Welcome to our Xperience, the first ever of its kind. I'm standing here at the Chabot Space and Science Center in Oakland, California, and behind me, these telescopes, these beautiful tools, have been used to explore the universe much in the same way that the tools 10x is developing are being used to explore the universe of biology. After all, we're living in the century of biology, and whether that be tools for a single-cell analysis, for spatial analysis, or for in-situ analysis of complex biological samples, these tools are going to enable new discoveries. It's the discoveries that you make is what makes me the most excited about our journey together. With that, welcome to our Xperience, and I can't wait to see what you discover next. Innovation is an essential component to being a scientist. Your job description is an objective search for truth is like an absolute privilege. Working with other people as a team to achieve something, I think that you can derive a lot of passion from that. I think it's the best job in the world to say that you're going to work every day to make new discoveries. In genomics, it's technology and also computational methods that have to work together to make the magic happen. The innovations in technology have been so incredibly rapid, especially over the last 10 years. They've completely changed how we do science. You'll be able to study not an individual tree, but a forest. You'll be able to have the global view of a particular problem. That can change the way we think about cells and tissues and organs and population. The innovations change what's possible. The Human Cell Atlas wouldn't have been feasible to even think about 20 years ago. Having the ability to look at thousands of single cells and hundreds or thousands of genes is really revolutionizing immunology, and it's allowing us to ask questions and discover therapies faster than we would have ever thought. Scientists have come together, shared ideas, fed off each other. The crossing of disciplines lends a creative spark. It's been a fantastic open ride of people sharing data and papers and information, getting it out there just for the greater good. At the end, there is a potential to see what you're doing can be translated into something that can help people. I think that's something that's really exciting. When you think of innovation, you could immediately think of a brand-new technology that's a game-changer, that's paradigm-shifting. I also think within science, it's about advancement. Every scientist is an innovator in a way, because if you're advancing the knowledge, that's innovation. Thank you all for joining us at our first 10x Genomics Xperience Event. I'm thrilled to get a chance to introduce the agenda and the speakers because we have a lot of exciting new things to share with you. At 10x, our vision is to master biology to advance human health. Many of us here at 10x are both energized and frankly, a bit intimidated by this vision. We are energized because this is one of the key opportunities of this century. This opportunity is also intimidating because the true complexity of biology and the human body is mind-boggling. If we are honest with ourselves, we are just beginning to scratch the surface. This past year and the pandemic have shown us that despite all of our advances, we are still far from mastering biology, and the consequences of that lack of mastery have been alarming. It has also demonstrated how far we've come in even the past few years. Key understandings of COVID's effects on the body and the development of multiple therapeutics and vaccines have all been done at a pace that wouldn't have been possible even a few years ago. We have been excited to see both our Chromium and Visium products used by you to make advances in our collective battle against COVID. At 10x, we build products to reveal the underlying complexity of biology. Since 2015, when we first launched our GemCode platform, until today, we have released more than 25 major physical products and more than 100 major software releases to you, and we've been excited to see all of the amazing work that you've been doing with them. We are particularly proud of the breadth of advancements that have been made by customers using our products. From understanding the basic building blocks of the body with projects like the Human Cell Atlas, to providing core advancements in immunology and neuroscience, to impacting both near and long-term treatment options in cancer and infectious disease, the work you've delivered has been incredible. In only a few short years, there have been more than 2,000 publications using our products. In the coming years, it's hard to imagine an area of biology or human health that will not be revolutionized by single-cell or spatial genomics. Each year, we share with you the new products we aim to deliver over the following year, and we strive our hardest to follow through and bring all those new capabilities to you at high quality and on time. Since last AGBT, we've been excited to deliver many new products, including the Chromium Connect for full automation of our workflows, a substantially improved version 2 of our single-cell immune profiling assay and software, the world's first commercial single-cell multi-omic product that combines paired gene expression and chromatin accessibility data from thousands to tens of thousands of single cells, CellPlex, a fully supported solution for cell and nuclei multiplexing, targeted versions of both our Chromium and Visium assays, the ability to layer on protein measurements with our Visium assays using immunofluorescence, and multiple software advances, including the release of the 10x Genomics Cloud Analysis platform, as well as major improvements to our Cell Ranger, Space Ranger, and Loupe software. In order to gain a mastery of biology, there are three key elements we aim to deliver in all of our new products. First, resolution. Whether it's at the single-cell or tissue or molecular level, we aim to provide the capability to understand your biological system at its unit of fundamental complexity. Second, scale. Our technologies are built to run large numbers of cells, large sections of tissue, and large numbers of samples. Revealing the complexity of biology requires technologies that allow you to go broad as well as deep. Third, access. We aim to build products that work in any lab and in any scientist's hands. Ultimately, mastering biology is going to require tens of thousands of labs working together across the world. Our products are organized into three major platforms, and today, we will have one tech talk focused on each. Our Chromium platform is the ultimate single-cell platform for dissociated samples. An understanding of the basic building blocks of biological systems starts here. Our Visium platform is a no-compromise spatial discovery and translational platform, allowing whole transcriptome and targeted profiling of fresh or FFPE tissues down to single-cell resolution. Finally, our upcoming in-situ platform builds on the foundations of the recent acquisitions of CARTANA and ReadCoor. Using in-situ, discoveries from Chromium and Visium can be screened at the highest spatial resolution and across many samples, enabling a multitude of translational and ultimately clinical applications as well. We're excited about each of these platforms and plan on investing into years of major technological advancements in all three. While each is powerful in its own right, we're also dedicated to bringing you tools that allow you to combine data from across the platforms to enable applications impossible with any one alone. Our first talk will be on the Chromium platform. We've been honored to see Chromium highlighted by both Nature Methods in their Methods of the Year in 2018 and 2019, The Scientist Top 10 Innovations in all four of the last four years. Katie Pfeiffer from 10x R&D will be leading our Chromium talk. Let me turn it over to you, Katie. Thanks, Mike. Our understanding of biology has been transformed by single-cell analysis. It's provided critical insights into diseases that involve complex cellular interactions or rare cell populations. These insights have also paved the way for the development of life-changing therapeutics. This year, we've seen a global effort from the scientific community to unravel the complex biology underlying COVID-19. By providing unprecedented resolution, single-cell technologies have played a part in advancing our understanding of this disease. In less than a year, we've seen close to 60 publications using 10x technologies to gain