Name: comprehensive workflow for the genome-wide identification and expression meta-analysis of the atl e3 ubiquitin ligase gene family in grapevine
Uploaded: 2017-12-22T12:30:00
Description: Watch this Scientific Journal Video about Comprehensive Workflow for the Genome-wide Identification and Expression Meta-analysis of the ATL E3 Ubiquitin Ligase Gene Family in Grapevine at JoVE.com

The work was supported by the University of Verona within the frame of Joint Project 2014 (Characterization of the ATL gene family in grapevine and of its involvement in resistance to Plasmopara viticola).

1. Identification of Putative ATL Gene Family Member(s)
<ol>
	<li>PSI-BLAST web version
	<ol>
		<li>Open the BLAST web page13 and click on the protein BLAST section.</li>
		<li>In the &#34;Enter Query sequence&#34; field, enter the amino acid sequence of the protein (here VIT_05s0077g01970) that will be used as the probe to identify the other family members. 
		NOTE: A good representative protein should be used (a protein displaying all the important features that character...

<ol>
	<li>Jaillon, O., 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+grapevine+genome+sequence+suggests+ancestral+hexaploidization+in+major+angiosperm+phyla.">The grapevine genome sequence suggests ancestral hexaploidization in major angiosperm phyla.</a> Nature. 449 (7161), 463-467 (2007).</li><li>Adam-Blondon, A. -. 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=.">.</a> Genetics, Genomics, and Breeding of Grapes. , 211-234 (2011).</li><li>Chen, L., Hellmann, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Plant+E3+Ligases:+Flexible+Enzymes+in+a+Sessile+World.">Plant E3 Ligases: Flexible Enzymes in a Sessile World.</a> Mol. Plant. 6 (5), 1388-1404 (2013).</li><li>Vierstra, 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=The+ubiquitin-26S+proteasome+system+at+the+nexus+of+plant+biology.">The ubiquitin-26S proteasome system at the nexus of plant biology.</a> Nat. Rev. Mol. Cell Biol. 10 (6), 385-397 (2009).</li><li>Serrano, M., Parra, S., Alcaraz, L. D., Guzm&#225;n, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+ATL+Gene+Family+from+Arabidopsis+thaliana+and+Oryza+sativa+Comprises+a+Large+Number+of+Putative+Ubiquitin+Ligases+of+the+RING-H2+Type.">The ATL Gene Family from Arabidopsis thaliana and Oryza sativa Comprises a Large Number of Putative Ubiquitin Ligases of the RING-H2 Type.</a> J. Mol. Evol. 62 (4), 434-445 (2006).</li><li>Aguilar-Hern&#225;ndez, V., Aguilar-Henonin, L., Guzm&#225;n, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Diversity+in+the+Architecture+of+ATLs,+a+Family+of+Plant+Ubiquitin-Ligases,+Leads+to+Recognition+and+Targeting+of+Substrates+in+Different+Cellular+Environments.">Diversity in the Architecture of ATLs, a Family of Plant Ubiquitin-Ligases, Leads to Recognition and Targeting of Substrates in Different Cellular Environments.</a> PLoS One. 6 (8), e23934 (2011).</li><li>Guzm&#225;n, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+prolific+ATL+family+of+RING-H2+ubiquitin+ligases.">The prolific ATL family of RING-H2 ubiquitin ligases.</a> Plant Signal Behav. 7 (8), 1014-1021 (2012).</li><li>Grimplet, J., 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+grapevine+gene+nomenclature+system.">The grapevine gene nomenclature system.</a> BMC Genomics. 15, 1077 (2014).</li><li>Prince, V. E., Pickett, F. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Splitting+pairs:+the+diverging+fates+of+duplicated+genes.">Splitting pairs: the diverging fates of duplicated genes.</a> Nat. Rev. Genet. 3 (11), 827-837 (2002).</li><li>Magadum, S., Nerjee, U., Murugan, P., Gangapur, D., Ravikesavan, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+duplication+as+a+major+force+in+evolution.">Gene duplication as a major force in evolution.</a> J. Gen. 92 (1), 155-161 (2013).</li><li>Wang, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Patterns+of+Gene+Duplication+and+Their+Contribution+to+Expansion+of+Gene+Families+in+Grapevine.">Patterns of Gene Duplication and Their Contribution to Expansion of Gene Families in Grapevine.</a> Plant Mol. Biol. Rep. 31 (4), 852-861 (2013).</li><li>Fasoli, 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+Grapevine+Expression+Atlas+Reveals+a+Deep+Transcriptome+Shift+Driving+the+Entire+Plant+into+a+Maturation+Program.">The Grapevine Expression Atlas Reveals a Deep Transcriptome Shift Driving the Entire Plant into a Maturation Program.</a> Plant Cell. 24 (9), 3489-3505 (2012).</li><li>. BLAST2.6.0 Available from: <a target="_blank" href="https://blast.ncbi.nlm.nih.gov/Blast.cgi">https://blast.ncbi.nlm.nih.gov/Blast.cgi</a> (2016)</li><li>. Vitis vinifera cv. Corvina gene expression Atlas Available from: <a target="_blank" href="https://www.researchgate.net/publication/273383414_54sample_datamatrix_geneIDs_Fasoli2012">https://www.researchgate.net/publication/273383414_54sample_datamatrix_geneIDs_Fasoli2012</a> (2015)</li><li>. Sequence Read Archive (SRA) Available from: <a target="_blank" href="https://www.ncbi.nlm.nih.gov/sra">https://www.ncbi.nlm.nih.gov/sra</a> (2017)</li><li>Bolger, A. M., Lohse, M., Usadel, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trimmomatic:+a+flexible+trimmer+for+Illumina+sequence+data.">Trimmomatic: a flexible trimmer for Illumina sequence data.</a> Bioinformatics. 30 (15), 2114-2120 (2014).</li><li>Langmead, B., Salzberg, S. