Kristin ARDLIE (keynote) Director
Broad Institute of MIT & Harvard
Dr. Ardlie studies the genetic regulation of gene expression. She lead the Genotype Tissue Expression (GTEx) Project's, Laboratory, Data Analysis, and Coordinating Center, producing and analyzing a resource of ~20,000 RNA-sequenced tissues from 960 whole genome sequenced human donors. Recently she has been working on single cell projects in the context of GTEx, including technical methods development for snRNA-seq, the development of open access consent documents, and extension of the GTEx pipeline for the enrollment of new donors for single cell project efforts. Kristin received a PhD from Princeton University in 1995, completed a fellowship with the Harvard Society of Fellows, and worked at the Whitehead Institute/MIT Center for Genome Research. She spent 6 years as VP of Genetics at Genomics Collaborative Inc. She is currently at the Broad Institute.
Leveraging Lessons from the GTEx Project for the HCA
The Genotype-Tissue Expression (GTEx) project was established to characterize and interpret the function of genetic effects on the transcriptome across human tissues, and to link regulatory mechanisms to trait and disease associations. The project goals included collecting biospecimens from ~50 tissues from up to ~1000 postmortem donors, creating standards and protocols for optimizing postmortem tissue collection, processing and donor recruitment, and for data sharing. Our analyses of the v8 data release, which contains 17,382 RNA-seq samples, reveal that regulatory associations are found for almost all genes, and provide insights into the population and tissue-specificity of genetic effects. Importantly, we also show that cell type composition is a key factor in understanding gene regulatory mechanisms, and that we now need to investigate genetic regulatory effects at the cellular level, to study additional tissues and developmental time points, and to continue investment in increasing sample sizes from diverse populations.
Piero CARNINCI Deputy Director
RIKEN Center for Integrative Medical Sciences
Born and educated in Italy, Dr Carninci obtained his doctoral degree at the University of Trieste in 1989. From 1990 to 1995, he developed technologies for DNA extraction and DNA sequencing at Talent, a spin-off biotech. Dr Carninci moved to Japan in 1995 at RIKEN and became tenure researcher in 1997. He has developed a series of technologies to capture full-length cDNAs and the CAGE, which have been broadly used in the RIKEN FANTOM projects. It allowed identifying non-coding RNAs as the major output of the mammalian genome and provided comprehensive maps of the mammalian promoters. Between 2008 and 2013, Dr Carninci was a Team and Unit Leaders and a Deputy Project Director at the RIKEN Omics Science Center. From April 2013 to March 2018, he was Director of the Division Genomics Technologies and Deputy Director of the RIKEN Center for Life Science Technologies. Subsequently, he became Deputy Director of the RIKEN Center for Integrative Medical Sciences in April 2018. Dr Carninci is currently focusing on investigating the functions of lncRNAs (FANTOM6) and Human Cell Atlas. Also, he has been exploring the mechanisms of SINEUPs, antisense lncRNAs which upregulate targeted protein translation. He has published more than 320 papers and book chapters, edited books and is a member of editorial boards of various scientific journals.
Single Cell Transcriptomics in Ageing Populations
Global ageing raises a major social challenge, how does people remain independent and active as they age? Supercentenarians, who have reached the age of 110 or more, are good models of healthy ageing. In order to explore the keys of their healthy ageing, we performed single cell transcriptome analysis over 61,202 peripheral blood mononuclear cells (PBMCs) derived from seven supercentenarians and five younger controls. The results showed an increase in cytotoxic CD4 T-cells (CD4 CTLs) and reduction in B-cells in the supercentenarians. Furthermore, single cell sequencing of T-cell receptor derived from two supercentenarians revealed that the CD4 CTLs had accumulated through massive clonal expansion. The CD4 CTLs exhibited heterogeneity in their degree of cytotoxicity as well as a nearly identical transcriptome to that of CD8 CTLs, indicating that CD4 CTLs utilize the transcriptional program of the CD8 lineage while retaining CD4 expression. These unique characteristics of immune system in supercentenarians may be involved in their longevity.
Jonah COOL Science Program Officer
Chan Zuckerberg Initiative (CZI) Program Lead
Human Cell Atlas
Dr Jonah Cool is a cell biologist and geneticist by training, and is currently a Science Program Officer at the Chan Zuckerberg Initiative, where he leads the organization's efforts to support the international Human Cell Atlas consortium. He was an American Heart Association fellow while completing his PhD at Duke Medical Center, with a focus on the role of vascularization during cell differentiation and organ morphogenesis, and was subsequently a Ruth Kirchstein Fellow at the Salk Institute studying nuclear organization during stem cell differentiation. Dr Cool previously worked in intellectual property litigation, as well as ran an industry research group working toward therapeutic application of 3D bio-printed human tissue. He has a deep love of cell biology and, in particular, the origins of cellular heterogeneity and how diverse cells assemble into complex tissues.
