Literature DB >> 36208292

Uncovering pseudogenes and intergenic protein-coding sequences in TriTryps' genomes.

Mayla Abrahim1, Edson Machado2, Fernando Alvarez-Valín3, Antonio Basílio de Miranda4, Marcos Catanho4.   

Abstract

Trypanosomatids belong to a remarkable group of unicellular, parasitic organisms of the order Kinetoplastida, an early diverging branch of the phylogenetic tree of eukaryotes, exhibiting intriguing biological characteristics affecting gene expression (intronless polycistronic transcription, trans-splicing, and RNA editing), metabolism, surface molecules, and organelles (compartmentalization of glycolysis, variation of the surface molecules, and unique mitochondrial DNA), cell biology and life cycle (phagocytic vacuoles evasion, and intricate patterns of cell morphogenesis). With numerous genomic-scale data of several trypanosomatids becoming available since 2005 (genomes, transcriptomes, and proteomes), the scientific community can further investigate the mechanisms underlying these unusual features and address other unexplored phenomena possibly revealing biological aspects of the early evolution of eukaryotes. One fundamental aspect comprises the processes and mechanisms involved in the acquisition and loss of genes throughout the evolutionary history of these primitive microorganisms. Here, we present a comprehensive in silico analysis of pseudogenes in three major representatives of this group: Leishmania major, Trypanosoma brucei, and Trypanosoma cruzi. Pseudogenes, DNA segments originating from altered genes that lost their original function, are genomic relics that can offer an essential record of the evolutionary history of functional genes, as well as clues about the dynamics and evolution of hosting genomes. Scanning these genomes with functional proteins as proxies to reveal intergenic regions with protein-coding features, relying on a customized threshold to distinguish statistically and biologically significant sequence similarities, and reassembling remnant sequences from their debris, we found thousands of pseudogenes and hundreds of open reading frames (ORFs), with particular characteristics in each trypanosomatid: mutation profile, number, content, density, codon bias, average size, single- or multi-copy gene origin, number and type of mutations, putative primitive function, and transcriptional activity. These features suggest a common process of pseudogene formation, different patterns of pseudogene evolution and extant biological functions, and/or distinct genome organization undertaken by those parasites during evolution, as well as different evolutionary and/or selective pressures acting on distinct lineages.
© The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.

Entities:  

Keywords:  genomics; homology search; sequence alignment; trypanosomatids

Year:  2022        PMID: 36208292      PMCID: PMC9576210          DOI: 10.1093/gbe/evac142

Source DB:  PubMed          Journal:  Genome Biol Evol        ISSN: 1759-6653            Impact factor:   4.065


  48 in total

Review 1.  Using comparative genome analysis to identify problems in annotated microbial genomes.

Authors:  Maria S Poptsova; J Peter Gogarten
Journal:  Microbiology       Date:  2010-04-29       Impact factor: 2.777

2.  The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000.

Authors:  A Bairoch; R Apweiler
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

Review 3.  Pseudogenes as regulators of biological function.

Authors:  Ryan C Pink; David R F Carter
Journal:  Essays Biochem       Date:  2013       Impact factor: 8.000

4.  featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

Authors:  Yang Liao; Gordon K Smyth; Wei Shi
Journal:  Bioinformatics       Date:  2013-11-13       Impact factor: 6.937