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+gapped-read+alignment+with+Bowtie+2.">Fast gapped-read alignment with Bowtie 2.</a> Nat Meth. 9 (4), 357-359 (2012).</li><li>Anders, S., Pyl, P. T., Huber, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HTSeq-a+Python+framework+to+work+with+high-throughput+sequencing+data.">HTSeq-a Python framework to work with high-throughput sequencing data.</a> Bioinformatics. 31 (2), 166-169 (2015).</li><li>. Version 3.4.1 Available from: <a target="_blank" href="https://www.r-project.org/">https://www.r-project.org/</a> (2017)</li><li>Ritchie, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=limma+powers+differential+expression+analyses+for+RNA-sequencing+and+microarray+studies.">limma powers differential expression analyses for RNA-sequencing and microarray studies.</a> Nucleic Acids Res. 43 (7), e47 (2015).</li><li>Love, M. I., Huber, W., Anders, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Moderated+estimation+of+fold+change+and+dispersion+for+RNA-seq+data+with+DESeq2.">Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.</a> Genome Biology. 15 (12), 550 (2014).</li><li>Ariani, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+characterisation+and+expression+profile+of+the+grapevine+ATL+ubiquitin+ligase+family+reveal+biotic+and+abiotic+stress-responsive+and+development-related+members.">Genome-wide characterisation and expression profile of the grapevine ATL ubiquitin ligase family reveal biotic and abiotic stress-responsive and development-related members.</a> Sci. Rep. 6, 38260 (2016).</li><li>Vitulo, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+deep+survey+of+alternative+splicing+in+grape+reveals+changes+in+the+splicing+machinery+related+to+tissue,+stress+condition+and+genotype.">A deep survey of alternative splicing in grape reveals changes in the splicing machinery related to tissue, stress condition and genotype.</a> BMC Plant Biol. 14 (1), 99 (2014).</li><li>Overbeek, R., Fonstein, M., D'Souza, M., Pusch, G. D., Maltsev, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+gene+clusters+to+infer+functional+coupling.">The use of gene clusters to infer functional coupling.</a> Proc. Natl. Acad. Sci. USA. 96 (6), 2896-2901 (1999).</li><li>Dalquen, D. A., Dessimoz, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bidirectional+Best+Hits+Miss+Many+Orthologs+in+Duplication-Rich+Clades+such+as+Plants+and+Animals.">Bidirectional Best Hits Miss Many Orthologs in Duplication-Rich Clades such as Plants and Animals.</a> Genome Biol. Evol. 5 (10), 1800-1806 (2013).</li><li>Remm, M., Storm, C. E. V., Sonnhammer, E. L. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automatic+clustering+of+orthologs+and+in-paralogs+from+pairwise+species+comparisons1.">Automatic clustering of orthologs and in-paralogs from pairwise species comparisons1.</a> J. Mol. Biol. 314 (5), 1041-1052 (2001).</li><li>Kaduk, M., Sonnhammer, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Improved+orthology+inference+with+Hieranoid+2.">Improved orthology inference with Hieranoid 2.</a> Bioinformatics. 33 (8), (2017).</li><li>Cramer, G. 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=Transcriptomic+analysis+of+the+late+stages+of+grapevine+(Vitis+vinifera+cv.+Cabernet+Sauvignon)+berry+ripening+reveals+significant+induction+of+ethylene+signaling+and+flavor+pathways+in+the+skin.">Transcriptomic analysis of the late stages of grapevine (Vitis vinifera cv. Cabernet Sauvignon) berry ripening reveals significant induction of ethylene signaling and flavor pathways in the skin.</a> BMC Plant Biol. 14, 370 (2014).</li><li>Juretic, N., Hoen, D. R., Huynh, M. L., Harrison, P. M., Bureau, T. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+evolutionary+fate+of+MULE-mediated+duplications+of+host+gene+fragments+in+rice.">The evolutionary fate of MULE-mediated duplications of host gene fragments in rice.</a> Genome Res. 15 (9), 1292-1297 (2005).</li><li>Filichkin, S. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+mapping+of+alternative+splicing+in+Arabidopsis+thaliana.">Genome-wide mapping of alternative splicing in Arabidopsis thaliana.</a> Genome Res. 20 (1), 45-58 (2010).</li><li>Quesada, V., Macknight, R., Dean, C., Simpson, G. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Autoregulation+of+FCA+pre-mRNA+processing+controls+Arabidopsis+flowering+time.">Autoregulation of FCA pre-mRNA processing controls Arabidopsis flowering time.</a> EMBO J. 22 (12), 3142-3152 (2003).</li><li>Wong, D. C. J., Gutierrez, R. L., Gambetta, G. A., Castellarin, S. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+analysis+of+cis-regulatory+element+structure+and+discovery+of+motif-driven+gene+co-expression+networks+in+grapevine.">Genome-wide analysis of cis-regulatory element structure and discovery of motif-driven gene co-expression networks in grapevine.</a> DNA Res. 24 (3), 311-326 (2017).</li><li>Wong, D. C. J., Matus, J. 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In the genomic era, many gene families have been deeply characterized in several plant species. This information is preliminary to functional studies and provide a frame to investigate further the role of different members in a family. In this context, there is also a need for a nomenclature system allowing to uniquely identify each member in a family, avoiding the redundancy and confusions that may arise when names are assigned independently to different genes by different research groups.
Af...

