How Do They Survive That? Stress Response in Agrostis

KEENAN AMUNDSEN, professor of turfgrass genetics, Department of Agronomy and Horticulture, University of Nebraska–Lincoln Author

11/11/2022 Added

15 Plays

Description

The Agrostis genus includes some of the highest valued turfgrass species, such as A. stolonifera and A. capillaris. These species differ in their functional quality and innate response to various stresses. Genomic and transcriptomic tools were used to characterize differences between these species, providing useful targets for introgression breeding.

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[00:00:00.810]The following presentation
[00:00:02.250]is part of the Agronomy and Horticulture Seminar Series
[00:00:05.850]at the University of Nebraska Lincoln.
[00:00:08.760]Thanks, everyone, for joining,
[00:00:10.320]both in person and online.
[00:00:12.480]It's my great honor
[00:00:13.313]to introduce today's speaker, Dr. Keenan Amundsen.
[00:00:16.740]So Dr. Amundsen and I, know each other for about 11 years.
[00:00:20.910]I was a student of him in the third, final class,
[00:00:26.670]and he later became my co-advisor for my master
[00:00:31.200]and he also served on my PhD committee.
[00:00:38.942]Dr. Amundsen holds both a bachelor degree in Mathematics
[00:00:45.270]and Plant and Soil Science.
[00:00:47.820]He received his masters in Plant and Soil Science
[00:00:51.600]from Michigan State University
[00:00:53.790]and PhD in Bioinformatic and Computational Biology
[00:00:58.200]from George Mason University.
[00:00:59.730]His research focus is on turf grass genetics.
[00:01:03.570]So without further ado, I'll turn it back to Dr. Amundsen.
[00:01:09.699]Can you hear me okay, Dan?
[00:01:11.437]Great.
[00:01:13.710]So we were talking a little bit before the seminar,
[00:01:15.690]and I think the last time I gave a departmental seminar
[00:01:18.210]was in 2016, and I'm pretty sure my wife and kids
[00:01:21.690]would pay good money if they could keep me
[00:01:23.850]from talking for six years.
[00:01:25.380]That would be great.
[00:01:26.700]So today I'm gonna talk a little bit about Agrostis,
[00:01:28.980]which has been honestly a pet project for a long time.
[00:01:32.490]So some of it'll be new stuff, some old stuff,
[00:01:34.770]just to put things in context.
[00:01:36.690]So, for the non-forage range and turf people,
[00:01:41.250]what is the agrostis genus?
[00:01:43.980]Anybody know the common name for that?
[00:01:49.260]There's a clue.
[00:01:52.080]No golfers either.
[00:01:53.850]Okay, so it's the bentgrasses.
[00:01:56.100]And so I've always been really fascinated
[00:01:59.070]about the bentgrasses.
[00:01:59.940]There's lots of interesting things about that
[00:02:01.680]particular genus, and so gonna just talk about that today.
[00:02:06.210]So this happens to be a picture from Lost Rail Golf Club,
[00:02:12.330]which is over near Gretna, and it's really,
[00:02:14.112]probably shouldn't stand right in front of the screen,
[00:02:16.080]but it's one of the newest constructed
[00:02:18.870]golf courses in the state.
[00:02:20.820]It's really elite, high-end golf club.
[00:02:24.180]Rock just led a tour of our 427, our capstone course
[00:02:29.250]there just this past weekend
[00:02:31.080]and I was fortunate enough to tag along.
[00:02:33.090]So Rock is there with some of our students
[00:02:35.610]and Steve Merkel's on the left.
[00:02:38.670]And gave really just a great tour of the facility
[00:02:42.030]and everything they have to offer.
[00:02:43.380]So what I wanna do today is just talk a little bit
[00:02:46.470]about why I love bentgrasses.
[00:02:48.540]So they're all standing on bentgrass right now.
[00:02:51.840]Why I love them?
[00:02:53.610]Some of the things that I think are really interesting
[00:02:55.320]and some of the reasons why I think they're pretty
[00:02:57.060]challenging and fun to work.
[00:03:00.300]So one of the things that I think is most fascinating
[00:03:03.120]about creeping bentgrass its ability
[00:03:08.100]to tolerate extremely low mowing heights.
[00:03:12.150]And so this picture here shows two different bentgrasses.
[00:03:17.280]So this is taken from that Last Rail Golf Club,
[00:03:19.980]over the weekend, the left is the collar,
[00:03:22.530]which is the area around the golf course putting green.
[00:03:25.410]It's typically mowed a little higher.
[00:03:26.970]And then we have the putting green on the right.
[00:03:30.150]The putting green in this instance,
[00:03:31.530]the mowing height was set to just over an eighth of an inch,
[00:03:36.330]which actually by today's standards is fairly high,
[00:03:39.720]but they have very contoured fast greens
[00:03:43.710]and so they get away with a slightly higher mowing height.
[00:03:46.440]And I don't even know what the height is
[00:03:48.450]of a standard collar, Rock?
[00:03:50.490]Three eighths of an inch.
[00:03:52.410]And so this is a profile taken from our green out here
[00:03:56.940]at our research facility on the right here.
[00:03:59.490]Forget people are online, can't see where I'm pointing,
[00:04:01.770]but on the right there.
[00:04:02.670]And there's not a lot of plant material there.
[00:04:07.650]And so it's one of the things that, I'm not a physiologist,
[00:04:11.010]so don't, no spoilers and don't ruin it for me,
[00:04:14.160]but I've always been amazed that bentgrasses can stay alive
[00:04:18.960]and thrive and persist when they're mowed at,
[00:04:23.010]an eighth of an inch.
[00:04:23.843]To me, it doesn't make sense,
[00:04:25.800]based on their photosynthetic capacity
[00:04:28.500]and being able to regenerate.
[00:04:30.240]I mean if you think about how we use these things
[00:04:32.550]on golf course putting greens,
[00:04:34.560]we cut a hole somewhere on the green
[00:04:37.110]and then we tell everyone to basically walk up
[00:04:40.320]to that thing, and so it gets lots of traffic
[00:04:42.870]in a really concentrated area.
[00:04:45.030]And so it puts a lot of pressure on these grasses
[00:04:48.210]and I've always again just been really fascinated by 'em.
[00:04:52.200]And just to put that in context a little bit here,
[00:04:54.870]so we have the creeping bentgrass.
[00:04:57.270]This is pure distinction.
[00:04:59.340]This is just a different cultivar on the putting green.
[00:05:03.270]And then the collar is 007, creeping bend grass.
[00:05:08.910]And then on the right is Kentucky Bluegrass
[00:05:12.720]that's mowed just an inch.
[00:05:14.760]And so that gives you an idea
[00:05:16.040]of some of the height differences.
[00:05:18.000]The mowing height's one of the things
[00:05:19.560]that I've always been really fascinated
[00:05:21.853]about the bentgrasses.
[00:05:23.724]And then the other is the complexity of the genome.
[00:05:25.317]And so I spent a lot of time working on genetics
[00:05:29.580]and genomics, that's kind of more my area of expertise.
[00:05:32.190]And so this is where, these were sadly taken
[00:05:35.010]directly from my dissertation.
[00:05:37.020]So that's how old this is and that's how long
[00:05:38.910]I've been working on it.
[00:05:39.743]So about, I don't know, more than 15 years,
[00:05:43.650]but there's lots of complexity among agrostis species.
[00:05:47.970]There was a famous or an important taxonomist
[00:05:52.110]and I don't remember the year,
[00:05:53.400]but Hancock, and he described more than 150 different
[00:05:57.690]agrostis species, so it's a really complex genus,
[00:06:00.990]lots of different species.
[00:06:02.490]There's really only about five that are recognized
[00:06:05.730]for being used as turf,
[00:06:07.680]although there's probably more like 10,
[00:06:09.900]but it's just creeping bentgrass,
[00:06:12.120]colonial bentgrass, velvet bentgrass.
[00:06:15.030]And I'll describe some of, a couple in a little more detail.
[00:06:18.990]Highland bentgrass and giant or red top bentgrass.
[00:06:22.710]So those are the main five, agrostis stolonifera,
[00:06:27.455]agrostis capillaris, agrostis canina.
[00:06:29.970]Creeping, colonial, and velvet bentgrass,
[00:06:31.960]those are the three most commonly used in, or for turf.
[00:06:36.810]Castellina and giant bentgrass are used
[00:06:40.860]a little differently.
[00:06:43.140]So the bank grasses are not unique among turf grass species
[00:06:46.500]or probably a lot of other grasses in that there's a kind of
[00:06:50.850]a ploy series among them.
[00:06:53.640]And so that adds to the complexity
[00:06:55.650]of some of our breeding work and genetics.
[00:06:57.900]So if we're inter-mating these things,
[00:06:59.550]we have to really understand the kind of genome structure
[00:07:03.450]before we can do any successful mating.
[00:07:07.290]One of the things that we really rely on
[00:07:10.260]is some of this early work by Keith Jones in the mid 1950s.
[00:07:15.598]We did some early cytology work
[00:07:17.130]and so we're primarily working with tetraploid species.