Chan Zuckerberg Initiative: Support of the Human Cell Atlas
The Chan Zuckerberg Initiative is an active supporter of the Human Cell Atlas. To date, there have been three grant programs as well as support for the development of the Data Coordination Platform, a central platform to help the HCA community contribute and access data in an accessible and centralised way. In addition to CZI's external support and collaboration, we are also actively developing various tools that are aimed at supporting analysis and exploration of diverse types of single cell data. This talk will cover CZI's historical support for the HCA, as well as future programs and development of open source analysis tools.
Alistair FORREST Head
Systems Biology and Genomics Lab
The Harry Perkins Institute of Medical Research Professor
University of Western Australia
Professor Alistair Forrest is head of the Systems Biology and Genomics Lab at the Harry Perkins Institute of Medical Research, and a professor at the University of Western Australia. He is an expert in transcriptomics and as scientific coordinator (FANTOM5 led the international consortium to global maps of human promoters, enhancers, microRNAs and long non-coding RNAs using Cap Analysis of Gene Expression and RNA-seq). Professor Forrest is currently leading the Cancer Research Trust funded Western Australian cancer single cell consortium. He also uses the 10x genomics system to study the cellular composition of tumors. His lab benchmarks dissociation conditions for solid tissues and develops new computational tools for interpreting this data, including tools for cell annotation and predicting cell-to-cell interactions.
Systematic Bias Assessment in Solid Tissue 10x scRNA-seq Workflows
Single-cell and single-nucleus RNA sequencing have been widely adopted in studies of heterogeneous tissues to estimate their cell composition and obtain transcriptional profiles of individual cells. However, the current fragmentary understanding of artefacts introduced by sample preparation protocols impedes selection of optimal workflows and can compromise data interpretation. To bridge this gap, we compared performance of several workflows applied to adult mouse kidneys. Our study encompasses two tissue dissociation protocols, two cell preservation methods, bulk tissue RNA sequencing, single-cell and three single-nucleus RNA sequencing workflows for the 10x Genomics Chromium platform. These experiments enable a systematic comparison of recovered cell types and their transcriptional profiles across the workflows and highlight protocol-specific biases important for the experimental design and data analysis.
Florent GINHOUX Senior Principal Investigator
Florent Ginhoux’s Lab
Singapore Immunology Network (SIgN)
Singapore Adjunct Professor
Translational Immunology Institute, SingHealth and Duke-NUS
Singapore Adjunct Visiting Professor
Shanghai Immunology Institute, Jiao Tong University
Florent Ginhoux graduated in Biochemistry from the University Pierre et Marie CURIE, Paris VI and obtained a Masters degree in Advanced Studies in Immunology from the Pasteur Institute, Paris. He then started his PhD in the Immunology Team of GENETHON, Evry and obtained his PhD in 2004 from the University Pierre et Marie CURIE, Paris VI. As a postdoctoral fellow, Florent Ginhoux joined the Laboratory of Miriam Merad in the Mount Sinai School of Medicine (MSSM), New York where he studied the ontogeny and the homeostasis of cutaneous dendritic cell populations, with a strong focus on Langerhans cells and Microglia. In 2008, he became an Assistant Professor in the Department of Gene and Cell Medicine, MSSM and member of the Immunology Institute of MSSM. He joined the Singapore Immunology Network (SIgN), A*STAR in May 2009 as a Principal Investigator. He joined the EMBO Young Investigator (YIP) program in 2013 and is a Web of Science Highly Cited Researcher since 2016. He is also an Adjunct Visiting Associate Professor in the Shanghai Immunology Institute, Jiao Tong University, in Shanghai, China since 2015. Both laboratories are focusing on the ontogeny and differentiation of macrophages and dendritic cells (DCs).
Macrophage and Dendritic Cell Biology: From Development to Functions
Macrophages, monocytes, and dendritic cells play crucial and distinct roles in tissue homeostasis and immunity, but also contribute to a broad spectrum of pathologies and are thus attractive therapeutic targets. Potential intervention strategies aiming at manipulation of these cells will require in-depth insights of their origins and the mechanisms that govern their homeostasis and activation. Our approach encompasses the integration of high dimensional platforms such as RNAseq, single cell transcriptome analysis and deep immunophenotypic assessment using state of the art 25 parameters flow cytometry or Cytometry by Time-Of-Flight mass spectrometry (CyTOF). Such high density molecular profiling at the single level and at unprecedented dimensionality and complexity will provide new insights in the biology of DC, monocyte and macrophage cell populations. Defining macrophage and DC populations on the criteria of their origin may aid our understanding of their discrete roles in tissue immunity and homeostasis, as ontogeny of DC and macrophage subsets likely underlie their functional specializations.
