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  • My name is Sue Wessler. I am a Professor of Genetics at the University of California, Riverside.

  • And my lab studies transposable elements.

  • The title of these two presentations are The Dynamic Genome.

  • In the first talk I introduced transposable elements by describing their discovery by Barbara McClintock,

  • how they move, and how that discovery over the years was recognized as a major revolution in biology

  • as it became appreciated that transposable elements

  • are the major component of most of the genomes of higher eukaryotes.

  • In this talk I am going to go into detail about how my lab

  • studies the evolutionary impact of transposable elements on genomes.

  • And how we develop strategies to identify elements

  • that have an impact on transposable elements.

  • I have divided this talk into three parts.

  • In the first part I talk about the transition from genetic approaches to genomic approaches

  • in order to identify elements that in fact impact genome evolution.

  • The elements that were discovered in my lab are called MITEs,

  • and I will tell you about that discovery in the second part of this talk.

  • And in the final part of the talk I will tell you about how MITEs

  • are able to increase their copy number in the genome without harming the host significantly.

  • So to review the first part, we talked about the genetic analysis of transposable elements,

  • how genetic analysis led to the discovery of transposable elements,

  • and I used this spotted corn kernel as an example to tell you really how powerful the genetic analysis was.

  • So when you see a spotted corn kernel like this,

  • we know, the geneticist knows, that the reason that kernel is spotted

  • is because there are active transposable elements.

  • There are... that is the spots reflect the movement of transposable elements.

  • The other thing the genetics tells us is exactly where in the genome that active transposable element is.

  • So for example, here when we are looking at spotted corn kernels,

  • we know that there is an active transposable element, in other words, one that is capable of moving

  • in a gene responsible for kernel pigmentation.

  • The other thing that the genetics tells us is the type of element that's there.

  • And I described at the beginning of the first talk the difference between autonomous elements,

  • that is, ones that encode transposase, and non-autonomous elements.

  • Those are the elements that don't make transposase

  • but are able to move if there is an autonomous element in the genome.

  • McClintock and others were able to deduce this just by looking at the behavior

  • of transposable elements in crosses.

  • Now that is the good news about the genetic analysis.

  • Unfortunately the genetic analysis is limited in its scope.

  • And that is that by its very nature genetics depends on the analysis of mutant alleles,

  • and so the transposable elements that were being studied were the ones causing mutations.

  • They were mutagenic elements.

  • Now because these elements cause mutations, there aren't many copies of them in the genome.

  • So, I mentioned in the first talk that genomes are up to 50-80%

  • of the genome sequence is derived from transposable elements.

  • However, the elements that cause mutations are not those elements.

  • And you can understand that an element that causes mutation is eventually,

  • if its copy number increases too high, will kill the host.

  • So these are.... these are a special class of transposable elements that cause mutations.

  • And as such these elements really have a minimal impact on genome evolution.

  • They're bad. They are really bad.

  • So McClintock as I also described in the first talk,

  • not only discovered transposable elements,

  • but she hypothesized that they were also tools that diversify organisms.

  • And to review, she hypothesized that transposable elements that are in the genome

  • do not move around frequently,

  • that there are conditions, such as changes in climate for example,

  • that could activate transposable elements.

  • that this activation would generate genetic diversity in the population

  • by increasing the frequency of mutation,

  • and that some of these transposable element mutations may be adaptive.

  • I will come back to this scenario at the end of the talk

  • when I show you how the elements that we have identified

  • in plant genomes fit this scenario very, very nicely.

  • So to review, I described in the last talk the two general classes of transposable elements in the genome.

  • The first class, which is called Class 2,

  • are DNA transposons. These are the elements that were discovered by McClintock genetically.

  • We know these elements have a typical structure of terminal inverted repeats,

  • that they encode a single protein necessary for the movement of the element, and that is transposase.

  • The other class of elements which I am not going to go into extensively in this talk,

  • and nor did I in the last talk, are called retrotransposons.

  • These are elements that encode reverse transcriptase,

  • and they move through an RNA intermediate, again by mechanisms that were described in the last talk.

  • I also want to re-introduce you to transposable elements families

  • because we are going to revisit families in this talk.

  • That transposable element families contain autonomous elements.

  • That is the elements that encode transposase.

  • And non-autonomous elements these are elements that don't encode transposase,

  • but are able to move utilizing the transposase that's encoded by the autonomous element.

  • Something else that I discussed in the first talk is just how prevalent transposable elements are in genomes.

  • So this was a human gene where I showed you the exons that are in the gene,

  • and this is really a pretty typical gene. And what we find is that

  • in the non-coding regions, there are many, many, many transposable elements,

  • that some human genes have over a hundred transposable elements in their introns.

  • Now the element that I am referring to, most of the elements in the human genome are called Alu.

  • They are a class 2 retrotransposon which are present at an astonishing copy number of over a million copies.

  • It's almost ten percent of the human genome.

  • Now one of the things, if we are interested in the evolutionary impact of a particular transposable element,

  • one question we could ask is, so for example, if we picked out one of these elements,

  • we could ask what happened when it inserted?

  • Did it change the expression of the gene?

  • These are the questions, if we are interested in the evolutionary impact,

  • these are the questions that we would like to be able to address.

  • Unfortunately we can't do that with the human elements, most of the humans elements.

  • And that is that the insertions may have changed gene expression,

  • but we have no way to address that now. And the reason is

  • first of all in the human population, virtually all of us, 99.99% of us, have these insertions,

  • have exactly these insertions. That's because these elements moved millions of years ago.

  • So what that means is that if we want to know how did the insertion

  • of a particular element change the expression of a gene, if at all, we are too late.

  • So what we want to do is identify a group of organisms

  • where these high copy number elements are actively transposing.

  • And I am going to talk about that strategy- that's exactly what this talk is about.

  • So here is our strategy for analyzing the impact of transposable elements on genome evolution.

  • And this is a figure from the previous talk which is sort of a typical region of a genome, a grass genome,

  • and this is from the barley genome,

  • and the blue boxes are genes and the triangles are transposable elements.

  • So in barley about 85% of the genome is derived from transposable elements.

  • So the strategy that we would like to do to identify evolutionarily relevant transposons

  • is to find a species that is in the midst of genome expansion.

  • So where these high copy number elements are moving, are increasing their copy number.

  • And we would then go ahead and identify and isolate an active element.

  • So this is not one of the mutagens that was identified by the geneticists,

  • but in fact these are the high copy number elements that are now increasing in copy number.

  • Ok, so we would then ask the question,

  • how is this element able to increase its copy number so extensively without harming the host?

  • What are its strategies for success? And success in this case is defined by being able to increase

  • your copy number without killing or harming the host, and possibly even by benefiting the host in some way.

  • And we are going to address all of those issues in this talk.

  • So in the first talk we talked about the discovery of transposable elements in maize.