[00:07:22.680]And so Keith Jones had done some work.
[00:07:24.690]I realize this is a fairly grainy image here
[00:07:26.520]and it's not really that important, but what is important,
[00:07:30.240]I'm gonna talk a lot today about colonial bentgrass
[00:07:33.210]and creeping bentgrass.
[00:07:35.520]They are both closely related tetraploid species.
[00:07:38.880]They have one common progenitor
[00:07:44.295]which is believed to be agrostis canina or velvet bentgrass.
[00:07:51.540]Agrostis capillaris was renamed from agrostis tenuous
[00:07:56.070]a long time ago.
[00:07:56.970]And so they're, agrostis stolinifera's down here,
[00:07:59.370]so all three of those are believed to have this diploid
[00:08:02.550]agrostis canina genome in common.
[00:08:05.490]And then there are separate diploid progenitors that led
[00:08:08.340]to tetraploidization, if I can pronounce that correctly,
[00:08:13.530]of agrostis capillaris and agrostis stolonifera.
[00:08:16.280]So those two species have one sub genome in common and also
[00:08:19.320]one distinct (indistinct), and that'll come into play
[00:08:21.450]later in some of what I'm gonna talk about.
[00:08:25.380]So the reason that I'm talking about creeping and colonial
[00:08:28.740]bank grass, and part of the reason that I really like them,
[00:08:32.730]is that one, we can inter-mate them and I'll talk more
[00:08:35.910]about that later, but they differ quite a bit
[00:08:39.090]in some of their traits.
[00:08:40.860]And so they're both used on golf courses.
[00:08:42.720]Creeping bentgrass is predominantly used, again, on golf
[00:08:45.270]course putting greens, it generally is considered
[00:08:48.390]to have finer leaf texture,
[00:08:51.360]much higher shoot density.
[00:08:52.830]So it lends itself to a really nice,
[00:08:55.200]basically carpet if you will,
[00:08:57.540]for sports that are involving ball roll,
[00:09:00.870]things like that, like golf.
[00:09:03.060]Colonial bentgrass, I feel it could be the same.
[00:09:05.760]It just, we haven't had as much breeding
[00:09:07.680]and development efforts on that,
[00:09:09.990]but there's still a lot of good colonial bentgrass lines
[00:09:12.480]and they're oftentimes found more frequently,
[00:09:15.510]I guess on golf course fairways, areas like that, right?
[00:09:19.890]So particularly out in the western part of Nebraska,
[00:09:24.780]they'll intermix colonial bank grasses
[00:09:27.660]with some other species.
[00:09:30.330]So this is a picture of a golf course in Denmark,
[00:09:32.700]very different, very significant contrast
[00:09:36.150]from the one I showed at in Gretna here,
[00:09:39.480]Lost Rail, this one didn't use any pesticides.
[00:09:43.200]And their green, interestingly, was a mix
[00:09:45.750]of fine leaf fescues, colonial bank grass,
[00:09:48.600]and velvet bank grass, which is not normally
[00:09:51.600]a mix we think of for golf course putting beans, right?
[00:09:56.310]Okay, so some of the things, again, that we think,
[00:09:59.190]that we find most fascinating, colonial bentgrass
[00:10:01.987]or agrostis capillaris, on the left there,
[00:10:06.210]it originates from the European highlands
[00:10:08.190]and it has really good drought tolerance
[00:10:11.760]and it also has kind of this innate resistance
[00:10:17.190]to dollar spot.
[00:10:18.930]Dollar spot's probably the most,
[00:10:21.120]the number one most important economic or economically
[00:10:24.360]important disease in turf grasses.
[00:10:27.240]Whereas creeping bentgrass is oftentimes considered more
[00:10:31.470]susceptible to dollar spot.
[00:10:34.740]It's also naturally adapted to ditch banks.
[00:10:37.740]And so it tends to be more of a water-loving species.
[00:10:43.440]Now there's been lots of breeding work on both
[00:10:45.420]of these over decades, and so some of those traits
[00:10:49.650]have definitely been improved upon.
[00:10:51.030]So that's really more just a kind of more of a generic
[00:10:54.480]description of the species.
[00:10:57.270]But because we can inter-mate these things,
[00:10:59.520]there's always been an effort to take something like drought
[00:11:03.720]tolerance, or something like dollar spot resistance
[00:11:07.980]from colonial bank grass and through traditional plant
[00:11:10.800]breeding, try to move it into creeping bentgrass.
[00:11:14.970]And so here's a couple of just colonial bentgrass, creeping
[00:11:18.570]bank grass grown in the greenhouse and some containers.
[00:11:22.590]And you can see, they look pretty similar,
[00:11:26.700]really high shoot densities.
[00:11:28.170]Again, they love that low mowing, jumping ahead.
[00:11:33.090]Okay, so one of the things that I've really focused
[00:11:38.910]my efforts on is on the genetic side.
[00:11:41.190]So I'm a turf grass geneticist,
[00:11:42.540]so that's probably not that surprising.
[00:11:45.318]And so really I've been interested in identifying genes
[00:11:48.960]that confer kind of resistance tolerance trait.
[00:11:55.050]This is an example where we did some drought tolerance work
[00:11:58.050]in the bentgrasses.
[00:12:00.390]And so we had colonial and creeping bentgrass clones
[00:12:03.780]either grown under well-watered conditions or managed at
[00:12:07.110]about 20% irrigated, about 20% ET, the picture quality
[00:12:11.790]on the bottom pictures is not nearly
[00:12:14.730]as good as that on the top, so they look dead,
[00:12:17.910]but they're not quite dead.
[00:12:18.840]There's still quite a bit of green tissue there,
[00:12:20.790]but definitely are being challenged by drought stress.
[00:12:25.950]So when we compare these species,
[00:12:27.570]one of the big differences is that if you really
[00:12:30.600]drought-stress creeping bentgrass,
[00:12:32.280]it tends to die out, really thin out,
[00:12:34.020]not do well colonial bank grass, once you irrigate it again,
[00:12:37.890]it regenerates pretty quickly.
[00:12:40.200]And so that's one of the challenges.
[00:12:41.520]So we really wanna try to bring
[00:12:43.620]those drought-tolerant traits
[00:12:44.850]from colonial bank grass into creeping bank grass.
[00:12:46.800]But before we can do that, we need to have a pretty good
[00:12:48.630]understanding of it.
[00:12:50.102]And so that led to some subsequent projects
[00:12:52.620]that I'm gonna talk more about for the next little bit.
[00:12:58.380]So if we think back to how we started all of this.
[00:13:01.080]So it was explained early to me in my turf genetics career
[00:13:06.300]that the turf grass genetics industry
[00:13:08.130]is always about 10 to 15 years behind
[00:13:11.610]where the row crops are.
[00:13:13.590]We don't have as much, we don't have genome sequences,
[00:13:18.360]we don't have the money and other resources
[00:13:21.060]to advance some of these, some of the genetics work
[00:13:24.000]as what's done in the other crops.
[00:13:26.610]But we're also fortunate
[00:13:28.320]in that there is a lot of symphony among the grasses
[00:13:31.410]and so there's lots of conservation of genes
[00:13:33.810]and gene order and so we can take
[00:13:35.880]advantage of that from other systems.
[00:13:37.590]And so we've done that for a number of years.
[00:13:40.380]So if we identify a gene of interest in barley or something
[00:13:43.800]like that, we can oftentimes use that information
[00:13:46.770]to try and improve that in the species
[00:13:50.250]or other turf grasses.
[00:13:52.650]And so this is just a graph,
[00:13:54.930]it just illustrates different genomes.
[00:13:57.360]Each ring represents a different genome
[00:13:59.130]and it shows kind of the relationship.
[00:14:01.380]So everything that's in kind of the same piece of the pie
[00:14:04.230]is considered to be related.
[00:14:08.400]And so that was kind of our old way of doing it.
[00:14:10.200]And then about, I don't know, about,
[00:14:12.600]I guess the first time I did some of this work
[00:14:14.490]was in probably 2005, so about 15, 17 years now.
[00:14:19.500]So we started getting into high throughput sequencing work
[00:14:22.770]and this was a great kind of advancement
[00:14:26.640]in tools and technologies for us in turf
[00:14:29.040]because we didn't need to rely on any of that
[00:14:31.560]other information to begin to understand
[00:14:35.773]some of the genetic differences in these species.
[00:14:38.010]So basically the procedure is to design your experiment,
[00:14:45.540]extract RNA, convert that to cDNA, ligate on some adapters,
[00:14:51.690]sequence from those adapters, and then you enter
[00:14:54.810]into this computational phase
[00:14:57.180]where you get these millions
[00:14:59.070]and millions of sequencing reads and then you try
[00:15:00.990]to reassemble something that represents
[00:15:04.650]the true biological sequences.
[00:15:06.930]And so that's a bit of a computational challenge,
[00:15:11.670]but that's something that we do routinely
[00:15:13.320]pretty much every day now.
