genomics
And they're doing it open access style.
Jonathan Eisen and Michael Eisen have each published papers in the PLoS journals using newly available genome sequence data. Jonathan is lead on author on the paper describing the genome sequence of the ciliate, Tetrahymena thermophila. He has blogged about the publication here and provides a wrap-up of a bunch of the coverage here. This single celled eukaryote is a model organism for cell biology, although not at the same level as Saccromyces cerevicea.
Michael Eisen's lab is heavily involved in the Drosophila genomes project. He is the senior author…
Nobel Intent has an excellent summary of a paper in the PNAS pipeline on the origin of new exons in the human genome. The authors compared genes between humans and seven other vertebrates to identify newly arisen exons. They found that many new exons are composed of repeat sequences, such as transposable elements. Also, recently evolved exons are more likely to be alternatively spliced, suggesting there is a "trial period" for a new exon before it can be fully incorporated into the protein coding sequence of a gene.
If we compare sections 1, 2, and 3, we see that section 2 matches very well in a number of different samples, and that there are differences between the sequences in sections 1 and 3.
We also learn something about the people who did the experiment.
At first it appears somewhat odd that there are many matching sequences that are all shorter than the genome and all the same length.
What's up with that?
It turns out that information doesn't have anything to do with the fraction of the genome that matches our query. These short segments are PCR products. They're the same size because the PCR…
Like biology, all bioinformatics is based on the idea that living things shared a common ancestor. I have posted, and will post other articles that test that notion, but for the moment, we're going to use that idea as a starting point in today's quest.
If we agree that we have a common ancestor, then we can use that idea as a basis to ask some interesting questions about our genomes. For, example, we know that genomes change over time - we've looked at single nucleotide changes here and here, and we've seen that large chunks of DNA can move around here.
So, it's interesting to consider…
Have you ever wondered how people actually go about sequencing a genome?
If they're sequencing a chicken genome, do they raise chickens in the lab and get DNA from the eggs? Does the DNA sequence come out in one piece? Why is there so much talk about computers? What are Phred, Phrap, and Consed? What is the Golden Path?
Wonder no more!
You too, can take a virtual tour of the Washington University Genome Center.
I found this really excellent series of short videos that follows two genetics students, Libby and Bryce, as they meet on the bus to the Genome Center and learn about all the steps…
The past few Fridays, we've been comparing human mitochondrial DNA with the mitochondrial DNA of different apes.
We started doing this here, where you can find directions for getting started.
And, we've found some interesting things.
In this installment, we found that humans have practically an entire mitochondrial genome stuck in chromosome 17.
Last week, we found that human mitochondrial DNA is more similar to that of chimpanzees than to gorillas. We found that 90.6% of the bases in human mitochondrial DNA match bases in the Bonobo chimp and 90.7% match bases in the Chimpanzee.
This…
When can a really bad virus be used to do something good?
When we can use it to learn.
The human immunodeficiency virus, cause of AIDS, scourge of countries, and recent focus of ScienceBlogs; like humans, evolves. As one of my fellow ScienceBloggers noted, few biological systems demonstrate evolution as clearly as HIV. In this series, I'm going to guide you through some experiments on HIV evolution that you can do yourself. You won't even have to put on any special clothing (unless you want to), wash glassware or find an autoclave. And, you don't need to any UNIX commands or borrow a…
David Haussler and colleagues have identified a 118 base pair sequence that has evolved really fast along the human lineage relative to the chimpanzee lineage (Carl Zimmer has a good review). In fact, this sequence differs by two base pairs out of 118 between chimpanzees and chickens, and 18 out of 118 between chimps and humans. Differences in relative rates usually indicate changes in selection regimes along at least one lineage. These changes could be due to increased selective constraint along one lineage, relaxed constraint, or adaptive evolution. More on that later.
Also interesting is…
Here are three interesting items that I don't plan on blogging, but are worth linking to:
Here is a news release on indel variation in humans. SNPs are so 20th century. Deletions, duplications, and insertions are the molecular polymorphisms of the future.
Speaking of deletions and duplications, Nobel Intent has a good review of three articles (available here, here, and here) that deal with structural polymorphism and disease on human chromosome 17. Interestingly, the same region examined the three papers harbors an inversion that may confer a fitness benefit.
Finally, totally unrelated…
During these past couple of weeks, we've been comparing mitochondrial DNA sequences from humans and great apes, in order to see how similar the sequences are.
Last week, I got distracted by finding a copy of a human mitochondrial genome, that somehow got out of a mitochondria, and got stuck right inside of chromosome 17! The existence of this extra mitochondrial sequence probably complicates some genetic analyses. One of my readers also asked an interesting question about whether apes have a similar mitochondrial sequence in their equivalent of chromosome 17, and how it compares. We will…
Last week, we decided to compare a human mitochondrial DNA sequence with the mitochondrial sequences of our cousins, the apes, and find out how similar these sequences really are.
