Tag Archives: ensembl

VideoTip of the Week: ENCODE @ Ensembl

We have a lot of tutorials (2 in fact, ENCODE Foundations & ENCODE @ UCSC), tips and information about ENCODE. We also have a lot of tutorials (again 2, Ensembl and Ensembl Legacy- on the older versions ), tips and information about Ensembl, the database and browser at EBI.

Now here is a tip of the week on both Ensembl AND ENCODE. This is one of the more recent additions to Ensembl’s video tutorials. This video looks at how to identify sequences that may be involved in gene regulation. Most of this data at Ensembl is based on ENCODE data. This is using the “Matrix,” a way to select the regulation data you need based on cell types and TF’s. At the end of the 8 minute video they discuss a bit more about how to get all ENCODE data.

So, now you have a wealth of information here at OpenHelix through our tutorials and our blog about ENCODE and Ensembl.

Quick links:

ENCODE: http://encodeproject.org/ENCODE/
ENCODE @ UCSC: http://genome.ucsc.edu/ENCODE/
Ensembl: http://www.ensembl.org
ENCODE Tutorials: http://openhelix.com/encode
Ensembl Tutorials: http://openhelix.com/cgi/tutorialInfo.cgi?id=95

Video Tip of the Week: Browsing Butterflies with GBrowse and Ensembl

A couple of months back when the Heliconius (Postman) Butterfly genome paper was released, we got to see another example of how the new sequencing technologies are giving us access to more and more genome data–in species that are not the main model organisms. Monarch butterfly genome data had been released prior to that as well. And you may not know that there’s a huge effort to get thousands of insect genomes–the i5k project. I think that’s my favorite thing about where we are today: we can examine more species in more detail than we ever have before.  Not only do we get interesting details from the genome sequence framework, but interesting info about species evolutionary relationships, and intriguing and novel biology features can be explored as well. I mean–the human genome and its variations are great–but Monarch butterflies have a sun compass! How cool is that??

And like most genome papers today, only a fraction of the data that was obtained is in the main body of the paper. The “compelling examples” might be there. But of the “12,699 predicted protein-coding genes” of the Heliconius genome, only a handful are really addressed in the text. A few more handfuls in some figures. The earlier Monarch butterfly paper delivered “a set of 16,866 protein-coding genes” (and 10 supplements beyond the paper!). But to access the data yourself and compare to your genes and species of interest you need to turn to the browsers that accompany the papers.

In this case you have two choices for browser styles: the Heliconius Genome Consortium (authors of the paper) maintain a GBrowse installation at their Butterflygenome.org site. The Monarch group has a GBrowse at MonarchBase. In addition, the data for both is also now included in Ensembl as of the July 2012 release 15. [note: see administrative details in the comments --mm]

For this week’s tip we fly around from the species-specific GBrowsers to the collected sets at Ensembl. It’s great to have the species-specific sites for depth of information about the projects and resources, but it’s also nice to have the additional tools and displays of the larger genome browsers. Community browsers can offer very current and new data that might not yet be included in the super-browsers, and the super-browsers may offer additional tools and infrastructure that is not available from the community browsers. Your best bet is to be aware of both, and to get comfortable with the main software features and their strengths and weaknesses.

The bugs are coming–and thousands of them. Be ready. And beware: look for the right superhero

Note: I have been unable to locate the Mothra genome that’s been all atwitter for the last couple of days.

Quick links:

Heliconius GBrowse: http://butterflygenome.org/

MonarchBase: http://monarchbase.umassmed.edu/genome.html

Ensembl Metazoa: http://metazoa.ensembl.org/

i5k Insect and other Arthropod Genome Sequencing Initiative http://arthropodgenomes.org/wiki/i5K

If you came looking for butterfly photos, try this: http://www.butterfliesandmoths.org/ This is also a citizen science site where you can submit your own sightings–I have done that in the past.