[00:15:15.630]And then once we reconstruct these reference sequences,
[00:15:18.603]then we can map our sequencing reads back to them
[00:15:21.510]and then we can count the sequencing reads
[00:15:24.390]and the number of reads that map to these different things
[00:15:27.150]give us a idea of their expression levels.
[00:15:30.570]And so with that information we can identify
[00:15:33.420]a number of genes that are differentially expressed
[00:15:36.330]in response to a given trait.
[00:15:39.300]What's nice about this approach, again,
[00:15:41.430]we don't need any upfront information to be able to do it.
[00:15:44.310]And then also it gives us a snapshot at any point in time
[00:15:47.390]of basically all of the express genes, and so it allows us
[00:15:51.540]to look at thousands and thousands of genes being expressed
[00:15:55.080]at any point in time.
[00:15:57.240]And so we've done a lot of work in this transcriptomics area
[00:16:01.470]and basically if we identify or have a gene of interest,
[00:16:06.660]if something, so that's represented by the two blue bars
[00:16:10.530]on the left there, and then we map sequencing reads to it,
[00:16:14.070]which are shown in the black lines above it.
[00:16:16.830]If we just count the number of times those reads map,
[00:16:19.830]so three on the left and then a bunch on the right,
[00:16:22.560]it gives us an idea that that gene is differentially
[00:16:24.720]expressed in response to that treatment
[00:16:27.780]or those two different time points
[00:16:29.580]or different genotypes or whatever.
[00:16:31.110]We can make any kind of comparison that we want.
[00:16:35.112]And we've been pretty successful in my lab of designing then
[00:16:37.710]PCR primers that allow us to amplify some of those targets
[00:16:41.370]and then use them as markers for all different kinds
[00:16:44.490]of things, either to advance certain lines
[00:16:47.670]in our breeding program, to identify new sources of disease
[00:16:50.880]resistance, like we had here in this study.
[00:16:54.720]And also just use them as genetic markers to advance,
[00:17:00.060]well, to differentiate species and things.
[00:17:02.610]So this figure on the right is just a gel image of a couple
[00:17:04.860]of buffalo grass lines.
[00:17:05.850]So this is I think the only buffalo grass slide
[00:17:08.490]I have in here.
[00:17:09.810]And basically we did a RNA-seq type study where we compared
[00:17:14.520]control plants to those challenged with curvularia
[00:17:17.600]inaequalis, which is a pathogen that causes
[00:17:20.130]leaf spot disease.
[00:17:21.930]We identified a number of genes involved in that defense
[00:17:25.470]response that differed between our susceptible lines
[00:17:28.380]and resistant lines, designed some PCR primers
[00:17:31.170]and then tested those across
[00:17:33.090]a number of different genotypes.
[00:17:36.780]And through that we identified new sources
[00:17:39.540]of resistant material that we could then introduce
[00:17:41.760]in our breeding efforts.
[00:17:44.773]And so we could do that, we'd basically
[00:17:45.810]just design PCR primary.
[00:17:47.070]You can see where on the left it doesn't amplify.
[00:17:49.920]If you look at the gel image on the right,
[00:17:51.870]if you look at the left side of that,
[00:17:53.730]that particular prime repair doesn't amplify in those
[00:17:56.520]susceptible lines, but it does.
[00:17:59.430]And so we can use that.
[00:18:00.510]It's pretty simple diagnostic tool to employ
[00:18:04.230]and we've been pretty successful at using this in a number
[00:18:05.850]of different studies.
[00:18:08.220]So we've used it to identify genes involved in chin bud
[00:18:13.080]resistance in buffalo grass.
[00:18:14.180]So I lied, this is the second one.
[00:18:16.110]And then also more recently, we've done it to look
[00:18:19.470]at drought tolerance in the bentgrasses.
[00:18:21.867]And so again, that's really the focus
[00:18:23.880]of what I'm talking about today.
[00:18:26.940]And so we published this paper two years ago now
[00:18:30.000]and basically we looked
[00:18:31.320]at three different bentgrass genotypes,
[00:18:35.190]BCD colonial, which is a colonial bentgrass line
[00:18:39.600]and then Declaration and providence
[00:18:41.670]creeping bentgrass lines.
[00:18:43.140]Declaration is I think a newer,
[00:18:47.370]more modern creeping bentgrass line.
[00:18:49.530]Providence is an older variety.
[00:18:51.900]For today's talk, I'm really just focusing in on
[00:18:53.760]BCD colonial and Declaration.
[00:18:55.860]So I'll refer to them probably as creeping
[00:18:58.410]in colonial bank grasses,
[00:18:59.670]but I know I'll screw up likely and refer to them
[00:19:02.823]as other things just to confuse you.
[00:19:05.040]But basically we designed an experiment.
[00:19:07.260]So we looked at these things growing under,
[00:19:09.270]again, well-watered conditions,
[00:19:11.190]so that's the control treatments here.
[00:19:12.720]And then under drought stress or water-limited conditions.
[00:19:16.560]And we identified a number of different genes
[00:19:18.930]or a number of genes that were differential expressed.
[00:19:20.550]So things that were upregulated, so if we look at the VCD
[00:19:23.310]colonial control versus water limiting,
[00:19:26.640]we see 626 upregulated genes in the second row there.
[00:19:31.110]And those are things that had higher expression
[00:19:32.760]in the control samples compared
[00:19:34.290]to the drought stress samples.
[00:19:36.120]So it would be a number of genes that are down regulated,
[00:19:39.900]turned off, have lower expression when subjected to drought
[00:19:43.470]stress kind of makes sense that we identify a bunch
[00:19:45.810]of genes that are maybe turned off as the plants
[00:19:47.880]reallocating resources and things like that.
[00:19:50.310]And then we also identify 349 genes that are upregulated
[00:19:53.790]or change expression in response to that drought stress.
[00:19:57.804]And so those again are how the plants
[00:19:59.580]kind of either sensing,
[00:20:00.930]responding to that drought stress by turning on
[00:20:03.090]or increasing expression of the number of different genes.
[00:20:06.390]And so this will be more interesting later,
[00:20:10.350]I think rather than just a table of number.
[00:20:13.020]I kinda hate just presenting tables of numbers.
[00:20:15.529]I don't think it's very exciting for talk.
[00:20:18.360]All right, so that's kind of how we've done things
[00:20:20.910]up until now, up until recently where we've done
[00:20:24.240]these transcriptomics type projects, identified some genes,
[00:20:27.540]we can annotate them, figure out what they are,
[00:20:28.920]those kinds of things, and then we can design some specific
[00:20:32.340]primers, work with them, that sort of thing.
[00:20:35.250]But with that we're missing a lot of information.
[00:20:38.760]And so we're missing things that...
[00:20:41.760]Because we're just working with express genes,
[00:20:43.950]we don't have the promoter regions of the gene.
[00:20:48.270]So we can't identify maybe regulatory elements,
[00:20:51.030]things like that, that affect expression.
[00:20:54.000]We can't look more globally at genome structure
[00:20:56.610]and organization, things like that,
[00:20:57.750]that can impact expression.
[00:21:01.530]And so we we're just missing out on a lot of information.
[00:21:04.770]And so a couple of years ago now,
[00:21:08.076]there was a push by the USDA to put in some funding
[00:21:12.750]to sequence a number of turf grass genomes
[00:21:15.720]and several have been released.
[00:21:17.250]I think there's a paper that's going to be released soon
[00:21:20.460]on annual bluegrass, which is probably one of our most
[00:21:22.620]important weed species.
[00:21:25.080]I'm collaborating with some of these folks on the creeping
[00:21:29.010]in colonial bentgrass genomes.
[00:21:30.780]I'm in the process of sequencing a buffalo grass genome.
[00:21:33.330]So we have a bunch of these going on as part of this effort.
[00:21:37.410]And again, the idea is it gives us a little more background
[00:21:40.290]information so hopefully we can make a little more sense
[00:21:43.410]of some of our transcriptomic work.
[00:21:47.490]And so I had mentioned early on
[00:21:50.220]that we're working with tetraploids,
[00:21:52.080]so they have a base haploid chromosome number
[00:21:54.600]of 14 in these species.
[00:21:57.480]And so when we do some of the sequencing work,
[00:21:59.520]we'd essentially expect to have 14 good scaffolds.
[00:22:03.660]But with this particular project,
[00:22:06.150]the colonial bank grasses are shown in the red
[00:22:08.460]and the creeping bank grasses are shown in the blue.
[00:22:12.060]And each one of those dots represents one of our scaffolds.
[00:22:15.690]And so for each of those species,
[00:22:17.430]so there's 1,818 colonial bank grass scaffolds that we got
[00:22:23.310]back from the sequencing facility,
[00:22:24.570]2,284 from the creeping bank grass.
[00:22:28.530]And that's very common.
[00:22:30.600]So we always get way more than we expect.
[00:22:34.950]And so then there becomes this game of analyzing the data,
[00:22:38.310]trying to filter it and identify
[00:22:39.840]those that are maybe relevant, most important.
[00:22:42.510]And there's tons of different ways of doing that.
