Hi, everyone. Thank you for joining us today for the webinar. My name is Mio Tonouchi. I am the director of marketing for the Asia Pacific region, and I'll be hosting today's session. We are really excited for today because we have an announcement of the new solutions and also the products to come this year and next. Today I invited a few product marketing manager from the headquarters to go over some of the details. Next slide, please. Okay, cool. We have two sessions. The first one, we're gonna spend the first 20-25 minutes talking about the single-cell solutions. As you can see, there are five products updates that we break down. Dina Finan, who is the product manager for the single cell, Zuly Peralta, who is the product manager for Spatial, as well as Samantha Shelton for the high-throughput single cell, they will be speaking on these products. Using the second half of the webinar, I will cover on the spatial solutions as well. If you have any questions during the session, please feel free to submit through the Q&A chat box so that we can address that at the end. With that, I'll hand it over to you, Sam, so that you can get started. Thanks, Mio. Thanks everyone for joining. We're really excited to be here today to talk about some of our new solutions. At 10x Genomics, we really see ourselves as advancing biology and creating new tools for researchers to advance biology across our three complementary product platforms. The first of these is our Chromium single-cell platform, which has enabled tons of discoveries across many different research areas, including oncology, immunology, and neuroscience and has allowed researchers to do things like discover new cell types, identify new gene signatures, and really deeply characterize the heterogeneity of many different sample types. Next, we have our Visium spatial platform, which will be highlighted later by Courtney and Jyoti, which greatly enables researchers to profile the heterogeneity of their tissues while also maintaining the morphological context as well. Courtney and Jyoti are gonna talk about some of the exciting new developments that we have coming there. Lastly, we are also building our third product platform, our Xenium In Situ Platform, which will be a more targeted approach compared to our Chromium Single Cell and Visium Spatial platforms, which are better for early-stage discovery. We're really excited about that platform as well. I believe Courtney and Jyoti will talk about that a little bit as an addition. That will be released later this year. With that, I do wanna start by highlighting our Chromium Single Cell platform and just how far we've come even through 2021. We released our first single-cell gene expression product, just actually only about five years ago, but we've really come a long way since then, releasing tons of new products that have enabled a wide array of discoveries, including our immune profiling solution, our targeted gene expression product, our Multiome ATAC + Gene Expression product to profile open chromatin as well as gene expression data from the same cell. More recently, we released our newest instrument, which is the Chromium X series of instruments, which is compatible with our single-cell high-throughput assays. We're really excited. We're always really excited to talk about these products. We're very proud to show that, you know, it's not just us who thinks that these products are exciting and innovative. Our products have made it to The Scientist's Top 10 Innovations of the year list in five of the last five years. This most recent year, the product which made it to this list was our Chromium X product, which allows researchers to scale up their single-cell experiments and achieve costs as low as $0.02 per cell. We can also see that, you know, researchers share the enthusiasm of these products as well, just looking at the number of publications. This slide, you know, constantly needs to be updated and so I think is usually out of date. I think, yes, as you can see, we actually have 3,400 publications now. This just goes to show how single-cell research is being used more and more frequently to fuel discoveries across the life sciences. It's been used in a wide array of different research areas and topics including discovering new cell types in cancer, understanding the early stages of embryogenesis, and looking at neuropathogenesis as well. Really just from every research area, I think has been touched by the power of single-cell sequencing. As I mentioned, the Chromium X is our latest instrument. We're really excited about this instrument launch for a number of reasons. The first is the degree of throughput flexibility. The Chromium X is the instrument with the highest degree of throughput flexibility on the market. What we mean by that is that it has the ability to go from very low throughput samples, very low throughput cell loads for those pilot and early-stage experiments, all the way to the highest throughput experiments, very easily depending on what your research needs are. In addition to having this range of throughput flexibility, it also provides a one-stop shop for all single-cell assays. As I mentioned earlier, we've released a number of single-cell assays over the past few years. The Chromium X can run all of our on-market products currently. This includes products for single-cell gene expression, single-cell immune profiling, as well as for single-cell ATAC, and Multiome ATAC with gene expression. It really provides a one-stop shop for any researcher who's interested in looking at biology at the single-cell level. Compatibility with our high-throughput products makes it ideal for researchers who want to achieve economies of scale for those larger scale experiments. For experiments where you might need, you know, hundreds of thousands of cells, for example, for cell atlas, cell atlas or deep tissue profiling, you can those experiments are brought much more within reach with our high-throughput assays. Lastly, our instrument is extremely easy to use with an intuitive user interface, more advanced sensors which allows for better support and troubleshooting. As I mentioned, the Chromium X is compatible with our complete single Our complete suite of single-cell assays, which allows for the most comprehensive selection of assay types, which allows for deeper profiling of your sample. With using our Chromium X, it's possible to look at chromatin accessibility, perform CRISPR screens, look at single-cell gene expression, sequence T and B-cell receptor sequences, and profile cell surface protein markers all from the same single cell using our complete suite of single-cell assays. We're really excited about the instrument's ability to handle a diverse array of assay types. Additionally, as I mentioned, the range of throughput flexibility allows for researchers to perform experiments in any stage of study that they're at. For those small scale experiments where you maybe are just piloting out a new sample type and you want to see if, you know, the data that you get is interesting, for that we, the Chromium X is compatible with our Single Cell Gene Expression LT product. For those larger scale experiments where you want to, you know, test over cell types and profile your sample a bit deeper, our standard Single Cell Gene Expression solution provides throughput