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Comparative Genomics 1

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丛书名： Methods in Molecular Biology

1000年

作者： Nicholas H. Bergman

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Multitissue single-cell analysis reveals differential cellular and molecular sensitivity between fructose and high-fat high-sucrose diets

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Cell reports 2025年第5期44卷 115690页

作者： Yen-Wei Chen In Sook Ahn Susanna Sue-Ming Wang Sana Majid Graciel Diamante Ingrid Cely Guanglin Zhang Angelus Cabanayan Sergey Komzyuk Jack Bonnett Douglas Arneson Xia Yang Department of Integrative Biology & Physiology University of California Los Angeles Los Angeles CA USA Interdepartmental Program of Molecular Toxicology University of California Los Angeles Los Angeles CA USA. Department of Integrative Biology & Physiology University of California Los Angeles Los Angeles CA USA. Interdepartmental Program of Bioinformatics University of California Los Angeles Los Angeles CA USA. Interdepartmental Program of Molecular Toxicology University of California Los Angeles Los Angeles CA USA Interdepartmental Program of Bioinformatics University of California Los Angeles Los Angeles CA USA Department of Molecular and Medical Pharmacology University of California Los Angeles Los Angeles CA USA. Electronic address: xyang123@ucla.edu.

Metabolic syndrome (MetS), a conglomerate of dysregulated metabolic traits that vary between individuals, is partially driven by modern diets high in fat, sucrose, or fructose and their interactions with host genes in metabolic tissues. To elucidate the roles of individual tissues and cell types in diet-induced MetS, we performed single-cell RNA sequencing on the hypothalamus, liver, adipose tissue, and small intestine of mice fed high-fat high-sucrose (HFHS) or fructose diets. We found that hypothalamic neurons were sensitive to fructose, while adipose progenitor cells and macrophages were responsive to HFHS. Ligand-receptor analysis revealed lipid metabolism and inflammation networks among peripheral tissues driven by HFHS, while both diets stimulated synaptic remodeling within the hypothalamus. mt-Rnr2, a top responder to both diets, mitigated diet-induced MetS by stimulating thermogenesis. Our study demonstrates that HFHS and fructose diets have differential cell type and network targets but also share regulators such as mt-Rnr2 to affect MetS risk.

关键词： CP: Metabolism SVF adipose stromal vascular fraction fructose diet high-fat high-sucrose diet hypothalamus liver metabolic syndrome single-cell RNA-seq small intestine tissue crosstalk

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Nuclear Factor I/A Controls A-fiber Nociceptor Development

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Neuroscience Bulletin 2020年第7期36卷 685-695页

作者： Lu Qi Guangjuan Yin Yongchao Zhang Yeqi Tao Xiaohua Wu Richard M.Gronostajski Mengsheng Qiu Yang Liu College of Life Sciences Zhejiang UniversityHangzhou 310058China Zhejiang Key Laboratory of Organ Development and Regeneration Institute of Life SciencesHangzhou Normal UniversityHangzhou 310036China Department of Biochemistry Program in GeneticsGenomics and BioinformaticsCenter of Excellence in Bioinformatics and Life SciencesState University of New York at BuffaloBuffaloNY 14203USA

Noxious mechanical information is transmitted through molecularly distinct nociceptors,with pinprickevoked sharp sensitivity via A-fiber nociceptors marked by developmental expression of the neuropeptide Y receptor 2(Npy2 r)and von Frey filament-evoked punctate pressure information via unmyelinated C fiber nociceptors marked by ***,the molecular programs controlling their development are only beginning to be *** we demonstrate that Npy2 r-expressing sensory neurons are in fact divided into two groups,based on transient or persistent Npy2 r ***2 r-transient neurons are myelinated,likely including A-fiber nociceptors,whereas Npy2 r-persistent ones belong to unmyelinated pruriceptors that co-express *** then showed that the transcription factors NFIA and Runx1 are necessary for the development of Npy2 r-transient A-fiber nociceptors and MrgprD^+C-fiber nociceptors,***,mice with conditional knockout of Nfia,but not Runx1 showed a marked attenuation of pinprick-evoked nocifensive *** studies therefore identify a transcription factor controlling the development of myelinated nociceptors.