[00:22:46.212]And so my approach was just to one,
[00:22:48.240]look at the size of them, bigger is better in this case
[00:22:50.910]for the most part, and then, two, also I took the data
[00:22:55.110]from the previous transcriptomics data set
[00:22:58.020]and I mapped those sequencing reads
[00:23:00.360]to all those different contigs or scaffolds,
[00:23:05.010]and that's shown on the vertical axis, right?
[00:23:08.820]So the number of those transcripts that mapped to a given
[00:23:11.790]scaffold shown on the vertical axis,
[00:23:13.980]the length of the scaffold shown on the right.
[00:23:15.930]So ultimately we wanna identify
[00:23:19.081]or work with those 14 chromosomes
[00:23:22.290]from each species or 14 scaffolds
[00:23:25.740]as kind of our...
[00:23:26.573]We're gonna work with those as kind
[00:23:27.930]of our pseudo chromosomes for those.
[00:23:34.020]So that's basically how we got to those,
[00:23:37.170]which is not that exciting, but it's a...
[00:23:41.430]So we have this list of 14 chromosomes
[00:23:44.880]from colonial bank grass,
[00:23:46.050]14 from creeping bank grass.
[00:23:47.970]And now we need to start trying to figure out
[00:23:50.160]which transcripts are on which chromosomes
[00:23:52.590]and some of those kinds of things.
[00:23:54.030]So thinking back to this figure from Keith Jones
[00:23:59.970]and thinking about the relationship
[00:24:01.380]of these different species,
[00:24:02.910]if we align these genomes, we would expect then,
[00:24:10.800]since they have seven ancestral chromosomes sub genome,
[00:24:16.650]one shared sub genome in common between creeping
[00:24:19.410]and colonial bentgrass, we would expect
[00:24:21.270]some of those chromosomes to loosely align with one another,
[00:24:24.960]some creeping colonial bank grass.
[00:24:26.817]And so here is kind of a global alignment of a couple
[00:24:30.120]of different chromosomes in both of these figures.
[00:24:34.740]Creeping bank grass is shown on the vertical axes,
[00:24:37.410]colonial bank grasses on the bottom.
[00:24:38.940]And each one of these just represents
[00:24:40.290]one pairwise combination.
[00:24:42.120]And so on the left is representative of two
[00:24:44.370]that don't align at all.
[00:24:46.710]And on the right is what we might see
[00:24:48.630]if two chromosomes do align.
[00:24:52.380]And so you see this nice line cutting across,
[00:24:55.140]we can identify with this certain introns,
[00:24:58.440]or I mean certain insertions
[00:25:00.420]and deletions where we see gaps in that line,
[00:25:03.780]we can identify certain things like inversions.
[00:25:06.810]So if we see this line moving up and then all of a sudden
[00:25:08.820]it jets back the other way, that means that that piece
[00:25:12.000]has been kind of flipped.
[00:25:13.920]We can also identify things like what's shown in the upper
[00:25:16.920]right part of that figure where we can see duplications
[00:25:21.150]and inversions so we can identify with those.
[00:25:24.810]This information in by itself is not really that useful,
[00:25:28.470]but what it does let us do is it identify,
[00:25:30.660]it allows us to identify the pairs of chromosomes
[00:25:34.110]that are important.
[00:25:34.943]So we did this globally for all 14 and you can see that
[00:25:39.060]there are a number of places where they align.
[00:25:41.850]So that allows us to basically define certain chromosomes.
[00:25:45.600]And then also because these things have certain amount
[00:25:49.170]of chromosomes in relationship to one another,
[00:25:54.570]we also find plenty of places where one chromosome
[00:25:59.670]from colonial bentgrass has two from creeping bentgrass
[00:26:02.940]that align to it.
[00:26:04.920]Okay, so that gives us an idea, initially at least,
[00:26:09.847]of which ones are related.
[00:26:12.180]But then the next step is to figure out kind of,
[00:26:14.820]it's important based on what I talked about previously
[00:26:17.340]about conservation with other cool season grasses.
[00:26:20.130]So we wanna basically find out which ones we should assign
[00:26:25.200]to which chromosomes.
[00:26:26.220]A lot of times we'll use barley as a reference.
[00:26:29.580]Barley has a base haploid chromosome number of seven.
[00:26:32.280]So it's pretty simple genome, easy to work with.
[00:26:35.425]And so that's all of them aligned with one another.
[00:26:38.010]If we separated out on a per chromosome basis,
[00:26:42.870]we can identify certain chromosomes aligned with,
[00:26:46.740]for example, HV1H, so horgan vulgar.
[00:26:50.940]Chromosome one, if you look at that top left figure,
[00:26:53.940]you can see a couple of green lines that are lit up
[00:27:00.180]basically in a couple of red.
[00:27:01.890]All those green dashes represent the colonial bentgrass,
[00:27:06.030]those 14 scaffolds that we're working with.
[00:27:08.400]So essentially the colonial bentgrass genome,
[00:27:10.830]the red represents the creeping bentgrass genome.
[00:27:13.800]And as you work around this,
[00:27:14.970]you can find places where basically all of those
[00:27:17.700]are represented by the horgan vulgar, the barley sequence.
[00:27:25.530]So that just kinda sets up where we're at on a genome.
[00:27:28.470]So I'm not gonna test you
[00:27:29.760]and make you memorize all that stuff.
[00:27:34.230]But again, I just wanted to go back to this.
[00:27:36.030]So our focus with this is to try and identify genomic things
[00:27:40.140]that are controlling gene expression that we might be able
[00:27:43.230]to use when we're progressing drought tolerance or something
[00:27:45.810]like that, increasing. (indistinct)
[00:27:48.210]So we're trying to identify genetic differences between
[00:27:51.120]these species that are conferring some of these adaptation
[00:27:53.550]traits, whether to disease resistance,
[00:27:56.100]drought tolerance, whatever.
[00:27:58.830]Okay, so as a side project then, so I'm gonna switch gears
[00:28:03.120]just a little bit because I mentioned that I was gonna talk
[00:28:07.470]about some of my prior work and some new stuff
[00:28:11.790]and it was a collaborative project
[00:28:14.070]that I did with Brian Waters several years ago
[00:28:17.160]that kind of renewed my interest in this.
[00:28:21.030]And this was the bentgrasses was a project
[00:28:24.270]that's been kind of sitting on the shelf for several years,
[00:28:27.840]five, six, seven years now.
[00:28:29.850]And so I did a project with Brian Waters.
[00:28:32.160]Brian and his graduate student Ragoo...
[00:28:36.510]Well, Brian was interested in nutrient uptake in several
[00:28:40.710]specialty crops, mainly the cucurbits,
[00:28:43.170]but he was also doing some work on melon here.
[00:28:48.565]And he had a particular mutant that was deficient
[00:28:52.770]in its ability to uptake iron.
[00:28:55.020]So he called it this Fefe mutant and his graduate student
[00:29:00.060]Ragoo developed this mapping population
[00:29:03.210]and they basically fine-mapped this mutant
[00:29:06.480]to a very small interval
[00:29:07.920]and there was maybe just 40 or 50 genes in the interval.
[00:29:14.214]But with subsequent work,
[00:29:15.060]they couldn't figure out which gene was responsible
[00:29:19.465]for this iron uptake mutation.
[00:29:23.160]And so Brian and I talked a little bit and we decided
[00:29:25.830]to do an RNA-seq experiment to try and figure out
[00:29:29.310]what the heck was going on.
[00:29:32.836]And ideally in this scenario what we were looking for,
[00:29:36.120]is a gene in this interval
[00:29:38.250]that was differential expressed
[00:29:39.960]with and without and behave differently
[00:29:42.960]between the wild type species or genotype,
[00:29:46.620]which is a Edisto here and the Fefe mutant,
[00:29:50.310]and so there's our gene of interest
[00:29:53.160]and again that was based on some of the work
[00:29:55.650]that Brian had done to fine map this gene
[00:29:58.710]to a specific interval.
[00:29:59.910]And then we also know the genes that are in that region.
[00:30:02.637]And so we could figure out
[00:30:04.230]basically which genes are in there,
[00:30:06.540]we know something about them
[00:30:07.950]so we can guess at which ones are most important
[00:30:11.160]for this iron uptake mutation.
[00:30:15.330]And so again, we're interested in identifying,
[00:30:18.420]or what we're expecting
[00:30:19.650]to see is something that behaves differently,
[00:30:22.350]between the wild type and this mutant
[00:30:25.920]with and without iron, right?
[00:30:28.344]And so that's what we're seeing.
[00:30:29.177]So we definitely see some expression differences between
[00:30:32.880]this iron mutant and Edisto.
[00:30:34.770]You can see that those are recount numbers
[00:30:36.930]that basically a measure of gene expression,
[00:30:41.190]but thinking about how we look at or count
[00:30:44.820]the total number of sequencing reads in these projects,
[00:30:48.450]it wasn't statistically different.
[00:30:50.910]And so that was a little disappointing.
[00:30:52.440]And then the other thing we were interested in is to see
[00:30:55.418]if we could identify differences
[00:30:57.478]between the iron treatments.
[00:30:59.880]And again, we didn't see any differences again.