References:

Dasmahapatra, K.K., Walters, J.R., Briscoe, A.D., Davey, J.W., Whibley, A., Nadeau, N.J., Zimin, A.V., Hughes, D.S.T., Ferguson, L.C., Martin, S.H. & (2012). Butterfly genome reveals promiscuous exchange of mimicry adaptations among species, Nature, DOI: 10.1038/nature11041

Zhan, S., Merlin, C., Boore, J. & Reppert, S. (2011). The Monarch Butterfly Genome Yields Insights into Long-Distance Migration, Cell, 147 (5) 1185. DOI: 10.1016/j.cell.2011.09.052

Stensmyr, M. & Hansson, B. (2011). A Genome Befitting a Monarch, Cell, 147 (5) 972. DOI: 10.1016/j.cell.2011.11.009

Kersey, P.J., Staines, D.M., Lawson, D., Kulesha, E., Derwent, P., Humphrey, J.C., Hughes, D.S.T., Keenan, S., Kerhornou, A., Koscielny, G. & (2011). Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species, Nucleic Acids Research, 40 (D1) D97. DOI: 10.1093/nar/gkr895

Video Tips of the Week: Annual Review IV, 2nd half

As you may know, we’ve been doing these video tips-of-the-week for FOUR years now. We have completed around 200 little tidbit introductions to various resources from last year, 2011 (yep, it’s 2012 now). At the end of the year we’ve established a sort of holiday tradition: we are doing a summary post to collect them all. If you have missed any of them it’s a great way to have a quick look at what might be useful to your work.

You can see past years’ tips here: 2008 I2008 II2009 I2009 II2010 I2010 II. The summary of the first half of 2011 is available from last week.

July 2011

July 6: Prioritizing genes using the Gene Prioritization Portal

July 13: PolySearch, searching many databases at once

July 20: Human Epigenomics Visualization Hub

July 27: The new SIB Bioinformatics Resource Portal

 

August 2011

August 3: SNPexp, correlation between SNPs and gene expression 

August 10: CompaGB for comparing genome browser software

August 17: CoGe, comparing genomes revisited

August 24: Domain Draw for quick motif diagrams

August 31: From UniProt to the PSI SBKB and back again

 

September 2011

September 7: Plant comparative genomics using Plaza

September 14: phiGENOME for bacteriophage genome exploration

September 21: Getting flanking sequences of genomic locations

September 28: Introduction to R statistical software 

 

October 2011

October 5: VnD resource for genetic variation and drug information

October 12: Track Hubs in UCSC Genome Browser

October 19: Mitochondrial Transcriptome GBrowser 

October 26: Variation data from Ensembl

 

November 2011

November 2: MizBee Synteny Browser

November 9: The new database of genomic variants: DGV2

November 16: MapMi, automated mapping of microRNA loci

November 23: BioMart’s new central portal

November 30: Phosphida, a post-translational modification database

December 2011

December 7: VarSifter, for identifying key sequence variations

December 14: Big changes to NCBI’s genome resources

December 21: eggNOG for the Holidays (or to explore orthologous genes)

December 28: Video Tips of the Week: Annual Review IV (first half of 2011)

Announcement of Updated Tutorial Materials: UniProt, Overview of Genome Browsers, and World Tour of Resources

As many of you know, OpenHelix specializes in helping people access and utilize the gold mine of public bioscience data in order to further research.  One of the ways that we do this is by creating materials to train people – researchers, clinicians, librarians, and anyone interested in science - on where to find data they are interested in, and how to access data at particular public databases and data repositories. We’ve got over 100 such tutorials on everything from PubMed to the Functional Glycomics Gateway (more on that later).

In addition creating these tutorials, we also spend a lot of time to keep them accurate and up-to-date. This can be a challenge, especially when lots of databases or resources all have major releases around the same time. Our team continually assesses and updates our materials and in this post I am happy to announce recently released updates to three of our tutorials: UniProt, World Tour, and Overview of Genome Browsers.

Our Introductory UniProt tutorial shows users how to: perform text searches at UniProt for relevant protein information, search with sequences as a starting point, understand the different types of UniProt records, and create multi-sequence alignments from protein records using Clustal.

Our Overview of Genome Browsers introduces users to introduce Ensembl, Map Viewer, UCSC Genome Browser, the Integrated Microbial Genomes (IMG) browser, and to the GBrowse software system. We also touch on WebGBrowse, JBrowse, the Integrative Genomics Viewer (IGV), the ARGO Genome Browser, the Integrated Genome Browser (IGB)GAGGLE, and the Circular Genome Viewer, or CGView.

