Literature DB >> 16603267

Assessing the potential of regions of the nuclear and mitochondrial genome to develop a "molecular tool box" for the detection and characterization of Phytophthora species.

Leonardo Schena1, David E L Cooke.   

Abstract

Four different intergenic regions of mitochondrial DNA (mt-IGS), a fragment of the intergenic spacer (IGS) region of the rDNA (rDNA-IGS), and a fragment of the ras-related protein (Ypt1) gene were amplified and sequenced from a panel of 31 Phytophthora species representing the most significant forest pathogens and the breadth of diversity in the genus. Over 80 kbp of novel sequences were generated and alignments showed very variable (introns and non-coding regions) as well as conserved coding regions. The mitochondrial DNA regions had an AT/GC ratio ranging from 67.2 to 89.0% and were appropriate for diagnostic development and phylogeographic analysis. The IGS fragment was less variable but still appropriate to discriminate amongst some important forest pathogens. The introns of the Ypt1 gene were sufficiently polymorphic for the development of molecular markers for almost all Phytophthora species, with more conserved flanking coding regions appropriate for the design of Phytophthora genus-specific primers. In general, phylogenetic analysis of the sequence alignments grouped species in clades that matched those based on the ITS regions of the rDNA. In many cases the resolution was improved over ITS but in other cases sequences were too variable to align accurately and yielded phylograms inconsistent with other data. Key studies on the intraspecific variation and primer specificity remain. However the research has already yielded an enormous dataset for the identification, detection and study of the molecular evolution of Phytophthora species.

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Year:  2006        PMID: 16603267     DOI: 10.1016/j.mimet.2006.03.003

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  15 in total

1.  Mitochondrial haplotype determination in the oomycete plant pathogen Phytophthora ramorum.

Authors:  Frank N Martin
Journal:  Curr Genet       Date:  2008-05-17       Impact factor: 3.886

2.  A Metabarcoding Survey on the Fungal Microbiota Associated to the Olive Fruit Fly.

Authors:  Antonino Malacrinò; Leonardo Schena; Orlando Campolo; Francesca Laudani; Saveria Mosca; Giulia Giunti; Cinzia Patricia Strano; Vincenzo Palmeri
Journal:  Microb Ecol       Date:  2016-09-29       Impact factor: 4.552

3.  Faster, simpler, more-specific methods for improved molecular detection of Phytophthora ramorum in the field.

Authors:  J A Tomlinson; I Barker; N Boonham
Journal:  Appl Environ Microbiol       Date:  2007-04-20       Impact factor: 4.792

4.  Incidence of endornaviruses in Phytophthora taxon douglasfir and Phytophthora ramorum.

Authors:  Zisis Kozlakidis; Neil A Brown; Atif Jamal; Xiyu Phoon; Robert H A Coutts
Journal:  Virus Genes       Date:  2009-11-14       Impact factor: 2.332

5.  Phytophthora taxa associated with cultivated Agathosma, with emphasis on the P. citricola complex and P. capensis sp. nov.

Authors:  C M Bezuidenhout; S Denman; S A Kirk; W J Botha; L Mostert; A McLeod
Journal:  Persoonia       Date:  2010-10-29       Impact factor: 11.051

6.  Host adaptation and speciation through hybridization and polyploidy in Phytophthora.

Authors:  Lien Bertier; Leen Leus; Liesbet D'hondt; Arthur W A M de Cock; Monica Höfte
Journal:  PLoS One       Date:  2013-12-26       Impact factor: 3.240

7.  Development of SCAR Markers for the Identification of Phytophthora katsurae Causing Chestnut Ink Disease in Korea.

Authors:  Dong Hyeon Lee; Sun Keun Lee; Sang Yong Lee; Jong Kyu Lee
Journal:  Mycobiology       Date:  2013-06-30       Impact factor: 1.858

8.  Use of genome sequence data in the design and testing of SSR markers for Phytophthora species.

Authors:  Leonardo Schena; Linda Cardle; David E L Cooke
Journal:  BMC Genomics       Date:  2008-12-19       Impact factor: 3.969

9.  Simultaneous detection and quantification of Phytophthora nicotianae and P. cactorum, and distribution analyses in strawberry greenhouses by duplex real-time PCR.

Authors:  Mingzhu Li; Minoru Inada; Hideki Watanabe; Haruhisa Suga; Koji Kageyama
Journal:  Microbes Environ       Date:  2013-04-24       Impact factor: 2.912

10.  Evaluation of Different PCR-Based Assays and LAMP Method for Rapid Detection of Phytophthora infestans by Targeting the Ypt1 Gene.

Authors:  Mehran Khan; Benjin Li; Yue Jiang; Qiyong Weng; Qinghe Chen
Journal:  Front Microbiol       Date:  2017-10-05       Impact factor: 5.640

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