ht: Pharyngula

Hey, btw, if you want to see what they are singing about, check out the cute little stickleback’s genome at UCSC, Ensembl, or read a bit more .

Mark this database (as with many others) as one whose acronyms were created to fit the name. Barbels are the whiskers on a catfish and cBARBEL stands for “Catfish Breeder and Researcher Bioinformatic Entry Location.” See, I was thinking more along the lines of “Catfish Breeder And Researcher Research Entry Location” or Catfish Barrel, but that is too culturally obscure and specific isn’t it? cBARBEL is good .

All kidding aside, it’s a great start to another agriculturally important model organism database.

• A Cuban bioinformatics group announces updates to their Cytoscape plug-in. “A new update of SysBiomics database is ready. SysBiomics contains the data feeding BisoGenet network building process; it was updated with most recently versions of protein-protein interactions sources (DIP, BIOGRID, HPRD, MINT and INTACT), GO and KEGG databases as well as the latest information on genes an proteins form Entrez Gene and Uniprot .” Bioinformatics Group http://bio.cigb.edu.cu/ Cool–I think that’s the first tool I know about from Cuba.  [Mary]
• “In October’s “Nature Genetics”, and just in time for pie-making: http://www.ncbi.nlm.nih.gov/pubmed/20802477 …but where’s the gene that keeps the doctor away?” [Trey, via a colleague's email ]
• Cool new site on the History of Vaccines. Hat tip to Tara at Aetiology. [Mary]
• RT @kshameer: RT: @suganthibala: 200 exomes resequenced, found many rare nonsyn SNPs http://bit.ly/bjm2Q6 http://bit.ly/ctQJ59 #genomics #bioinformatics [Mary]

As Razib points out, and as you can read in the announcement at UCSC, the UCSC Genome Browser now has the draft data up in the hg18 genome assembly. Like the coding region allelic differences data, selective sweep data, etc. With the Neanderthal data now being in the UCSC Genome Browser and other data sources, we can pull apart that data, analyze it.. (and you know I’ll be putting my personal genome in a comparative track when I ever get it. Just curious ya know).

(btw, there is an interesting photo, copyrighted… so I won’t post it here, you might want to check out. There’s an interesting story there, how our illustrations of Neanderthal have evolved over the years to be more ‘humanizing’ as we learn that they made tools, had culture and now… are part of our ancestry…”)

I am itching to go play there and see what I can see, as I am sure many scientists are. It’s also fascinating to be in this world of huge amounts of data coming quickly. I think a lot of paradigms will be shifting for a while.

UCSC Main site: http://genome.ucsc.edu and click Neandertal from left navigation button.

This next post in our continuing semi-regular Guest Post series is from Eric Lyons, of CoGe at the University of California, Berkeley. If you are a provider of a free, publicly available genomics tool, database or resource and would like to convey something to users on our guest post feature, please feel free to contact us at wlathe AT openhelix DOT com.

Thanks both for the prior CoGe post (editors note: a tip of the week on GoGe) and the invitation to write a bit about CoGe.  Since most people are probably not familiar with CoGe, let me begin with how it is designed:

CoGe’s architecture and philosophy:  Solve a problem once

CoGe is a web-based platform for comparative genomics and consists of many interconnected web-based tools.  The entire system is hooked up to a database that can store any version of any genome in any state of assembly from any organism (currently ~9000 genomes from ~8000 organisms). Each of CoGe’s tools is designed to do one task (e.g. search and display information about a genome, compare two genomes and generate syntenic dotplots, search any number of genomes for similar sequence, manage a list of genes, etc.), and are linked to one another. This means that there is no predefined analysis workflow. Instead, people can begin exploring a genome of interest, compare it to what they want, find something interesting, explore that, finding something else, explore that, etc.) People anywhere in the world can perform computationally intense analyses by clicking a few buttons on a web-page, and letting our servers crunch away on whatever genomes we have currently loaded in our system .  Since each tool is web-based, links are used to move from tool to tool which creates an easy way to save an analysis for future work or to send to a colleague. This also has the benefit that as we develop new tools to solve a specific problem, we can generalize the solution, and plug it into CoGe’s database and connect it to its pre-existing tool set. Overall, this allows an easy way for us to expand CoGe’s functionality.

This paradigm has its roots in CoGe’s genomes database. Many genomics systems require a separate database for each genome being used, which usually means significant administrative overhead (aka headache) when a new genome is deployed.  Instead, CoGe’s database is designed to store any number of genomes simultaneously. That way, as new genomes are released, they just get loaded into the database and immediately become available for analysis. For those interested, if there is a genome you’d like to see loaded into CoGe, just send me an e-mail with some necessary information (http://genomevolution.org/r/49z). I have a variety of programs to load genomes into CoGe. Some places, like NCBI, have a consistent data format (genbank record) for their data, and I have programs that periodically run through their system check for new genomes or new versions of genomes and load them automatically. Other place, like JGI, use GFF3 for their annotations, but frequently change exactly what identifiers they use in the file to denote feature types (e.g. “3′” versus “three-prime”), names and annotations. For those places, it takes a bit more time to figure out what’s important, but I can usually get genomes loaded in a couple of hours to days (depending on regular work stuff).

