AbstractThe Anopheles Hyrcanus Group comprises 25 recognized mosquito species that exhibit significant variations in critical vector characteristics despite having similar morphology and ecological niches. Cross-species transcriptional profiling with appropriate reference genes is essential to evaluate the physiological differences among these closely related species. This study aimed to identify reliable pan-species reference genes among six Anopheles Hyrcanus Group species found in South Korea. We assessed the expression stability of eight candidate genes across five developmental stages in each of the six species. Utilizing qPCR and analysis programs, our analysis revealed that the transcription of ribosomal protein L8 (RPL8) and ribosomal protein L13a was the most stable at the larval stage. In contrast, ribosomal protein L32 and ribosomal protein S17 (RPS17) exhibited stability across all tested adult stages. In comparisons across different developmental stages within individual species, RPS17 emerged as a reliable reference gene for Anopheles belenrae, Anopheles pullus, Anopheles sinensis, and Anopheles sineroides, whereas ribosomal protein S7 and RPL8 were suitable for Anopheles kleini and Anopheles lesteri. These selected reference genes may facilitate comparative gene expression profiling within the Anopheles Hyrcanus Group, thereby providing insights into the molecular mechanisms underlying their differences, such as distinct vector competence and baseline insecticide susceptibility.
IntroductionThe Anopheles Hyrcanus Group, comprising at least 25 species, is widely distributed throughout East Asia1. Some mosquitoes in this group are capable of transmitting Plasmodium vivax, and the primary vectors vary depending on the country and region because of the species distribution and their vectorial capacity2,3,4,5. In South Korea, six species in the Anopheles Hyrcanus Group (Anopheles belenrae, Anopheles kleini, Anopheles lesteri, Anopheles pullus, Anopheles sinensis, and Anopheles sineroides) have been identified in malaria high-risk areas, particularly in the northern Gyeonggi province6. As the molecular differentiation of An. belenrae and An. kleini was performed in 2005, which found that they were distinct species from An. sinensis7, in-depth research has been conducted on the Anopheles Hyrcanus Group. Epidemiology studies in the northern Gyeonggi province revealed that An. pullus is prevalent during early summer, An. kleini in midsummer, and An. sinensis dominates from mid to late-summer6. Comparative studies on the vector competence of An. sinensis, An. kleini, An. pullus, and An. belenrae determined that An. kleini exhibits the strongest vector competence, whereas An. sinensis demonstrated the lowest susceptibility to Plasmodium vivax4,8. Despite their distinct physiological and ecological characteristics, comparative studies across these species have been challenging because of their overlapping habitats and difficulties in species identification.To establish a comprehensive understanding of the differences in their epidemiologically important physiology, it is crucial to compare the expression profiles of genes associated with vector-pathogen interactions, immune responses, and xenobiotic metabolism across the different species within the Anopheles Hyrcanus Group. Furthermore, comparative gene expression studies among the different species offer the opportunity to identify conserved genetic pathways and the regulatory elements that play fundamental roles in mosquito biology. However, existing gene expression studies have primarily considered the comparative analysis of genes related to insecticide resistance within the most predominant species, An. sinensis9.Quantitative polymerase chain reaction (qPCR) is a widely used method to compare transcription levels of specific genes and relies on relative quantification based on a reference gene. To ensure an accurate comparison of transcription levels of the target gene across samples, it is essential to select a reference gene with a consistent expression level for normalization. The reference gene is typically selected from among housekeeping genes that exhibit high expression levels. However, variations in the stability of gene transcription can occur even within the same orthologous genes across different species and can be influenced by factors such as tissue type, developmental stage, and environmental conditions10,11,12. Therefore, it is crucial to select an appropriate reference gene with confirmed transcription stability that is least influenced by varying conditions.Most studies on insect reference genes focus on identifying appropriate internal reference genes within a particular species. Commonly used reference genes, such as ribosomal proteins, tubulin, actin, glyceraldehyde 3-phosphate dehydrogenase (GAPDH), and elongation factor 1α (EF1α), are selected for their consistently high and stable expression levels13. In Anopheles gambiae, the ribosomal protein S7 (RPS7) gene has been commonly used as a reference gene to normalize data when comparing the expression levels of cytochrome P450s (CYP450s) and odorant receptors14,15. For An. sinensis, the ribosomal protein S18 (RPS18) gene was used for the transcriptome analysis of pyrethroid-resistant strains9. In addition, both the RPS7 and