  • Well, maize is a member of a larger group of organisms. It's a grass.

  • These are the most important organisms for human health, for the human diet.

  • More calories come from members of the grass clade than any other group of organisms on this planet.

  • We are familiar with maize. The other members of the grass clade is: rice,

  • which actually is the most important source of human calories,

  • sorghum, which is also a very important crop plant especially in Africa,

  • and finally barley. Another member of this family, which I am not showing is wheat.

  • So what you would notice here, those numbers are the size of the genome.

  • The maize genome is about the same size as the human genome, at 2500 megabasepairs.

  • The rice genome is much, much smaller. It is almost ten-fold smaller.

  • And what is remarkable is that here are these plants that are so incredibly similar,

  • yet their genomes size differs dramatically, by more than ten-fold.

  • So these organisms diverged from a common ancestor only about 70 million years ago.

  • And the main reason for this difference in genome size is this dramatic amplification,

  • expansion of transposable elements.

  • And this slide helps explain in part how that can happen.

  • These organisms, the grasses, in fact have about the same gene number.

  • They have about 30,000 genes, give or take a few 1000.

  • And so the genomes of these organisms are largely syntenous. The genes are mostly in the same order.

  • So in rice you could see, with smallest genome, I've shown three genes there in pink, yellow and blue

  • that are pretty close together. In maize those genes are further apart.

  • And in rice those genes, I'm sorry, in barley those genes are even further apart.

  • So what's happening here is transposable elements,

  • which are the squares and circles and ellipses in between,

  • transposable elements are inserting massively between the genes and expanding the genome.

  • So this is largely responsible for the difference in genome size.

  • And it's the safe havens that transposable elements can go without harming the host.

  • So I want to show you a little bit at a higher resolution

  • to show you what elements are involved.

  • So I introduced to you before that there were two types of transposable elements.

  • There were Class 1 elements which are retrotransposons,

  • and then Class 2 elements which are DNA transposons.

  • The retrotransposons which are generally these big elements that make RNA copies.

  • That RNA copy is then made into double stranded DNA.

  • The double stranded DNA can insert back into the genome.

  • It almost make copies like a printing press, like an old fashioned mimeograph machine,

  • which most of you probably never experienced.

  • So what you see here is that the huge blocks could be hundreds of kb

  • that separate some genes in the grass genome

  • are largely retrotransposons that are inserted into each other,` literally driving the genes apart.

  • So as we say it's almost like genes sitting in a sea of transposable elements.

  • Now these are not the elements that we are going to talk about today.

  • Instead we are going to talk about elements that I think are probably more involved in diversifying the genome.

  • And that is, so what I have done here is I've blown up the area of one gene

  • and broken it up into its exons and introns.

  • And I've shown you that sitting in plant genes, much like the Alu elements that are inserted in human genes,

  • are little elements, little transposable elements called MITEs.

  • These are DNA transposons. They are non-autonomous elements

  • and in the next few slides I am going to tell you a little bit more about MITEs

  • because they were discovered in my lab at least 2 decades ago.

  • So the way the first MITE was discovered was it was an insertion sitting in a mutant gene.

  • And this is the work of several people in my lab, especially Tom Bureau and Rita Varagona.

  • What you see here is a maize gene, and sitting in it is a little DNA transposon,

  • disrupting the gene, causing a mutation.

  • When Tom Bureau isolated this transposon, like I said,

  • this was back in the early 90s, when he isolated the transposon,

  • he took the sequence and compared it to several other maize genes or plant genes

  • that had been deposited into databases. This was before you did BLAST searches.

  • This was in the early 90s when there were some wildtype genes that had been sequenced.

  • And what he found was that in fact sequences like this little element

  • were present in many of the other wildtype genes.

  • And I am showing that here. So what you see is here are some wildtype genes

  • that were revealed by this computer search.

  • And so for example, this gene has an insertion in an intron.

  • So these are normal genes. So these insertions are in non-coding regions.

  • They are not effecting the expression of the gene.

  • This one is in the 5' promoter region.

  • And the one at the end here is in the 3' region.

  • So he discovered these elements, they are called... MITEs stand

  • for miniature inverted repeat transposable elements.

  • What is similar about these elements is their structure.

  • Their sequence may not be similar and is not similar when you go from organism to organism.

  • But these are the most predominant transposable element type associated with the genes of plants.

  • So let me tell you where MITEs fit in in a transposable element family.

  • I told you before about autonomous elements. I told you about non-autonomous elements.

  • MITEs are non-autonomous elements,

  • but they have no coding capacity. So in this case I have shown them.

  • They look like they are a deletion derivative of the autonomous element,

  • but have none of the coding sequence of the transposase.

  • That is one possibility. The other thing, first of all, MITEs are very, very small.

  • Very short. And they can attain very high copy numbers.

  • So where as most non-autonomous elements in the genome may be five or ten of them,

  • maybe up to 50, there can be 1000s of MITEs.

  • I am going to talk more about that in a bit.

  • Here's an example of MITEs that look like an autonomous element that's in the genome.

  • Its terminal inverted repeats, its ends, are very, very similar.

  • So we can look at this and say, Ah! This autonomous element must move these MITEs.

  • We've done lots of experiments over the years to validate that.

  • There are other MITEs in the genome that don't look like any other element that's in the genome except for the ends,

  • except for the terminal inverted repeats.

  • And I think you might remember from the first talk that the terminal inverted repeats

  • are critical because that is where the transposase binds and facilitates the transposition of the element.

  • So MITEs are short, miniature inverted repeat transposable elements,

  • I won't say that anymore, I'll just say MITEs from now on.

  • They are short elements. They can attain very, very high copy numbers unlike most other DNA transposons.

  • And that is what is relevant here. That its a high copy number elements that I will argue

  • are the ones that have an impact in diversifying genomes.

  • Not the lower copy number elements that McClintock and others had discovered cause mutations.

  • So fortunately, MITEs are not restricted to plant genomes.

  • And I say fortunately because a lot of my work over the years was funded by the National Institutes of Health,

  • and if you are working on a plant system, it's nice to be able to say that what you find in this plant

  • will be relevant to human health. And we all try to say that.

  • So in this case this is a composition of transposable element composition of a mosquito genome, Aedes aegypti.

  • And it turns out that about 16% of this genome is due to... is derived from MITEs.

  • From transposable elements.

  • So what I would say in my grant application is that by understanding how MITEs move,

  • and how they increase their copy number,

  • in a plant genome we can extrapolate...

  • we can use that information to understand how they expand in animal genomes.

  • And there are MITEs in zebrafish, and in most higher eukaryotes, but none of them to date have been shown to be moving.

  • So the other thing about MITEs that's really relevant is that they are preferentially in genic regions.

  • Now remember again from the first talk we said that very small percentage of the genomes of plants are genic.