Isaac GOH Research Assistant
Issac Goh is a biologist by training and is currently undertaking bioinformatic analysis of the human development cell atlas datasets. Issac is currently employed as a research assistant in the Haniffa lab, Newcastle University. He is also actively involved in developing interactive bio-informatic tools to support the analysis and exploration of complex single cell data. Issac trained in Bio-engineering at the Singapore Polytechnic and later completed a Bsc in Biomedical sciences at Newcastle University where he worked in the development of alginate and bacterial derived protein-based hydrogel substrates for use in the first 3D bio-printed human corneas. He was also previously a professional operative in the Singaporean Air-force. Issac is interested in the complexity of tissue assembly during development and the changes in the cellular landscape during this process.
The Human Development Cell Atlas: A case study into Decoding human fetal liver haematopoiesis
During human fetal development, regulated differentiation programmes ensure the generation of a comprehensive repertoire of cells bearing specialised functions and tissue specific spatiotemporal localisations, many of which remain poorly defined. The Human Developmental Cell Atlas (HDCA) aims to generate a comprehensive profile of the cell types and states present during development. Studying the changing cellular landscape during development will be invaluable for the understanding of congenital and childhood disorders. In addition, the study will provide insight into the development programmes exploited by malignant cells in tumorigenesis, thereby advancing cancer research. In the UK, the Wellcome Sanger Institute and Newcastle University are partnering with the Wellcome Trust- and MRC- funded Human Developmental Biological Resource (HDBR) to achieve the goals of the HDCA. Using the recent publication “Decoding human fetal liver haematopoiesis” which analysed approximately 140,000 liver and 74,000 skin, kidney and yolk sac cells as an example, this talk aims to outline the pipeline of collaborative efforts, focused on generating a Human Developmental Cell Atlas. Furthermore, the talk will also discuss efforts to increase the equitability of data analysis, exploration and accessibility through the development of data portals. These portals seek to arm biologists with intuitive tools by which they may analyse and explore complex single cell data without the requirement of coding skills.
GUO Guoji Deputy Director
Center for Stem Cell and Regenerative Medicine
Zhejiang University School of Medicine
Dr Guoji Guo is the deputy director of Center for Stem Cell and Regenerative Medicine at Zhejiang University School of Medicine. He is also the deputy chair of Stem Cell Society at Zhejiang University. He obtained his Ph.D at National University of Singapore in 2005, and then moved to Harvard Medical School for postdoc training. In 2014, he was recruited and directly tenured at Zhejiang University. In 2017, he was awarded the National Science Fund for Excellent Young Scholars. Dr. Guoji Guo is interested in developing new single cell analysis technologies and applying these technologies to study stem cell self-renewal.
A Human Cell Landscape for Cell Type Identification at the Single-Cell Level
The transcriptome of a cell represents its unique cell type identity. However, a systematic single-cell atlas has not been achieved for human beings. We used single-cell RNA sequencing to determine the cell type composition of all major human organs and construct a basic scheme for the human cell landscape (HCL). We reveal a single-cell hierarchy for many tissues that have not been well characterized previously. We present a "single-cell HCL analysis'' pipeline that helps to define human cell types and exemplify its utility in stem cell biology. Finally, we perform single-cell comparative analysis of the human and mouse cell landscapes to reveal the conserved genetic networks in the mammalian system.
HWANG Daehee Professor in Department of Biological Sciences at Seoul National University
Department of Biological Sciences
Seoul National University
Republic of Korea
During Ph.D. study at MIT, he developed bioinformatic tools for integrative analyses of gene expression and metabolomic data. In 2003, he started his postdoctoral career at ISB and developed a data integration tool, Pointillist; proteomic data analysis tools, MS-BID and Prequips; a systems approach to prion disease; and a prion disease database. In 2006, he joined POSTECH in Korea and had developed systems approaches for understanding complex human diseases and proteomic approaches for identifying protein tissue/serum biomarkers for complex human diseases. In 2010, he became the director of System Biodynamics-National Core Research Center (NCRC). He developed tools for understanding spatiotemporal operations of biological networks. In 2013, he moved to DGIST in Korea and had worked on proteogenomic analyses of human cancers. In 2019, he moved to Seoul National University and have been developing systems approaches for network-based big proteomic data analysis and precision medicine.
