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Evolutionary Adaptation of Genes Involved in Galactose Derivatives Metabolism in Oil-Tea Specialized Andrena Species

School of Life Sciences, Jinggangshan University, Ji’an 343009, China
Author to whom correspondence should be addressed.
Genes 2023, 14(5), 1117;
Submission received: 5 May 2023 / Revised: 17 May 2023 / Accepted: 18 May 2023 / Published: 22 May 2023
(This article belongs to the Special Issue Wildlife Genomics and Genetic Diversity)


Oil-tea (Camellia oleifera) is a woody oil crop whose nectar includes galactose derivatives that are toxic to honey bees. Interestingly, some mining bees of the genus Andrena can entirely live on the nectar (and pollen) of oil-tea and are able to metabolize these galactose derivatives. We present the first next-generation genomes for five and one Andrena species that are, respectively, specialized and non-specialized oil-tea pollinators and, combining these with the published genomes of six other Andrena species which did not visit oil-tea, we performed molecular evolution analyses on the genes involved in the metabolizing of galactose derivatives. The six genes (NAGA, NAGA-like, galM, galK, galT, and galE) involved in galactose derivatives metabolism were identified in the five oil-tea specialized species, but only five (with the exception of NAGA-like) were discovered in the other Andrena species. Molecular evolution analyses revealed that NAGA-like, galK, and galT in oil-tea specialized species appeared under positive selection. RNASeq analyses showed that NAGA-like, galK, and galT were significantly up-regulated in the specialized pollinator Andrena camellia compared to the non-specialized pollinator Andrena chekiangensis. Our study demonstrated that the genes NAGA-like, galK, and galT have played an important role in the evolutionary adaptation of the oil-tea specialized Andrena species.

1. Introduction

Bees have a monophyletic lineage within a clade of Anthophila in the superfamily Apoidea [1]. There are around 20,000 different species of bees and, thanks to their effective pollination for both crops and natural flora, bees are now essential parts of practically all terrestrial ecosystems [2,3]. Bees can be broadly divided into two functional groups based on floral specificity: oligolectic species, which forage on one or a small number of closely related plant species, and polylectic species, which collect nectar and/or pollen from many different plant species [4]. The most well-known bee species include the polylectic honey bees (Apis spp.) and bumble bees (Bombus spp.). Numerous biological and ecological investigations of the polylectic species have been conducted [2,5]. In contrast, oligolectic bees have received significantly less research despite making up a sizable fraction of the world’s bee fauna [6]. For oligolectic bee exploitation and conservation, therefore, a greater understanding of their biology and ecology is required.
Andrena Fabricius (Andrenidae) is a large bee genus of around 1600 species with a wide distribution mainly throughout the Holarctic. They are a crucial pollinator in both natural and agricultural contexts, and they are a particularly important aspect of northern temperate ecosystems [7]. Andrena species exhibit a spectrum of diet breadth, from polylectic to oligolectic, which makes this genus a superb group to study the evolution of diet specialization [8,9]. Oil-tea (C. oleifera) is an important woody oil crop in many countries, including China, the Philippines, India, Brazil, and South Korea [10]. This plant only blooms in November and December [11], when there are few wild pollinators present. As a result, crop yields are very limited due to significant pollinator constraints [12,13]. Local farmers have attempted to utilize domestic honey bees (Apis mellifera and Apis cerana) to increase pollination efficiency, however, both species are badly damaged by the nectar’s toxicity [14]. Interestingly, some wild bees such as A. camellia and Colletes gigas primarily rely on oil-tea nectar to survive, suggesting these species have coevolved to become experts in oil-tea [15,16,17].
Direct observation on floral visiting and microscope examination of pollen from pollen baskets showed that A. camellia near exclusively collects nectar and pollen from oil-tea blossom [12]. A. camellia emerges in the middle of October and keeps its activities (mating, oviposition, and larval development) mainly during November and December, well synchronizing with the blossom period of oil-tea tree [11,12]. Besides A. camellia, at least three other Andrena bees (A. chekiangensis, Andrena hunanensis, and Andrena striata) are also reported to visit oil tea flowers [18,19]. A. chekiangensis is much larger than A. camellia, which makes it easier to identify between the two species. Our field observations found that, A. chekiangensis is strictly not an oil-tea specialist, because it also frequently visits tea tree blossoms (Camellia sinensis). In some sympatric habitats of C. oleifera and C. sinensis, A. chekiangensis individuals were more frequently observed in C. sinensis blossoms. On the contrary, A. hunanensis and A. striata were almost indistinguishable from A. camellia in terms of morphology features and feeding habits (oil-tea specialization). It should be noted that A. hunanensis and A. striata are frequently mistakenly classified as A. camellia in many amateur fieldwork reports. Due to the morphological similarity among A. camellia and its close relatives, the researchers believe there may even be hidden unknown species that have yet to be discovered.
Understanding the poisoning and detoxifying processes used by various bee species could be crucial to enhancing oil-tea flower pollination. According to chemical tests, the primary toxins affecting western honey bees are the galactose derivatives: raffinose, manninotriose, and stachyose [20,21]. Typically, these oligosaccharides must be broken down in two steps: first, the α-galactosidine linkages are hydrolyzed by galactosidases to produce sucrose and galactose and, then, the galactose molecules are converted to UDP-glucose via the Leloir route [22,23,24]. It should be noted that little is known about the genes involved in the metabolism of galactose derivates in Andrena species. Here, we present the first next-generation sequencing of Andrena species consuming oil-tea nectars. By combining these data with genomic information on other Andrena species from GenBank, we performed bioinformatic analyses of the genes involved in the metabolism of galactose derivatives. The objective is to determine whether the oil-tea-specialized Andrena species differ from the other Andrena species in terms of evolutionary specialization.

