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"Phylogenetic Profiling"
Introductory Review Phylogenetic p rofiling Matteo Pellegrini, Todd O. Yeates and David Eisenberg Howard Hughes Medical Institute, University of California at Los Angeles, Los Angeles, CA, USA Sorel T. Fitz-Gibbon IGPP Center for Astrobiology, University of California at Los Angeles, Los Angeles, CA, USA 1. Introduction Biology has been profoundly changed by the development of techniques to se- quence DNA. The advent of rapid sequencing in conjunction with the capability to assemble sequence fragments into complete genome sequences enables researchers to read and analyze entire genomes of organisms. Parallel progress has been made in algorithms to study the evolutionary history of proteins. The techniques rely on the ability to measure the similarity of protein sequences in order to determine the likelihood that different proteins are descended from a common ancestor. It is therefore possible to reconstruct families of proteins that share a common ancestor. Combining these two capabilities, we can now not only determine which proteins are coded within an organism’s genome but we can also discover the evolutionary relationships between the proteins of multiple organisms. Phylogenetic profiling is the study of which protein types are found in which organisms. In order to perform phylogenetic profiling, one must first establish a classification of proteins into families. An example of such a classification scheme across a broad range of fully sequenced organisms is the Clusters of Orthologous Groups (Tatusov, 1997), where an attempt is made to group together proteins that perform a similar function. Next, each organism is described in terms of which protein families are coded or not coded in its genome. -
Supplementary Information for Microbial Electrochemical Systems Outperform Fixed-Bed Biofilters for Cleaning-Up Urban Wastewater
Electronic Supplementary Material (ESI) for Environmental Science: Water Research & Technology. This journal is © The Royal Society of Chemistry 2016 Supplementary information for Microbial Electrochemical Systems outperform fixed-bed biofilters for cleaning-up urban wastewater AUTHORS: Arantxa Aguirre-Sierraa, Tristano Bacchetti De Gregorisb, Antonio Berná, Juan José Salasc, Carlos Aragónc, Abraham Esteve-Núñezab* Fig.1S Total nitrogen (A), ammonia (B) and nitrate (C) influent and effluent average values of the coke and the gravel biofilters. Error bars represent 95% confidence interval. Fig. 2S Influent and effluent COD (A) and BOD5 (B) average values of the hybrid biofilter and the hybrid polarized biofilter. Error bars represent 95% confidence interval. Fig. 3S Redox potential measured in the coke and the gravel biofilters Fig. 4S Rarefaction curves calculated for each sample based on the OTU computations. Fig. 5S Correspondence analysis biplot of classes’ distribution from pyrosequencing analysis. Fig. 6S. Relative abundance of classes of the category ‘other’ at class level. Table 1S Influent pre-treated wastewater and effluents characteristics. Averages ± SD HRT (d) 4.0 3.4 1.7 0.8 0.5 Influent COD (mg L-1) 246 ± 114 330 ± 107 457 ± 92 318 ± 143 393 ± 101 -1 BOD5 (mg L ) 136 ± 86 235 ± 36 268 ± 81 176 ± 127 213 ± 112 TN (mg L-1) 45.0 ± 17.4 60.6 ± 7.5 57.7 ± 3.9 43.7 ± 16.5 54.8 ± 10.1 -1 NH4-N (mg L ) 32.7 ± 18.7 51.6 ± 6.5 49.0 ± 2.3 36.6 ± 15.9 47.0 ± 8.8 -1 NO3-N (mg L ) 2.3 ± 3.6 1.0 ± 1.6 0.8 ± 0.6 1.5 ± 2.0 0.9 ± 0.6 TP (mg -
Table S4. Phylogenetic Distribution of Bacterial and Archaea Genomes in Groups A, B, C, D, and X
Table S4. Phylogenetic distribution of bacterial and archaea genomes in groups A, B, C, D, and X. Group A a: Total number of genomes in the taxon b: Number of group A genomes in the taxon c: Percentage of group A genomes in the taxon a b c cellular organisms 5007 2974 59.4 |__ Bacteria 4769 2935 61.5 | |__ Proteobacteria 1854 1570 84.7 | | |__ Gammaproteobacteria 711 631 88.7 | | | |__ Enterobacterales 112 97 86.6 | | | | |__ Enterobacteriaceae 41 32 78.0 | | | | | |__ unclassified Enterobacteriaceae 13 7 53.8 | | | | |__ Erwiniaceae 30 28 93.3 | | | | | |__ Erwinia 10 10 100.0 | | | | | |__ Buchnera 8 8 100.0 | | | | | | |__ Buchnera