insights into everything from the nature of the immune response to SARS-CoV-2 to identifying novel therapeutic antibodies and drug targets. At 10x, we're proud to have played a role in enabling scientists across the world to resolve the complexities of biology in fields such as oncology, immunology, neuroscience, and many more research areas with our suite of single-cell tools. This includes our single-cell gene expression solution, the current standard in single-cell transcriptomic profiling, our immune profiling solution, a powerful multi-omic assay for resolving the intricacies of the immune system, and our ATAC plus gene expression solution, which simultaneously profiles the transcriptome and chromatin landscape from the same single cells. We're not stopping here. Our mission is to enable scientists to answer the most challenging questions. To do this, we continue developing solutions year after year while pushing the limits in three key areas. The first is powering large-scale studies. We'll show you our new instrument and high-throughput reagent kits that will make million-cell experiments both routine and cost-effective. We'll talk about our new Fixed RNA Profiling solution that enables access to more samples than ever before. We're also making it easier to access single-cell research. We're launching a new low throughput gene expression kit to decrease the upfront cost of getting started with small-scale experiments. We'll be adding new resolution to our single-cell assays, expanding capabilities in functional genomics, antibody discovery, and T-cell receptor specificity. We're also expanding the functionality of our automation instrument, the Chromium Connect. Finally, we'll talk about our new 10x Genomics Cloud Analysis product, which will streamline the analysis of your 10x data. Let's dive right in, starting with new capabilities that will drive the next level of scale for single-cell research. Scaling up starts before running the assay itself during sample preparation. We'll release our CellPlex technology within the next few weeks. It uses a lipid-based cell tagging strategy that enables you to multiplex up to 12 samples, increasing the per-channel single-cell recovery severalfold. It's compatible across a broad range of sample types, it's species-agnostic, and it works with both cells and nuclei. Once libraries are sequenced, our software can be used to demultiplex the samples, remove multiplex, and visualize your data. CellPlex will bring you one step closer to the large-scale experiments we want to enable, but f or truly high-throughput applications, we need something more. From combinatorial drug screens to studies with large patient cohorts to antibody discovery and pooled CRISPR screens, each of these applications gains power through the routine analysis of hundreds of thousands to millions of cells. Today, conducting these types of translational experiments requires a huge investment of both time and resources to accomplish. We have changed this paradigm, and we're taking single-cell analysis to a new scale. We're excited to introduce the newest member of the Chromium family. This is the Chromium X. The Chromium X is the next generation of instrumentation, purposefully designed to enable high-throughput experiments. With its unique ability to simplify large-scale studies, it will make 1 million cell experiments routine. The Chromium X will support two new high-throughput reagent kits, the Single Cell Gene Expression HT Solution and the Single Cell Immune Profiling HT Solution. The new HT kits, along with the Chromium X, will make it more cost-effective, faster, and far less labor-intensive to perform these high-throughput experiments. The HT kits are based on a new chip design built on proven next-gen technology. The reagents have been engineered to match the performance of current Chromium reagents. This allows HT samples to be compared or integrated with data from our existing reagent kits with minimal technical batch effects. The new chip design also enables us to drive a number of key improvements, including the ability to run twice as many samples and process more than 4 times as many cells. When CellPlex is combined with HT reagent kits, over three-quarters of a million single cells can be recovered on a single HT chip at a lower cost per cell than ever before. In addition to measuring gene expression, our HT kits will be compatible with feature barcoding technology to simultaneously measure cell surface proteins or CRISPR guide RNAs. At the end of this talk, we'll show you some data for a high-throughput drug screening experiment demonstrating our HT solutions, so stay tuned. The high-throughput kits and the Chromium X, which will all be available later this year, deliver the necessary scale, operational simplicity, and lower cost per cell to finally enable routine large-scale experiments. We've built powerful, sensitive solutions for single-cell gene expression on fresh tissues, but as single-cell research using clinical samples has grown, new challenges have emerged. Patients spread across the country or globe, samples collected at all hours, and fragile cell types that might decompose before they make it into a Chromium. Our new Single Cell Fixed RNA Profiling kit helps overcome these challenges. Paraformaldehyde fixation makes it possible to stabilize samples at the point of collection, preserving biological states. This allows single-cell biology to be integrated into translational and clinical research. The workflow is compatible with any single-cell suspension. The sample can be optionally stained with antibodies for F eature Barcode compatibility and is then fixed with PFA. The assay is designed to capture either a subset of genes via targeted panels or the whole transcriptome, and achieves gene detection sensitivities comparable with fresh samples. Here's a demonstration of fixed RNA profiling on a PBMC sample, fixed and then stored for seven days at 4 degrees Celsius. When we run the fixed samples with a 2,000-gene immuno-oncology panel, cell type annotation is stable over seven days of storage, as is the median number of genes and UMIs detected per cell. When we plot the per-gene UMI counts between the day zero control and the day seven sample, we see an excellent correlation. The sample is effectively stabilized over seven days, meaning that samples can be collected, shipped, and batched with other samples to be analyzed days later. We aim for our fixed RNA profiling solution to achieve the same sensitive gene and UMI detection capability as our 3' gene expression solution does for fresh samples. Here, we compare UMI detection over the same 2,000 panel genes. Sensitivity is similar between the fresh and fixed workflow. Cell type annotation is similar between the two samples as well. We detect all the major PBMC cell types in each of the two samples. The new fixed RNA profiling solution will enable sensitive single-cell gene expression profiling together with cell fixation to stabilize delicate samples. Larger patient cohorts from samples collected and shipped will enable powerful new clinical research. We'll be shipping this solution in the second half of 2021, and we can't wait to see what the research community will do with it. We're excited about the large-scale capabilities coming this year, but we've also heard your requests for lower-stakes kits for testing new samples. That's why we've created the Low Throughput Gene Expression Kit. Whether you want to optimize your sample prep for a new tissue type, generate pilot data, or optimize experimental conditions before scaling up, the LT kit is a cost-effective way to run these small-scale experiments. You can profile between 100 and 1,000 cells per channel, and it works with the same wide range of sample types compatible with our existing single-cell 3' expression kits today. These plots compare 1,000 cells from the 3' LT gene expression data with about 9,000 cells from the same sample on our standard gene expression kit. You can see that the clustering shows great concordance between the two kits. The LT kit has the same sensitivity and detects the same cellular phenotypes, just with fewer cells. You can be confident that the performance you see in the LT format will be matched when you scale up to a higher throughput. The LT kit will reduce the upfront cost of optimizing and sample preparation and generating proof-of-concept data. You can run a sample for just one-third the cost of existing reagents per gene expression channel, and we're shipping the first half of this year. In 2021, we're continuing to