Good morning, welcome. In this presentation, we'll be presenting a quick overview of an ideation that we have, the architecture, and more about a deep dive of the architecture, the use cases that we have, and how it can enable our enterprise customers and different other users to use this application, service sentinel, and use the use cases. I am Partha. I lead the solution development for next generation technologies in open source communities. We are active contributors to OpenStack, Open Daylight, and OpenWaySwitch. Along with me, I have Swati. Hello. Hello. A very good morning to all of you. I'm Swati, and I am a solution architect from TCS. I'm working on OpenStack. So our today's topic for discussion is service sentinel. This is basically a mobile application that deals with the critical OpenStack operations for the OpenStack users on the go. So to provide a heads up, what we have for you today is in the first section, we are going to show you what are the day to day operations of OpenStack, and what are the OpenStack users still missing. So we'll draw an insight into what is still there in OpenStack that are still not supported for the users while mobile. In the second section, we will take a deep dive into the viable service sentinel use cases, the technical architecture that it covers, along with the different dashboard it has for different kinds of OpenStack users. In the third section, we demo day in the life of a user, showcasing what are the key activities of OpenStack that can be performed via service sentinel for the OpenStack users. So to kick off, let's take a look at what are OpenStack users doing today. So a diverse variety of OpenStack users are working on tools. They are working on OpenStack frameworks, products, suites, and et cetera. Depending upon the kind of work that the users perform, they are primarily classified into three main categories. So as you all know, category A users will be the ones who are basically dealing with the infrastructure operations. They are performing different kinds of monitoring activities via different dashboards, OpenStack tools, et cetera. And these users are also dealing with the scaling request depending upon the criticality of the request. The infrastructure users are also responsible for the migration activities across sites, depending upon the thresholds of the resources. The second category of users that we have here are basically the ones who are dealing with the CI CD operations, that is the continuous integration and continuous development. So as per different release cycles, we have development activities, we have release management activities, and we have deployment tasks that have to be performed on different target holes. So DevOps user will be able to perform such tasks via our application. The third category of users we have in OpenStack are the general users. As the name suggests, these users are the ones who are using the services that are provided by different OpenStack service providers. By service providers, we mean here they are the business people or the enterprise-specific people who are responsible for planning, strategizing, different OpenStack product suits, and services. Moving to the next slide. We named category A users in Service Sentinel as a lab-infra-people. So as we just discussed, the lab-infra-people are the ones who are managing the monitoring activities, performing horizontal scaling, vertical scaling, and migration across sites. So there are certain key challenges that a lab-infra user faces today while on the go. He's not able to perform certain tasks, which are critical to him. For example, we have, can he actually monitor the various sites across locations on the go? Or can he monitor or address different kind of service requests or scaling requests while he's mobile? Or the third challenge for him can be if he wants to perform a scaling or migration activities while on the move. So these are the key challenges that a lab-infra user faces today. Moving to the next category of users, we call them as the DevOps users. As the name suggests, these people are the ones who are basically engaged in CI CD at TAS. So here also we have three main challenges that a DevOps user faces today. So can he actually monitor or trigger the different kinds of build requests of critical open stack bugs or blueprints while he's mobile? The second challenge for him is he wants to monitor different build processes, and on which tool the build process is happening right now. So there might be certain failures, and he wants to deep dive into the build process to check out where and all the root cause lies. This will enable a DevOps user to further take actions to resolve a particular issue. And the third challenge can be when he has to perform certain releases on the target host while on the move. So these are the key challenges for a DevOps user today. And coming to the last family of users in open stack, these are the general users. So here also we have certain challenges. As a general user, I want to be updated with certain activities of open stack services. I want to be updated with open stack vendors and categories of product suits that they provide. As a challenge, I have is when I want to request certain feature sets, or I want to order a product, open stack service, from vendor XYZ. So I want to, I should be able to do that from a mobile application itself. I want to see the list. I request for a particular open stack product and there you go. The second challenge can be when I feel like comparing the different open stack services that are provided by different open stack vendors. And I just want to fire an act to compare commands so that I can fetch out my results. The third key challenge can be when I am subscribed to certain open stack product features and I want to receive notifications for that particular product or a vendor. So this will also provide a win-win situation for a service provider because he can enable or keep the users abreast with the open stack services that are still going on today. Moving to the next slide. So boom, this gives a view of Service Sentinel. That is how an on-the-go user will be able to access the open stack critical operations on the go. This solution will enable all the open stack users to get rid of their main pain areas. And the modularity and extensibility of this application will make it interoperable to work with different enterprise tools as well. This is applicable, as we discussed, for the LabnPri user, the DevOps users, and the general users of open stack. Our final aim to achieve via Service Sentinel is to allow any time and anywhere access of the open stack critical operations on the go for any kind of open stack user. To summarize, we discussed about the different kinds of main-to-main day-to-day activities of Service Sentinel. So we now will do a deep dive into the top-level features of Service Sentinel. What are the key features that it provides today that makes it unique? The first one being on-the-go. That is, it allows any time and anywhere access of the open stack operations to the user. The second one being collaboration tools. That is, it can be made interoperable with various open stack collaboration tools as well. So today, various open stack tools are evolving, be it public, be it open source, be it proprietary, or there are certain licensed tool as well. So the extensibility of this application will enable it to interwork with tools via adapters. The third key feature setters, it is an extensible framework. What we mean by that is, it can be extended with existing enterprise solutions that are existing in today's world and which are otherwise only available via CLI or web-based interfaces. The fourth key feature setters, it can enable the services provided for the DevOps users and the lab and for people to carry out the mundane tasks. The fifth key feature setters, it can be enhanced for the general users as well so that they can use the services that are provided by the service providers of OpenStack. Last but not the least, this is customizable and deployable. That means it can be tailored and customized according to the needs of different enterprise networks. So to summarize, we have discussed about the day-to-day operations of OpenStack users, what are the users missing, what are the top-level features of Server Sentinel, and let's take a deep dive into the architecture of Server Sentinel. In Server Sentinel, we target three main use cases for the lab-infra users and they are the remote monitoring of data centers or sites across locations. The second one can be a lab-infra user will be able to perform scale-up and scale-down activities of the resources across locations depending upon certain KPIs. And the third one can be when a lab-infra user will be able to manually trigger the migration activities. So for example here, I can state this, in daytime the sites are used to the maximum potential. And in lean time hours, there is always a scope of reducing the power consumption. So a lab-infra user will be able to perform these migration tasks so that the VMs can be consolidated and can be used to the maximum potential via Server Sentinel. Below we have different dashboards that relate to different tasks and we will see that in the forthcoming demo. Moving to the next slide, before we deep dive into every use case of the OpenStack user, we will discuss in detail about the Server Sentinel framework and the high-level architectural overview. So here we have four main tiers specifically. The first tier being the presentation tier where the users can receive requests. The users can be lab-infra, the revops or the general users. And this presentation tier interacts with the northbound interface or the NBI layer through a certain REST APIs that we have written. The NBI layer consists of Sentinel-specific or vendor-specific APIs that perform the different tasks on the controller or the Sentinel-coliar. The Sentinel-coliar consists of various components that are targeted when a lab-infra user or a revops user, et cetera, perform certain kind of activity and we will discuss that in detail in the forthcoming demo. The next is the Sentinel agents tier. So here we have certain agents that are doing different kinds of jobs depending upon the activity. For example, we have the monitoring agent that is looking over to the monitoring task of hosts, VMs, resources, and so on. The second is the tool agent tier which is basically leveraging different kinds of open-stack tools or the third-party tools that are used for performing the tasks for the lab-infra or the revops user. The next one is the message broker that is being used to streamline the communication between the Sentinel-coliar and the base-level APIs. And the last one being the DB connector which is responsible to fire DB-specific commands on different vendor databases. Along with these agents, we have the lower API layer as well which consists of public APIs, private APIs, and third-party tool APIs. Now let's take a look at the deep-dive architecture for service Sentinel lab-infra users. As we discussed, the service Sentinel architecture will remain the same. Only the components will change with respect to the tasks that a lab-infra user performs. So here the Sentinel-coliar with consists of four main components. The first one being the resource manager which is basically used for tracking the resources and updating the records of the resources pre- and post-migration and scaling activities. The second is the workflow manager. This comes into picture when different user requests come up on the dashboards and the processed responses are sent on the respective dashboards. So the workflow manager will also be responsible when there are certain notifications coming up from different enterprise networks as well. The third one being the scheduler. So scheduler is a component that is scheduling different kinds of scaling requests and different kinds of migration requests across the sites and also depending upon the priority of the request. And the last one is the load balancer. So load balancer is tracking different resource APIs to distribute the workload and the traffic that is driven by different kinds of servers and the service request. Let's move to the next slide. Here we can see what kind of APIs we are leveraging here and what kind of tools we are using in this current release of service Sentinel for the lab and for users. Some of these APIs listed here are the resource APIs that is used for gathering or updating the resource records. The Selometer API that we are using here for the meter list and the sample list records. Griffana is the tool that we are using for different kinds of monitoring activities and it has various kinds of dashboards. For scaling and migration, we are engaging the APIs of OTCS and House Framework that is NFV Concerto. And lastly, as we explained, this tool can be extendable with different enterprise networks as well. So we are planning to integrate it with other third party tools like Ibana and LogStash. So