in the range of 500-10,000 cells per channel. Lastly, for those large scale experiments where you really need to profile your samples very deeply, our Single Cell Gene Expression HT assay allows for profiling cells, samples from 2,000-20,000 cells per channel. This ability to run the HT assays allows researchers to achieve much lower total project costs for their projects that are really high scale. In this particular example, we performed a high-throughput drug screen using our single-cell gene expression HT and our CellPlex product line. What we did here was we took a 96-well plate, which you can see here. We then loaded this 96-well plate with these non-small cell lung cancer cell lines, two different cell lines. We treated both of these different cell lines with a variety of different drugs at different time points. We pooled these different samples with our CellPlex product. From there we were able to pool all of these samples together knowing that we could do multiplex them on the bioinformatics end using our CellPlex product. We pooled all these samples together and ran them across 16 lanes of our high-throughput chip in a single high-throughput experiment run. This generated 48 simultaneous conditions, which we were able to visualize in this 3-D UMAP here. Here you can see that, the, there's, you know, a ton of data to dig into here, but just as an example, you can see how the crizotinib treated cells in particular, so these cells in blue here, have a very strong change in phenotype compared to the ponatinib, ozanimod cell treated cell line. This whole project, you know, could be quite costly using our standard kits and reagents as well as, you know, not doing targeted sequencing but doing whole transcriptome sequencing. When we combine our high-throughput kits and reagents along with our CellPlex product line and our targeted gene expression assay, which helps us cut down on sequencing costs, you can see that we're able to reduce the total cost of the project by about 70%. Which allows us to really think about scaling up experiments and open the doors to new types of experiments that can be performed. This is just another way of looking at the total drop in project costs that's achieved with our high-throughput assays. Here if you look at the overall cost per cell using our standard assay starting in 2016, the cost per cell was about $0.15 per cell. You can see how over time and the introduction of these new products we've launched, including CellPlex and HT, this cost per cell has dropped dramatically for those high-throughput experiments. That covered our most recent innovation of the Chromium X and our high-throughput assays. Next we're gonna talk a little bit about some of the new products that we have coming up in 2022. The first of these is our five' feature barcoding on our Chromium Connect. Our Chromium Connect is our automated single-cell platform, which allows you to basically load cells, load their reagents, and then run your assay with walk-away convenience. This is our five' single-cell immune profiling assay is currently available on the Chromium Connect, but we're now releasing this with compatibility for our five' feature barcoding assay as well. This will allow researchers to perform single-cell immune profiling plus gene expression with full, like, full-length paired VDJ transcripts that will also be compatible with cell surface proteins. We expect this to be launched in the middle of this year. Next, we have our five' CRISPR assay that is also being released early in the year. Our five' CRISPR assay is really cool because in addition to being able to detect gene expression as well as guide RNAs at the single-cell level, we're also able to detect multi-omic readouts in addition. Here we're able to detect cell surface protein expression as well as the expression of TCRs and BCRs, all from the same single sample using this assay. Additionally, the other nice thing about the five' CRISPR assay is that it will be off-the-shelf compatible with most existing Cas9 libraries, so it won't require additional modification or optimization or tweaking of your guides in order to get it to work. Most Cas9 libraries will just work off the shelf, which makes it very convenient to fit into your existing CRISPR screening workflows. Finally, I'm going to cover a little bit about BEAM before I turn it over to Dina. BEAM is our antigen profiling product that is built off our single-cell immune profiling solution and is expected later this year. This will be enabled in kind of two flavors. We'll have BEAM-Ab, which will be our high-throughput antibody discovery platform, as well as BEAM-T, which will be able to look at antigen-specific TCR receptor sequences. Both will be launching later this year. It allows for comprehensive surveillance of the adaptive immune system at scale. To show what kind of data this can generate, this is an example where we used BEAM to tag COVID-19 antigens with a 10x barcode. We then took blood from a recovered COVID-19 patient and labeled those cells with these tagged antigens. From there, we flow sorted out the B cells that were onto the antigen and then ran these cells on our single-cell immune profiling platform. We were able to use the feature barcode sequences on the tagged antigens to quantify the binding of these tagged antigens to our B-cell receptors. In addition to that, we were also able to capture the paired full-length B-cell receptor sequences from this data. This data generated what we call a honeycomb plot. This would be a new data type that will be available in BEAM, which allows us to visualize the strength of the binding to these different antigens. The honeycomb plot, each dot represents a single cell. Clusters of dots represent a clonotype. Here what you can see is that there are, that we're able to detect a range of binding affinity for these B-cell receptor sequences for the spike protein. Okay, with that I'll go ahead and turn it over to Dina. Thanks, Sam. Sam covered, you know, some new exciting products and capabilities that are layered on top of our immune profiling single-cell product. What I want to talk about today is an entirely new assay chemistry and a brand-new assay that really opens up, you know, new single-cell workflows. We're really excited about this assay called Fixed RNA Profiling for single cell, and this is expected in the middle of this year. Just to set this up, you know, most of our users use fresh living cells as input into the single-cell assays. This is great, but sometimes there's a lot of constraints around the time that you collect samples to the time that you can process them. Of course, you know, some cells are fragile, some cells are changing rapidly, and sometimes you need to transport your samples from the site that you collect them, you know, maybe to a core facility, a core lab, or even just to, you know, to the lab from an operating room or a blood collection site. Really when you start thinking about these larger studies that can include, you know, collecting samples from multiple centers, geographically separated or over time, really, we want to enable the use of single-cell analysis methods for these types of studies, because I think there's so much valuable information that can be gleaned from these types of data sets. On the next slide, we're excited to announce