aphidicola 8 8 100.0 | | | | | |__ Pantoea 8 8 100.0 | | | | |__ Yersiniaceae 14 14 100.0 | | | | | |__ Serratia 8 8 100.0 | | | | |__ Morganellaceae 13 10 76.9 | | | | |__ Pectobacteriaceae 8 8 100.0 | | | |__ Alteromonadales 94 94 100.0 | | | | |__ Alteromonadaceae 34 34 100.0 | | | | | |__ Marinobacter 12 12 100.0 | | | | |__ Shewanellaceae 17 17 100.0 | | | | | |__ Shewanella 17 17 100.0 | | | | |__ Pseudoalteromonadaceae 16 16 100.0 | | | | | |__ Pseudoalteromonas 15 15 100.0 | | | | |__ Idiomarinaceae 9 9 100.0 | | | | | |__ Idiomarina 9 9 100.0 | | | | |__ Colwelliaceae 6 6 100.0 | | | |__ Pseudomonadales 81 81 100.0 | | | | |__ Moraxellaceae 41 41 100.0 | | | | | |__ Acinetobacter 25 25 100.0 | | | | | |__ Psychrobacter 8 8 100.0 | | | | | |__ Moraxella 6 6 100.0 | | | | |__ Pseudomonadaceae 40 40 100.0 | | | | | |__ Pseudomonas 38 38 100.0 | | | |__ Oceanospirillales 73 72 98.6 | | | | |__ Oceanospirillaceae -
Novel Methanotrophs of the Family Methylococcaceae from Different Geographical Regions and Habitats
Microorganisms 2015, 3, 484-499; doi:10.3390/microorganisms3030484 OPEN ACCESS microorganisms ISSN 2076-2607 www.mdpi.com/journal/microorganisms Article Novel Methanotrophs of the Family Methylococcaceae from Different Geographical Regions and Habitats Tajul Islam 1,*, Øivind Larsen 2, Vigdis Torsvik 1, Lise Øvreås 1, Hovik Panosyan 3, J. Colin Murrell 4, Nils-Kåre Birkeland 1 and Levente Bodrossy 5 1 Department of Biology, University of Bergen, Thormøhlensgate 53B, Postboks 7803, 5006 Bergen, Norway; E-Mails: [email protected] (V.T.); [email protected] (L.Ø.); [email protected] (N.-K.B.) 2 Uni Research Environment, Thormøhlensgate 49B, 5006 Bergen, Norway; E-Mail: [email protected] 3 Department of Microbiology, Plant and Microbe Biotechnology, Yerevan State University, A. Manoogian 1, 0025 Yarevan, Armenia; E-Mail: [email protected] 4 School of Environmental Sciences, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK; E-Mail: [email protected] 5 Commonwealth Scientific and Industrial Research Organization (CSIRO), Marine and Atmospheric Research and Wealth from Oceans National Research Flagship, Hobart, TAS 7004, Australia; E-Mail: [email protected] * Author to whom correspondence should be addressed; E-Mail: [email protected]; Tel./Fax: +47-5558-4400. Academic Editors: Ricardo Amils and Elena González Toril Received: 10 July 2015 / Accepted: 7 August 2015 / Published: 21 August 2015 Abstract: Terrestrial methane seeps and rice paddy fields are important ecosystems in the methane cycle. Methanotrophic bacteria in these ecosystems play a key role in reducing methane emission into the atmosphere. Here, we describe three novel methanotrophs, designated BRS-K6, GFS-K6 and AK-K6, which were recovered from three different habitats in contrasting geographic regions and ecosystems: waterlogged rice-field soil and methane seep pond sediments from Bangladesh; and warm spring sediments from Armenia. -
Pellegrini M. Using Phylogenetic Profiles To
Chapter 9 Using Phylogenetic Profiles to Predict Functional Relationships Matteo Pellegrini Abstract Phylogenetic profiling involves the comparison of phylogenetic data across gene families. It is possible to construct phylogenetic trees, or related data structures, for specific gene families using a wide variety of tools and approaches. Phylogenetic profiling involves the comparison of this data to determine which families have correlated or coupled evolution. The underlying assumption is that in certain cases these couplings may allow us to infer that the two families are functionally related: that is their function in the cell is coupled. Although this technique can be applied to noncoding genes, it is more commonly used to assess the function of protein coding genes. Examples of proteins that are functionally related include subunits of protein complexes, or enzymes that perform consecutive steps along biochemical pathways. We hypothesize the deletion of one of the families from a genome would then indirectly affect the function of the other. Dozens of different implementations of the phylogenetic profiling technique have been developed over the past decade. These range from the first simple approaches that describe phylogenetic profiles as binary vectors to the most complex ones that attempt to model to the coevolution of protein families on a phylogenetic tree. We discuss a set of these implementations and present the software and databases that are available to perform phylogenetic profiling. Key words: Phylogenetic profiles, Coevolution, Functional associations, Comparative genomics, Coevolving proteins 1. Introduction The remarkable improvements in sequencing technology that have occurred over the past few decades have made the sequenc- ing of genomes an ever more routine task. -