  • So it may just be like 10 or 20% are where genes are, but MITEs preferentially go into genic regions.

  • And we will talk a little bit later about that preference.

  • So we have this situation here where we have these very high copy numbers,

  • so we have elements that expand, that increase their copy number,

  • and they go into genes, but they are not killing the host.

  • So how do they do that? So not only do they not kill the host, but they seem to be beneficial.

  • So what I've shown here are two examples of wildtype genes.

  • In the first one we see the red exons, and what I am showing is that transcription,

  • the sequences that initiate transcription,

  • are actually derived from the MITE sequence that is in the promoter region.

  • Similarly, there are other MITE examples of wildtype genes

  • that have MITEs that in fact carry the sequences for transcription termination.

  • So MITEs carry in some cases, regulatory sequences that are used by genes.

  • MITEs also contribute to allelic diversity.

  • So what I have shown here is the same gene

  • or alleles of the same gene, one with a MITE and one without.

  • So here would be a wonderful example to be able to say, okay,

  • I have a gene without a MITE, I have one with a MITE, what is... how do they differ in expression?

  • And that may be able to tell us what is the impact of insertion of that MITE.

  • Unfortunately, when we look at a database, and we harvest all of these related sequences and genes

  • it turns out that these genes don't just differ, the alleles don't just differ by the presence or absence of the MITE sequence.

  • They have many other single nucleotide polymorphisms, indels, that differentiate them.

  • And this indicates that this insertion happened a very long time ago.

  • So these are essentially dead elements, and really we can't tell by

  • comparing the expression of these two genes what the impact of the MITE was

  • because there are lots of other differences between those two genes.

  • So as I said, these are old insertions.

  • Okay, so what we need are active MITEs in order to understand how they...

  • and we need to catch them in the act of increasing their copy number.

  • So what we need is a situation like this, and I am going to come back to this later,

  • and that is two genes that differ only in the presence or absence of the MITE.

  • Then we can compare the two genes and say, okay,

  • if this one for example is expressed in the roots and the leaves, and this one is just expressed in the roots,

  • we can say that the MITE sequences allowed this gene to be expressed in a different tissue.

  • It diversified its expression.

  • Ok. So we want alleles that only differ by the presence or absence of the MITE.

  • So now I am going to.... the next part of the talk is that quest,

  • that search for active MITEs.

  • So what I am showing here is a phylogenetic tree.

  • And it's called a star phylogeny. So the way we interpret these,

  • so what's done is you take all of the MITE sequences that are in a genome,

  • you put it into a computer program, and it generates a tree

  • that tells you how these sequences are related to each other.

  • So this is, what you see, what this tells us, the story that this tree tells us

  • is sometime long, long ago, there was a single element or a couple of related elements.

  • They increased their copy number. They were all identical. They increased their copy number.

  • And then somehow transposition stopped and over the thousands or millions of years these sequences drifted.

  • They accumulated mutations and now you see this star phylogeny.

  • So that's a story that this tree tells us.

  • And that's a typical MITE family tree.

  • Okay, so what it tells us is that MITEs amplify rapidly from one or a few nearly identical copies.

  • Ok. So if we look at a typical, the genome of a higher plant or animal,

  • what we see are lots of bursts.

  • And I have, for convenience, I am showing the same tree that I have cut and pasted

  • but in fact each of these trees should be different

  • since it is a different MITE that started out as one copy and then increased their copy number.

  • So forgive me because these trees are not easy to draw.

  • So you see there are just, genomes are filled with MITEs, tens of thousands of them

  • that all started from a few elements, and burst, but over evolutionary time.

  • So in order to understand how those elements amplified without killing the host

  • we need to, as I said before, catch a MITE in the act of bursting,

  • and that is that central region, this red circle here,

  • where the element is rapidly amplifying, and that is what the rest of this talk is about.

  • So in order to identify active MITEs, my lab had to switch directions.

  • And I think this happens frequently that sometimes the organism you work on

  • isn't ideal for the questions that you want to address.

  • And so this was from the first talk I showed you-

  • this was the first maize genetics group, or the maize genetics group,

  • R. A. Emerson's group at Cornell. And there is a picture of Barbara McClintock at the end.

  • And here's the spotted kernels that she used to discover transposable elements.

  • And I mentioned that this is a shed in the Cornell plantation.

  • And this picture was taken in 1929.

  • Well, what we did in 2002 is we got a new group of researchers together,

  • involving Susan McCouch at Cornell, Sean Eddy, who at that time was at WashU,

  • Zhirong Bao, many other people,

  • and we took a picture in front of the same shed in the Cornell plantation.

  • And so this is our collaborative group that focused on identifying active MITEs,

  • and to do that we had to switch organisms, and we switched to rice.

  • And I will tell you in a second why we did that. I think I mentioned that maize has this really, really large genome

  • of 2500 megabasepairs. That it's about the same size as the human genome, very dynamic, very complex.

  • The rice genome is significantly smaller, almost, about 6 fold smaller.

  • And it is of this group of grasses that I talked about before.

  • It has the smallest genome of the cereal grasses, 350 megabases.

  • And for that reason, and plus because it is so important to human health,

  • it was the first grass genome that was completely sequenced.

  • And for us to do this project we required the complete genomic sequence in order to identify the active MITE.

  • We weren't going to use a genetic approach. We were going to use a computational approach,

  • and that is what I am going to talk about.

  • So here is the strategy.

  • We had the complete genome sequence of rice, and when I say we,

  • the person mainly responsible for this- two people- Zhirong Bao who is a graduate student in the lab of Sean Eddy,

  • who, as I said, was at WashU at that time.

  • And Ning Jiang who was a graduate student in my lab.

  • Zhirong Bao had devised a computer program called RECON.

  • What this program does is it takes.... so what we are looking for...

  • We are trying to find an element, a MITE, in the genome sequence, that has the features of an active transposon.

  • What are those features? First of all, a transposable element will have many copies.

  • So we are looking for something that has multiple copies,

  • but we are looking for something where those copies were generated very recently.

  • So those copies, remember, we are looking at the red region of that phylogenetic tree,

  • those copies should be identical or nearly identical.

  • Because when an element duplicates the two copies are identical, and over time they drift,

  • and that is what the star phylogeny is there.

  • So what was done, we used, we took the rice genome sequence,

  • compared it to itself, and in that way identified high copy number repeats.

  • And in about three thousand repeats were identified. These could be genes.

  • These could be transposable elements.

  • Now then the human being has to come in, or the human being came in devising the RECON protocol,

  • but what you have to do, and this was done by Ning Jiang,

  • she manually searched each of these three thousand families to try to find a sequence that looked like a MITE.

  • And she found one, obviously, or I wouldn't be talking about it now.

  • K, so what she found was a family that had fifty-one nearly identical copies in the sequenced genome,

  • which is called Nipponbare. That is the name of the strain.

  • There were 51 copies in this genome.