our Fixed RNA Profiling assay. This is an assay that will run exclusively on our Chromium X and iX series of instruments that Sam introduced really nicely. These are really our instruments of the future that not only enable those high-throughput assays, but also this new type of high-throughput assay for fixed samples. This assay, which I'll introduce a little bit, today, as I said, it really opens up new types of study designs and unlocks new samples. It does also really simplify the way that you can batch and multiplex samples together, which further, you know, really increases the throughput of the experiments that can be run. Additionally, as I'll show you, the design of this assay, as I said, it's a new chemistry. It will really open up a new path on our gene expression roadmap into the future. On the next slide. Thanks. It is a probe-based assay. It is a discovery tool. This does cover, you know, sort of the whole transcriptome, but it does not depend on poly-A capture of transcripts as our other gene expression assays do. In this case, we're using formaldehyde fixation to really lock in the biological state at the time of fixation. Once you fix, you know, you have freedom to store the samples, transport them, you know, wait until a convenient time to batch them or to run the experiment. Once that experiment is, you know, ready to start, it uses a probe set that is either specific to humans or mouse, and each of these will cover over 18,000 genes, human or mouse genes. Those probe pairs allow you to, you know, very sensitively detect the genes in these, formaldehyde fixed cells. You might know that fixation, you know, can cause some cross-linking. It can cause some changes to the molecules inside the cell. This is a really sensitive way to ensure that we're getting very, very good gene expression data. I'm just showing a little workflow here where the assay is also compatible with multi-omic measurements like cell surface protein measurements. In that case, you would do the staining for those cells, before the fixation. You would fix and permeabilize cells, at which point you can store them. When we release this product, we'll have lots of good data showing storage conditions and what we recommend for keeping those samples intact. Then you proceed with the Chromium workflow on the Chromium X with this brand-new chip and this brand-new chemistry. What you get out is a your gene expression library that you sequence and you can analyze. On the next slide, just to show how the data compares to one of our existing gene expression assays. Here we're showing how it correlates with our three' assay, which you might be familiar with. On the X-axis of this plot, you can see the three' v3 10x assay that was run with a fresh sample. This is breast cancer dissociated tumor cells. On the X-axis, as I said, is the fresh sample run with a three' assay. On the Y-axis is the same sample but fixed and run with a Fixed RNA assay. You can see that the correlation where each of these dots represents one gene, the correlation is very high, and the fixed assay is very sensitive. We're showing four specific genes in red there that are marking nice populations of cell clusters in this sample. You can see a range of an immune cell populations and mesenchymal cells. What you can see is that when we integrate the two data sets together, those genes that are marking those clusters are very concordantly overlaid. We're really replicating the same biological insights, even though it's an orthogonal chemistry for detection. On the next slide, I also wanted to talk about the multiplexing capability. Because we're using a probe-based assay here, you can actually take advantage of the probes themselves and include a unique barcode. We have up to 16 individual sets of barcodes that can be combined into one lane of the chip. What we're showing here is just three as an example in this picture. We're showing three tubes with the three colors representing different barcodes. What you do is you label, you know, you fix, you can store same workflow as before, where you free yourself of the constraints of needing to rush and get those samples processed quickly or drive them quickly to the core lab. Once you're ready to, you know, resume the experiment, you would hybridize with those sets of probes, and then you would pool the samples together into one lane. You can, again, run up to 16 in one single lane. Then in the final data set, you would demultiplex all the data where each transcript is labeled with a 10x barcode, tells you which cell it came from and which probe set it belongs to. You can really, you know, demultiplex all of that data and run really high throughput experiments. Of course, this also reduces the cost for example. Here's an example where we took a big PBMCs. We split it into 16 individual pools, and we ran each of those with a probe set, and then we loaded them together into one lane of a chip. This was showing 80,000 cells. That's not the maximum, but it's just what we did in this case. You can see the different clusters of immune cells that we are detecting in this PBMC lot. On the next slide, we're separating them by probe barcode. Hopefully it, you know, you can see that it's completely identical in each of those little graphs. You know, really indicating that there are no batch effects between the different barcodes. This is a really great way to increase your throughput, reduce your batch effects or your variability because you can combine, you know, samples from different time points, from different experiments and run them all on the same day. We're really excited about this product, which we feel will really unlock, you know, larger studies, more complex study designs, and really just, you know, relieve a lot of the constraints that people face with single-cell workflows today. Next, we wanna talk about ATAC v2. Really just to understand gene regulation, you really need to understand chromatin accessibility. In 2018, we introduced the single-cell ATAC assay, and this made studies of chromatin accessibility and transcription regulation in single cells possible. In the middle of this year, what we will be releasing is a version two of the single-cell ATAC workflow. As you can see here, this gives a boost in sensitivity of anywhere from 50%-75%, depending on your sample type. This also means that because of a reduced background signal, you can increase the number of peaks that you can call within your sample, which is shown on the right panel. Next slide, please. Just to recap, ATAC v2 lets you measure chromatin accessibility at single-cell resolution, same that you would be able to measure with ATAC v1. We have an improved signal-to-noise ratio with this kit. This also means that you're able to get more information compared to at the same sequencing depth compared to ATAC v1.1. If you wanted to, you could also reduce your sequencing depth and save up on that front as well. Along with the release of ATAC v2, we'll also be releasing a software update that enables you to do batch correction from V1 to V1.2, so that you can analyze them together, which is really important for customers who are doing perhaps longitudinal studies, and may want to switch in the middle of the project to really harness the increased sensitivity. Next slide, please. On this slide, you'll really