ribosomal protein L49 (RPL49) genes were used to compare the expression levels of CYP450 between resistant strains16.Some studies have identified reference genes specifically for the purpose of comparing gene expression levels between species or genera. For example, one study employed microarray techniques to select the most suitable reference gene for six Eucalyptus species17. Moreover, common reference genes have been identified among birds from different genera18, as well as intergenus species of livestock19. Selecting genes with consistent expression levels across multiple species poses a challenge because of genetic variance and the difficulty of designing primers with acceptable efficiency for all target species. Nevertheless, employing such an approach enables research that encompasses broader and more diverse gene expression studies.In this study, we aimed to identify suitable reference genes for (1) comparisons across developmental stages within a single species and (2) interspecies comparisons that encompass the developmental stages of six mosquito species in the Anopheles Hyrcanus Group. The representative developmental stages used were 4th instar larva (4L), pupa (pup), 24-h-old adult female (24 h-A), 72-h-old adult female (72 h-A), and mixed-aged, oviposited female (ovi-A). qPCR and four analysis programs (geNorm20, Bestkeeper21, NormFinder22, and RefFinder23) were utilized to determine gene stability. Leveraging these reference genes will facilitate the investigation into physiological differences among the Anopheles Hyrcanus Group species.Materials and methodsMosquito collection and sample preparationAdult mosquitoes were collected from three locations in Gyeonggi province, South Korea (Paju: 37.871385, 126.772513; Gimpo: 37.708802, 126.643029; and Hwaseong: 37.098884, 126.783453) using black light traps (BT global, South Korea) from June to September over a three-year period (2021–2023). Species identification was performed using a multiplex PCR method with the internal transcribed spacer 2 gene sequences as the molecular marker24 with slight modifications. Oviposited eggs from individual blood-fed mosquitoes were collected, and TetraMin flakes (Tetra, VA, USA) were provided daily to the hatched larvae. A total of 8–10 individuals were collected from each developmental stage (4L, pup, 24 h-A, 72 h-A, and ovi-A) for each species and stored at − 80℃ until RNA extraction. Due to the low population density, 2–3 individuals were used for the oviposited stage of An. kleini, An. lesteri, and An. sineroides.To obtain the mRNA sequences of each gene from the six mosquito species used in this study, 10 female mosquitoes were homogenized with a 2.0 mm stainless-steel bead using a bullet blender (Next Advance, NY, USA), and total RNA was extracted using TRI reagent (MRC, OH, USA) according to the manufacturer’s protocol. The samples were treated with DNase I (Takara Bio Inc., Shiga, Japan) to remove any DNA contamination. cDNA was synthesized from 1.5 µg of DNase I-treated RNA using SuperScript IV reverse transcriptase (Invitrogen, Carlsbad, USA).Verification of candidate reference gene sequencesEleven candidate genes were initially selected based on previous transcriptional studies on mosquitoes and commonly used housekeeping genes in other insect species13,16,25. These included: actin, alpha-tubulin (α-tub), EF1α, GAPDH, ribosomal protein L13a (RPL13a), ribosomal protein L32 (RPL32), RPL49, ribosomal protein L8 (RPL8), ribosomal protein S17 (RPS17), RPS18, and RPS7. Gene fragments were amplified using primers designed from the conserved regions of each gene obtained from at least five species of Anopheles mosquitoes with completed genome sequencing (Supplementary tables 1, 2). The reaction mixture (25 μL total) contained 10 ng of template cDNA, 2 μL of 2.5 mM dNTP, 2.5 μL of 10 × buffer, 0.4 μM of each primer, 0.12 μL of EX Taq polymerase (Takara Bio Inc.), and double distilled water (ddH2O) up to 25 μL. A 3 min preincubation at 95℃ was followed by 34 cycles at 95℃ for 20 s, 55℃ for 30 s, and 72℃ for 1 min, with a final extension at 72°℃ for 5 min. The PCR products were purified using a Monarch Clean-up kit (New England Biolabs, Ipswich, MA).Amplified fragments less than 600 bp in size (RPL49, RPL32, RPS17, RPS18, and RPS7) were directly sequenced, whereas larger amplicons were cloned for precise sequencing. Purified amplicons were ligated into the pGEM-T easy vector (Promega, Madison, MU, USA) using T4 DNA ligase (Promega) and transformed into DH5α competent cells. After overnight culture at 37℃ on an LB agar plate, colonies were isolated and subsequently cultured in LB broth. Plasmids were then extracted using the AccuPrep Plasmid Mini Extraction Kit (Bioneer, Daejeon, Korea) and sequenced by Macrogen (Seoul, Korea) using an ABI3730xl genetic analyzer. The obtained sequences were submitted to GenBank (Supplementary table 3).qPCR primer design and efficiency testingTo design a common primer set for qPCR in the conserved regions, candidate gene sequences from six species were aligned using CLC Main Workbench 8.1.2 software (QIAGEN, Aarhus, Denmark). Primers with a length of 20–21 bp, a GC content of 45–60%, and product sizes ranging from 90 to 180 bp were selected. Primer dimerization was checked using a Multiple Primer Analyzer (ThermoFisher