Downloaded from the Fungene Database (
bioRxiv preprint doi: https://doi.org/10.1101/2020.09.21.307504; this version posted September 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Enhancement of nitrous oxide emissions in soil microbial consortia via copper competition between proteobacterial methanotrophs and denitrifiers Jin Chang,a,b Daehyun Daniel Kim,a Jeremy D. Semrau,b Juyong Lee,a Hokwan Heo,a Wenyu Gu,b* Sukhwan Yoona# aDepartment of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon, 34141, Korea bDepartment of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, 48109 Running Title: Methanotrophic influence on N2O emissions #Address correspondence to Sukhwan Yoon, [email protected]. *Present address: Department of Civil & Environmental Engineering, Stanford University, Palo Alto CA, 94305 bioRxiv preprint doi: https://doi.org/10.1101/2020.09.21.307504; this version posted September 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract Unique means of copper scavenging have been identified in proteobacterial methanotrophs, particularly the use of methanobactin, a novel ribosomally synthesized post-translationally modified polypeptide that binds copper with very high affinity. The possibility that copper sequestration strategies of methanotrophs may interfere with copper uptake of denitrifiers in situ and thereby enhance N2O emissions was examined using a suite of laboratory experiments performed with rice paddy microbial consortia. Addition of purified methanobactin from Methylosinus trichosporium OB3b to denitrifying rice paddy soil microbial consortia resulted in substantially increased N2O production, with more pronounced responses observed for soils with lower copper content. -
The Phylogeny of Plant and Animal Pathogens in the Ascomycota
Physiological and Molecular Plant Pathology (2001) 59, 165±187 doi:10.1006/pmpp.2001.0355, available online at http://www.idealibrary.com on MINI-REVIEW The phylogeny of plant and animal pathogens in the Ascomycota MARY L. BERBEE* Department of Botany, University of British Columbia, 6270 University Blvd, Vancouver, BC V6T 1Z4, Canada (Accepted for publication August 2001) What makes a fungus pathogenic? In this review, phylogenetic inference is used to speculate on the evolution of plant and animal pathogens in the fungal Phylum Ascomycota. A phylogeny is presented using 297 18S ribosomal DNA sequences from GenBank and it is shown that most known plant pathogens are concentrated in four classes in the Ascomycota. Animal pathogens are also concentrated, but in two ascomycete classes that contain few, if any, plant pathogens. Rather than appearing as a constant character of a class, the ability to cause disease in plants and animals was gained and lost repeatedly. The genes that code for some traits involved in pathogenicity or virulence have been cloned and characterized, and so the evolutionary relationships of a few of the genes for enzymes and toxins known to play roles in diseases were explored. In general, these genes are too narrowly distributed and too recent in origin to explain the broad patterns of origin of pathogens. Co-evolution could potentially be part of an explanation for phylogenetic patterns of pathogenesis. Robust phylogenies not only of the fungi, but also of host plants and animals are becoming available, allowing for critical analysis of the nature of co-evolutionary warfare. Host animals, particularly human hosts have had little obvious eect on fungal evolution and most cases of fungal disease in humans appear to represent an evolutionary dead end for the fungus. -
PDF, Also Known As Version of Record