[00:31:02.820]So there was no evidence at this stage that suggested
[00:31:07.980]that this was in fact the gene of interest.
[00:31:10.380]And so that was a pretty big disappointment for Brian
[00:31:13.260]and for me who said that this project
[00:31:15.180]was gonna be easy and I could just knock it out
[00:31:17.520]and it wasn't the case.
[00:31:18.900]And for any students here, and I know there's at least
[00:31:22.680]one in my class who's here, I think there's a temptation
[00:31:27.720]to stop at this step because most papers and things
[00:31:33.030]that I see, they'll stop here,
[00:31:35.190]they'll publish this nice little table of gene expression
[00:31:37.530]information just because that's the output from the software
[00:31:41.100]tools, but it's important to, to dig a little deeper.
[00:31:44.370]And so if we think back to kind of this cartoon
[00:31:46.950]representation of gene expression,
[00:31:49.740]what we were expecting to see is a difference
[00:31:52.800]in read counts, like what's shown on the left side,
[00:31:55.350]but what we saw is what's on the right.
[00:31:58.741]And so when we looked a little more closely,
[00:32:00.540]it was interesting to actually see what was going on.
[00:32:03.510]So this is the same gene and the kind of gray
[00:32:10.680]graph at the top shows the distribution of mapped sequencing
[00:32:15.120]reads across that gene for the wild type.
[00:32:19.980]And then on the second one there,
[00:32:22.650]it shows the distribution of mapped reads across that same
[00:32:27.030]gene in the Fefe mutant line.
[00:32:30.270]And the vertical scales are not the same.
[00:32:34.350]So what we see is basically they have the same number
[00:32:38.190]of reads mapped to this gene, but it's pretty clear,
[00:32:42.000]I think to most of you, it's clear to me at least,
[00:32:45.120]that the distribution of those map reads
[00:32:46.920]across that gene differs a lot, right?
[00:32:49.440]So it kind of gets halfway through that Fefe gene
[00:32:53.400]and then just stops.
[00:32:55.530]And so that was definitely really interesting to us.
[00:32:58.890]So this was not captured by just the typical differential
[00:33:03.411]gene expression analysis.
[00:33:04.740]And what we found was that a transposable element
[00:33:07.140]had inserted into that gene and disrupted its function.
[00:33:11.370]And the reason that that brings me back
[00:33:13.740]to this agrostis study,
[00:33:17.160]is that I did my PhD work on transposable elements
[00:33:21.030]in agrostis, and so I was very interested in that finding
[00:33:26.220]and kind of revisiting some of that old data
[00:33:28.890]and also revisiting it now that we have genome sequences
[00:33:32.370]to work with too.
[00:33:34.170]And so transposable elements
[00:33:35.730]are these mobile genetic elements.
[00:33:37.980]I think many of us are familiar with them.
[00:33:39.390]First discovered by Barbara McClintock years
[00:33:41.760]and years and years ago.
[00:33:43.740]But since then there's still a lot of unknowns around them.
[00:33:46.890]But there's lots of information about how they can influence
[00:33:50.310]gene expression, disrupt gene function, mess up
[00:33:54.930]regulatory networks, influence how plants respond
[00:33:58.380]to certain things.
[00:33:59.490]So they play a much bigger role than frankly we know, right?
[00:34:04.260]So, and one of the things that I didn't explain very well
[00:34:09.480]at the beginning, is that we're maintaining this bentgrass
[00:34:12.980]at this really tight mowing height, right?
[00:34:15.390]So less than an eighth of an inch,
[00:34:16.873]a 10th of an inch is kind of what modern golf courses
[00:34:19.590]are mowing at.
[00:34:20.640]There's not much photosynthetic activity there,
[00:34:23.760]or maybe not activity, but it doesn't seem like
[00:34:25.920]it could photosynthesize enough to keep these things alive.
[00:34:28.860]And then we challenge them with all kinds of stresses,
[00:34:31.500]traffic with disease, poor management, all kinds of things.
[00:34:37.380]And they never have an opportunity to go through any kind
[00:34:41.160]of sexual recombination or anything like that.
[00:34:44.700]And so it's been kind of my working hypothesis for a while
[00:34:48.990]now that the genomes of these species are highly variable
[00:34:52.800]and they can fluctuate and change in response
[00:34:54.900]to some of those stresses.
[00:34:56.610]And transposable elements are kind of an interesting thing
[00:34:59.280]to look at because they're known to regulate
[00:35:01.860]some of those typically that happens
[00:35:03.870]through some kind of sexual recombination,
[00:35:06.420]but at the same time they can kind of muck up
[00:35:10.050]certain parts of the genome.
[00:35:11.610]So that's why part of the reason
[00:35:14.610]that I've always had interest in these things.
[00:35:18.090]So my PhD work, this is years and years ago,
[00:35:21.810]is focused primarily on mites,
[00:35:23.400]which is a certain class of DNA transposons,
[00:35:26.340]I was particularly interested in those.
[00:35:27.990]It stands for miniature inverted repeat transpose elements
[00:35:30.630]because they're short, they're small,
[00:35:31.890]they're easy to amplify in a lab-based test.
[00:35:37.210]And so they're characterized by having these terminal
[00:35:40.200]inverted repeats shown in red.
[00:35:42.480]I'll show you an example next I guess what that looks like.
[00:35:44.820]So that's shown in those, the black bars there
[00:35:48.450]show the terminal inverted repeats and typically
[00:35:51.150]there's a shorter target site duplication
[00:35:53.910]that flanks those terminal inverted repeats.
[00:35:56.370]It's a direct repeat.
[00:35:57.630]And so that means that it's in the same orientation,
[00:36:00.390]the terminal inverted repeat is in opposite orientation,
[00:36:03.390]reverse compliment, so we can use that information
[00:36:07.230]though to identify these sequences.
[00:36:09.870]We can just look for some of those signatures,
[00:36:11.820]and there's lots of software tools out for for doing that.
[00:36:16.440]And again, we use these to develop a bunch of primers
[00:36:21.360]to study agrostis, and so there was two different types
[00:36:25.710]that I looked at.
[00:36:26.543]One was MIPS, shown here, it's very simple straightforward
[00:36:29.430]PCR reaction, we can see some differences,
[00:36:31.440]and so we anchor one PCR primer to within this mite
[00:36:36.450]and then one outside in the bentgrass sequence.
[00:36:39.300]And you can see how that changes, jumping ahead on me here.
[00:36:46.320]And we use that information along with some other random
[00:36:49.080]markers anchored to those mites and it allows us to really
[00:36:53.250]test and understand kind of relationships
[00:36:56.310]between these species.
[00:36:57.300]I remember I proposed something like this when I interviewed
[00:37:00.000]here and Jeff Mauer, who's a systematicist,
[00:37:02.130]gave me a really hard time
[00:37:03.240]because why would you build this kind
[00:37:06.000]of genetic relationship tree based
[00:37:09.390]on mobile genetic elements that are variable?
[00:37:12.090]And then, yeah, it doesn't make a lot of sense.
[00:37:13.920]And there's actually a justification to it
[00:37:16.828]that I'm gonna talk about today,
[00:37:18.030]but he bought my story so it must be okay.
[00:37:22.800]But for that work, we used like 1200 of these.
[00:37:25.490]We looked at more than 350 agrostis species.
[00:37:29.130]So there's, or not species, but genotypes,
[00:37:32.160]I think we looked at about 50 or so different species.
[00:37:35.430]So again, there's estimated
[00:37:37.620]to be more than 150 different species,
[00:37:41.416]and so we really wanted to look at,
[00:37:42.870]kind of resolve some of the genetic relationships.
[00:37:46.560]Mainly, if we think back to being able to use
[00:37:51.240]inner specific hybridization as a way of introducing new
[00:37:54.390]traits into creeping bank grass,
[00:37:55.740]this kind of information gives us targets
[00:37:58.650]to know if we can use other sources
[00:38:01.500]of plant material to introduce new traits.
[00:38:06.300]Okay, so one last piece of that project before I get
[00:38:09.510]into the new data I guess.
[00:38:12.900]So one other thing that we did is we looked
[00:38:15.690]at these miniature very repeat transposable elements.
[00:38:21.030]And if you have a given DNA sequence,
[00:38:23.640]so these things are oftentimes repeated throughout
[00:38:26.850]the genome and there's lots of copies of them,
[00:38:29.640]several thousand of them.
[00:38:30.630]Oftentimes if it's a sequence,
[00:38:35.220]a transposable element that's been recently mobilized,
[00:38:39.150]they have a high level of sequence similarity
[00:38:41.880]because there hasn't been this length
[00:38:44.850]of time allowing mutations to occur.
[00:38:46.860]Whereas if it's something that's been around
[00:38:49.530]for longer in the genome, it tends to accumulate mutations.
[00:38:53.250]And so we can use that information then to identify
[00:38:57.180]potentially recently active transposable elements.
[00:39:02.610]And so with the early bentgrass study,
[00:39:05.970]not the one that I'm talking about today,
[00:39:08.280]this is kind of the first high throughput sequencing dataset
[00:39:11.400]I had access to, but we identify with some software tools
[00:39:15.060]like 60,000 mites and then we wanted to align them
[00:39:18.210]by themselves, right?
