Questo lavoro è stato supportato da Discovery dei bambini dell&#39;Istituto concessione MC-II-2006-1 (RDM e TED), il NIH Epigenetica Roadmap sovvenzione [1R01DA025744-01 e 3R01DA025744-02S1] (RDM e FLMV), U01AG023746 (SC), il Saigh Foundation (FLMV e TED), 1K08CA140720-01A1 e Lemonade stand di Alex &quot;A&quot; di supporto Award (TED). Ringraziamo il Genome Technology Center di accesso presso il Dipartimento di Genetica presso la Washington University School of Medicine di aiuto con l&#39;analisi genomica. Il Centro è parzialmente supportato dal Servizio Supporto NCI di Grant Cancer Center # P30 CA91842 al Cancer Center Siteman e ICTS / CTSA Grant N. UL1RR024992 dal NationalCenter per le Risorse Ricerca (NCRR), un componente del National Institutes of Health (NIH), e NIH Roadmap for Medical Research. Questa pubblicazione è di esclusiva responsabilità degli autori e non rappresentano necessariamente l&#39;opinione ufficiale di NCRR o 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>

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C&#39;è una crescente evidenza che l&#39;incidenza e la risposta terapeutica dei comuni fenotipi complessi e le malattie come l&#39;obesità 8, 4 ipercolesterolemia, ipertensione 7 e altri possono essere moderato da profili personali di variazione rare. Identificare i geni e le vie in cui queste varianti aggregati in popolazioni colpite avranno profonde implicazioni diagnostiche e terapeutiche, ma analizzando separatamente gli individui affetti possono essere tempi e costi proibitivi. Basato sulla popolazione analisi offre un metodo più efficiente per la rilevazione variazione genetica a loci multipli. Vi presentiamo un nuovo pool-protocollo di sequenziamento del DNA in coppia con il pacchetto software SPLINTER progettato per identificare questo tipo di variazione genetica nelle popolazioni. Dimostriamo l&#39;accuratezza di questo metodo per identificare e quantificare gli alleli minori all&#39;interno di una vasta popolazione aggregata di 947 persone, incluse le varianti rare che eranochiamato de novo dal sequenziamento pool e convalidati da pirosequenziamento individuale. La strategia differisce principalmente da altri protocolli per l&#39;incorporazione di un controllo positivo e uno negativo in ogni esperimento. Questo permette SPLINTER di ottenere una precisione molto più elevata e potenza rispetto ad altre soluzioni 1. La copertura ottimale di 25-volte per allele è fissata indipendentemente dalla dimensione della piscina, rendendo l&#39;analisi di grandi vasche fattibile questo requisito solo bilance linearmente con la dimensione del pool. Il nostro approccio è molto flessibile e può essere applicato a qualsiasi fenotipo di interesse, ma anche a campioni che sono naturalmente eterogenei, come le popolazioni di cellule miste e biopsie tumorali. Dato il crescente interesse per la sequenza in pool dalle regioni di destinazione di grandi dimensioni come il exome o genoma, la nostra preparazione biblioteca e l&#39;analisi SPLINTER è compatibile con i costumi-capture e con tutto il exome sequenziamento, ma l&#39;utilità di allineamento nel pacchetto SPLINTER non è stato progettato per granderiferimenti sequenze. Pertanto, abbiamo utilizzato con successo la mascherina di programmazione dinamica, Novoalign, per genome-wide allineamenti seguiti da variante chiamando dal campione composito (Ramos et al., Ha presentato). Quindi, la nostra strategia di sequenziamento pool in grado di scalare con successo per piscine di grandi dimensioni con quantità crescenti di sequenza bersaglio.

<table border="1"><tbody><tr><td> Reagente Nome </td><td> Azienda </td><td> Numero di catalogo </td><td> Sezione </td></tr><tr><td> PfuUltra High-Fidelity </td><td> Agilent </td><td> 600384 </td><td> 1,4 </td></tr><tr><td> Betaina </td><td> SIGMA </td><td> B2629 </td><td> 1,4 </td></tr><tr><td> M13mp18 ssDNA vettore </td><td> NEB </td><td> N4040S </td><td> 1,5 </td></tr><tr><td> pGEM-T facile </td><td> Promega </td><td> A1360 </td><td> 1,5 </td></tr><tr><td> Polinucleotide chinasi T4 </td><td> NEB </td><td> M0201S </td><td> 2,2 </td></tr><tr><td> Ligasi T4 </td><td> NEB </td><td> M0202S </td><td> 2,2 </td></tr><tr><td> Polietilene glicole 8000 MW </td><td> SIGMA </td><td> P5413 </td><td> 2,2 </td></tr><tr><td> Bioruptor ultrasuoni </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