Downloaded from orbit.dtu.dk on: Dec 18, 2017 Aspergillus is monophyletic: Evidence from multiple gene phylogenies and extrolites profiles Kocsubé, S.; Perrone, G.; Magistà, D.; Houbraken, J.; Varga, J.; Szigeti, G.; Hubka, V.; Hong, S.-B.; Frisvad, Jens Christian; Samson, R.A. Published in: Studies in Mycology Link to article, DOI: 10.1016/j.simyco.2016.11.006 Publication date: 2016 Document Version Publisher's PDF, also known as Version of record Link back to DTU Orbit Citation (APA): Kocsubé, S., Perrone, G., Magistà, D., Houbraken, J., Varga, J., Szigeti, G., ... Samson, R. A. (2016). Aspergillus is monophyletic: Evidence from multiple gene phylogenies and extrolites profiles. Studies in Mycology, 85, 199-213. DOI: 10.1016/j.simyco.2016.11.006 General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. available online at www.studiesinmycology.org STUDIES IN MYCOLOGY 85: 199–213. Aspergillus is monophyletic: Evidence from multiple gene phylogenies and extrolites profiles S. -
Integrating Genomic Data to Predict Transcription Factor Binding
Integrating Genomic Data to Predict Transcription Factor Binding Dustin T. Holloway 1 Mark Kon 2 Charles DeLisi 3 [email protected] [email protected] [email protected] 1 Molecular Biology Cell Biology and Biochemistry, 3 Boston University, Boston, MA 02215, U.S.A. Bioinformatics and Systems Biology, 2 Boston University, Boston, MA 02215, U.S.A. Department of Mathematics and Statistics, Boston University, Boston, MA 02215 , U.S.A. Abstract Transcription factor binding sites (TFBS) in gene promoter regions are often predicted by using position specific scoring matrices (PSSMs), which summarize sequence patterns of experimentally determined TF binding sites. Although PSSMs are more reliable than simple consensus string matching in predicting a true binding site, they generally result in high numbers of false positive hits. This study attempts to reduce the number of false positive matches and generate new predictions by integrating various types of genomic data by two methods: a Bayesian allocation procedure, and support vector machine classification. Several methods will be explored to strengthen the prediction of a true TFBS in the Saccharomyces cerevisiae genome: binding site degeneracy, binding site conservation, phylogenetic profiling, TF binding site clustering, gene expression profiles, GO functional annotation, and k-mer counts in promoter regions. Binding site degeneracy (or redundancy) refers to the number of times a particular transcription factor’s binding motif is discovered in the upstream region of a gene. Phylogenetic conservation takes into account the number of orthologous upstream regions in other genomes that contain a particular binding site. Phylogenetic profiling refers to the presence or absence of a gene across a large set of genomes. -
Chapter 9: Historic Preservation
CHAPTER 9: HISTORIC PRESERVATION 9.1 Auburn Historic Preservation Commission he City of Auburn has a rich and diverse history. Organized efforts to preserve locally significant historic and cultural resources allow the City to recognize and protect its past, while T simultaneously planning for future development and growth. Preservation planning, or a lack thereof, can have a significant impact not only on aesthetic appearance, but on the unique sense of place created by a community. The Auburn Historic Preservation Commission (AHPC), the City’s governing body concerning issues of preservation, was created on March 2, 1999 with the passage of Ordinance 1818 by City Council. The Commission is comprised of seven members, and is intended to meet several essential needs. For the community, it assures that Auburn’s historic resources are maintained in a manner appropriate to the City’s heritage. For property owners, residents and contractors, it provides primary guidance in the planning and design of projects that are sympathetic to the special character of the historic district; and that will, in turn, assure that property values are maintained and enhanced. 9.2 North College Historic District On June 21, 2005 the City Council passed Ordinance 2302, which gave the AHPC the task of recommending designation of historic districts and properties in the city. These recommendations are presented to the Council, which then reviews them for final action. The City’s first locally designated district, the North College Historic District, contains 37 parcels north of downtown Auburn and was officially designated by Ordinance 2377 on March 21, 2006. All of the properties in the North College Historic District lie within the boundaries of the Old Main and Church Street District, a National Register of His toric Places District designated in 1978. -
