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X-WR-CALDESC:Events for Sydney Precision Data Science Centre
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DTSTART;TZID=Australia/Sydney:20250407T130000
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DTSTAMP:20260415T093114
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SUMMARY:Toward a cell-type-specific understanding of complex diseases
DESCRIPTION:Statistical Bioinformatics SeminarDr Boxiang Liu\, National University of Singapore\n\n\n\n\n\n\n\n\n\n\n\n\n\nHigh-throughput genotyping and sequencing have led to the discovery of thousands of disease-associated variants. Because most of these variants lie in non-coding regions\, their functional mechanisms remain unclear. To identify genetic effects underlying complex diseases\, it has become increasingly important to investigate the proper cell types and contexts. We demonstrate the power of cell-type-specific assays for three complex diseases.  \n\n\n\nCoronary artery disease (CAD) is the leading cause of death globally. Approximately 40 – 60% of CAD severity can be attributed to genetic factors. GWAS meta-analyses have uncovered more than 100 significant loci\, but most are difficult to interpret because they reside in non-coding regions. We found that coronary artery smooth muscle-specific genetic regulatory mechanisms are highly enriched in CAD GWAS signals. By jointly analyzing eQTL and GWAS datasets\, we identified five risk genes. TCF21 and SMAD3 were subsequently validated by single-cell analysis in atherosclerotic mouse models. Age-related macular degeneration is one of the leading causes of blindness in elderlies. It has been estimated that genetic factors explain 45% – 70% of the variation in the severity of age-related macular degeneration. Retinal pigment epithelium (RPE) is vital in ocular development but is underrepresented in genetic regulation studies.  \n\n\n\nBy jointly analyzing RPE eQTL and AMD GWAS\, we identified several risk genes including RDH5. In particular\, we found that the eQTL regulatory SNP also regulates splicing. Experimental validation confirms that the minor allele leads to aberrant splicing and subsequently RNA non-sense-mediated decay. This result revealed the genetic mechanism of RDH5 regulation and confirmed RDH5 as a risk gene for age-related macular degeneration\, making it a potential target for drug development. Autoimmune diseases are a group of illnesses that are individually rare but collectively affect 5% of the population. Leveraging ~1M PBMC single cells from the Asian Immune Diversity Atlas (AIDA)\, we showcase our recent results on leveraging single-cell sQTLs to disentangle autoimmune diseases. \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 Boxiang Liu\n\n\n\nBoxiang Liu obtained BA degree in Biophysics from Illinois Wesleyan University\, a MS degree in Statistics and a PhD degree in Bioinformatics from Stanford University. He was a research leader at Baidu Research USA and joined the National University of Singapore as an Assistant Professor in 2022. His research group specializes in genetic regulation of molecular traits (QTLs) and single-cell multi-omics. He is the winner of President’s Award in Natural Sciences and Mathematics\, Stanford University CEHG fellowship\, Charles B. Carrington Memorial Award\, and the Chinese Government Outstanding Overseas Ph.D. Students. His research group focuses on using computational and statistical tools to understand the genetics of complex human diseases\, with the long-term goal of validating known and identifying novel drug targets.
