Relevant genetic differentiation among Brazilian populations of Anastrepha fraterculus (Diptera, Tephritidae)

ZooKeys
Mosè ManniAnna Rodolfa Malacrida

Abstract

We used a population genetic approach to detect the presence of genetic diversity among six populations of Anastrepha fraterculus across Brazil. To this aim, we used Simple Sequence Repeat (SSR) markers, which may capture the presence of differentiative processes across the genome in distinct populations. Spatial analyses of molecular variance were used to identify groups of populations that are both genetically and geographically homogeneous while also being maximally differentiated from each other. The spatial analysis of genetic diversity indicates that the levels of diversity among the six populations vary significantly on an eco-geographical basis. Particularly, altitude seems to represent a differentiating adaptation, as the main genetic differentiation is detected between the two populations present at higher altitudes and the other four populations at sea level. The data, together with the outcomes from different cluster analyses, identify a genetic diversity pattern that overlaps with the distribution of the known morphotypes in the Brazilian area.

References

Oct 12, 2000·Comparative Biochemistry and Physiology. Part B, Biochemistry & Molecular Biology·G K Chambers, E S MacAvoy
Dec 18, 2001·Molecular Ecology·M BonizzoniA R Malacrida
Nov 28, 2002·Molecular Ecology·I DupanloupL Excoffier
Feb 24, 2004·Journal of Economic Entomology·Janisete G SilvaWalter S Sheppard
Sep 12, 2007·Development Genes and Evolution·María Fernanda RuizLucas Sánchez
Sep 14, 2007·Molecular Ecology·Thelma BarbaráChristian Lexer
Dec 1, 1998·Trends in Ecology & Evolution·M R Orr, T B Smith
Jan 23, 2016·ZooKeys·Lucie VaníčkováRuth Rufino do Nascimento

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Citations

Jan 23, 2016·ZooKeys·Jorge HendrichsAnthony R Clarke
Dec 5, 2017·Journal of Economic Entomology·Norman B BarrDonald B Thomas

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Software Mentioned

Microsatellite Analyser
CERVUS
GENEPOP
Spatial Analysis of Molecular Variance ( SAMOVA )
SAMOVA
ARLEQUIN
Microsatellite Analyzer ( MSA )
GenAIEx

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