[00:39:19.800]So it's 60,000 by 60,000, which becomes somewhat
[00:39:23.010]computationally challenging to do that.
[00:39:26.250]And then we pulled out certain mites based on their target
[00:39:32.520]site duplication, and so this entire figure here
[00:39:36.450]represents one particular target site duplication class.
[00:39:40.440]And then each column then represents a different terminal
[00:39:45.150]inverted repeat class.
[00:39:46.860]And then within each of those terminal inverted repeat
[00:39:49.080]classes, we align them and then plotted an alignment score.
[00:39:53.670]So in this case, when things have a lower alignment score,
[00:39:58.170]there's more mutations, they don't align that well.
[00:40:00.300]So it's suggested that it's maybe
[00:40:02.100]an older transposable element,
[00:40:04.560]whereas if we have one that kind of shows up
[00:40:07.200]on the north side of the figure there, right?
[00:40:09.300]That suggests that they're more recently acted
[00:40:11.430]because there's a lot more similarity.
[00:40:14.550]All right, so that is just kind of a side note that probably
[00:40:19.110]has no bearing on anything, but that took me, that script
[00:40:23.400]to do that 60,000 by 60,000 pairwise alignments
[00:40:27.030]took like four weeks to run.
[00:40:29.430]So I have to show the data to someone.
[00:40:31.980]All right, so anyway, okay, so getting back to this, right,
[00:40:36.690]so again we're interested in identifying genes
[00:40:41.130]differential expressed, so we can do that pretty efficiently
[00:40:44.730]just with our RNA-seq type study.
[00:40:47.790]But then I kind of threw
[00:40:48.840]all this transposable element stuff at you,
[00:40:52.590]and so now we're interested in taking those genes
[00:40:56.070]from the transcriptomic study,
[00:40:58.710]basically aligning them, putting them on this genome
[00:41:01.950]that we now have access to,
[00:41:03.990]and then, identifying transposable elements
[00:41:06.540]that are in or near those genes,
[00:41:07.950]'cause it might disrupt function
[00:41:09.060]if we can identify some different ones between colonial
[00:41:13.140]and creeping bentgrass might give us an idea
[00:41:15.937]of how some of the function of some of those genes
[00:41:18.750]that are differential expressed,
[00:41:19.680]how it can be disrupted or changed.
[00:41:21.840]And so that's kind of what we focused on.
[00:41:24.000]So we started with a couple
[00:41:25.290]of these two different agrostis lines, agrostis capillaris,
[00:41:29.817]agrostis stolonifera, colonial and creeping bentgrass.
[00:41:33.930]And so this is just some basic data
[00:41:35.850]on the transcriptomes and genomes.
[00:41:37.740]We happen to use the same lines in both of these studies,
[00:41:42.060]which helps quite a bit
[00:41:43.680]because there's a lot of variabilities
[00:41:45.630]I alluded to in the bentgrasses.
[00:41:47.820]And so having the same lines in these studies
[00:41:50.850]kind of helped.
[00:41:54.000]And I guess the big thing to point out here
[00:41:56.070]is just the numbers of transcripts that we have,
[00:41:58.500]because we'll start with those.
[00:42:00.210]So again, we started with our transcripts
[00:42:03.000]and this is just focused on this chromosome one in barley.
[00:42:07.770]So we start, we have a little over 200,000 transcripts
[00:42:11.160]and so we map those to the genome,
[00:42:13.620]but it's a little more complicated than that because we need
[00:42:15.780]to map them separately to each genome, each chromosome.
[00:42:22.860]And so we end up with significantly more mapped sequences
[00:42:27.030]than we started with.
[00:42:28.110]That's not so uncommon because we have partial alignments,
[00:42:31.860]we have things that map to repetitive elements
[00:42:34.320]and so that kind of thing's pretty common.
[00:42:36.330]But that definitely muddies the waters a bit.
[00:42:39.780]And so what we did is basically just search
[00:42:42.690]for things that uniquely mapped.
[00:42:45.300]So they just mapped a single time.
[00:42:47.820]So those, we have a lot more confidence in those sequences,
[00:42:50.880]and so that gets us down to around 10,000,
[00:42:52.710]which is a much manageable number.
[00:42:56.280]And then we filtered it further
[00:42:57.360]because we were most interested in sequences
[00:43:00.210]that were uniquely expressed in colonial bentgrass
[00:43:03.990]that were not expressed in creeping bentgrass, for example.
[00:43:08.187]And so we did that for all of them.
[00:43:10.020]So for each colonial bentgrass, the A cap, A capillaris,
[00:43:15.152]agrostis capillaris, we mapped to the corresponding
[00:43:17.520]creeping bentgrass lines and similarly,
[00:43:20.490]the creeping bentgrass line to the colonial bentgrass line.
[00:43:22.980]So we did that for all of those and found
[00:43:24.510]the uniquely mapped transcripts per chromosome.
[00:43:29.100]All right, so then we went back and we...
[00:43:30.930]So that's just the transcripts part.
[00:43:33.630]And then we wanted to identify the location and distribution
[00:43:38.640]of transposable elements across or near those genes.
[00:43:41.670]And so here's just a cartoon representation of a gene.
[00:43:46.470]And so we looked at first the number
[00:43:49.320]of transposable elements that we could identify
[00:43:51.210]within the expressed sequences, and then we looked at those
[00:43:55.530]in the upstream region.
[00:43:58.110]So, 1,000 base pairs, that's supposed to say, 1,000 not 100.
[00:44:00.763]1,000 base pairs upstream of the gene,
[00:44:03.570]within the gene itself and then 1,000 base pairs,
[00:44:06.450]again, 1,000 not 100 downstream of the gene.
[00:44:11.130]And what is really interesting to me with this
[00:44:14.340]is that we find a lot of transposable elements
[00:44:17.580]within and near these genes
[00:44:19.800]and that's pretty important, I think.
[00:44:23.520]So the other thing we wanted to do is ask,
[00:44:25.920]do we see any differences in the species,
[00:44:29.640]the type of transposable elements that we see
[00:44:33.720]in these different species?
[00:44:34.890]Because if we see a certain class
[00:44:36.960]that's maybe uniquely transposed,
[00:44:40.320]multiplied, whatever in colonial bentgrass
[00:44:42.960]compared to creeping bentgrass, that that might explain
[00:44:46.650]some of the different gene regulation that we're seeing.
[00:44:49.770]So, and also, if we see unique types
[00:44:53.310]or if we see different distribution of these things,
[00:44:55.380]so different numbers of...
[00:44:57.360]There are some differences.
[00:44:58.530]So each of these pie charts represent the different species
[00:45:03.240]and counts of transposable elements
[00:45:05.370]within each one of these sequencing libraries
[00:45:07.950]that we were looking at,
[00:45:09.240]that don't really see much of a difference.
[00:45:13.336]And so then the next question is, can we identify
[00:45:15.960]any that are also related to drought, right?
[00:45:19.110]So that was kind of our last piece.
[00:45:22.260]And so in this case, if we're interested or looking
[00:45:26.130]at just this colonial bank grass line under the well-watered
[00:45:33.180]and drought stress treatments, we see right about 970-ish
[00:45:39.090]sequences differential expressed.
[00:45:40.770]If we had those two together.
[00:45:43.950]And if we look at those 970-ish sequences,
[00:45:48.960]we can identify roughly about 30 transposable elements
[00:45:54.000]within or near those genes, which is really interesting,
[00:45:57.660]especially related to kind of what I was talking about,
[00:46:02.795]about potentially, are those potentially influencing gene
[00:46:04.800]expression related to some of these traits.
[00:46:08.160]Okay, so I just talked about barley chromosome one,
[00:46:11.520]so now I'm gonna go on and talk about the other six.
[00:46:14.880]I'm not gonna do that.
[00:46:16.571]All right, so my wife's outta town this weekend
[00:46:19.290]and she always gives me a to-do list,
[00:46:21.360]so I thought I'd use that here.
[00:46:24.300]So this is my last slide, I promise.
[00:46:26.190]So, I'm not sure how well I conveyed that today.
[00:46:31.290]But these transposable elements in looking at them
[00:46:34.560]and their relationship with our gene expression,
[00:46:37.590]I think is really interesting.
[00:46:40.470]So some of my colleagues that do some of this work in turf,
[00:46:44.550]we've been collaborating on this off and on
[00:46:46.770]in lots of different species,
[00:46:48.630]turf species and we see similar types
[00:46:50.430]of things in in all of them.
[00:46:52.080]So we see lots of transposable elements
[00:46:54.750]expressed in lots of different ways
[00:46:57.300]and they're always mucking up gene expression,
[00:47:00.360]sometimes for good, sometimes for bad.
[00:47:03.720]All right, so we need to look at clearly
[00:47:05.520]for something like this with those rest of those chromosomes
[00:47:07.890]which I'll spare you of today.
[00:47:11.640]I just showed information on colonial bank graphs
[00:47:15.120]on that last slide.