关键词： Dorsal root ganglion Acute pain Pinprick pain Npy2r Nppb Nociceptor A-fiber mechanonociceptor

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Recovering the tree-like trend of evolution despite extensive lateral genetic transfer: A probabilistic analysis

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16th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2012

作者： Roch, Sebastien Snir, Sagi Department of Mathematics Bioinformatics Program UCLA United States Institute of Evolution University of Haifa Haifa 31905 Israel

ISBN: (纸本)9783642296260

Lateral gene transfer (LGT) is a common mechanism of non-vertical evolution where genetic material is transferred between two more or less distantly related organisms. It is particularly common in bacteria where it contributes to adaptive evolution with important medical implications. In evolutionary studies, LGT has been shown to create widespread discordance between gene trees as genomes become mosaics of gene histories. In particular, the Tree of Life has been questioned as an appropriate representation of bacterial evolutionary history. Nevertheless a common hypothesis is that prokaryotic evolution is primarily tree-like, but that the underlying trend is obscured by LGT. Extensive empirical work has sought to extract a common tree-like signal from conflicting gene trees. Here we give a probabilistic perspective on the problem of recovering the tree-like trend despite LGT. Under a model of randomly distributed LGT, we show that the species phylogeny can be reconstructed even in the presence of surprisingly many (almost linear number of) LGT events per gene tree. Our results, which are optimal up to logarithmic factors, are based on the analysis of a robust, computationally efficient reconstruction method and provides insight into the design of such methods. Finally we show that our results have implications for the discovery of highways of gene sharing. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Genes

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Local Sparse Component Analysis for Blind Source Separation: An application to resting state FMRI 36

Local Sparse Component Analysis for Blind Source Separation:...

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2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

作者： Vieira, Gilson Amaro, Edson Baccala, Luiz A. Inter-institutional Grad Program on Bioinformatics Universidade de São Paulo São Paulo Brazil

ISBN: (纸本)9781424479290

We propose a new Blind Source Separation technique for whole-brain activity estimation that best profits from FMRI's intrinsic spatial sparsity. The Local Sparse Component Analysis (LSCA) combines wavelet analysis, group-separable regularizers, contiguity-constrained clusterization and principal components analysis (PCA) into a unique spatial sparse representation of FMRI images towards efficient dimensionality reduction without sacrificing physiological characteristics by avoiding artificial stochastic model constraints. The LSCA outperforms classical PCA source reconstruction for artificial data sets over many noise levels. A real FMRI data illustration reveals resting-state activities in regions hard to observe, such as thalamus and basal ganglia, because of their small spatial scale. © 2014 IEEE.

关键词： Blind source separation Correlation Principal component analysis Signal to noise ratio Sparse matrices Vectors Wavelet packets

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Characterizing Emergency Department Care for Patients With Histories of Incarceration

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JACEP Open 2025年第1期6卷 100022-100022页

作者： Huang, Thomas Socrates, Vimig Ovchinnikova, Polina Faustino, Isaac Kumar, Anusha Safranek, Conrad Chi, Ling Wang, Emily A. Puglisi, Lisa Wong, Ambrose H. Wang, Karen H. Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Department for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States SEICHE Center for Health and Justice Yale School of Medicine New Haven CT United States Equity Research and Innovation Center Yale School of Medicine Yale University New Haven CT United States

Objectives: Patients with a history of incarceration experience bias from health care team members, barriers to privacy, and a multitude of health care disparities. We aimed to assess care processes delivered in emergency departments (EDs) for people with histories of incarceration. Methods: We utilized a fine-tuned large language model to identify patient incarceration status from 480,374 notes from the ED setting. We compared socio-demographic characteristics, comorbidities, and care processes, including disposition, restraint use, and sedation, between individuals with and without a history of incarceration. We then conducted multivariable logistic regression to assess the independent correlation of incarceration history and management in the ED while adjusting for demographic characteristics, health behaviors, presentation, and past medical history. Results: We found 1734 unique patient encounters with a history of incarceration from a total of 177,987 encounters. Patients with history of incarceration were more likely to be male, Black, Hispanic, or other race/ethnicity, currently unemployed or disabled, and had smoking and substance use histories, compared with those without. This cohort demonstrated higher odds of elopement (OR: 3.59 [95% CI: 2.41–5.12]), leaving against medical advice (OR: 2.39 [95% CI: 1.46–3.67]), and being subjected to sedation (OR: 3.89 [95% CI: 3.19–4.70]) and restraint use (OR: 3.76 [95% CI: 3.06–4.57]). After adjusting for covariates, the association between incarceration and elopement remained significant (adjusted odds ratio: 1.65 [95% CI: 1.08–2.43]), while associations with other dispositions, restraint use, and sedation did not persist. Conclusion: This study identified differences in patient characteristics and care processes in the ED for patients with histories of incarceration and demonstrated the potential of using natural language processing in measuring care processes in populations that are largely hidden, but highly prev

关键词： artificial intelligence emergency medicine incarceration large language models quality of health care

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A randomized algorithm for aligning DNA sequences to reference genomes

A randomized algorithm for aligning DNA sequences to referen...