see here that if we take a look at the Human Cell Atlas data portal, the majority of the data is derived from nuclei. It's about 25%. This really makes sense. You know, freezing tissue is fast, easy, and as Dina talked about, you know, there are certain constraints of working with fresh tissue. Freezing this tissue really solves some of these problems associated with transporting and storing fresh tissue. On top of that, there may be labs with boxes full of archival tissue that are not currently being accessed by single-cell analysis just due to the complex nuclei isolation workflows that are sometimes complex, low throughput and time-consuming or perhaps require additional instrumentation to remove debris and optimize for each individual tissue. Next slide, please. I'm very excited to introduce our first single-cell sample preparation product, which is the Chromium Nuclei Isolation Kit. As you can see here, the workflow is pretty simple. You take your tissue of interest, you dissociate it in a lysis buffer, pass it through a spin column, and then a debris removal buffer followed by subsequent washing steps. After your nuclei are washed, they're counted, and they're really ready to go at this stage to be loaded on any of our Chromium assays for either gene expression, chromatin accessibility, or the combined Multiome assay. Again, all you really need is an hour of lab time, a benchtop centrifuge, and an interesting frozen sample that you wanna analyze with single-cell sequencing. Next slide, please. Really quickly, just to show this, how this method compares to existing methods. Here we tested nuclei isolated from adult mouse kidney using the Chromium Nuclei Isolation Kit with a home-brewed nuclei isolation protocol. You can see here that the increase in sensitivity is up to 40%. Next slide, please. Just to quickly show you how this translates into UMIs and genes per cell, you'll see that the increase in terms of genes captured can be up to 25, 20% for this sample type. Next slide, please. Just to really put this nuclei isolation kit to the test, we wanted to try some real-life samples because we know that's what you will be doing out there in the field. Here we went ahead and isolated nuclei from eight tumors in parallel, in under one hour. What you can see here is that, you know, we have a wide range of cell types. The majority of these cell types correspond to the primary tumor cells for each of these tumors. You can also see distinct clusters that represent immune cells, including neutrophils that we can also see normal epithelial cells, endothelial, and stroma, really just showing you how this nuclei data can capture the overall tumor microenvironment. On the next slide, what you'll see is that if we just take a look at two of these samples, you can see the differences in this tumor biology and really captured by this data. For example, for these two samples, even though the fraction of B cells is very similar to each other, the breast tumor contains a higher fraction of NK cells as compared to the melanoma, which has a higher fraction of monocytes and T cells. You know, although this is just a few samples, and you definitely need more samples, and complete medical history to draw any conclusions from this data, by utilizing this kit, it's very easy to generate high-quality, high-throughput single-cell data than it has been before. Next slide, please. Again, just to recap, for the nuclei isolation kit, this is really meant to standardize nuclei isolation. There is little to no optimization needed for most of these samples. I think the most importantly is to highlight that this kit was built and optimized specifically for 10x Chromium assays, really just to give you the high level of performance that you expect from all our samples. We're really excited to see how you apply it to the amazing research that you're working with. To tie it off with, I just wanna highlight the fact that, you know, at 10x Genomics, the single-cell gene expression landscape has really evolved to the point where single-cell is sometimes the de facto standard for analyzing new sample types and approaching new biological questions. During that time, we've really continued to innovate, listening and working with you, our customers, to help tools that are needed to answer some of these really challenging biological questions. As a result of this, there's a wide range of scales, sample types, 'omics, and budgets that we have products for to make single-cell analysis more accessible for accelerating your research. Cool. All right. Well, thank you so much, Sam and Zuly and Dina, for the presentation or the updates on the single-cell. Before we move on to the spatial biology, I'd like to hear some of the feedback from the audience. We mentioned many new products including fixed RNA gene expression for clinical sample, nuclei isolation that you can use for multiple single-cell assays, higher sensitivity ATAC v2, CRISPR now we are enabling for the five' single-cell immunoprofiling solution, last but not least, we will be preparing for the BEAM. I'd like to see which products you are interested in from these nine up. This is a multi-selection, so if you have any multiple interests, then please let us know. All right. Cool. Let me stop the poll question and share the results so that we can instantly see what type of the products that you are excited about. Fixed RNA really high interest. Good to see the nuclei as well as ATAC. People are excited about it. CRISPR is coming up, and then as well as the Beam. Cool. Excellent. Thank you so much. All right, let's move on to the second session, which is about the spatial biology. Let me stop sharing. Cool. All right. With that, Jyoti, Courtney, if you can share the slide. Yeah. Give me just one second. Cool. All right. It's all yours. Thank you. Thank you so much, Mio. Thanks to the single-cell team for setting up the background for our single-cell solutions. Everyone, welcome. My name is Jyoti Sheldon. I am the product marketing manager for our on-market Visium solutions. Me and Courtney are going to go over the different Visium as well as our Xenium platform that are now available, and some of our upcoming products that will be available later this year. To get started, as the single-cell team clearly pointed out earlier that the various 10x technologies, they're really driving, you know, their discovery across multiple research areas. That's seen through our various number of publications. Now, that driving of discovery and research also holds true for Visium. We've seen over 200 Visium publications as well as preprints. These publications really from a wide range of applications, all the way from discovery to even translational research. In fact, this year we were honored to make a cover debut where Visium was featured on the cover of the Science Translational Medicine magazine, but also have been listed as one of the top 10 innovations in several articles over the last two years. We continuously aim to innovate and improve our products. To give you guys a little bit of background on what are some of the key features or key characteristics of the Visium Spatial Discovery platform. Visium Spatial Discovery allows you to do whole transcriptomic analysis in both FFPE as well as in fresh frozen tissues. It gives you that data at a higher resolution, and