2. Materials and Methods

All pollinators were live-trapped from oil-tea blossoms in Jiangxi, Anhui, Sichuan, Zhejiang, Guangdong, and Hunan Provinces, China (Figure 1). In order to pick out Andrena samples, the specimens were identified based on morphological characteristics [18]. One female sample for each species was chosen for genome sequencing. Total genomic DNA was extracted from the thorax of each individual using the QIAGEN DNeasy Blood and Tissue kit (Germany), following the manufacturer’s protocols. DNA libraries with ~350 bp insertions were constructed and were then sequenced with both directions of 150 bp reads using the Illumina HiSeq 2000 sequencing platform (Illumina Inc., San Diego, CA, USA). Quality control for raw reads data was performed using fastp 0.20.0 with default settings and parameters [25].
The clean reads were used for de novo assembly with MEGAHIT [26]. The mitochondrial COI sequences were extracted by local blast using NCBI-BLAST+ program v2.13.0 [27] and were used as queries to search in BOLD system (, accessed on 1 April 2023) to determine their taxonomic information. Previously published six Andrena genomes downloaded from GenBank were used as comparison objects: Andrena dorsata, GCA_929108735.1; Andrena fulva, GCA_946251845.1; Andrena haemorrhoa, GCA_910592295.1; Andrena hattorfiana, GCA_944738655.1; Andrena minutula, GCA_929113495.1; and Andrena bucephala, GCA_947577245.1. All 13 mitochondrial coding sequences in the genomes sequenced in this study and those from GenBank were extracted and were concatenated to reconstruct phylogenetic trees using IQ-TREE [28].
The galactose metabolism pathway of Hymenoptera in KEGG (ko00052) was used to identify the candidate genes involved in galactose derivatives metabolism. With honey bee (A. mellifera) candidate genes as query sequences, the exonerate program v2.4.0 [29] was used to find homologous genes in Andrena genomes. MEGA v10 [30] was used to combine and align the coding sequences from all samples for each gene. DNasP v6 [31] was used to identify the genetic variation information for each gene. The sequence similarity information among the genes as well as their translated protein sequences are calculated using clustal omega [32].
The molecular evolution analyses were performed in PAML program package [33]. The branch model was used to estimate the dN/dS (nonsynonymous/synonymous mutation) ratios of the foreground clade (oil-tea specialized species). The likelihood ratio tests (LRTs) between M0 (null model) and the branch model were performed by comparing twice the difference in log-likelihood values (2ΔlnL) against a chi-square distribution (df = 2). We also used the branch-site model called Model A to test for positive selections in the foreground clade oil-tea specialized species. The null model for Model A is Model A1, which is a modification of Model A, but with ω2 = 1 fixed [34,35]. The putative positive selection sites were deduced with Bayes Empirical Bayes (BEB) analysis. It should be noted that the seven non-specialized Andrena species lacked NAGA-like gene. Due to the high sequence similarity between NAGA and NAGA-like genes, we arbitrarily used NAGA genes of these species instead.
In order to analyze the relative expression level of each gene, we also carried out RNAseq sequencing for A. camellia and A. chekiangensis, representing specialized and non-specialized oil-tea pollinators, respectively. Total mRNA was isolated from whole specimens of each individual (4 individuals were analyzed for each species). Following the manufacturer’s instructions, 150 bp reads were sequenced bidirectionally by the Illumina platform (Illumina, San Diego, CA, USA). The obtained clean reads of a randomly selected individual of each species were used for de novo assembly using the Trinity program [36]. The transcripts were processed by CD-HIT-EST [37] to remove the redundant sequences, and the generated unigenes were then used to predict coding sequences (CDSs) with the GeneMarkS-T program [38].
Orthologous genes were identified using OrthoFinder v2.3.11 [39]. The salmon program v1.0.0 [40] was used to calculate the expected read counts and transcripts per million (TPM) value for every orthologous gene, which were then used to identify differentially expressed genes (DEGs) with the DEBrowser program [41]. The genes with posterior fold changes (FC) in A. camellia against A. chekiangensis over two (i.e., FC > 2 or FC < 0.5) and with highly significant posterior probabilities of differential expression (Padj < 0.05) were considered to be DEGs. It should be noted that one of our candidate genes for the galactose derivatives metabolism had two closely related copies (NAGA and NAGA-like, see below), which made it challenging to pinpoint the true source of their mapped reads. In order to differentiate the relative expression levels between the copies, we initially extracted all reads that map to the two copies using bowtie2 program [42] and samtools [43]. We then randomly selected five 50 bp variable segments (in each segment, at least seven variable sites occurred between the two gene copies) as baits, and directly counted the number of reads that match the baits using grep module of seqkit program [44].

