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U1 snRNP regulates alternative promoter activity by inhibiting premature polyadenylation

Molecular Cell 2025年第10期85卷 1968-1981.e7页

作者： Kim, GyeungYun Carroll, Christine L. Wakefield, Zachary Peters Tuncay, Mustafa Fiszbein, Ana Biology Department Boston University Boston 02215 United States Graduate Program in Molecular Biology Cell Biology & Biochemistry Boston University Boston 02215 United States Graduate Program in Cell and Molecular Biology Boston University Boston 02215 United States Bioinformatics Program Faculty of Computing and Data Science Boston University Boston 02215 United States Center for Computing & Data Sciences Boston University Boston 02215 United States

Emerging evidence indicates that splicing factors mediate the close link between transcription and splicing. However, the mechanisms underlying this coupling remain unclear. U1 small nuclear ribonucleoprotein particle (U1 snRNP) not only initiates splicing but also plays a crucial role in preventing premature cleavage and polyadenylation, facilitating long-distance transcriptional elongation. Here, we show that U1 snRNP regulates alternative promoter activity in human cells by inhibiting premature polyadenylation. In genes carrying premature polyadenylation sites between two promoters, U1 snRNP inhibition with antisense oligonucleotides leads to a significant decrease in downstream promoter activity. Conversely, restoring U1 snRNP activity or inhibiting premature polyadenylation rescues downstream promoter activity. Mechanistically, U1 snRNP inhibition correlates with reduced chromatin accessibility, decreased RNA polymerase II serine 5 phosphorylation, and increased promoter-proximal pause at downstream promoters. Our findings support a model in which U1 snRNP favors productive elongation from upstream promoters, triggering downstream promoter activation by destabilizing nucleosomes and promoting promoter escape. © 2025 The Author(s)

关键词： alternative promoters dowsntream promoters promoter-proximal pause splicing factors splicing transcription transcription cooperativity transcription initiation transcription interfierence transcription start sites U1 snRNP

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Genomic data processing with GenomeFlow

arXiv

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arXiv 2025年

作者： Park, Junseok Maury, Eduardo A. Oh, Changhoon Shin, Donghoon Denisko, Danielle Lee, Eunjung Alice Division of Genetics and Genomics Boston Children’s Hospital 3 Blackfan Circle BostonMA United States Department of Pediatrics Harvard Medical School 25 Shattuck St BostonMA United States Bioinformatics Integrative Genomics Program Harvard/MIT MD-PHD Program Harvard Medical School BostonMA United States Program in Medical and Population Genetics Broad Institute of MIT and Harvard CambridgeMA United States Graduate School of Information Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul Korea Republic of Department of Human Centered Design and Engineering University of Washington SeattleWA United States Department of Biomedical Informatics Harvard Medical School BostonMA United States

Advances in genome sequencing technologies generate massive amounts of sequence data that are increasingly analyzed and shared through public repositories. On-demand infrastructure services on cloud computing platforms enable the processing of such large-scale genomic sequence data in distributed processing environments with a significant reduction in analysis time. However, parallel processing on cloud computing platforms presents many challenges to researchers, even skillful bioinformaticians. In particular, it is difficult to design a computing architecture optimized to reduce the cost of computing and disk storage as genomic data analysis pipelines often employ many heterogeneous tools with different resource requirements. To address these issues, we developed GenomeFlow, a tool for automated development of computing architecture and resource optimization on Google Cloud Platform, which allows users to process a large number of samples at minimal cost. We outline multiple use cases of GenomeFlow demonstrating its utility to significantly reduce computing time and cost associated with analyzing genomic and transcriptomic data from hundreds to tens of thousands of samples from several consortia. Here, we describe a step-by-step protocol on how to use GenomeFlow for a common genomic data processing task. We introduce this example protocol geared toward a bioinformatician with little experience in cloud computing. © 2025, CC BY.

关键词： Cloud platforms

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Computational systems biology of metabolism in single- and multi- species microbial systems

Computational systems biology of metabolism in single- and m...

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Liaison Functions 2014 - Core programming Area at the 2014 AIChE Annual Meeting

作者： Zomorrodi, Ali R. Department of Biomedical Engineering Graduate Program in Bioinformatics Boston University BostonMA United States

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A structural haplotype in the 17q21.31 MAPT region is associated with increased risk for chronic traumatic encephalopathy endophenotypes

Cell Reports Medicine

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Cell Reports Medicine 2025年第5期6卷 102084-102084页