If you are interested in learning a bit more about CoGe’s system architecture and database design please see: http://genomevolution.org/r/4a0

Designing new tools in CoGe — zombie-style: “the need for biologists’ brains”

While I’m trained as a biologist, there is no substitute for the expertise and depth of knowledge that comes from years of working with a group of organisms.  By working closely with biologists who have specific questions about their genomes of interest, CoGe’s team develops new solutions or extends existing tools.  As these solutions are tested and validated, some become the basis for new tools in CoGe.  What is particularly fun about this process is that many times, tools developed for one problem can be used to solve problems that were not originally intended.

An example of this type of development was the recent extension of SynMap, CoGe’s tool for generating syntenic dotplots between any two genomes.  Working with a group sequencing E. coli genomes in order to determine polymorphisms, I developed a hybrid assembly pipeline that would first use de novo assembly to generate contigs, and then use syntenic comparison to a reference genome to order and orient the contigs.  The second part of this assembly process was integrated into SynMap as an option (http://genomevolution.org/r/4a1).  While useful for putting together small genomes with a relatively close reference genome, this syntenic path assembly can also be used in generating very approximate assemblies between very divergent genomes — for example grape and potato (~120MYA):  http://genomevolution.org/r/4a2.  This type of analysis turned a 68,000 piece genome into a visual pattern that confirms that these two genomes have  nearly an identical genome structure, as well as evidence for ancient whole genome duplication events.

Another example using SynMap is comparing differences in genome assemblies.  While designed to identify syntenic regions within and between genomes, it works equally when comparing two version of a genome.  These two examples comparing versions 1 and 2 of the grape genome (http://genomevolution.org/r/49y), and versions 2 and 3 of the medicago genome (http://genomevolution.org/r/49x), made me appreciate how much salt to take when analyzing genome structure evolution.

Learning to use CoGe:

Using CoGe is very much like the old “choose your own adventure” books.  Which is fun for its open-ended story-lines, but does mean that there is a learning curve to the system.  To help with this learning process, there are several text and video tutorials available that are set up as “How to do [something]“.  You can view them at: http://genomevolution.org/r/4a3 .   Also, there is some necessary background information that will help you along an analytical path.  Knowing something about the types of patterns for which you are searching, or the types of information you’d like to obtain, is required.  To help with that aspect of learning about comparative genomics, and genome structure and evolution in general, we maintain a wiki to describe these terms and provide links to CoGe for analyzing and visualizing different patterns of genome structure and evolution.  Still, there are many tricks that you learn by doing, and the best way to start is finding a genome of interest, looking at it, and comparing it to other genomes.

What’s coming up for CoGe:

For the most part, CoGe is under constant development.  New genomes are loaded, tools are tweaked, bugs are squashed, new features implemented, and new tools deployed.  The latest set of tool developments are:

Much more significantly, we will be rolling out a new version of CoGe as a whole in the next 2-4 months (we are waiting for new hardware).  This will sport a new UI layout, some changes to CoGe’s genomes database, and updated system code (e.g. update code-base for new version of dependent modules.)

How to help:

If any one is interested in helping:

1. Provide feedback on what is working and what is not.

2. Make a tutorial.  Just a couple of pictures and some words can go a long ways to help someone else. Or better yet, a 5 minute video.

Credits:

I have to thank several people who have been instrumental in putting CoGe together.  Their programming, algorithm, visualization, and UI skills have been and continue to be invaluable:  Josh Kane, Brent Pedersen, James Schnable, Shabari Subramaniam,  Haibao Tang

Eric Lyons

• A great list of bioinformatics analysis algorithms and tools. [Trey]
• BMC has a new journal entitled Mobile DNA (and one of the editors-in-chief was my Ph.D. advisor, Thomas Eickbush). Some excellent first papers you should check out. [Trey]
• Interesting study on genetically engineered plants: “The impact of transgenes is basically limited to their immediate function” for the interview, paper is here. [Mary]
• Speaking of BMC, BMC Biology now incorporates the Journal of Biology (they had a ‘relaunch’ of the journal at the Experimental Biology conference, across the aisle from where we were.. cake, champagne and t-shirts! . Hey, check out the site for the free iPad giveaway. Funny, I counted 3 iPad giveaways in the exhibit hall.. [Trey]
• Found this as I was writing an article on informal education in bioinformatics for a special issue of Briefings in Bioinformatics. It is from NatureNews: “US seeks to make science free for all“   [Jennifer]
• Xenopus!  I always liked that name.  In fact, am now kicking self that I haven’t used that for some online persona….Anyway, Xenopus tropicalis, first amphibian sequence now available, see Science.  [Mary]

to assemble a genomic zoo—a collection of DNA sequences representing the genomes of 10,000 vertebrate species, approximately one for every vertebrate genus. The trajectory of cost reduction in DNA sequencing suggests that this project will be feasible within a few years. Capturing the genetic diversity of vertebrate species would create an unprecedented resource for the life sciences and for worldwide conservation efforts.

