The Vav GEF Family: an Evolutionary and Functional Perspective
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Effects and Mechanisms of Eps8 on the Biological Behaviour of Malignant Tumours (Review)
824 ONCOLOGY REPORTS 45: 824-834, 2021 Effects and mechanisms of Eps8 on the biological behaviour of malignant tumours (Review) KAILI LUO1, LEI ZHANG2, YUAN LIAO1, HONGYU ZHOU1, HONGYING YANG2, MIN LUO1 and CHEN QING1 1School of Pharmaceutical Sciences and Yunnan Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming, Yunnan 650500; 2Department of Gynecology, Yunnan Tumor Hospital and The Third Affiliated Hospital of Kunming Medical University; Kunming, Yunnan 650118, P.R. China Received August 29, 2020; Accepted December 9, 2020 DOI: 10.3892/or.2021.7927 Abstract. Epidermal growth factor receptor pathway substrate 8 1. Introduction (Eps8) was initially identified as the substrate for the kinase activity of EGFR, improving the responsiveness of EGF, which Malignant tumours are uncontrolled cell proliferation diseases is involved in cell mitosis, differentiation and other physiological caused by oncogenes and ultimately lead to organ and body functions. Numerous studies over the last decade have demon- dysfunction (1). In recent decades, great progress has been strated that Eps8 is overexpressed in most ubiquitous malignant made in the study of genes and signalling pathways in tumours and subsequently binds with its receptor to activate tumorigenesis. Eps8 was identified by Fazioli et al in NIH-3T3 multiple signalling pathways. Eps8 not only participates in the murine fibroblasts via an approach that allows direct cloning regulation of malignant phenotypes, such as tumour proliferation, of intracellular substrates for receptor tyrosine kinases (RTKs) invasion, metastasis and drug resistance, but is also related to that was designed to study the EGFR signalling pathway. Eps8 the clinicopathological characteristics and prognosis of patients. -
The University of Chicago Epistasis, Contingency, And
THE UNIVERSITY OF CHICAGO EPISTASIS, CONTINGENCY, AND EVOLVABILITY IN THE SEQUENCE SPACE OF ANCIENT PROTEINS A DISSERTATION SUBMITTED TO THE FACULTY OF THE DIVISION OF THE BIOLOGICAL SCIENCES AND THE PRITZKER SCHOOL OF MEDICINE IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY GRADUATE PROGRAM IN BIOCHEMISTRY AND MOLECULAR BIOPHYSICS BY TYLER NELSON STARR CHICAGO, ILLINOIS AUGUST 2018 Table of Contents List of Figures .................................................................................................................... iv List of Tables ..................................................................................................................... vi Acknowledgements ........................................................................................................... vii Abstract .............................................................................................................................. ix Chapter 1 Introduction ......................................................................................................1 1.1 Sequence space and protein evolution .............................................................1 1.2 Deep mutational scanning ................................................................................2 1.3 Epistasis ...........................................................................................................3 1.4 Chance and determinism ..................................................................................4 1.5 Evolvability ......................................................................................................6 -
What Can We Learn from Fitness Landscapes?
What can we learn from fitness landscapes? The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Hartl, Daniel L. 2014. “What Can We Learn from Fitness Landscapes?” Current Opinion in Microbiology 21 (October): 51–57. doi:10.1016/j.mib.2014.08.001. Published Version 10.1016/j.mib.2014.08.001 Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:22898356 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Open Access Policy Articles, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#OAP Elsevier Editorial System(tm) for Current Opinion in Microbiology Manuscript Draft Manuscript Number: Title: What Can We Learn From Fitness Landscapes? Article Type: 22 Growth&Develop: prokaryotes (2014 Corresponding Author: Dr. Daniel Hartl, Corresponding Author's Institution: First Author: Daniel Hartl Order of Authors: Daniel Hartl Manuscript Click here to view linked References What Can We Learn From Fitness Landscapes? Daniel L. Hartl Department of Organismic and Evolutionary Biology Harvard University Cambridge, Massachusetts 02138 USA Contact information: Email: [email protected], TEL: 617-396-3917 In evolutionary biology, the fitness landscape of set of mutants is the mapping of genotypes onto phenotypes when the phenotype is fitness or some proxy for fitness such as growth rate or drug resistance. When the set of mutants is not too large, it is possible to create every possible combination of mutants and map these to fitness. -
Phenotypic Landscape Inference Reveals Multiple Evolutionary Paths to C4 Photosynthesis