3. Results

Based on the morphological characteristics and DNA barcoding using mitochondrial COI sequences, six distinct Andrena species were discovered. Four species were recognized: A. camellia, A. hunanensis, A. striata, and A. chekiangensis. Since neither GenBank blasting nor BOLDSYSTEMS searching produced any COI hits for the two remaining species, they were temporarily designated as Andrena sp. 1 and Andrena sp. 2 (Table 1). A total of 62.74 giga bases (Gb) of WGS clean reads were obtained for the six Andrena species (five oil-tea-specialized species and A. chekiangensis). After assembly, 345~389 Mb of contigs were generated, with an N50 contig size of 8.8~15.6 Kb (Table 2). Phylogenetic analysis showed that the known three species (A. camellia, A. hunanensis, and A. striata) and the unknown two species formed to a single clade, while A. chekiangensis and A. haemorrhoa formed another clade (Figure 2).
According to the KEGG database, α-galactosidase (EC, also known as α-galactosidase A), which is prevalent in chordates, plants, and bacteria, is not found in arthropods such as bees (Hymenoptera) and other insects. As an alternative, bees have the equivalent α-N-acetylgalactosaminidase (NAGA, EC, also called α-galactosidase B), which is a homologous gene of α-galactosidase. Similar to other bees, there was only one NAGA gene in the A. chekiangensis genome. Intriguingly, two close, similar copies of the NAGA gene were discovered in the genome of the five oil-tea-specialized species. One was the conventional NAGA, while the other appeared to be a novel copy of the conventional NAGA. For ease of use, we refer to the novel copy as a NAGA-like gene. The NAGA and NAGA-like genes were highly similar; taking A. camellia as an example, there were 86% and 78% identity sites between them at nucleotide and amino acid sequence levels, respectively. It is worth noting that NANA-like had a termination mutation in the last exon (the sixth exon) which resulted in a shortened protein (Figure 3). All genomes of the five oil-tea-specialized species and the other seven species (including A. chekiangensis) contained four of the Leloir pathway genes [22], which most organisms use to metabolize galactose: aldose 1-epimerase (galM, EC, galactokinase (galK, EC, galactose-1-phosphate uridylyltransferase (galT, EC, and UDP-galactose 4-epimerase (galE, EC
Genetic variations were surveyed within the five oil-tea-specialized species. The coding sequence of NAGA was 1320 bp in length, with 16 (1.21%) variable sites among the five species. The NAGA-like gene was shorter but, interspecifically, much more variable (2.66%) than NAGA. The four Leloir pathway genes were shorter than NAGA and NAGA-like and the number of variable sites ranked as galM > galK > galT > galE (Table 3). The sequences of the six genes of all the 12 Andrena species analyzed in this study are shown in the Supplementary Table S1. Branch model analyses were executed with the five oil-tea-specialized species as foreground clade and the remaining seven species as background clade. The results showed that NAGA-like, galK, and galT had significantly greater dN/dS ratios in the foreground clade than in the background clade (χ2 test, df = 1, p < 0.001). However, no significant divergence was seen for NAGA, galM, and galE (p > 0.2) (Table 4). We also assessed the putative positive selection sites in the two genes using the branch-site model test. With the Bayes Empirical Bayes (BEB) analysis, twelve sites in NAGA-like, four sites in galK, and one site in galT were found under positive selection with posterior probabilities >0.95.
A total of 33.7 Gb and 35.1 Gb of RNASeq clean reads were obtained for A. camellia and A. chekiangensis, respectively (Table 5). The assembly of A. camellia generated 23,087 unigenes, with a N50 value of 1668 bp. For A. chekiangensis, 18,387 unigenes were produced with a N50 value of 1692 bp. A total of 7151 orthologs were shared by the two species, with a total length of 7,847,865 bp and N50 of 1632 bp. The average value of relative expression level (TPM) of these orthologs in each sample was 140. The TPM values of the six candidate galactose metabolism genes are shown in Table 6. Taking the A. chekiangensis samples as the control group, 1987 differentially expressed genes were detected, including 1155 up-regulated (FC > 2) and 853 down-regulated (FC < 0.5) genes in A. camellia. NAGA-like, galK, and galT were significantly up-regulated in A. camellia (FC > 2, Padj < 0.05), while NAGA, galM, and galE did not deviate in expression levels between A. camellia and A. chekiangensis (Padj > 0.05) (Figure 4).