Our World Tour of Genomics Resources is free and accessible without registration. It includes a tour of example resources, organized by categories such as Algorithms and Analysis tools, expression resources, genome browsers (both Eukaryotic and Prokaryotic/Microbial) , Literature and text mining resources, and resources focused on nucleotides, proteins, pathways, disease and variation. This main discussion will then lead into a discussion of how to find resources with the free OpenHelix Resource Search Portal, followed by learning to use resources with OpenHelix tutorials, and a discussion of additional methods of learning about resources.

Quick Links:

OpenHelix Introductory UniProt tutorial suite: http://www.openhelix.com/cgi/tutorialInfo.cgi?id=77

OpenHelix Overview to Genome Browsers tutorial suite: http://www.openhelix.com/cgi/tutorialInfo.cgi?id=65

Free OpenHelix World Tour of Genomics Resources tutorial suite: http://www.openhelix.com/cgi/tutorialInfo.cgi?id=119

 


Got a genome + transcriptome. Now what?

I was catching up on some mailing list reading last week when I saw an unusual item come across the UCSC discussion mailing list. Someone who is in the process of obtaining genome and transcriptome sequence for a new project asked the UCSC group for guidance on what to do with it. It’s actually a question we’ve been hearing a lot in workshops–people are considering grants for this sort of project, or have plans for a brand new sequencer that’s arrived at their site. I thought other people might consider these recommendations useful information too, so I’m re-posting it here:

Question:

Dear UCSC Genome Bioinformatics,

My name is Padraig Doolan and I am the Program Leader for Expression
Microarrays and Bioinformatics at the National Institute for Cellular
Biotechnology (NICB), Ireland (www.nicb.ie/). We are a publicly-funded
basic science research institute.

Our small bioinformatics group are just starting the process of
analysisng a new genome (and transcriptome) for the Chinese Hamster
Ovary (CHO) cell line which was recently published (Xu et al., The
genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line. Nat
Biotechnol. 2011 Jul 31;29(8):735-41. doi: 10.1038/nbt.1932.) by another
group. We do a lot of functional work on this organism and we’re looking
for some good guidelines (published papers, online resources, etc.)
which might help us map out some achievable goals with regard to the
in-silico characterisation of this genome.

For example, after the sequence is published, what are the next step(s)
in providing relevant information? Lists of SNPs? Predicted
proteome/secretome/numbers of predicted protein types (e.g.
kinases/g-coupled/nuclear-/membrane-localised), etc.?

I’m looking through the Human Genome Project Publications list
(http://www.ornl.gov/sci/techresources/Human_Genome/publicat/publications.shtml)
for inspiration, but this type of analysis output is relatively new for
our group (we are usually more focussed on translational medicine). Is
there any recommended guidelines your institute can suggest for
following in the footsteps of the HGP in in silico analysis of novel
genomes/transcriptomes? Can your organisation suggest a couple of key
papers or maybe a good analysis strategy?

Best regards,
Padraig Doolan

UCSC generally tries to limit their discussion to specifics of the data and software at their site–because that’s their mission, of course, and because they can’t be all things genomics to everyone–they wouldn’t have time for their own work. But this was a special case, and they assembled a very cool answer for Padraig and his team.

The CHO paper that Padraig references I had remembered seeing at the time, but I didn’t investigate further. So I went looking to see if the group had a browser set up, and I was unable to find one. I did find a preview assembly at Ensembl. But I can see why a local group would need more details in their own collection and why they’d want to do some things themselves too. And possibly an easy way to extend the reference sequence with their own data rather than waiting for a big browser team to get to it.

