scholarly journals Identification of Rhizoctonia solani associated with soybean in Brazil by rDNA-ITS sequences

2003 ◽  
Vol 28 (4) ◽  
pp. 413-419 ◽  
Author(s):  
Roseli C. Fenille ◽  
Maísa B. Ciampi ◽  
Eiko E. Kuramae ◽  
Nilton L. Souza
Keyword(s):  
Nucleotide Sequence ◽  
Rhizoctonia Solani ◽  
Gene Sequence ◽  
Sequence Similarity ◽  
5.8S Rdna ◽  
Nucleotide Sequence Similarity ◽  
Rdna Its ◽  
Foliar Blight ◽  
Rdna Its Sequences ◽  
Its1 And Its2

The aim of this study was to identify isolates of Rhizoctonia solani causing hypocotyl rot and foliar blight in soybean (Glycine max) in Brazil by the nucleotide sequences of ITS-5.8S regions of rDNA. The 5.8S rDNA gene sequence (155 bp) was highly conserved among all isolates but differences in length and nucleotide sequence of the ITS1 and ITS2 regions were observed between soybean isolates and AG testers. The similarity of the nucleotide sequence among AG-1 IA isolates, causing foliar blight, was 95.1-100% and 98.5-100% in the ITS1 and ITS2 regions, respectively. The nucleotide sequence similarity among subgroups IA, IB and IC ranged from 84.3 to 89% in ITS1 and from 93.3 to 95.6% in ITS2. Nucleotide sequence similarity of 99.1% and 99.3-100% for ITS1 and ITS2, respectively, was observed between AG-4 soybean isolates causing hypocotyl rots and the AG-4 HGI tester. The similarity of the nucleotide sequence of the ITS-5.8S rDNA region confirmed that the R. solani Brazilian isolates causing foliar blight are AG-1 IA and isolates causing hypocotyl rot symptoms are AG-4 HGI. The ITS-5.8S rDNA sequence was not determinant for the identification of the AG-2-2 IIIB R. solani soybean isolate.

scholarly journals Rhizoctonia solani AG-1 IA infects both rice and signalgrass in the Colombian Llanos

2016 ◽  
Vol 46 (1) ◽  
pp. 65-71 ◽  
Author(s):  
Lina Maria Ramos-Molina ◽  
Edisson Chavarro-Mesa ◽  
Danilo Augusto dos Santos Pereira ◽  
María del Rosario Silva-Herrera ◽  
Paulo Cezar Ceresini
Keyword(s):  
Rhizoctonia Solani ◽  
Species Complex ◽  
Molecular Detection ◽  
Sheath Blight ◽  
Pathogenicity Test ◽  
Rice Sheath Blight ◽  
Specific Primers ◽  
5.8S Rdna ◽  
Foliar Blight ◽  
Rhizoctonia Oryzae

ABSTRACT Foliar blight and death of signalgrass (Urochloa spp.) pastures are caused by the Rhizoctonia solani fungus. This study aimed at determining which pathogens from the Rhizoctonia species complex are associated with leaf and sheath blight in Urochloa and rice, in the Colombian Llanos. Sympatric areas of Urochloa pastures adjacent to rice cropping areas were sampled using a linear transect system. The pathogens were identified using morphological traits, molecular detection based on specific primers and sequencing of the ITS-5.8S rDNA region. R. solani AG-1 IA predominated as the pathogen associated with foliar blight in all samples from U. brizantha cv. 'Toledo' and hybrid Urochloa cv. 'Mulato'. Besides R. solani AG-1 IA (18 % of the samples), Rhizoctonia oryzae-sativae (71 %) and Sclerotium hydrophilum (11 %) were also detected. In the cross-pathogenicity test, the R. solani AG-1 IA fungus was the most aggressive to Urochloa, while R. oryzae-sativae produced very mild infection symptoms. This is the first report of R. oryzae-sativae and S. hydrophilum associated with the complex of rice sheath blight diseases in Colombia.

Isolation of a RT-PCR fragment from human colon and sheep rumen RNA with nucleotide sequence similarity to human and rat urea transporter isoforms

1998 ◽  
Vol 26 (2) ◽  
pp. S122-S122 ◽  
Author(s):  
ARMIN RITZHAUPT ◽  
I. STUART WOOD ◽  
ALLAN A. JACKSON ◽  
BRENDAN J. MORAN ◽  
SORAYA P. SHIRAZI-BEECHEY
Keyword(s):  
Nucleotide Sequence ◽  
Sequence Similarity ◽  
Human Colon ◽  
Urea Transporter ◽  
Rt Pcr ◽  
Nucleotide Sequence Similarity ◽  
Sheep Rumen