we discussed about the lab and for user use cases, the architecture for a lab and for user and the different kinds of APIs. Now let's take a look at how the logic flow happens for a lab and for user when he performs different tasks from a mobile application. The first sequence shows how a migration or a monitoring activity is happening from the dashboard for a lab and for user. So these are the key functions that are taking place to actually fulfill the scenario of monitoring of the sites. The second scenario is when a user is performing the migration activity across the sites. So this kind of workflow happens when he's performing migration to reduce the carbon footprint. And the third sequence comes into picture when a critical service request comes into the queue of a lab and for user and he has to fulfill that request. So the third is for scaling up or down the resources. Moving to the next category of users, we have the DevOps users. So these users are the ones who are basically dealing with the CI CD task and equivalently important is to get the releases deployed on different testbed environments. The main use cases that we are targeting for a DevOps user in Service Sentinel are to remotely monitor different kinds of service requests or the build activities that are taking place. The second use case can be he can track the different build processes that are happening on different tools and also he will be able to perform the root cause investigation of where and all the requests are failing, where are the block requests and what applicable action he can take to resolve a particular issue. The third use cases when he allows the deployment of a created package on different target hosts. Moving to the next slide. Here we present an architectural overview of Service Sentinel for DevOps users specifically. So the layout will remain the same. That is the framework for a Service Sentinel. The Sentinel core layer will now deal with only two main components here, that is the build manager and the release manager. So as the DevOps user are mainly engaged in the building processes, the build manager here will deal with the components that are involved in the performing the build request of different packages or releases. This manager will in the end forward the details of the packages or the releases to the release manager. And lastly, since a DevOps user's primary task is to perform the deployment of the releases on different target host bed environments, the release manager component will come into picture. So this is primarily responsible for creating the releases from the build packages and getting these releases deployed on different environments. After we have discussed about the architectural detail for a DevOps user, we have the different APIs that we are leveraging in the current release of Service Sentinel for a DevOps user. And some of the tools that we are using here are Git and Garrett APIs for tracking the repository changes, the Jenkins API that we are using for the build processes, heat and zero meter we are basically using for gathering the meter records and performing the automated deployments. And it can also be extended with third party enterprise tools as well. For example, we are planning to integrate it with dockers, containers, LXC, Ansible, Zool, NotePool, et cetera. Moving to the next slide. This gives an overview of the different dashboards we have for a DevOps user on a mobile application. So we will discuss this in detail in the last demo. Coming to the last family of users, that is the general users in Service Sentinel. So as we discussed, the general users are the ones who are using the services that are offered by the service providers of OpenStack. The three main use cases that we are targeting for a general user of Service Sentinel are, firstly, he can deep dive into the vendor specific catalogs. He can check out what are the different vendors available in OpenStack world and what are the different kinds of services or the product suites that they provide. Second one, he can have a comparative readout, that is he can compare and filter the different OpenStack services that are provided by different service providers. And thirdly, he can keep the, it is like the solution can keep the users notified and updated with the services that are provided by the providers. So this will be a win-win situation for the service provider itself because he can keep the users updated with all the OpenStack services that are available in his enterprise. Moving to the architecture overview of a general user in detail, the basic framework will remain the same, only the Sentinel core components will change here. So the workflow manager is usually required for processing the requests and the responses. Then comes the services module, which is basically dealing with managing different kinds of OpenStack provider services and also performing a comparative study of the different OpenStack services that are provided. The next comes the policy control module, which comes into picture when a general user requests for certain policy from a service provider and a service provider can perform a feasibility check via this component so that he can enable or disable a particular service for the general user. So in all, we have discussed about what are the users missing today? What are the day-to-day operations of OpenStack? What are the high-level service Sentinel features that a user can use on the go? Now, let's take a look at day in the life of a user where we have a recorded video of the demo because we have emulated this environment on an XS tab. So this shows a dashboard overview for a lab-infra user, where in the left panel, we can see the different sites that a lab-infra user can monitor. Once I put the status of site A as on, the different processes start for this particular site. That is, we can see the usage or the memory is changing, the number of VM processes are changing and in the graph, we can see the RAM usage in the last one hour. So now I have put the site B also on. So here also, the processes keep on starting. This is basically a wandering dashboard where the user can see what is happening on different site locations. In the next view, I am able to see a detailed view of a specific site or a data center that is site A, Sheena Gava. Here, I will be able to perform the migration activity from this dashboard. So once the user selects a particular host, he sees that there are certain resources that are about to reach the thresholds. For example, the threshold value is 85 and so let's see what he does. He selects certain particular VMs who have reached the threshold beyond 85 and he wants to perform the migration activity. So for the migration activity to take place, the user has to select a destination site. The migration activity can take place in the same site or a different site. He selects a destination site from the dropdown. Suppose he selects site B and he starts the migration progress to happen. In this migration process, the VMs that have attained their threshold are being migrated from one host to another or from one data center to another. The third use case that we discussed was regarding scaling activity. So here, this gives an overview of the different requests that I have received on my dashboard for scaling. Some requests have a high priority status amount against them. The user goes and selects the high priority request first and he wants to scale the host so that the users or the RAM or the CPUs goes up. In the backend, there are certain APIs we are leveraging from the thesis in-house framework that is NFV Concerto, which is basically taking care of what are the feasibility checks required for the resources. So this is a scaling process happening for site A hosts. This is all we had for the lab infra users. Now let's take a look at the demo for a DevOps user. Okay, so this shows a dashboard for a DevOps user. When he has received certain requests for build activities, these requests are for certain bugs that he wants to get built on certain tools of OpenStack. So the user decides to pick on some of the bugs here. That is the first three bugs so that he can start the build process for these bugs. He starts the build process and what happens in the cycle is for a particular bug that is the first one, there are different tools that are being used for the build activity. So the first one gets ticked here. That means the build process for this bug is attained and the second one is still on with the build request. We can also check out the cycle here that we had clicked on three bugs that were there for the build request and this is dynamically happening here. When the third bug is also finished, a build cycle is complete. Now we take a different scenario wherein there is a bug which is facing a problem for build request. I've selected two more bugs here. The build process completes for the first one and in the second one, we'll see what happens. This is a process that is facing an issue while the build process. I monitor it for some time and I see that this is not moving on. Then I'll take a deep dive into a detailed view of what's happening for this particular bug and I monitor the build process for only this bug. I can see here this bug is marked as yellow. That is still, it is pending. And I see here there is a red mark for the Jenkins tool. That means it is failing at Jenkins. From here itself, I will be able to monitor the issue that is coming up in Jenkins for this particular bug. It says, prepare an environment for the run. So I'm able to track the issue that is happening here and I will be able to log this issue in Storyboard as a DevOps user does. Coming to the last use case for a DevOps user, we have the deployment activity. So here we basically see in the left panel, there are certain releases that I want to get deployed on different hosts that are on the right side. The processes are running on different kinds of hosts. I pull a Juno release that is 3.1 and I want to make it deployed on 3.0.  Here I start my deployment process. So this is very plain and simple via service central. Things are made very easy. The deployment activity, the monitoring tasks, the scaling activities, the migration activities, etc. Now let's see what we have for the general user. As we discussed, a general user will be able to perform the tasks that are offered by the open stack service providers. So this gives a basic view of the dashboard for a general user where he has certain open stack news and events coming up on the dashboard. And on the leftmost panel, there are certain vendors that are available for a general user. He can pick on those windows and decide on the activity. There are other features as well for a general user that is ask open stack, attending IRC, there are sharing details, add to favorites and whatever the products he has subscribed to. The second use case that we were discussing was comparing products of different open stack services. So let's see what happens when he clicks on comparing products. A general user will be able to see different open stack products and services when he clicks on comparing products. So now we select two different products. These products details will also be available when he clicks on different kinds of vendors. So that they provide the vendor specific products of open stack. He has selected two products. He can subscribe to a particular product. Now when he says compare products, he fetches the details of two products of different vendors or the same vendor along with the feature sets. So this will enable a general user to perform the comparing and filtering activity according to his need. That's all we had from our side. We are open to questions. Thanks, Wathi. So we are happy to take your questions. As we mentioned to summarize, the service Sentinel is more of a framework which can integrate with any of the enterprise open stack versions. And so it's more as it has modularity and extensibility to connect with any of the enterprise customers or products. So any questions, we are happy to take that. Logs, yeah, control. Which user you are talking about? Archive. Okay, so the question is for any of the users, are we able to access any of the logs or do we get access to those logs, right? Okay, so for build activities, if you consider the DevOps users, he will be able to monitor different kinds of activities or the tools that are being leveraged for a DevOps user, as I just said. So when he monitors the build activities, he will be able to check out the tools, right? The build activity was failing on one section that was red that time. So there he will be able to find out what is the different problem. There will be a proper link on the dialogue and he can check out the logs from that variant. So while at present we're retrieving only the exception, it will be another line of code, a few lines of code to access the logs and retrieve it back on the dashboard. Yeah. So that's feasible. Any more questions? If not, thank you for your time. Thank you. Thank you.