Reply:

Hi Padraig,

I queried our engineers and got this list of recommendations for you:

1) Aligning all genbank mRNAs from Chinese Hamster
2) Aligning all of their own transcriptome data
3) Aligning all of genbank ESTs from Chinese Hamster
4) Mapping human proteins as derived from either the UCSC gene set or RefSeq
5) Mapping mouse proteins from UCSC or RefSeq
6) Doing a multiple species genome alignment with mouse, rat, rabbit,
dog, elephant, opossum, platypus, chicken. Do pairwise alignments as well.
7) Mine the genomic reads and transcriptomic reads for SNPs. Be careful
not to call recently duplicated and only slightly diverged regions
slight divergences as SNPs though.
\8) Run several repeat finders.
9) Run a CpG island detector.
10) Run a good gene prediction program like Augustus.
11) Try to find a wet lab group willing to do some DNAse assays….

I hope this is helpful. Good luck with your work!


Brooke Rhead
UCSC Genome Bioinformatics Group

 

I thought this was pretty much the list of things I’d want to see with a new genome on a new browser. And the reason I think this is especially key is because there’s only going to be more and more of this. With the new sequencing technologies and the data deluge, more groups are going to find themselves with important sequence data for their labs or their local researchers. Could be patients, could be model organisms, could be species. How to proceed with this data is important.

What else would you do? Do you have other recommendations for groups faced with this?

Also today I just happened to note that Jonathan Eisen linked to a paper that might offer guidance for people with new genomes: Important paper on annotation standards for bacterial/archael genomes — readying for the “data deluge”. I think this is great, and a crucial discussion and awareness to have right now. For exactly the same reasons–new folks are going to be faced with assembling and annotating features of new genomes at incredible rates, and we have learned some things about best practices and the needs. Of course, things will evolve–but a few good starting points are really helpful guidance.

EDIT: just got a note from the CHO paper researchers, and they point me to this site for some tools: http://www.chogenome.org/

References:

Xu, X., Nagarajan, H., Lewis, N., Pan, S., Cai, Z., Liu, X., Chen, W., Xie, M., Wang, W., Hammond, S., Andersen, M., Neff, N., Passarelli, B., Koh, W., Fan, H., Wang, J., Gui, Y., Lee, K., Betenbaugh, M., Quake, S., Famili, I., Palsson, B., & Wang, J. (2011). The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line Nature Biotechnology, 29 (8), 735-741 DOI: 10.1038/nbt.1932

Klimke, W., O’Donovan, C., White, O., Brister, J., Clark, K., Fedorov, B., Mizrachi, I., Pruitt, K., & Tatusova, T. (2011). Solving the Problem: Genome Annotation Standards before the Data Deluge Standards in Genomic Sciences, 5 (1), 168-193 DOI: 10.4056/sigs.2084864

Saving your genome views: Ensembl (and UCSC Genome Browser, others)

In the latest update of Ensembl, the developers added the ability to save configurations. This allows you to set your  track views and analysis to a specific configuration and load that configuration at a later time. The blog post linked previously (or here) explains the steps to creating your own configurations you can save and return to. In the future they will be adding the ability to share your configurations with colleagues and other researchers.

UCSC has a similar function they call sessions. You can read more about it here on our blog or go to the sessions user guide at UCSC.

As far as I know, NCBI’s Map Viewer does not have the same functionality (please correct me if I’m wrong).

GBrowse has the ability to save sessions, but since it is an open-source program, it will depend on the specific installation on whether that function is available.

NAR database issue (always a treasure trove)

The advance access release of most of the  NAR database issue articles is out. As usual, this this database issue includes a wealth of new and updated data repositories and analysis tools. We’ll be writing up additional more extensive blog posts on it and doing some tips of the week over the next couple months, but I thought I’d highlight the issue and some of the reports:

There are a lot of updates to many of the databases we know and love (links to go full text article): UCSC Genome Browser, Ensembl, UniProt, MINT, SMART, WormBase, Gene Ontology,  ENCODE, KEGG, UCSC Archaeal Browser, IMG/M, DBTSS, InterPro and others (we have tutorials on all those listed here).

And, as an indication of the explosion of data available (itself a subject of a database issue article, SRA), there are a lot of new(ish) databases on specific datatypes such as MINAS, a database of metal ions in nucleic acids (nice name :D); doRiNA, a database of RNA interactions in post-transcriptional regulation; BitterDB, a database of bitter compounds and well over 100 more.