it allows you to do true discovery and ask those true discovery questions for your research. It is a kitted and ready-to-use solution. You also get to co-detect both protein as well as RNA or your whole transcriptome in the same tissue section. It has an efficient workflow that leads into streamlined data analysis. Because 10x as a family aims to deliver everything from single-cell to spatial, you get that world-class support. How does the Visium Discovery platform work? Now, the Visium Discovery platform really allows researchers to map their spatial gene expression data of various complex as well as heterogeneous tissues using these Visium slides that utilize poly capture as well as our novel spatial bar coding technology. Now, what you see on the screen here is that a standard Visium gene expression slide, which consists of four capture areas. Each of these capture areas consist of about 5,000 bar-coded spots, and these spots are about 55 micron in diameter. Now, within each of these spots, there are several oligonucleotides, and these oligonucleotides are made up of multiple components that allow researchers to identify their transcripts, count the number of RNA molecules, as well as really allow you to find out where those molecules are within the tissue and give you that morphological context. The Visium platform is compatible with both FFPE as well as fresh frozen samples. We launched our FFPE assay last year, and I'm very proud to announce that we just saw the release of our first FFPE publication that came out of Catherine Sautès-Fridman's lab at Cordeliers Research Centre. This is a very good publication that really demonstrates the utility of our FFPE Visium assay in revealing and resolving the heterogeneity in renal cell carcinoma. In this particular publication, the researchers used both the Visium Fresh Frozen as well as the Visium FFPE assay, and they combined data set from this spatial transcriptomic assay with bulk RNA sequencing, as well as protein imaging using immunofluorescence. With the combination of these three techniques, they studied the role of tertiary lymphoid structures, or TLS, in how they form or how they mediate B-cell maturation and how they produce immunoglobulin-producing plasma cells. Overall, how this mechanism then fuels to improve responses for patients to immune checkpoint inhibitors as well as lead to a progression-free survival. What you see on this slide is a pathologist-annotated H&E section in both FFPE as well as frozen samples, and a CA9, which is a tumor marker, really allowing them to identify tumors that were TLS positive as well as TLS negative. Once they established these two different tumor types, they used the Visium assay to really zone in and profile the gene signature for this particular tertiary lymphoid structure. After identifying those gene signatures, they focused and looked into phenotyping as well as localizing the B cells as well as plasma cells. They used robust cell type decomposition, or RCTD, along with single-cell sequencing data sets that showed subtypes of B cells from tonsil samples. They applied the clusters for those B cells to the Visium data, and they found out that primarily these memory B cells, along with plasma blasts and plasma cells, showed an increased expression in that TLS region. Now, because publications have shown that plasma cells are responsible for producing antibodies, they also looked at the gene expression profile of various immunoglobulin genes, and they saw an increased expression and a dispersed expression of IGHG1 and IGHA1. Now, after spatial transcriptomic Visium revealed colocalization of these B cells as well as the plasma cells, this suggested that there was a B cell adaptive immunity generation happening in situ. Naturally, they wanted to study the B cell receptor sequences which get mutated as a result of this immunity generation. For that also, they were able to combine both RNA sequencing data with data from Visium. With the power of Visium, they were able to reveal or identify the raw transcripts of these BCR sequences and found out that there was an increase of heavy chain clonotypes along with immunoglobulin in these tumor cells. Overall, they had a lot more findings, but in this paper, with the use of the Visium fresh frozen and the FFPE assay, the scientists revealed a mechanism by which TLS mediates the production of B cells and these immunoglobulin-producing plasma cells that then produce antibodies that have apoptotic activity and thereby help improve the response to immune checkpoint inhibitors. A very powerful paper. As excited as we are about our FFPE assay, we are even more excited about our upcoming platforms. This year alone, we are improving as well as innovating to allow researchers to get access to more samples, more analyte types, and see all your data at a higher resolution. We will be launching a CytAssist instrument as well as the larger capture area slides and the Visium Gene and Protein Expression assay in the middle of this year, and I will talk about them in a little bit of detail. Later this year, we will be launching our Visium HD assay, which Courtney will cover in the second part of the presentation. As we all know that RNA expression truly provides valuable insights into various kind of cell types, states, and even reveal their function. RNA is only part of the story. By adding protein as an additional key analyte, it allows researchers to really understand and characterize cells. An example of such a data might be identifying immune cells. These cells often have low expression or are even post-transcriptionally regulated. Really by combining analysis for both RNA and protein can enable users or researchers to get an even better understanding of their tissue architecture, the spatial architecture, and its underlying biological function. Our Visium gene and protein product will truly enable you to take a microscopy image, so an H&E or immunofluorescence image that's stained on an FFPE tissue section, and then simultaneously profile RNA and protein in that same section at a high spatial resolution. This will be an NGS-based antibody readout, and so you really get that freedom to scale to a large number of targets. Because it is NGS-based, you're not limited or constrained by things such as spectral overlap, which is very commonly seen when you use optical dyes for protein detection. How does this product work? It will use our new Visium slides along with DNA bar-coded antibodies. Now, these antibodies can be bound to specific intracellular or extracellular proteins in the tissues onto the Visium capture slide. The antibody barcodes, as well as your transcriptome-wide RNA probes, are converted into libraries in parallel and in sequence. When you do your data analysis, you take the protein and the gene expression data, and then you align it with your H&E or immunofluorescence image that you take earlier in the workflow. As I mentioned before, this will at the end give you that NGS-based readout. To really kind of demonstrate the power of this and to evaluate the performance of this assay, we work with some reference tissues that have known morphology as well as distinct expression patterns. Here, what you're seeing is where we've analyzed a tonsil section with our Visium gene and protein expression assay using a panel of 