Unrevealing the genetic diversity and population structure of Varroa destructor (Acari: Varroidae) across Ethiopian landscape

The invasive parasite, Varroa destructor, is recognized a major biotic threat to the survival of honeybees (Apis mellifera) worldwide. Although the mite is rapidly spreading, little is known about its genetic diversity in African honeybee populations. We employed the first analysis of high-throughput diversity array technology (DArT) combined with SNP markers to assess the genetic variation of 228 varroa samples collected from different locations in Ethiopia representing 28 apiaries country. After eliminating markers with missing data (>10%) and loci with unknown chromosome positions, a total of 1414 SNP markers were maintained. Genetic diversity parameters were employed to deduce variability among the Varroa genotypes. The overall mean allele number, genetic diversity, and polymorphic information content (PIC) were 1.53, 0.14, and 0.29, respectively. The results revealed that there was low genetic variation (2%) among populations but high genetic variation (72%) among individuals. A weighted neighbour-joining cluster analysis grouped the Varroa genotypes into three clusters with the highest ΔK value at K = 3. The present study provided important insights into the low genetic diversity among Varroa genotypes infesting local honeybee populations in Ethiopia. This information helps to understand the biology of the mite and for developing sustainable strategies for its effective control.

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Publication Details

Journal
International Journal of Acarology
Published
2026-09-29
DOI
https://doi.org/10.1080/01647954.2026.2729235
Primary Topic
Insect and Pesticide Research
Type
article
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article

Unrevealing the genetic diversity and population structure of Varroa destructor (Acari: Varroidae) across Ethiopian landscape

Ermias Assefa, Araya Gebresilassie, Alemayehu Gela, Yitbarek Woldehawariat et al.
International Journal of Acarology
Insect and Pesticide Research
article

Unrevealing the genetic diversity and population structure of Varroa destructor (Acari: Varroidae) across Ethiopian landscape

Ermias Assefa, Araya Gebresilassie, Alemayehu Gela, Yitbarek Woldehawariat, Anagaw Atickem
article en

Abstract

The invasive parasite, Varroa destructor, is recognized a major biotic threat to the survival of honeybees (Apis mellifera) worldwide. Although the mite is rapidly spreading, little is known about its genetic diversity in African honeybee populations. We employed the first analysis of high-throughput diversity array technology (DArT) combined with SNP markers to assess the genetic variation of 228 varroa samples collected from different locations in Ethiopia representing 28 apiaries country. After eliminating markers with missing data (>10%) and loci with unknown chromosome positions, a total of 1414 SNP markers were maintained. Genetic diversity parameters were employed to deduce variability among the Varroa genotypes. The overall mean allele number, genetic diversity, and polymorphic information content (PIC) were 1.53, 0.14, and 0.29, respectively. The results revealed that there was low genetic variation (2%) among populations but high genetic variation (72%) among individuals. A weighted neighbour-joining cluster analysis grouped the Varroa genotypes into three clusters with the highest ΔK value at K = 3. The present study provided important insights into the low genetic diversity among Varroa genotypes infesting local honeybee populations in Ethiopia. This information helps to understand the biology of the mite and for developing sustainable strategies for its effective control.

International Journal of Acarology
Bio and Emerging Technology Institute (ET), Addis Ababa University (ET)
Industry, innovation and infrastructure
Openalex Percentile: Top 12%
Insect and Pesticide Research
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Unrevealing the genetic diversity and population structure of Varroa destructor (Acari: Varroidae) across Ethiopian landscape — Ermias Assefa, Araya Gebresilassie, et al. · International Journal of Acarology (2026) | TGRS Research Map | TGRS