Scalable Phylogenetic Profiling Using Minhash Uncovers Likely Eukaryotic Sexual Reproduction Genes
bioRxiv preprint doi: https://doi.org/10.1101/852491; this version posted November 22, 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 4.0 International license. 1 Scalable Phylogenetic Profiling using MinHash Uncovers Likely Eukaryotic Sexual Reproduction Genes 1,2,3,* 1,2,3 4,5 1,2,3,6,7,* David Moi , Laurent Kilchoer , Pablo S. Aguilar and Christophe Dessimoz 1 2 Department of Computational Biology, University of Lausanne, Switzerland; Center for Integrative Genomics, 3 4 University of Lausanne, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland; Instituto de 5 Investigaciones Biotecnologicas (IIBIO), Universidad Nacional de San Martín Buenos Aires, Argentina; Instituto de 6 Fisiología, Biología Molecular y Neurociencias (IFIBYNE-CONICET), Department of Genetics, Evolution, and 7 Environment, University College London, UK; Department of Computer Science, University College London, UK. *Corresponding authors: [email protected] and [email protected] Abstract Phylogenetic profiling is a computational method to predict genes involved in the same biological process by identifying protein families which tend to be jointly lost or retained across the tree of life. Phylogenetic profiling has customarily been more widely used with prokaryotes than eukaryotes, because the method is thought to require many diverse genomes. There are now many eukaryotic genomes available, but these are considerably larger, and typical phylogenetic profiling methods require quadratic time or worse in the number of genes. We introduce a fast, scalable phylogenetic profiling approach entitled HogProf, which leverages hierarchical orthologous groups for the construction of large profiles and locality-sensitive hashing for efficient retrieval of similar profiles. -
Grasses of the Texas Hill Country: Vegetative Key and Descriptions
Hagenbuch, K.W. and D.E. Lemke. 2015. Grasses of the Texas Hill Country: Vegetative key and descriptions. Phytoneuron 2015-4: 1–93. Published 7 January 2015. ISSN 2153 733X GRASSES OF THE TEXAS HILL COUNTRY: VEGETATIVE KEY AND DESCRIPTIONS KARL W. HAGENBUCH Department of Biological Sciences San Antonio College 1300 San Pedro Avenue San Antonio, Texas 78212-4299 [email protected] DAVID E. LEMKE Department of Biology Texas State University 601 University Drive San Marcos, Texas 78666-4684 [email protected] ABSTRACT A key and a set of descriptions, based solely on vegetative characteristics, is provided for the identification of 66 genera and 160 grass species, both native and naturalized, of the Texas Hill Country. The principal characters used (features of longevity, growth form, roots, rhizomes and stolons, culms, leaf sheaths, collars, auricles, ligules, leaf blades, vernation, vestiture, and habitat) are discussed and illustrated. This treatment should prove useful at times when reproductive material is not available. Because of its size and variation in environmental conditions, Texas provides habitat for well over 700 species of grasses (Shaw 2012). For identification purposes, the works of Correll and Johnston (1970); Gould (1975) and, more recently, Shaw (2012) treat Texas grasses in their entirety. In addition to these comprehensive works, regional taxonomic treatments have been done for the grasses of the Cross Timbers and Prairies (Hignight et al. 1988), the South Texas Brush Country (Lonard 1993; Everitt et al. 2011), the Gulf Prairies and Marshes (Hatch et al. 1999), and the Trans-Pecos (Powell 1994) natural regions. In these, as well as in numerous other manuals and keys, accurate identification of grass species depends on the availability of reproductive material.