4. Discussion

Oil-tea is an important woody edible and industrial oil tree species [45]. Its product, tea oil, was categorized by the FAO (Food and Agriculture Organization of the United Nations) as a premium health-grade edible oil [46]. This plant presents a low oil yield because of self-incompatibility. Previous studies showed that the oil yield can be improved by an increase in pollinating insects [19,47]. However, blooms occur in late autumn and winter (from October to January), when bee pollinators are few due to cold temperatures. Additionally, some compounds in the nectar are toxic to most bees, including managed honey bees [13]. It is interesting to note that the poisonous elements in oil-tea nectar can be detoxified by both adults and larvae of several Andrena species. Unfortunately, despite the significant attention these species have received [47,48,49,50], little is known about the molecular mechanisms of detoxification. In this study, we presented the first genome and transcriptome sequencing of oil-tea specialized Andrena species and carried out bioinformatic analyses on the genes involved in galactose derivatives metabolism.
As stated in the introduction, in order to degrade galactose derivatives, the α-galactosidine bonds need to be first hydrolyzed to release galactose residues. In most organisms, such as chordates, plants, and bacteria, this process is accomplished by α-galactosidase A. However, honey bees and other insects have not yet been found to contain such a gene. Instead, NAGA, a homologous gene of α-galactosidase A, was commonly present in insect genomes. Although the protein produced by NAGA was initially thought to be an isozyme of α-galactosidase and given the name α-galactosidase B, it was actually an exoglycosidase acting on N-acetylgalactosamine [51]. There is no proof that it can replace α-galactosidase A’s role, which is why honey bees (such as A. mellifera and A. cerana) are unable to process oil-tea nectar. According to our molecular evolution analyses, there was no discernible selective differentiation of NAGA between the five oil-tea-specialized species and the other Andrena species. According to gene expression assessments, NAGA in A. camellia was not significantly deviated from that in A. chekiangensis (p > 0.05). As a result, we hypothesize that the conventional NAGA makes no contribution to the detoxification of oil-tea-specialized Andrena species.
The most intriguing discovery in this study might be the novel copy of NAGA, named the NAGA-like gene, in the five oil-tea-specialized Andrena species. Such a gene duplication pattern was not found in the other seven Andrena species, including A. chekiangensis which also consume oil-tea nectar, although not specifically. We also examined the genomes and transcriptomes of C. gigas, another crucial oil-tea pollinator [17,19], and no novel copy was found. Considering that the five oil-tea-specialized Andrena species formed a monophyletic group, we speculated that the NAGA-like gene was created from a particular gene-duplicating event that occurred in the common ancestor of these species. Molecular evolution analyses with branch models and branch-site models indicated that NAGA-like was under strong positive selections, a sign that a new phenotype of this gene would arise for these species [52]. The seqkit grep counts showed that the majority of reads mapping on NAGA were actually from NAGA-like. As a result, it is possible to estimate that the expression level of NAGA-like in A. camellia is ~120 times that of NAGA in the same species, or ~94 times that of NAGA in A. chekiangensis. Additionally, given that each of the 7151 orthologs had an average expression level (TPM) of 140, NAGA-like had a TPM that was around 496 times the average value. Such a high degree of NAGA-like expression suggests that it is essential for oil-tea specialization in A. camellia, and maybe for the other four oil-tea-specialized species. Since the novel NAGA-like gene was highly similar (86% DNA identity) to conventional NAGA, it was logical to assume that the NAGA-like protein could likewise catalyze N-acetylgalactosamine residue. In other words, although more research is required to confirm this idea, we propose that NAGA-like may have acquired a new role to break the α-galactosidine linkages from galactose derivatives.
There are four steps in the classic Leloir pathway. Firstly, β-d-galactose (natural galactose) is epimerized to α-d-galactose by galM. Secondly, α-d-galactose is phosphorylated to yield α-d-galactose 1-phosphate by galK. Thirdly, galT catalyzes the transfer of a UMP (uridine monophosphate) group from UDP-glucose (uridine diphosphate glucose) to galactose 1-phosphate, thereby generating glucose 1-phosphate and UDP-galactose. Finally, UDP-galactose is converted to UDP-glucose by galE [22]. Our results of the branch model and branch-site model tests showed that, galK and galT, but not galM nor galE, showed significantly larger dN/dS ratios in the five oil-tea-specialized species than in the background Andrena species. Moreover, the gene expression analyses showed that galK and galT, but not galM nor galE, was significantly more upregulated in A. camellia than in A. chekiangensis. These findings suggested that galK and galT may have been crucial in helping the oil-tea-specialized Andrena species adapt. We hypothesize that an improvement in catalytic efficiency may result from positive selection in galK and galT of the oil-tea-specialized species. In contrast, although galM and galE were also involved in galactose metabolism, no significant deviations in molecular evolution and gene expression were detected between A. camellia and A. chekiangensis, suggesting that the universal activity and quantity of these two epimerases are sufficient to deal with the catalytic demand in the oil-tea-specialized species.

