Developmental and environmental stability of candidate reference genes in the wild bee ceratina calcarata

developmental-and-environmental-stability-of-candidate-reference-genes-in-the-wild-bee-ceratina-calcarata
Developmental and environmental stability of candidate reference genes in the wild bee ceratina calcarata

Scientific Reports volume 15, Article number: 39046 (2025) Cite this article

Subjects

Abstract

Quantitative real-time PCR (q-RT-PCR) is a widely used method for measuring gene expression, but its accuracy depends on the use of stable reference genes for data normalization. In this study, we evaluated the expression stability of seven candidate reference genes (RPS18, RPS5, RPL32, RPL8, EF-1α, β-Actin, and GAPDH) in the small carpenter bee Ceratina calcarata across developmental stages (larvae, pupae, adults) and different landscape environments (conventional farms, organic farms, and roadside sites). Using four analytical algorithms, GeNorm, NormFinder, BestKeeper, and the comparative ΔCt method, we identified RPS18 and RPL8 as the most stable reference genes under varying biological and environmental conditions. These findings were further supported by RefFinder, which integrates results from all algorithms. Our study provides the first validated reference genes for C. calcarata, enabling more accurate and reproducible gene expression analysis in this ecologically important wild bee species. This work will support future research in pollinator biology, environmental stress responses, and conservation genomics.

Introduction

The service provided by pollinators is essential for global ecosystems. About 87.5% of flowering plants worldwide require pollination service by animals1. About 75% of the agricultural crops benefit from pollinators, resulting in a 35% increase in yield and generating billions of dollars in value2,3. The honeybee (Apis mellifera) is the most important managed pollinator for crop and fruit productions4,5. Native wild bees are far more numerous than managed bees6. They provide complementary pollination service thought to surpass managed bees, which contribute to the ecological and agricultural stability7,8. The small carpenter bees refer to a large group of more than 300 species from genus Ceratina (Apidae: Xylocopinae)9. Ceratina calcarata Robertson is a species native to eastern North America, ranging Florida to the south, Ontario to the north, and Nova Scotia to the east10. The species, as well as the sympatric species C. dupla Say, can effectively pollinate many fruit, vegetable, and other crops11,12 and are among the most abundant pollinator species in recent restored land12,13. Similar to honey bees, native wild bees also suffered from declining populations, potentially caused by loss of habitat, the use of agrochemicals, land-scape alternation, and parasitism14,15.

Besides its economic and ecological importance, C. calcarata is considered as a subsocial species with features of prolonged maternal care and mother-adult offspring interaction. It also demonstrates traits of facultative sociality such as division of labor and cooperative brood care16. The eldest daughters are dwarf in body size and responsible for foraging, guarding and feeding their younger siblings17,18,19. Their roles resemble worker-like behavior in eusocial species and they do not have chance to overwinter or reproduce the next spring. Therefore, C. calcarata is an ideal model to study the evolution and mechanism of sociality in hymenopteran insects.

To date, many molecular and genomics approaches have been adopted to study the phylogeny10,20,21, adaptation22,23 and reproduction24 of Ceratina species. The reference genome of C. calcarata25 and C. australensis26 has been sequenced and assembled. The transcriptome and metatranscriptome of C. calcarata have been sequenced, which revealed the gene and microbiome regulations associated with overwintering27, maternal and sibling care18,28,29, social behavior30, and landscape adaptation31. Compared to high-throughput sequencing, real-time quantitative reverse transcription polymerase chain reaction (q-RT-PCR) provides a fast and accurate approach to quantify genes32,33,34. It involves the reverse transcription of RNA into complementary DNA (cDNA), followed by real-time PCR amplification. This method is cost-effective when a small number of target genes are analyzed from a large number of samples. The calculation of relative expression is relied on internal controls, which are housekeeping genes with constant expression levels across the treatments35. However, as a prerequisite procedure for studying gene expressions associated with development and adaptation to agricultural landscapes, there is a lack of highly conserved reference genes in C. calcarata for q-RT-PCRs. Thus, it is a challenge to study target gene expressions in this bee species.