[00:47:16.200]And so it'd be interesting to also look
[00:47:17.730]at creeping bentgrass.
[00:47:19.940]Mainly, I'm interested in seeing if there's any speciation
[00:47:24.570]differences in the classes of transposable elements
[00:47:27.450]between creeping and colonial bentgrass,
[00:47:29.970]particularly, related to their association with genes.
[00:47:32.610]I think that has a lot of value and interest,
[00:47:35.400]that drought tolerance sequencing project,
[00:47:40.080]the transcriptomics project,
[00:47:41.310]we also had providence creeping bentgrass in there,
[00:47:44.130]and I think there's some value in looking at that
[00:47:45.990]to see if we can identify how things are conserved
[00:47:49.170]between the different creeping bentgrass species.
[00:47:55.530]We can do comparative analysis with non-genic regions.
[00:47:58.260]So I focused on the gene space, but it'd also be interesting
[00:48:01.530]to see how that changes compared to the non-genic space
[00:48:03.960]to see if there's some bias in which types
[00:48:07.410]of transposable elements we find in and near genes.
[00:48:12.630]And then also looking at some other traits
[00:48:14.700]I think has some value.
[00:48:17.310]So before I just move on with...
[00:48:20.400]Any questions, if there are any.
[00:48:22.500]I didn't include an acknowledgement slide
[00:48:24.420]because I started putting it together
[00:48:25.500]and it was frankly too long.
[00:48:27.871]So there's just five people in groups
[00:48:30.690]that I wanna thank, though.
[00:48:32.130]So Scott Warnke at the USDA in Beltsville, Maryland,
[00:48:37.020]who I got my PhD under, we still collaborate all the time.
[00:48:40.650]Sean Bushman and Matt Robbins who are at the USDA
[00:48:43.860]in Logan, Utah.
[00:48:46.667]They're leading a lot of the genome sequencing efforts
[00:48:49.080]and so I've been working pretty closely
[00:48:50.370]with them (indistinct).
[00:48:52.230]And then the last two or more groups,
[00:48:55.050]the US Golf Association has funded our research
[00:48:57.840]for probably more than 30 years now,
[00:48:59.820]and so they've definitely helped
[00:49:02.610]advance a lot of these projects in turf.
[00:49:05.670]And then some of my local stakeholder groups,
[00:49:08.610]the Native Turf Grass Group, especially,
[00:49:10.890]in Todd Valley Farms, have supported a lot of my research.
[00:49:14.100]So anyway, thanks for sitting through that
[00:49:15.750]and I'll be happy to answer any questions, if there are.
[00:49:19.477](indistinct) for the presentation.
[00:49:21.840]So for online-only, if you a question, please send me
[00:49:25.554]your question in the Q&A,
[00:49:27.734]through the Q&A button of your Zoom,
[00:49:31.190]and for the audience here,
[00:49:33.300]if you have a question you can just ask
[00:49:35.820]and we'll just using the same mics.
[00:49:41.748](indistinct) one thought, if people
[00:49:49.890]ever planting (indistinct) pre-dominating,
[00:49:57.872]and what are we doing right and doing wrong?
[00:50:01.230]So, I mean I think that that's a great strategy.
[00:50:03.360]We do that all the time, right?
[00:50:04.883]I mean I think one of our recommendations for lawn
[00:50:08.700]in Nebraska is to plant a mixture of tall fescue
[00:50:12.480]Kentucky Bluegrass, that's been a really common
[00:50:15.540]recommendation for us for a long time.
[00:50:17.970]And oftentimes based on environmental conditions and things
[00:50:23.040]we can see certain species kind of win out, right?
[00:50:27.930]With the bed grasses, it's a little different story though
[00:50:30.210]because if we think about how they're used on golf course,
[00:50:33.390]putting greens predominantly, that's where the big money is.
[00:50:36.717]At least we don't want that kind of variability in there.
[00:50:41.130]I think that would detract from playability, visual quality,
[00:50:45.330]lots of things that golfers expect.
[00:50:49.590]So from a research standpoint, sure it makes sense,
[00:50:52.290]we can do that out at our research farm.
[00:50:56.890](indistinct) Challenges, right?
[00:50:59.451]So if we move, say, drought tolerance or something like that
[00:51:00.843]from colonial grass into creeping bentgrass,
[00:51:03.870]I wish it were that easy.
[00:51:04.950]It's definitely not.
[00:51:06.000]So probably an easier trait than that.
[00:51:09.150]One of the problems is there's also a lot of baggage
[00:51:11.730]that comes along with that, right?
[00:51:13.260]So the creeping bentgrass breeders,
[00:51:15.840]that's really our elite material,
[00:51:18.660]they're reluctant to introduce either wild material
[00:51:21.660]or stuff from these inner specific hybrids
[00:51:24.780]because it also drops quality down pretty substantially
[00:51:30.000]in their leaf material
[00:51:30.897]and it takes years and years and years
[00:51:32.460]to get it back to where is was.
[00:51:40.008](indistinct) capturing capacity,
[00:51:50.160]bentgrass (indistinct).
[00:51:52.501]Yeah, I don't know anything about that, so.
[00:51:54.515](indistinct) that stuff being
[00:51:57.924]able to live, (indistinct) and then you've gotta be,
[00:52:05.580]have a great capacity to capture light.
[00:52:09.990]It's got to do something, right?
[00:52:11.713]And that's kind why I've always been fascinated with it
[00:52:14.850]as a species because we're continually managing it at that
[00:52:20.520]really low mowing height, and it used to be probably
[00:52:24.030]even as recent as maybe a decade ago,
[00:52:27.193]the management philosophy used to be keep it growing,
[00:52:30.930]keep it growing.
[00:52:31.763]So they used to like put down as much as eight pounds
[00:52:34.560]nitrogen for 1,000 square feet annually,
[00:52:37.380]water the heck out of it and just push it,
[00:52:39.030]just keep it growing, keep it growing, right?
[00:52:40.770]But it causes a lot of other problems
[00:52:43.200]when it grows that aggressively.
[00:52:44.640]So now we've gone to more lean,
[00:52:48.543]both on irrigation and nutrients.
[00:52:50.550]So now we're down to probably around
[00:52:52.560]two pounds per 1,000 square feet annually
[00:52:55.440]and keeping it more on the dry side,
[00:52:57.540]it makes for a much more faster, firmer playing surface.
[00:53:00.990]And we have less problems, but it's not growing as fast.
[00:53:06.474](indistinct)
[00:53:08.280]I'm afraid to talk to a physiologist
[00:53:10.453]'cause they'll just give some easy answers,
[00:53:11.940]So what happens if you had the (indistinct) rule?
[00:53:16.320]Yeah, we've done a lot of experiments
[00:53:18.480]like that (indistinct).
[00:53:28.402]If you go to the Pacific Northwest, another species,
[00:53:31.167]not that there's gonna be a quiz, but (indistinct),
[00:53:37.490]I think, something related, that's what they call it anyway.
[00:53:41.280]It's all over all lawns out there.
[00:53:44.760]So they'll maintain it,
[00:53:47.100]for these things that have been bred to perform
[00:53:50.920]at that length of an inch,
[00:53:52.590]10th of an inch mowing height.
[00:53:54.930]If you let those grow up, they grow a little
[00:53:57.570]too aggressively so they get kinda like goofy,
[00:54:01.410]if you walk on, it's kind of uncomfortable.
[00:54:03.330]You can't mow it very well with the rotary mower,
[00:54:05.490]things like that.
[00:54:11.910]Online from Bob, do transposable elements play a role
[00:54:16.010]in gene expression of plants like buffalo grass
[00:54:19.470]that have different (indistinct) levels?
[00:54:21.630]I'm sure they do, right?
[00:54:23.392]So most oftentimes because (indistinct)
[00:54:29.070]because they disrupt function of a gene, right?
[00:54:31.980]So they'll insert either in a promoter region
[00:54:34.680]or within the gene itself,
[00:54:35.850]kinda like what we saw with that Fefe mutant,
[00:54:37.830]and it'll screw things up and we'll lose expression.
[00:54:41.580]I don't have the data on that, but we've identified
[00:54:45.960]tens of thousands of these things in every grass species
[00:54:48.570]I've looked at, they're really well-documented.
[00:54:50.160]So I suspect it'll definitely affect gene expression
[00:54:55.170]in some way.
[00:54:56.003]Now if we can use it to our advantage
[00:54:58.260]in some kind of a programmed way,
[00:54:59.580]I think there's value to that
[00:55:01.110]and that's the big unknown question right now, I think.
[00:55:10.501](indistinct) Opportunity understood
[00:55:13.050]what you're talking about, but I have two questions,
[00:55:18.840]probably stupid questions, (indistinct) I've thought about
[00:55:21.358]for a long time and you know full-well that I'm not
[00:55:26.340]a geneticist (indistinct).
[00:55:33.330]You're talking about the (indistinct) levels of these
[00:55:36.317]and you know that I worked in the past with both
[00:55:37.860]Johnson grass and sorghum (indistinct)
[00:55:46.110]tetraploid (indistinct) that allows for (indistinct)
[00:55:51.240]reproduction, it seems more common that
[00:55:53.820]if you're tetraploiding, (indistinct)
[00:55:55.443]tetraploiding (indistinct) you have (indistinct).