RESEARCH ARTICLE elife.elifesciences.org Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis Ben P Williams1†, Iain G Johnston2†, Sarah Covshoff1, Julian M Hibberd1* 1Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom; 2Department of Mathematics, Imperial College London, London, United Kingdom Abstract C4 photosynthesis has independently evolved from the ancestral C3 pathway in at least 60 plant lineages, but, as with other complex traits, how it evolved is unclear. Here we show that the polyphyletic appearance of C4 photosynthesis is associated with diverse and flexible evolutionary paths that group into four major trajectories. We conducted a meta-analysis of 18 lineages containing species that use C3, C4, or intermediate C3–C4 forms of photosynthesis to parameterise a 16-dimensional phenotypic landscape. We then developed and experimentally verified a novel Bayesian approach based on a hidden Markov model that predicts how the C4 phenotype evolved. The alternative evolutionary histories underlying the appearance of C4 photosynthesis were determined by ancestral lineage and initial phenotypic alterations unrelated to photosynthesis. We conclude that the order of C4 trait acquisition is flexible and driven by non-photosynthetic drivers. This flexibility will have facilitated the convergent evolution of this complex trait. DOI: 10.7554/eLife.00961.001 Introduction *For correspondence: Julian. The convergent evolution of complex traits is surprisingly common, with examples including camera- [email protected] like eyes of cephalopods, vertebrates, and cnidaria (Kozmik et al., 2008), mimicry in invertebrates and †These authors contributed vertebrates (Santos et al., 2003; Wilson et al., 2012) and the different photosynthetic machineries of equally to this work plants (Sage et al., 2011a). -
Quantifying the Fitness of Tissue-Specific Evolutionary
bioRxiv preprint doi: https://doi.org/10.1101/401059; this version posted August 27, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC 4.0 International license. Quantifying the fitness of tissue- specific evolutionary trajectories by harnessing cancer’s repeatability at the genetic level Tokutomi N1, Moyret-Lalle C2, Puisieux A2, Sugano S1, Martinez P2. 1 Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo 108-8639, Japan. 2 Univ Lyon, Université Claude Bernard Lyon 1, INSERM 1052, CNRS 5286, Centre Léon Bérard, Cancer Research Center of Lyon, Lyon, 69008, France, INSERM U1052, Cancer Research Center of Lyon, Lyon, F-69008, France. Correspondence to Pierre Martinez: [email protected] Abstract Cancer is a potentially lethal disease, in which patients with nearly identical genetic backgrounds can develop a similar pathology through distinct combinations of genetic alterations. We aimed to reconstruct the evolutionary process underlying tumour initiation, using the combination of convergence and discrepancies observed across 2,742 cancer genomes from 9 tumour types. We developed a framework using the repeatability of cancer development to score the fitness of genetic clones, as their potential to malignantly progress and invade their environment of origin. Using this framework, we found that pre-malignant skin and colorectal lesions appeared specifically adapted to their local environment, yet insufficiently for full cancerous transformation. We found that metastatic clones were more adapted to the site of origin than to the invaded tissue, suggesting that genetics may be more important for local progression than for the invasion of distant organs. -
Insights Into Functional Connectivity in Mammalian Signal Transduction Pathways by Pairwise
bioRxiv preprint doi: https://doi.org/10.1101/2019.12.30.891200; this version posted December 30, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Insights into Functional Connectivity in Mammalian Signal Transduction Pathways by Pairwise Comparison of Protein Interaction Partners of Critical Signaling Hubs Chilakamarti V. Ramana * Department of Medicine, Dartmouth-Hitchcock Medical Center, Lebanon, NH 03766, USA *Correspondence should be addressed: Chilakamarti V .Ramana, Telephone. (603)-738-2507, E-mail: [email protected] ORCID ID: /0000-0002-5153-8252 1 bioRxiv preprint doi: https://doi.org/10.1101/2019.12.30.891200; this version posted December 30, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract Growth factors and cytokines activate signal transduction pathways and regulate gene expression in eukaryotes. Intracellular domains of activated receptors recruit several protein kinases as well as transcription factors that serve as platforms or hubs for the assembly of multi-protein complexes. The signaling hubs involved in a related biologic function often share common interaction proteins and target genes. This functional connectivity suggests that a pairwise comparison of protein interaction partners of signaling hubs and network analysis of common partners and their expression analysis might lead to the identification of critical nodes in cellular signaling. -
Correction for Barua and Mikheyev, an Ancient, Conserved Gene Regulatory Network Led to the Rise of Oral Venom Systems