For the opportunity to be here. And to talk a little bit about how I see sort of past and future interplays between questions of basic biology, fundamental mechanisms, and sort of unbiased approaches to collecting genomic data. All good? Okay. Okay. And so, and I want to note that a lot of the things that sort of I want to talk about today are things that come from not only my head, but also discussions with John Liss, who unfortunately cannot be here today, but where I sort of want to make a plug for the ideas that he and I would probably both be presenting here during these discussions. So basically from the context of basic biology, one of the things that we've heard again and again is that as we've started to describe what these functional elements are, or these regulatory elements are, it's going to be important to understand really how do they function. And I think we've heard a few examples of where we can't assume that all enhancers or all silencers are the same, that they function identically, and that the logic or the grammar underlying them is going to be identical. And so one of the things that I think we've learned as of, you know, the past few years is that these early studies showing that enhancer regions were actually regions of transcription, that's not just the locus control region for beta-globin, that's actually a really generalizable thing that we can say about enhancer regions and these regulatory elements is they're not just sites where transcription factors bind and only function at a distance, but there are local events taking place. There's local transcription and that's something that I think really needs to function, to get its way into our catalog of these regulatory elements is to understand the transcription of non-coding RNAs that's happening locally. And so I think that this really begs the question of what new readouts and what new techniques we should be developing, we should be focusing on. And so I think we've heard a decent amount about possible readouts for regulatory elements, things like everything from reporter assays to some really lovely sort of unsophisticated phenotypic examples. And so I think that we really need to think hard about if we're going to attack function, how are we going to define function in specific contexts. But I do think that it's important in our description of these elements to take the step beyond chromatin state, beyond histone modifications and to start asking questions about how these things are affecting gene expression and in fact how the expression of these elements, how these non-coding RNAs is being regulated. And so I make a sort of push for not just doing this by thinking that expression is summed up in an RNA-seq experiment. That tells you about processed, stable, polyadenylated RNAs and they're really cheap, really easy experiments that you can do that tell you just so much more. And so I'm going to sort of argue that we need to start looking at nascent transcription, nascent RNA species so that we can study the direct and proximal effects of enhancers. So we've heard arguments that enhancer effects could be either amplified or suppressed by everything that functions downstream of that, right? If you're specifically looking at transcription at an enhancer and at nearby genes, then you don't have to worry as much about processing or stability or localization or translation of the protein, et cetera. And so I really think that we need to come at this from both angles. I think we need better assays of the proteome and I think we need better assays of the nascent transcriptome to really understand how these two things interface with each other because there's a whole world in between there that we don't fully understand. Okay. So I want to also make the argument that doing so doesn't just tell us something about basic biology, but if you can figure out a way of taking let's say human-derived IPS lines or some sort of differentiated tissue and looking at nascent RNA, you can quantitatively and simultaneously measure the activity from an enhancer and all the local genes in that region as well as understanding how changing expression in that region affects all the other genes in the genome. And so I think you get basically a quantitative effect of how changing, for example, sequence or deletion of an enhancer affects not only local target genes, but the entire genome and I think then you start to get some insights into networks of interactions. Okay. So again, I'm going to sort of suggest that we need to look at more sensitive measures of transcription and how it's affected by regulatory elements and again not just identifying the direct target in the local region, but also sort of getting at these big networks. And I want to just point out that if you can identify where transcription takes place in an enhancer, then understanding the transcription factors that are regulating that is easier. Now I'll give you examples of how identifying where enhancer transcription takes place pinpoints a spot, a nucleotide around which you can look for transcription factors and that gives you a lot more focus, a lot higher resolution than looking at a 5KB region that has some histone modification. All right. And so also one of the things that we heard from Joe yesterday is that ultimately to understand how these things function, how these regulatory elements function, we need to start to get a handle on how these might be affecting gene expression at the level of initiation or elongation, RNA processing, RNA stability. And by defining exactly where transcription starts and ends, I think you can start to put a bound on what these non-coding RNAs do. If they're really short, if they're long, can you find hidden orps by better defining the actual extent of that transcript? And so I think that we need to work harder to find assays that can be high throughput. Those that require a small number of cells. And ideally they would be able to yield meaningful data in a sort of cheap way, meaning that you can get some information without having to sequence incredibly deeply, which is an issue with some of the histone modifications, so that we could actually multiplex and evaluate different time points, different conditions, multiple either patient samples or deletions and SNPs. Okay. So this is my main point is I think that in a next iteration of ENCODE, we can look more closely at RNA and not just a full, stable RNA but also nascent and newly produced species because I think that this is efficient and direct way to look at function. And I just want to give a couple examples of how unbiased genomic data collection has already interfaced with fundamental biological questions and how they've both really led to new techniques that have then fed back and fostered. I don't see, again, as a view pointed out, these aren't two sides where if one gives the other has to take, I actually see these things really as functioning together. Okay. So the example I want to give derives from the studies of John List. So for many years, he studied a couple of genes in the fly. And he had discovered this phenomenon called promoter proximal pausing, where the polymerase would transcribe a short RNA and then just sort of sit in the promoter proximal region waiting for a signal, in this case heat shock, to come and release that pause signal and let the polymerase go rapidly into the gene. And so he studied this sort of in isolation for quite a long time before we had the ability to look at things genomically. And so even though a few other genes had been demonstrated to be regulated in a similar fashion, before we could do unbiased data collection, we had no idea how broad this fundamental biological process really was, right? And so we thought this was a rare phenomenon. We thought this was something that happened in a handful of genes.  And this was like the state of the art. I did some chip, and I had some primer pairs, and I said, look, there's a peak of polymerase at the promoter of this gene. That's where we were. And fast forward to being able to do chip-chip and chip-seq. So Ginger Muse in my lab did these experiments in Drosophila as two cells and looked across the entire genome. For are there other genes in the genome that are regulated using the same strategy? So fundamental biological questions identified a strategy, but we needed genomics. We needed unbiased data collection to ask how broad is this strategy, how broadly used is it in cells? And so just as an example of this here, I'm just showing some chip-chip. At all 16,000 Drosophila genes, there's a heat map where I think you can see that the intensity of signal for every gene that has polymerase at the promoter, basically, the intensity of the signal is really enriched right around the promoter. So that pausing isn't something that happens at five genes, but it's something that's really a regulatory strategy that now we have to integrate into the way that we think about how genes are regulated. And so I really think that that's where genomics enable basic biology to make a leap. But then basic biology had a question. It said, well, here's Paul too, and yeah, it's sitting there at the promoter, but is it engaged in transcription? Is this actually the same thing that John Liss had been talking about for three decades? And so both John, both Leighton-Corin, John's lab and Serginichaev in my lab wanted to develop techniques to look at the nascent RNA generated by either specifically by pause, Paul too, or by elongation-competent transcription complexes, again, across the genome. And so as many of you know, Leighton developed this global run-on-seq technology where you isolate nuclei and then you feed them a labeled nucleotide and you then purify RNA containing that labeled nucleotide so you can identify very specifically with very beautiful signal-to-noise where transcription complexes were sitting in the genome that are competent to elongate. So this just gives such nicer estimation or evaluation of the actual transcription rate in a cell at a specific time than you're going to get from RNA-seq or from Paul too, chip-seq or from anything of the like. It really tells you something about where engaged elongation complexes are. So the strategy that we took, just focusing on transcription start sites, doesn't give you information about the level of transcription going through the entire gene. Oh, so anyway, the basic biology question that this answered was that we could find nascent RNAs almost everywhere we could find Paul too. All right, so that was the answer to the basic biology. But what