20 antibodies. The tonsil, as you know, is an immune organ that shows very clear, discernible repetitive structures, and it contains a lot of major immune cell types. As you can see from this H&E image, you clearly see those follicular regions that contain mature immune cells as well as epithelial layers. Now we wanted to add another layer, and so we looked at the protein expression. As you can see, the protein expression very clearly correlated with that morphology. We were able to nicely see those clusters align with the macroscopic structures that we saw with the H&E. The power really came in when we added another layer of RNA data, and we saw that same correlation consistent with both protein, RNA, as well as H&E. We take a look here at an example of an ovarian cancer sample, where we studied a panel of 25 antibodies. Again, it consists of both intracellular as well as extracellular markers. Now, the pathology annotations showed a very visible invasive carcinoma region, as well as some immune cells in this section. We identified two compartments of invasive carcinoma, a small invasive carcinoma and a large invasive carcinoma. Now, using our protein expression or antibody panel, we first confirmed the presence of those immune cells in the same location. Additionally, we were able to also subtype these cells based on very characteristic surface markers using our protein panel. In addition, as you can see here, we saw that the small region of carcinoma that was annotated by the pathologist, it showed a cytotoxic T cell infiltration, but the large carcinoma did not show that. To really get that multi-omic readout, we went a step further, and then we added the RNA component, and we compared the gene expression profile of the large as well as the small carcinoma region to really find out what those differences were. We also saw how they correlated to the varying immune cell infiltration that we saw in the protein data. Now, as you can clearly see here, we saw an upregulation of this HLA-G, which is an immune response gene in that small carcinoma region where we saw an increase in cytotoxic T cells, again, correlating to that antibody data. We saw an upregulation of INPG-2, which is known to be involved in tumor growth in that large carcinoma region. Really, again, highlighting the power of combining RNA and protein. Now with that, I want to move on to our next product. As we know that our 10x Spatial solutions or discovery platforms, they really combine the power of histology as well as that highplex molecular readout in the same tissue section. Oftentimes, combining the power of these two worlds can involve a lot of logistical challenges because histology labs, they may not always be equipped or even trained, to adapt to those tissue preparation workflows for Visium. NGS labs may not be comfortable with that. To truly bridge the gap between these two workflows, we will be launching our CytAssist instrument. The CytAssist instrument is a benchtop instrument that will allow users to get that expanded sample accessibility, so you can use H&E or immunofluorescence stained slides. You can also use blocks or pre-sectioned tissues on standard glass slides. It will also allow users to have simplified handling because they're not gonna need specialized training. It's going to make collaboration between organizations of course easier. Lastly, it's going to give researchers a freedom of choice, where researchers can now pre-screen their tissue sections and then align their tissue so they can focus on regions of biological significance. Taking a look at the CytAssist workflow, the CytAssist workflow is pretty comparable to the current manual workflow, where you do your sample preparation, imaging, and probe hybridization offline. Inside the instrument, you load your standard glass slides with the Visium capture slide, where the instrument will enable or facilitate permeabilization of your tissue and allow for transfer of either RNA or both RNA and protein analytes to the Visium capture slide. After which your probe extension and library construction happen offline. At launch, this product will be only compatible with our FFPE assays, but we are evaluating other assays down in our roadmap. Here's a great illustration and, data that shows you how exactly will this instrument allow you to choose and focus on those regions. We're looking here at a large embryo section and using the window on the instrument and the guides, we're able to focus either on the mouse embryo head or the mouse embryo torso, really giving you that freedom of choice. Here's where we're seeing again how we were able to precisely target those regions and see that clustering that was obtained from the remainder of the Visium workflow. Now, because CytAssist is an enabler and facilitator for our manual workflow, I just wanted to show you guys this data set that shows that this instrument and the performance has been benchmarked to our existing manual workflow, really showing that we are able to retain the sensitivity and show spatiality comparable to our manual workflow. Really, again, I wanted to highlight the power of this platform to take Visium to that extra step and giving researchers that flexibility in their Visium analysis for FFPE samples. With that, I'm gonna hand it over to Courtney, who will cover the other two topics. Thank you. Great. Thank you very much, Jyoti, and hello, everyone. It's nice to be here tonight. If we go to the next slide, I'd like to focus a little bit now on the higher resolution needs. As Jyoti mentioned earlier in the presentation, Visium has over 200 in publications and preprints. The platform has really enabled a large variety of important applications and addressed many research questions. Some of those questions really do need higher resolution, inclusive for profiling developing organs or interrogating the spatial architecture of heterogeneous tissues such as the tumor microenvironment. That's what HD will do. If we just click forward here, with the advantages of the existing Visium technology, which includes whole transcriptome profiling, the streamlined workflow, and the easy-to-use data analysis tools, HD will take all that into account, and then additional distinguishing factors behind HD will be increased spot density as well as smaller spot size. The capture features will be very densely packed, and they will be sub-10 microns in size. This is what will allow us to truly offer single-cell scale data with that spatial context. This will really provide unprecedented resolution and tissue coverage, so you can really profile those smaller tissue sections, those developing organs, again, highly heterogeneous tissues. To achieve this massive jump in resolution, we're developing a completely new slide architecture. What we show here is a mouse eye, which really helps give the feel of the scale of HD. So you can see how that resolution and expanded tissue coverage with the more compacted, spots for HD will allow precise identification of the layers within the eye and then even the cellular composition, within a single layer. On the next slide, I'd like to highlight a breast cancer section, where again, by using this very high resolution HD assay, we can really finally resolve that tumor border and also select, you know, two different regions. What we show here on the