innovate, building new products and supporting new applications on existing products. Pooled single-cell CRISPR screens enable researchers to interrogate the function of hundreds to thousands of genes in parallel, while single-cell transcriptomics analysis provides a rich phenotypic readout of the gene expression perturbations being applied. We shipped a fully supported Feature Barcode solution for CRISPR perturbation in 2018 with our 3' gene expression solution, and now we're bringing the same functionality to our 5' immune profiling kit with a fully supported Feature Barcode capability for CRISPR. Our 5' CRISPR Feature Barcode Kit is designed to be compatible with all of the most commonly available guide RNA scaffold sequences with no guide optimization required. That means that if you've already constructed and tested a guide library for a bulk or arrayed CRISPR screen, you'll have the flexibility of analyzing it as is in a single-cell format. In addition to broad guide RNA compatibility, you could also generate the other multi-omic readouts of our immune profiling assay, including cell surface protein, VDJ assembly, and antigen specificity. We'll make these capabilities available during the second half of this year. We built the single-cell immune profiling product to enable paired full-length antigen receptor sequencing on a massive scale. T-cell receptors and B-cell receptors play a key role in the immune system by recognizing specific antigens and regulating downstream pathways. Surveying and cataloging receptor sequences on their own is powerful, to fully understand the immune response, we also need the ability to map the antigens that these receptors recognize. We have a vision of truly large-scale mapping of T and B-cell receptors with their antigen-binding partners. That's why we're building a fully integrated solution for immune mapping. We call this Barcode Enabled Antigen Mapping, or BEAM. In the BEAM workflow, we create barcoded antigens, mix immune cells with these antigens in bulk, and then determine the antigen receptor sequence of single cells alongside the antigen specificity in our GEMs. Today, we'll introduce two new solutions using this technology for mapping antigen-specific T-cell receptors and for antibody discovery. TCRs recognize antigenic peptides that are presented by MHC molecules. Two years ago at AGBT, we unveiled the world's largest public data set of paired TCRs and the antigens they bind. Now, to map TCR peptide interactions at scale, researchers need more tools for the creation of peptide MHC reagents, tools that enable panels of many peptide MHC specificities to be prepared quickly and easily. Our Barcode Enabled Antigen Mapping for T-cell receptors, or BEAM-T solution, is that tool. BEAM-T will be built upon a technology developed by Denmark-based Tetramer Shop, now a part of 10x. Tetramer Shop has created a stabilized MHC scaffold that allows custom peptide loading in a simple mixing reaction. Researchers can design a library of peptides based on their research interests. The synthesized peptides can be loaded directly into the stabilized MHC. Tens, hundreds, or even more peptide MHC specificities can be created in parallel. The peptide MHC is given a Feature Barcode oligo to form a library of customized barcoded multimers ready to use in TCR discovery at an unprecedented scale. Of course, T-cell receptors are only one form of antigen recognition by the adaptive immune system. Antibodies produced by B- cells bind to protein antigens and can be used as powerful therapeutics and diagnostic tools. Using our BEAM technology, we're creating a fully supported workflow to barcode any antigen of interest and identify antigen-specific BCRs. Let me show you just how powerful BEAM- Ab can be for antibody discovery. We built a small library of five SARS-CoV-2 antigens and two control antigens. After barcoding the antigens and staining 100 million PBMCs from a convalescent donor, we used flow cytometry to enrich antigen-specific B- cells and used BEAM- Ab to link each B- cell's antigen specificity to its natively paired full-length antibody sequence. In just seven days from sample to antigen-specific antibody sequences, we identified over 2,500 B- cells with receptors specific to these antigens from a diverse set of clonotypes. Each circle on this figure represents an antigen-specific B- cell from our experiment. Colors indicate the antigen to which the cell had affinity. For example, the light blue central group recognizes the extracellular domain of the spike protein, while the yellow group recognizes the receptor-binding domain. We detect antibodies highly specific to each antigen, in addition to those that cross-react against multiple antigens. These are detectable only because we can test many antigens in parallel using BEAM-Ab. BEAM-T and BEAM-Ab are powerful tools for antigen-specific TCR and antibody discovery. BEAM-T will enable truly large-scale mapping of peptide MHC specificity by making it fast and easy to create new bar-coded MHC multimers. We demonstrated BEAM-Ab to show how researchers can identify antigen-specific antibodies against many antigens in parallel in just one week. Finally, we'll provide integrated software that uses this enormous amount of receptor sequence and specificity data to identify the most promising receptors for further development. BEAM solutions for integrated TCR and antibody discovery, together with our high throughput reagent kits and the Chromium X, will enable mapping of the immune system at a massive scale. We'll be shipping both solutions in the first half of next year. As researchers routinely adopt single-cell analysis into more complex workflows that span multiple users and multiple sites, the need for standardization becomes critical to ensure consistent, high-quality results. Last year, we began shipping the Chromium Connect to offer automated library preparation for 10x single-cell gene expression libraries. With the Connect, your library prep is done exactly the same way every time, no mistakes. This year, our single-cell immune profiling solution will be enabled on the Connect for both 5' gene expression and immune receptor profiling. Here you can see data comparing the manual and automated workflows. This plot shows the median UMIs per cell on a 5' gene expression library. Clearly, the Chromium Connect reduces technical variability between users. Connect reduces the hands-on time in the lab and produces highly reproducible results across sites and across users. We'll be bringing support for the single-cell immune profiling solution this year. We'll continue to expand the capabilities of the Connect in the future to include more assays. While the Chromium X and Chromium Connect simplify running 10x assays, our goal is to make every part of the workflow seamless, including data analysis. Since day one, we've been committed to delivering complete analysis and visualization for every assay, and we've shipped hundreds of software releases across our product lines. Today, we're taking this commitment one step further and introducing 10x Genomics Cloud Analysis, which will make it even easier for new 10x users to get started and for existing users to scale up to larger and more complex experiments. With the 10x Cloud, we're taking the technology that's accelerated our own internal product development for years, and we're bringing it to you. Optimized for Cell Ranger and our other pipelines, 10x Cloud is the easiest to use and fastest way to run 10x analysis anywhere. For example, some researchers are running Cell Ranger up to 500% faster on 10x Cloud compared to their local clusters. Because we believe that analysis is an integral part of our products, we're providing free cloud analysis for every single 10x sample you run. Whether you're analyzing two samples or thousands of samples, you can do so at no additional costs and without limits to scaling. This is just the beginning. 