Scientific). qPCR was performed with varying amounts of cDNA (0.024, 0.12, 0.6, 3, and 15 ng) to assess efficiency. The reaction mix consisted of 4 µL of cDNA, 1 µL of the 5 pmol primer set, and 5 µL of TB Green premix EX Taq (Takara Bio Inc.). Amplification followed the following thermal protocol: 95℃ for 60 s (initial step); 35 cycles of 95℃ for 15 s, 57℃ for 20 s, and 72℃ for 25 s; and a final melting curve analysis from 60–95℃ at a rate of 1℃/sec. Fluorescence was measured in each cycle and during the melting curve analysis. The Ct values and efficiency of each primer set in the six different species were automatically calculated using LightCycler 96 software (Roche). Following the efficiency test, the same qPCR reactions were performed for all sample groups and genes using 10 ng of cDNA with two technical and three biological replicates.Stability evaluations and validation of reference genesFour normalization methods—delta Ct, geNorm, BestKeeper, and NormFinder—were used to evaluate the stability of the eight candidate reference genes, with RefFinder employed to determine the overall ranking. The delta Ct method calculates the average differences in threshold cycle (Ct) values between pairs of genes based on Cq values to identify the gene with the highest expression stability26. Using one gene as a reference, the delta Ct values for the remaining genes were calculated, and the standard deviations (SDs) were derived. This process was repeated for each of the eight candidate genes. The geNorm program evaluates stability based on stability value (M), which represents the average pairwise variation (V) between genes, with a cutoff value of 0.15. It also identifies the optimal number of reference genes for normalization through pairwise variation analysis (Vn/Vn + 1)20. BestKeeper algorithm identifies stable reference genes based on minimal Cq variations. It calculates metrics such as geometric mean, arithmetic mean, standard deviation (SD), and coefficient of variation (CV), and performs pairwise correlation analyses to determine the best reference genes21. NormFinder ranks candidate genes according to their expression stability while considering sample grouping or experimental design22. The most stable genes with the lowest stability value (SV) were identified based on log-transformed Cq values.For validation of the selected reference genes for each species and developmental stage, CHS2 and Vg1 were tested as the target genes using the two most stable reference genes and the least stable reference gene for each test. qPCR was performed using 10 ng of template cDNA, and the reaction mixture and conditions were the same as described for the efficiency test.ResultsPrimer set design and efficiency testPrimer sets for 10 of these candidate genes (excluding RPS18) were designed from conserved regions across the six Anopheles Hyrcanus Group species (Table 1). Although the RPS18 gene was used in a previous study with An. sinensis, it was excluded from our study because no suitable primers that met our criteria (a length of 20–21 bp, a GC content of 45%–60%, and a product size ranging from 90 to 180 bp) could be found within the conserved regions. After efficiency testing, the RPL49 and α-tub primers, which exhibited lower average amplification efficiencies (89.1 and 92.1%, respectively) than the other reference genes, were excluded from further analysis. The remaining primers demonstrated robust performance, with average efficiencies ranging from 95.8 to 103.1%. Notably, their species-specific efficiencies ranged from 90.7 to 106%, with an R2 ≥ 0.99, thus satisfying the criteria for reference genes.Table 1 Primers used for qPCR.Full size table
qPCR for C
q
values and comparative delta C
t
qPCR was performed to compare the transcript abundance and stability of the candidate genes. Cq values for the eight remaining candidate reference genes across the five developmental stages and six species were determined using LightCycler 96 software (Roche, Mannheim, Germany). The average Cq values for these eight genes ranged from 14.77 (EF1a) to 16.95 (GAPDH), thus indicating their robust expression levels (Fig. 1). Among the eight candidate reference genes, EF1α exhibited the highest abundance across the six species, with average Cq values ranging from 14.48 in An. lesteri to 15.07 in An. kleini.Fig. 1Cq values of the eight candidate genes in the six Anopheles Hyrcanus Group species (A) and five developmental stages (B).Full size imageThe gene with the lowest SD was determined to be the most stable in the delta Ct analysis, which varied across species: RPL8 in An. belenrae (SD = 0.63) and An. kleini (SD = 0.74); RPS7 in An. lesteri (SD = 0.52); RPL32 in An. pullus (SD = 0.79); and RPS17 in An. sinensis (SD = 0.76) and An. sineroides (SD = 0.63) (Fig. 2, Table 2). In the 4L and ovi-A stages, RPL13a was found to be the most stable gene (SD = 0.42 and SD = 0.25, respectively), while RPL32 was the most stable gene in the other developmental stages (SD = 0.30–0.75) (Table 3).Fig. 2Delta Ct values of the eight candidate genes in the six Anopheles Hyrcanus Group species (A) and five developmental stages (B).Full size imageTable 2 Ranking of gene stability across the six species was determined using various algorithms.Full size tableTable 3 Ranking of gene stability across the five