  • And it had the structure of a MITE.

  • And here it is. It is called mPing, and it is 430 basepairs in length.

  • So the problem though is that when you do computational analysis,

  • and you identify something that looks like it should be active,

  • you've got to go back to the bench and prove that it is active.

  • This is what we call a candidate. It's a candidate in development.

  • You've got to then do an experiment that validates, that shows it moving around.

  • So what Ning did was she took cells that were in the freezer for 4 years.

  • She popped these cells out, and we had a cell culture.

  • So cell culture is an environment where DNA... where transposable elements have been shown to move around

  • in other situations. So what we had is we had the DNA from the plant, two plants,

  • one before cell culture, and then after cell culture.

  • The question we are asking is can we see the movement of the mPing element.

  • And we use a technique called transposon display. This is what we used years ago.

  • Now all you have to do is sequence the genome. And we'll talk about that later.

  • But this was the technology available to us at the time.

  • And what you do is you make a primer,

  • and here we made a primer that was near the end of the mPing element.

  • And then what we are going to do is we are going to take genomic DNA,

  • we are going to cut it up with a restriction enzyme.

  • And we are going to put adaptors at the end of the genomic DNA fragments.

  • We are then going to do PCR using the primer from the end of the genomic fragment

  • and a primer from the mPing element.

  • And you resolve this on a gel, and that is what you see here.

  • So what you see in lanes 1 and 2 is a situation where it is a rice plant in one,

  • the DNA of the rice plant before cell culture,

  • and 2 is the DNA from the cell culture.

  • And all of the bands, and nothing is happening. You see one and two, they look exactly the same.

  • That's because the mPing element is not moving around in that cell culture.

  • Each of the bands comes from at one end of the band

  • is the mPing primer, which you see over here.

  • At the other end of the band is the region in the genomic DNA where the adaptor sequences is.

  • Okay, this is a modification of a technique called RFLP.

  • I am sorry, AFLP.

  • So anyway, lanes three and four are far more interesting.

  • And this is something that... there are...

  • Science is really slow, but there are these days you have which you always remember.

  • And this was a day. It was a Sunday morning and I turned on my computer and Ning had sent me this picture

  • that showed that the mPing element was moving around in the rice genome,

  • and it was, needless to say, it made my day.

  • So what you see in lane three is the plant before it went into cell culture.

  • And there are only a couple of copies of mPing in that strain.

  • However after cell culture there are hundreds of copies.

  • So what we can actually do is cut out those bands, re-amplify them, and sequence them,

  • and determine the position of insertion of mPing in the cell culture DNA.

  • So what I want to show you here is where mPing fits in.

  • mPing is a MITE. It is a non-autonomous element as are all MITEs.

  • It doesn't code for anything. It is only 430 basepairs in length.

  • Xiaoyu Zhang who was a graduate student in my lab took the mPing sequence

  • and BLASTed it, compared it to the entire rice genome sequence.

  • And he found a single transposon that looked like it was the autonomous element for this family.

  • So that is called Ping.

  • So we have Ping. We have mPing.

  • And there was only a single copy of that element in the entire Nipponbare genome.

  • And we went on over the years to show that the transposase from Ping is able to move mPing,

  • and I am not going to talk about that in this talk.

  • So what I want to tell you about is the copy number of mPing.

  • Because I've told you that MITEs are great because they attain these really high copy numbers

  • of hundreds to thousands.

  • And yet I am bragging about some element that has fifty copies.

  • That's not a whole lot.

  • And in fact when we look at a lot of strains...

  • what I've shown here is the Nipponbare, the sequenced genome, which has 51 copies

  • as Nb. And then when we look at a lot of other Japonica strains,

  • and this was done in collaboration with Susan McCouch.

  • We obtained the strain collection.

  • We see that there are very low numbers of mPing from 25 up to 38.

  • That's not the burst that I've talked about, which is...

  • So fortuitously another... two other groups in Japan had identified the mPing element,

  • but they identified it in plants, in living plants.

  • And I am going to talk about those plants in a second, but when we analyzed those plants,

  • we found that these four related land races, as I've shown here, had over 600 copies of the mPing element.

  • So this really said to us that here's an element that is capable and has increased its copy number very, very quickly.

  • But the next question, remember one of the things we are interested in,

  • is how can the element do this.

  • Here we have 4 strains where the mPing element had increased tremendously to 600 copies.

  • The question, what I want to show you in the next slide,

  • is just how closely related all of these strains are.

  • How the major difference between these strains is the mPing insertion sites.

  • And so what we can do, and again, this is another transposon display

  • where in the first lane, the Nb is Nipponbare,

  • with its sequenced genome, and where there are 50 copies of mPing.

  • Those are fewer than 50 copies, which I am not going to go into.

  • why that is. It's the way the experiment is done.

  • The next three lanes are three of the four land rices where the mPing element... where there are 600 copies of the mPing element.

  • And what you'll notice first of all is that the patterns are very, very different.

  • So the insertion sites for the elements are very, very different for each of those.

  • So from that we concluded that the mPing element had, at least at some stages,

  • amplified independently. These strains at some point, there probably was one strain

  • in which the mPing element had amplified, had activated, had become active.

  • And then land rices are strains of rice that farmers have grown in particular areas.

  • So these strains, they were then grown in particular areas,

  • They were kept separate. And now we are bringing them back together in the lab.

  • So what you see is the different patterns, but you can see that there are many more bands.

  • So we say that they burst independently in these three strains.

  • What I want to show in the next slide, not next slide,

  • but the next experiment is just how similar these strains all are.

  • So what you see here, is using, in the first, in the gel on the left, we've used the mPing element

  • the primer from the mPing element, remember I showed you that before,

  • in PCR. What we are using in this second panel is a primer from a different element.

  • So exactly the same genomic DNA preparations,

  • but the difference is one of the primers in PCR.

  • This is a primer from a retrotransposon called Dasheng,

  • which was also identified in my lab. There are about 1500 copies of this in the genome,

  • but what you see, again using the exactly the same DNA preparations,

  • is that the pattern for all of those strains is exactly the same.

  • So what that, or virtually the same.

  • So what that says is the major difference between these strains is the different insertion sites of mPing.

  • Now what I want to tell you is I want to show you

  • the experiment we devised, and this is Eunyoung Cho in my lab, devised this experiment

  • to see if the mPing element was still transposing in these high copy number strains.

  • And this is a, people in this area of transposon biology,

  • people will look at one organism and see transposons, and look at another and see them in different places.

  • And they'll say, okay, the transposon is moving.

  • They are probably not. What they are seeing is just polymorphism.

  • The only way you can really see transposition to say something is transposing,

  • is if you see it right before your eyes.

  • And that is what I am going to show you right here.

  • So what's done is we have ten. We have one plant that was grown up, one rice plant,

  • and from that plant Eunyoung took ten seeds.