10x Cloud supports Cell Ranger in the United States today, and we'll soon add other pipelines, Loupe visualizations, and other regions. We're very excited about future developments that will bring even deeper insights into your data. To learn more and to ride along as we expand the cloud, visit 10xgenomics.com/cloud. Now that you've seen the ways that we're expanding our capabilities this year, let's look at how some of these solutions can work together to enable really powerful large-scale studies. In this example, we'll focus on a high-throughput drug screening use case. We conducted an in-house study to assess the impact of seven different drug compounds on two non-small cell lung cancer cell lines over several days. Before running the full experiment, we did a small-scale time course to determine the most informative time points to observe the effects of our drugs. We treated the A549 adenocarcinoma cell line with a combination of two commonly used lung cancer drugs, osimertinib and lenvatinib, and compared the impact of treatment with untreated samples over 72 hours using the Single-Cell 3' Gene Expression Low Throughput Kit and the Chromium Controller. For each sample, we captured between 500 and 1,000 cells. Here's a UMAP plot overlaying each time point for the drug conditions and the untreated control. As you'd expect, the drug treatments result in changes to the UMAP projections at all time points. We looked at the expression levels of genes associated with pathways known to be affected by these drugs. Shown here are three genes in the DNA repair pathway. In the dot plot, you can see that the drugs have reached their maximum effect on these genes at about 24-hour time point. We decided to focus on sub-24-hour time points to observe the effect of the drug when it's its most active. Building on this, for our high-throughput experiment, we took two non-small cell lung cancer cell lines and treated them with seven different drugs. We prepared samples at three different time points between four and 24 hours. Using our CellPlex technology, we multiplexed samples from the same treatment together, processed them with our single-cell gene expression HT solution, and ran them on the Chromium X. To get highly sensitive gene expression data on the most important genes, we used our targeted gene expression solution with pre-designed pan-cancer and gene signature panels. The final libraries were sequenced to just 10,000 reads per cell. Here you can see the UMAP projections for nearly 400,000 cells that were profiled, colored by cell line. Using the soon-to-be-released Cell Ranger 6.0 pipeline, we demultiplexed the pooled samples and were able to see distinct transcriptional profiles for each cell line, independent of treatment condition. Next, we wanted to investigate the effect of drug treatment on each cell line over time. As expected, we see that the clustering within each cell line cluster is driven by the treatment condition. For both cell lines, we saw that a specific treatment condition leads to changes in the transcriptional profiles that are common to both cell lines. We looked at each drug time course in detail. Interestingly, the erlotinib treatment led to notable changes in the transcriptional profiles over the short time course we examined, with the biggest change occurring between four and 16 hours. We looked at the specific genes driving those global changes, we saw notable downregulation in the expression of EGFR. We know erlotinib inhibits EGFR at the protein level, the rapid post-treatment downregulation at the mRNA level was striking. In this experiment that took one week, we screened 96 conditions simultaneously on almost half a million cells from a single HT kit using the Chromium X. The new technology advancements we've talked about today will allow experiments of this scale and nature to become routine, allowing the pace of understanding and discovery in biology to be rapidly accelerated. As we look back and see how single-cell tools have contributed to basic and applied research, we're in awe of what researchers have uncovered, and we're committed to providing new tools to facilitate the next phase in discovery. In order to push the limits of large-scale studies, we will launch the new Chromium X instrument and high-throughput reagent kits, making million-cell experiments both routine and cost-effective. Our new fixed RNA profiling solution will open up access to new clinical samples by simplifying the logistics of collecting and stabilizing cells from distributed sources. With the introduction of our Low Throughput Kit, it'll be more affordable than ever to get started generating high-quality single-cell gene expression data. Building on our immune profiling solution, we'll enable 5' CRISPR to support functional genomic studies and provide Barcode Enabled Antigen Mapping solutions to scale antibody discovery and high-throughput characterization of T-cell receptor specificity. To further simplify the use of our products, we'll add support for 5' gene expression and VDJ enrichment to the Chromium Connect. We'll also enable streamlined data analysis with cloud analysis. By continuing to develop and deliver a wide breadth of tools that enable routine, high-resolution single-cell studies, our goal is to empower researchers to gain deeper insights into biology. With that, I'm pleased to introduce Dr. Yvanka de Soysa, who will be talking about her work in characterizing organ-level developmental defects during cardiogenesis. Hello. My name is Yvanka de Soysa, and I did my PhD work in Deepak Srivastava's lab at UCSF and the Gladstone Institutes. The Srivastava Lab studies the mechanisms underlying cardiac development in order to better understand the mechanisms by which congenital heart defects, or CHDs, arise during embryogenesis. A salient feature of CHDs is that only a specific structure of the heart is malformed, and this is due to dysregulation of distinct cell subsets. A major hurdle in understanding which cell subsets are perturbed in CHD has been an inability to appreciate the full repertoire of cell types that make up the heart. As a result, we don't understand the molecular drivers that regulate the identity and behavior of these cell types, and this is largely due to technological limitations. For my PhD, I applied the 10x Genomics single-cell 3' gene expression solution to overcome this hurdle and capture tens of thousands of single cells from the early developing mouse heart. This technology enabled us to study the full spectrum of cardiac cell populations at a time when the heart is undergoing major changes in shape and cellular composition. Using this rich data set, my collaborators and I uncovered novel cardiac genes and identified key regulators of differentiation of cardiac progenitors to mature cell types. We were also able to pinpoint the specific cell types that express genes in which causal genetic variants linked to CHDs have been identified. This is exciting because this provided a starting point and framework to unravel the mechanisms underlying CHDs for which we know the genetic cause but not the cellular and functional consequence. We then applied the 10x technology to early stages of heart formation in a mouse that lacked a critical cardiac gene called Hand2. Absence of Hand2 leads to a severe heart malformation. We don't know, again, the mechanisms by which its loss leads to dysregulation at the cellular level to cause this malformation. We found that Hand2 loss led to perturbations in just two cell populations, and the defects in each population was distinct. For example, one population was formed but had migratory defects and prevented it from getting to the right place at the right time, while the other population failed to form entirely. Importantly, applying the 10x Genomics platform to this question made us change the way we think about Hand2 and its role in cardiac development. It also established that single-cell RNA sequencing is a tremendous tool to dissect the mechanisms of developmental defects. Moving forward, we are excited to use 10x technologies to probe the spatial and gene regulatory aspects of these cell types in a variety of human CHD contexts. Thank you. Thanks, Yvanka. That was a really exciting application of the Chromium platform to heart development. Our next talk will be on the Visium platform. Our Visium platform was based on technology acquired from Spatial Transcriptomics in 2018. We've been honored to see Visium featured on the cover of "Nature Methods" for its Method of the Year in 2020, and "The Scientist" Top 10 Innovations in 2020. James Chow from 10x R&D in Stockholm will be leading our Visium talk. Let me turn it over to you, James. Thanks, Mike. As humans, we are visual by nature. We use images and visualizations to help interpret and understand our environment. To truly understand and resolve biology, visualizing data in its spatial context is essential. This is what our spatial platforms give you access to. Let's illustrate this further by comparing the complexity of the human body, with its trillions of cells forming complex spatial systems, to the surface of our planet. When you first want to make a map, you start from nothing, then over time, improvements in technology allow for