In this study, we tested the expressional stability of seven commonly used reference genes, including four ribosomal binding proteins: ribosomal protein L8 (RPL8) and L32 (RPL32) binding to large subunits, S5 (RPS5) and S18 (RPS18) binding to small subunit, a cytoskeleton protein: β-actin (ACT), a translation elongation protein: elongation factor 1-alpha F2 (EF-1α), and a housekeeping enzyme: glyceraldehyde 3-phosphate dehydrogenase (GADPH). We used four methods to compare the stability of each gene: comparative ΔCt analysis36, NormFinder37, geNorm38, and BestKeeper39. Further RefFinder was utilized for integrated analysis with incorporating GeNorm, BestKeeper, NormFinder, and ∆Ct analysis40. Our results present the most stable genes across landscapes and developmental stages, which can be used in studies of gene expression analysis under similar scenarios.

Materials and methods

Sample collection and total RNA extraction

C. calcarata individuals were collected from multiple sites in Western Ohio during the spring 2024. The sites include three types of landscape: conventional farms with regular applications of pesticides and other agrochemicals, organic farms with natural based pesticides, and roadside landscape without agricultural activity. Given that C. calcarata nests in raspberry (Rubus idaeus L.)17,41, raspberry stems with diameters over 7 mm from the previous growing season were cut to 1.20 m stems, attached to bamboo sticks with twist ties, and vertically inserted into the ground randomly for about 20 cm in early May to attract C. calcarata (Supplementary figure S1).

After four weeks, the nesting individuals were collected from stems and their life stages were visually identified as larva, pupa and adult stages. Immatures were categorized into small larvae, large larvae, pre-pupae, white-eyed pupae31. For RNA extraction, we used large larvae which may be either 4th or 5th instar. However, we did not determine the sex of the larvae, and sex differences may contribute to variation in gene expression. The samples were frozen in dry ice and stored temporarily at −80 °C. Individual total RNA was extracted using TRIzol and purified by ZYMO Direct-zol RNA Miniprep Kit (Zymo Research, Irvine, CA, USA). Genomic DNA (gDNA) was removed by DNase I (Zymo Research) using in-column digestion method. The concentrations of RNA were measured by Qubit RNA BR Assay (Thermo Fisher Scientific, Waltham, MA). The RNA samples were preserved at −80 °C for future use.

Primer design and q-RT-PCR experiments, and efficiency test

The predicted coding sequences of candidate genes were searched from C. calcarata genome assembly annotation25 and confirmed by PCR. The primers were designed using Primer3Plus with default settings with q-RT-PCR module targeting amplicons of 90–130 bp42. The details of the primers are presented in Supplementary Table S1. Where possible, primers were designed to span exon-exon junctions to avoid amplification of gDNA. Primer specificity was confirmed by reverse transcription polymerase chain reaction (RT-PCR) followed by 1% agarose gel electrophoresis, which produced a single band of the expected size for each primer set. A single peak in the melting curve further verified the specificity of the amplification. Primer efficiency was determined using a five-point, 10-fold serial dilution of pooled cDNA as standard. The amplification efficiencies ranged from 91.05% to 108.40%.

The first strand cDNA for each sample was synthesized by iScript cDNA Synthesis Supermix (Bio-Rad, Hercules, CA) following the factory protocol. A mixture of oligo(dT) and random hexamers were used to prime the reaction. Samples were normalized to 1 µg total RNA per 20 µl reaction mix. Real time PCR were conducted using PowerUp SYBR Green Mix (Thermo Fisher Scientific) in QuantStudio 3 Real-Time PCR System (Thermo Fisher Scientific) by following procedure: 50 °C for 2 min, 95 °C for 2 min; 40 cycles of 95 °C for 15 s, 60 °C for 30 s; then a 60–95 °C melting curve to confirm the specificity of amplification. Three technical replications were incorporated for each sample. To obtain the PCR efficiency of each primer set, q-RT-PCR was also performed on 10X serial dilution of cDNA. The efficiency of each primer set was calculated by formula (:Efficiency={10}^{-1/slope}).

