecção de Genomic copiar o número de variantes

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its ...

Isolating Potentiated Hsp104 Variants Using Yeast Proteinopathy Models

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic lateral sclerosis, and &#945;-synuclein, implicated in Parkinson&#8217;s disease, are toxic and form cytoplasmic aggregates in yeast. These features recapitulate protein pathologies observed in patients with these disorders. Thus, yeast are an ideal platform for isolating toxicity suppressors from libraries of protein variants. We are interested in applying protein disaggregases to eliminate misfolded toxic protein conformers. Specifically, we are engineering Hsp104, a hexameric AAA+ protein from yeast that is uniquely capable of solubilizing both disordered aggregates and amyloid and returning the proteins to their native conformations. While Hsp104 is highly conserved in eukaryotes and eubacteria, it has no known metazoan homologue. Hsp104 has only limited ability to eliminate disordered aggregates and amyloid fibers implicated in human disease. Thus, we aim to engineer Hsp104 variants to reverse the protein misfolding implicated in neurodegenerative disorders. We have developed methods to screen large libraries of Hsp104 variants for suppression of proteotoxicity in yeast. As yeast are prone to spontaneous nonspecific suppression of toxicity, a two-step screening process has been developed to eliminate false positives. Using these methods, we have identified a series of potentiated Hsp104 variants that potently suppress the toxicity and aggregation of TDP-43, FUS, and &#945;-synuclein. Here, we describe this optimized protocol, which could be adapted to screen libraries constructed using any protein backbone for suppression of toxicity of any protein that is toxic in yeast.

Yeast proteinopathy models are valuable tools to assess the toxicity and aggregation of proteins implicated in disease. Here, we present methods for screening Hsp104 variant libraries for toxicity suppressors. This protocol could be adapted to screen any protein library for toxicity suppressors of any protein that is toxic in yeast.

Isolando potencializado Hsp104 variantes usando levedura Proteinopathy Models

Many protein-misfolding disorders can be modeled in the budding yeast Saccharomyces cerevisiae. Proteins such as TDP-43 and FUS, implicated in amyotrophic ...

TRAP-rc, Translating Ribosome Affinity Purification from Rare Cell Populations of Drosophila Embryos

Measuring levels of mRNAs in the process of translation in individual cells provides information on the proteins involved in cellular functions at a given point in time. The protocol dubbed Translating Ribosome Affinity Purification (TRAP) is able to capture this mRNA translation process in a cell-type-specific manner. Based on the affinity purification of polysomes carrying a tagged ribosomal subunit, TRAP can be applied to translatome analyses in individual cells, making it possible to compare cell types during the course of developmental processes or to track disease development progress and the impact of potential therapies at molecular level. Here we report an optimized version of the TRAP protocol, called TRAP-rc (rare cells), dedicated to identifying engaged-in-translation RNAs from rare cell populations. TRAP-rc was validated using the Gal4/UAS targeting system in a restricted population of muscle cells in Drosophila embryos. This novel protocol allows the recovery of cell-type-specific RNA in sufficient quantities for global gene expression analytics such as microarrays or RNA-seq. The robustness of the protocol and the large collections of Gal4 drivers make TRAP-rc a highly versatile approach with potential applications in cell-specific genome-wide studies.

TRAP-rc, Translating Ribosome Affinity Purification from Rare Cell Populations of Drosophila Embryos

Translating Ribosome Affinity Purification (TRAP) is able to capture cell-type-specific translation of mRNA. Here we report the first TRAP protocol dedicated to isolation of mRNA in rare cell populations of Drosophila embryos.

TRAP-rc, Traduzindo Ribossomo Affinity Purificação de populações de células raras<em&gt; Drosophila</em&gt; Os embriões

Measuring levels of mRNAs in the process of translation in individual cells provides information on the proteins involved in cellular functions at a given ...