the discovery of more detail and greater resolution. There are currently several approaches being used to try and help map the human body. Some of these rely on sampling several small areas of your tissue section. These small areas are often referred to as regions of interest. The problem with such approaches is that it's very easy to miss key details, as you never capture the full picture. Let me show you what this looks like. As you can see, it's like looking through a keyhole into the incredibly complex world of biology. It's just not enough to get a good picture. What if you could open the door? This is where Visium comes in. Not only are you able to achieve a full overview of any tissue, but this overview is extremely information-rich, capturing data across the entire transcriptome. This now empowers researchers to address many fundamental questions in biology and accelerate discovery. We're immensely proud of the research that is being enabled by Visium. A rapidly growing number of publications demonstrate the impact true spatial biology can have in a wide range of applications that spans discovery and translational research, including oncology, neuroscience, and immunology. The pace is only increasing, as evidenced by the tremendous number of preprints that utilize Visium. Just as with the single-cell platform, we'll be pushing the boundaries of what is possible for Visium when it comes to scale, access, and resolution. First, we'll cover scale. We'll talk about our new FFPE-compatible solution, as well as a new Visium slide with larger capture areas. Then we'll go through the different ways we're enabling easier access to Visium. This will cover a new instrument from 10x, the CytAssist, enablement of pathology-driven workflows, and our Clinical Translational Research Network, or CTRN. We'll look at two new offerings that will dramatically improve the resolution of spatial analysis currently available, our highly multiplexed protein product for Visium, and finally, we'll introduce our ultra-high-resolution product, Visium HD. Let's start with scale. At 10x, our goal is to make our technologies available to as many researchers as possible, and this means to as many sample types as possible for large-scale studies. One of the most frequent requests we've had from researchers for our Visium platform is to make it compatible with formalin fixed, paraffin embedded, or FFPE samples. FFPE samples make up the vast majority of patient samples collected in the clinic. Enabling this sample type opens up a whole new universe of high-impact studies using biobank samples across every disease area from cancer to neurodegenerative disease to inflammatory conditions. However, unlocking the transcriptome hidden in FFPE tissues is not a straightforward task. The modification and fragmentation of RNA caused by FFPE preservation and storage has made assessment of the transcriptome a huge challenge. Until now, t o address these issues, we took a completely new approach for our FFPE-compatible Visium product. The approach allows us to overcome the challenges introduced by RNA modification and fragmentation. We have developed and optimized a distinct chemistry to work with FFPE tissue. To benchmark this, we looked at a newly prepared FFPE mouse brain sample. When using our standard poly(A)-based chemistry, the FFPE sample yields very low sensitivity. When using the optimized poly(A) protocol developed by the Lundeberg group at SciLifeLab, the sensitivity improves to the point where we can start to retrieve some transcriptomic data, but it's still limited. With our new approach, we're able to achieve levels of sensitivity comparable to the standard Visium product in fresh frozen samples. All this while still maintaining the same high spatial resolution. Now, we take an example of how this sensitivity translates into gene expression data that can resolve and define disease. This sample is a triple positive breast cancer, a two-year-old sample retrieved from a biobank. When we process this sample with Visium for FFPE and compare the results with standard Visium run on a matched fresh frozen control from the same tumor, we see an excellent correlation between the two analyses. If we look at the number of genes our new FFPE assay detects, we see comparable sensitivity to the standard Visium assay with fresh frozen tissue. We asked the pathologist to annotate the cancerous regions of the sample, represented here by the outlines in this image. Now we have a grasp of where the cancer cells are located, but is there more biological information hidden in this tumor? Let's investigate further. First, we'll look at the clustering. Using Visium for FFPE in combination with our Space Ranger software, we can output four major clusters based on differential gene expression. You can see how tightly these clusters align with the pathologist annotation. For example, the red cluster identifies regions of carcinoma within the tissue. If we use immunohistochemistry to look at the diagnostic markers of triple positive breast cancer, HER2 and the estrogen and progesterone receptors, you can see the Visium gene expression data correlates very nicely with the protein data. We can go much further with Visium data. Subdividing these larger, apparently uniform areas into regions with distinct molecular signatures and identifying clinically relevant cell types. Let's look at the pathologist annotations for another sample and focus on the regions of ductal carcinoma highlighted in yellow. Now we'll add our Visium gene expression information. As you can see, yet again, how well this data aligns with the demarcations provided by the pathologist. Let's go a step further. We don't have to stick to a few markers but can investigate the entire transcriptome. We can answer the question many of you will be thinking about at this point. Where are the immune cells? Tumor-infiltrating lymphocytes are a hallmark of the immune response in cancer and have prognostic value in the clinic. Here, as an example, we use Visium for FFPE to identify infiltrating T- cells and macrophages. It's also possible to drive powerful analyses of Visium data by combining it with data from our single-cell assays. We paired our spatial data with single-nucleus RNA seq data generated using our Chromium Single Cell 3' Assay. Cell type expression profiles derived from the Chromium Single Cell 3' Prime Assay allowed us to estimate cell type proportions for each Visium feature and give insight into cell type co-localization. As an example, staying on the topic of immune infiltrates, we can map B- cell populations at different stages of maturation within our breast cancer tissue section. Here we see the distribution of memory B- cells, plasmablasts, and then finally the mature plasma cells. With Visium for FFPE, you can now analyze the whole transcriptome for your entire tissue section at high resolution and with high sensitivity in FFPE tissue samples. To streamline your workflow, we've eliminated optimization for individual tissue types so you can get to the data faster. The protocol is compatible with both H&E and immunofluorescence stains. Initially, we will launch with support for human and mouse tissues. Just as with our other solutions, we'll offer integrated software for data analysis and visualization. Visium Spatial Gene Expression for FFPE is a groundbreaking technology that complements traditional pathologist-led analysis by combining the benefits of histological techniques with the massive throughput and discovery power of RNA sequencing. This technology will enable new discoveries that will prove instrumental in helping scientists gain a better understanding of biological processes and disease. We are extremely excited about the potential for this product and plan to release it first half of this year. Enabling as many samples as possible not only means sample types, but also sample sizes. The current size of the Visium capture area has been used for a wide range of applications to date, but for some samples, such as certain human biopsies, a larger capture area is desired. Therefore, we will release a completely new configuration of Visium Slide with even larger capture areas to accommodate more samples of varying size. The new setup will contain two large capture areas on one slide while maintaining the same resolution as the current Visium slides. Each capture area will contain around 14,000 spots and fit tissue sections up to a size of 11 by 11 millimeters to accommodate tissues that are almost 3 times as large. With these larger capture area slides, we'll help researchers