The answer is: really, really, similar.
And you can see that, in the BLAST graph, below the fold.
A quick glance shows that the ape with the most similar mitochondrial sequence is Pan paniscus, the pigmy chimpanzee. Next, is Pan troglodytes, the chimp that we see in movies, and last we have Gorilla gorilla.
Then we have a really curious, and unexpected, matching sequence.
Click the picture to see a larger…
A few weeks ago I introduced y'all to Genoinformatics, the hot new abbreviation for Genome Informatics (some sort of derivative of Bioinformatics). I pointed out that I have quite a few international collaborators in this research area, including people in Italy (Geno Informatico), Germany (Jan Informatik) and Mexico (Juan Informatica). I'm hoping that one of them makes it to this CSH/Wellcome conference on Genome Informatics in September. Maybe they could even give a presentation on the Genome-ome.
(Via Post-Genomics.)
We've had a good time in the past few last weeks, identifying unknown sequences and learning our way around a GenBank nucleotide record. To some people, it seems that this is all there is to doing digital biology. They would, of course, be wrong.
We can do much, much more than identifying DNA sequences and obtaining crucial information, like who left their DNA behind on that little blue dress.
Today, we're going to a deeper question about who we are and who are our relatives.
Drumroll, okay, here it comes:
How similar are DNA sequences between humans and apes?
Your assignment is to find…
A few years ago, the General Biology students at the Johns Hopkins University began to interrogate the unseen world. During this semester-long project, they study the ecosystems of the Homewood campus, and engage in novel research by exploring the microbial ecosystems in different sections of the campus. Biology lab students gather environmental samples from different campus ecosystems, isolate DNA, amplify 16s ribosomal DNA by PCR, and check their PCR results by gel electrophoresis.
DNA samples are next sent to the university's Genetic Resources Core Facility , where scientific staff, in…
Or maybe his copy editor reads this blog. Either way, there are changes afoot at the NY Times.
Three days ago I ragged on NY Times science reporter Nicholas Wade for using the word 'decode' when describing genome sequencing. In his latest article he has improved. Last time he wrote about cheap whole genome sequencing; this time he has written about sequencing of a Neanderthal nuclear genome. Now, Wade hasn't entirely kicked the decoding habit:
The project is a collaboration between Dr. Svante Paabo of the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany, and 454 Life…
If you could have practiced science in any time and any place throughout history, which would it be, and why?
That's what they are asking us this week. And, once again, I'm going to skirt the question. You see, it depends on whether the future counts as a "place throughout history." Currently, the future is not history, but it will be history once the future becomes the past. You'll probably need a few minutes to digest that, as I must have just blown your mind. Or not.
My chosen place in time (yeah, I abandoned the whole history thing): the day of the $1000 genome. This is the population…
The National Human Genome Research Institute (NHGRI, sorry no clever acronym) has announced the next primate genome to be sequenced: the white cheeked gibbon (pictured right). This genome is of particular interest due to the large amount of segmental duplications, which are of both medical and evolutionary interest. Here is Francis Collins, the NHGRI Director, pimping the project:
"The gibbon genome sequence will provide researchers with crucial information when comparing it to the human genome sequence and other primate genomes, shedding light on molecular mechanisms implicated in human…
The NY Times has chimed in on cheap DNA sequencing with this article from Nicholas Wade. Wade's article deals with medical applications of affordable whole genome sequencing technologies (with the goal being the $1000 genome). The article, however, is cringe-inducing because Wade has decided that 'sequencing' and 'decoding' are synonyms (I hate it when people do that). Only yesterday did I bitch about science reporters butchering terminology, and Wade goes out and gives me multiple quotes in which he refers to genome sequencing as decoding a genome. Here's a passage that would be readable if…
Here is some light reading for your Sunday:
Mosquitoes sing to each other by flapping their wings. This paper reports sexually dimorphic responses to wing beat patterns in mosquitoes (PZ Myers has a good review). This leads me to wonder whether we can study intra- and inter-specific differences in flight behavior and response, which then gets me wondering whether we can find QTLs responsible for these differences. And (this should come as no surprise to those who know me) I also wonder whether these QTLs will map to within inversions for sympatric species pairs more so that allopatric…
The Scientist is linking to an imaginary1 article from PNAS in which researchers compare the cost of sequencing microbial (I'm guessing they mean bacteria) genomes using the traditional Sanger method and the hot new technology developed by 454. Not so surprisingly, they find that a hybrid method -- ~5x coverage with Sanger followed by a couple rounds of 454 -- is the most cost effective strategy. I say it's not surprising because usually some intermediate solution wins out in science.
The Sanger method is nice because you get paired end reads from clones, which are very helpful in assembling…