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DTSTART;TZID=Australia/Sydney:20260511T130000
DTEND;TZID=Australia/Sydney:20260511T140000
DTSTAMP:20260502T113000
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SUMMARY:Coupling Single-cell Genome & Epigenome to Study Functional Consequence of Somatic SVs
DESCRIPTION:Statistical Bioinformatics SeminarSpeaker: Dr Hyobin Jeong\, Yonsei University \n\n\n\nThis is an online event held via Zoom: https://uni-sydney.zoom.us/j/85114748391 \n\n\n\n\n\n\n\n\n\nSomatic structural variants are widespread in cancer\, but their impact on disease evolution is understudied due to a lack of methods to directly characterize their functional consequences. We proposed a computational method\, scNOVA\, which utilizes Strand-seq to perform haplotype-aware integration of structural variant discovery and molecular phenotyping in single cells\, by using nucleosome occupancy to infer gene expression as a read-out. Application to leukemias and cell lines identifies local effects of copy-balanced rearrangements on gene deregulation\, and consequences of structural variants on aberrant signaling pathways in subclones. We discovered distinct SV subclones with dysregulated Wnt signaling in a chronic lymphocytic leukemia patient. We further uncovered the consequences of subclonal chromothripsis in T-cell acute lymphoblastic leukemia\, which revealed c-Myb activation\, enrichment of a primitive cell state and informed successful targeting of the subclone in cell culture\, using a Notch inhibitor. More recently\, scNOVA to complex karyotype acute myeloid leukemia (AML) revealed dynamic clonal evolution and targetable phenotypes. Not only cancer system\, we can apply this approach to study functional effect of somatic SVs in clonal hematopoiesis and aging. Also\, we are now extending scNOVA to develop scalable and broadly applicable bioinformatics methods which can link SVs to their functional effects\, to enable systematic single-cell multiomic studies of structural variation in heterogeneous cell populations. \n\n\n\n\n\n\nSubscribe to our seminar mailing list\n\n\n\n\n→\n\n\n\n\n\n\n\nFind out more about the Statistical Bioinformatics seminar series\n\n\n\n\n\n→\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDr Hyobin Jeong\n\n\n\nDr Hyobin Jeong is an assistant professor at Yonsei University in the Department of Systems Biology. She received her PhD in Interdisciplinary Bioscience and Biotechnology from Pohang University of Science and Technology (POSTECH). She has completed postdoctoral fellowships at the European Molecular Biology Laboratory (EMBL) and the Institute of Molecular Biology (IMB) in Germany\, and the Institute of Basic Science in Korea. Before her current role\, she was a Research Professor at the Hanyang Institute of Bioscience and Biotechnology.
URL:https://spds.sydney.edu.au/event/coupling-single-cell-genome-epigenome-to-study-functional-consequence-of-somatic-svs/
ATTACH;FMTTYPE=image/jpeg:https://spds.sydney.edu.au/wp-content/uploads/2025/02/Complex-systems-1-edited-scaled.jpeg
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DTSTART;TZID=Australia/Sydney:20260518T130000
DTEND;TZID=Australia/Sydney:20260518T140000
DTSTAMP:20260502T113000
CREATED:20260424T022258Z
LAST-MODIFIED:20260424T022259Z
UID:4897-1779109200-1779112800@spds.sydney.edu.au
SUMMARY:Genetic regulation of human skeletal muscle: from bulk QTLs to single-nucleus resolution
DESCRIPTION:Statistical Bioinformatics SeminarSpeaker: Wang Wenjing\, National University of Singapore \n\n\n\nThis is an online event held via Zoom: https://uni-sydney.zoom.us/j/85114748391 \n\n\n\n\n\n\n\n\n\nAlthough lifestyle-induced weight loss reduces type 2 diabetes risk\, how genetic variation shapes gene expression and splicing responses to weight loss remains poorly understood\, particularly in Asian populations. In the first part of this talk\, I will present our recently published work (Cell Genomics\, 2025) in which we profiled skeletal muscle transcriptomes from 54 overweight/obese Asian individuals before and after a 16-week lifestyle intervention in the Singapore Adult Metabolism Study (SAMS). The intervention resulted in ~10% weight loss and ~30% improvement in insulin-stimulated glucose uptake. We identified 505 differentially expressed genes enriched in mitochondrial function and insulin sensitivity pathways\, mapped