access larger samples while still providing all other Visium advantages, such as whole transcriptome data from the entire tissue section with high resolution. This product will be available in the second half of 2021. We'll now discuss a few of the different ways in which 10x will help streamline workflows specifically geared for translational research. As mentioned earlier, many patient samples end up archived in biobanks. We're talking about millions of samples every year. Many of them look like this. Some are sectioned already and stored on slides waiting to be stained and studied. Due to the nature of the Visium process, these samples have not been compatible with the Visium technology so far. We are happy to introduce Visium CytAssist, a powerful platform designed to simplify slide handling. Now you can identify the optimal tissue section to address your biological question in advance. Use your own slides during sectioning, capture and annotate your images, and then choose the best sections to analyze further with Visium. The CytAssist pairs the tissue sections of your choice with Visium slides, allowing broader access to archive samples with a streamlined workflow. Tissue sections are permeabilized inside the instrument, allowing analytes such as antibodies bound to the sample and RNA transcripts, to be released from the tissue for hybridization to the Visium capture probes. From here on, you follow the standard Visium protocol to create Visium libraries. Comparing gene expression clusters detected in FFPE samples that were sectioned directly onto Visium slides with FFPE samples processed by CytAssist, you can see the same detailed expression patterns between the two different workflows. Visium CytAssist simplifies sample handling while preserving data integrity in FFPE analyses. Now, researchers and pathologists will be able to preview tissue sections from archive samples and select the most interesting sections for analysis with Visium assays. The Visium CytAssist platform will be available for pre-order in 2022. The CytAssist will enable expanded sample access and user choice for Visium FFPE assays, Visium slides with larger capture areas, and is designed for compatibility with future Visium products. Pathologists have been spatially assessing tissue sections for hundreds of years to understand and diagnose disease. More recently, molecular tests have been combined with histological stains to decipher a patient's underlying disease. This is why we're thrilled to see how our Visium users are working with the pathology community to come together and combine their vast experience in molecular and spatial biology to enhance the pathology workflow. I want to show you just how easy it is to incorporate information from pathological annotations in our own software, Loupe Browser. You can do your analysis without regrets because we've captured all the data within the entire tissue section at this point. This is a significant advantage over region of interest-based solutions, where you have to decide upfront which areas you want to compare and can't redefine the areas later during data analysis. Let's take a look at data analysis of a breast cancer sample. Our pathologist annotations show most notably ductal carcinoma in situ in yellow and immune cells in red. To integrate this information with our gene expression data, all we have to do is to create clusters reflecting the annotations. We'll quickly recreate the annotations for DCIS and immune cells, and you can see just how easy it is to remove a spot from your selection if you don't want to include it. You have tremendous flexibility in the software to choose the precise areas of tissue you want to analyze. Now with the click of a button, I can compare the gene expression patterns in both the cancer and immune cell region. This can enable identifying new biomarkers, as well as integrating them with known biomarkers. Key questions such as, what are the genes driving a certain morphology? What's the difference between a healthy and a diseased area? What biomarkers will be predictive of prognosis or response? Just a few clicks away. With all of these features to make Visium more useful to pathologists and researchers, we see tremendous potential for Visium in clinical translational research. This led us last year to kick off our global Clinical Translational Research Network or CTRN program. The goal was to create a network of outstanding translational researchers to fuel their research. We want to remove barriers by giving them access to the most innovative technology and accelerate clinical and pharmaceutical research in the translational space. The CTRN currently has over 50 members from nearly 40 institutions around the globe, including GSK, Johns Hopkins, Mass General Brigham Cancer Institute, and the Garvan Institute, where CTRN members are leveraging Visium in a number of ways, including discovering novel predictive biomarkers with morphological context to better inform and improve treatment response. We're happy to announce that starting today, we're accepting applications for the 2021 class of our CTRN. You can follow the link shown here to learn more and submit your application for a chance to be part of this elite group of clinical translational researchers. The last theme that we'll look at is resolution. So far, we spoke about RNA. Another critical component in cells are proteins, which are encoded by the RNA. While RNA and proteins each have their own value in biology and disease development, the ability to study the transcriptome and the proteome at the same time using the same tissue section allows you to further characterize rare cell types and get insights into functional workings of normal and diseased tissues. Our current Visium product allows for the co-detection of a handful of proteins using immunofluorescence. While the addition of this qualitative capability has proven to be of great value, our goal is to support the study of large numbers of proteins while providing a quantitative measurement. That is why we're excited to introduce our highly multiplexed protein assay for Visium. This multi-omic approach uses antibody oligonucleotide conjugates to enable simultaneous detection of many tens of proteins together with RNA with spatial context. We are most excited about the fact that the RNA and protein modalities can be measured simultaneously in the same tissue section. No additional work is required or the need to approximate using serial sections for two separate measurements. Further, now you can conserve your precious tissue samples by getting multiple measurements, whole transcriptome, and highly multiplexed protein in just one experiment. The highly multiplexed protein assay for Visium will be available in the second half of this year, allowing researchers to conduct true multi-omics spatial experiments and resolve the complex biology in a tissue section. Now switching gears, we wanted to address a huge ask from you since we launched Visium, the need for higher resolution to the level of a single cell. From the first generation of spatial transcriptomics to Visium, we improved the resolution fourfold, among other major improvements. We wanted to push Visium to the extreme in terms of resolution. By reducing the size of each spot 25 micrometers, we've increased the resolution of Visium 1,500-fold over the first generation of spatial transcriptomics. We'll call this product Visium HD. Let me demonstrate the resolution that Visium HD will give you access to. With Visium HD, Visium is going to single-cell scale. This will enable even more scientific questions to be addressed with Visium in the future. It will allow for finding rare cells while still giving you access to the transcriptome of the entire tissue section. In this overlay, you can get a grasp of just how high the Visium HD resolution really is. Here is one of our in-house data sets from Visium HD analyzing a mouse brain sample. By overlaying the HD capture spots with the current Visium capture spots, it becomes apparent how our highly sensitive assay allows you to capture heterogeneity at single-cell scale. Notice how you can pick up even subtle differences in gene expression at this scale. One more thing, this is FFPE. Each Visium spot with the current size can fit up to 120 Visium HD spots, thus achieving single-cell scale. Each 5-micron spot is only a few microns apart from the next, allowing for high tissue coverage. When compared to other methods of a similar scale, Visium HD shows superior sensitivity. Probably just as important, we'll offer Visium HD as an end-to-end