Institute for Quantitative and Computational Biosciences

QCBio Research Seminar: Helena Winata (Boutros), Grad Student, Bioinformatics IDP
2023-03-17 12:30 - 13:00 (America/Los_Angeles) | ZOOM, CA, United States
TITLE: “Efficient, Multi Sample Inference of Cancer Phylogeny.”
ABSTRACT: Cancer is characterized by the ongoing accumulation of somatic mutations that may lead to dysregulated cellular proliferation. The selection of advantageous mutations leads to clonal expansions of progressively more aberrant and fit cancer cells. Reconstructing the evolutionary history of a tumor allows us to understand key events in disease progression and mechanisms that lead to disease lethality. Sequencing multiple tumor samples provide an opportunity to study tumor evolution in much greater detail and accuracy than was previously feasible through single-sample datasets. However, current reconstruction methods utilize stochastic-search algorithms, which iterates through a parameter space to jointly infer clone populations and their phylogeny. As tumor phylogenetic topology increases in complexity, the parameter space grows exponentially, and stochastic-search algorithms become computationally intractable. To circumvent current computational limitations, we developed a heuristic-based algorithm for subclonal reconstruction that leverages fundamental principles of cancer biology to encode heuristics that reduce the solution space to biologically plausible phylogenies. Benchmarking on real and simulated datasets are ongoing, and preliminary results indicate a ten-fold reduction in runtime. We have thus presented a novel method for rapid and optimized reconstruction of tumor evolutionary histories from multi-sample datasets.

https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/03/Helena-Winata-31723.mp4

QCBio Research Seminar: Jessica Ding (Yang), Grad Student, Molecular, Cellular, and Integrative Physiology
2023-03-17 12:00 - 12:30 | ZOOM, CA, United States
TITLE: “Multi-tissue single-cell level understanding of Alzheimer’s disease points to the therapeutic potential of nutritional and metabolic modulation.”
ABSTRACT: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by extracellular amyloid plaque deposition and intracellular neurofibrillary tangles. The direct cause of abnormal protein accumulation and aggregation is largely unknown, and no treatments exist to effectively delay or prevent development of AD. AD onset and progression is affected by many genetic and environmental factors, and exploration of significant risk factors for AD may help elucidate its complexity. AD is often comorbid with metabolic syndrome, which includes hypertension, elevated blood glucose and triglycerides, and abdominal obesity. We investigate the potential connection between AD and metabolic syndrome by testing the effect of high fructose consumption, omega-3 fatty acid docosahexaenoic acid (DHA), and nicotinamide riboside (NR) on hippocampal and hypothalamic single cell transcriptomes of the 5XFAD mouse model of amyloid accumulation. We report that metabolically challenging 5XFAD mice with fructose promotes expression of certain proinflammatory genes that may further exacerbate neuronal loss. Supplementation of 5XFAD with DHA and NR was shown to downregulate microglial activation genes, but DHA and NR on 5XFAD with fructose background also enhanced specific aspects of microglial function while downregulating fructose-induced exacerbation of proinflammatory genes, which may indicate mechanisms to counteract further worsening of AD by fructose. Overlaying differentially expressed genes (DEGs) onto a microglial gene regulatory network showed fructose, DHA, and NR target shared and specific aspects of the disease subnetwork. We also observed that fructose led to a depletion of an intermediate activated microglial state which was enhanced by DHA and NR. Transcriptomic signatures derived from this study showed high enrichment of GWAS signals including cell-type specific nutrition DEGs, regulatory network modules, and microglia trajectory associated genes. Our study has demonstrated that metabolic modulation impacts AD transcriptomic signatures and has significant implications for the treatment of AD with DHA and NR or modulators that enhance associated mechanisms.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/03/Jessica-Ding-3.17.23.mp4

QCBio/Bioinformatics/Human Genetics seminar: Min Xu, PhD, Assistant Professor, Computational Biology Department, Co-Director, MS in Computational Biology Program, Carnegie Mellon University
2023-03-13 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Automatic analysis of cryo-electron tomography using computer vision and machine learning.”