5. Conclusions

Our study clearly demonstrated that the genes involved in galactose derivatives metabolism were crucial in the evolution of the oil-tea-specialized Andrena species. A novel NAGA-like gene was created to aid in the hydrolysis of the galactose residue from galactose derivatives, while the galK and galT genes were functionally improved to speed up the metabolism of the hydrolyzed galactose. It should be noted that, despite the fact that these species can handle poisonous oligosaccharides, their too-small population densities make it appear as though they are unable to meet the pollination needs of oil-tea. Our findings would provide insight into the poisoning and detoxifying processes of various bee species. We propose that the genetic engineering of relevant genes in cultivated species such as A. mellifera may finally assist in meeting the enormous pollination needs.

Supplementary Materials

The following supporting information can be downloaded at:, Table S1: Genes involved in galactose derivatives metabolism used in this study.

Author Contributions

Conceptualization, G.L., F.Z. and Z.H.; methodology, G.L., B.H. and F.Z.; software, G.L.; validation, formal analysis, investigation, resources, data curation, visualization, B.H., T.S., K.J.; writing—original draft preparation, writing—review and editing, G.L. and F.Z.; supervision, project administration and funding acquisition, F.Z. and Z.H. All authors have read and agreed to the published version of the manuscript.


This research was funded by the Natural Science Foundation of Jiangxi, China (No. 20212BAB215024, 20212ACB205006), the Jiangxi “Double Thousand Plan” (No. jxsq2020101050), and the Science and Technology Foundation of Jiangxi Provincial Department of Education (No. GJJ201007, GJJ190538).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

All data are presented in the text.

Conflicts of Interest

The authors declare no conflict of interest.