  • Rice is a selfer. It self-pollinates, so all those seeds are virtually identical.

  • She planted the seeds, she grew them up. She isolated genomic DNA.

  • She did transposon display using the mPing primer.

  • And what you see are the ten lanes of the 10 individual plants there.

  • And you'll see differences.

  • You'll see differences, and I'll explain that in a minute.

  • So she took the last plant here, the very last one.

  • She took 10 seeds from that plant and she grew the next generation.

  • And she did the same thing, transposon display.

  • She took seed from the last plant here, I am sorry, ten seeds from that plant.

  • She grew it up. Here is the last generation.

  • So by comparing these three panels and by looking at the white arrows, the white empty arrows,

  • what you'll notice is that there may be... there's a band say in the F1.

  • Umm, that then in the next generation it is segregated.

  • Okay. So you see that band. That is a heritable insertion of mPing.

  • That is now segregating because when it inserts in the F1 generation,

  • it is heterozygous. And in the next generation we can see it segregating.

  • So essentially by looking at this what you can see is what I think is pretty remarkable.

  • That is this rapid increase in the mPing copy number over a very, very short period of time.

  • A couple of generations.

  • And so we can actually, just by simply counting bands,

  • we can determine how many new insertions there are per generation.

  • And that is what I will show you here.

  • So we had basically found that there were approximately forty new insertions per plant, per generation,

  • and that 80 percent of these insertions are heritable.

  • This blew us away. We had no idea that a transposable element could increase its copy number so rapidly.

  • So now we have the material to address the questions that I had...

  • one of the questions that I posed at the very beginning,

  • which is how do transposable element amplify without killing their host?

  • And then the second question I will end the talk with is does amplification actually benefit the host?

  • So the first one is the way were addressing this first question is where are the elements going?

  • Where are they in the genome?

  • So the way we... experimentally the way we address that question

  • was to take genomic DNA from these plants and essentially amplify out the ends of the element,

  • much like in transposon display, but we are not going to run a gel.

  • So we are taking genomic DNA, and you'll see in a second,

  • we are not taking it from one plant. We are taking it from a small population.

  • We are using the primer from the mPing element

  • and a flanking primer in an adapter and amplifying up all of these flanking regions,

  • and then instead of running it on a gel because we don't want to look at a few insertions,

  • we want to look at all the insertions,

  • we use high-throughput sequencing. In this case we used 454 sequencing

  • to sequence tens of thousands of... hundreds of thousands, flanking regions, regions flanking the mPing insertion sites

  • to try to find out where mPing is.

  • But more importantly, and this was an experiment done by Ken Naito

  • when he was a postdoc in my lab.

  • What he did is he figured out that the capacity for sequencing

  • is so great that we don't have to restrict ourselves to one plant.

  • He can actually determine where mPing is in a small population of plants.

  • And he chose the number 24, so we took 24 rice plants, and he was able

  • to barcode the PCR reaction so we could tell which plant

  • the PCR products came from.

  • And so, what he did, so what you see on the left in the gel,

  • is, you'll see for example some of the PCR patterns, products,

  • from each of, from a subset of the 24 plants. And you can see that in blue I am showing you

  • the bands that are shared by all of the plants.

  • In pink I am showing you the bands that are only present in one plant.

  • The ability to look independently at shared and unshared insertions is very powerful.

  • Because what we want to know is not just what are the insertions that are present in all 24 plants,

  • We want to know... those we will call "old" insertions.

  • We want to know what are the new insertions. What are the ones that are just happening.

  • And the reason is, it is possible that the old insertions have been filtered by selection.

  • So that over generations insertions that are in places that are in exons or whatever

  • have been removed because they have been detrimental.

  • So by looking at shared an unshared we are able to get the whole spectrum of new and old insertions.

  • Old is also... old is not really old. These are insertions that happened, this initial burst really

  • happened maybe over the last 50 to 75 years.

  • But these shared insertions, these unshared insertions, happened in our greenhouse.

  • So essentially what he was able to sequence, so we know

  • that if all of the bar-coded plants or some of them show the same insertion,

  • we call that shared. If only one of the plants shows an insertion, we call that unshared.

  • So he was able to determine 928 shared insertion sites,

  • and 736 unshared insertion sites.

  • Ok, so, as I said before, these unshared insertion sites are de novo insertions. They just happened.

  • And they are heterozygous. Heterozygous because when insertion happens it goes into one of the two alleles.

  • And heterozygous is important because if it is a detrimental insertion,

  • if it's a detrimental mutation, it is likely to be a recessive mutation.

  • So. This is a... I don't expect you to see this. It is just really to impress you.

  • What you are seeing is each of these graphs is a different rice chromosome

  • and the blue... I am going to blow it up in a second.

  • The shared insertions are shown in blue and the unshared insertions are shown in red.

  • And it essentially shows that the mPing insertion can insert throughout the 12 chromosomes

  • of rice. It is on every single chromosome.

  • And this shows a single chromosome, chromosome 4,

  • and we are looking at the insertions on chromosome 4.

  • And chromosome 4 has a very large region of heterochromatin.

  • And most of the transposable elements, the DNA transposons, don't insert into heterochromatin.

  • They insert near genes which are euchromatin.

  • But even, but we do have a few insertions that are in or near heterochromatin.

  • So what we know, what we have learned from this analysis,

  • first of all the distribution of shared and unshared insertions is the same.

  • It is exactly the same. There is no difference in the insertion preference of either class.

  • That, remember I said before, that MITEs prefer to insert into single copy regions, intergenic regions,

  • and sure enough, 91% of the insertions that we found were in single copy sequences.

  • The genome average of single copy sequences is about 54%.

  • So this is saying that MITEs do prefer to insert into single copy sequences.

  • And that we found that even when it does insert into heterochromatin,

  • it's actually inserting near genes that are in the heterochromatin.

  • So now we have looked at a gross scale throughout the chromosomes.

  • Let's look more closely and see where is mPing inserting in and around genes.

  • So here is a summary, with a very surprising result.

  • So what we see, we are looking at insertions that are in the 5' untranslated region,

  • in the exon sequences, in intron sequences, and in the 3' UTR.

  • And we are looking at again at a summary of a very large number of genes,

  • and what you are seeing is the percentage of insertions.

  • And so what we find is that the grey here is the expected number,

  • is the expected number of insertions given the composition of the genome.

  • The pink are the unshared insertions and the blue are the shared insertions.

  • And the only thing that really stands out on this histogram is this.

  • We find that there are far fewer insertions into exon sequences than we would expect by chance.

  • Almost ten fold fewer insertions.

  • Both the shared and the unshared.

  • And the unshared is significant again because it tells us that mPing prefers not to insert into exon sequences.

  • How it does this, how it knows exon from intron we can only speculate at this point,

  • and I'll speculate a little later.