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2013 IEEE 3rd International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2013

作者： Vo, Nam S. Tran, Quang Niraula, Nobal Phan, Vinhthuy Department of Computer Science United States Bioinformatics Program University of Memphis Memphis TN 38152 United States

ISBN: (纸本)9781479907144

The alignment of reads generated by nextgeneration sequencers is an important problem in many biomedical applications. Although many methods have been proposed, we introduce a new randomized algorithm with the distinction of having high performance across a wide range of read lengths and base error rates. We utilize two FM indices to facilitate efficient bidirectional searching. Randomization allows us to estimate effectively key parameters, which ultimately account for the consistency in performance of the method. Our method by and large outperformed some of the recent and popular methods over a wide range of read lengths and base error rates. © 2013 IEEE.

关键词： DNA sequences

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An analysis of conformational changes upon RNA-Protein binding 14

An analysis of conformational changes upon RNA-Protein bindi...

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5th ACM Conference on bioinformatics, Computational Biology, and Health Informatics, ACM BCB 2014

作者： Sankar, Kannan Jernigan, Robert L. Walia, Rasna R. Honavar, Vasant G. Mann, Carla M. Dobbs, Drena Bioinformatics and Computational Biology Program Dept. of Biochem. Biophysics and Molecular Biology Iowa State University United States Dept. of Biochem. L.H. Baker Center for Bioinformatics and Biological Statistics Iowa State University United States Bioinformatics and Computational Biology Program Dept. of Computer Science Iowa State University United States Bioinformatics and Genomics Program College of Information Sciences and Technology Pennsylvania State University United States Dept. of Genetics Development and Cell Biology L.H. Baker Center for Bioinformatics Iowa State University United States

ISBN: (纸本)9781450328944

RNA-binding proteins (RBPs) have myriad functions in transcription, translation, and post-transcriptional gene regulation, with central roles in normal development as well as in both genetic and infectious diseases. When a protein binds RNA, a conformational change often occurs. For RNA-protein complexes that have been characterized, conformational changes have been observed in the protein, the RNA, or both. These conformational changes have not been sufficiently characterized, however, in part due to the small number of structures of bound and unbound complexes of RNA-binding proteins available until recently. Here we systematically analyze a new dataset of 90 pairs of bound and unbound proteins to evaluate the conformational changes that occur upon RNA binding. Most of the conformational changes were observed in noninterfacial regions of the RNA-binding proteins. Detailed analyses of the modes of RNA binding and any associated conformational changes in proteins are critical for fully understanding the mechanisms of RNA-protein recognition, for developing better RNA-protein docking methods and methods for predicting interfacial residues, and for RNA-based drug design. Copyright © 2014 ACM.

关键词： RNA

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MorPhiC Consortium: towards functional characterization of all human genes

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Nature 2025年第8050期638卷 351-359页