QCBio Research Seminar: Brandon Tsai (Boutros), Grad Student, Human Genetics
2023-03-10 12:30 - 13:00 | ZOOM, CA, United States
TITLE: “Exercise and tumor genomic landscapes in 2,702 patients with cancer”
ABSTRACT: Approximately two-thirds of cancer diagnoses globally are attributed to modifiable lifestyle factors such as smoking, diet and inactivity. Conversely, regular exercise is linked to decreased risk of multiple cancers. However, the underlying molecular mechanisms are not fully elucidated. Specifically, how exercise impacts tumor genomic landscapes has not been considered. To address this gap, we integrated clinical annotation of exercise exposure with tumor mutational profiling of 2,702 patients with cancer. Exercise exposure was evaluated by validated questionnaire and tumor genomic profiling of ≥ 505 commonly mutated cancer genes was performed using the Memorial Sloan Kettering Cancer Center Integrated Mutation Profiling of Actional Cancer Targets (MSK-IMPACT) assay. Among the most represented cancer types were breast (n = 629), lung (n = 525), endometrial (n = 260), colorectal (n = 213) and prostate (n = 177). We found that exercise influences the genomic landscapes of tumors in a cancer-type specific manner. For instance, breast and lung cancers from exercising patients had lower tumor mutation burden (TMB) compared with non-exercisers. A pan-cancer analysis revealed a higher risk ratio among exercisers for mutations in ERBB2 and lower risk ratio for mutations in PIK3CA and CDKN2A. Overall, this study shows that exercise regulates tumor genomic landscapes in a cancer-site specific manner.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/03/Brandon-Tsai-31023.mp4

QCBio Research Seminar: Daniel Ha (Yang), Postdoc, Dept. Integrative Biology and Physiology
2023-03-10 12:00 - 12:30 | ZOOM, CA, United States
TITLE: ““Cross-tissue multiomics studies reveal gutbrain interactions mediating the effect of Akkermansia muciniphila in counteracting fructose-induced obesity”
ABSTRACT: The gut bacterium Akkermansia muciniphila (A. muciniphila) has been implicated in anti-obesity effects, but a systems level understanding of the molecular mechanisms is lacking. We carried out multiomics studies to investigate the molecular cascades mediating the anti-obesity effect of A. muciniphila in a fructoseinduced obesity mouse model. We found that A. muciniphila colonization triggered significant shifts in gut microbiota composition, gut and plasma metabolites, and gene expression in hypothalamic neurons. Multiomics integration and network analysis prioritized the metabolite oleoylethanolamide (OEA) in the gut and circulation as a regulator of gut-brain interactions that underlie the A. muciniphila antiobesity effect. Oral administration of OEA counteracted the fructose-induced obesity through the regulation of hypothalamic anorexigenic neuropeptides such as oxytocin and arginine vasopressin. Our multiomics investigation and experimental validation elucidates the molecular regulators and pathways involved in the communication between A. muciniphila in the gut and hypothalamic neurons that counter fructose-induced obesity.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2023/03/Daniel-Ha-3.10.23.mp4

QCBio/Bioinformatics/Human Genetics seminar: Zoltán Kutalik, PhD, Associate Professor, University of Lausanne
2023-03-06 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Pushing the boundaries of causal inference.”

QCBio Research Seminar: Gregoire Altan-Bonnet, Principal Investigator – Immunodynamics group Laboratory of Integrative Cancer Immunology NCI, NIH, Bethesda MD
2023-03-06 14:00 - 15:00 | Boyer 159
TITLE: “Stochasticity in cancer immunotherapies: identifying the T cell subset that sparks tumor eradication”
ABSTRACT: We use an ex vivo model of tumor eradication to dissect the fundamental variability of clinical outcomes in cancer immunotherapies. We demonstrate that there exists an inherent stochastic variability in immune responses, based on the low abundance of hyper-responsive naïve T cells (so-called Spark T cells) and feedback regulations amongst leukocytes. We introduce a methodology (combining hierarchical clustering of single-cell measurements and statistical matching with functional outcomes) to identify Spark T cells. We then carry out functional tests to model the mechanics of Spark T cells igniting global immune responses and tumor rejection.

QCBio/Center for Biological Physics: Gregoire Altan-Bonnet, Principal Investigator – Immunodynamics group Laboratory of Integrative Cancer Immunology NCI, NIH, Bethesda MD
2023-03-03 16:00 - 17:00 | Boyer Hall 130

Webinar: Mapping The Brain With 100 Billion Cells, Is This an Impossible Task?
2023-03-01 17:30 - 18:30 | ZOOM, CA, United States