  • So mPing has another insertion preference.

  • And so here is genic regions, so what you are seeing at the top is around the gene.

  • And what we are seeing on the X axis is the percentage of insertions.

  • And the blue or purple bar is the actual mPing insertions and the grey dotted line is our control.

  • So if we just sampled genome sequences what we would expect to see in those regions.

  • And what we are seeing where the dotted line is

  • is the transcriptional start site, and we go upstream from there to -1, -3, and that's in kb.

  • And what you see is that there is a spike.

  • There is a preference for mPing inserting within 1 kb of the transcription start site.

  • And when we take this together, and you say how could this possibly happen?

  • We don't know. And that is obviously an area of intensive interest.

  • One of the ideas is that in plant genomes, and in other genomes,

  • it is known that the region just upstream of the transcription start site

  • has fewer nucleosomes, as do exons. Exons have fewer nucleosomes, I'm sorry, exons have more nucleosomes.

  • And so, introns have fewer nucleosomes compared to exons,

  • so it seems that the mPing is avoiding insertion into dense chromatin regions,

  • or relatively dense chromatin regions.

  • But this is pure speculation at this point.

  • It is the only thing that is consistent with this pattern of insertion,

  • that is avoiding exons and preference for insertion near the transcription start site.

  • So let me summarize at this point, and that is we find that 91% or so

  • of the mPing insertions are in single copy regions near genes.

  • That exons insertions are 10 fold under-represented. So the element is avoiding insertion into exons.

  • And that insertions within 1 kb of the transcription start site are also enriched.

  • Ok, and finally that the distribution of shared and unshared insertions are indistinguishable

  • meaning that this is the insertion preference of the mPing element.

  • I said we don't understand it, but this is the preference.

  • So at the beginning of this section I posed two questions that we want to answer with these experiments.

  • The first one is how do transposable elements amplify without killing their host?

  • And the answer to that question for mPing is the following.

  • And that is the rapid amplification of a successful element,

  • and mPing is a successful element, has really a more modest impact on the host than previously thought.

  • So this is actually, when I first saw this data I was kind of disappointed

  • because I was like, "boy, it is just not doing a whole lot."

  • And then it kind of dawned on me that that is what successful elements have to do.

  • I mean in order to be successful, and success again

  • is defined as being able to attain very, very high copy number,

  • it has to do little harm.

  • So the second question that is more difficult to address is does the amplification actually benefit the host?

  • And we have some data that suggests that it does, and it is experiments that we are pursuing now,

  • and I am going to tell you what those results are.

  • And really what we want to do is we want to look at the impact of mPing insertions on host transcription.

  • So I showed you at the beginning of this talk the situation that we wanted in order to...

  • the experimental material we needed in order to address the question

  • of what is the impact of insertion on diversifying gene expression for example.

  • And what we needed were alleles that differ by the presence or absence of a transposable element.

  • Now we have lots of those examples.

  • So as I said, we wanted alleles that only differ by the presence or absence of the MITE.

  • And this summarizes really what we have now.

  • We have 710 genes, and EG4, I didn't show this before,

  • EG4 is one of the land rices. It is a strain that we determine the mPing insertion sites.

  • So by comparing the mPing insertions in EG4, with the same genes in Nipponbare,

  • we now have essentially 710 genes that have alleles that differ largely by the presence of this mPing element.

  • Of those 710 genes, almost 400 have insertions within the promoter region,

  • the 5' untranslated... I'm sorry, the promoter region.

  • 120 or so have insertions within the gene.

  • And 193 have insertions downstream of the gene.

  • So the question we are asking is what is the impact of insertion on transcription.

  • To do that, Ken Naito when he was a postdoc in the lab

  • compared the transcription of the 710 alleles in EG4 versus Nipponbare

  • initially under normal growth conditions in the greenhouse.

  • So to do this he used a microarray of rice genes. He did microarray analysis of 31,000+ rice genes.

  • He isolated RNA from Nipponbare and EG4 seedlings.

  • And essentially he determined that for a significant percentage of these alleles,

  • there was no difference in gene transcription.

  • So for 78% the transcript levels for these genes

  • were the same for Nipponbare as they were largely the same in EG4.

  • So this is a pretty benign effect on host transcription.

  • So what you see in this slide is a comparison of the expression of the remaining alleles,

  • that is those where we did see a difference

  • between the transcription in EG4 and Nipponbare.

  • And for three quarters, approximately three quarters of those alleles,

  • three quarters of those alleles, we saw upregulation in EG4.

  • That is the presence of the mPing element was correlated with increased transcription of the gene.

  • And most of that difference, or what you see here is,

  • most of that difference were insertions that were in the 5' upstream regions.

  • So this is upstream of the transcription start site.

  • We do see also differences in insertion in introns.

  • That many of the intron insertions, many meaning of the remaining 25% that show an effect,

  • most of those in fact were upregulated.

  • There weren't many that were downregulated except the few that were in exons, and that is understandable.

  • So what I want to do know is to show you how we confirm this microarray analysis.

  • So what you'll see... I'll just take one of these over here.

  • To the left. What you see is a particular allele, and this is OS... some long number.

  • The insertion of mPing is at -2497. So it is 2.5 kb upstream from the transcription start site.

  • And yellow here is transcription in EG4. Gray is transcription in Nipponbare.

  • So what we are seeing... what we are doing here is we are isolating RNA and instead of using the microarrays,

  • we are doing PCR, quantitative PCR.

  • And what we find in every case we check, the EG4 allele for the particular alleles we are looking at,

  • the ones that showed upregulation by microarrays,

  • we're able to confirm that result using quantitative PCR.

  • Yes, indeed there is more transcription from the EG4 alleles.

  • Now we have a problem.

  • And this, I'll try to make this as simple as possible.

  • There's another difference between Nipponbare alleles and EG4 alleles.

  • besides the presence or absence of mPing.

  • And that is that the allele in Nipponbare, which doesn't have the transposon in it

  • is in a genome that only has 50 mPings.

  • Whereas the EG4 alleles, all of them, are in genomes that have,

  • I show here a thousand, but 500-1000 mPing elements.

  • So it is possible that the differences that we are seeing in transcription between EG4 and Nipponbare

  • is due to that load of 1000 elements in the background.

  • What we need is a control.

  • We need a control where we can compare the alleles with and without mPing

  • in the same type of genomic background.

  • And again, I wouldn't be telling you that we need this control if we didn't have one.

  • And so I mentioned at the beginning that EG4 is one of a couple of land rices

  • that have... in which the mPing element has burst, where we have many copies of mPing.

  • And recall I showed this transposon display, and so what I am showing here is EG4 is one of these land rices.

  • Another is A123, and another is A157.

  • So, and the other thing you'll notice is that the mPing insertions in those strains,

  • just by looking at the patterns you can see the patterns on the transposon display differ.