During the last decade, much research has been carried out in grapevine genomics. Grapevine is a recognized economically relevant crop, which has become a model for research on fruit development and on the responses of woody plants to biotic and abiotic stresses. In this context, the release of the Vitis vinifera cv. PN40024 genome in 20071 and its updated version in 20112 led to a rapid accumulation of &#34;Omics&#34;-scale data and to a burst of high-throughput studies. Based on the published sequence data, the comprehensive analysis of a given gene family (generally composed of proteins sharing conserved motifs, structural and/or functional similarities and evolutionary relationships), can now be performed to uncover its molecular functions, evolution, and gene expression profiles. These analyses can contribute to understanding how gene families control physiological processes at a genome-wide level.
Many aspects of the plant life cycle are regulated by ubiquitin-mediated degradation of key proteins, which require a fine-tuned turnover to ensure regular cellular processes. Important components of the ubiquitin-mediated degradation process are the E3 ubiquitin ligases, which are responsible for system flexibility, thanks to the recruitment of specific targets3. Accordingly, these enzymes represent a huge gene family, with around 1,400 E3 ligase-encoding genes predicted in Arabidopsis thaliana genome4, each E3 ubiquitin ligase acting for the ubiquitination of specific target proteins. Despite the importance of substrate-specific ubiquitination in cellular regulation in plants, little is known about how the ubiquitination pathway is regulated and target proteins have been identified only in a few cases. The deciphering of such specificity and regulation mechanisms relies first on the identification and characterization of the different components of the system, in particular the E3 ligases. Among ubiquitin ligases, the ATL subfamily is characterized by 91 members identified in A. thaliana displaying a RING-H2 finger domain5,6, some of them playing a role in defense and hormone responses7.
The first crucial step to define the members of a new gene family is the precise definition of the family features, such as consensus motifs, key domains, and protein sequence characteristics. Indeed, the reliable retrieval of all gene family members based on BLAST analysis requires some mandatory sequence characteristics, in particular protein domains responsible for protein function/activity, serving as protein signature. This can be facilitated by previous characterization of the same gene family in other plant species or achieved by analyzing different genes putatively belonging to the same family in different plant species, to isolate common sequences. The family members can then be individually named following common rules settled by international consortia for a given plant species. In grapevine, for instance, such procedure is subjected to the recommendations of the Super-Nomenclature Committee for Grape Gene Annotation (sNCGGa), establishing the construction of a phylogenetic tree including V. vinifera and A. thaliana gene family members to allow gene annotation based on nucleotide sequences8.
Chromosome localization of family members and gene duplication survey allow highlighting the presence of whole-genome or tandem duplicated genes. Such information appears useful to unravel putative gene functions, since it might show functional redundancy or reveal different situations, i.e., non-functionalization, neo-functionalization, or sub-functionalization9. Both neo- and sub-functionalization are important events that create genetic novelty, providing new cellular components for plant adaptation to changing environments10. In particular, duplications of ancestral genes and production of new genes were very frequent during the evolution of the grapevine genome and newly formed genes originating from proximal and tandem duplications in grapevine were more likely to produce new functions11.
Another key factor in deciphering gene family function is the transcriptomic profile. The availability of public databases giving access to a huge amount of transcriptomic data can be thus exploited to assign putative functions to gene family members using large-scale in silico expression analyses. Indeed, the peculiar expression of some genes in specific plant organs or in response to certain stresses can give some hints regarding the putative roles of the corresponding proteins in defined conditions, and give support to hypotheses about possible sub-functionalization of duplicated genes to respond to different challenges. For that purpose, it is important to consider several datasets: these can be already available gene expression matrixes, such as the genome-wide transcriptomic atlas of grapevine organs and developmental stages12, or can be built ad hoc by retrieving transcriptomic datasets for the particular plant species subjected to defined stresses. Moreover, a simple approach using two matrices, one with pairwise similarity data and the other one with pairwise co-expression coefficients can be applied to evaluate the relationships between sequence similarity and expression patterns within a gene family.
The aim of this work is to provide a global approach, defining gene structure, conserved protein motifs, chromosomal location, gene duplications, and expression patterns, as well the prediction of protein localization and phosphorylation sites, to attain an exhaustive characterization of a gene family in plants. Such a comprehensive approach is applied here to the characterization of the ATL E3 ubiquitin ligase family in grapevine. According to the emerging role of ATL subfamily members in regulating key cellular processes7, this work can well assist the identification of strong candidates for functional studies, and eventually unravel the molecular mechanisms governing the adaptation of this important crop to its environment.