Come tecnologia di sequenziamento del DNA è nettamente avanti negli ultimi anni 2, è diventato sempre più evidente che la quantità di variazione genetica tra due individui è maggiore di quanto si pensasse 3. Al contrario, array-based genotipizzazione non è riuscito a identificare un contributo significativo di varianti di sequenza comuni per la variabilità fenotipica di malattia comune 4,5. Prese insieme, queste osservazioni hanno portato alla evoluzione della malattia comune / ipotesi Variant Rare suggerendo che la maggioranza dei &quot;ereditabilità mancante&quot; in fenotipi comuni e complesso è invece dovuta al profilo personale di un individuo di varianti di DNA rare o private 6-8 . Tuttavia, caratterizzando come la variazione raro impatto fenotipi complessi richiede l&#39;analisi di molti individui affetti in molti loci genomici, ed è idealmente rispetto a un&#39;indagine simile in una coorte inalterato. Nonostante la potenza sequenza offerto dalle piattaforme di oggi,basato sulla popolazione sondaggio di molti loci genomici e la successiva analisi computazionale richiesto rimane proibitivo per molti ricercatori. Per rispondere a questa esigenza, abbiamo sviluppato un approccio di sequenziamento pool 1,9 e un pacchetto software nuovo 1 per il rilevamento ad alta precisione rara variante dai dati risultanti. La capacità di genomi piscina da intere popolazioni di individui interessati e di indagine il grado di variazione genetica a più aree mirate in una libreria sequenza unica, offre ottimi risparmi sui costi e il tempo alla tradizionale single-campione metodologia di sequenziamento. Con una copertura di sequenziamento per allele media di 25 volte, il nostro algoritmo personalizzato, SPLINTER, utilizza una strategia di controllo interno variante chiamata per chiamare inserimenti, cancellazioni e sostituzioni fino a quattro paia di basi di lunghezza con alta sensibilità e specificità da pool di fino a 1 allele mutante in 500 individui. Qui si descrive il metodo per preparare il pool sequencing biblioteca seguita passo-passo le istruzioni su come usare il pacchetto per l&#39;analisi di sequenziamento SPLINTER aggregati ( <a href="http://www.ibridgenetwork.org/wustl/splinter" target="_blank">http://www.ibridgenetwork.org/wustl/splinter</a> ). Mostriamo un confronto tra sequenziamento pool di 947 individui, ognuno dei quali sono stati sottoposti a genome-wide array, a più di 20kb di sequenziamento a persona. Concordanza tra genotipizzazione di tag e varianti romanzo intitolato nel campione pool erano eccellenti. Questo metodo può essere facilmente scalabile a qualsiasi numero di loci genomici e qualsiasi numero di individui. Con l&#39;integrazione dei controlli interni ampliconi positivi e negativi a rapporti che imitano la popolazione in studio, l&#39;algoritmo può essere calibrato per ottenere prestazioni ottimali. Questa strategia può anche essere modificato per l&#39;utilizzo con la cattura ibridazione o individuale-specifici codici a barre e può essere applicato alla sequenza di campioni naturalmente eterogenei, come il DNA tumorale.

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

Sequenziamento del DNA pool è una strategia rapida ed efficace per individuare le varianti rare associate a fenotipi complessi in coorti di grandi dimensioni. Qui si descrive l&#39;analisi computazionale del pool, sequenziamento di prossima generazione di 32 geni legati al cancro utilizzando il pacchetto software SPLINTER. Questo metodo è scalabile, e applicabile a qualsiasi fenotipo di interesse.

Rilevamento di Rare varianti genomiche da Sequencing pool Uso 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

Nanyang Technological University

Research

JoVE Journal

Biology

15.1K Views.  Washington University School of Medicine. Sequenziamento del DNA pool è una strategia rapida ed efficace per individuare le varianti rare associate a fenotipi complessi in coorti di grandi dimensioni. Qui si descrive l'analisi computazionale del pool, sequenziamento di prossima generazione di 32 geni legati al cancro utilizzando il pacchetto software SPLINTER. Questo metodo è scalabile, e applicabile a qualsiasi fenotipo di interesse.

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

Isolation of Genomic DNA from Mouse Tails

Isolamento del DNA genomico da Tails mouse

Ricerca

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.