5.  The genome of the African trypanosome Trypanosoma brucei.

Authors:  Matthew Berriman; Elodie Ghedin; Christiane Hertz-Fowler; Gaëlle Blandin; Hubert Renauld; Daniella C Bartholomeu; Nicola J Lennard; Elisabet Caler; Nancy E Hamlin; Brian Haas; Ulrike Böhme; Linda Hannick; Martin A Aslett; Joshua Shallom; Lucio Marcello; Lihua Hou; Bill Wickstead; U Cecilia M Alsmark; Claire Arrowsmith; Rebecca J Atkin; Andrew J Barron; Frederic Bringaud; Karen Brooks; Mark Carrington; Inna Cherevach; Tracey-Jane Chillingworth; Carol Churcher; Louise N Clark; Craig H Corton; Ann Cronin; Rob M Davies; Jonathon Doggett; Appolinaire Djikeng; Tamara Feldblyum; Mark C Field; Audrey Fraser; Ian Goodhead; Zahra Hance; David Harper; Barbara R Harris; Heidi Hauser; Jessica Hostetler; Al Ivens; Kay Jagels; David Johnson; Justin Johnson; Kristine Jones; Arnaud X Kerhornou; Hean Koo; Natasha Larke; Scott Landfear; Christopher Larkin; Vanessa Leech; Alexandra Line; Angela Lord; Annette Macleod; Paul J Mooney; Sharon Moule; David M A Martin; Gareth W Morgan; Karen Mungall; Halina Norbertczak; Doug Ormond; Grace Pai; Chris S Peacock; Jeremy Peterson; Michael A Quail; Ester Rabbinowitsch; Marie-Adele Rajandream; Chris Reitter; Steven L Salzberg; Mandy Sanders; Seth Schobel; Sarah Sharp; Mark Simmonds; Anjana J Simpson; Luke Tallon; C Michael R Turner; Andrew Tait; Adrian R Tivey; Susan Van Aken; Danielle Walker; David Wanless; Shiliang Wang; Brian White; Owen White; Sally Whitehead; John Woodward; Jennifer Wortman; Mark D Adams; T Martin Embley; Keith Gull; Elisabetta Ullu; J David Barry; Alan H Fairlamb; Fred Opperdoes; Barclay G Barrell; John E Donelson; Neil Hall; Claire M Fraser; Sara E Melville; Najib M El-Sayed
Journal:  Science       Date:  2005-07-15       Impact factor: 47.728

6.  InteractiVenn: a web-based tool for the analysis of sets through Venn diagrams.

Authors:  Henry Heberle; Gabriela Vaz Meirelles; Felipe R da Silva; Guilherme P Telles; Rosane Minghim
Journal:  BMC Bioinformatics       Date:  2015-05-22       Impact factor: 3.169

7.  Identification of positive and negative regulators in the stepwise developmental progression towards infectivity in Trypanosoma brucei.

Authors:  Justin Y Toh; Agathe Nkouawa; Saúl Rojas Sánchez; Huafang Shi; Nikolay G Kolev; Christian Tschudi
Journal:  Sci Rep       Date:  2021-03-11       Impact factor: 4.379

8.  CD-HIT Suite: a web server for clustering and comparing biological sequences.

Authors:  Ying Huang; Beifang Niu; Ying Gao; Limin Fu; Weizhong Li
Journal:  Bioinformatics       Date:  2010-01-06       Impact factor: 6.937

9.  Comparative genomic analysis of three Leishmania species that cause diverse human disease.

Authors:  Christopher S Peacock; Kathy Seeger; David Harris; Lee Murphy; Jeronimo C Ruiz; Michael A Quail; Nick Peters; Ellen Adlem; Adrian Tivey; Martin Aslett; Arnaud Kerhornou; Alasdair Ivens; Audrey Fraser; Marie-Adele Rajandream; Tim Carver; Halina Norbertczak; Tracey Chillingworth; Zahra Hance; Kay Jagels; Sharon Moule; Doug Ormond; Simon Rutter; Rob Squares; Sally Whitehead; Ester Rabbinowitsch; Claire Arrowsmith; Brian White; Scott Thurston; Frédéric Bringaud; Sandra L Baldauf; Adam Faulconbridge; Daniel Jeffares; Daniel P Depledge; Samuel O Oyola; James D Hilley; Loislene O Brito; Luiz R O Tosi; Barclay Barrell; Angela K Cruz; Jeremy C Mottram; Deborah F Smith; Matthew Berriman
Journal:  Nat Genet       Date:  2007-06-17       Impact factor: 38.330

10.  Quantitative proteome and phosphoproteome analyses highlight the adherent population during Trypanosoma cruzi metacyclogenesis.

Authors:  Juliana C Amorim; Michel Batista; Elizabeth S da Cunha; Aline C R Lucena; Carla V de Paula Lima; Karla Sousa; Marco A Krieger; Fabricio K Marchini
Journal:  Sci Rep       Date:  2017-08-29       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.