  1. Peters, R.S.; Krogmann, L.; Mayer, C.; Donath, A.; Gunkel, S.; Meusemann, K.; Kozlov, A.; Podsiadlowski, L.; Petersen, M.; Lanfear, R.; et al. Evolutionary history of the Hymenoptera. Curr. Biol. 2017, 27, 1013–1018. [Google Scholar] [CrossRef] [PubMed]
  2. Michener, C.D. The Bees of the World, 2nd ed.; The Johns Hopkins University Press: Baltimore, MD, USA, 2007. [Google Scholar]
  3. Potts, S.G.; Imperatriz-Fonseca, V.; Ngo, H.T.; Aizen, M.A.; Biesmeijer, J.C.; Breeze, T.D.; Dicks, L.V.; Garibaldi, L.A.; Hill, R.; Settele, J.; et al. Safeguarding pollinators and their values to human well-being. Nature 2016, 540, 220–229. [Google Scholar] [CrossRef] [PubMed]
  4. Cane, J.H.; Sipes, S. Characterizing floral specialization by bees: Analytical methods and revised lexicon for oligolecty. In Plant-Pollinator Interactions: From Specialization to Generalization; Waser, N.M., Ollerton, J., Eds.; The University of Chicago Press: Chicago, IL, USA, 2006; pp. 99–121. [Google Scholar]
  5. Goulson, D. Bumblebees: Behaviour, Ecology, and Conservation; Oxford University Press Inc.: New York, NY, USA, 2010. [Google Scholar]
  6. Minckley, R.L.; Roulston, T.H. Incidental mutualisms and pollen specialization among bees. In Plant-Pollinator Interactions: From Specialization to Generalization; Waser, N.M., Ollerton, J., Eds.; The University of Chicago Press: Chicago, IL, USA, 2006; pp. 69–98. [Google Scholar]
  7. Bossert, S.; Wood, T.J.; Patiny, S.; Michez, D.; Almeida, E.A.B.; Minckley, R.L.; Packer, L.; Neff, J.L.; Copeland, R.S.; Straka, J.; et al. Phylogeny, biogeography and diversification of the mining bee family Andrenidae. Syst. Entomol. 2022, 47, 283–302. [Google Scholar] [CrossRef]
  8. Larkin, L.L.; Neff, J.L.; Simpson, B.B. The evolution of pollen diet: Host choice and diet breadth of Andrena bees (Hymenoptera: Andrenidae). Apidologie 2008, 39, 133–145. [Google Scholar] [CrossRef]
  9. Wood, T.J.; Roberts, S.P.M. An assessment of historical and contemporary diet breadth in polylectic Andrena bee species. Biol. Conserv. 2017, 215, 72–80. [Google Scholar] [CrossRef]
  10. Luan, F.; Zeng, J.; Yang, Y.; He, X.; Wang, B.; Gao, Y.; Zeng, N. Recent advances in Camellia oleifera Abel: A review of nutritional constituents, biofunctional properties, and potential industrial applications. J. Funct. Food. 2020, 75, 104242. [Google Scholar] [CrossRef]
  11. Wang, X.N. Research on Phenology and Blossom Biology of Oil-Tea Camellia. Master’s Thesis, Central South University of Forestry and Technology, Changsha, China, 2011. [Google Scholar]
  12. Huang, D.Y.; Ding, L.; Zhang, Y.Z.; Huang, H.R.; Yu, J.F.; Hao, J.S.; Zhu, C.D. Life history and relevant biological features of Andrena camellia Wu (Hymenoptera: Andrenidae). Acta Entomol. Sin. 2008, 51, 778–783. [Google Scholar]
  13. Xie, Z.; Chen, X.; Qiu, J. Reproductive failure of Camellia oleifera in the plateau region of China due to a shortage of legitimate pollinators. Int. J. Agric. Biol. 2013, 15, 458–464. [Google Scholar]
  14. Zhao, S.W. Management measure for honey colony in flowering period of Camellia oleifera. Apicult. China 1993, 5, 19–20. [Google Scholar]
  15. Ding, L.; Huang, D.Y.; Zhang, Y.Z.; Huang, H.R.; Li, J.; Zhu, C.D. Observation on the nesting biology of Andrena camellia Wu (Hymenoptera: Andrenidae). Acta Entomol. Sin. 2007, 50, 1077–1082. [Google Scholar]
  16. He, B.; Su, T.J.; Niu, Z.Q.; Zhou, Z.Y.; Gu, Z.Y.; Huang, D.Y. Characterization of mitochondrial genomes of three Andrena bees (Apoidea: Andrenidae) and insights into the phylogenetics. Int. J. Biol. Macromol. 2019, 127, 118–125. [Google Scholar] [CrossRef] [PubMed]
  17. Su, T.J.; He, B.; Zhao, F.; Jiang, K.; Lin, G.; Huang, Z. Population genomics and phylogeography of Colletes gigas, a wild bee specialized on winter flowering plants. Ecol. Evol. 2022, 12, e8863. [Google Scholar] [CrossRef] [PubMed]
  18. Wu, Y.R. The pollinating bees on Camellia olifera with descriptions of 4 new species of the genus Andrena. Acta Entomol. Sin. 1977, 20, 199–204. [Google Scholar]
  19. Li, H.Y.; Luo, A.C.; Hao, Y.J.; Dou, F.Y.; Kou, R.M.; Orr, M.C.; Zhu, C.D.; Huang, D.Y. Comparison of the pollination efficiency of Apis cerana with wild bees in oil-seed camellia fields. Basic Appl. Ecol. 2021, 56, 250–258. [Google Scholar] [CrossRef]
  20. Kang, X.D.; Fan, Z.Y. Toxic contents of nectar of oil-tea flowers to honey bees. J. Bee 1991, 1, 8–10. [Google Scholar]
