期刊论文详细信息
Genetics and Molecular Biology
Distinctively variable sequence-based nuclear DNA markers for multilocus phylogeography of the soybean- and rice-infecting fungal pathogen Rhizoctonia solani AG-1 IA
Maisa B. Ciampi2  Liane Rosewich Gale1  Eliana G. De Macedo Lemos2  Paulo C. Ceresini1 
[1] ,Universidade Estadual Paulista Faculdade de Ciências Agrárias e Veterinárias Departamento de TecnologiaJaboticabal SP ,Brazil
关键词: multilocus genotyping;    polymorphisms;    allelic discrimination;    primer design;   
DOI  :  10.1590/S1415-47572009005000063
来源: SciELO
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【 摘 要 】

A series of multilocus sequence-based nuclear DNA markers was developed to infer the phylogeographical history of the Basidiomycetous fungal pathogen Rhizoctonia solani AG-1 IA infecting rice and soybean worldwide. The strategy was based on sequencing of cloned genomic DNA fragments (previously used as RFLP probes) and subsequent screening of fungal isolates to detect single nucleotide polymorphisms (SNPs). Ten primer pairs were designed based on these sequences, which resulted in PCR amplification of 200-320 bp size products and polymorphic sequences in all markers analyzed. By direct sequencing we identified both homokaryon and heterokaryon (i.e. dikaryon) isolates at each marker. Cloning the PCR products effectively estimated the allelic phase from heterokaryotic isolates. Information content varied among markers from 0.5 to 5.9 mutations per 100 bp. Thus, the former RFLP codominant probes were successfully converted into six distinctively variable sequence-based nuclear DNA markers. Rather than discarding low polymorphism loci, the combination of these distinctively variable anonymous nuclear markers would constitute an asset for the unbiased estimate of the phylogeographical parameters such as population sizes and divergent times, providing a more reliable species history that shaped the current population structure of R. solani AG-1 IA.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License

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