left-hand side is an invasive carcinoma, and then on the right-hand side is a ductal carcinoma in situ. Just with the way the Visium assay as a whole works, is that you get that entire tissue section coverage, not just a few arbitrary regions. You can really look at the entire tissue section and analyze any of that section in the data analysis after the experiment. The same will be true again with HD. You'll be able to profile the whole transcriptome in these entire tissue sections at that single-cell scale and with that expanded tissue coverage. We're expecting to release this later this year, and so we're really excited to provide this capability to you and to see all the new applications that it will enable. With that, just to summarize the Visium platform that Jyoti has brought, mentioned and highlighted, with Visium as a whole, with all of these new, you know, capabilities that we're gonna be unleashing, you'll be able to detect more analytes, more samples, and do this at higher resolution. As we mentioned, the gene and protein assay and CytAssist instrument will be released in the middle of this year, and HD will be released later this year. With that now, I'd like to then switch gears from Visium and then talk about our new in situ platform and some of the developments happening there. As we've already heard from the Chromium side and the Visium side, you know, these two platforms really continue to push the boundaries and the frontiers of cell and tissue research. These two platforms are ideal discovery tools. They measure the entire transcriptome of a sample, so you can identify cell type markers, cell composition, regional gene expression, again, all with an unbiased whole transcriptome approach and with a sequencing readout. With in situ, with all this information, a natural follow-up question is going to be, where are these cells exactly located? What specific combination of markers can be found in a single cell, and where is that cell located? That's really where Xenium comes in. This platform will deliver targeted gene expression information at subcellular resolution and with high sensitivity. We'll have platforms ranging from discovery that can then help fuel and feed into in situ targeted panels. On the next slide, we can highlight our new instrument. This is the Xenium In Situ Platform, and it really will take in situ analysis to a new level. With traditional in situ, you're only looking at a handful of genes. With Xenium, you'll be able to use gene panels that will comprise of hundreds of targets, and our roadmap plans to extend to a thousand plus targets in the future. This platform will also enable simultaneous profiling of both RNA and protein in the same tissue section, so you get a really much more complete picture of the biology that's happening on the tissue slide. In addition, we'll support both fresh, frozen and FFPE tissues and have the throughput capability to support large cohort studies. On the next slide here, we can show you just a quick look at how the Xenium workflow actually works. Starting with sample preparation, which includes permeabilization and hybridization of our circular DNA probes, and those probes have a gene-specific barcode. After the sample prep, the sections are then loaded onto the instrument and the tissues undergo cyclic rounds of fluorescent hybridization and imaging. This is how we can generate an optical signature for each gene, which is then used to construct a spatial map of the transcripts across the tissue section at a subcellular level. Following that, secondary analysis and visualization is all done off the instrument. Here on the next slide, we have an example of some early R&D gene expression data using Xenium on an FFPE human breast cancer section. On the left we show an H&E image. This was annotated by a pathologist, which identified invasive carcinomas surrounded by fibrous tissue, adipose tissue, as well as tumor necrosis. On the right-hand side, we have the corresponding gene expression in situ image that was generated by Xenium, looking at over 200 RNA targets. If we compare the annotated H&E section with the corresponding Xenium in situ image, we can see that there is a strong spatial correlation between the distribution of the cell types and the pathologist annotations. We also took it a step further and also compared it to our Visium assay. We wanted to look at the spatial distributions that we see with Visium as well as with Xenium. We see a very strong correlation between the spatial distribution of the cell types that we obtained and cell types and genes obtained with Visium, which was detected through NGS sequencing, and that's in the middle panel. Xenium, which was detected by microscopy with that subcellular resolution. In this particular example, we honed in on one gene, ERBB2, which encodes HER2, and we can see that this is indeed a HER2 positive breast cancer tumor. Now in addition, as I mentioned, we can also detect proteins with Xenium. We examined another breast cancer sample, and we used DNA bar-coded antibodies in addition to RNA labeling. After we finished multiple cycles of RNA decoding, we also imaged the DNA bar-coded antibodies. That allowed us, in this particular example, with a combination of antibodies, shown here on the screen, to identify cells of epithelial and mesenchymal origin. During this process, tissue morphology and antibody staining are well preserved even after several cycles of RNA decoding. Finally, I just wanted to highlight the resolution of Xenium, showing here, because of that high resolution, we can really start to zoom into specific regions of the tissue and identify key biological events such as immune infiltration into the tumor. What we show here is an H&E stain on the left, where we can see a few interesting cell types by eye. When we look at the molecular profiling, we actually can identify some rare immune cells that are in close proximity to the tumor region. This could be clinically relevant and important for development of immunotherapies in cancer research. Overall, Xenium will be a complete platform that includes a versatile instrument, consumables, panels and software, and it comes with the full support of 10x Genomics expertise, all the way from tissue prep to data analysis. The initial commercial release of our Xenium platform is expected later this year. This is just the beginning of the Xenium roadmap. Like Chromium and Visium, we'll continue to build this solid foundation with enhancements on core capabilities, adding more panels, more analytes, and a whole suite of new software tools and other features. In conclusion, the three platforms at the core of 10x Genomics's technologies are really driving research all the way from discovery to very targeted, focused research. Our Chromium platform is the ultimate single-cell analysis workflow for dissociated samples. Visium is our spatial discovery platform of choice, allowing whole transcriptome profiling of tissue sections. Xenium, our upcoming in situ platform, will provide the highest spatial resolution across many sample types, really enabling translational and ultimately clinically relevant applications with its focused approach. Thank you very much for your attention, and I will turn it over to Mio now. Thank you, Jyoti and Courtney. Just a reminder that we are actually having a