Correction EVOLUTION Correction for “An ancient, conserved gene regulatory network led to the rise of oral venom systems,” by Agneesh Barua and Alexander S. Mikheyev, which was first published March 29, 2021; 10.1073/pnas.2021311118 (Proc. Natl. Acad. Sci. U.S.A. 118, e2021311118). The editors note that, due to a printer’s error, the article in- advertently published with a number of language errors. The article has been updated online to correct these errors. Published under the PNAS license. Published May 24, 2021. www.pnas.org/cgi/doi/10.1073/pnas.2108106118 CORRECTION PNAS 2021 Vol. 118 No. 22 e2108106118 https://doi.org/10.1073/pnas.2108106118 | 1of1 Downloaded by guest on October 1, 2021 An ancient, conserved gene regulatory network led to the rise of oral venom systems Agneesh Baruaa,1 and Alexander S. Mikheyeva,b aEcology and Evolution Unit, Okinawa Institute of Science and Technology Graduate University, Okinawa, 904-0495, Japan; and bEvolutionary Genomics Group, Australian National University, Canberra, ACT 0200, Australia Edited by Günter P. Wagner, Yale University, New Haven, CT, and approved February 11, 2021 (received for review October 27, 2020) Oral venom systems evolved multiple times in numerous verte- over time; this diminishes their utility in trying to understand brates, enabling the exploitation of unique predatory niches. Yet events that lead to the rise of venom systems in the nonvenom- how and when they evolved remains poorly understood. Up to ous ancestors of snakes (14, 15). now, most research on venom evolution has focused strictly on A gene coexpression network aims to identify genes that in- toxins. -
S41467-017-02329-Y.Pdf
ARTICLE DOI: 10.1038/s41467-017-02329-y OPEN The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy Dan A. Landau1,2,3, Clare Sun 4, Daniel Rosebrock2, Sarah E.M. Herman4, Joshua Fein1,3,5, Mariela Sivina6, Chingiz Underbayev4, Delong Liu4, Julia Hoellenriegel6, Sarangan Ravichandran7, Mohammed Z.H. Farooqui4, Wandi Zhang8, Carrie Cibulskis2, Asaf Zviran1,3, Donna S. Neuberg 9, Dimitri Livitz 2, Ivana Bozic10, Ignaty Leshchiner 2, Gad Getz 2, Jan A. Burger6, Adrian Wiestner4 & Catherine J. Wu2,8,11 1234567890 Treatment of chronic lymphocytic leukemia (CLL) has shifted from chemo-immunotherapy to targeted agents. To define the evolutionary dynamics induced by targeted therapy in CLL, we perform serial exome and transcriptome sequencing for 61 ibrutinib-treated CLLs. Here, we report clonal shifts (change >0.1 in clonal cancer cell fraction, Q < 0.1) in 31% of patients during the first year of therapy, associated with adverse outcome. We also observe tran- scriptional downregulation of pathways mediating energy metabolism, cell cycle, and B cell receptor signaling. Known and previously undescribed mutations in BTK and PLCG2,or uncommonly, other candidate alterations are present in seventeen subjects at the time of progression. Thus, the frequently observed clonal shifts during the early treatment period and its potential association with adverse outcome may reflect greater evolutionary capacity, heralding the emergence of drug-resistant clones. 1 New York Genome Center, New York, NY 10013, USA. 2 Broad Institute, Cambridge, MA 02142, USA. 3 Meyer Cancer Center & Institute of Computational Biomedicine, Weill Cornell Medicine, New York, NY 10065, USA. 4 Hematology Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA. -
The Role of the Src Homology-2 Domain Containing Protein B (SHB) in B Cells
M WELSH and others Role of SHB in b cells 56:1 R21–R31 Review The role of the Src Homology-2 domain containing protein B (SHB) in b cells Correspondence † Michael Welsh, Maria Jamalpour, Guangxiang Zang and Bjo¨rn Åkerblom should be addressed to M Welsh Department of Medical Cell Biology, Uppsala University, PO Box 571, Husargatan 3, SE-75123 Uppsala, Sweden Email †G Zang is now at Department of Medical Biosciences, Umea˚ University, Umea˚ , Sweden [email protected] Abstract This review will describe the SH2-domain signaling protein Src Homology-2 domain Key Words containing protein B (SHB) and its role in various physiological processes relating in " signal transduction particular to glucose homeostasis and b cell function. SHB operates downstream of several " insulin secretion tyrosine kinase receptors and assembles signaling complexes in response to receptor " vascular activation by interacting with other signaling proteins via its other domains (proline-rich, " islet cells phosphotyrosine-binding and tyrosine-phosphorylation sites). The subsequent responses " immune system are context-dependent. Absence of Shb in mice has been found to exert effects on hematopoiesis, angiogenesis and glucose metabolism. Specifically, first-phase insulin secretion in response to glucose was impaired and this effect was related to altered characteristics of focal adhesion kinase activation modulating signaling through Akt, ERK, b catenin and cAMP. It is believed that SHB plays a role in integrating adaptive responses to various stimuli by simultaneously modulating cellular responses in different cell-types, thus Journal of Molecular Journal of Molecular Endocrinology playing a role in maintaining physiological homeostasis. Endocrinology (2016) 56, R21–R31 Introduction The limited replicative capacity of human pancreatic (bTC1 cells) after serum-stimulation, the Src Homology-2 b cells contributes significantly to the development of domain containing adapter protein B (SHB) was identified diabetes mellitus and thus comprises a major hurdle for (Welsh et al. -
Genetics of Alternative Splicing Evolution During Sunflower Domestication
