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Molecular variability of Spodoptera frugiperda (Lepidoptera: Noctuidae) populations associated to maize and cotton crops in Brazil.

作者信息

Martinelli Samuel, Barata Reinaldo Montrazi, Zucchi Maria Imaculada, Silva-Filho Marcio de Castro, Omoto Celso

机构信息

Departamento de Entomologia, Fitopatologia e Zoologia Agrícola, ESALQ-USP, Piracicaba, SP, Brazil.

出版信息

J Econ Entomol. 2006 Apr;99(2):519-26. doi: 10.1603/0022-0493-99.2.519.

DOI:10.1603/0022-0493-99.2.519
PMID:16686155
Abstract

The molecular variability among 10 populations of Spodoptera frugiperda (J.E. Smith), collected from maize, Zea mays L., or cotton Gossypium hirsutum L. crops located at distinctive geographical regions in Brazil, was assessed through random amplification of polymorphic DNA (RAPD)-polymerase chain reaction (PCR). In total, 208 RAPD markers were evaluated, and 98% of them were polymorphic. The mean genetic similarity was 0.6621 and 0.2499 by the Simple Matching and Jaccard matrices, respectively. In general, the unweighted pair-group method with arithmetic average dendrograms separated the populations into clusters related to the geographical origin of the samples. No branch of the dendrograms underpinning a molecular association of S. frugiperda has been identified to either of the two host plants. The molecular variance analysis showed that 18 and 82% of the genetic variation was distributed among and within the groups of populations, respectively. The principal coordinate analysis reinforced the pattern of population clustering found with the unweighted pair-group method with arithmetic average method. These results suggest the occurrence of considerable gene flow between S. frugiperda populations from maize and cotton fields located in the same region in Brazil. Therefore, for an effective management of this pest, there is an urgent need for a better understanding of the gene flow of S. frugiperda populations associated to different host plants along the distribution range of this pest over time in a specific cropping system.

摘要

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