And I’ll give a special shout out to my former PI at EMBL because I can, Peer Bork’s group has 4 databases listed in the issue: eggNOG, SMART, STITCH and OGEE. (and he and a couple members are on the InterPro paper also).

This is going to be a wealth of information to wade through!

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Video Tip of the Week: Variation Data from Ensembl

Trey introduced me to this “decent collection of video tutorials ” from Ensembl, but he and Mary are currently in Morocco teaching a 3-day bioinformatics workshop & then attending the conference (yes, I am envious!). I am therefore creating this week’s tip based on the tutorials that Trey pointed me to. In today’s tip I am going to parallel a tutorial available from Ensembl on SNP information in order to both: 1) show you haw you can access variation information from Ensembl and 2) compare doing these steps using Ensembl 64 (here in this video) and using Ensembl 54 (archived) (in the Ensembl video).

Bioscience resources often are continuously being developed and improved & it can be difficult to keep videos and documentation up-to-date. That’s why here at OpenHelix we work continuously to keeping our materials up-to-date, with weekly tips on new features and updated tutorials as updated sites become stable.

The Ensembl video (SNPs and other Variations – 1 of 2) is quite nice & provides more detail about the actual Ensembl data than I can in my short movie, but it was done a few years ago on an older version of Ensembl. Since then the resource has been updated, and gone through several new versions of the data. I’m going to follow the same steps that are done in part one of the Ensembl SNP tutorial so that you can see examples of what’s changed & what is pretty much the same. I’d suggest you watch both videos back-to-back to get a good idea of what’s changed, and what types of variation information are available from Ensembl. From that basis I’m sure you’ll be able to watch Ensembl’s second SNP video & apply it to using the current version of Ensembl without much trouble. For more details you can refer to the most recent Ensembl paper in the NAR database  issue, which describes not just variation information but Ensembl as a whole.

Quick links:

Ensembl Browser: http://www.ensembl.org/index.html

Legacy Ensembl Browser (release 54): http://may2009.archive.ensembl.org/index.html

Ensembl tutorial, part 1 of 2: http://useast.ensembl.org/Help/Movie?id=208

Ensembl tutorial, part 1 of 2: http://useast.ensembl.org/Help/Movie?id=211

OpenHelix Ensembl tutorial materials: http://www.openhelix.eu/cgi/tutorialInfo.cgi?id=95

Ensembl Tutorial List: http://useast.ensembl.org/common/Help/Movie?db=core

Reference:
Flicek, P., Aken, B., Ballester, B., Beal, K., Bragin, E., Brent, S., Chen, Y., Clapham, P., Coates, G., Fairley, S., Fitzgerald, S., Fernandez-Banet, J., Gordon, L., Graf, S., Haider, S., Hammond, M., Howe, K., Jenkinson, A., Johnson, N., Kahari, A., Keefe, D., Keenan, S., Kinsella, R., Kokocinski, F., Koscielny, G., Kulesha, E., Lawson, D., Longden, I., Massingham, T., McLaren, W., Megy, K., Overduin, B., Pritchard, B., Rios, D., Ruffier, M., Schuster, M., Slater, G., Smedley, D., Spudich, G., Tang, Y., Trevanion, S., Vilella, A., Vogel, J., White, S., Wilder, S., Zadissa, A., Birney, E., Cunningham, F., Dunham, I., Durbin, R., Fernandez-Suarez, X., Herrero, J., Hubbard, T., Parker, A., Proctor, G., Smith, J., & Searle, S. (2009). Ensembl’s 10th year Nucleic Acids Research, 38 (Database) DOI: 10.1093/nar/gkp972

Customization of views at Ensembl

Hi folks–we’re on the road doing workshops this week, back to near our old stomping grounds of upstate New York, in fact! So I won’t be able to write blog posts. Luckily Ewan Birney of Ensembl published one over the weekend that you should check out. In it he describes some of the newer features in Ensembl that will help you to group and show features in the human genome browser that you might be interested in. Check out his post:

Customising Ensembl Displays

Friday SNPpets

Welcome to our Friday feature link collection: SNPpets. During the week we come across a lot of links and reads that we think are interesting, but don’t make it to a blog post. Here they are for your enjoyment…