<table>
	<tbody>
		<tr>
			<td>Personal computer</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Basic Local Alignment Search Tool (BLAST)</td>
			<td></td>
			<td></td>
			<td>https://blast.ncbi.nlm.nih.gov/Blast.cgi</td>
		</tr>
		<tr>
			<td>Molecular Evolutionary Genetics Analysis (MEGA)</td>
			<td></td>
			<td></td>
			<td>http://www.megasoftware.net/</td>
		</tr>
		<tr>
			<td>Motif-based sequence analysis tools (MEME)</td>
			<td></td>
			<td></td>
			<td>http://meme-suite.org/</td>
		</tr>
		<tr>
			<td>Geneious</td>
			<td>Biomatters Limited</td>
			<td></td>
			<td>http://www.geneious.com/</td>
		</tr>
		<tr>
			<td>ProtParam Tool</td>
			<td></td>
			<td></td>
			<td>http://web.expasy.org/protparam/</td>
		</tr>
		<tr>
			<td>ngLOC</td>
			<td></td>
			<td></td>
			<td>http://genome.unmc.edu/ngLOC/index.html</td>
		</tr>
		<tr>
			<td>TargetP v1.1 Server</td>
			<td></td>
			<td></td>
			<td>http://www.cbs.dtu.dk/services/TargetP/</td>
		</tr>
		<tr>
			<td>Protein Prowler</td>
			<td></td>
			<td></td>
			<td>http://bioinf.scmb.uq.edu.au:8080/pprowler_webapp_1-2/</td>
		</tr>
		<tr>
			<td>MUsite</td>
			<td></td>
			<td></td>
			<td>http://musite.sourceforge.net/</td>
		</tr>
		<tr>
			<td>Pfam</td>
			<td></td>
			<td></td>
			<td>http://pfam.xfam.org/</td>
		</tr>
		<tr>
			<td>TMHMM Server v. 2.0</td>
			<td></td>
			<td></td>
			<td>http://www.cbs.dtu.dk/services/TMHMM/</td>
		</tr>
		<tr>
			<td>ProtScale</td>
			<td></td>
			<td></td>
			<td>http://web.expasy.org/protscale/</td>
		</tr>
		<tr>
			<td>Grape Genome Database (CRIBI)</td>
			<td></td>
			<td></td>
			<td>http://genomes.cribi.unipd.it/grape/</td>
		</tr>
		<tr>
			<td>PhenoGram</td>
			<td></td>
			<td></td>
			<td>http://visualization.ritchielab.psu.edu/phenograms/plot</td>
		</tr>
		<tr>
			<td>MCScanX</td>
			<td></td>
			<td></td>
			<td>http://chibba.pgml.uga.edu/mcscan2/</td>
		</tr>
		<tr>
			<td>Interactive Tree Of Life (iTOL)</td>
			<td></td>
			<td></td>
			<td>http://itol.embl.de/</td>
		</tr>
		<tr>
			<td>UniProt</td>
			<td></td>
			<td></td>
			<td>http://www.uniprot.org/</td>
		</tr>
		<tr>
			<td>Phylogeny.fr</td>
			<td></td>
			<td></td>
			<td>http://www.phylogeny.fr/index.cgi</td>
		</tr>
		<tr>
			<td>MUSCLE</td>
			<td></td>
			<td></td>
			<td>http://www.ebi.ac.uk/Tools/msa/muscle/</td>
		</tr>
		<tr>
			<td>Gblocks Server</td>
			<td></td>
			<td></td>
			<td>http://molevol.cmima.csic.es/castresana/Gblocks_server.html</td>
		</tr>
		<tr>
			<td>Vitis vinifera cv. Corvina gene expression Atlas datamatrix</td>
			<td></td>
			<td></td>
			<td>https://www.researchgate.net/publication/273383414_54sample_datamatrix_geneIDs_Fasoli2012</td>
		</tr>
		<tr>
			<td>Multi Experiment Viewer (MeV)</td>
			<td></td>
			<td></td>
			<td>http://mev.tm4.org/#/welcome</td>
		</tr>
		<tr>
			<td>Sequence Read Archive (SRA)</td>
			<td></td>
			<td></td>
			<td>https://www.ncbi.nlm.nih.gov/sra</td>
		</tr>
		<tr>
			<td>R</td>
			<td></td>
			<td></td>
			<td>https://www.r-project.org/</td>
		</tr>
		<tr>
			<td>EMBOSS Needle (EMBL-EBI)</td>
			<td></td>
			<td></td>
			<td>http://www.ebi.ac.uk/Tools/psa/emboss_needle/</td>
		</tr>
	</tbody>
</table>