developmental stages determined using various algorithms.Full size tablegeNormIn each species, the use of two genes consistently exhibited the least pairwise variation when compared to using three or four genes. However, an exception was observed in An. lesteri and An. sineroides, where lower pairwise variation values were estimated for three genes (Fig. 3). When testing the different stages across six species, three genes were found to be superior to two genes, as indicated by their lower pairwise variations. However, it is worth noting that two genes were also acceptable, as their V2/3 values were < 0.1. When assessing the M values of the eight candidate genes, the combination of RPL32, RPL8, RPL13a, and RPS17 consistently exhibited lower values, indicating greater stability across all of the sample groups (Tables 2, 3, Fig. 4). Furthermore, the most stable genes with the lowest M values varied across species: RPL32 and RPS17 in An. belenrae (M = 0.1), An. pullus (M = 0.16), and An. sineroides (M = 0.16); RPL32 and RPL8 in An. kleini (M = 0.15) and An. sinensis (M = 0.1); and RPL13a and RPS7 in An. lesteri (M = 0.08).Fig. 3Pairwise variation values of the six Anopheles Hyrcanus Group species and five developmental stages with a 0.15 cutoff value.Full size imageFig. 4geNorm-based average expression stability (M) values of the six Anopheles Hyrcanus Group species and five developmental stages.Full size imageBestKeeper and NormFinderBestKeeper analysis, based on the SD and CV values using pairwise correlation, identified that RPS17 was the most stable gene for An. belenrae, An. lesteri, and An. pullus, while RPS7 was found to be the most stable gene for An. kleini, An. sinenesis, and An. sineroides (Table 2). In addition, RPS17 emerged as the best reference gene for the 4L and ovi-A stages across the six species. RPL8 was determined to be the best reference gene for the 24 h-A and pup stages, while RPL32 exhibited the highest stability as the reference gene for the 72 h-A in the Anopheles Hyrcanus Group (Table 3).By NormFinder algorithm, the most stable genes for each species with the lowest SV, were determined as follows: RPL8 in An. belenrae and An. kleini (SV = 0.31 and 0.26, respectively); RPS17 in An. lesteri, An. pullus, and An. sineroides (SV = 0.26, 0.38, and 0.17, respectively); and RPS7 in An. sinensis (SV = 0.33) (Table 2). When testing across the different developmental stages, results similar to those of the delta Ct method were obtained, where RPL13a emerged as the most stable gene in the 4L and ovi-A stages (SV = 0.23 and 0.11, respectively), while RPL32 was the most stable gene in the 24 h-A and 72 h-A stages (SV = 0.07 and 0.24, respectively) (Table 3).RefFinderUsing the results obtained from the four normalized methods described above, the overall ranking of gene stability was determined using RefFinder23. For An. belenrae, An. pullus, An. sinensis, and An. sineroides, RPS17 was identified as the most stable reference gene, while RPL8 and RPS7 were identified as the most stable genes for An. kleini and An. lesteri, respectively. When using two reference genes, the following combinations were recommended: RPS17 + RPL8 for An. belenrae and An. sinensis; RPL8 + RPL32 for An. kleini; RPS17 + RPS7 for An. lesteri; and RPS17 + RPL32 for An. pullus and An. sineroides. When comparing the expression levels between species, RPL32 was identified as the most stable gene for the pup and adult stages, while RPL13a was found to be the most stable gene for the 4L stage. For normalization with two reference genes, RPL13a + RPL8 was recommended for the 4L stage, RPL32 + RPL8 for the pup and 72 h-A stages, and RPL32 + RPS17 or RPL32 + RPL13a for the 24 h-A and ovi-A stages.Validation of reference genesChitin synthase 2 (CHS2) and vitellogenin 1 (Vg1) genes are known to exhibit distinct expression patterns throughout the mosquito life cycle27,28. To validate the selected reference genes, qPCR was performed, and the transcription levels of CHS2 and Vg1 were normalized using either the two most stable genes or the least stable gene and compared. When using RPS7 and RPS17, which were identified as the most stable genes for An. lesteri, as references, the expression level of CHS2 was determined to be highest in the 24 h-A stage (Fig. 5A). However, when normalized using the least stable gene, actin, a different pattern of CHS2 emerged during the adult stages, with a 4.9-fold higher expression level in the ovi-A stage compared to the 24 h-A stage. The expression pattern of Vg1 across stages varied depending on whether it was normalized to the most or least stable gene (Fig. 5B).Fig. 5Comparison of relative transcription levels of the two target genes, CHS2 and Vg1, across the five developmental stages of Anopheles lesteri (A, B) and 24 h-old adult females (24 h-A) of the six Anopheles Hyrcanus Group species (C, D). Values were normalized using the best (blue) or worst (red) reference genes selected in this study.Full size imageWhen comparing the expression levels of CHS2 in the 24 h-A stage across the six species, An. pullus and An. sinensis exhibited the lowest expression levels when the stable reference genes (RPL32 and RPL13a) were used for normalization. In contrast, An. belenrae showed the lowest expression level when an unstable gene (EF1α) was used as the reference (Fig. 5C). The expression level of Vg1 also varied among the six species, but the order of expression level for each species was more consistent when using the RPL32 and RPL13a genes (An. pullus < An. kleini < An. sinensis < An. belenrae < An. sineroides < An. lesteri) compared to using EF1α (An. belenrae < An. pullus < An. sineroides < An. sinensis < An. kleini < An. lesteri) (Fig. 5D). These results emphasize the importance of appropriate reference gene selection and confirm the reliability of the reference genes identified in this study.DiscussionWhen comparing the gene expression levels among the different species, it is essential to consider that even within the same genus, substantial variation may exist within the nucleotide sequences of the same orthologous target or reference genes (Supplementary table 3). Therefore, precise primer design is essential to avoid errors resulting from sequence polymorphisms at the priming sites between species29. Differences in the sequence can lead to variations in the efficiency of the primer set, despite designing the qPCR primers from conserved regions. In this study, certain primer sets, such as those for α-tub and RPL49, exhibited considerably lower average amplification efficiencies, possibly because of imperfect sequence matching at the priming sites, which resulted in their exclusion from further testing. The performance of primer sets for the remaining reference genes appeared to be acceptable, as indicated by their higher average amplification efficiencies.In some Anopheles species, such as An. gambiae, RPS7 has traditionally been used as a reference gene for normalization in transcriptional studies30. However, it has been observed that the expression level of RPS7 fluctuates across the developmental stages of An. gambiae31. As gene stability varies among species and experimental conditions10, the indiscriminate use of RPS7 as a reference candidate can introduce bias when interpreting the expression results. For example, in this study, RPS7 was the most stable gene in An. lesteri, but its stability notably decreased in An. belenrae and An. sineroides, thus indicating significant cross-species variation in RPS7 expression stability. Moreover, pronounced differences in expression levels among the six species were observed, making it unsuitable for cross-species comparisons.The most stable genes across the six species and five developmental species were those that encoded ribosomal proteins, which are essential components of the large and small subunits. Ribosomal protein genes are widely recognized for their high sequence conservation across organisms, which makes them excellent candidates as reference genes in many insect species. They have been validated as optimum reference genes across diverse experimental conditions, including developmental stages. For example, in Cimex hemipterus, RPL8 was the most stable gene across many different experimental conditions (developmental stages, sex, tissue, gas stimulation, and temperature)32. Similarly, RPL32 in Frankliniella occidentalis showed remarkable stability in different developmental stages and temperature conditions33. In Helopeltis theivora, RPL13a was identified as the most stable gene across the different developmental stages and sexes34, while the expression of RPS17 remained stable throughout the entire life stage of Aedes aegypti25. In contrast, despite being selected as the most stable genes under various experimental conditions for many other insect species13, genes such as actin, EF1α, and GAPDH exhibited unstable expression patterns among the Anopheles Hyrcanus Group species and developmental stages.In conclusion, this study successfully identified reliable reference genes for the normalization of target gene expression across the five developmental stages in six species in the Anopheles Hyrcanus Group distributed in South Korea. The use of two reference genes (RPL13a + RPL8) is recommended when comparing the expression profiles of genes related to important larval physiology, including detoxification metabolism against various larvicidal agents and immune reactions to aquatic microbes. For the cross-species comparison of diverse physiological aspects of female mosquitoes, including vector competence, pathogen immune responses, and insecticide susceptibility, the simultaneous use of these genes (either RPL32 + RPS17 or RPL32 + RPL13a) as reference standards will be recommended for future studies. While these reference genes are valuable for comparing various gene expression profiles across different species or different developmental stages, further validation is required to assess their suitability for other experimental conditions, such as tissue-specific expression profiling, investigations involving varying temperatures, and the evaluation of infection dynamics. This study only focused on six mosquito species found within the same region; therefore, further investigation is required to determine whether these results apply to other species within the Anopheles Hyrcanus Group, which could broaden the utility of our findings for additional research. Nevertheless, these validated reference genes are essential for advancing research on mosquito biology and vector control and enabling a deeper understanding of mosquito behavior and physiology.