John and I realized or what a number of people have realized is that these techniques have a life beyond pausing, right? So they have a life way beyond what our geeky little initial question got us into. And now I think these techniques should be more broadly utilized to address genomic questions. And so just to sort of say something about our technique, which is a start-seq, and John now is doing a five-prime cap a version of gross-seq. They really focus on the five-prime end of these nascent transcripts. And so this gives you single nucleotide resolution of exactly where transcription is starting, right? And so we pulled these either from the chromatin fraction or out of the nucleus. We get them when they're short and still associated with the polymerase by and large, and we purify them by use of the fact that they have a cap. So we can decap, we can identify that first nucleotide. And the nice thing about doing something like the start-seq is that you don't require the polymerase to put another nucleotide in there. And so you can get these RNAs even if these polymerases are not stably paused, even if they're just actively transcribing through, if they're arrested in transcription or if they're in the process of termination. So you can get these short RNAs from wherever transcription is initiating. And again, the thing is that all these reads get focused at the five prime end so that you don't need a billion reads to cover your sequence space. Because you're really just looking at exactly where transcription is initiating. And so I'll give you some examples of that. Okay, so here's just an example of what data looks like. So you have the start RNA-seq, the same thing can be said for the five-prime grow cap. And so you can get sent strand reads that line up to transcription start sites. And you can get antisense reads that tell you something about divergent transcription. So this is a surprise. Again, something that people would have never guessed at. But genomics told us it was there. So in mammals, the polymerase goes in both directions at many coding genes. And in the antisense, upstream antisense direction makes a non-coding transcript. And so again, we know this because of these genomic assays, because of unbiased data collection. And then, but then this raises questions that basic biology can delve into further. All right, and so we can use these techniques to specifically say, well, I think the start site of this is slightly different from annotation in the cell type. We can use this to annotate exactly where the antisense transcription is originating. And again, we can also use these to define the end of that transcription. So now here's just an example of what the data can be used for is you can start to get a handle on promoter structure. So if you align, these are in mouse macrophages. You look, align all the data by the start RNA sense strand. And you sort of rank over to the genes by how far away the antisense transcription start site is from the sense. You can see, as Frank Pugh showed for yeast, that you actually have two distinct Paul II complexes going in opposite directions. And you have, and you can see TBP is there. This is this tautobinding protein. And you can see that you have this big nucleosome deprived region in between these two sites. And so now we have an understanding of promoter structure that we didn't have before we could precisely identify where the antisense, where this divergent transcription was coming from. And again, this is, you know, this is new information from a technique that is being repurposed, I would say, to do an unmore unbiased search of the genome. Okay, so this is not just something that can be used to look at promoters or divergent non-coding transcription around promoters, but it can also give us insight into some of these unstable non-coding RNAs that are generated in enhancers. And so what I want to point out here is that enhancers are described often by the presence of DNAs, hypersensitivity, and a number of histone modifications. And while this is really beautiful and it's given us lots of sites to look at, one thing I should note is that the regions defined are awfully broad. And so here I'm just showing an example from this cell stem cell paper, where they were identifying the enhancer regions in embryonic stem cells. And then later, after those stem cells were differentiated into epiblast or epiSCs. Okay, so the things that are labeled here in blue are the things that they define as enhancers in mouse embryonic stem cells. And you notice that a lot of these key enhancers right around this KDM5B gene are actually lost in the epiSCs. And so you lose the monomethyl, DNAs, H3K27, settle, etc. And then they would argue that there are new enhancers that are coming up. And so again, here's a situation where the perturbation, or in this case the time course of development, is informative because you see these things changing. Okay, so is there a way, then, of better defining enhancers and asking whether or not everything in this region is identical? Or are there hot spots? Are there hubs or specific loci within this enhancer that are potentially more relevant to their function? And so one thing, when we can think about this is in this big region, where's the action? And so I just wanna sort of show our work that we've done in collaboration with Joanna Wiseca characterizing the same transition from ESCs to epiSCs. And this is super preliminary data. We've done one lane on a my seek of our start seek data. And here in the mouse embryonic stem cells, this is the forward strand. And then this is the divergent transcription on the reverse strand. And you can see that in fact in these loci that are described as enhancers, you can see both forward and reverse transcription in the embryonic stem cells that's totally gone in the epiSCs. So again, in a lane of my seek, you can sort of identify where transcription is taking place within these regions. And one thing I just wanted to note is that the alignment of these reads is really beautifully sort of lined up with the DNAs, which sort of, I think tells us that there's a focal region within these enhancers that we need to be thinking about what the transcription and the DNAs are pinpointing the exact same region within this sort of multi-KB locus. Okay, so the only, the thing I wanna point out here is that, again, in the lane on a my seek, we can easily monitor changes in the enhancer activity in these altered contexts. Okay, and then again, because it's a high resolution definition of five prime ends, we've looked around these five prime ends and tried to understand which transcription factors are present and absent in the ESCs versus the EpiSCs to try to get a handle on this. It's easier to do if you're looking in 200 base pairs upstream of a promoter than in a six KB region. Okay, so I just wanna say that what we've done is sort of what I've tried to get at here is that you can take techniques that are developed to get at a very specific biological problem and use these techniques. And I focused on grow seek and start seek, but I also am in love with this metabolic labeling for SU seek that Aviv has done a lot of, because it gives you this broad sort of agnostic data collection possibility. And yet you can use it for everything from annotating functional elements to answering very specific biological questions. So I would argue that NHGRI should continue supporting technology development, even if it seems like it might be set out to answer a specific question. Almost everything that is done in ENCODE was started that way. And then it can be repurposed to then ask the same kinds of questions. How broad are they in a bigger context? And I would just like to say that I think that investing in new technologies is important. But I also wonder if some of the large consortia projects could be structured in a way so that they could flexibly integrate new kinds of techniques, new sorts of data analysis, you know, add on a new collaboration to a consortia to integrate some of these new data sets. And I think that these are things that are already in the works, but I think in the next phase doing even more of that would be great. Okay, so these are the questions that I was asked. I just want to say that I think we need better assays of direct consequences and better readouts of phenotype and function of some of these elements. And I think that there are ways of doing this in an efficient manner that can be then easily scalable and multiplexed across many perturbations, many time points, many conditions, which I think ultimately is a goal that I hear sort of reiterated here is to understand the functional genome. You sometimes have to push it a little bit and ask how it responds. But we can't do that with 800 different assays. And so there are probably some low hanging fruit and I would just argue that RNA should be among them. We're running behind schedule, so we're going to leave the questions to the discussion session and move on straight to Anjana Rao, who will talk about analyzing cytosine modifications in genomic DNA.


Kremlin predicts long hybrid war. Dmitry Peskov, press secretary of the president of the Russian Federation, believes that the hybrid war of hostile countries against the Russian Federation will last for a while, so Russians should unite around Vladimir Putin. Peskov evaded the question of when Russia's war against Ukraine will end, but he said that the hybrid war of unfriendly countries against the Russian Federation will last for a long time. And if you mean the war in the broad context, confrontation with hostile states, unfriendly countries, this hybrid war that has been unleashed against our country, then it will last for a while. And here we need fortitude, loyalty to ourselves, determination and unity around the president, Peskov said. Peskov is sure that in the Russian Federation, there is an unprecedented consolidation around the president, the supreme commander-in-chief around the policies he is pursuing. In addition, he declared that the confidence that all the goals of the special military operation will and must be achieved absolutely predominates among Russians. Peskov has said that Russia's struggle with the West is a war in the broad sense and warned that it is bound to last. If you mean let's say war in a broad context, a confrontation with hostile states, with unfriendly countries, a hybrid war that they have unleashed against our country, it is bound to last. We need to stay firm, confident, self-concentrated and united around the president, he told.