Amplification, Next-generation Sequencing, and Genomic DNA Mapping of Retroviral Integration Sites

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of diverse libraries of retroviral integration sites using ligation-mediated PCR (LM-PCR) amplification and next-generation sequencing (NGS), (2) mapping the genomic location of each virus-host junction using BEDTools, and (3) analyzing the data for statistical relevance. Genomic DNA extracted from infected cells is fragmented by digestion with restriction enzymes or by sonication. After suitable DNA end-repair, double-stranded linkers are ligated onto the DNA ends, and semi-nested PCR is conducted using primers complementary to both the long terminal repeat (LTR) end of the virus and the ligated linker DNA. The PCR primers carry sequences required for DNA clustering during NGS, negating the requirement for separate adapter ligation. Quality control (QC) is conducted to assess DNA fragment size distribution and adapter DNA incorporation prior to NGS. Sequence output files are filtered for LTR-containing reads, and the sequences defining the LTR and the linker are cropped away. Trimmed host cell sequences are mapped to a reference genome using BLAT and are filtered for minimally 97% identity to a unique point in the reference genome. Unique integration sites are scrutinized for adjacent nucleotide (nt) sequence and distribution relative to various genomic features. Using this protocol, integration site libraries of high complexity can be constructed from genomic DNA in three days. The entire protocol that encompasses exogenous viral infection of susceptible tissue culture cells to integration site analysis can therefore be conducted in approximately one to two weeks. Recent applications of this technology pertain to longitudinal analysis of integration sites from HIV-infected patients.

We describe a protocol for amplifying retroviral integration sites from the genomic DNA of infected cells, sequencing the amplified virus-host junctions, and then mapping these sequences to a reference genome. We also describe techniques to quantify the distribution of integration sites relative to various genomic annotations using BEDTools.

Amplificação, sequenciamento de próxima geração, e Genomic DNA Mapeamento das retrovirais Integração Sites

Retroviruses exhibit signature integration preferences on both the local and global scales. Here, we present a detailed protocol for (1) generation of ...

Targeted RNA Sequencing Assay to Characterize Gene Expression and Genomic Alterations

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding RNAs. Standard RNAseq requires 30 - 100 million sequencing reads and can include multiple RNA products such as mRNA and noncoding RNAs. We demonstrate how targeted RNAseq (capture) permits a focused study on selected RNA products using a desktop sequencer. RNAseq capture can characterize unannotated, low, or transiently expressed transcripts that may otherwise be missed using traditional RNAseq methods. Here we describe the extraction of RNA from cell lines, ribosomal RNA depletion, cDNA synthesis, preparation of barcoded libraries, hybridization and capture of targeted transcripts and multiplex sequencing on a desktop sequencer. We also outline the computational analysis pipeline, which includes quality control assessment, alignment, fusion detection, gene expression quantification and identification of single nucleotide variants. This assay allows for targeted transcript sequencing to characterize gene expression, gene fusions, and mutations.

We describe a targeted RNA sequencing-based method that includes preparation of indexed cDNA libraries, hybridization and capture with custom probes and data analysis to interrogate selected transcripts for gene expression, mutations, and gene fusions. Targeted RNAseq permits cost-effective, rapid evaluation of selected transcripts on a desktop sequencer.

Targeted RNA Sequenciação Ensaio para Caracterizar expressão gênica e genômica Alterações

RNA sequencing (RNAseq) is a versatile method that can be utilized to detect and characterize gene expression, mutations, gene fusions, and noncoding ...

Genome Engineering of Primary Human B Cells Using CRISPR/Cas9

B cells are lymphocytes derived from hematopoietic stem cells and are a key component of the humoral arm of the adaptive immune system. They make attractive candidates for cell-based therapies because of their ease of isolation from peripheral blood, their ability to expand in vitro, and their longevity in vivo. Additionally, their normal biological function&#8212;to produce large amounts of antibodies&#8212;can be utilized to express very large amounts of a therapeutic protein, such as a recombinant antibody to fight infection, or an enzyme for the treatment of enzymopathies. Here, we provide detailed methods for isolating primary human B cells from peripheral blood mononuclear cells (PBMCs) and activating/expanding isolated B cells in vitro. We then demonstrate the steps involved in using the CRISPR/Cas9 system for site-specific KO of endogenous genes in B cells. This method allows for efficient KO of various genes, which can be used to study the biological functions of genes of interest. We then demonstrate the steps for using the CRISPR/Cas9 system together with a recombinant, adeno-associated, viral (rAAV) vector for efficient site-specific integration of a transgene expression cassette in B cells. Together, this protocol provides a step-by-step engineering platform that can be used in primary human B cells to study biological functions of genes as well as for the development of B-cell therapeutics.

Here we provide a detailed, step-by-step protocol for CRISPR/Cas9-based genome engineering of primary human B cells for gene knockout (KO) and knock-in (KI) to study biological functions of genes in B cells and the development of B-cell therapeutics.