Single cell multiomics analysis
A number of studies have demonstrted the value of multiomics analysis of bulk tissue samples, such as proteogenomics and genomic-epigenomic analysis. Recently, various technologies for mutiomics analysis at the single cell level have been introduced. They are being applied to diverse biological systems in order to investigate key molecular mechanisms defined by multiple layers of regulatory components under biological or pathological conditions. In this year, National Research Foundation (NRF) in Korean ministry of science and ICT have launched research projects for single cell multiomics analysis that aims to identify molecular mechanisms underlying the pathogenesis of lung cancer and severe asthma. In this talk, I will present the overview of three single cell multiomics projects funded by the Korean NRF and also summarize the single cell analysis projects to be funded next year.
KIM Seon-Young Principal Investigator
Medical Genomics Research Centre
Korea Research Institute of Bioscience and Biotechnology (KRIBB)
Dr Kim Seon-Young received his PhD in microbiology from Seoul National University. He then worked at KRIBB and Columbia University as a post-doc research studying molecular virology. After returning to KRIBB at 2005, he turned his research interests into bioinformatics, genomics, and epigenomics. He developed several tools to facilitate the interpretation of omics data and a few web databases for biologists. He now leads a local genome project aiming to sequence about 6,000 Korean genomes, and is trying to establish a single cell genomics program at KRIBB to contribute to HCA and HCA-Asia consortia.
Transcriptomic Profiling of Stomach Organoids Derived from Gastric Corpus Using Single Cell RNA-Seq
Several studies have reported the patterns of gene expression dynamics in stomach tissues development and differentiation by bulk tissue RNA-seq. However, those studies are limited as the individual changes of each cell are not revealed. Here we applied single cell RNA-seq (scRNA-seq) using Chromium's 10x platform to identify the transcriptomes of individual stomach organoid cells derived from ESD tissue of a patient with gastric cancer. First, we generated gene expression data of 5,084 individual stomach organoid cells. Interestingly, cells were separated into nine distinct clusters corresponding to each of the four differentiation stages. By using maturation-specific gene markers, we identified the early stage (isthmus stem cells) and the late stage stomach cells showing bidirectional differentiation patterns toward chief cell and gastric surface/pit cell. Second, we compared our data with stomach embryo scRNA-seq data from public database (GSE95630); both data showed similar patterns of gene expression each developmental stages. Especially, the later stage specific genes (such as PGC, GKN1, and TFF1) and early stage genes (ASPM, β-catenin) showed similar expression changes in organoids and embryos, respectively. In conclusion, single-cell RNA-seq approach revealed that our stomach organoids are composed of heterogeneous cell populations, and have similar expression profiles to stomach samples.
LEE Hae-Ock Chief Researcher
Samsung Genome Institute, Samsung Medical Center Research Professor
My research interests lie in understanding of cancer and development of better therapeutic strategies. With background training in immunology and cancer cell biology, I saw the great opportunity of using single cell genomics in cancer to delineate molecular signatures in cancer cells and cellular components in cancer tissues. As many anti-cancer drugs target non-cancer components such as extracellular matrix, vasculature and immune cells, understanding the association and interaction of diverse cellular components became particularly important in cancer research. Starting from the massively parallel RNA sequencing, my research group produces and explores the genetic, epigenetic, transcriptomic and proteomic data from cancer samples at single cell resolution. Based on the findings, we pursue developing prognostic and therapeutic tools in collaboration with clinicians.
Molecular and Cellular Reprogramming of Cancer During the Disease Progression
Tumor tissues are comprised of numerous cell types including tumor cells and many stromal and immune cells controlling tumor growth. This intra-tumoral heterogeneity can be estimated by high-throughput single-cell RNA sequencing, and hence examined for specific molecular and cellular modules contributing to tumor progression. In particular, advanced metastatic cancer poses the utmost clinical challenges, and may present molecular and cellular features distinct from the early stage cancer. Here, we provide single cell transcriptome profiling for metastatic lung adenocarcinoma, the most prevalent histologic type of lung cancer diagnosed at stage IV in over 40% cases. Of the 208,506 cells from 44 lung adenocarcinomas including normal lung encompassing localized to metastatic disease, we found a cancer cell subtype deviating from the normal differentiation trajectory and dominating in the metastatic stage. In parallel, normal resident stromal and immune populations were gradually replaced with myofibroblasts and newly recruited innate and adaptive immune cells. This extensive single-cell analysis enhances our understanding of molecular and cellular dynamics in metastatic lung cancer.