separate webinar session coming up for April for some of the products. If you are interested, please scan or type this URL for the registration. We are going to the Q&A session, but before that, same with the single cell product line, I'd like to hear some audience interest on the spatial biology. We mentioned about Visium Spatial Gene and Protein Expression. Visium CytAssist, so that you can transfer the slide, FFPE slide to the Visium slide. Or high-density Visium HD. Last but not least, Xenium In Situ Platform, which is new capability outside of the next generation sequencer. Let's see how it goes. I'm getting some answers. Okay, let me finish the poll and then share the information. All right. High interest in the co-detection on gene expression and protein, which is great. Also, high interest on the Xenium platform. Thank you very much for your interest. We are going to the Q&A session. If you have any questions, please submit through the Q&A chat box. I also leave this one open. If you want to have a private discussion with us for the pricing of the products that we mentioned or some of the technical questions, just answer these and then we'll follow up with you later. Right. With that, we have a few questions for the single cell. Let's try this one. I am trying to use single cell RNA sequencing. How could I narrow down the type of single cell RNA sequencing, for example, three' gene expression or five' feature barcoding? Yeah. I can take that one. It's a great question. I think especially as we have more and more single cell gene expression assays, you know, it definitely can get a little bit trickier to narrow down and figure out exactly which one is best suited for your sample type. Actually with the release of the fixed assay, we'll be providing kind of like a, you know, some guidance, like a little flow chart that helps you decide basically, you know, which single cell assay is going to be most appropriate for the work that you're doing. You can imagine that there are a couple of factors that play into it. Species is a big one. Our fixed assay is going to be probe-based, it'll be compatible with human and mouse. If you're working with a non-human, non-mouse species, it would be better to go with three-prime or five-prime. Then also the requirements for your analytes will also be important. For example, if you want VDJ receptor sequences, in that situation, I definitely recommend going with our five-prime assay as the primary assay of choice. As I said, we'll provide more specific guidance closer to the launch of fixed. But those are just a couple of key considerations to take into account. Any 10x Genomics representative can walk you through that. Thanks, Sam. Let's go to the next question about Nuclei Isolation Kit. We need to purify nuclei by FACS when we use the Nuclei Isolation Kit? That's a really good question, and I think I'm very pleased to tell you that the answer is no. When I show you a little bit of the workflow, you'll see that, again, you're, you know, dissociating your tissue, you're passing it through the spin column. There is a debris removal buffer step that helps you get rid of some of the debris there, and there are additional washes. The combination of those three steps helps remove most of the debris present within your sample. For all the sample types that we've tried in-house, and these range from human tumors to, like, about 20 mouse tissues, we haven't had to use FACS for cleanup. The results that we get from using the kit and the protocol as is is pretty clean. If there are some debris present, these tend to be pretty small and really not impactful to the data. Thank you, Zuly. Next question is about fixed RNA. May I clarify that the fixed RNA solution is compatible with cell surface protein profiling? Would the molecular destiny of the antibody-derived tags be different from the current three-prime and five-prime solutions? Yeah, that's a good question, and I'm happy to clarify. So it will be compatible with cell surface protein, and that will be using the TotalSeq-B group of antibodies that are conjugated to, you know, an oligo that is the same group that's compatible with our three-prime gene expression products. The only thing to keep in mind is that to run cell surface protein with this assay, you will run it in a single-plex format. So in other words, one sample per lane if you want the cell surface protein. If you are interested in gene expression only, you can multiplex multiple samples per lane. Thank you. Yeah. Let's move on to the spatial questions. Could you describe pre-designed panel composition? Yes, I can take that. I think I can speak to both from the protein and the Xenium side. With both of those, the composition, we're still working on the finalization of what exactly will be in those panels. What we do to take into account, particularly for the Xenium platform, is, you know, leveraging what's in the literature, what we know are key targets or proteins, that are related for cell typing, cell markers. Also taking into account, you know, the discoveries that we're learning, again, from techniques like Chromium and Visium and those discovery applications to fuel the panel development. Then also taking into account researchers and what their needs and markers are. We would also love to hear from you and you know, what you would also like to see in the panel as well. Thanks, Courtney. Let's go to the CytAssist question. Can you use IHC-stained sample with CytAssist? Yeah, I can answer that one. At the moment, CytAssist will only be compatible with either H&E or immunofluorescence stained samples, primarily because IHC staining can be quite aggressive on the tissue and can, you know, damage RNA quality. It will only be compatible with H&E or immunofluorescence, not IHC or DAPI staining. Thanks, Jyoti. We have one question on the Xenium. Will Xenium be compatible with FFPE samples? Yes, it will. Both FFPE and fresh frozen samples. Going back to the Visium Spatial Gene and Protein Expression, how many protein targets will you be able to look at? Okay, let's see. Again, as I mentioned earlier with the panel, we're still really finalizing the panel, and we'll release more information closer to launch. For now we've tested dozens of markers. Jyoti showed earlier panels of 25 proteins, but we've tested even more than that. Again, we're still finalizing the final content, but it will be dozens of markers in that final panel. Thanks, Courtney. Let's take the last question. Going back to the Chromium Nuclei Isolation Kit, is it compatible with all the Chromium assays, including high-throughput? You can take the nuclei isolated using the Chromium Nuclei Isolation Kit and put them into any of the single cell gene expression assays. I think one of the things about this kit is you can process a bunch of samples in parallel. You can process up to eight in an hour, and this makes higher throughput experiments utilizing some of the HT capability possible. Great. Thank you very much. I think we covered most of the question here. Sorry that we are 10 minutes late for the finishing time, but thank you very much for all the speakers for the update. Thank you everyone for great questions. The recording of this webinar will be available next week. With that, I'd like to finish the session. Thank you very much and see you next time.