Data analysis

The cycle threshold (Ct) value of each reaction was obtained by Design & Analysis 2 (DA2) software (version 2.8.0, Thermo Fisher Scientific). Standard curves of Ct were made by liner regression, and the efficiency of each primer set was calculated by formula as mentioned above. We addressed the expression stabilities under developmental stages or agricultural landscapes using following algorithms: comparative ΔCt method36, NormFinder37, geNorm38, and BestKeeper39. R Package ctrlGene (version 1.0.1)43 were used to address geNorm and BestKeeper analysis. RefFinder was utilized for integrated analysis with incorporating GeNorm, BestKeeper, NormFinder, and ∆Ct analysis40.

Results

Primer specificity and efficiency test

The specificity of primers was confirmed by reverse transcription PCR. The results of 1% agarose gel electrophoresis followed presented the unique bands for each primer set within the expected size range. The single peak in melting curves also confirmed the result. Using cDNA serial dilution as standard, the primers present efficiency from 91.05% to 108.40%, which are within the acceptable range.

Analysis of candidate reference gene expression

The expression levels of different reference genes of C. calcarata under different developmental stages and landscapes is presented in the Fig. 1a, b. The results revealed a range of Ct values for analysed candidate reference genes varying from 14.83 to 32.01. The Ct values for candidate reference genes varied across developmental stages (larvae vs. adult) and collection sites (conventional vs. organic vs. roadside sites). Among all genes, RPS18 and RPL8 showed lower Ct variability. However, GADPH and ACT exhibited greater fluctuation.

Fig. 1
figure 1

Expression levels of different candidate reference genes in small carpenter bee across developmental stages and landscapes. The x-axis shows the tested candidate reference genes and the y-axis shows their relative expression levels (mean standard deviation of Ct values. (a) Adult stage samples (b) Larval stage samples. Bars represent mean vaues from biological replicates; error bars indicate standard deviation.

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Stability of candidate reference genes

∆Ct method

The ∆Ct method utilizes the standard deviations of Ct values to assess gene expression stability of genes. In both larval and adult stages, RPL8 was the most stable gene among the seven investigated genes. While analyzing the data based on collection sites as organic, roadside and conventional sites, RPS18, RPS5 and RPS32 were the more stable genes, respectively (Fig. 2a-e).

Fig. 2
figure 2

Expression stability of candidate reference genes in small carpenter bee across different developmental stages and landscapes using ∆Ct method. The x-axis shows the candidate reference genes, and y-axis shows mean ∆Ct values, where lower values indicate higher expression stability. (a) Larval stage (b) Adult stage (c) Organic sites (d) Roadside sites (e) Conventional sites.

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GeNorm analysis

GeNorm analysis uses expression stability measurement (M) value based on the average pairwise variation to calculate the stability of expression levels. The M of different candidate reference genes using geNorm are presented in Fig. 3a-e. RPL8 followed by RPL32 were the most stable genes in the larval stage, whereas RPS18 followed by RPL8 were the most stable genes in adult stage. In addition, RPS18, RPS5 and RPL8 were the most stable genes based on the organic, roadside and conventional sites of collection, respectively.

Fig. 3
figure 3

Expression stability measurement (M value) of candidate reference genes in small carpenter bee across developmental stages and landscapes using geNorm analysis. The x-axis shows the candidate reference genes, and the y-axis shows their average expression stability value (M value), where lower M indicates higher stability. (a) Larval stage (b) Adult stage (c) Organic sites (d) Roadside sites (e) Conventional sites.

