Sakiko Yaegashi

With increasing contamination in aquatic ecosystems, effective monitoring is crucial to preserve biodiversity and protect public health. This study quantified bioindicators (red swamp crayfish (Pcla), Genji-firefly (Lcr2), Ayu fish (Paa), and caddisfly (Sma)), microbial source tracking markers (ruminants (BacR), pigs (Pig2Bac), and humans (gyrB)), and a fecal indicator bacterium (Escherichia coli (sfmD)) using quantitative PCR on river water samples collected every 2 h between 21 and 22 July 2023 (from the Omo and Bingushi Rivers in Yamanashi Prefecture, Japan). Initially, the optimal filter sizes of 1.0, 0.65, and 0.22 µm were evaluated, where the 0.65 µm filter yielded higher Paa concentrations (Kruskal–Wallis test, p < 0.05) and was used subsequently. BacR and Paa exhibited 100% detection in the Omo (13/13) and Bingushi (13/13) Rivers with concentrations of 5.0 log₁₀ and 5.5 log₁₀ copies/L, respectively. These concentrations were used to assess 24 h temporal variability, but no significant fluctuations or cyclical trends between morning, afternoon, evening, and night were observed in either river. The BacR–Paa pair exhibited perfect positive detection correlation (Φ = 1.0) and complete similarity (Jaccard Index = 1.0), but a moderate negative correlation of mean concentrations highlights the importance of considering habitat overlaps and behavioral synchronicity.

Dengue fever is an important arthropod-borne disease which is transmitted by the mosquito vector, Aedes aegypti. Vector control programs rely heavily on targeting the mosquito vector in order to stop the disease transmission cycle. Hence, the present study conducted a fine-scale population genetics of Ae. aegypti in a highly urbanized and dengue endemic region in the Philippines. Furthermore, the study also explored the correlation of population genetic indices to the local dengue incidence of the region. The genetic diversity and population structure of Ae. aegypti populations were analyzed by genotyping 11 microsatellite loci from 526 adult mosquitoes sampled in 21 study areas in Metropolitan Manila. Five genetic indices and its dengue incidence were then correlated using Pearson’s correlation. Results showed low genetic differentiation among mosquito populations indicating high gene flow activity in the region. However, the study also revealed a considerable number of inferred genetic clusters (K=5). The constructed UPGMA dendrogram exhibited close proximity of genetically-similar Ae. aegypti mosquito populations that extends in long distances suggesting passive dispersal ability of the mosquito vector. Moreover, a positive and significant correlation was observed between dengue incidence and inbreeding coefficient (Fis) (r = 0.52, p = 0.02). Overall, the study showed that population genetic structuring can occur in a fine-scale area which consisted notable clustering and extending patterns of genetically-similar mosquito populations. This infers the potential migration ability of Ae. aegypti in different locations of the region where specific vector control zones could be carried out to disrupt its dispersal ability. Also, this is the first study that attempted to correlate genetic indices to dengue incidence that could serve as a supplementary index in identifying high dengue risk areas in the future.AUTHOR SUMMARY: Dengue disease puts billions of people worldwide at risk. To mitigate this risk, population genetic studies of its vector, Aedes aegypti, are being conducted. The information established from these studies can be utilized to reduce mosquito population and thereby, reduce the opportunity for dengue transmission. In this study, we used microsatellite markers to determine genetic structure and diversity followed by correlation analyses between genetic indices and dengue incidence. Results show a low genetic differentiation among mosquito populations in Metro Manila; it also indicates population genetic structuring in a fine-scale area. This suggest a pattern of migration activity of Ae. aegpyti which can be used to mitigate dengue transmission. Moreover, the study also explored in correlating genetic indices and local dengue incidence where it demonstrated significant correlation with the inbreeding coefficient (Fis). Further investigation is needed on how these genetic indices may be utilized in predicting and identifying high dengue risk areas in endemic areas.

Adaptive divergence is a key mechanism shaping the genetic variation of natural populations. A central question linking ecology with evolutionary biology concerns the role of environmental heterogeneity in determining adaptive divergence among local populations within a species. In this study, we examined adaptive the divergence among populations of the stream mayfly Ephemera strigata in the Natori River Basin in northeastern Japan. We used a genome scanning approach to detect candidate loci under selection and then applied a machine learning method (i.e. Random Forest) and traditional distance-based redundancy analysis (dbRDA) to examine relationships between environmental factors and adaptive divergence at non-neutral loci. We also assessed spatial autocorrelation at neutral loci to quantify the dispersal ability of E. strigata . Our main findings were as follows: 1) random forest shows a higher resolution than traditional statistical analysis for detecting adaptive divergence; 2) separating markers into neutral and non-neutral loci provides insights into genetic diversity, local adaptation and dispersal ability and 3) E. strigata shows altitudinal adaptive divergence among the populations in the Natori River Basin.