Comparison of rDNA-ITS Sequences between Potato and Tobacco Strains in Rhizoctonia solani AG-3

2000 ◽  
Vol 66 (1) ◽  
pp. 2-11 ◽  
Author(s):  
Shiro KUNINAGA ◽  
Donald E CARLING ◽  
Toru TAKEUCHI ◽  
Ryozo YOKOSAWA
Keyword(s):  
Rhizoctonia Solani ◽  
Its Sequences ◽  
Rdna Its ◽  
Rdna Its Sequences

scholarly journals Trichothecene Nonproducer Gibberella Species Have Both Functional and Nonfunctional 3-O-Acetyltransferase Genes

Genetics ◽  
2003 ◽  
Vol 163 (2) ◽  
pp. 677-684
Author(s):  
Makoto Kimura ◽  
Takeshi Tokai ◽  
Gentaro Matsumoto ◽  
Makoto Fujimura ◽  
Hiroshi Hamamoto ◽  
...  
Keyword(s):  
Nucleotide Sequence ◽  
Fission Yeast ◽  
Fusarium Graminearum ◽  
Sequence Similarity ◽  
Fusarium Species ◽  
Fungal Genome ◽  
Expression Cloning ◽  
Nucleotide Sequence Similarity ◽  
Cdna Expression ◽  
Pcr Techniques

Abstract The trichothecene 3-O-acetyltransferase gene (FgTri101) required for trichothecene production by Fusarium graminearum is located between the phosphate permease gene (pho5) and the UTP-ammonia ligase gene (ura7). We have cloned and sequenced the pho5-to-ura7 regions from three trichothecene nonproducing Fusarium (i.e., F. oxysporum, F. moniliforme, and Fusarium species IFO 7772) that belong to the teleomorph genus Gibberella. BLASTX analysis of these sequences revealed portions of predicted polypeptides with high similarities to the TRI101 polypeptide. While FspTri101 (Fusarium species Tri101) coded for a functional 3-O-acetyltransferase, FoTri101 (F. oxysporum Tri101) and FmTri101 (F. moniliforme Tri101) were pseudogenes. Nevertheless, F. oxysporum and F. moniliforme were able to acetylate C-3 of trichothecenes, indicating that these nonproducers possess another as yet unidentified 3-O-acetyltransferase gene. By means of cDNA expression cloning using fission yeast, we isolated the responsible FoTri201 gene from F. oxysporum; on the basis of this sequence, FmTri201 has been cloned from F. moniliforme by PCR techniques. Both Tri201 showed only a limited level of nucleotide sequence similarity to FgTri101 and FspTri101. The existence of Tri101 in a trichothecene nonproducer suggests that this gene existed in the fungal genome before the divergence of producers from nonproducers in the evolution of Fusarium species.

New Method for Sequence Similarity Analysis Based on the Position and Frequency of Statistically Significant Repeats

2021 ◽  
Vol 16 ◽  
Author(s):  
Jasmina T. Jovanovic
Keyword(s):  
Nucleotide Sequence ◽  
Clustering Algorithm ◽  
Sequence Similarity ◽  
Random Sequence ◽  
Nucleotide Sequences ◽  
Similarity Analysis ◽  
Frequency Method ◽  
Nucleotide Sequence Similarity ◽  
Alignment Free ◽  
Multiple Data Sets

Background: The analysis of DNA nucleotide sequence similarity among different species is crucial in identifying their functional, structural or evolutionary relationships. The number of bioinformatics tools designed to perform the similarity analysis of nucleotide sequences has been growing rapidly. According to the current literature, alignment-free methods ha-ven’t been performed on nucleotide sequence repeats of different lengths. Objective: To develop a new algorithm for determining sequence characteristics and similarity based on statistically signifi-cant repetitive elements of different lengths, which are located in analyzed sequences. Method: This paper presents Repeats-Position/Frequency method (R-P/F method), for determining nucleotide sequence similarity which takes into consideration statistically significant repetitive parts of analyzed sequences. It is based on infor-mation theory and the fact that both position and frequency of repeated sequences are not expected to occur with the identical presence in a random sequence of the same length. Nucleotide sequences are presented in rn-dimensional vector space and their hierarchy is constructed by applying hierarchical clustering algorithm. Results: R-P/F method has been validated on multiple data sets of nucleotide sequences and compared with results obtained from alignment-based algorithms BLAST and Clustal Omega, and multiple well-established alignment-free dissimilarity measures. Presented method provides results comparable with other commonly used methods focused on resolving the same problem, with the new view on the used repetitive parts of sequences in these calculations. Conclusion: The presented, novel algorithm for calculating sequence similarity measure is effective in discovering relation-ships among the sequences and makes a powerful and complementary addition to existing sequence similarity methods.

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