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BestKeeper analysis

BestKeeper uses both the coefficient of variations (CVs) and standard deviations (SDs) to determine the stability of each candidate reference gene. The SDs used by BestKeeper were from Ct values. The stability of a reference gene is considered better if it has a lower CV ± SD value44. According to BestKeeper analysis, ACT and RPS18 were the top two most sable genes in the larval stage and RPS18 and RPL8 were the top most stable genes in the adult stage. The most stable candidate reference genes identified were RPL32 and RPLS18 on the organic area, RPS18 and RPS5 on the roadside area, and ACT and RPS18 on the conventional area (Table 1).

Table 1 Expression stability of candidate reference genes in small carpenter bee under different developmental stages and landscapes using bestkeeper analysis.

Full size table

NormFinder analysis

NormFinder identifies the most suitable reference gene by an expression stability value, where lower values indicate more stable expression. The expression stability of candidate reference genes of C. calcarata under different developmental stages and landscapes using NormFinder is presented in Fig. 4. RPS18 and RPL32 were identified as the most stable candidate reference genes based on the NormFinder analysis.

Fig. 4
figure 4

Expression stability of reference genes in small carpenter bee across different developmental stages and landscapes using NormFinder analysis. The x-axis shows the candidate reference genes, and the y-axis shows their stability value calculated by NormFinder, where lower values indicate more stable expression.

Full size image

RefFinder analysis

RefFinder is an integrated analysis tool used for the validation of reference genes that incorporates several methods including GeNorm, BestKeeper, NormFinder, and ∆Ct analysis. Based on the RefFinder, RPL8 and RPS18 were the top two most sable genes in the larval and adult stages. RPS18 consistently ranked among the most stable candidate reference genes across all collection sites, paired with EF-1α in the organic site, RPS5 in the roadside site and RPL8 in the conventional site (Table 2).

Table 2 Expression stability of candidate reference genes in small carpenter bee under different developmental stages and landscapes using reffinder analysis.

Full size table

Discussion

C. calcarata is considered an indicator species of healthy ecosystems and an important pollinator for natural and agricultural ecosystems45,46. This species is commonly used for studying pollinator ecology, behavior, evolution and genomics17,47. In this study, we collected larval and adult stages of C. calcarata from different habitats, namely organic, roadside and conventional landscapes and evaluated the expression stability of seven candidate reference genes as ACT, EF-1α, GADPH, RPL8, RPL32, RPS5 and RPS18 using widely adopted analytical tools. Integrated analysis using RefFinder revealed that RPS18 consistently ranked among the top two most sable genes across both developmental stages and all habitat types. Similarly, RPS5 was identified as one of the two most stable genes in larvae, adults and roadside habitat. However, EF-1α and RPL8 were among the other two most stable genes in the organic and conventional site, respectively. In a study of a solitary bee, Megachile rotundata, also reported RPS18, and RPL8 as stable reference genes across all life stages and under a variety of environmental conditions48. Similarly, a transcriptional study of C. calcarata reported significant variation in gene expression associated with overwintering27. These findings suggest that RPS18 and RPL8 exhibit overall high expression stability and are suitable reference genes for gene expression studies in C. calcarata across different developmental stages and habitat conditions. To our knowledge, no study has investigated the gene expression stability of C. calcarata. Therefore, the present findings will be an important basis for future studies in C. calcarata with broader implications for native wild bees.

The expression stability of candidate reference genes varied across developmental stages and habitat types, suggesting that both intrinsic and environmental factors influence gene expression. In other bee species, such as Euglossa viridissima also exhibited age-related gene expression patterns49. Differences between larvae and adults may reflect distinct physiological processes, such as growth and differentiation in larvae and processes like reproduction, foraging or immune function in adults50. Additionally, environmental stressors such as pesticide exposure and resource availability may affect gene expression in bees51. These findings highlight the need to carefully validate reference genes across both developmental stages and ecological contexts for accurate normalization in q-RT-PCR studies.