  21. Li, Z.; Huang, Q.; Zheng, Y.; Zhang, Y.; Li, X.; Zhong, S.; Zeng, Z. Identification of the toxic compounds in Camellia oleifera honey and pollen to honey bees (Apis mellifera). J. Agric. Food Chem. 2022, 70, 13176–13185. [Google Scholar] [CrossRef]
  22. Holden, H.M.; Rayment, I.; Thoden, J.B. Structure and function of enzymes of the Leloir pathway for galactose metabolism. J. Biol. Chem. 2003, 278, 43885–43888. [Google Scholar] [CrossRef]
  23. Vinson, C.C.; Mota, A.P.Z.; Porto, B.N.; Oliveira, T.N.; Sampaio, I.; Lacerda, A.L.; Danchin, E.G.J.; Guimaraes, P.M.; Williams, T.C.R.; Brasileiro, A.C.M. Characterization of raffinose metabolism genes uncovers a wild Arachis galactinol synthase conferring tolerance to abiotic stresses. Sci. Rep. 2020, 10, 15258. [Google Scholar] [CrossRef]
  24. Elango, D.; Rajendran, K.; Van der Laan, L.; Sebastiar, S.; Raigne, J.; Thaiparambil, N.A.; El Haddad, N.; Raja, B.; Wang, W.; Ferela, A.; et al. Raffinose family oligosaccharides: Friend or foe for human and plant health? Front. Plant Sci. 2022, 13, 829118. [Google Scholar] [CrossRef]
  25. Chen, S.; Zhou, Y.; Chen, Y.; Gu, J. fastp: An ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 2018, 34, i884–i890. [Google Scholar] [CrossRef]
  26. Li, D.; Liu, C.M.; Luo, R.; Sadakane, K.; Lam, T.W. MEGAHIT: An ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 2015, 31, 1674–1676. [Google Scholar] [CrossRef] [PubMed]
  27. Camacho, C.; Coulouris, G.; Avagyan, V.; Ma, N.; Papadopoulos, J.; Bealer, K.; Madden, T.L. BLAST+: Architecture and applications. BMC Bioinform. 2009, 10, 421. [Google Scholar] [CrossRef] [PubMed]
  28. Nguyen, L.T.; Schmidt, H.A.; von Haeseler, A.; Minh, B.Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 2015, 32, 268–274. [Google Scholar] [CrossRef]
  29. Slater, G.S.C.; Birney, E. Automated generation of heuristics for biological sequence comparison. BMC Bioinform. 2005, 6, 31. [Google Scholar] [CrossRef]
  30. Kumar, S.; Stecher, G.; Li, M.; Knyaz, C.; Tamura, K. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol. Biol. Evol. 2018, 35, 1547–1549. [Google Scholar] [CrossRef] [PubMed]
  31. Rozas, J.; Ferrer-Mata, A.; Sánchez-DelBarrio, J.C.; Guirao-Rico, S.; Librado, P.; Ramos-Onsins, S.E.; Sánchez-Gracia, A. DnaSP 6: DNA sequence polymorphism analysis of large data sets. Mol. Biol. Evol. 2017, 34, 3299–3302. [Google Scholar] [CrossRef]
  32. Sievers, F.; Higgins, D.G. Clustal omega. Curr. Protoc. Bioinf. 2014, 48, 3.13.1–3.13.16. [Google Scholar] [CrossRef]
  33. Yang, Z. PAML 4: Phylogenetic analysis by maximum likelihood. Mol. Biol. Evol. 2007, 24, 1586–1591. [Google Scholar] [CrossRef]
  34. Yang, Z.; Wong, W.S.W.; Nielsen, R. Bayes empirical Bayes inference of amino acid sites under positive selection. Mol. Biol. Evol. 2005, 22, 1107–1118. [Google Scholar] [CrossRef]
  35. Zhang, J.; Nielsen, R.; Yang, Z. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Mol. Biol. Evol. 2005, 22, 2472–2479. [Google Scholar] [CrossRef]
  36. Grabherr, M.G.; Haas, B.J.; Yassour, M.; Levin, J.Z.; Thompson, D.A.; Amit, I.; Adiconis, X.; Fan, L.; Raychowdhury, R.; Zeng, Q.D.; et al. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat. Biotechnol. 2011, 29, 644–652. [Google Scholar] [CrossRef] [PubMed]
  37. Li, W.Z.; Godzik, A. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 2006, 22, 1658–1659. [Google Scholar] [CrossRef] [PubMed]
  38. Tang, S.; Lomsadze, A.; Borodovsky, M. Identification of protein coding regions in RNA transcripts. Nucl. Acid. Res. 2015, 43, e78. [Google Scholar] [CrossRef] [PubMed]
  39. Emms, D.M.; Kelly, S. OrthoFinder: Phylogenetic orthology inference for comparative genomics. Genome Biol. 2019, 20, 238. [Google Scholar] [CrossRef]
  40. Patro, R.; Duggal, G.; Love, M.I.; Irizarry, R.A.; Kingsford, C. Salmon provides fast and bias-aware quantification of transcript expression. Nat. Methods 2017, 14, 417–419. [Google Scholar] [CrossRef]
  41. Kucukural, A.; Yukselen, O.; Ozata, D.M.; Moore, M.J.; Garber, M. DEBrowser: Interactive differential expression analysis and visualization tool for count data. BMC Genom. 2019, 20, 6. [Google Scholar] [CrossRef]
  42. Langmead, B.; Salzberg, S. Fast gapped-read alignment with Bowtie 2. Nat. Methods 2012, 9, 357–359. [Google Scholar] [CrossRef]
  43. Li, H.; Handsaker, B.; Wysoker, A.; Fennell, T.; Ruan, J.; Homer, N.; Marth, G.; Abecasis, G.; Durbin, R. The sequence alignment/map format and SAMtools. Bioinformatics 2009, 25, 2078–2079. [Google Scholar] [CrossRef]