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.

The VIT_05s0077g01970 gene, identified as the most similar to A. thaliana ATL2 (At3g16720) through a BLASTp search, was used as probe to survey the ATL family members in the grapevine genome (V. vinifera cv Pinot Noir PN40024). The PSI-BLAST analysis converged after a few cycles revealing a list of putative genes belonging to the grapevine ATL gene family (Figure 1A). The presence of the canonical RING-H2 domain for each candidate was evalua...

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

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.

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

The overall goal of this procedure is to attain an exhaustive characterization of a gene family in plants to a global approach including the definition of gene structure, concerned protein motifs, chromosomal location, gene duplications, and expression patterns. This method can help answer key questions in the classification of plants in families such as world genomic identification of family members and their transcriptomy provides this through gene expression analysis. The main advantage of the whole procedure is to provide an exhaustive list of experimental steps to achieve a complete gene family characterization.This procedure can be applied for any gene family of any plant species for which genetic data are available. Moreover, this approach provides valuable information to identify interesting candidates for functional studies. Demonstrating the whole procedure will be Pietro Ariani from my laboratory.Open the Blast web page and click on the protein blast section. In the enter query sequence field, enter the amino acid sequence of the protein that will be used as the probe to identify the other family members. Use a protein that has all the important features that characterize the family.Next, in the field choose search set, select the reference protein data base and the organism of interest. Now, in the field program selection, select the PSI-BLAST algorithm. If desired, click on algorithm parameters to adjust advanced parameters such as max target sequence and scoring matrix.The E value is the threshold, which for this search is decreased from 005 to 001. Click the BLAST button to run the analysis. From all the sequences displaying relative matches to the query, un-select the entries which clearly do not belong to the family.Do so by clicking on the tick in the select for PSI-BLAST column. Then, run a second PSI-BLAST iteration by clicking the go button. All of the newly identified sequences will be highlighted in yellow.Again, un-select the hits that do not belong to the family. Continue this process until the algorithm does not find any relevant entry or it reaches convergence. Once all the false-positives are weeded out, collect the amino acidic sequences in a FASTA formatted file and upload the file into the bio-informatics software suite.Next, select all the imported sequences in the list and click the align/assemble button in the toolbar. Then click pair wise multiple alignment and select MUSCLE alignment and OK.The alignment will now be made using the defaults. Now visualize the sequence logo of the alignment and inspect the genes visually to search for false-positives.Further analysis of protein physical parameters and domains, chromosomal distribution, duplications, and exon intron organization are described in the text protocol. Next analyze the relationships among the ATL family members through the construction of a high quality phylogenetic tree and the definition of a family nomenclature. First, retrieve the arab adopt systeliana ATL sequences, required as references for a grape vine gene nomenclature, from the UmoProt database for reference.Then make a FASTA file including all the nucleotide sequences of the grape vine and the Arabidopsis gene family members for the phylogenetic analysis. Now browse the phylogeny France home page and select the phylogeny analysis pipeline. One click is suitable in most of the cases, but if needed, it is possible to select specific advanced settings using the advanced options or even a fully customized analysis using the a la carte options.Next, input a name for the analysis and upload the FASTA file. Then click submit to run the analysis. If this procedure results in an error message, complete each step of the phylogeny suite pipeline individually.First, go to the MUSCLE software homepage and upload the FASTA file. Select Pearson FASTA as output format and submit. Next, download the file in FASTA format and eliminate any poorly aligned positions.Open the G-block server tool, upload the alignment FASTA file, select DNA as type of sequence, and choose the stringency that best fits with the analysis. For a grape vine ATL gene family alignment, select all the three options proposed for less stringent selection because of high sequence divergence. Then click get blocks to run the analysis.To save the results, click on resulting alignment at the bottom of the output page and make a new FASTA file. G-blocks eliminates poorly aligned position in divergent regions of a DNA or prodding alignment so that it becomes more suitable for a phylogenetic analysis. For this step, impericle parameter selection for the columns stringency is crucial