[00:55:59.610]Is there something to that genetically?
[00:56:02.610]I honestly don't know.
[00:56:05.760]It is interesting.
[00:56:06.840]I'm pretty sure velvet bentgrass,
[00:56:09.210]which is the most well-known documented diploid bentgrass
[00:56:14.070]is just a bunch type, I'm pretty sure.
[00:56:16.620]The grass is stoloniferous, stoloniferous,
[00:56:19.243]the grass is capillaris,
[00:56:20.971]and those are the two I talked about today.
[00:56:22.590]That's more rhizomatis with some stolons.
[00:56:26.760]With buffalo grass though,
[00:56:30.330]I don't think we really see a difference,
[00:56:33.330]so our diploid lines,
[00:56:35.280]they produce all kinds of stolons
[00:56:37.170]the same as our tetraploids and hexaploids,
[00:56:40.363]so I feel like it's probably not as much related
[00:56:43.380]to (indistinct) as it
[00:56:46.539]is just kind of a genetic artifact of the species.
[00:56:49.170]But I don't know what contributes to that.
[00:56:52.140]I think it's a good question.
[00:56:53.610]I mean, our breeding efforts on the bentgrasses,
[00:56:57.450]how they produce stolons, inner node length,
[00:57:02.640]how aggressive those stolon spread,
[00:57:04.980]if they grow along the ground or up over the turf canopy,
[00:57:09.210]those are all traits we're really interested in,
[00:57:11.220]in our breeding efforts.
[00:57:13.182]And so having a better understanding of that
[00:57:14.700]I think is important, so it's a great question,
[00:57:17.880]but I don't really know.
[00:57:20.520]You had another one, too, or no?
[00:57:22.860]Anybody else got a question?
[00:57:25.354]A smarter question?
[00:57:27.964]My second question had to do with conservation genes.
[00:57:31.620]Yeah.
[00:57:32.453]I mean it's always been so, we knew back in the 90s
[00:57:35.010]for sure that the ALS (indistinct).
[00:57:43.200]Weeds became very resistant to them very quickly
[00:57:46.080]because there were as many as, we now know,
[00:57:48.810]up to eight mutations that occur that would modify
[00:57:53.325]the shape or function of the gene,
[00:57:55.530]but not make it unusable for what its purposes (indistinct).
[00:58:03.660]That was not the case.
[00:58:05.010]So I've always said, well, it's because whatever
[00:58:07.920]the ESPS gene is served then for the ALS genes,
[00:58:13.887]but I don't know that, and I wonder why it is
[00:58:17.400]that some genes like that would be more conserved
[00:58:20.007]and more protected.
[00:58:22.440]I mean, (indistinct) not so much the mutation changed,
[00:58:32.865](indistinct)
[00:58:36.660]it was about the expression like that.
[00:58:38.940]Yeah.
[00:58:40.221]Which is completely different
[00:58:41.325]than (indistinct),
[00:58:43.198]and I'm just wondering if there, why is it that some genes
[00:58:46.495]are like that and others not so much?
[00:58:48.547]Yeah, and that's a great question.
[00:58:50.370]So within the gene itself, naturally the entire genome
[00:58:56.790]is exposed to different things
[00:58:58.140]and accumulates mutations, right?
[00:58:59.397]And some are more successful than others,
[00:59:02.100]the more successful ones proliferate, and the other ones
[00:59:05.471]that are less so don't, and the ones that are detrimental,
[00:59:09.948]it craps out and they don't do well, right?
[00:59:12.420]And so in some respects, the genes that are really important
[00:59:16.950]in kind of everyday function, photosynthesis,
[00:59:19.770]and things like that,
[00:59:20.970]those are the ones that are very highly conserved
[00:59:23.250]or highly redundant in the system, so if you lose one,
[00:59:28.110]you have another backup copy, right?
[00:59:32.460]I frankly don't know enough
[00:59:33.540]about herbicide resistance genes,
[00:59:37.710]and so the promoter regions,
[00:59:39.900]which oftentimes are involved in regulating gene expression,
[00:59:45.450]those probably come to a little more rapid mutation
[00:59:49.290]than the gene itself.
[00:59:51.060]There's a lot of selection pressure to maintain
[00:59:55.500]the sequence, the conservation, the sequence of the gene
[01:00:02.582]a little more loose in the promoter.
[01:00:05.190]But at the same time, it's the same kind of story.
[01:00:08.040]If you get some mutations that are deleterious
[01:00:11.370]to that region and muck up expression,
[01:00:15.737]it's gonna screw up function of that gene
[01:00:17.520]and then that plan is not gonna be successful, right?
[01:00:20.070]And so a lot of those are kind of weeded out over time,
[01:00:24.030]essentially, so the reason that some do better than others
[01:00:28.050]are either they're smaller, so less of a big target
[01:00:31.590]for some of these mutations,
[01:00:33.750]or they're really important genes,
[01:00:35.820]and so (indistinct) they're redundant copies of them.
[01:00:39.480]Those are kind of (indistinct).
[01:00:47.096]All right.
[01:00:49.892]Good.
[01:00:51.448](indistinct)
[01:00:56.100]You mentioned at the beginning the susceptibility
[01:00:58.817]of the disease, and drought tolerance
[01:01:04.230]is kind of the differences
[01:01:05.760]between the colonial and the creeping.
[01:01:09.927]Which one of those is a bigger priority, or (indistinct).
[01:01:16.590]They're kind of, I mean that's a good question,
[01:01:21.345]and I don't know.
[01:01:22.178]So the reason is that, we can show pictures
[01:01:26.790]of this really pristine, nice golf course,
[01:01:29.160]but I can tell you all of my colleagues
[01:01:31.560]were still trying to develop, improve better quality stuff,
[01:01:35.730]but that's pretty low on our radar, right?
[01:01:37.560]So instead what we're trying to do is breed for things
[01:01:40.590]like improved drought tolerance, improved disease tolerance,
[01:01:44.340]even if you don't as a manager, cut back on your water,
[01:01:47.520]it gives you a better,
[01:01:48.660]a bigger window for your material to persist, right,
[01:01:51.660]especially on something like a multimillion dollar
[01:01:54.780]putting green, right, which you can't afford to lose
[01:01:57.840]or you're out of a job.
[01:02:00.870]And so I think one, so it's an interesting question
[01:02:05.010]for different reasons.
[01:02:06.090]Certainly, drought tolerance is probably number one
[01:02:08.880]on the list right now
[01:02:09.960]for most turf grass breeders for improvement.
[01:02:13.440]But dollar spot is the most economically important disease.
[01:02:18.090]And so that's the only caveat I have,
[01:02:21.120]is that there's been tons of efforts
[01:02:22.860]to develop dollar spot resistant bentgrass.
[01:02:27.570]So that's why it's a hard one to answer,
[01:02:29.070]but I'd say probably, probably drought.
[01:02:31.744](indistinct)
[01:02:35.217](indistinct) on the dollar spot,
[01:02:37.320]I mean the two best are probably less susceptible.
[01:02:41.180]I mean, they've done a pretty good job.
[01:02:42.930]You look at at (indistinct) station.
[01:02:46.260]I agree with that.
[01:02:48.140](indistinct)
[01:02:50.820]You know any superintendents that aren't (indistinct)
[01:02:53.730]on their regular schedule?
[01:02:55.680]No, they're still (indistinct).
[01:02:59.040]That's the problem we run into.
[01:03:00.853](indistinct) They're clearly more (indistinct),
[01:03:03.270]absolutely, right, and so, and like I said,
[01:03:06.720]breeders have really come a long way on the new material
[01:03:09.690]of improving drought tolerance too,
[01:03:11.700]and disease resistance while improving quality,
[01:03:15.690]but I feel like quality is kind of secondary
[01:03:18.090]to some of those other, but I don't.
[01:03:19.860]I think they're taking advantage
[01:03:21.326]of the drought because they know a drier green
[01:03:23.340]is a faster green and plays better and all of the components
[01:03:26.460]that they're looking at.
[01:03:27.293]Yeah, and I mean if you think about the acreage
[01:03:28.890]on a golf course, greens are a pretty small piece of that,
[01:03:34.320]and so saving some water on a green
[01:03:36.110]is not gonna save you overall on your budget.
[01:03:38.760]It's really more in the fairways,
[01:03:40.560]which are less higher value.
[01:03:44.370]But that's really where you're gonna probably make
[01:03:46.050]the biggest impact on some savings.
[01:03:49.680]So, yeah, no, I mean, I think that's a good point, Rock,
[01:03:51.930]but I know, I don't know, (indistinct), right?
[01:03:56.730]Yeah, one and a half percent
[01:03:57.780]of the acreage and they take up 60% of the chemicals.
[01:04:01.782]Yeah, right?
[01:04:06.747]All right, let's cut it off.
[01:04:09.625](audience applauds)

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How Do They Survive That? Stress Response in Agrostis

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