QCBio Webinar: Mapping The Brain With 100 Billion Cells, Is This an Impossible Task?
2023-03-01 17:30 - 18:30 | ZOOM, CA, United States
A conversation featuring:
Roy Wollman, Ph.D.
Professor, UCLA Integrative Biology & Physiology and Chemistry & Biochemistry
Jingyi Jessica Li, Ph.D.
Professor, UCLA Statistics, Biostatistics, Computational Medicine and Human Genetics
Hong-Wei Dong, Ph.D.
Professor, UCLA Neurobiology – Director, UCLA Brain Research & Artificial Intelligence Nexus (B.R.A.I.N.)
Introduction by:
Alexander Hoffmann, Ph.D.
Director, Institute for Quantitative & Computational Biosciences – Thomas M. Asher Professor of Microbiology, UCLA Microbiology, Immunology & Molecular Genetics

QCBio/Bioinformatics/Human Genetics seminar: Molly Przeworski, PhD, Professor, Biological Sciences, Systems Biology, Columbia University
2023-02-27 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Why do human germline mutation rates depend on sex and age.”

QCBio/Bioinformatics/Human Genetics seminar: Jonathan Sebat, PhD, Chief, Beyster Center for Molecular Genomics of Neuropsychiatric Diseases, Professor of Psychiatry and Cellular and Molecular Medicine, UC San Diego
2023-02-13 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “TBA”

QCBio/Bioinformatics/Human Genetics seminar: Haiyuan Yu, PhD, Professor, Biological Statistics and Computational Biology, Cornell University
2023-02-06 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “New perspectives to dissect global dynamics of protein interactome and gene regulation in disease.”

QCBio/Bioinformatics/Human Genetics seminar: Soojin Yi, PhD, Professor, Ecology, Evolution, and Marine Biology, UC Santa Barbara
2023-01-30 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “DNA Methylation in Brain Evolution and Neuropsychiatric Disorders.”

QCBio/Bioinformatics/Human Genetics seminar: Pleuni Pennings, PhD, Associate Professor, Biology, San Francisco State University
2023-01-23 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Part 1: “How important is evolution vs transmission of drug resistance”.
Part 2: “Computing skills for every biology student.”

QCBio Research Seminar: Friedrich Simmel, Department of Bioscience, School of Natural Sciences, TU Munich, Germany
2023-01-13 14:00 - 15:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Electric actuation of DNA-based molecular machines.”
ABSTRACT: A wide range of machine-like molecular assemblies have been generated over the past years. Most of them have been driven (or controlled) by DNA hybridization, utilization of buffer changes, or using chemical modifications such as photoswitches. A more recently explored strategy is the use of electrical fields for the manipulation of DNA devices, which enables fast and computer-controlled actuation. In the talk, several examples of such DNA origami-based „nanorobotic“ systems will be discussed, including a DNA „robot arm“, molecular springs, an origami based Brownian ratchet with rotary movement, and others. On a slightly different topic, also a novel strategy to control microswimmers using AC electrical fields will be presented.

QCBio/Bioinformatics/Human Genetics seminar: Shamil Sunyaev, PhD, Professor, Biomedical Informatics, Harvard Medical School
2023-01-09 16:00 - 17:00 | Boyer 159
TITLE: “Statistics, Biology and Applications of Human Mutation.”

QCBio Research Seminar: Zhiqian Zhai (Li JJ), Graduate Student in Statistics
2022-12-15 13:30 - 14:00 | Boyer Hall 159
TITLE: “Supervised capacity preserving mapping: a clustering guided visualization method for scRNA-seq data.”
ABSTRACT: Recently, various computational methods have been developed to analyze the scRNAseq data, such as clustering and visualization. However, current visualization methods, including t-SNE and UMAP, are challenged by the limited accuracy of rendering the geometric relationship of populations with distinct functional states. Most visualization methods are unsupervised, leaving out information from the clustering results or given labels. This leads to the inaccurate depiction of the distances between the bona fide functional states. In particular, UMAP and t-SNE are not optimal to preserve the global geometric structure. They may result in a contradiction that clusters with near distance in the embedded dimensions are in fact further away in the original dimensions. Besides, UMAP and t-SNE cannot track the variance of clusters. Through the embedding of t-SNE and UMAP, the variance of a cluster is not only associated with the true variance but also is proportional to the sample size. Here, we present supCPM, a robust supervised visualization method, which separates different clusters, preserves the global structure and tracks the cluster variance.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/Zhiqian-Zhai-edited.mp4