to ensure they're a liability of the three.To complete the tree, we turn to the Phylogeny France home page. There, select the a la carte pipeline and deselect the following options:multiple alignment and alignment curation. Next, click create workflow, upload the G-blocks curated FASTA file, select bootstrapping procedure, and use default parameters and settings.Finally, click submit to run the analysis. This completes the step by step process. Now that the phylogenic tree is made, collapse the poorly supported branches with bootstrap values of less than 70%Then download the final results in the Newick format to further analysis.The text protocol provides instructions on assigning a gene name based on the phylogeny. For this protocol, make a tapped, lineated, text format file of arma-normalized expression values taken from a gene expression library. Organize the values for each family gene under the same pattern rows.Next, perform the hierarchical bi-clustered analysis using multi-experiment viewer software. First, upload the working data matrix and select the text file. Select single-color array and remove the tick from load annotation when an automatic annotation is not provided.Select the upper-left most expression value of the expression table preview and click the load button. Next, adjust the data, applying Log2 transformation and gene/row normalization. Then set the proper scale limit.Now calculate the hierarchical clustering. In the ordering optimization field, select optimize gene leaf order and optimize sample leaf order. Next, in the linkage method selection field, select average linkage clustering and in the distance matrix selection field choose Pearson correlation.Then click OK to run the analysis. View the results in the left panel of the window and export the heat map by clicking save image in the file menu. The most similar gene to arabidopsis thaliana ATL2, according to a BLAST-P search was used to survey the ATL family members in the grape vine genome.The PSI BLAST analysis converged after a few cycles providing a list of putative genes in the gene family. The presence of the canonical ring H2 domain for each candidate was evaluated by the visual inspection of the MUSCLE alignment. This narrowed the search to 96 grape vine genes.A phylogenetic analysis of the identified genes comparing them with the arabidopsis ATL gene family was used for a nomenclature. 13 of 96 grape vine ATLs received a specific identifier as an arabidopsis ATL gene ortholog. Mapping the identified genes to the grape vine global gene expression atlas using a hierarchical bi-clustered analysis showed that all 96 are expressed in at least one tissue and five expression clusters can be identified.A similar approach was applied to study the expression of these genes in response to biotic stresses. There was direct involvement of the ATL gene family in response to pathogen infection with 62 genes showing a significant modulation in at least two conditions. After watching this video, you should have a good understanding of how to deal with the softwares used to characterize a gene family.While attempting this procedure, it's important to carefully define the characteristics of a given gene family and the corresponding probe used for the whole genome family member identification. Following this procedure, it is possible to investigate gene family evolution and P30 function by making additional phylogenetic trees based on some species other than the species required for the attribution of gene families nomenclature.

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Biology

The Preparation of Primary Hematopoietic Cell Cultures From Murine Bone Marrow for Electroporation

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser MXcell  electroporation system and Gene Pulser  electroporation buffer were specifically developed to transfect nucleic acids into mammalian cells and difficult-to-transfect cells, such as primary and stem cells.This video demonstrates how to establish primary hematopoietic cell cultures from murine bone marrow, and then prepare them for electroporation in the MXcell system. We begin by isolating femur and tibia. Bone marrow from both femur and tibia are then harvested and cultures are established. Cultured bone marrow cells are then transfected and analyzed.

This procedure describes how to establish primary hematopoietic cell cultures from murine bone marrow and is followed by transfection using the Gene Pulser MXCell electroporation system.

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser ...

Spinal Cord Electrophysiology

The neonatal mouse spinal cord is a model for studying the development of neural circuitries and locomotor movement. We demonstrate the spinal cord dissection and preparation of recording bath artificial cerebrospinal fluid used for locomotor studies. Once dissected, the spinal cord ventral nerve roots can be attached to a recording electrode to record the electrophysiologic signals of the central pattern generating circuitry within the lumbar cord.

A demonstration of the isolation of neonatal mouse spinal cord for electrophysiologic studies.

The neonatal mouse spinal cord is a model for studying the development of neural circuitries and locomotor movement. We demonstrate the spinal cord ...