Data availability
All data generated during this study are included in this published article and its Supplementary Information files. The associated sequences are available on GenBank (http://www.ncbi.nlm.nuh.gov/genbank; OQ581089—OQ581147, OQ122132—OQ122143, OQ984005 -OQ984034).
ReferencesHarbach, R. E. in Anopheles mosquitoes-New insights into malaria vectors (IntechOpen, 2013).Zhang, C. et al. Survey of asymptomatic malaria and mosquito vectors in Muang Khua district of Phongsaly province, China-Laos border. Int. J. Infect Dis. 96, 141–147. https://doi.org/10.1016/j.ijid.2020.03.066 (2020).Article
CAS
PubMed
Google Scholar
Poncon, N. et al. Biology and dynamics of potential malaria vectors in Southern France. Malar. J. 6, 18. https://doi.org/10.1186/1475-2875-6-18 (2007).Article
PubMed
PubMed Central
Google Scholar
Lee, W. J. et al. Anopheles kleini, Anopheles pullus, and Anopheles sinensis: potential vectors of Plasmodium vivax in the Republic of Korea. J. Med. Entomol. 44, 1086–1090. https://doi.org/10.1603/0022-2585(2007)44[1086:akapaa]2.0.co;2 (2007).Article
PubMed
MATH
Google Scholar
Zhang, S. et al. Anopheles vectors in mainland China while approaching malaria elimination. Trends Parasitol. 33, 889–900. https://doi.org/10.1016/j.pt.2017.06.010 (2017).Article
PubMed
MATH
Google Scholar
Kim, H. C. et al. Distribution and larval habitats of Anopheles species in northern Gyeonggi Province, Republic of Korea. J. Vector Ecol. 36, 124–134. https://doi.org/10.1111/j.1948-7134.2011.00149.x (2011).Article
PubMed
MATH
Google Scholar
Rueda, L. M. Two new species of Anopheles (Anopheles) Hyrcanus Group (Diptera: Culicidae) from the Republic of South Korea. Zootaxa 941, 1–26 (2005).Article
MATH
Google Scholar
Ubalee, R. et al. Vector competence and the susceptibility of Anopheles pullus and Anopheles belenrae to Plasmodium vivax-infected blood from Thai patients. J. Med. Entomol. 59, 1047–1052. https://doi.org/10.1093/jme/tjab226 (2022).Article
PubMed
Google Scholar
Zhu, G. et al. Transcriptome profiling of pyrethroid resistant and susceptible mosquitoes in the malaria vector, Anopheles sinensis. BMC Genomics 15, 448. https://doi.org/10.1186/1471-2164-15-448 (2014).Article
CAS
PubMed
PubMed Central
MATH
Google Scholar
Teng, X., Zhang, Z., He, G., Yang, L. & Li, F. Validation of reference genes for quantitative expression analysis by real-time rt-PCR in four Lepidopteran insects. J. Insect Sci. 12, 60. https://doi.org/10.1673/031.012.6001 (2012).Article
CAS
PubMed
PubMed Central
Google Scholar
Shakeel, M., Rodriguez, A., Tahir, U. B. & Jin, F. Gene expression studies of reference genes for quantitative real-time PCR: an overview in insects. Biotechnol. Lett. 40, 227–236. https://doi.org/10.1007/s10529-017-2465-4 (2018).Article
CAS
PubMed
MATH
Google Scholar
Nardini, L. et al. Malaria vectors in the Democratic Republic of the Congo: the mechanisms that confer insecticide resistance in Anopheles gambiae and Anopheles funestus. Malar. J. 16, 448. https://doi.org/10.1186/s12936-017-2099-y (2017).Article
CAS
PubMed
PubMed Central
MATH
Google Scholar
Lu, J., Yang, C., Zhang, Y. & Pan, H. Selection of reference genes for the normalization of RT-qPCR data in gene expression studies in insects: A systematic review. Front. Physiol. 9, 1560. https://doi.org/10.3389/fphys.2018.01560 (2018).Article
ADS
PubMed
PubMed Central
MATH
Google Scholar
Muller, P. et al. Field-caught permethrin-resistant Anopheles gambiae overexpress CYP6P3, a P450 that metabolises pyrethroids. PLoS Genet. 4, e1000286. https://doi.org/10.1371/journal.pgen.1000286 (2008).Article