In conclusion, the present study evaluated the expression stability of seven candidate reference genes in C. calcarata across different developmental stages and habitat types. The results demonstrate that gene stability varies with both developmental stages and environmental conditions, underscoring the importance of selecting appropriate reference genes for accurate normalization in q-RT-PCR. Our findings provide a valuable resource for future gene expression studies in wild bees and highlight the necessity of validating reference genes under specific conditions.

Data availability

All raw data and related metadata of this report was deposited in Zenodo, [https://doi.org/10.5281/zenodo.16414347](https:/doi.org/10.5281/zenodo.16414347).

References

  1. Klein, A-M., Boreux, V., Fornoff, F., Mupepele, A-C. & Pufal, G. Relevance of wild and managed bees for human well-being. Curr. Opin. Insect Sci. 26, 82–88. https://doi.org/10.1016/j.cois.2018.02.011 (2018).

    Article  PubMed  Google Scholar 

  2. Classen, A. et al. Complementary ecosystem services provided by pest predators and pollinators increase quantity and quality of coffee yields. Proc. Biol. Sci. 281(1779),20133148 (2014). https://doi.org/10.1098/rspb.2013.3148

  3. Stein, K. et al. Bee pollination increases yield quantity and quality of cash crops in Burkina Faso, West Africa. Sci. Rep. 7, 17691. https://doi.org/10.1038/s41598-017-17970-2 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  4. Li-Byarlay, H. et al. Transcriptomic and epigenomic dynamics of honey bees in response to lethal viral infection. Front. Genet. 11, 566320. https://doi.org/10.3389/fgene.2020.566320 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Li-Byarlay, H. et al. Biting behavior against Varroa mites in honey bees is associated with changes in mandibles, with tracking by a new mobile application for mite damage identification. Apidologie 56, 3. https://doi.org/10.1007/s13592-024-01126-z (2025).

    Article  Google Scholar 

  6. Wang, F. et al. Insights into adult worker foraging dynamics within a Bombus terrestris (Hymenoptera: Apidae) colony. J. Econ. Entomol. 118 (1), 28–36. https://doi.org/10.1093/jee/toae295 (2025).

    Article  PubMed  Google Scholar 

  7. Brittain, C., Kremen, C. & Klein, A-M. Biodiversity buffers pollination from changes in environmental conditions. Glob Change Biol. 19 (2), 540–547. https://doi.org/10.1111/gcb.12043 (2013).

    Article  ADS  Google Scholar 

  8. Winfree, R., Williams, N. M., Dushoff, J. & Kremen, C. Native bees provide insurance against ongoing honey bee losses. Ecol. Lett. 10 (11), 1105–1113. https://doi.org/10.1111/j.1461-0248.2007.01110.x (2007).

    Article  PubMed  Google Scholar 

  9. Michener, C. D. The Bees of the World 2nd edn (John Hopkins University, 2007).

  10. Rehan, S. M. & Sheffield, C. S. Morphological and molecular delineation of a new species in the Ceratina dupla species-group (Hymenoptera: apidae: Xylocopinae) of Eastern North America. Zootaxa 2873 (1), 35–50. https://doi.org/10.11646/zootaxa.2873.1.3 (2011).

    Article  Google Scholar 

  11. Hung, A. C. F. & Norden, B. B. Biochemical systematics of bees in the Ceratina calcarata-dupla complex. Biochem. Syst. Ecol. 15 (6), 691–693. https://doi.org/10.1016/0305-1978(87)90048-2 (1987).

    Article  CAS  Google Scholar 

  12. Lawson, S. P., Kennedy, K. B. & Rehan, S. M. Pollen composition significantly impacts the development and survival of the native small carpenter bee, Ceratina calcarata. Ecol. Entom. 46 (2), 232–239. https://doi.org/10.1111/een.12955 (2021).

    Article  Google Scholar 

  13. Fiedler, A. K., Landis, D. A. & Arduser, M. Rapid shift in pollinator communities following invasive species removal. Restor. Ecol. 20 (5), 593–602. https://doi.org/10.1111/j.1526-100X.2011.00820.x (2012).