Jonathan LOH Senior Principal Investigator
Institute of Molecular and Cell Biology (IMCB)
Jonathan is a Senior Principal Investigator at the Institute of Molecular and Cell Biology where he also serves as the Programme Coordinator for the Stem cell, Regenerative Medicine and Ageing research. Concurrently, he is an Associate Professor (Adjunct) at the NUS School of Medicine, NUS Faculty of Science, as well as the NUS Graduate School of Integrative Sciences and Engineering. His laboratory is interested in dissecting the mechanisms regulating cell fate changes, and developing novel tools for the use of stem cells in clinical cell based therapies. His research work has earned him several accolades including the Singapore National Academy of Science Young Scientist Award, Singapore Youth Award, MIT TR35 Asia Pacific Award, Stem Cell Society Singapore Outstanding Investigator Award and the National Research Foundation Investigatorship Award. He serves on both the International and the Education Committee of the International Society for Stem Cell Research and the Executive Committee of the Stem Cell Society Singapore.
Parallel Bimodal Single-cell Sequencing of Transcriptome and Chromatin Accessibility
We developed ASTAR-Seq (Assay for Single-cell Transcriptome and Accessibility Regions) integrated with automated microfluidic chips, which allows for parallel sequencing of transcriptome and chromatin accessibility within the same single-cell. Using ASTAR-Seq, we profiled mESCs cultured in serum+LIF and 2i medium, human cell lines including BJ, K562, JK1, and Jurkat, and primary cells undergoing erythroblast differentiation. Integrative analysis using Coupled NMF identified the distinct subpopulations and uncovered sets of regulatory regions and the respective target genes determining their distinctions. Analysis of epigenetic regulomes further unravelled the key transcription factors responsible for the heterogeneity observed.
MINODA Aki Unit Leader
Epigenome Technology Exploration Unit
Minoda Aki is a Unit Leader of Epigenome Technology Exploration Unit at RIKEN Center for Integrative Medical Sciences in Yokohama, Japan. She earned her Bachelor of Science in Microbiology at University College, London, UK in 2000, and received her PhD training at Cancer Research UK under the guidance of Dr. Takashi Toda, which led to her PhD degree in Cell Biology from University College, London in 2005. In her thesis work, she characterised a fission yeast mutant that is a subunit of several chromatin remodeling complexes.
She then moved to Berkeley, California, USA, to receive her postdoctoral training under the guidance of Dr. Gary Karpen at Lawrence Berkeley National Laboratory, where her main project was generating ChIP-chip/seq datasets for the Fly Chromatin modENCODE project, which was led by Dr. Karpen. In addition to generating datasets, she also played a large role in managing the modENCODE project, which was a joint effort between four wet labs and one bioinformatics lab. In 2013, she accepted the Unit Leader position at RIKEN where she has been since. In her lab, she is developing a novel epigenome technology that enables mapping of multiple histone modifications simultaneously at the singe nucleosome level. More recently, her lab started to work on understanding changes that take place during ageing by utilising single cell genomics technologies such as single cell RNA-seq and single cell ATAC-seq on mouse tissues.
Capturing Immunosenescence of the Innate Immune System at the Single Cell Resolution
Progressive immune dysfunction with age, termed immunosenescence, is a major contributing factor towards morbidity and mortality of the elderly, and a major target for slowing down aging. Immunosenescence is observed with the well-studied adaptive immunity. However, occurrence of immunosenescence with the innate immunity is understudied in comparison. Tissue-resident ILC2s (group 2 innate lymphoid cells) play a central role in orchestrating the type 2 innate inflammation response to parasite infections and tissue repair, and are also known to play a role in pathogenesis of allergies such as asthma. To determine whether immunosenescence occurs with the type 2 innate immune system, ILC2 was activated at different ages (8 weeks to 80 weeks old mice) by IL-33, and carried out single cell RNA-seq analysis of the lung. Our preliminary analysis suggests we have captured immunosenescence of the type 2 innate immune response at the molecular level for multiple immune and non-immine cells. I report here these findings.
Shyam PRABHAKAR Associate Director
Integrated Genomics Senior Group Leader
Computational and Systems Biology
Genome Institute of Singapore (GIS)
Shyam Prabhakar obtained a B.Tech in Electronics and Communications Engineering from IIT, Madras and a PhD in Applied Physics from Stanford University. He was sole recipient of the American Physical Society thesis award for Beam Physics in 2001. As a postdoctoral fellow under Eddy Rubin at Lawrence Berkeley National Laboratory, he discovered and characterized the first known human-specific developmental enhancer. His group uses ChIP-seq and single-cell omics to uncover molecular mechanisms and markers of human diseases, and develops new algorithms as needed. Major achievements include the first single-cell transcriptomic analysis of colorectal cancer, the first histone acetylome-wide association study of a psychiatric disorder and the first general-purpose peak detection algorithm for omics profiles. Dr Prabhakar is currently Associate Director of Integrative Genomics and Head of the Single Cell Omics Centre at the Genome Institute of Singapore. He also leads genome analytics for Singapore’s National Precision Medicine Program.
