Tag Archives: prediction

Tip of the Week: SKIPPY predicting variants w/ splicing affects


More and more disease-causing mutations are being identified in exonic splicing regulatory sequences (ESRs). These disease effects can result from ESR mutations that cause exon skipping in functionally diverse genes. In today’s tip I’d like to introduce you to a tool designed to detect exon variants that modulate splicing. The tool is named SKIPPY and has been developed and is maintained by groups in the Genomic Functional Analysis research section of the NHGRI.

At the end of the post I cite a very well-written paper describing the development of SKIPPY, as well as the background on why the tool was developed. I won’t have time to go into all those details, but if you are interested the paper is freely available from Genome Biology. The site also has nice, clear documentation and example inputs – which I will use as my examples. Splicing can be modulated in a variety of ways, including the loss or gain of exonic splicing enhancers (ESEs) or silencers (ESSs). Variants accomplishing either of those are referred to as splice-affecting genome variants, or SAVs. Not all of the abbreviations are explained on the results page, as you will see in the tip, but all are explained in detail in the SKIPPY publication, and the  ‘Methods and Interpretations‘ and ‘Quick Reference and Tutorial‘ areas of the site.

I first found the tool because it was mentioned in a nice review entitled “Using Bioinformatics to predict the functional impact of SNVs“, which is a paper that reviews mechanisms by which point mutations can effect function, describes many of the algorithms and resources available & provides some sage advice. I’ll post more on it in a later post. For now, check out the tip & the SKIPPY resource, and if you use the site please let us know what you think.

Woolfe, A., Mullikin, J., & Elnitski, L. (2010). Genomic features defining exonic variants that modulate splicing Genome Biology, 11 (2) DOI: 10.1186/gb-2010-11-2-r20

Cline, M., & Karchin, R. (2010). Using bioinformatics to predict the functional impact of SNVs Bioinformatics DOI: 10.1093/bioinformatics/btq695

Tip of the Week: RepTar, a database of miRNA target sites

microRNAs have become a rich source of research as they probably have a huge effect on gene expression and disease. The human genome may encode over 1,000 miRNAs that target over half of our genes. They might be implicated in a lot of common diseases (which not yet have been picked up in GWAS studies?). They are a fascinating area of biology that has only come of it’s on in the last decade. As such, the number of databases to catalog miRNAs is large. Today’s tip is on a new one, RepTar, which is reported in the upcoming NAR database issue. The niche RepTar is attempting to fill is to get predictions of miRNAs more comprehensive by including new research in the algorithm. This new research suggests there are more possible target sites than previously thought. As mentioned in the article,

Recently, the miRNA binding options were expanded further with the identification of ‘centered sites’, functional miRNA target sites that lack both perfect seed pairing and 3′-compensatory pairing and instead exhibit pairing with the target along 11–12 contiguous pairs at the center of the miRNA (4). While some algorithms relaxed the evolutionary conservation criterion (5–11) and/or offer also predictions of 3′-compensatory sites [e.g. (6,12,13)], few databases offer predictions of the whole repertoire of miRNA targeting patterns. Furthermore to date, no database lists genome-wide prediction of cellular targets of viral miRNAs. These miRNAs lack significant evolutionary conservation and their targets are not necessarily expected to be evolutionarily conserved. In addition, the few identified viral miRNA targets have shown both conventional seed binding and 3′-compensatory binding [e.g. (3,14)].

Here we present a database of genome-wide miRNA target predictions for mouse and human genes, based on the predictions of our novel target prediction algorithm, RepTar

I’ll leave the predictive value up to miRNA researchers, but I thought I’d introduce the site.

While I’m at it, allow me to list a few other miRNA sites from labs and institutes as far flung as China, Italy, Israel, Canada and the U.S.. Perhaps someday I’ll do a comparison.