I'm John Bridle, and I'm a biologist in the School of Biological Sciences at the University of Bristol. My research is mostly about understanding how organisms evolve in response to environmental change and how quickly they can do that. Climate change is having big effects on biodiversity. It's causing losses of biodiversity at precisely the time when we need the biodiversity to allow us to support a growing population. And the big problem is climate change is affecting the people that depend most directly on biodiversity because they're the poor of this planet. And those people are not being massively affected by climate change and we're buffered from it in the more sort of wealthy parts of the world. So from my point of view I think the big interesting thing is how there's now been a connection between development and biodiversity. Protecting biodiversity is essential for development, essential for social justice and poverty alleviation and that connection wasn't really made before. People thought that protecting biodiversity was like an alternative to development. But it's not the environment or development. The environment is the economy. It's what makes development possible. I think that's the big message that biodiversity is not like protecting some pandas so we can go and look at them. It's about protecting the systems that actually we depend on. I mean it's not as if life's going to end because of climate change but human life is going to become a lot harder. A lot of species are going to go with us and the poor of this planet and our grandchildren. So the unborn generations who don't have any say in how we govern the planet now are definitely going to have a much more impoverished life because of the actions of the last 50 hundred years. I think from the climate change point of view it's like how could you think that you were going to burn billions of years worth or accumulated carbon from a period when the earth was incredibly productive during the carbon if it was high temperatures, lots of rain. How could you think you'd burn or release that into the atmosphere over such a short period and it wouldn't affect the climate? I mean I don't think the onus from us should be to prove that climate change is happening. It's like releasing all that fossilised carbon into the atmosphere and something that's already at such a low abundance in the atmosphere increasing its doubling or increasing its abundance but it's already very rare. It seems to be a very dangerous thing to do. So I don't see how people could think that we wouldn't affect the climate in some way and we've got all the evidence that we are affecting the climate. The issue that I'm interested in is how those changes that are projected are going to affect the systems we depend on for our food and for our wellbeing and that's biological systems. I think it's important that we're mostly dealing initially with climate scientists in terms of understanding what the likely rates of change are going to be, the average changes across years in temperature and how that's being forced by greenhouse emissions. So understanding the mechanism by which the climate is changing is very important. But even if we have a great deal of certainty of exactly how much the temperatures can like to change in the next 50 years the upper and lower bounds of that, we still know remarkably little about how those changes are going to affect populations of organisms and communities and ecosystems. And I think although the idea of tsunamis and storms and floods looms very large in the public imagination, most people's experience of climate change is going to be by the way it affects food security, the way it affects ecosystems and organisms. And we know that organisms face environmental changes all the time. We know that they're dealing with the environment changing on a daily basis, on a weekly basis. The issue is how much climate change is going to take that beyond the bounds that they're used to experiencing. I mean, especially in season environments, organisms deal with wintertime and summertime and they have all kinds of interesting adaptations to cope with that. But what's happening with climate change is the extremes are increasing. We're getting more variable climates and less predictable climates. But I think what we really miss in terms of predicting how organisms will respond to climate change is how that's going to affect the types of outputs we rely on for our human economies, like farming, for food security, predicting when diseases are going to emerge, the emergence of diseases, the spread of diseases through invasions. We really need to understand the biology. And the difficulty there is that organisms experience the environment in a very local way. They experience it across metres, not hundreds of metres, and across hours and minutes. And they can change their behaviour to change how they experience the environment. They can choose where they lay their egg, so they can choose when they go into diopause. So they have a certain amount of plasticity to cope with the environmental change they're facing. But the issue is that the environment is changing in a much less predictable way from their point of view. These cues they were using are becoming no longer reliable cues that tell them when they should emerge to synchronise with other organisms or when they're going to be free from frost. So the persistence of organisms in most parts of the world depends on them being able to cope with environmental variation. But climate change is changing the way that variation is being experienced. And we know very little about how organisms experience that just as individuals, but on top of that you have the idea of genetic variation. The organisms actually differ in how they deal with the environment and that gives you the capacity for them to actually evolve in response to change. That's the main issue that my research really addresses is trying to understand what limits populations' responses to environmental variation. So I think one of the issues that we think about species as single units and this is why perhaps we've lost or missed this evolutionary aspect of responses to climate change. We know that organisms are distributed in space have limits to where they're found. That's determined by their niche, what they can cope with. But we don't know how much they vary across their range as individual populations. They've been responding historically to changes. What happens in Canada is different to what happens in Latin America. It could have the same species with a very broad distribution. But those populations can be very different in the niches they inhabit. So that in itself is testament to the fact that organisms have responded to environmental change across their distribution. They often have clines, they often have changes in characters which tell us that they can respond to some change. But what really fascinates me as a scientist is why at the edge of their distribution do they stop adapting. We know that over longer timescales organisms have been able to go into, I mean mammals return to the ocean several times and we colonize the oceans, became completely marine. So clearly these niche barriers can be overcome given enough time. But probably that happens only very rarely. So I'm really interested in what are the factors that limit how fast organisms can respond to change. They have this plastic variability so they have an ability to kind of use the environment in different ways. They respond to cues and they vary in the way they respond to cues. And that kind of plasticity gives you a resilience just without necessarily evolving. But also those cues can evolve. How you use the environment, how you respond to the environment can evolve as well. And we're really interested in understanding if the environment changes too fast, whether populations are not able to keep up with to track that changing environment sufficiently fast before their population declines. So this is a concept that's called evolutionary rescue. It's an idea that when a population is in an environment and the environment changes suddenly, under what conditions can it evolve, change the gene frequencies in its population to allow it to match that new optimum and thereby continue to grow and continue to be sustained. And fundamental to that idea is the idea that when the population experiences a new environment its growth rate declines because it's far from the optimum so many organisms are unable to grow as quickly or reproduce as quickly as they were before. So this feedback between your distance from the optimum of the population and your growth rate is really what determines the limit to evolution. It's the way that your growth rate declines as the environment changes and how much genetic change is needed to allow you to get to that new optimum. Because that genetic change, the time it takes for that to happen, that's all the time when the population is suffering reduced size. And that reduced size feeds back and reduces the genetic variation. So it actually makes it even harder for it to evolve. So it's a kind of like a, if you don't evolve quickly while the population size is still large and the population declines then you're losing variation to allow you to continue to adapt. So it's kind of like a bit of a sort of positive feedback. The rescue has to happen fairly early on we think. So we have very good theoretical models for the situations under which evolution can occur, the sort of maximum sustainable rate of adaptation. We look at populations and how they're distributed now and tell us all in the past what have they been able to respond to, how much they vary across their range and their niche which tells us the kind of range that they can clearly evolve into these new niches. But we don't know a lot of these key parameters like the growth rate, the amount of how strong selection is in the field, how it varies with the varying environment. We don't have good estimates in the real world of those things because actually they're quite hard to measure. But we don't even know very much about how much genetic variation there is within populations or between populations which is the fundamental engine that allows organisms to evolve. Without genetic variation, variation in reproductive success, there's no evolution. Evolution stops. So we need to understand more about how genetic variation is distributed across populations and within populations or across families essentially. And we also need to know how changing in one direction so evolving one type of morphology or one type of response may limit your ability to respond in another way. And this comes into this idea of trade-offs which is the idea that you can't be everything at once. And fundamentally that's why organisms are diverse, why they've gone into different niches and proliferated into the biodiversity that we see is because one species can't do everything. So they evolve a larger body size. It means they have a longer gestation time and they can't reproduce as quickly. So you have these kind of trade-offs that are involved throughout history. By understanding those trade-offs we can maybe start to understand more about what limits organisms are responding to environmental change. And we've actually got an incredible new ways of doing that now with next generation sequencing, a sort of genomics revolution has allowed us to study organisms in the wild and actually look at how the genetic basis of the variation that affects their fitness in natural populations and there's been some fantastic studies that have been done on that. Really from a biological point of view it's like we've just discovered the telescope like in the 16th century, you know. So we are now able to do things in a few weeks that previously would have taken several years. And so the ability to actually address these really quite difficult questions is now with us in terms of genomics but we need more and more studies in the field to actually tell us how what's really limiting organisms range. The degree to which their responses to the environment are affected by extremes in particular is a key issue. Like we know they respond in space but the experience environment in a very local, very