作者： Adli, Mazhar Przybyla, Laralynne Burdett, Tony Burridge, Paul W. Cacheiro, Pilar Chang, Howard Y. Engreitz, Jesse M. Gilbert, Luke A. Greenleaf, William J. Hsu, Li Huangfu, Danwei Hung, Ling-Hong Kundaje, Anshul Li, Shuzhao Parkinson, Helen Qiu, Xiaojie Robson, Paul Schürer, Stephan C. Shojaie, Ali Skarnes, William C. Smedley, Damian Studer, Lorenz Sun, Wei Vidović, Dušica Vierbuchen, Thomas White, Brian S. Yeung, Ka Yee Yue, Feng Zhou, Ting Žurauskienė, Justina Zhong, Aaron Zheng, Shujian Zhao, Hengqiang Zhang, Nan Zhang, Zhehao Zhang, Stephen Zeng, Tony Yu, Bo Yordanova, Galabina N. Yang, Dapeng Xing, De Wang, Xianming Wang, Ping Torre, Denis Tang, Wenzhuo Shivalikanjli, Anu Sengupta, Kaustav Seker, Fidan Ventura, Enrique Sapena Ross, Nicolette C. Rivera-Diaz, Jamilex Rana, Arushi Pongpamorn, Praeploy Poirion, Olivier B. Pillai, Ajay Pilarczyk, Marcin Parker, Devon Ning, Gang Neyisci, Ozlem Nasam, Niharika Mittal, Varun Mitchell, Joshua M. Metzl-Raz, Eyal Meng, Chen Melo-Carrillo, Adrian McDonough, Justin A. Marengo, Gabriel Mao, Yuzhen Leite, Davi Lyra Luo, Renhe Liu, Nianping Liu, Dingyu Liu, Zukai Liu, Si Li, Zhaoheng Kraft, Katerina Koci, Orges A. Kirsammer, Gina Kendra, Angelina Hutter, Carolyn Huebner, Aaron J. Huang, Yung-Hsin Hu, Nan Gupta, Dipayan Gupta, Revant Guo, Tingfeng Griffiths, Alexandra M. Goyal, Juhee Glenn, Rachel A. Garofalo, Jessica L. Fukuda, Bryce Nobutoshi Fu, Yihao Flynn, William F. Flores, Jesse Fletcher, Colin F. Fleming, Patrick J. Felsenfeld, Adam L. Eraslan, Basak Doty, Anthony Dahlstrom, Thomas J. Chung, Caty E. Choudhary, Anshul Cho, Hyein S. Chen, Xintong Chen, Sijie Chan, Chia Baroch, Jacob J. Baker, Dylan S. Bai, Tao Avireddy, Rohan N. V. S. R. K. Amiri, Anahita Diniz, Juliana Alcoforado Abbaszadeh, Neda Robert H. Lurie Comprehensive Cancer Center Department of Obstetrics and Gynecology Northwestern University Feinberg School of Medicine Chicago IL United States Department of Biochemistry and Biophysics University of California San Francisco CA United States Omics Section European Bioinformatics Institute (EMBL-EBI) European Molecular Biology Laboratory Hinxton United Kingdom Department of Pharmacology Center for Pharmacogenomics Northwestern University Feinberg School of Medicine Evanston IL United States William Harvey Research Institute Clinical Pharmacology and Precision Medicine Queen Mary University of London London United Kingdom Department of Dermatology Stanford University Stanford CA United States Department of Genetics Stanford University Stanford CA United States Basic Science and Engineering (BASE) Initiative Stanford University Stanford CA United States Department of Urology University of California San Francisco CA United States Department of Biostatistics Public Health Sciences Fred Hutchinson Cancer Center Seattle WA United States Developmental Biology Program Sloan Kettering Institute New York NY USA School of Engineering and Technology University of Washington Tacoma Tacoma WA United States Departments of Genetics and Computer Science Stanford University Stanford CA United States Jackson Laboratory for Genomic Medicine Farmington CT United States Knowledge Management Section European Bioinformatics Institute (EMBL-EBI) European Molecular Biology Laboratory Hinxton United Kingdom Molecular and Cellular Pharmacology Sylvester Comprehensive Cancer Center University of Miami Coral Gables FL USA Department of Biostatistics University of Washington Seattle WA United States Department of Biochemistry and Molecular Genetics Robert H. Lurie Comprehensive Cancer Center Northwestern University Feinberg School of Medicine Chicago IL United States

Recent advances in functional genomics and human cellular models have substantially enhanced our understanding of the structure and regulation of the human genome. However, our grasp of the molecular functions of human genes remains incomplete and biased towards specific gene classes. The Molecular Phenotypes of Null Alleles in Cells (MorPhiC) Consortium aims to address this gap by creating a comprehensive catalogue of the molecular and cellular phenotypes associated with null alleles of all human genes using in vitro multicellular systems. In this Perspective, we present the strategic vision of the MorPhiC Consortium and discuss various strategies for generating null alleles, as well as the challenges involved. We describe the cellular models and scalable phenotypic readouts that will be used in the consortium's initial phase, focusing on 1,000 protein-coding genes. The resulting molecular and cellular data will be compiled into a catalogue of null-allele phenotypes. The methodologies developed in this phase will establish best practices for extending these approaches to all human protein-coding genes. The resources generated-including engineered cell lines, plasmids, phenotypic data, genomic information and computational tools-will be made available to the broader research community to facilitate deeper insights into human gene functions. © 2025. Springer Nature Limited.

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Anticonvulsant-induced dyskinesia

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Expert Opinion on Drug Safety 2003年第4期2卷 385-393页

作者： Zaatreh, Megdad M. Epilepsy Surgery Program University of North Carolina Department of Neurology Chapel Hill NC 27599-7025 3114 Bioinformatics United States

Anticonvulsant-induced dyskinesia (AID) is an underdiagnosed side effect of many anticonvulsants that may take place during initial or chronic treatment at normal or toxic drug levels. The occurrence of AID subjects the patient to another medical condition and may prompt an extensive work-up. Similarities with other drug-induced dyskinesias and some animal studies suggest that dopaminergic dysfunction in the basal ganglia is pivotal in the occurrence of dyskinesia. Clinical presentation and outcomes are variable;however, in most cases, dyskinesias respond well to anticonvulsant withdrawal. Enhancing the awareness of AID is important in light of the recent development of many new anticonvulsants and their wider clinical use. © Ashley Publications Ltd.

关键词： adverse effects anticonvulsants dyskinesia epilepsy movement disorders

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