Using the Gene Pulser MXcell Electroporation System to Transfect Primary Cells with High Efficiency

It is becoming increasingly apparent that electroporation is the most effective way to introduce plasmid DNA or siRNA into primary cells. The Gene Pulser MXcell electroporation system and Gene Pulser electroporation buffer (Bio-Rad) were specifically developed to easily transfect nucleic acids into mammalian cells and difficult-to-transfect cells, such as primary and stem cells. We will demonstrate how to perform a simple experiment to quickly identify the best electroporation conditions. We will demonstrate how to run several samples through a range of electroporation conditions so that an experiment can be conducted at the same time as optimization is performed. We will also show how optimal conditions identified using 96-well electroporation plates can be used with standard electroporation cuvettes, facilitating the switch from electroporation plates to electroporation cuvettes while maintaining the same electroporation efficiency. In the video, we will also discuss some of the key factors that can lead to the success or failure of electroporation experiments.

This procedure shows how to use the Gene Pulser MXcell electroporation system to rapidly and easily identify the best electroporation conditions for mouse embryonic fibroblasts (MEFs) or other primary cells. Considerations for troubleshooting are also discussed in the associated video.

Robotics and Dynamic Image Analysis for Studies of Gene Expression in Plant Tissues

Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The gfp gene was placed under regulatory control of different promoters and introduced into lima bean cotyledonary tissues via particle bombardment. Cotyledons were then placed on a robotic image collection system, which consisted of a fluorescence dissecting microscope with a digital camera and a 2-dimensional robotics platform custom-designed to allow secure attachment of culture dishes. Images were collected from cotyledonary tissues every hour for 100 hours to generate expression profiles for each promoter. Each collected series of 100 images was first subjected to manual image alignment using ImageReady to make certain that GFP-expressing foci were consistently retained within selected fields of analysis. Specific regions of the series measuring 300 x 400 pixels, were then selected for further analysis to provide GFP Intensity measurements using ImageJ software. Batch images were separated into the red, green and blue channels and GFP-expressing areas were identified using the threshold feature of ImageJ. After subtracting the background fluorescence (subtraction of gray values of non-expressing pixels from every pixel) in the respective red and green channels, GFP intensity was calculated by multiplying the mean grayscale value per pixel by the total number of GFP-expressing pixels in each channel, and then adding those values for both the red and green channels. GFP Intensity values were collected for all 100 time points to yield expression profiles. Variations in GFP expression profiles resulted from differences in factors such as promoter strength, presence of a silencing suppressor, or nature of the promoter. In addition to quantification of GFP intensity, the image series were also used to generate time-lapse animations using ImageReady. Time-lapse animations revealed that the clear majority of cells displayed a relatively rapid increase in GFP expression, followed by a slow decline. Some cells occasionally displayed a sudden loss of fluorescence, which may be associated with rapid cell death. Apparent transport of GFP across the membrane and cell wall to adjacent cells was also observed. Time lapse animations provided additional information that could not otherwise be obtained using GFP Intensity profiles or single time point image collections.

We report a method for introduction, tracking and quantitative analysis of GFP expression in plant cells. This method utilizes a custom-designed robotics system for semi-continuous image collection from large numbers of samples, over time. We also demonstrate the use of ImageJ and ImageReady for analysis of image series.

Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods ...

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression.  siRNA studies are being conducted not only to study the effects of downregulating single genes, but also to interrogate signaling pathways and other complex interaction networks.  These pathway analyses require both the use of relevant cellular models and methods that cause less perturbation to the cellular physiology.  Electroporation is increasingly being used as an effective way to introduce siRNA and other nucleic acids into difficult to transfect cell lines and primary cells without altering the signaling pathway under investigation. There are multiple critical steps to a successful siRNA experiment, and there are ways to simplify the work while improving the data quality at several experimental stages.  To help you get started with your siRNA mediated gene knockdown project, we will demonstrate how to perform a pathway study complete from collecting and counting the cells prior to electroporation through post transfection real-time PCR gene expression analysis.  The following study investigates the role of the transcriptional activator STAT6 in IL-4 dependent gene expression of CCL17 in a Burkitt lymphoma cell line (Namalwa).  The techniques demonstrated are useful for a wide range of siRNA-based experiments on both adherent and suspension cells.  We will also show how to streamline cell counting with the TC10 automated cell counter, how to electroporate multiple samples simultaneously using the MXcell electroporation system, and how to simultaneously assess RNA quality and quantity with the Experion automated electrophoresis system.

This procedure describes a quick and easy workflow to introduce siRNA into difficult to transfect cell lines and follow gene expression by real-time PCR. Use of an automated cell counter, multi-well electroporation plate, and automated electrophoresis station provide quick and reliable results without the need for expensive robotic handling.

The use of siRNA mediated gene knockdown is continuing to be an important tool in studies of gene expression.  siRNA studies are being conducted not only ...