QCBio Research Seminar: Roni Haas (Boutros), Postdoc in Human Genetics
2022-12-15 13:00 - 13:30 | Boyer Hall 159
TITLE: “Proteogenomic characterization of the molecular determinants of prostate cancer radioresistance.”
ABSTRACT: Prostate Cancer (PC), the second most common cause of cancer death in men, is frequently treated using radiotherapy with curative intent. Despite its effectiveness, radiotherapy often results in aggressive PC relapse characterized by radioresistance. The diversity in therapeutic response to radiotherapy, and the molecular processes underlining radioresistance are not fully understood. Here we integrated genomic, transcriptomic, and proteomic investigations to comprehensively characterize the molecular determinants of PC radioresistance. To model radioresistance, we have created Conventional-Fractionation (CF) and Hypo-Fractionated (HF) isogenic radioresistant cells that represent different therapeutic regimens: the traditional CF radiotherapy with daily small radiation doses over weeks, and the relatively new HF radiotherapy with high radiation doses across several single treatments. We discovered that CF radioresistant cells gained twice the number of somatic single-nucleotide variants than HF. Nevertheless, the gained mutations, irrespective of the treatment schedule, converged on mutational signatures associated with mismatch DNA repair. CF radioresistant cells demonstrated strong and exclusive dysregulation of driver and hallmark-cancer genes in RNA abundance profiles. The differences in protein abundance display cell-fraction-dependent clusters, foremost of which are elevated levels of DNA repair proteins in CF radioresistant cell nuclei. Collectively, we observed a far more aggressive phenotype in CF radioresistant cells compared to HF. The clinical relevance of our top potential therapeutic targets was assessed using a cohort of 380 PC patients. Our study provides a platform for the development of therapies for radio-recurrent PC. Ongoing proteogenomic integration will help understand the relationships amongst radioresistance-associated changes at the DNA, RNA, and protein levels.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/Roni-Haas.mp4

QCBio Research Seminar: Guanao Yan (Li JJ), Graduate Student in Statistics
2022-12-07 12:00 - 12:30 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “scReadSim: a single-cell RNA-seq and ATAC-seq read simulator.”
ABSTRACT: Rapid advances of single-cell RNA-seq and ATAC-seq technologies have propelled the development of many computational tools, benchmarking of which demands realistic simulators. However, few simulators can generate sequencing reads, and none of the existing read simulators aim to mimic real cells, hindering the benchmarking of low-level computational tools that process reads. To fill this gap, we propose scReadSim, a single-cell RNA-seq and ATAC-seq read simulator that generates synthetic cells which mimic real cells. Trained on real data, scReadSim can generate synthetic data in FASTQ and BAM formats. By deploying scReadSim on sci-ATAC-seq and 10x Multiome (ATAC+RNA) data, we show that the scReadSim synthetic data resemble real data at both read and count levels. Moreover, as a flexible simulator, scReadSim enables users to arbitrarily specify open chromatin regions for the synthetic scATAC-seq reads, and is also capable of allowing varying the cell number and sequencing depths for the synthetic data. To illustrate the versatile usage of scReadSim, we include two exemplar benchmark studies to show that scReadSim provides unique molecular identifier (UMI) counts for benchmarking scRNA-seq deduplication tools and can accommodate user-specified open chromatin regions (“ground truths”) to generate single-cell ATAC-seq data. Our benchmark applications of scReadSim show that cellranger is a preferred scRNA-seq deduplication tool, and MACS3 achieves top performance in scATAC-seq peak calling.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/video1156562562.mp4

QCBio Research Seminar: Mark Xiang (Hoffmann), Graduate Student in Bioinformatics
2022-12-07 11:00 - 11:30 | Boyer Hall 159
TITLE: “Heterogeneity in cell states: Is it important whether cell states are heritable or change rapidly?”
ABSTRACT: Cells of the same cell type show molecular and phenotypic heterogeneity. Is the particular cell state of a given cell heritable from one generation to the next? Previous work in liver cancer cells indicates that the molecular network that controls cell death may change within hours, but the data from B-cells shows that their cell state is durable and heritable. In this project, I address this question by formulating a model of B-cell-mediated antibody responses. This model recapitulates the Darwinian selection process to produce high affinity antibodies against an antigen. I then test how heterogeneity in the cell states affects the antibody repertoire, and then what the effect of heritability of those cell states might be. The preliminary results from model simulation will be presented and discussed.

