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. T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Constructing+Integrated+Networks+for+Identifying+New+Secondary+Metabolic+Pathway+Regulators+in+Grapevine:+Recent+Applications+and+Future+Opportunities.">Constructing Integrated Networks for Identifying New Secondary Metabolic Pathway Regulators in Grapevine: Recent Applications and Future Opportunities.</a> Front. Plant Sci. 8, 505 (2017).</li></ol>

The authors have nothing to disclose.

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...

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

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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10.3K visualizações.  Università degli Studi di Verona. 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...