cis-eQTLs and cis-sQTLs that are shared or condition-specific\, and integrated these regulatory variants with GWAS signals for metabolic traits to pinpoint candidate causal genes and mechanisms. In the second part\, I will introduce our ongoing effort to build a comprehensive single-nucleus and spatial transcriptomic atlas of human skeletal muscle. Using snRNA-seq from over 300 biopsies spanning lean and obese individuals across three Asian ancestries\, we have profiled more than one million nuclei and annotated over 20 cell types capturing substantial cellular heterogeneity across ancestry\, adiposity\, and metabolic states. We are now extending this resource with spatial transcriptomics (MERFISH and Xenium) on paired pre- and post-intervention samples to spatially resolve cell-type-specific regulatory programs and microenvironment remodeling during weight loss. Together\, these efforts establish the first longitudinal\, ancestry-diverse single-nucleus and spatial regulatory reference for Asian human skeletal muscle. \n\n\n\n\n\n\nSubscribe to our seminar mailing list\n\n\n\n\n→\n\n\n\n\n\n\n\nFind out more about the Statistical Bioinformatics seminar series\n\n\n\n\n\n→\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nWenjing Wang\n\n\n\nWenjing Wang is a third-year PhD candidate in the lab of Prof. Liu Boxiang at the National University of Singapore\, working at the intersection of functional genomics and metabolic disease. Her work combines bulk and single-nucleus RNA sequencing with QTL mapping to understand how genetic variation and lifestyle interventions reshape gene regulation across cell types. Her recent study on gene expression and splicing responses to exercise- and diet-induced weight loss was published in Cell Genomics (2025). She is currently building a large-scale single-cell and spatial atlas of human skeletal muscle across diverse Asian populations. \n\n\n\nFind out more on LinkedIn: https://www.linkedin.com/in/wenjing-wang-40a67b18b/
URL:https://spds.sydney.edu.au/event/genetic-regulation-of-human-skeletal-muscle-from-bulk-qtls-to-single-nucleus-resolution/
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DTSTART;TZID=Australia/Sydney:20260601T130000
DTEND;TZID=Australia/Sydney:20260601T140000
DTSTAMP:20260502T113000
CREATED:20260417T015751Z
LAST-MODIFIED:20260420T051802Z
UID:4869-1780318800-1780322400@spds.sydney.edu.au
SUMMARY:Through the Unlabeled Lens of Spatial Multi-Omics
DESCRIPTION:Statistical Bioinformatics SeminarSpeaker: Dr Anthony A. Fung\, Yale University \n\n\n\nThis is an online event held via Zoom: https://uni-sydney.zoom.us/j/85114748391 \n\n\n\n\n\n\n\n\n\nSometimes it matters less what you look at\, and more what you see. Common practices in clinical pathology often involve multiple histological stains on serial sections of tissue biopsy to obtain the highest diagnostic power\, but this requires expertise\, reagent costs\, consumes tissue\, risks deformation\, and complicates co-registration\, potentially missing rare microstructures. Now there is a major push for spatial multi-omics integration\, but even adjacent tissue sections captured with different modalities decrease performance. Today’s seminar introduces a non-destructive label-free optical platform combining SRS\, SHG\, and TPF enables high-resolution molecular imaging to unravel the lipidomic\, metabolic\, and morphometric landscape of kidney disease\, and how these data types can augment your modalities. \n\n\n\n\n\n\nSubscribe to our seminar mailing list\n\n\n\n\n→\n\n\n\n\n\n\n\nFind out more about the Statistical Bioinformatics seminar series\n\n\n\n\n\n→\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDr Anthony A. Fung\n\n\n\nDr Anthony A. Fung is a T32 postdoctoral fellow in Professor Rong Fan’s group at Yale University. He received his PhD in Bioengineering at University of California San Diego from Professor Lingyan Shi’s group. Anthony has received several awards in the quantitative spatial biology field and is a collaborating investigator in both HuBMAP and SenNet consortia. His current work centers on the development and application of spatial multi-omics technologies in aging and immune senescence.Find out more on LinkedIn:https://www.linkedin.com/in/anthony-fung/
URL:https://spds.sydney.edu.au/event/through-the-unlabeled-lens-of-spatial-multi-omics/
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