QCBio Research Seminar: Jee Yun Han (Boutros), Graduate Student in Gene Regulation, Epigenomics, and Transcriptomics
2022-12-02 14:30 - 15:00 | ZOOM, CA, United States
TITLE: “Comprehensive study of gene expression outliers and their regulation mechanisms in pan-cancer.”
ABSTRACT: Cancer is a disease characterized by remarkable heterogeneity. Gene expression varies drastically between tumours and within cells of a single. This variability can generate extreme outliers: transcripts that show atypically high gene expression in a small percentage of cancers. These outliers increase the molecular and phenotypic diversity between individuals, contributing to tumour heterogeneity. However, the previous research has been limited to a single cancer type or a single gene. To fill the gap of our understanding, this study will identify the outliers from various cancer types using our novel statistical method and explore the biological functions of outliers. With integrated analysis with the clinical outcome, it will show how outliers affect the progression of cancer. This study is expected to deepen our understanding of the impact of outliers on different cancers by dissecting their dysregulation and will allow us to identify a novel cancer driver and potential drug target.

QCBio Research Seminar: Matthew Soldano, Staff Research Associate for the Pellegrini Bioinformatic's Lab
2022-12-02 14:00 - 14:30 | ZOOM, CA, United States
TITLE: “Predicting Biological Aging from Epigenetics.”
ABSTRACT: Epigenetics are a proven measure of cellular health. Therefore, a field of research has emerged that utilizes epigenetics to measure, treat, and potentially reverse biological age in humans. Specifically, DNA methylation, responsible for cell differentiation and gene expression, has the potential to be a barcode for measuring biological age. Current DNA methylation aging tests require blood and are trained to predict chronological aging. To address this, we are developing a buccal swab DNA methylation test that measures fitness and general health. We utilize targeted bisulfite sequencing and are testing several machine learning techniques to generate a reliable test.
https://qcb.ucla.edu/wp-content/uploads/sites/14/2022/11/video1371794408.mp4

W4: Galaxy for NGS Data Analysis
2022-10-26 13:30 - 2022-10-27 16:30 | 529 Boyer Hall, 611 Charles E Young Dr E,, Los Angeles, CA, 90095, United States
Galaxy (https://usegalaxy.org/) is a web-based infrastructure for bioinformatics application. First, this workshop introduces participants to using Galaxy for analysis of Next-Generation Sequencing data. Next, this workshop covers the structure of Galaxy, data format and manipulation, obtaining and sharing data, and building and sharing workflows. We will use the tools installed on the UCLA galaxy to perform a few types of NGS analysis.

W22: Intro to Cytoscape
2022-10-25 09:00 - 2022-10-27 12:00 | 529 Boyer Hall, 611 Charles E Young Dr E,, Los Angeles, CA, 90095, United States
The workshop introduces Cytoscape (https://cytoscape.org/) – an open source platform for retrieval and visualization of complex biological interactions that are available from public interaction resources: The IMEx Consortium (https://www.imexconsortium.org/), STRING (https://string-db.org/) and BioGIRD (https://thebiogrid.org/). It covers querying for interactions data using built-in search interface, interaction data cleanup and visualization as well as overlying of the in-house generated data (eg. gene expression levels) on top of the imported reference interaction network. The workshop will also provide an overview of the experimental methods of interaction determination and of the information available from the interaction resources, both necessary to critically evaluate imported interaction networks.

QCBio/BIG Summer Research Seminar: Dr. Michael Wells, Assistant Professor, Human Genetics, UCLA
2022-08-05 16:00 - 17:00 | Boyer 159
TITLE: “Exploration of human genetic and phenotypic diversity through cell villages”.
ABSTRACT: Our species is characterized by an immense diversity in neurological and psychological traits. Common and rare genetic variants have been linked to trait differences and disease risk in human populations, though the underlying biology is poorly understood and difficult to study at large scales. In this presentation, I will first describe a novel experimental platform that enables high-throughput investigations into the influence of human genetic variation on the earliest stages of brain development. This system, known as a “cell village” captures genetic, molecular, and phenotypic heterogeneity in a shared in vitro environment, thus facilitating the detection of relationships among human alleles, gene expression, and cellular behaviors. I will then describe how we used cell villages to identify a single nucleotide polymorphism in the IFITM3 gene that could explain over half of the variance in neural progenitor cell susceptibility to the Zika virus, which is a pathogen that causes severe neurodevelopmental disorders. I will conclude with a brief discussion on the future of the village approach and how we plan to deploy this technology to investigate neurodevelopmental disorders of genetic origin in my laboratory at UCLA. Throughout this talk, I will talk about the career decisions that led me to a career in neuroscience.