solution, giving you the same seamless experience and support you're used to from our other products. Like Visium today, it will support both H&E and immunofluorescence stains on the same tissue section without the need for any other instrumentation. As we want to help you make the most out of your Visium HD experience, everything we've done on Visium, we'll bring to Visium HD as well. This means that it will be compatible with FFPE tissue, our coming highly multiplexed protein assay, as well as with being loaded onto the CytAssist. Visium HD will be available during 2022. As you've seen throughout this talk, we have big plans for Visium, and this is only the beginning of our roadmap. We're thrilled to see how all of you have been using our current Visium product for true spatial discovery and how you'll continue resolving biology together with all of these upcoming products. To push current boundaries when it comes to scale, we introduced our Visium for FFPE solution, as well as our Visium slides with larger capture areas. In order to simplify access to our solutions, our CytAssist instrument will facilitate integrating Visium into routine histological workflows, together with our easy-to-use software. Our clinical translational research network will continue to prove the enormous potential of our products to improve patient-oriented research. Finally, our highly multiplexed protein assay, combined with gene expression, will offer true spatial multiomics, while Visium HD will allow us to elevate the entire Visium platform to an unprecedented level of resolution. With that, I'm pleased to introduce Alma Andersson, who will be talking about research that leveraged the initial spatial transcriptomics technology and combined it with single-cell data to study HER2 positive breast cancer. My name is Alma Andersson, and I'm a PhD student in the Lundeberg Lab, situated at SciLifeLab, Stockholm. My work is mainly focused on computational method development, but every now and then I get the opportunity to be enrolled in projects with a slightly more biological take to them. One such example is a fantastically fun and exciting project that actually started several years ago and turned into the manuscript, "Spatial Deconvolution of HER2-Positive Breast Tumors Reveals Novel Intracellular Relationships." In this study, we wanted to assess the molecular transcription landscape of HER2 positive breast cancer tumors. However, given the prominent role of the tumor microenvironment for treatment response as well as prevention and promotion of tumor growth, it was essential for us to put gene expression in a spatial context, hence why we used the first-generation spatial transcriptomics platform. In short, in this study, we collected 36 tissue samples from each HER2-positive patients and used spatial transcriptomics to obtain full transcriptome spatial resolve data for all of these sections. Applying different methods of analysis such as expression-based unsupervised clustering, single-cell data integration, and colocalization analysis, we made several interesting observations. Just to highlight a few of them. The expression-based clustering, exemplified in Figure 2, identified spatially separated tumor foci in the same tissue section with different expression profiles, but also varying degrees of immune infiltration. Just seeing one example of intra-patient heterogeneity. As shown in Figure 4, single-cell integration allowed us to infer the spatial distribution of cell types in our tissues, where we observed a strong colocalization signal between chemokine-expressing macrophage subsets and a T- cell subset expressing interferon response-related genes. As well as more support for a mechanism where the macrophage subset recruits this T- cell subset in order for them to be activated by an interferon signal. Finally, as Figure 5 illustrates, using the joint presence of B and T- cells as a proxy for Tertiary Lymphoid Structures, TLSs, important for tumor treatment and outcome, as well as impacting the degree of tumor-infiltrating lymphocytes, we could extract a TLS gene signature and construct a predictive model for TLS sites. In summary, spatial transcriptomics allowed us to survey the molecular transcription landscape, cell type interactions, and spatial heterogeneity in our tumor samples. If you're interested in more of the details, please do check out the manuscript and the paper. Thank you all for listening, of course, and to 10x for letting me partake in this amazing event. Finally, to all of my collaborators and co-authors on this paper. Thanks, Alma, for that really cool combination of Chromium and Visium technologies. Our final talk will be on our upcoming in situ platform. Our in situ platform builds on the foundational technologies from our acquisitions of both CARTANA and ReadCoor. As we have done with Visium, we plan to invest heavily in this platform in the coming years, bringing new capabilities far beyond the initial technological foundations. Nikhil Rao from our product marketing group will lead our in situ talk. Let me turn it over to you, Nikhil. Thanks, Mike. As you've seen, whole transcriptome spatial Visium and single-cell Chromium platforms provide a global understanding of your tissue and cell biology by allowing you to interrogate thousands of genes simultaneously. By focusing on a subset of genes, there are ways to determine localization of specific gene signatures even more precisely. Such a targeted approach also offers a means for a simplified readout, enabling large follow-on studies. Just as in a map, let's start zooming in to see what this can look like. We start to see more details, such as groups of cells, individual cells, and eventually inside those cells. We've already used two 10x platforms to identify distinct cell types represented by different colors. By focusing on a few immune cell markers of interest, you can distinguish and clearly see the immune cell distribution, together with all other cells in the surrounding microenvironment and in the context of the entire tissue section. You can dive deeper into the cells themselves to see the individual RNA molecules within the immune cell. This is what our new third platform, In Situ, will enable you to do. Our In Situ platform, geared toward researchers who know what they are looking for and want to focus on specific targets discovered with Chromium or Visium at single-molecule resolution as an orthogonal approach for measuring biological molecules. Like our other two platforms, In Situ will allow us to push the boundaries of what is possible when it comes to resolution, scale, and access. In Situ analysis complements and adds to the capabilities provided by our Chromium and Visium platforms. A number of publications based on Chromium and Visium already take advantage of in situ approaches from third parties to validate, refine, and localize transcriptional findings. We plan to provide our own in situ solution to address this need and far more. Our platform will build on the foundation of our two recent acquisitions of CARTANA and ReadCoor. ReadCoor developed the RC2 instrument based on FISSEQ, fluorescent in situ sequencing, developed by the Church Lab at Harvard Wyss Institute. CARTANA was spun out from Mats Nilsson's laboratory at the SciLifeLab in Stockholm. They had early successes in providing commercial reagent kits for in situ sequencing to researchers. Last year, CARTANA was listed as full partner on three of the six European Human Cell Atlas projects. Foundational technologies from ReadCoor and CARTANA, together with the expertise from 10x, will allow us to build the best In Situ platform for our customers. While its roots are in ReadCoor and CARTANA, our In Situ platform will be a 10x solution that extends performance, robustness, and sample access in key ways. We believe that equipping scientists with the platform will enable virtually limitless applications and help accelerate the mastery of biology. The In Situ platform uses a distinct approach from Visium. Targeted probes are hybridized directly to the RNA within the tissue section on a glass slide. In order to identify the targeted RNA with high specificity and sensitivity, the probe barcodes are sequenced directly on the tissue with several rounds of imaging. This approach eliminates the need for a next-generation sequencing-based readout while providing subcellular resolution and high throughput. It shows you individual molecules in their native context within intact cells and tissues with minimal manipulation before the readout. Our In Situ platform enables visualization