作者： Han, Xudong Zhang, Yichi Petrosky, Jillian N. Bald, Sarah Sherva, Richard M. Labadorf, Adam Cherry, Jonathan D. Chung, Jaeyoon Farrell, Kurt Abdolmohammadi, Bobak Durape, Shruti Martin, Brett M. Palmisano, Joseph N. Farrell, John J. Alvarez, Victor E. Huber, Bertrand R. Dwyer, Brigid Daneshvar, Daniel H. Jun, Gyungah R. Lunetta, Kathryn L. Goldstein, Lee E. Katz, Douglas I. Cantu, Robert C. Shenton, Martha E. Cummings, Jeffrey L. Reiman, Eric M. Stern, Robert A. Alosco, Michael L. Tripodis, Yorghos Farrer, Lindsay A. Stein, Thor D. Crary, John F. McKee, Ann C. Mez, Jesse Bioinformatics Graduate Program Boston University Boston MA United States Section of Biomedical Genetics Department of Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Department of Neurology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston University Alzheimer's Disease Research Center Boston University Chobanian & Avedisian School of Medicine Boston MA United States Boston VA Healthcare System Boston MA United States Boston University Chronic Traumatic Encephalopathy Center Boston University Boston MA United States Department of Pathology and Laboratory Medicine Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Pathology Neuroscience and Artificial Intelligence & Human Health Neuropathology Brain Bank & Research CoRE Friedman Brain Institute Ronald M. Loeb Center for Alzheimer's Disease Icahn School of Medicine at Mount Sinai New York NY United States Biostatistics and Epidemiology Data Analytics Center Boston University School of Public Health Boston MA United States Bedford VA Healthcare System Bedford MA United States Braintree Rehabilitation Hospital Braintree MA United States Department of Physical Medicine and Rehabilitation Harvard Medical School Boston MA United States Department of Rehabilitation and Human Performance Brain Injury Research Center Icahn School of Medicine at Mount Sinai New York NY United States Department of Neurology Icahn School of Medicine at Mount Sinai New York NY United States Department of Biostatistics Boston University School of Public Health Boston MA United States Department of Ophthalmology Boston University Chobanian & Avedisian School of Medicine Boston MA United States Departments of Biomedical Electrical & Computer Engineering Boston University College of Engineering Boston MA United States Departments of Radiology and Psychiatry Boston University Chobanian & Avedisia

Chronic traumatic encephalopathy (CTE) is a neurodegenerative tauopathy associated with repetitive head impact (RHI) exposure. Genetic variation in the 17q21.31 region, containing microtubule-associated protein tau (MAPT), has been implicated in tauopathies but has not been investigated in CTE. The region includes a megabase-long inversion (H1/H2) and copy-number variations, including α, β, and γ segments, which can be characterized as nine segregating structural haplotypes. We leveraged array SNP data and a reference panel across the 17q21.31 region to impute structural haplotypes and test their association with CTE endophenotypes in 447 European ancestry brain donors with RHI exposure. The H1β1γ1 haplotype was significantly associated with dementia and semi-quantitative tau burden in multiple cortical and medial temporal regions commonly affected in CTE. H1β1γ1 differential expression analyses in dorsolateral frontal cortex implicated cis-acting genes and inflammatory pathways. Taken together, the H1β1γ1 haplotype may help explain CTE heterogeneity among those with similar RHI exposure. © 2025 The Authors

关键词： 17q21.31 chronic traumatic encephalopathy dementia differential gene expression immune system MAPT repetitive head impacts structural haplotypes tauopathy traumatic brain injury

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Circuits of the cell

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Drug Discovery Today: BIOSILICO 2004年第3期2卷 120-126页

作者： Mellor, Joseph C. Delisi, Charles Bioinformatics Graduate Program Boston University Boston MA 02215 44 Cummington Street United States Department of Biomedical Engineering Boston University Boston MA 02215 44 Cummington Street United States

Networks of gene regulation control many aspects of cellular biology, ranging from development and differentiation to the cell cycle and apoptosis. However, the precise control of genetic regulation is poorly understood for whole cells and large systems. Technical achievements in the genome-wide measurement of DNA, mRNA and proteins - and their assorted interactions - have enabled systematic approaches to regulation in molecular biology, which promise to shed new light on the complex architecture of gene regulatory networks. Detailed knowledge of such systems is crucial for our understanding of molecular phenotypes;similarly, our ability to treat and cure many diseases will depend on our understanding of molecular disease at its regulatory and mechanistic roots.

关键词： bioinformatics biological networks genetic networks interactions regulatory models

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Evolution Arrests Invasions of Cooperative Populations

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Physical Review Letters 2015年第20期115卷 208104-208104页

作者： Kirill S. Korolev Department of Physics and Graduate Program in Bioinformatics Boston University Boston Massachusetts 02215 USA

Population expansions trigger many biomedical and ecological transitions, from tumor growth to invasions of non-native species. Although population spreading often selects for more invasive phenotypes, we show that this outcome is far from inevitable. In cooperative populations, mutations reducing dispersal have a competitive advantage. Such mutations then steadily accumulate at the expansion front, bringing invasion to a halt. Our findings are a rare example of evolution driving the population into an unfavorable state, and they could lead to new strategies to combat unwelcome invaders.