  • This means that the insertions are different. They are in different places in the genome.

  • So this allows us to have valid controls.

  • So here we see alleles that differ between Nipponbare and EG4.

  • The control is we can identify in for example, A123, we can identify A123 that has the Nipponbare allele in it.

  • Okay. So in that way we are able to compare A123 and Nipponbare to EG4

  • and in that way we sort of eliminate the complication of 1000 mPing insertions in the background.

  • And I'll show you that data now.

  • So here we have, what I am showing is a histogram, this is a particular gene Os... so on... It's a rice gene.

  • An annotated rice gene.

  • The -600 means that it has insertion of mPing 600 basepairs upstream of the transcription start site.

  • And that is shown in this schematic below here.

  • So what you see is that in Nipponbare, which is the gray,

  • we see a level of transcription which is set arbitrarily as 1.

  • In EG4 we see about 5-fold more transcription. Transcripts.

  • Now we also have to compare, we have the blue.

  • The blue is the A123, which is another land rice where there is no mPing

  • in that position. So A123 has the Nipponbare allele

  • and despite having that allele and that background. No, not that ... Despite.

  • Even with the 1000 copies of mPing in the background,

  • we still see reduced expression of the gene. So the alleles, the Nipponbare allele,

  • and A123 allele, we are getting about the same level of transcription.

  • A154 has the same insertion as EG4.

  • And as you see, we get increased transcription.

  • So this clearly tells us that the difference in transcription is due to the mPing, somehow.

  • We don't know how. It is due to the insertion of the mPing at -600 from the transcription start site of this gene.

  • Here's another experiment. I am not going to show you all of them. Don't worry.

  • Here's another gene it is Os01g0.... whatever.

  • This insertion is at -2.5 kb from the transcription start site.

  • Again, so what we have here, Nipponbare, the negative next to Nipponbare means

  • that there is no mPing in that gene. The + means that there is.

  • So here EG4 and A123 have that allele with mPing.

  • A157 doesn't. Again, the expression has to do with the presence of mPing,

  • in this case 2.5 kb upstream from the transcription start site.

  • So, just to summarize this part-the impact of mPing insertion on nearby gene transcription.

  • In the vast majority of alleles we see no impact.

  • No effect. This would be a neutral mutation.

  • Of the 710 alleles we are comparing, 111 we see upregulation of the nearby gene.

  • And for 45 we see down regulation of the nearby gene.

  • Now the question that we are going to ask is does the presence

  • of mPing affect transcription in a different way?

  • Does it in this case confer stress inducibility on nearby genes?

  • Now remember from McClintock's scenario she mentioned the possibility

  • that transposable elements are induced by stress.

  • So here we are going to look at something a little different.

  • We are going to ask does the presence of a transposable element

  • cause the nearby gene to be stress inducible?

  • So this experiment... I'll lead you through this here....

  • is we are looking at three different stresses: cold, high salt and desiccation,

  • dryness. So this is a gene which has an mPing element at -55.

  • So 55 basepairs from the transcription start of this gene.

  • And this is a gene, you'll see the control under normal conditions,

  • it's one of those vast majority, 78%, that show no effect under normal growth conditions.

  • That is what you see in the control there.

  • However, when we subject these plants to cold, and we meaning Ken Naito again.

  • Cold or salt, we see that the strain EG4, which has mPing at -55, we see increased transcription.

  • Not much, but we see reproducible increased transcription,

  • whereas the other high copy strains that don't have this allele with mPing do not respond.

  • So here's another example. This is an mPing element in gene Os02...

  • it has an insertion at -41, 41 basepairs upstream of the transcription start.

  • What we see is that the alleles... here EG4, in blue, and A123, in yellow, have the mPing containing allele.

  • And you see those are the ones that are induced by cold and salt.

  • What's nice here is we are not seeing any effect of desiccation.

  • We see a consistent effect of cold and salt.

  • We don't know the mechanism for this. It is under investigation. So then the question is,

  • how... so one of the things you might wonder is how is the transposon effecting transcription?

  • Is it acting as an enhancer?

  • Or is it acting as a new promoter? A site of transcription initiation?

  • So we have several intron insertions and we can do the same experiment.

  • Here we have Os... another gene... which has an mPing element only in EG4 in an intron.

  • And when we do the same experiment, under room temperature, RT is room temperature,

  • normal conditions, there is no difference in the transcription of the allele with and without mPing.

  • However when we look at the situation in the cold,

  • we see that it is cold-inducible.

  • So here the transposon in a distant intron is effecting the inducibility of this gene.

  • And we see that in the next slide also. This is another gene, a very large gene, with an mPing element in an intron.

  • And these introns are in the EG4 allele. I am sorry, these mPing insertions are in the EG4 allele and in the A123.

  • And again, we see that those two are inducible, suggesting that mPing sequences

  • are in some way acting to enhance transcription under cold conditions.

  • We didn't do this experiment under... we didn't test dry and salt.

  • Okay, so let me give you conclusions from this part of the talk.

  • The first thing is that we found surprisingly, or maybe we were surprised, but that is why you do experiments,

  • to get surprised, and then you see the results and you say, "Oh that makes sense".

  • That massive amplification is largely benign.

  • And when I say up to a point, we've caught this element in the act of amplifying.

  • Obviously at some point if the number of elements transposing gets too great

  • it is going to start causing some damage,

  • and that is one of the things we are really, really interested in.

  • When does this activation stop? What happens?

  • And we don't know yet.

  • That the amplification has a subtle impact on the expression of many genes.

  • It causes stress induction. It induces the expression of some of genes,

  • but it really is tweaking them. Most of the expression we see is maybe a two-fold, three-fold increase.

  • And again, it produces stress inducible networks. And I say cold and salt.

  • Others, I'll give you a few tastes of where this experiment, where this is going.

  • And the other thing that is significant is that it generates dominant alleles.

  • So if you think about a population. Remember I said that when these elements insert they are heterozygous.

  • That... if it caused a phenotypic change, that overexpression will be a phenotypic change

  • that can be seen possibly in a heterozygous organism.

  • So we don't have to wait for this to become homozygous.

  • So I want to go back to McClintock's scenario.

  • Again, and that transposable elements... her scenario for how transposable elements can function as tools

  • to generate diversity.

  • Transposable elements usually don't move around, and we know that now.

  • We know that the vast majority of transposons in the genome are inactive,

  • even though genomes are 50-80%, 20-50-80% derived from transposable elements,

  • that most are inactive, that they are inactive because they have accumulated mutations.

  • Or the few that are active are being epigenetically restrained by the host.

  • That it is possible that somehow stress conditions may activate transposons.

  • Now I haven't shown you that. We started with the strain mPing, the EG4 strain, where...

  • the system was active already. We don't know how it became active.

  • That obviously is something that we are very interested in.