CAS
PubMed
PubMed Central
Google Scholar
Liu, C. et al. Distinct olfactory signaling mechanisms in the malaria vector mosquito Anopheles gambiae. PLoS Biol. https://doi.org/10.1371/journal.pbio.1000467 (2010).Article
PubMed
PubMed Central
Google Scholar
Yan, Z. W. et al. Genome-wide and expression-profiling analyses suggest the main cytochrome P450 genes related to pyrethroid resistance in the malaria vector, Anopheles sinensis (Diptera Culicidae). Pest Manag. Sci. 74, 1810–1820. https://doi.org/10.1002/ps.4879 (2018).Article
CAS
PubMed
MATH
Google Scholar
de Oliveira, L. A. et al. Reference genes for the normalization of gene expression in eucalyptus species. Plant Cell Physiol. 53, 405–422. https://doi.org/10.1093/pcp/pcr187 (2012).Article
CAS
PubMed
MATH
Google Scholar
Olias, P., Adam, I., Meyer, A., Scharff, C. & Gruber, A. D. Reference genes for quantitative gene expression studies in multiple avian species. Plos ONE https://doi.org/10.1371/journal.pone.0099678 (2014).Article
PubMed
PubMed Central
Google Scholar
Moura, M. T. et al. Inter-genus gene expression analysis in livestock fibroblasts using reference gene validation based upon a multi-species primer set. Plos ONE https://doi.org/10.1371/journal.pone.0221170 (2019).Article
PubMed
PubMed Central
MATH
Google Scholar
Vandesompele, J. et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. https://doi.org/10.1186/gb-2002-3-7-research0034 (2002).Article
PubMed
PubMed Central
Google Scholar
Pfaffl, M. W., Tichopad, A., Prgomet, C. & Neuvians, T. P. Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper–excel-based tool using pair-wise correlations. Biotechnol. Lett. 26, 509–515. https://doi.org/10.1023/b:bile.0000019559.84305.47 (2004).Article
CAS
PubMed
Google Scholar
Andersen, C. L., Jensen, J. L. & Orntoft, T. F. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 64, 5245–5250. https://doi.org/10.1158/0008-5472.CAN-04-0496 (2004).Article
CAS
PubMed
Google Scholar
Xie, F., Xiao, P., Chen, D., Xu, L. & Zhang, B. miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs. Plant Mol. Biol. https://doi.org/10.1007/s11103-012-9885-2 (2012).Article
PubMed
MATH
Google Scholar
Li, C. et al. A newly recognized species in the Anopheles Hyrcanus Group and molecular identification of related species from the Republic of South Korea (Diptera: Culicidae). Zootaxa 939, 1–8 (2005).Article
Google Scholar
Dzaki, N., Ramli, K. N., Azlan, A., Ishak, I. H. & Azzam, G. Evaluation of reference genes at different developmental stages for quantitative real-time PCR in Aedes aegypti. Sci. Rep. 7, 43618. https://doi.org/10.1038/srep43618 (2017).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Silver, N., Best, S., Jiang, J. & Thein, S. L. Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol. Biol. 7, 33. https://doi.org/10.1186/1471-2199-7-33 (2006).Article
CAS
PubMed
PubMed Central
Google Scholar
Zhang, X., Zhang, J., Park, Y. & Zhu, K. Y. Identification and characterization of two chitin synthase genes in African malaria mosquito, Anopheles gambiae. Insect Biochem. Mol. Biol. 42, 674–682. https://doi.org/10.1016/j.ibmb.2012.05.005 (2012).Article
CAS
PubMed
PubMed Central
MATH
Google Scholar
Provost-Javier, K. N., Chen, S. & Rasgon, J. L. Vitellogenin gene expression in autogenous Culex tarsalis. Insect Mol. Biol. 19, 423–429. https://doi.org/10.1111/j.1365-2583.2010.00999.x (2010).Article
CAS
PubMed
PubMed Central
Google Scholar
Boyle, B., Dallaire, N. & MacKay, J. Evaluation of the impact of single nucleotide polymorphisms and primer mismatches on quantitative PCR. Bmc Biotechnol. 9, 75. https://doi.org/10.1186/1472-6750-9-75 (2009).Article