关键词： Evolutionary dynamics Mutation

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Public Good Diffusion Limits Microbial Mutualism

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Physical Review Letters 2015年第16期114卷 168102-168102页

作者： Rajita Menon Kirill S. Korolev Department of Physics and Graduate Program in Bioinformatics Boston University Boston Massachusetts 02215 USA

Standard game theory cannot describe microbial interactions mediated by diffusible molecules. Nevertheless, we show that one can still model microbial dynamics using game theory with parameters renormalized by diffusion. Contrary to expectations, greater sharing of metabolites reduces the strength of cooperation and leads to species extinction via a nonequilibrium phase transition. We report analytic results for the critical diffusivity and the length scale of species intermixing. Species producing slower public good is favored by selection when fitness saturates with nutrient concentration.

关键词： GAME theory MICROBIAL diversity METABOLITES DIFFUSION -- Measurement MUTUALISM

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Choroid plexus apocrine secretion shapes CSF proteome during mouse brain development

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Nature Neuroscience 2025年 1-14页

作者： Ya’el Courtney Joshua P. Head Neil Dani Frederick B. Shipley Maria K. Lehtinen Olga V. Chechneva Cameron Sadegh Yong Zhang Michael J. Holtzman Towia A. Libermann Department of Pathology Boston Children’s Hospital and Harvard Medical School Boston MA USA Graduate Program in Neuroscience Harvard Medical School Boston MA USA Department of Cell and Developmental Biology Vanderbilt University Nashville TN USA Graduate Program in Biophysics Harvard University Cambridge MA USA Department of Neurosurgery University of California Davis Sacramento CA USA Pulmonary and Critical Care Medicine Department of Medicine Washington University School of Medicine St. Louis MO USA Proteomics Bioinformatics and Systems Biology Center Beth Israel Deaconess Medical Center and Harvard Medical School Boston MA USA

The choroid plexus (ChP) regulates cerebrospinal fluid (CSF) composition, providing essential molecular cues for brain development; yet, embryonic ChP secretory mechanisms remain poorly defined. Here we identify apocrine secretion by embryonic ChP epithelial cells as a key regulator of the CSF proteome and neurodevelopment in male and female mice. We demonstrate that the activation of serotonergic 5-HT2Creceptors (by WAY-161503) triggers sustained Ca2+signaling, driving high-volume apocrine secretion in mouse and human ChP. This secretion alters the CSF proteome, stimulating neural progenitors lining the brain’s ventricles and shifting their developmental trajectory. Inducing ChP secretion in utero in mice disrupts neural progenitor dynamics, cerebral cortical architecture and offspring behavior. Additionally, illness or lysergic acid diethylamide exposure during pregnancy provokes coordinated ChP secretion in the mouse embryo. Our findings reveal a fundamental secretory pathway in the ChP that shapes brain development, highlighting how its disruption can have lasting consequences for brain health.

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Interplay between morphology and competition in two-dimensional colony expansion

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Physical Review E 2023年第3期108卷 L032301-L032301页

作者： Daniel W. Swartz Hyunseok Lee Mehran Kardar Kirill S. Korolev Department of Physics Graduate Program in Bioinformatics and Biological Design Center Boston University Boston Massachusetts 02215 USA

In growing populations, the fate of mutations depends on their competitive ability against the ancestor and their ability to colonize new territory. Here we present a theory that integrates both aspects of mutant fitness by coupling the classic description of one-dimensional competition (Fisher equation) to the minimal model of front shape (Kardar-Parisi-Zhang equation). We solve these equations and find three regimes, which are controlled solely by the expansion rates, solely by the competitive abilities, or by both. Collectively, our results provide a simple framework to study spatial competition.

关键词： Ecological population dynamics Front propagation Surface growth Coarse graining

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Retroactivity Affects the Adaptive Robustness of Transcriptional Regulatory Networks

Retroactivity Affects the Adaptive Robustness of Transcripti...

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American Control Conference

作者： Junmin Wang Calin Belta Bioinformatics Graduate Program Boston University Boston MA 02215 USA Division of Systems Engineering and the Bioinformatics Graduate Program Boston University Boston MA 02215 USA

ISBN: (纸本)9781538679012;9781538679265

Adaptation refers to the system's ability to respond transiently to an input signal and subsequently recover to the initial states. Adaptive robustness, the ability of a network to achieve adaptation, is subject to the loading effects arising from modular interconnections, known as retroactivity. Studying the effects of retroactivity on adaptive robustness facilitates the employment of retroactivity to improve circuit performance in synthetic biology. In this paper, we developed a framework for quantifying adaptive robustness via statistical model checking and used this framework to investigate the effects of retroactivity on adaptive robustness. We found that increasing retroactivity tends to raise adaptive robustness in networks where the output protein does not perform regulatory functions, such as incoherent feedforward loops.

关键词： Self tuning input signal Robustness Circuit optimization Model checking Frameworks synthetic biology Network Gene Regulatory Networks Regulatory

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