Predatory phytoseiid mites associated with cassava in Kenya, identification key and molecular diagnosis (Acari: Phytoseiidae)

Background: The morphological and molecular identification of mites is challenging due to the large number of species, the microscopic size of the organisms, diverse phenotypes of the same species, similar morphology of different species and a shortage of molecular data. Methods: Nine medically important mite species belonging to six families, i.e. Demodex folliculorum, D. brevis, D. canis, D. caprae, Sarcoptes scabiei canis, Psoroptes cuniculi, Dermatophagoides farinae, Cheyletus malaccensis and Ornithonyssus bacoti, were collected and subjected to DNA barcoding. Sequences of cox1, 16S and 12S mtDNA, as well as ITS, 18S and 28S rDNA from mites were retrieved from GenBank and used as candidate genes. Sequence alignment and analysis identified 28S rDNA as the suitable target gene. Subsequently, universal primers of divergent domains were designed for molecular identification of 125 mite samples. Finally, the universality of the divergent domains with high identification efficiency was evaluated in Acari to screen DNA barcodes for mites. Results: Domains D5 (67.65%), D6 (62.71%) and D8 (77.59%) of the 28S rRNA gene had a significantly higher sequencing success rate, compared to domains D2 (19.20%), D3 (20.00%) and D7 (15.12%). The successful divergent domains all matched the closely-related species in GenBank with an identity of 74-100% and a coverage rate of 92-100%. Phylogenetic analysis also supported this result. Moreover, the three divergent domains had their own advantages. D5 had the lowest intraspecies divergence (0-1.26%), D6 had the maximum barcoding gap (10.54%) and the shortest sequence length (192-241 bp), and D8 had the longest indels (241 bp). Further universality analysis showed that the primers of the three divergent domains were suitable for identification across 225 species of 40 families in Acari. Conclusions: This study confirmed that domains D5, D6 and D8 of 28S rDNA are universal DNA barcodes for molecular classification and identification of mites. 28S rDNA, as a powerful supplement for cox1 mtDNA 5'-end 648-bp fragment, recommended by the International Barcode of Life (IBOL), will provide great potential in molecular identification of mites in future studies because of its universality.

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Divergent domains of 28S ribosomal RNA gene: DNA barcodes for molecular classification and identification of mites

Zhao

Zhang

Wang

et al. 2020

Parasites Vectors

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Positive Yield Impact of Predacious Mites in Tea Production Areas of Kenya

Mutisya¹,

Banhawy²,

Cheramgoi³

2018

SAR

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Tea agro ecosystems are least disturbed in comparison to other crop systems due to the plant canopy type. A survey on predacious mites’ abundance and impact on leaf yield in different tea production areas was carried out in 2014-2015 in Kenya. Major pest species were the red spider mite Oligonychus coffeae and the yellow thrip, Scirtothrips dorsalis. The red crevice mite, Brevipalpus phoenicis was found in few areas and in low numbers. Predacious mites of Phytoseiidae Family were highest at 5.8 and 6.8 mites per sample during dry and wet seasons, respectively. Phytoseiid abundance during the dry and wet seasons did not differ much within most sample sites. Presence of phytoseiid mites in combination with NPK-fertilizer-high altitude led to the strongest correlation to leaf yield than any other combination variable. High phytoseiid density- high altitude was third with positive impact to yield increase after high altitude combined with NPK-fertilizer. The findings here show contributory positive impact of phytoseiids in tea leaf yield in an agro eco-system.

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Predatory phytoseiid mites associated with cassava in Kenya, identification key and molecular diagnosis (Acari: Phytoseiidae)

Cited by 2 publications

References 11 publications

Divergent domains of 28S ribosomal RNA gene: DNA barcodes for molecular classification and identification of mites

Divergent domains of 28S ribosomal RNA gene: DNA barcodes for molecular classification and identification of mites

Positive Yield Impact of Predacious Mites in Tea Production Areas of Kenya

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