temporally changing way that changes over time and what climate change is doing is it's increasing the probability of extreme events. So not only is the mean changing and the mean changing actually doesn't seem that much a few degrees but the probability of extreme 15 degree differences is becoming much more frequent. And what interests me is how do organisms evolve to things that they've never experienced before unless it once in the last sort of 5,000 years, that kind of temperature of that kind of event. How can they possibly have evolved with the ability to be resilient to that change? Yes, yes. I should say first of all that I think the focus on returning back to what I was saying before about climate scientists I think the focus on demonstrating there's been a temperature change and the surface temperature change or oceanic temperature change is all fine. We can look at biological organisms and see them responding to climate change. What we see actually when we look across thousands of species is their ranges of all shifting polewoods. So in the southern hemisphere they're shifting towards Antarctica and in the northern hemisphere they're shifting towards the Arctic. And they're becoming extinct to their southern margins in the northern hemisphere and shifting northwards. And that's a clear ecological response to climate change. Organisms are moving into habitats that are now becoming sysfal for them at the northern edge of their range in Europe and they're declining on moving up onto mountain tops and parts of their range. And that's something that we work on in butterflies because we know a lot about butterfly's ecology and about the habitats that they use, the interactions they have with other species and also about their historical distribution. So a lot of work has been done on butterflies in this area. So we know there are definitely across, there's a signature, a very strong signature across the globe of organisms responding to climate change by shifting. So there's definitely something going on. It's unequivocal. I don't have a meteor biologist who doesn't believe in changing. The question is how fast and how much is that average change interacting with changes on a very local scale. And that's something that takes a lot of work to understand because organisms are complex, they have individual behaviour that varies. Our butterflies, for example, that we work on are UK species of butterfly, the brown argus. And that's a butterfly that can change where it lays its eggs. And actually butterflies in general, if they choose to lay their eggs five centimetres off the ground, the eggs are going to experience a much lower temperature if they lay them on the ground. So five or six degrees difference on average. And that's work that's been done in the States on a checker spot butterfly. And that shows like an incredible ability of organisms to choose by the maternal behaviour to affect the microclimate that they're offspring are going to grow in. And knowing that on average across this latitude of the US, there's going to be a change of two degrees centigrade, doesn't tell you what the individual organisms are going to do on the ground. So there are definitely strong signatures of ecological responses. So organisms are shifting their ranges. For many of those organisms, we don't know if they're actually changing their habitat requirements or they're actually changing their niches, which is what evolution would do. It would change what their tolerances are. We can actually say that a lot of them are doing pretty much what they're moving to areas that would have been habitable before. So they're moving into areas which are just the same areas they were previously living in, do you see what I mean? So they haven't changed their niche. They're just passively, not passively, but they're tracking the change. But the general pattern that we see is actually that most generalist species are able to do that. So species that have large population sizes that don't have specific requirements for other species, don't have particular interactions with other species that they exploit. So in butterflies, some species are pretty generalist about the host plants that they use for their larvae to grow on. And others are a bit more specialised. They need certain types of habitat where these particular plants grow. And those organisms with very particular habitat types that they require tend to be not expanding their ranges or not shifting their ranges. And that seems to be because they're very limited by habitat availability. So you have this kind of double whammy of like the anthropogenic change of the environment causing things to have to move. But habitat loss on a local scale restricting their ability to shift their ranges. So most specialist species of butterfly actually declining, about 75% of specialist species, are declining. They're becoming increasingly trapped in sort of fragmented locally cool places rather than expanding their ranges into areas that are now suitable for them further north. And the butterfly species that we work on, the Brown Argus, is in a very interesting example because it seems to have shifted its range northward despite having particular habitat requirements. So in most of its range in the south that uses a host plant called rockrose, which is a Cystaceae family of plants. It's quite different. It's quite a particular plant that grows on short downland. But it's a specialist species in a way in that it uses mostly this host plant. And yet it has been able to shift its range northwards in Britain. It seems to have been able to do that by actually evolving to specialise on a different host in the new part of the range and so use that on geronaceae species like geranium, which are found in very different types of habitat, have a very different type of microclimate, we think, and a very different type of growth form, a very different family of plant. And yet it seems to have had an evolutionary response very quickly that's allowed it to colonise this new area. So that's one example. I mean there are lots of examples of changes in organisms but it's often quite difficult to distinguish those changes that you see in the field from just plastic changes and the idea they've just evolved to use the environment slightly differently, they haven't actually evolved. So there are lots of examples in mammals where they've shifted their range. But knowing the degree to which evolution is responsible for allowing that change to happen or conversely the degree to which evolution means they don't have to shift their ranges as much. Maybe they can just move half as far because they can evolve to cope with a warmer temperature. So when species are lagging behind and not tracking the environment exactly, is that because they've evolved locally? Often we just don't know. So there's a big knowledge gap in understanding the way that evolution allows resilience in terms of allowing populations to respond to climate change and rescuing them from just contracting and becoming trapped in local places. So it's a huge area that we don't really... Now that we have the genomic tools it's going to become a lot easier to demonstrate that evolution has actually happened. But just looking in the field and saying they're now here and they were there, things like mammals and birds, it's hard to bring them into the laboratory and rear them and show that they've genetically changed in these traits. And often the changes are things like changes in the way they react to the environment. So they're not... They're like changes in the genes that underlie the plasticity, which is much harder to detect when you put them in the lab. You have to test them under a whole range of conditions rather than just one particular condition and show that they're different. But pretty much whenever we bring organisms into the lab and rear them, we find that they do have all-genetic differences in most traits and certainly a lot of capacity to evolve in many traits. The thing that we don't really understand is how those traits correlate with each other and how that might limit their ability to adapt. The issue about whether or not the organism is going to be able to track the environment sufficiently fast I think in many cases they won't be able to. And we know for example that some tree species are still increasing their range in response to glacial changes, post-glacial expansions. Some tree species are moving quite slowly. Others are already where you'd expect them to be given the existing environment. But it's hard often to know exactly what's limiting a species in a particular place. It could be like every ten years there's a frost and that stops the sapling, kills all the saplings or often it's these extreme events that limit species ranges. But I think certainly the rate of, for many organisms, the rate of environmental change is going to be too fast. Again, we're slightly hampered in understanding that fully because we don't know how much it's going to change on a local scale. Organisms may well persist in places just because they're able to use moist microclimates or shaded. They might move to north-facing slopes or the south-facing slopes. So this comes back to the side of needing to understand this very local way that the environment is changing. Certainly, as I say in butterflies, 75% of the species we define as specialists, they have particular species they depend on, their ranges haven't tracked, they haven't responded to climate change. And that's basically what we're seeing across most species that have particular species they need to interact with because those species have to expand as well. And often those species, like if their plants might be limited by a soil type or by some other feature of the environment, not by temperature. And that will mean that unless they shift their niches to use different plants, they won't be able to actually persist in that place. I mean, there was a famous study done in 2005 by Chris Thomas, which caused a lot of discussion, where he modelled a species as a sort of single unit. Like I was talking about before, the problem is we assume that species have got the same niche everywhere. But let's assume that the species has basically got the same niche everywhere, which is basically quite conservative if you're saying actually giving it a lot of latitude to evolve because you're saying, well, every population has all the genes it needs to move, has all the tolerance necessary to move to anywhere in 50 years' time where there's going to be a habitat that can currently inhabit. If that habitat exists anywhere on the globe, then it can be there. So you assume there's no limitation in how fast they can move or their dispersal, there's no fragmentation, there's no oceans in the way. He basically suggested that 10% of species of which we had good estimates would go extinct even if they could get anywhere they wanted to be. Simply because those habitats would no longer exist. So without evolutionary change, 10% would be condemned to extinction. If you allow there to be some limitation in the rates of movement, that estimate goes up to about 35% of species within this century. There's a lot of assumptions in those models and they've been questioned a lot recently. They pertain to particular types of organisms and other people have challenged that paper based on looking at vegetation analyses and other types of organisms that may not have that particular limit. But certainly the best available information we had in 2004 suggested that we were looking at between 25% and 35% extinction if you allow some dispersal limitation. So if you allow that they can't get north of Scotland, they can't get up into further places in Scandinavia where there might be suitable habitats. But even if you assume there's no limits to dispersal, you still have all those 10% of species having nowhere where they can still live because of climate change. I worked a lot previously on understanding what happened post-glacially, so understanding what the consequences of glaciation were for species distributions. The issue with doing those analyses is firstly it's hard to see the things that didn't make it. So you've got a big ascertainment bias and you don't always underestimate