Estrazione di DNA ad alta peso molecolare genomico da terreni e sedimenti

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

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova &amp; Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al. 2009).
Here we demonstrate a freely available Internet resource -- the Genomic MRI program package -- designed for computational analysis of genomic sequences in order to find and characterize various MRI patterns within them (Bechtel et al. 2008). This package also allows generation of randomized sequences with various properties and level of correspondence to the natural input DNA sequences. The main goal of this resource is to facilitate examination of vast regions of non-coding DNA that are still scarcely investigated and await thorough exploration and recognition.

We present a public computational web site for the analysis of genomic sequences. It detects DNA sequence patterns with various non-random nucleotide compositions. This resource also generates randomized sequences with diverse levels of complexity.

Genomica risonanza magnetica - una risorsa pubblica per lo Studio Patterns sequenza all&#39;interno del DNA genomico

Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in ...

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.

Schermi competitivo genomica delle Biblioteche di lievito con codice a barre

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

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Studies using the Saccharomyces cerevisiae aging model have uncovered life span regulatory pathways that are partially conserved in higher eukaryotes1-2. The simplicity and power of the yeast aging model can also be explored to study DNA damage and genome maintenance as well as their contributions to diseases during aging. Here, we describe a system to study age-dependent DNA mutations, including base substitutions, frame-shift mutations, gross chromosomal rearrangements, and homologous/homeologous recombination, as well as nuclear DNA repair activity by combining the yeast chronological life span with simple DNA damage and mutation assays. The methods described here should facilitate the identification of genes/pathways that regulate genomic instability and the mechanisms that underlie age-dependent DNA mutations and cancer in mammals.

Studying Age-dependent Genomic Instability using the S. cerevisiae Chronological Lifespan Model

Here we describe a set of DNA mutation assays that can be combined with the yeast chronological life span model to study the genes/pathways that regulate or contribute to genomic DNA instability during aging.

Studiare età-dipendente instabilità genomica utilizzando il S. Saccharomyces Modello Durata cronologica

Studies using the Saccharomyces cerevisiae aging model have uncovered life span regulatory pathways that are partially conserved in higher eukaryotes1-2. ...

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.

Cattura selettiva di 5 hydroxymethylcytosine dal DNA genomico

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.

Array Comparative Genomic Hybridization (CGH Array) per il rilevamento di Genomic Copy Number Varianti

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.

L&#39;isolamento potenziato Hsp104 Varianti Utilizzando lievito Proteinopathy modelle

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

Evaluation of Zebrafish Kidney Function Using a Fluorescent Clearance Assay

The zebrafish embryo offers a tractable model to study organogenesis and model human genetic disease. Despite its relative simplicity, the zebrafish kidney develops and functions in almost the same way as humans. A major difference in the construction of the human kidney is the presence of millions of nephrons compared to the zebrafish that has only two. However, simplifying such a complex system into basic functional units has aided our understanding of how the kidney develops and operates. In zebrafish, the midline located glomerulus is responsible for the initial blood filtration into two pronephric tubules that diverge to run bilaterally down the embryonic axis before fusing to each other at the cloaca. The pronephric tubules are heavily populated by motile cilia that facilitate the movement of filtrate along the segmented tubule, allowing the exchange of various solutes before finally exiting via the cloaca2-4. Many genes responsible for CKD, including those related to ciliogenesis, have been studied in zebrafish5. However, a major draw back has been the difficulty in evaluating zebrafish kidney function after genetic manipulation. Traditional assays to measure kidney dysfunction in humans have proved non translational to zebrafish, mainly due to their aquatic environment and small size. For example, it is not physically possible to extract blood from embryonic staged fish for analysis of urea and creatinine content, as they are too small. In addition, zebrafish do not produce enough urine for testing on a simple proteinuria &#8216;dipstick&#8217;, which is often performed during initial patient examinations. We describe a fluorescent assay that utilizes the optical transparency of the zebrafish to quantitatively monitor the clearance of a fluorescent dye, over time, from the vasculature and out through the kidney, to give a read out of renal function1,6-9.

The zebrafish is a popular tool to model chronic kidney disease (CKD). However, their small size makes it impossible to evaluate renal function using traditional methods. We describe a fluorescent dye kidney clearance assay1 that allows quantitative analysis of zebrafish kidney function in CKD.

Valutazione del rene Zebrafish Funzione Con un test Clearance fluorescente

The zebrafish embryo offers a tractable model to study organogenesis and model human genetic disease. Despite its relative simplicity, the zebrafish ...

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, Translating Ribosome Affinity Purification da popolazioni di cellule rare<em&gt; Drosophila</em&gt; Embrioni

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