Robust, Scalable Algorithms for scRNA-seq and scATAC-seq
Single-cell RNA-seq (scRNA-seq) is the method of choice for characterizing cellular heterogeneity. However, data analysis is still a challenge – existing methods are highly sensitive to parameter settings and batch effects, and most do not scale easily to large datasets. By analogy to the explicit semantic analysis method used in natural language processing, we recently introduced Reference Component Analysis (RCA), an algorithm that clusters single cells by projecting them onto bulk-transcriptome reference panels. RCA robustly identifies common and rare cell types in scRNA-seq data, despite profound batch effects and technical variation. We have now extended the RCA reference panel to additional cell types and accelerated the code 50-fold, so that moderate-sized datasets can be clustered in 15 seconds on the average laptop computer. RCA provides a robust, accurate strategy for quickly identifying cell types in single cell data.
Feature selection (marker gene selection) substantially improves clustering accuracy. However, the performance of existing feature selection methods is highly inconsistent across benchmark single cell datasets. We therefore developed a feature selection algorithm based on gene-gene correlations and a novel measure of spatial inhomogeneity, termed the Compactness Index (CI). Our algorithm, Discovering Underlying Basis vectors using Stepwise Regression (DUBStepR), substantially outperformed existing single-cell feature selection methods, despite selecting a relatively small number of genes (100-400). Importantly, DUBStepR also works well on scATAC-seq data, which are too sparse for conventional feature selection methods.
Overall, our methods are broadly applicable and they increase the speed, accuracy and parameter-insensitivity of single cell analysis, thus facilitating generation of cell atlases and identification of disease mechanisms.
Ankur SHARMA National Medical Research Council (NMRC) Young Investigator Research Associate
Cancer Therapeutics & Stratified Oncology
Genome Institute of Singapore
Ankur Sharma is a NMRC Young Investigator and Research Associate at Genome Institute of Singapore. He obtained his PhD from the Indian Institute of Science, Bangalore. He joined GIS in 2015 and is one of the earlier adoptor of single-cell genomics to understand the impact of various selection pressures (chemotherapy/immunotherapy) on evolution and ecosystem of tumours. Major achievements include identification of drug-induced infidelity in stem-cell hierarchy and its implication in transdifferentiation, building comprehensive atlas of hepatocellular carcinoma (HCC) and Breast cancer. He is also member of multidisciplinary HCA team to build the liver atlas from development to disease. He has received Best PhD thesis award in 2014, GIS-clinical partnership award in 2019 and Conquer Cancer The ASCO Foundation Merit Award 2019.
Single Cell Atlas of Human Hepatocellular Carcinoma
Tumors reside and evolve in a complex ecosystem of immune and non-immune stromal cells. We are employing multi-sectoral single-cell RNA-seq to catalogue intra-tumor heterogeneity in human hepatocellular carcinoma (HCC). We have generated single-cell atlas form >100,000 cells from fifteen individual samples, each consisting of 2-5 tumor and matched adjacent normal sectors. In total, we profiled 57 individual tumor and normal sectors consisting of HBV+ and HBV- HCC. We also compared various cryopreservation technologies to understand the impact on cellular recovery. In total we identified >70 distinct cells-states in HCC including novel, previously uncharacterised subpopulations. Most importantly, we consistently observed a marked heterogeneity in tumor infiltrating immune cells suggesting a dynamic tumor-TME interactions. Taken together this resource provides unprecedented insights into biology of liver cancer and paves the way for patient stratification.
Jay SHIN Team Leader
RIKEN Center for Integrative Medical Sciences (IMS)
Dr Jay W. Shin acquired his PhD at ETH Zurich, Switzerland after his bachelors in computer informatics in Boston College and research training at Harvard Medical School (HMS) Boston, USA. During this period, Jay investigated Transcriptional Regulatory Network controlling tumor angiogenesis. In 2008, Jay continued his research at RIKEN, Japan with a Special Postdoctoral Fellowship. Now, as a team leader, Jay is co-leading two international consortiums: FANTOM6, investigating the functional role of long non-coding RNAs, and the Human Cell Atlas, building the atlas of the human body at the single cell resolution. Jay enjoys developing new technologies and building functional genomics platforms to decipher the molecular mechanisms involved in cellular plasticity and disease.