URL:https://spds.sydney.edu.au/event/toward-a-cell-type-specific-understanding-of-complex-diseases/
CATEGORIES:Videos
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DTSTART;TZID=Australia/Sydney:20250414T130000
DTEND;TZID=Australia/Sydney:20250414T140000
DTSTAMP:20260415T093114
CREATED:20250404T031759Z
LAST-MODIFIED:20250509T063228Z
UID:3253-1744635600-1744639200@spds.sydney.edu.au
SUMMARY:RNA polymerase II at histone genes predicts outcome in human cancer
DESCRIPTION:Dr Ye Zheng\, University of Texas MD Anderson Cancer Center\n\n\n\n\n\n\n\n\n\n\n\n\n\nGenome-wide hypertranscription is common in human cancer and predicts poor prognosis. To understand how hypertranscription might drive cancer\, we applied our formalin-fixed paraffin-embedded (FFPE)–cleavage under targeted accessible chromatin method for mapping RNA polymerase II (RNAPII) genome-wide in FFPE sections. We demonstrate global RNAPII elevations in mouse gliomas and assorted human tumors in small clinical samples and discover regional elevations corresponding to de novo HER2 amplifications punctuated by likely selective sweeps. RNAPII occupancy at S-phase-dependent histone genes correlated with WHO grade in meningiomas\, accurately predicted rapid recurrence\, and corresponded to whole-arm chromosome losses. Elevated RNAPII at histone genes in meningiomas and diverse breast cancers is consistent with histone production being rate-limiting for S-phase progression and histone gene hypertranscription driving overproliferation and aneuploidy in cancer\, with general implications for precision oncology. \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 Ye Zheng\n\n\n\nYe Zheng is a tenure-track Assistant Professor in the Bioinformatics and Computational Biology Department of the University of Texas MD Anderson Cancer Center and an NIH/NHGRI K99/R00 fellow. Dr. Zheng received her postdoctoral training at the Fred Hutchinson Cancer Center from both molecular biology and quantitative modeling perspectives mentored by Dr. Steven Henikoff. Before her postdoctoral training\, Dr. Zheng received a Ph.D. in Statistics from the University of Wisconsin-Madison under the supervision of Dr. Sündüz Keleş.  At MD Anderson Cancer Center\, Dr. Zheng leads a hybrid research group. Her quantitative research group is dedicated to the statistical modeling and computational pipeline development using bulk and single-cell transcriptomics\, proteomics\, epigenomics\, and 3D genomics data to address biological and clinical challenges. Her wet lab specializes in the epigenomic profiling of the Formalin-Fixed\, Paraffin-Embedded (FFPE) samples.
URL:https://spds.sydney.edu.au/event/rna-polymerase-ii-at-histone-genes-predicts-outcome-in-human-cancer/
CATEGORIES:Videos
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DTSTART;TZID=Australia/Sydney:20250428T130000
DTEND;TZID=Australia/Sydney:20250428T140000
DTSTAMP:20260415T093114
CREATED:20250403T231421Z
LAST-MODIFIED:20250509T062934Z
UID:3206-1745845200-1745848800@spds.sydney.edu.au
SUMMARY:Spatially resolved mapping of cells associated with human complex traits
DESCRIPTION:Liyang Song\, Westlake University\n\n\n\n\n\n\n\n\n\nDepicting spatial distributions of disease-relevant cells is crucial for understanding disease pathology. In our recent work\, we developed a method\, gsMap\, that integrates spatial transcriptomics (ST) data with genome-wide association study (GWAS) summary statistics to map cells to human complex traits\, including diseases\, in a spatially resolved manner. Using embryonic ST datasets covering 25 organs\, we benchmarked gsMap through simulation and by corroborating known trait-associated cells or regions in various organs. Applying gsMap to brain ST data\, we revealed that the spatial distribution of glutamatergic neurons (glu-neurons) associated with schizophrenia more closely resembles that for cognitive traits than that for mood traits\, such as depression. The schizophrenia-associated glu-neurons were distributed near the dorsal hippocampus\, with upregulated calcium signaling and regulation genes\, while the depression-associated glu-neurons were distributed near the deep medial prefrontal cortex\, with upregulated neuroplasticity and psychiatric drug target genes. \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\nLiyang Song\n\n\n\nLiyang Song is a fourth-year Ph.D. student in Statistical Genetics at Westlake University\, advised by Dr. Jian Yang. His research focuses on the intersection of human genetics\, statistics\, deep learning\, and spatial omics\, with applications to medicine. He is dedicated to developing efficient statistical methods and software tools that enable robust genetic and scientific discoveries by integrating genetic data with multi-omics datasets.
URL:https://spds.sydney.edu.au/event/spatially-resolved-mapping-of-cells-associated-with-human-complex-traits/
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