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.

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

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.
Telomerase is a specialized reverse transcriptase1 that adds short DNA repeats, called telomeres, to the 3' end of linear chromosomes2 that serve to protect them from end-to-end fusion and degradation. Following DNA replication, a short segment is lost at the end of the chromosome3 and without telomerase, cells continue dividing until eventually reaching their Hayflick Limit4. Additionally, telomerase is dormant in most somatic cells5 in adults, but is active in cancer cells6 where it promotes cell immortality7.
The minimal telomerase enzyme consists of two core components: the protein subunit (TERT), which comprises the catalytic subunit of the enzyme and an integral RNA component (TER), which contains the template TERT uses to synthesize telomeres8,9. Prior to 2008, only structures for individual telomerase domains had been solved10,11. A major breakthrough in this field came from the determination of the crystal structure of the active12, catalytic subunit of T. castaneum telomerase, TcTERT1.
Here, we present methods for producing large quantities of the active, soluble TcTERT for structural and biochemical studies, and the reconstitution of the telomerase RNP complex in vitro for telomerase activity assays. An overview of the experimental methods used is shown in Figure 1.

In vitro Reconstitution of the Active T. castaneum Telomerase

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more than a decade. Here, we present methods for the isolation of the recombinant Tribolium castaneum TERT (TcTERT) and the reconstitution of the active T. castaneum telomerase ribonucleoprotein (RNP) complex in vitro.

Efforts to isolate the catalytic subunit of telomerase, TERT, in sufficient quantities for structural studies, have been met with limited success for more ...

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.

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

Analysis of Global RNA Synthesis at the Single Cell Level following Hypoxia

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a particular transcriptional program in order to mount an appropriate and coordinated cellular response. The cell possesses several oxygen sensor enzymes that require molecular oxygen as cofactor for their activity. These range from prolyl-hydroxylases to histone demethylases. The majority of studies analyzing cellular responses to hypoxia are based on cellular populations and average studies, and as such single cell analysis of hypoxic cells are seldom performed. Here we describe a method of analysis of global RNA synthesis at the single cell level in hypoxia by using Click-iT RNA imaging kits in an oxygen controlled workstation, followed by microscopy analysis and quantification.&nbsp; Using cancer cells exposed to hypoxia for different lengths of time, RNA is labeled and measured in each cell. This analysis allows the visualization of temporal and cell-to-cell changes in global RNA synthesis following hypoxic stress.

We describe a technique for analysis of global RNA synthesis in hypoxia using imaging. Click-chemistry labeling of RNA has not previously been performed under hypoxia and allows visualization of global RNA changes at the single cell level. This approach complements the existing averaged RNA techniques, allowing direct visualization of cell-to-cell changes in global RNA synthesis.

Hypoxia or lowering of the oxygen availability is involved in many physiological and pathological processes. At the molecular level, cells initiate a ...

siRNA Screening to Identify Ubiquitin and Ubiquitin-like System Regulators of Biological Pathways in Cultured Mammalian Cells

Post-translational modification of proteins with ubiquitin and ubiquitin-like molecules (UBLs) is emerging as a dynamic cellular signaling network that regulates diverse biological pathways including the hypoxia response, proteostasis, the DNA damage response and transcription.&#160; To better understand how UBLs regulate pathways relevant to human disease, we have compiled a human siRNA &#8220;ubiquitome&#8221; library consisting of 1,186 siRNA duplex pools targeting all known and predicted components of UBL system pathways. This library can be screened against a range of cell lines expressing reporters of diverse biological pathways to determine which UBL components act as positive or negative regulators of the pathway in question.&#160; Here, we describe a protocol utilizing this library to identify ubiquitome-regulators of the HIF1A-mediated cellular response to hypoxia using a transcription-based luciferase reporter.&#160; An initial assay development stage is performed to establish suitable screening parameters of the cell line before performing the screen in three stages: primary, secondary and tertiary/deconvolution screening. &#160;The use of targeted over whole genome siRNA libraries is becoming increasingly popular as it offers the advantage of reporting only on members of the pathway with which the investigators are most interested.&#160; Despite inherent limitations of siRNA screening, in particular false-positives caused by siRNA off-target effects, the identification of genuine novel regulators of the pathways in question outweigh these shortcomings, which can be overcome by performing a series of carefully undertaken control experiments.

Here, we describe a methodology to perform a targeted siRNA &#8220;ubiquitome&#8221; screen to identify novel ubiquitin and ubiquitin-like regulators of the HIF1A-mediated cellular response to hypoxia.&#160; This can be adapted to any biological pathway where a robust read out of reporter activity is available.

Post-translational modification of proteins with ubiquitin and ubiquitin-like molecules (UBLs) is emerging as a dynamic cellular signaling network that ...