Building Towards Human Promoter and Enhancer Atlas at the Single Cell Resolution
Our lab focuses on the development of single cell RNA-seq at the 5'-end of transcripts in order to profile the transcriptome and epigenome landscape of human cells at the same time. In particular, we are using iPSC-derived cerebral organoids in conjunction with gene-targeting techniques to unravel the gene regulatory processes of neuronal development, regenerative medicine and neurodegeneration. We established iPSC-derived cerebral organoids and profiled promoter and enhancer activities at the single cell resolution. We can recapitulate the complexity of the human brain through identification of TH+ dopaminergic, vGLUT1+ glutamatergic neurons and GFAP+ astrocytes after 80 days of culture. Based on single cell differential gene analysis, we identified master regulators controlling neuronal subtype specification together with key regulatory enhancers associated in genetic disorders of the brain. Moving the single-cell CAGE platform forward, the lab is also engaging with medical and research communities in Japan to build the Human Cell Atlas (HCA) at single cell- and spatial-resolution. This 'periodic table' of human cells will provide a navigation map to reproducibly study diseases and to accelerate drug discovery, bringing a positive impact to our society.
Alex SWARBRICK Laboratory Head
Garvan Institute of Medical Research Co-Lead
Breast Translational Oncology Program
Kinghorn Cancer Centre Conjoint Associate Professor
Faculty of Medicine,
University of New South Wales Senior Research Fellow
National Health and Medical Research Council
Alex is an Associate Professor of Medicine at UNSW Sydney, Laboratory Head in the Garvan Institute of Medical Research, NHMRC Senior Research Fellow and co-head of the Breast Translational Oncology Program in the Kinghorn Cancer Center, Sydney. Alex completed his PhD at UNSW, followed by a postdoctoral fellowship with Nobel Laureate J. Michael Bishop at UCSF. Alex applies cell and molecular biology, animal models of disease and single cell genomics to find new treatment strategies for breast and prostate cancer.
Multidimensional Single Cell Analysis of the Tumour Microenvironment
Solid cancers are a complex 'ecosystem' of diverse cell types, whose heterotypic interactions play central roles in defining the aetiology of disease and its response to therapy. We used a multi-dimensional single cell genomics approach to characterise the tumour microenvironment in a unique cohort of early breast cancers. We have developed a single cell atlas of more than 200,000 cells collected from 28 patients with early breast cancer.
Malignant cells showed remarkable intra-tumoural heterogeneity for canonical breast cancer features, such as intrinsic subtype, hormone receptor expression and transcriptional drivers. By integrating with the Nanostring DSP platform for spatial RNA profiling, we identify signatures to distinguish malignant cell clusters from benign and morphologically normal epithelial cells.
Cancer Associated Fibroblasts (CAFs) were found in at least two states: a myofibroblast-like subset and an inflammatory-mediator subset. We show distinct transcriptional regulation and cellular function for these subsets.
We applied CITE-Seq to measure >150 cell surface immune markers and checkpoint proteins simultaneous to RNA-Sequencing. We resolve the tumour-immune milieu with high precision and generate new transcriptional signatures of breast tumour-infiltrating leukocytes.
To track lymphocyte clonal dynamics through space and time, we developed a novel method (RAGE-Seq) to permit simultaneous full-length lymphocyte receptor- and short-read RNA-sequencing at single cell resolution. We observe clonal expansion and trafficking of CD4+ and CD8+ T lymphocytes between the lymph nodes, blood and tumor of patients.
This data provides extensive insights into the cellular landscape of breast cancer and will reveal new biomarkers and opportunities for stromal- and immune-based therapy.
Angela WU Assistant Professor
Division of Life Science and Department of Chemical and Biological Engineering
Hong Kong University of Science and Technology
Angela Ruohao Wu is an assistant professor in the Division of Life Science and the Department of Chemical and Biological Engineering at The Hong Kong University of Science and Technology. Angela obtained her B.S. in Bioengineering from the University of California, Berkeley, her M.S. and Ph.D. degrees in Bioengineering from Stanford University, and her post-doctoral work also at Stanford University. In 2015, Angela co-founded Agenovir Corporation, a CRISPR-based therapeutics company targeting infectious diseases for a complete cure. Her research group is passionate about the development of new technologies at the interface of basic biology and engineering, and using these interdisciplinary approaches to investigate biological mechanisms and human diseases. As recognition of her achievements in technology and innovation, Angela was named one of MIT Technology Review Innovators under 35 Asia in 2016, and a World Economic Forum Young Scientist in 2018.