10,000 vertebrate genomes. That’s a lot. In fact, that’s 50 fold greater number than is currently in progress (that list is chordata, at 208, including multiple genomes form one species, humans), and nearly 500 fold the number of complete vertebrate genomes available. An ambitious goal to say the least. The participants are multitude including the coordinators David Haussler (Howard Hughs Medical Institute, UCSC), Stephen O’Brien (Laboratory of Genomic Diversity, National Cancer Institute) and Oliver Ryder (Institute of Conservation Research, San Diego Zoo).

The three coordinators’ institutes suggest some of particular benefits that they hope to get out of this project: medical data, evolutionary data, conservation efforts. I do believe such a project will indeed bring many of those benefits. I remember 20 years ago the arguments about the Human Genome Project (too expensive, too ambitious, benefits won’t be commiserate, big science pushing out basic research). I think it’s arguable that the worst fears were not realized and that there have been a number of benefits already and soon to come. 10k vertebrate genomes now seems feasible and beneficial.

Of course, one could hope there’d be a plant project and an invertebrate project down the pike?

And, it goes without saying, if you thought there were database funding, accessibility, usability, etc issues now…

Recently, I had the opportunity to give a short workshop at the Genetics and Genomics of Infectious Disease conference in Singapore. It went well, and I learned a lot. Afterwards, my family came out to SE Asia for a vacation, but because of they way frequent flyer miles are, I had 5 days of free time. Malaysian Borneo, here I come!  I spent three days hiking through the Sarawak jungle with a new-found British friend. It was fascinating. One of the most fascinating aspects for me were the stars at my feet.

We took a short night-hike and when my eyes got adjusted to the deep darkness, I noticed what looked like stars on the ground. We turned our flashlight back on, but saw nothing. Off, stars, on, nothing. I pinpointed one of the pin points of light and put my flashlight on it. It was a rotting piece of wood. I picked it up, turned off the light and the rotting piece of wood was glowing in the dark like there was a small LED lights running through it.

Amazing. I learned that this was a bioluminescent fungus. I was fascinated. I had never heard of bioluminescent fungus before, but life rarely surprizes me any more, there are so many strange and wonderful lifeforms on this planet.

But what did fascinate me was the question “why?”  What was the evolutionary origins of bioluminescence in fungus? I knew about bioluminescence in Insecta (I used to collect lighting bugs as a kid in my home state of Virginia), in Cnidaria (I saw bioluminescent jellyfish in the Monterey Bay Aquarium), in vertebrates (all those nature shows as a kid.. and adult.. paid off with movies of angler fish), bacteria and much more, but I hadn’t heard of it in fungus before. If I had paid attention in my reading of The Adventures of Hucklberry Finn in my highschool reading class, I would have learned that they do indeed exist, in fact, perhaps in my own back yard as a kid.

The adventures of Huckleberry Finn (Tom Sawyer’s comrade) By Mark Twain

I understood the evolutionary advantage of bioluminescence in lightning bugs has to do with sex (gotta attract that mate!), and for fish it can be sex or prey, etc. But why fungus? Ok, so not every feature of a creature needs to have an evolutionary advantage, in fact, a lot doesn’t. But I spent the next few evenings in the wilds of Borneo trying to figure out why something that would seem to have a metabolic cost so high would evolve in a fungus? Symbiotic like some bacterias? Couldn’t be to ‘attract a mate?’ could it? Damn, where was google when you need it?

Well, of course one of the first things I did was google ‘bioluminescent fungus’ and found that one of the possible advantages is that it attracts insects. Why would this be an advantage? Well, apparently these mushroom species often grow in the understory of thick forests and jungles, little air movement to spread spores. So, a nice friendly insect would be a perfect carrier of spores. How to attract them? Ah, yes… lanterns seem to be great attractor of insects as we humans have learned and put to our advantage. It seems so have some several tens of species of fungus, or at least through a long process of natural selection and not an engineering team. Interestingly, one of the scientists studying these species of glowing mushrooms lives in my backyard at SFSU (I’m not sure how, but that seems appropriate to me, studying glowing mushrooms in San Francisco).

Interestingly, just last week, we were giving a UCSC Genome Browser workshop at UC Berkeley. One of the questions that arose was for fungal genome resources, specifically browsers and comparative genomics. The new mycologist was lamenting that there wasn’t more genomic resources. I had to admit, I didn’t know off hand so we did a quick search and found Fungalgenomics.org. Of course, it’s using GBrowse software (which we have a publicly available tutorial on btw . We also found the Comparative Fungal Genomics Platform (CFGP) at Seoul National University (hey, I did a semester abroad there over 20 years ago, the strained connections just multiply don’t they? ).

So, now I’m thinking I should get a second Ph.D. on fungal evolution. Well, before I do that, I think I might just expand my search of fungal genomic resources.

Know any?

Speaking of which, the Exploratorium, an excellent science museum in my fair city, has a great exhibit (on site and online) on the ‘how we know things’ and how science works. This exhibit is specifically on the origins of humans and Neanderthal DNA and the research at Max Planck figures prominently.