of biomarkers with panel sizes of hundreds up to thousands of genes in the spatial context at unprecedented resolution. Even with the superbly high resolution, you're still able to image an entire tissue section. In this CARTANA example, you can see the outline of a mouse brain sample showing the entire image tissue. The color is a powerful representation of how rich the data is. This becomes even more apparent when zooming in and focusing on a specific cellular marker. Here, at higher magnification, you can spatially visualize oligodendrocytes marked in blue, somatostatin-positive inter neuron in green, and glutamatergic neurons in red. Furthermore, you can appreciate the single-molecule resolution of the In Situ assay, with each symbol representing an individual RNA molecule. To demonstrate the power of in situ technology, we'll investigate the tumor microenvironment of a human melanoma FFPE tissue section. It was analyzed with a target set of 137 immune cell-specific genes and immune oncology biomarkers using the CARTANA chemistry. The picture shows the entire melanoma tissue section with clear expression patterns. Here we show a few targets at higher magnification. Each color represents a single cell type based on one or more biomarkers in the animation. To give a few examples, a group of macrophage markers are in green, B-cell markers in pink, immune checkpoint markers in blue. When combining all of them once more, you can just see how much information can be captured in one single data set. At this magnification, it becomes also possible to distinguish different sub-regions of the tissue, such as stroma versus cancer, not only by using morphological information, but also by using distinct expression patterns of various biomarkers. Seeing the combined usage of in situ technology together with single-cell RNA sequencing data shows a great way to both characterize cell types as well as visualize them in the morphological context. Many publications using Chromium and Visium have used in situ techniques to further refine and go deeper into the tissue data. One example is demonstrating tissue atlasing. Tosti et al. recently demonstrated this in human pancreas using the CARTANA technology. First, the authors used the discovery capabilities of single-cell sequencing to identify specific cell markers. Then they used the sets to design a targeted panel for in situ sequencing. They were able to atlas different cell types in the human pancreas. Using 98 carefully selected gene markers, they were able to distinguish pancreatic cell types. When zooming in, you can visualize quiescent and activated stellate cells in the connective tissue in green or red endocrine islets and pink macrophages. This atlas can be used as a future reference to understand pancreatic cell biology and diseases. We will launch an integrated in situ solution with hardware, reagents, and software for a turnkey experience. The instrument will enable high-plex multiomics to interrogate transcriptomic and proteomic analytes simultaneously without the need for a separate next-generation sequencing instrument. Additionally, the platform will be compatible with most tissue samples and organs, supporting FFPE, fixed frozen, and fresh frozen samples while preserving the tissue morphology for H&E assessment. Optimized chemistry will allow highly specific and sensitive single-molecule detection of RNA and proteins at subcellular resolution. Based on your feedback, we will offer the flexibility through the use of pre-designed panels and customization options to incorporate your targets of interest. Lastly, the throughput will be optimal for large cohorts of preclinical and clinical studies. The technology will allow efficient imaging of entire tissue sections without being limited to specific regions of interest so that you achieve a holistic view of biology. Eventually, we believe that this proven technology will translate into clinical and tissue analysis to lead to broad adoption in tissue-based diagnostics. Based on the overwhelming demand for in situ technology, we recently kicked off an in situ access program. The goal is to enable the use of the current CARTANA technology to a limited number of researchers in order to initiate publications showing the potential of the existing CARTANA chemistry while our R&D team is working on our end-to-end 10x solution. The next round of applications will open in the middle of 2021. Here's a few example data sets from our very own customers. After all we've covered today, you might be wondering which product is right for me. The whole transcriptome discovery approach and large screening panels used on Chromium, Visium, and Visium HD are best suited for unbiased gene expression analyses for single-cell suspensions or tissue samples at single-cell resolution. This discovery approach can be supplemented with our In Situ platform to provide precise gene localization customized to the genes you care about. Simple analysis lends itself well to larger throughput follow-on studies. With all of these tools for translational research today, 10x aims to make these types of foundational technologies more clinically relevant in the future. Now I'd like to introduce Ashley Lu, who will be talking about how she combined the power of spatial transcriptomics and in situ sequencing to identify gene expression changes that occur in cells in amyloid plaques that are known to give rise to Alzheimer's disease. Hi. My name is Ashley. I'm a PhD student, from the VIB Center for Brain & Disease Research in Belgium. Our lab has been focusing on the study of Alzheimer disease. The role of amyloid plaques in Alzheimer disease has puzzled scientists ever since Alois Alzheimer first described them in the brain of a woman with young onset dementia. Now, over a century later, we have learned a lot about the molecular processes that leads to neurodegenerations and subsequent memory loss. The relationship between the plaques and the disease process in the brain is still unclear. Amyloid plaques might act as a trigger or as a driver of the disease, and the accumulation of amyloid beta in the brain likely initiates a complex multicellular neurodegenerative process. Our team trying to map out the molecular changes occurring in the cells in the vicinity of amyloid plaques by using spatial transcriptomics. This technology allows us to analyze genome-wide transcriptomic changes induced by amyloid plaques in hundreds of small tissue domains. In this way, we could generate an extensive data set of transcriptional changes that occur in response to increasing amyloid pathology, both in mouse and human brains. We identified two novel gene co-expression networks that appear highly sensitive to amyloid beta deposition. Genes in the first network were mainly expressed in astrocytes and microglias, and were not co-expressed in the absence of amyloid beta. The second network expressed primarily to oligodendrocytes, and this network was activated under mild amyloid stress, but depleted in microenvironments with high amyloid accumulation. For confirmation, we've also used target-orientated In Situ sequencing to visualize which cell types in the brain tissue express each of the genes from these two networks. As such, by using Spatial Transcriptomics in combined with In Situ sequencing, we have been able to map the pathogenic cellular response triggered by A-beta depositions and driving disease progression. Thanks, Ashley. I still remember when that work was first published and how exciting it was. Hopefully, this is an important step on the way to curing a terrible disease. With that, we finish the main talks of our first ever 10x Genomics Xperience event. We really hope you enjoyed the event and are as excited as we are about all the new products we have coming in the months and years ahead. As always, we encourage you to sign up to hear the latest at the URL shown below. As we move into our live Q&A breakout sessions on Chromium, Visium, and In Situ, we have an opportunity. Tweet about your favorite parts of today using the hashtag Xperience10x, and you will have a chance to win one of these custom 10x Genomics building block sets. If you like what you saw today and want to join us in our mission of mastering biology, please visit our jobs page and apply online. We've gotten where we are because of our amazing people and are always looking for the best to join us. Our breakout sessions will begin in five minutes. No need to do anything, just stay logged on into the event, and you'll be taken to the track you registered for. Again, thank you for joining us.