    Article  Google Scholar 

  14. Goulson, D., Nicholls, E., Botías, C. & Rotheray, E. L. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347 (6229), 1255957. https://doi.org/10.1126/science.1255957 (2015).

    Article  CAS  PubMed  Google Scholar 

  15. Winfree, R. The conservation and restoration of wild bees. Ann. N Y Acad. Sci. 1195 (1). https://doi.org/10.1111/j.1749-6632.2010.05449.x (2010). ,169 – 97.

  16. Costa, J. T. The other insect societies: overview and new directions. Curr. Opin. Insect Sci. 28, 40–49. https://doi.org/10.1016/j.cois.2018.04.008 (2018).

    Article  PubMed  Google Scholar 

  17. RehanSM & RichardsMH Nesting biology and subsociality in ceratina calcarata (Hymenoptera: Apidae). Can. Ent. 142 (1), 65–74. https://doi.org/10.4039/n09-056 (2010).

    Article  Google Scholar 

  18. Rehan, S. M., Berens, A. J. & Toth, A. L. At the Brink of eusociality: transcriptomic correlates of worker behaviour in a small carpenter bee. BMC Evol. Biol. 14 (1), 260. https://doi.org/10.1186/s12862-014-0260-6 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Lawson, S. P., Ciaccio, K. N. & Rehan, S. M. Maternal manipulation of pollen provisions affects worker production in a small carpenter bee. Behav. Ecol. Sociobiol. 70 (11), 1891–1900. https://doi.org/10.1007/s00265-016-2194-z (2016).

    Article  Google Scholar 

  20. Shell, W. A. & Rehan, S. M. Development of multiple polymorphic microsatellite markers for Ceratina calcarata (Hymenoptera: Apidae) using genome-wide analysis. J. Insect Sci. 16 (1), 57. https://doi.org/10.1093/jisesa/iew042 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Sless, T. J. L. et al. Phylogenomics and biogeography of the small carpenter bees (Apidae: xylocopinae: Ceratina). Mol. Phylogenet Evol. 198, 108133. https://doi.org/10.1016/j.ympev.2024.108133 (2024).

    Article  CAS  PubMed  Google Scholar 

  22. Brasil, S. N. R., Kelemen, E. P. & Rehan, S. M. Historic DNA uncovers genetic effects of climate change and landscape alteration in two wild bee species. Conserv. Genet. 24 (1), 85–98. https://doi.org/10.1007/s10592-022-01488-w (2023).

    Article  CAS  Google Scholar 

  23. Rehan, S. M. et al. Molecular phylogeny of the small carpenter bees (Hymenoptera: apidae: Ceratinini) indicates early and rapid global dispersal. Mol. Phylogenet Evol. 55 (3), 1042–1054. https://doi.org/10.1016/j.ympev.2010.01.011 (2010).

    Article  PubMed  Google Scholar 

  24. Mikát, M. & Straka, J. Genetic evidence for parthenogenesis in the small carpenter bee Ceratina dallatoreana (Apidae, Ceratinini) in its native distribution range. J. Hymenopt Res. 95, 199–213. https://doi.org/10.3897/jhr.95.87165 (2023).

    Article  Google Scholar 

  25. Rehan, S. M., Glastad, K. M., Lawson, S. P. & Hunt, B. G. The genome and methylome of a subsocial small carpenter bee, Ceratina calcarata. GBE 8 (5), 1401–1410. https://doi.org/10.1093/gbe/evw079 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Rehan, S. M. et al. Conserved genes underlie phenotypic plasticity in an incipiently social bee. GBE 10 (10), 2749–2758. https://doi.org/10.1093/gbe/evy212 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Durant, D. R., Berens, A. J., Toth, A. L. & Rehan, S. M. Transcriptional profiling of overwintering gene expression in the small carpenter bee, Ceratina calcarata. Apidologie 47 (4). https://doi.org/10.1007/s13592-015-0402-x (2016). ,572 – 82.