  • And we think that it is possible because EG4 and mPing are present in most rice strains,

  • that in most rice strains these elements are epigenetically silenced.

  • But that somehow in these few strains, these land rices and EG4, that the element became activated.

  • We do not know how. That obviously is an area of future research, and that is a critical area

  • because that's how we think most genomes are sort of poised. Many genomes.

  • They have the ability for active transposable elements to start amplifying.

  • But how that switches.... what is the switch and how is it thrown is the subject of future research.

  • Again the movement of transposable elements generates genetic diversity increases the mutation frequency,

  • McClintock looked at mutagens. She looked at elements that... geneticists look at mutants.

  • These are, as I said at the beginning, these are not insertions that will benefit the organism.

  • However, we have been able to identify an element where most of the insertions are benign.

  • And, as we said, a rare TE induced mutation may be adaptive.

  • So I want to sort of speculate a little bit.

  • And tell you about how we sort of fit mPing into this model

  • that somehow a stress could have induced Ping. Ping is the autonomous element.

  • Again, this is a black box. We do not know. We weren't there when this happened.

  • We came upon the strain, or our Japanese collaborators came upon the strain

  • when it was already active.

  • This leads to the massive and rapid amplification of mPing

  • that we're seeing. It is still in progress.

  • This generates tens of thousands of new alleles.

  • Now we looked at 24 plants, but imagine a field of a thousand plants.

  • mPing accumulating 25-40 new insertions per plant.

  • What is really interesting, a point I haven't made, is that rice is a selfer.

  • So it selfs. There is no new genetic information coming into populations.

  • The same genetic information is being scrambled up by recombination or whatever.

  • mPing is a way, transposons, are a way to dramatically diversify

  • the genetic material without introducing... without having gene flow into the population.

  • So this, what we are hypothesizing, we see it at the transcription level that this amplification

  • creates transcriptional changes and we are hypothesizing that these changes can lead to quantitative variation.

  • So changes in cold tolerance, changes in drought tolerance. Changes in desiccation.

  • But that is the point we are now testing.

  • And I am going to end by telling you about, very briefly,

  • about the experiments that we are currently doing to address the question.

  • Really the smoking gun question.

  • And that is what is the phenotypic consequences of the mPing burst on EG4?

  • Does this... we've talked about transcriptional changes,

  • but are there phenotypic changes that go along with those?

  • And the way we are doing that is a number of ways.

  • The first thing, and again we are taking advantage of the wonderful

  • new high throughput sequencing technologies.

  • So one of the things that has allowed this progress... this project to move forward,

  • and I think for most of us in molecular biology,

  • is the technology that really drives the questions that we ask.

  • And that we can get deeper and deeper into a particular problem as the technology changes.

  • And the availability of high throughput sequencing

  • has allowed us to address questions that we didn't even dream about,

  • you know as recently as 5 or 6 years ago.

  • In this case what we can do is, as shown here, we can... Well, first of all,

  • we know that Nipponbare and EG4 differ phenotypically in several characteristics.

  • They have different flowering time. They have different average height.

  • They differ in some of the stress responses.

  • We want to know for example, if any of those difference are due to one or more mPing insertion.

  • In order to figure this out the first thing we have to do is to figure out the...

  • we have to know is there more going on in EG4 and the land rices than just mPing amplifying.

  • Because remember when we sequenced the insertion sites we did an approach

  • where we used PCR primers and only amplified the element and flanking sequences.

  • Well again, we were limited before by the technology.

  • Now we can actually sequence the entire genome, and in fact we've done that.

  • So EG4 is currently being re-sequenced using next generation technology

  • so that we can see is the mPing amplification the only thing, the only transposon that is amplifying in the genome.

  • And so far the preliminary answer to that is yes.

  • It appears that mPing is the only transposon that is amplifying at this time.

  • The other thing is we are doing transcriptomics.

  • Rather than looking at particular individual genes, we are looking in a strand specific way

  • at the entire genome of mPing, of, I'm sorry, of EG4 and Nipponbare.

  • And this is done in collaboration with Tom Brutnell's group at Cornell

  • where they have developed a really nice protocol to look at single strand, do single strand RNAseq.

  • So now how do you... the way that is traditionally used

  • to find the regions of the genome that are responsible for quantitative traits

  • is mapping population or a recombinant, inbred population.

  • And our collaborators at Kyoto University in Tanisaka Okumoto's lab have over the last decade

  • been developing this incredibly valuable resource.

  • So what they did over ten years ago was to cross EG4 with Nipponbare.

  • Now what I want to point out is these are inbred lines. So all of their...

  • you know... they have two copies of exactly the same gene at every single locus.

  • So we have EG4 crossed with Nipponbare. We have our F1 progeny.

  • Many, many F1's. Those F1's are then selfed.

  • Selfcrossed for ten generations.

  • So we now have growing in this country 275 recombinant, inbred lines.

  • These lines have mosaic chromosomes that are derived from EG4 or Nipponbare.

  • And they are displaying different traits. So we are phenotyping them now, and I'll talk about that in a second.

  • So the question really and I think on the next slide I go into more here.

  • So we are looking at these recombinant, inbred lines. We are assaying... RILs for recombinant, inbred lines.

  • for morphological traits and stress responses.

  • And we are doing something that again I would never have thought would be possible

  • even in the grant application I wrote a couple of years ago.

  • I didn't even write that we world do this because it wasn't affordable,

  • but now again technology, the costs have come down.

  • We are actually re-sequencing all 275 RILs

  • to find out exactly the mosaic structure of their chromosomes. What part came from Nipponbare,

  • with its mPings? What parts came from EG4 with its mPings?

  • So that we can ultimately correlate the mPing insertions with the various phenotypes.

  • Now again, this is just correlative at this point. We then will have to prove that the candidates

  • that we find, the mPing insertions and alleles are the ones responsible for that phenotypic difference.

  • So many of us and many of us in the field think of Barbara McClintock

  • as the first genomicist. The first person who thought of the genome as an entity

  • not just of single genes. And there is a quote from her Nobel lecture which I want to end with.

  • And it is her thinking about the genome, and it really presents the challenge

  • that I have at least felt and have gone with with my lab.

  • And that is, "In the future, attention undoubtedly will be centered on the genome,

  • with greater appreciation of its significance as a highly sensitive organ

  • of the cell that monitors genome activities and corrects common errors,

  • senses unusual and unexpected events, and responds to them,

  • often by restructuring the genome."

  • She ends by saying, "We know about the components of genomes that could be

  • made available for such restructuring."

  • In part the transposable elements that she discovered.

  • "We know nothing, however, about how the cell senses danger

  • and instigates responses to it that are truly remarkable."

  • I'd like to say that we are beginning to understand that black box

  • of the connection between the outside world and the genomic changes.

  • And I think transposable elements are certainly part of that.

My name is Sue Wessler. I am a Professor of Genetics at the University of California, Riverside.

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