the amount of extinction that went on in the past. You're also looking at species as single units, again, you're not really seeing. The idea of focusing on species extinction is a natural thing to do but it really understates what's really happening. In terms of understanding how ecosystems work, what really matters is the way that populations decline and communities change in their composition because species might still be found in the centre of its range but if it's contracting in all these peripheral areas, it's basically essentially locally extinct. That means it's no longer part of the ecological network. Those are much more serious in terms of ecological outputs than worrying about whether one species is still present somewhere on the planet or not. By the time a species is just found in one population, you've lost all that intra-specific genetic variation that's probably important for adapting or certainly important for adapting to change. So you're losing your capital in the sense of your ability to respond to change. But I think using species' extinctions is a really poor currency for understanding the effects of climate change and biodiversity, all the effects of habitat loss and biodiversity. But we can look at what happened in the past where mass extinctions happened because of rapid climate change or because of habitat loss. And I think what we generally see, I mean I'm no expert in this, but I think we generally see as similar types of organisms go extinct as those organisms which we now see on red lists that are very critically endangered. There's a lot of fantastic work being done by people like Georgina Mace looking at correlates of extinction risk in existing mammals and other people comparing it to past extinctions and other mammals. And you can see the same traits come up. If you've got a long gestation time, if you've got a large body size, if you're specialised in a particular type of diet, then you tend to go extinct much more quickly. Definitely carnivores. Organisms that depend on top of food webs, if you like, or at higher trophic levels tend to be more endangered. I mean there are some exceptions to the red list in terms of organisms which we should be really congratulating ourselves we've managed to make endangered, like cod. I mean cod have a huge rate of increase. They're one of the real outlaws. They don't have the life history of an endangered organism, but they are endangered because of the massive huge amount of pressure that humans have basically put on them. So it's often quite hard to actually, like in looking at what's happened in the past, it's actually quite hard to look at correlates of extinction now because we've actually already lost a lot of the species that were already vulnerable. So there's a big filter. So we're actually looking at an ascertainment bias where we just see the species now that probably are fairly resilient. In the sense that we're not perceiving the organisms which, so there were previous organisms that went extinct thousands of years ago or hundreds of years ago which we aren't included in our studies now. We can't study them, we can't include them. And that's also presumably true when we look at what happened in the past as well. The fossil record only records widely distributed species going extinct. Species that are highly localised and show particular interactions. I mean they are much harder to find evidence for and they've probably already gone. I guess it's like, in a way that ascertainment bias means that the rates of biodiversity lost are going to go down eventually because you'll lose the easy things that go first. It's like being burgled several times. The first time you lose your computers and your iPhone or the next time it's other stuff and by the time they've been there you've had three rounds of extinction you're only seeing the things that nobody wants, the things that are very hard to get rid of or hard to move. I mean the UN Millennium Assessment and the Millennium Goals is to reduce the rate of biodiversity loss but eventually it will be reduced. And ecosystems that have been highly degraded you find extinction rates go down because you lose the vulnerable species very quickly. People often say to me, well extinction there's what five mammals gone extinct or something like that. But really in terms of the, it's about what we're trying to conserve and what we're interested in and we're interested in the effects basically we're interested in climate sensitivity which is the degree to which a certain change in the environment is going to affect the way an ecosystem functions what it outputs in terms of things like water and rainfall and soil decomposition or pollination these kind of things that people try and put an economic value on and that involves understanding how communities are going to change. Now communities of organisms interacting it matters if that species is present at that point in space. Now if the population has gone extinct in that particular part of its range then that species is no longer existing in that community no longer performing that role. So species this is why it's really important to look at species that are actually quite common and actually quite widely distributed and then say well actually they're declining at a very fast rate and they're becoming much less common in particular places the chance of finding it if you go to this bit of habitat is much less common much less likely to find it now. I think one of the issues has been that biologists have kind of painted themselves in a corner a little bit because they argued for protecting very rare species like you know and then people said well these species look you know there's no way they're going to be protected look at tigers or pandas look at the amount of money that has to go into protecting those and you have to argue for their protection for a very ethical point of view and say well they've got a right to exist look at these beautiful animals or plants or whatever but by the time a species is really endangered it's only found in a couple of places that it can't really be participating in the ecosystems as a whole their value in terms of what they contribute to life and how the life depends on them because in most parts of their range their former range they're not there so they're not part of the communities of interacting organisms which is what is basically biodiversity it's this kind of you know you go into a rainforest and basically it's full of these organisms interacting and that's lost with population extinction is what matters for that situation and also if a population goes from being distributed across a lot of habitats and each population is adapted locally to that environment it's got a lot of genetic variation it's got a lot of genes that are present in some parts of the range that aren't present elsewhere the population shrinks down to a single remnant couple of populations you've lost to those unique adaptations across the range which are the testament of the history of evolutionary change over the last hundreds or thousands of years so it's that currency it's that genetic variation within the species that's going to allow us to allow those populations to persist where they are to actually still continue to engage in ecosystems without genetic variation there's no evolution so there's no capacity to evolve and what we're doing at the moment is we're reducing biodiversity at just the point where we need it to adapt we're forcing it with massive you know overconsumption and massive increases in population in the globe we're also huge rates of habitat loss as well as climate change so we're destroying the very capital that's actually going to allow us to adapt and actually have these ecosystems continuing to operate in the future so from the point of view of climate sensitivity I mean climate scientists are generating these fantastic estimates of exactly how the variation how much the environment's going to change but determining to what extent that's going to be catastrophic and over what timescale depends on knowing how allisms will react and that's really a very different question I mean how close are we to tipping points do the tipping points even exist and how do they vary on a local or a global scale how do they vary across ecosystems or in the marine environment versus the terrestrial environment these are all questions that only biologists can really address and a key part of that which we've been missing is the degree to which you can't assume a species has the same niche across its whole range it actually has the capacity to adapt and use the planet differently or use the environment differently and have different tolerances this idea of problematic interactions how species interactions are affected by climate change that's a really key issue that is hard because the world is complicated one of the things we really value about biodiversity is these interactions between species it's not just this species that looks like this and lives here it's actually the interactions it has with all the other things it interacts with in its lifetime and those things particularly in seasoned environments they depend on allisms synchronising their emergencies sometimes times or their behaviours with each other and often there's conflicts there because often that's natural and often like a plant is trying to prevent a butterfly laying its eggs on it and its larvae growing on its leaves so there's like a bit of an arms race between the two where one's trying to emerge particularly in the tropics you see the plants are trying to have their big growth of their leaves at a time when the insects aren't around and the insects are trying to match so they're trying to be around so they can produce a lot of young just at that time but it's rapid increase in biomass in the leaves and that it always uses kind of these environmental cues which is incredibly fantastic amazing things that organisms do to match so they can survive winters, they know when to go and they use environmental cues to decide when to go into diopause, when to hibernate and then when to emerge and the difficulty is with climate change those cues are no longer as coordinated as they were, they're no longer as useful so for example the temperature and the photo period so the day length is no longer has the same correlation that it used to have it has a different correlation and this means organisms may start to make mistakes and more and so not only for their own survival they have to actually come out at the right time to actually exploit their resources they have to emerge, they pollinators have to emerge at the same time as the flowers otherwise the flowers don't get pollinated and the insects don't get fed and that's a mutualistic interaction where both organisms actually have to share the need to be pollinated and to be fed but if you have a parasitic interaction or a herbivory type interaction where once a bird timing when they lay their eggs for their chicks to emerge for a time when they're a larvae around and caterpillars around that they can eat or insects around that they can eat so if these different organisms in different trophic levels use different cues which they do and previously that actually was fairly reliable then that becomes a real problem because you get them emerging at different times you're getting this thing called trophic mismatch which people have been working on very nice systems in great tits looking at a moth species they're trying to track the bud burst of the trees so they can grow their larvae and the great tits are timing with their clutches when they lay their eggs so that their chicks have got and they can feed their chicks for these larvae and those things are becoming desynchronised because they're evolving at different rates or reacting in different ways to the environment actually there are quite nice examples of humans using cues like when other animals do things to actually decide when to do things like planting rice in some traditional Chinese communities they use the arrival of birds beginning when birds start to nest it's a cue that's when we should start planting our rice because the birds have got a good sense of when it's going to be raining when it's going