  28. Arsenault, S. V., Hunt, B. G. & Rehan, S. M. The effect of maternal care on gene expression and DNA methylation in a subsocial bee. Nat. Commun. 9 (1), 3468. https://doi.org/10.1038/s41467-018-05903-0 (2018).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  29. Chau, K. D., Shamekh, M., Huisken, J. & Rehan, S. M. The effects of maternal care on the developmental transcriptome and metatranscriptome of a wild bee. Commun. Biol. 6 (1), 904. https://doi.org/10.1038/s42003-023-05275-2 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Withee, J. R. & Rehan, S. M. Social aggression, experience, and brain gene expression in a subsocial bee. Integr. Comp. Biol. 57 (3), 640–648. https://doi.org/10.1093/icb/icx005 (2017).

    Article  CAS  PubMed  Google Scholar 

  31. Nguyen, P. N. & Rehan, S. M. Developmental Microbiome of the small carpenter bee. Ceratina Calcarata eDNA. 4 (4), 808–819. https://doi.org/10.1002/edn3.291 (2022).

    Article  CAS  Google Scholar 

  32. Gibson, U. E. M., Heid, C. A. & Williams, P. M. A novel method for real time quantitative RT-PCR. Genome Res. 6 (10), 995–1001. https://doi.org/10.1101/gr.6.10.995 (1996).

    Article  CAS  PubMed  Google Scholar 

  33. Li-Byarlay, H. et al. RNA interference knockdown of DNA methyl-transferase 3 affects gene alternative splicing in the honeybee. Proc. Natl. Acad. Sci. USA. 110,12750–12755 (2013). https://doi.org/10.1073/pnas.1310735110

  34. Li, H., Buczkowski, G. & Mittapalli, G. Transcriptomic profiles of Drosophila melanogaster third instar larval midgut and responses to oxidative stress. Insect Mol. Biol. 17, 325–339. https://doi.org/10.1111/j.1365-2583.2008.00808.x (2008).

    Article  CAS  PubMed  Google Scholar 

  35. Ho, K. H. & Patrizi, A. Assessment of common housekeeping genes as reference for gene expression studies using RT-qPCR in mouse choroid plexus. Sci. Rep. 11, 3278. https://doi.org/10.1038/s41598-021-82800-5 (2021).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  36. 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 (1), 33. https://doi.org/10.1186/1471-2199-7-33 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Andersen, C. L., Ldet-Jensen, J. & Ørntoft, 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 (15), 5245–5250. https://doi.org/10.1158/0008-5472.Can-04-0496 (2004).

    Article  CAS  PubMed  Google Scholar 

  38. Vandesompele, J. et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3 (7), research0034. https://doi.org/10.1186/gb-2002-3-7-research0034 (2002).

    Article  PubMed  PubMed Central  Google Scholar 

  39. 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 (6). https://doi.org/10.1023/B:BILE.0000019559.84305.47 (2004). ,509 – 15.

  40. 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. 80, 75–84. https://doi.org/10.1007/s11103-012-9885-2 (2012).

    Article  CAS  Google Scholar 

  41. Vickruck, J. L., Rehan, S. M., Sheffield, C. S. & Richards, M. H. Nesting biology and DNA barcode analysis of Ceratina dupla and C. mikmaqi, and comparisons with C. calcarata (Hymenoptera: apidae: Xylocopinae). Can. Entomol. 143 (3), 254–262. https://doi.org/10.4039/n11-006 (2011).

    Article  Google Scholar 

  42. Untergasser, A. et al. Primer3Plus, an enhanced web interface to Primer3. Nucleic Acids Res. 35, W71–W4. https://doi.org/10.1093/nar/gkm306 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Zhong, S. & ctrlGene Assess the Stability of Candidate Housekeeping Genes. R package version 1.0.1 ed. (2019).