Single-Cell Transcriptomic Dissection of Cell Fate Determining Molecular Switches in Mouse Pax7-Expressing Somitic Mesoderm
Pax7-expressing progenitor cells in the somitic mesoderm are known to differentiate into multiple lineages, such as brown adipose tissue, dorsal dermis, as well as muscle in the dorsal trunk and the diaphragm; however, the precise molecular characteristics of the cellular intermediates, as well as key molecular switches that determine and control the process of lineage commitment and cell fate are not well understood. To probe the mechanisms behind this process, we dissected transgenic mouse embryos wherein the cellular descendants of Pax7-expressing progenitors are YFP-labelled, and subject these YFP-expressing Pax7-descendents to single-cell RNA profiling. We observed that a subpopulation of cells differentiates into the myogenic lineage, showing Myf5 expression as early as E12.5, whereas the rest of the population is fibroblast-like and has high collagen expression. This fibroblast-like population appears to be the early stage of the adipocyte and dermal lineages. Cells at E14.5 have distinct myogenic populations that express Myod1 and Myog; we also identified other populations with Ebf2 or Twist2 expression which could belong to brown adipose and dermal lineage respectively. One subpopulations of cells at E16.5 show a marked increase in expression of distinct brown adipose tissue markers; while another subpopulation maintains expression of dermal markers. Importantly, we identified novel surface markers for the dermal and BAT intermediate subpopulations that allowed us to sort and culture these cells in-vitro. This discovery will enable further functional evaluation of these newly identified cell types.
Seyhan YAZAR Senior Research Officer
Garvan Institute for Medical Research
Dr Yazar is an early career researcher with a wide range of experience including biostatistics, genetics, epidemiology and bioinformatics. She studied Medical Sciences at the University of New South Wales and completed a Masters of Orthoptics at the University of Sydney. During her postdoctoral training she investigated genetic and environmental influences in common complex eye diseases and associated ocular traits through exploring data from population-based studies. She was awarded her PhD from University of Western Australia in February 2016. Dr Yazar was awarded a CJ Martin Early Career Fellowship from NHMRC in 2016 and joined the computational biology laboratory of Prof Colin Semple at the University of Edinburgh Institute of Genetics and Molecular Medicine. She returned to Australia in September 2018 and joined the computational genomics laboratory of A/Prof Joseph Powell as Senior Research Officer at the Garvan Institute of Medical Research.
Single Cell eQTL Mapping Identifies Cell-type Specific Control of Complex Disease
Genome-wide association studies in large populations have enriched our understanding of genetic variants implicated in health and disease while expression quantitative trait loci (eQTL) studies with microarray and bulk-RNA sequencing data showed us how these genetic variants affect the expression of one or more genes in a tissue-specific manner. However, it is much less known how genetic variants influence gene expression in various cell types within a tissue. This study, therefore, set to identify the cell-specific eQTLs in the human immune cells using single-cell sequencing technology. We have performed conditional cis-eQTL analysis on 14 cell types in 1,242,226 immune cells from 993 healthy human subjects and identified thousands of independent cis-eQTLs across 14 different immune cell types. We show that the majority of these eQTL were unique to an individual cell-type; however, eQTLs shared across the hematopoietic lineage are also identified. Linking GWAS variants with cis-eQTLs within different cell types, we were able to show disease variants exert their effects in specific cell types. We have shown cell-specific control of immune system disease and established a healthy immune cell resource at single-cell resolution to prioritise disease-associated variants in functional studies.
ZHANG Xuegong Professor
Pattern Recognition and Bioinformatics, Department of Automation, Adjunct Professor
School of Life Sciences and School of Medicine, Director
Bioinformatics Division, Beijing National Research Centre for Information Science and Technology (BNRist)
Prof Xuegong Zhang earned his BS degree in Industrial Automation in 1989 and Ph.D. degree in Pattern Recognition and Intelligent Systems in 1994, both from Tsinghua University. He joined the faculty of Tsinghua University in 1994, where he is now a Professor of Pattern Recognition and Bioinformatics in the Department of Automation, and an Adjunct Professor of the School of Life Sciences and also the School of Medicine. Dr. Zhang worked at Harvard School of Public Health as a visiting scientist on computational biology in 2001-2002, and had been a visiting scholar in the MCB program at USC in 2007. He is the Director of the Bioinformatics Division, Beijing National Research Center for Information Science and Technology (BNRIST). He is the Chair of the Committee of Bioinformatics and Artificial Life in Chinese Association of Artificial Intelligence (CAAI), and a member of the Board of Directors of ISCB (International Society of Computational Biology). His research interests include machine learning, biological data mining especially for single-cell and metagenomic sequencing data, human cell atlas, and analyses of multi-modal big healthcare data for precision medicine.
Single-Cell Omics Studies in China and an Informatics View of HCA
Single-cell genomics and other single-cell technologies have been revolutionizing many fields of biological studies. Scientists in China have been very active in developing single-cell technologies, developing bioinformatics models and algorithms, building cell atlas of multiple human organs and developmental stages, and applying single-cell technologies for many medical questions. This talk will give an overview on some recent progresses of single-cell genomics and bioinformatics studies in China, and discuss some challenging issues of HCA from an informatics view.