Genetics of alternative splicing evolution during sunflower domestication Chris C. R. Smitha,1, Silas Tittesa, J. Paul Mendietaa, Erin Collier-zansa, Heather C. Roweb,c, Loren H. Riesebergb, and Nolan C. Kanea aDepartment of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO 80309-0334; bDepartment of Botany, University of British Columbia, Vancouver, BC V6T 1Z4, Canada; and cInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA 19122-1801 Edited by Johanna Schmitt, University of California, Davis, CA, and approved May 18, 2018 (received for review February 27, 2018) Alternative splicing enables organisms to produce the diversity of studies report a high degree of splicing conservation among proteins necessary for multicellular life by using relatively few taxa (10), others report varying degrees of splicing differen- protein-coding genes. Although differences in splicing have been tiation among taxa, with more dissimilar groups having greater identified among divergent taxa, the shorter-term evolution of divergence in splicing (11). For example, there are genotype- splicing is understudied. The origins of novel splice forms, and the dependent splicing differences between tomato and (i)its contributions of alternative splicing to major evolutionary transi- relative Solanum habrochaites in response to cold stress (2) tions, are largely unknown. This study used transcriptomes of wild and (ii) its wild ancestor in response to growth environment and domesticated sunflowers to examine splice differentiation (12). Considerable evolution may be mediated by modifica- and regulation during domestication. We identified substantial tions in alternative splicing (11, 13, 14); however, little is splicing divergence between wild and domesticated sunflowers, known about the process of splice evolution and the role it mainly in the form of intron retention. -
COMP564: Advanced Computational Biology Methods and Research
COMP564: Advanced Computational Biology Methods and Research RNA sequence-structure maps and simulating the evolution of RNA populations Jérôme Waldispühl School of Computer Science, McGill RNA world In prebiotic world, RNA thought to have filled two distinct roles: 1. an information carrying role because of RNA's ability (in principle) to self-replicate, 2. a catalytic role, because of RNA's ability to form complicated 3D shapes. Over time, DNA replaced RNA in Its first role, while proteins replaced RNA in its second role. Principles Central assumptions: • The structure of a sequence can be determined using thermodynamics principles. • The structure determines the function. • Evolution tends to preserve and optimize the function. Figure from (Cowperthwaite&Meyers,2007) Outline • Mathematical modelling • Characterizing the evolutionary landscape • Evolutionary dynamics Sequence evolution For short sequences, the set of evolutionary operations can be restricted to: • Insertion • Insertion/Deletion • Mutation Figure from (Gobel,2000) Mutational landscape When the length of the sequence is fixed, the set of operations can be restricted to mutations. The mutation landscape is represented with Hamming graphs, where nodes are the sequences and edges connect sequences differing from one single nucleotide (i.e. 1 mutation). Figure from (Gobel,2000) Assigning a Phenotype Use folding programs (E.g. RNAfold, RNAstructure) to calculate the Phenotype. Usually, we assign a single structure (the M.F.E.) to the sequence but more sophisticated model have been proposed (i.e. plastic model). Figure from (Cowperthwaite&Meyers,2007) Evaluating structure similarities Hamming distance: Base pair distance: Base pair distance is the standard. It corresponds to the number of base pairs we have to remove and add to obtain one structure from the other. -
Simulating Natural Selection in Landscape Genetics
Molecular Ecology Resources (2012) 12, 363–368 doi: 10.1111/j.1755-0998.2011.03075.x Simulating natural selection in landscape genetics E. L. LANDGUTH,* S. A. CUSHMAN† and N. A. JOHNSON‡ *Division of Biological Sciences, University of Montana, Missoula, MT 59812, USA, †Rocky Mountain Research Station, United States Forest Service, Flagstaff, AZ 86001, USA, USA, ‡Department of Plant, Soil, and Insect Sciences and Graduate Program in Organismic and Evolutionary Biology, University of Massachusetts, Amherst, MA 01003, USA Abstract Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spa- tially-explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal panmictic populations in an allopatric setting in their predictions of population structure and frequency of fixation of adaptive alleles. We explore initial applications of a spatially-explicit, individual-based evolutionary landscape genetics program that incorporates all factors – mutation, gene flow, genetic drift and selection – that affect the frequency of an allele in a population. We incorporate natural selection by imposing differential survival rates defined by local relative fitness values on a landscape. Selection coefficients thus can vary not only for genotypes, but also in space as functions of local environmental variability. This simulator enables coupling of gene flow (governed by resistance surfaces), with natural selection (governed by selection surfaces). We validate the individual-based simulations under Wright-Fisher assumptions. We show that under isolation-by-distance processes, there are deviations in the rate of change and equilibrium values of allele frequency.