  44. De Spiegelaere, W. et al. Reference gene validation for RT-qPCR, a note on different available software packages. PLoS One. 10 (3), e0122515. https://doi.org/10.1371/journal.pone.0122515 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Lawson, S. P., Kennedy, K. B. & Rehan, S. M. Pollen composition significantly impacts the development and survival of the native small carpenter bee, Ceratina calcarata. Ecol. Entomol. 46 (2), 232–239. https://doi.org/10.1111/een.12955 (2021).

    Article  Google Scholar 

  46. Nooten, S. S. & Rehan, S. M. Agricultural land use yields reduced foraging efficiency and unviable offspring in the wild bee Ceratina calcarata. Ecol. Entomol. 44 (4), 534–542. https://doi.org/10.1111/een.12730 (2019).

    Article  Google Scholar 

  47. Brenman-Suttner, D. B., Rehan, S. M. & Zayed, A. Exploring the genetics of social behaviour in C. calcarata. Sci. Rep. 15, 5580. https://doi.org/10.1038/s41598-025-89870-9 (2025).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  48. Xu, J., Welker, D. L. & James, R. R. Variation in expression of reference genes across life stages of a bee, Megachile rotundata. Insects 12 (1), 36. https://doi.org/10.3390/insects1201003 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Séguret, A. et al. Transcriptomic signatures of ageing vary in solitary and social forms of an Orchid bee. GBE 13 (6), evab075. https://doi.org/10.1093/gbe/evab075 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Page, R. E. Jr & Peng, C. Y. S. Aging and development in social insects with emphasis on the honey bee, Apis mellifera L. Exp. Gerontol. 36(4–6),695–711 (2001). https://doi.org/10.1016/S0531-5565(00)00236-9

  51. Costa, C. P. et al. Pollen diet mediates how pesticide exposure impacts brain gene expression in nest-founding bumble bee queens. Sci. Total Environ. 833, 155216. https://doi.org/10.1016/j.scitotenv.2022.155216 (2022).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank Sakthi Kumaran Subburayalu for their valuable information and technical assistance, and appreciate Heaven Strachan, Laverne Ambrister, and Keara Clarke for assisting with sample collections.

Funding

The research is funded by USDA NIFA award 2021-38821-34576.

Author information

Authors and Affiliations

  1. Agricultural Research Development Program, Central State University, Wilberforce, OH, USA

    Zixiao Zhao, Rameshwor Pudasaini, Camiyah Woods, Danielle Kroh & Hongmei Li-Byarlay

  2. Department of Biology, York University, Toronto, ON, Canada

    Sandra M. Rehan

  3. Department of Agricultural and Life Sciences, Central State University, Wilberforce, OH, USA

    Camiyah Woods & Hongmei Li-Byarlay

Authors

  1. Zixiao Zhao
  2. Rameshwor Pudasaini
  3. Camiyah Woods
  4. Danielle Kroh
  5. Sandra M. Rehan
  6. Hongmei Li-Byarlay

Contributions

Conceptualization : Hongmei Li-Byarlay, Zixiao Zhao, Sandra M. RehanSample Collection : Hongmei Li-Byarlay, Zixiao Zhao, Danielle KrohFormal analysis : Rameshwor PudasainiInvestigation : Zixiao Zhao, Camiyah Woods, Hongmei Li-ByarlayResources : Hongmei Li-ByarlayValidation : Hongmei Li-ByarlayWriting – original draft : Rameshwor Pudasaini, Zixiao ZhaoWriting – review & editing : all authors.

Corresponding author

Correspondence to Hongmei Li-Byarlay.

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Competing interests

The authors declare no competing interests.

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Zhao, Z., Pudasaini, R., Woods, C. et al. Developmental and environmental stability of candidate reference genes in the wild bee ceratina calcarata. Sci Rep 15, 39046 (2025). https://doi.org/10.1038/s41598-025-23816-z

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  • DOI: https://doi.org/10.1038/s41598-025-23816-z

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