to be productive when the storms are going to finish so there's all these organisms using cues from each other and using cues to allow them to persist in places where the environment is sometimes harsh and those cues are all basically being they're changing and we don't know for how much organisms are going to be able to evolve in their way that they use the environment to actually cope with those changes and they're increasingly unpredictable nature of the environment these seasonal changes are periodic you can predict that it's going to be and maybe the first time having a first frost is a good indicator of when to flower but in the future it might not be like that and that's a real issue I think that we don't really understand well I was always fascinated by evolution when I was a child I've always been really interested in trade-offs actually and very interested in actually how behaviours evolve as well so behavioural ecology when I was a university kind of this idea that you're trying to optimise your decisions that you make and if you make this decision it compromises your ability to make another decision don't mean to think more generally about why this general question about I mean why do species have specialised niches why are species only found in one place and not in another place you know why in the past did you not just have one species that just does everything why do species evolve and acquire certain phenotypes and ways of doing things as they stop them doing other things we know evolution can achieve a lot but why are species limited in there in their distributions but I think the reason I got into what I'm doing now is really a lot of it was driven by by conservation and by being really quite shocked by the scale of biodiversity loss which I think is interesting because I think that's actually been downplayed in the media because there's been so much focus on addressing climate change denial and this idea of is climate change happening or not and if it is happening which obviously it is but if it is happening on a large enough scale to actually cause catastrophic change or not that's been a real focus of scientific research and rightly so but we know that habitats have been lost we know that biodiversity is declining in an alarming way and I think that kind of idea of the biological effects of human exploitation and human population growth, human overconsumption has been slightly lost in the story partly because people focus on species extinctions and not on the declines in abundance of species across their range and the interactions that are changing and partly because I think people don't value the nature as the thing that makes everything as possible the fact that the environment is the economy it's the thing that we all get everything from life is what we depend on and that life is being massively stressed we're losing biodiversity besides the time we need it the most and so I think I was really upset, anxious about that when I was a teenager and I studied biology because of that and I was also really fascinated by evolution and now it's really exciting that evolution is actually one of the key things that might or might not allow resilience to things like environmental change and it has done in the past and we need to understand how much it can temper those critical tipping points that we can predict or we can try to predict based on rates of climate change but really I mean I go into it because I find it absolutely fascinating really I'm a population geneticist so I try and understand how populations really how they respond to change how they're able to track a changing environment I was at a party actually and somebody asked me why I chose to study it was an astrophysicist and she said to me why are you choosing to study something that's so localised it's only found on one planet as far as we know and it's only existed for a very short period of time because I was thinking well I studied life it's an amazing thing to study because we're on this planet we might as well study life while we're here and she was like yeah it's a very localised phenomenon let's hope it doesn't stay it doesn't become more localised I mean I do do a lot of interacting with the public about these things and actually generally I think people are generally very concerned especially younger people, especially children something seems to happen to people when they get into their late teens early twenties someone seems to come back again in their thirties and especially when they become grandparents and they can sort of see the length of their grandchildren are going to be alive in 70 years time but there seems to be I think there's a period when the consumer culture gets people and they sort of trade this culture of disappointment driving their expectations so they seem to when you meet children who are like 7 or 8 up to about 13 they're really worried about the environment so I think there is already a great worry about it I think one of the problems that scientists have done is they present nightmares they basically make people afraid I mean people have often said Martin Luther King didn't say I have a nightmare he said I have a dream so it's aspirational and people really feel powerless so I think one thing scientists can do is say well look we know that this is a big challenge we know the planet is facing big consequences of what humans are doing but there is ways that we can improve things there's ways that we can reduce the impact I think scientists are fighting like a big well scientists, rationalists generally are fighting kind of like an industry that's basically trying to convince everyone that everything's fine we should just care on as we are and that's got a lot of money behind it and actually but I think the thing is it's not making us happy these things that we're doing it's consumption that we're doing I don't think they're happy happier than they were because of the consumption that they're doing someone said we're borrowing money we can't afford to buy things we don't need to impress people we don't care about but that machine is driving us to do that so I think what scientists can do especially biologists is to make people aware of how amazing how wonderful things are and communicate the reason we study these things because we're absolutely fascinated by them and I think actually why I spend a lot of time trying to communicate to people as a scientist is that we're driven by doubt we ask, I mean we're skeptics we question everything and I think we get we have to get across to the public the idea that scientists ask questions they don't come up with facts and dry sort of proof scientists are about asking questions and questioning everything and having doubt and every question it needs to be answered scientists are not ever certain of anything and I think the unfortunate thing is that lack of certainty which is what allows science to continue is sort of pounced on by people saying well this means they don't even know there's no consensus we know that to get 97% or a very large number of scientists agreeing on something is an incredibly rare thing to happen I think the real tragedy is that people are missing out on so much by not having this kind of approach to things actually thinking that science is about just dotting eyes and crossing teeth and proving things with a big stamp rather than actually sort of engaging with the world and trying to see beauty in it by understanding it more I think in this country particularly the media don't serve the public very well in terms of science I think they underestimate, I talk to people admittedly people who come to science fairs and things like that and come to the public engagement events we do here I talk to them about science a lot and I'm always incredibly impressed by how much they know the difficulty of course is they're the people that come to us if you go out and pick people around in the street it might not be the same story and I think with biodiversity it's a particular if you ask people in the street what biodiversity is most people don't know so I think we've really failed a scientist to get across you know that life is basically the thing that makes that everything is within it's the thing that makes everything possible like if I tell people that only one in ten of the cells in your body is actually human I mean the people are like shocked by that and that telling you that we are actually ecosystems ourselves we carry around tens of millions of organisms within us they're interacting in this ecosystem that we're just a platform for and people think well I'm me most of the cells in your body are not you at all so who are you and people get their mind swept by that maybe I'll show you this as well this is from a recent textbook on evolution which came out a few years ago it illustrates how much genetics has told us about the true of life and the history of life on this planet that we didn't know before and this is basically a tree based on neutral markers based on molecular markers which tells us about the evolutionary history of the planet and this point here is the what we think is the last universal common ancestor about five billion years ago and what this tells us first of all is that Darwin was absolutely right all life on this planet all existing life on this planet is related to a group of ancestors or a single ancestor five billion years ago and it also tells us there's a lot of biodiversity we know very little about this is biodiversity in bacteria these are all the eukaryotes all the forms of life that are multi-cellular most of them and these are the archaea and these are the bacteria these are three big kingdoms of life and what I usually do with the first years in one of their first lectures is point this up and ask them to put their hand up when they've seen where the animals are on this tree if you look on this tree very carefully here so this twig here of a tree of life this is basically all the animals that's not just all the mammals and birds that's also all the coral reefs and worms and all the mollusks and all the insects so you can see there's actually most biodiversity is not animal it's actually this sort of biodiversity we might find a handful of soil some of these things just a handful of soil, a world and a grain of sand so to speak actually we didn't know that there was this much diversity in soil in bacteria we'd try and grow from a load of soil we'd try and grow it on some agar and it wouldn't grow because it depends on quite complicated species interactions so these forms of life we can only find them when we actually sequence all the soil and find all the different lineages that exist in it and so we find a lot of evolutionary history we've actually nothing about it we focus so much in the last few thousand years on these animals here there's land plants here and you see they're flanked by algae what we call green algae two types of green algae though really divergent and red algae these are like kind of seaweeds but they're incredibly divergent fungi are here so these are all the fungi all the mushrooms they're quite closely related to animals but there's all this biodiversity that we know very little about and genetics is teaching us a huge amount about where the real evolutionary history is on the planet these small things that run the world especially in democratic systems is the public need to realise that they can actually do something and they can actually change how they spend their money or how they vote is actually going to have a huge effect convincing the government that these issues really matter and they matter for our children and for our grandchildren is really important so people, I think the most important thing is to make people not feel powerless I mean the environment has slipped off the agenda you know in politics certainly in UK politics maybe I shouldn't talk about this government in any detail you know DEFRA the people that are responsible for the sustainability of the ecosystems that we depend on they're basically the treasury they are the wealth of the planet the problem is we don't value that that wealth we value sort of financial wealth more imports and exports not the actual thing that makes that stuff possible