CAS
PubMed
PubMed Central
Google Scholar
Vizioli, J. et al. Gambicin: a novel immune responsive antimicrobial peptide from the malaria vector Anopheles gambiae. Proc. Natl. Acad. Sci. U. S. A. 98, 12630–12635. https://doi.org/10.1073/pnas.221466798 (2001).Article
ADS
CAS
PubMed
PubMed Central
MATH
Google Scholar
Togawa, T., Dunn, W. A., Emmons, A. C., Nagao, J. & Willis, J. H. Developmental expression patterns of cuticular protein genes with the R&R consensus from Anopheles gambiae. Insect Biochem. Mol. Biol. 38, 508–519. https://doi.org/10.1016/j.ibmb.2007.12.008 (2008).Article
CAS
PubMed
PubMed Central
Google Scholar
Kong, D. et al. Identification and validation of reference genes for expression analysis using qRT-PCR in Cimex hemipterus (Hemiptera: Cimicidae). Insects https://doi.org/10.3390/insects13090784 (2022).Article
PubMed
PubMed Central
MATH
Google Scholar
Zheng, Y. T., Li, H. B., Lu, M. X. & Du, Y. Z. Evaluation and validation of reference genes for qRT-PCR normalization in Frankliniella occidentalis (Thysanoptera: Thripidae). PLoS ONE 9, e111369. https://doi.org/10.1371/journal.pone.0111369 (2014).Article
ADS
CAS
PubMed
PubMed Central
Google Scholar
Wang, Z. et al. Evaluation and validation of reference genes for quantitative real-time PCR in Helopeltis theivora Waterhouse (Hemiptera: Miridae). Sci. Rep. 9, 13291. https://doi.org/10.1038/s41598-019-49479-1 (2019).Article
ADS
CAS
PubMed
PubMed Central
MATH
Google Scholar
Download referencesAcknowledgementsWe would like to thank Xuerong Jin for the technical assistance with some experiments.FundingThis work was supported by the Research Resettlement Fund for the new faculty of Seoul National University.Author informationAuthors and AffiliationsDepartment of Tropical Medicine and Parasitology, Seoul National University College of Medicine, Seoul, 03080, Republic of KoreaDo Eun Lee & Ju Hyeon KimCore Research Facilities, Seoul National University College of Medicine, Seoul, 03080, Republic of KoreaDo Eun LeeDepartment of Agricultural Biotechnology, Seoul National University, Seoul, 08826, Republic of KoreaSi Hyeock LeeResearch Institute of Agriculture and Life Sciences, Seoul National University, Seoul, 08826, Republic of KoreaSi Hyeock LeeInstitute of Endemic Diseases, Seoul National University College of Medicine, Seoul, 03080, Republic of KoreaJu Hyeon KimAuthorsDo Eun LeeView author publicationsYou can also search for this author in
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PubMed Google ScholarContributionsDEL conducted the experiments, analyzed the data, and wrote the manuscript. SHL and JHK designed and coordinated the project and reviewed the manuscript. All authors have approved the final version of the manuscript.Corresponding authorCorrespondence to
Ju Hyeon Kim.Ethics declarations
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Reprints and permissionsAbout this articleCite this articleLee, D., Lee, S. & Kim, J. Validation of reliable reference genes for comparison of gene expression across species in the Anopheles Hyrcanus Group.
Sci Rep 15, 9037 (2025). https://doi.org/10.1038/s41598-024-84361-9Download citationReceived: 11 October 2024Accepted: 23 December 2024Published: 16 March 2025DOI: https://doi.org/10.1038/s41598-024-84361-9Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
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Keywords
Anopheles Hyrcanus GroupReference geneqPCRRibosomal proteinCross-species comparisonDevelopmental stages