QCBio/BIG Summer Research Seminar: Dr. Xia Yang, Professor, Dept. Integrative Biology & Physiology, UCLA
2022-07-29 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Integrative systems analysis, applications, and challenges of single cell multiomics.”
ABSTRACT: Recent advances in single cell multiomics technologies such as single cell RNA-seq, single cell ATAC-seq, and spatial transcriptomics have brought enormous opportunities that enable our understanding of the molecular underpinnings of pathophysiology at a single cell resolution. However, integrative analysis across single cell multiomics domains and further incorporation of genetics information have proven challenging. I will introduce our recent efforts in single cell multiomics integration, network modeling, and eQTL analysis, present computational tools to carry out these analyses, and showcase application examples in studies of traumatic brain injury, Alzheimer’s disease, and genetic control of cell-type specific hypothalamic cell types to regulate energy homeostasis. I will also highlight the challenges and future directions of integrative systems analysis of single cell multiomics data.

QCBio/BIG Summer Research Seminar: Dr. Eleazar Eskin, Professor and Chair Department of Computational Medicine, UCLA
2022-07-22 16:00 - 17:00 | 529 Boyer Hall, 611 Charles E Young Dr E,, Los Angeles, CA, 90095, United States
TITLE: “Swab-Seq: Detecting COVID-19 with Genomic Sequencing: From bench to vending machine.”
ABSTRACT: At UCLA we developed one of the only novel technologies for COVID-19 diagnostic testing that was deployed on a large scale. The assay, which we named SwabSeq, performs genomic sequencing of pooled samples tagged with sample-specific molecular barcodes and then uses computational approaches to deconvolve the pooled samples into individual diagnoses, enabling the testing of thousands of nasal or saliva samples for SARS-CoV-2 RNA in a single run without the need for RNA extraction. The efficiency of SwabSeq has enabled a small facility with a handful of staff to perform over 1,000,000 tests, with an analytical sensitivity and specificity comparable to or better than traditional qPCR test with turnaround times of less than 24 h. SwabSeq could be rapidly adapted for the detection of other pathogens.

QCBio/BIG Summer Research Seminar: Dr. Eric Deeds, Associate Professor - Vice Chair, Life Sciences Core, UCLA
2022-07-15 16:00 - 17:00 | Boyer Hall 159
TITLE: “A lack of distinct cellular identities in scRNA-seq data: revisiting Waddington’s landscape”.
ABSTRACT: Single-cell RNA sequencing is revolutionizing our understanding of development, differentiation and disease. Analysis of this data is often challenging, however, and tasks like clustering cells to uncover distinct cellular identities sometimes yields results that fail to align with existing biological knowledge. We analyzed publicly available data where the cell identity for each cell is known a priori, and found that cells of very different types and lineages do not occupy distinct regions of gene expression space. Rather, cells from different lineages overlap extensively with one another, significantly complicating attempts to recover distinct identities within the data. Indeed, our analysis of available epigenetic data for a wide variety of tissues and organisms revealed these data are not consistent with the predictions of Waddington’s landscape, suggesting a need to revisit our picture of gene expression changes during differentiation and development.

QCBio/BIG Summer Research Seminar: Dr. Nandita Garud, Assistant Professor Assistant Professor, Department of Ecology and Evolutionary Biology, UCLA
2022-07-08 16:00 - 17:00 | Boyer 159, 611 Charles E. Young Dr. E., Los Angeles, CA, 90095, United States
TITLE: “Evolutionary dynamics in the human gut microbiome from infancy through adulthood.”
ABSTRACT: While the ecological dynamics of the infant gut microbiome have been intensely studied, relatively little is known about the evolutionary dynamics in the infant gut microbiome. Here we analyze longitudinal fecal metagenomic data from >700 infants and their mothers over the first year of life and find that the evolutionary dynamics in infant gut microbiomes are distinct from that of adults. We find evidence for almost 100-fold increase in the rate of evolution and strain turnover in the infant gut compared to healthy adults, with the mother-infant transition at delivery being a particularly dynamic period in which gene loss dominates. Within a few months after birth, these dynamics stabilize, and gene gains become increasingly frequent as the microbiome matures. We furthermore find that evolutionary changes in infants show signatures of being seeded by a mixture of de novo mutations and transmissions of pre-evolved lineages from the broader family. Several of these evolutionary changes occur in parallel in multiple infants, highlighting candidate genes that may play important roles in the development of the infant gut microbiome. Our results point to a picture of a volatile infant gut microbiome characterized by rapid evolutionary and ecological change in the early days of life.