CircuitsDB, which Jennifer did a great tip of the week tutorial on.

miRBase, which we have a full-length tutorial on.
microRNA.org
HMDD
miRDB
tarBase
miRecords:
PicTar, they have an annotation track for UCSC Genome Browser
miRNA2Disease
PuTmiR (in relation to transcription factors)
microRNAdb:

two lists to catch some others: http://mirnablog.com/microrna-target-prediction-tools/ and  http://www.ncrna.org/KnowledgeBase/link-database/mirna_target_database

Elefant, N., Berger, A., Shein, H., Hofree, M., Margalit, H., & Altuvia, Y. (2010). RepTar: a database of predicted cellular targets of host and viral miRNAs Nucleic Acids Research DOI: 10.1093/nar/gkq1233

The University of Toronto Announces Free OpenHelix Tutorial and Training Materials for GeneMANIA, a Gene Function Prediction Tool

Quote startThe OpenHelix tutorial suite is sure to help current and new users to get up to speed on our site and its new features, and therefore get their results more quickly to support their research.Quote end

Bellevue, WA (PRWEB) August 11, 2010

The creators of GeneMANIA have contracted with OpenHelix to provide comprehensive online training for the gene function prediction tool (http://genemania.org ).

GeneMANIA is a free public resource that offers a simple, intuitive web interface that shows the relationships between genes in a list and analyzes and extends the list to include other related genes. The web interface is backed by powerful analysis software and a large data warehouse containing extensive amounts of existing functional genomics data, and also includes Cytoscape Web, a web based advanced visualization tool to enable browsing of query results and creation of publication-ready figures.

“GeneMANIA will soon be updated to include significantly increased functionality,” according to Gary Bader and Quaid Morris, assistant professors in the Donnelly Centre (http://tdccbr.med.utoronto.ca/) and co-principal investigators for GeneMANIA. “OpenHelix based their tutorial on our development site, and even provided user feedback on our new features that resulted in improvements to our system. OpenHelix had very strong understanding of the GeneMANIA interface, which then translated into a powerful learning resource. The OpenHelix tutorial suite is sure to help current and new users to get up to speed on our site and its new features, and therefore get their results more quickly to support their research.”

The new training initiatives include a free online tutorial suite on GeneMANIA. The online narrated tutorial (http://www.openhelix.com/genemania ), which runs in just about any browser, can be viewed from beginning to end or navigated using chapters and forward and backward sliders. The approximately 60 minute tutorial highlights and explains the features and functionality needed to start using GeneMANIA effectively. The tutorial can be used by new users to introduce them to GeneMANIA, for previous users to view new features and functionality, or simply as a reference tool to understand specific features.

In addition to the tutorial, GeneMANIA users can also access useful training materials including the animated PowerPoint slides used as a basis for the tutorial, a suggested script for the slides, slide handouts, and exercises. This can save a tremendous amount time and effort for teachers and professors to create classroom content.

“GeneMANIA is an innovative, hypothesis generating tool that can be used to extend a given gene list to find related genes sharing similar functions,” said OpenHelix founder and President Dr. Mary Mangan. “OpenHelix is excited to contribute to furthering the field of gene function prediction by assisting researchers in effectively and efficiently using such a critical tool.”

Users can view the tutorials and download the free materials at www.openhelix.com .

In addition to the GeneMANIA tutorial suite, OpenHelix offers over 90 tutorial suites on some of the most powerful and popular bioinformatics and genomics tools available on the web. Some of the tutorials suites are freely available through support from the resource providers. The whole catalog of tutorials suites is available through a subscription. Users can view the tutorials and download the free materials at www.openhelix.com .

About GeneMANIA
GeneMANIA (www.genemania.org ) is a free web-based prediction tool that finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets.

GeneMANIA is actively developed at the University of Toronto, in the Donnelly Centre for Cellular and Biomolecular Research, in the labs of Gary Bader and Quaid Morris, with input from an independent scientific advisory board. GeneMANIA development is funded by Genome Canada, through the Ontario Genomics Institute (2007-OGI-TD-05).

About OpenHelix
OpenHelix, LLC, (www.openhelix.com ) provides a bioinformatics and genomics search and training portal, giving researchers one place to find and learn how to use resources and databases on the web. The OpenHelix Search portal searches hundreds of resources, tutorial suites and other material to direct researchers to the most relevant resources and OpenHelix training materials for their needs. Researchers and institutions can save time, budget and staff resources by leveraging a subscription to nearly 100 online tutorial suites available through the portal. More efficient use of the most relevant resources means quicker and more effective research.