  44. Shen, W.; Le, S.; Li, Y.; Hu, F. SeqKit: A cross-platform and ultrafast toolkit for FASTA/Q File manipulation. PLoS ONE 2016, 11, e0163962. [Google Scholar] [CrossRef]
  45. Wen, Y.; Su, S.C.; Ma, L.Y.; Yang, S.Y.; Wang, Y.W.; Wang, X.N. Effects of canopy microclimate on fruit yield and quality of Camellia oleifera. Sci. Horticult. 2018, 235, 132–141. [Google Scholar]
  46. Feng, J.L.; Jiang, Y.; Yang, Z.J.; Chen, S.P.; El-Kassaby, Y.A.; Chen, H. Marker-assisted selection in C. oleifera hybrid population. Silvae Genet. 2020, 69, 63–72. [Google Scholar] [CrossRef]
  47. Deng, Y.; Yu, X.; Liu, Y. The role of native bees on the reproductive success of Camellia oleifera in Hunan Province, Central South China. Acta Ecol. Sin. 2010, 30, 4427–4436. [Google Scholar]
  48. Huang, D.; Su, T.; Qu, L.; Wu, Y.; Gu, P.; He, B.; Xu, X.; Zhu, C. The complete mitochondrial genome of the Colletes gigas (Hymenoptera: Colletidae: Colletinae). Mit. DNA Part A 2016, 27, 3878–3879. [Google Scholar] [CrossRef] [PubMed]
  49. Huang, D.Y.; He, B.; Gu, P.; Su, T.J.; Zhu, C.D. Discussion on current situation and research direction of pollination insects of Camellia oleifera. J. Environ. Entomol. 2017, 39, 213–220. [Google Scholar]
  50. Zhou, Q.S.; Luo, A.; Zhang, F.; Niu, Z.Q.; Wu, Q.T.; Xiong, M.; Orr, M.C.; Zhu, C.D. The first draft genome of the plasterer bee Colletes gigas (Hymenoptera: Colletidae: Colletes). Genome Biol. Evol. 2020, 12, 860–866. [Google Scholar] [CrossRef]
  51. Michalski, J.C.; Klein, A. Glycoprotein lysosomal storage disorders: K- and L-mannosidosis, fucosidosis and K-N-acetylgalactosaminidase deficiency. Biochim. Biophys. Acta 1999, 1455, 69–84. [Google Scholar] [CrossRef]
  52. Vallender, E.J.; Lahn, B.T. Positive selection on the human genome. Hum. Mol. Genet. 2004, 13, R245–R254. [Google Scholar] [CrossRef]
Figure 1. Sampling sites of the six Andrena species of pollinating oil-tea (red dots, oil-tea specialized species; blue dot, non-specialized oil-tea pollinator).
Figure 1. Sampling sites of the six Andrena species of pollinating oil-tea (red dots, oil-tea specialized species; blue dot, non-specialized oil-tea pollinator).
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Figure 2. Phylogenetic relationship of 12 Andrena species analyzed in this study (red, specialized pollinator of oil-tea; blue, non-specialized pollinator of oil-tea; numbers beside each node represent percentages of bootstrap values).
Figure 2. Phylogenetic relationship of 12 Andrena species analyzed in this study (red, specialized pollinator of oil-tea; blue, non-specialized pollinator of oil-tea; numbers beside each node represent percentages of bootstrap values).
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Figure 3. Alignment of nucleotide and amino acid sequences of the last exons of NAGA and NAGA-like genes of A. camellia (note in the red box the termination mutation in NAGA-like).
Figure 3. Alignment of nucleotide and amino acid sequences of the last exons of NAGA and NAGA-like genes of A. camellia (note in the red box the termination mutation in NAGA-like).
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Figure 4. Differentially expressed genes of A. camellia against A. chekiangensis (blue dots, down-regulated; red dots, up-regulated; green stars, the three up-regulated genes involved in galactose derivatives metabolism).
Figure 4. Differentially expressed genes of A. camellia against A. chekiangensis (blue dots, down-regulated; red dots, up-regulated; green stars, the three up-regulated genes involved in galactose derivatives metabolism).
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Table 1. Sample information of six Andrena species collected from oil-tea blossoms.
Table 1. Sample information of six Andrena species collected from oil-tea blossoms.
XJ01A. camelliaXiajiang, Jiangxi115.128527.6546
QY01A. hunanensisQingyang, Anhui117.879630.5977
RX01A. striataRongxian, Sichuan104.291329.4377
CN02A. sp. 1Cangnan, Zhejiang120.255627.4591
DY03A. sp. 2Dongyuan, Guangdong114.979224.1905
NX04A. chekiangensisNingxiang, Hunan112.420627.9832
Table 2. Short reads and assembly of next-generation genome of six Andrena species.
Table 2. Short reads and assembly of next-generation genome of six Andrena species.
A. camellia10.38SRR23869504369.711.1
A. hunanensis11.01SRR23869503384.38.2
A. striata9.79SRR23869502393.18.5
A. sp. 110.75SRR23869501363.29.6
A. sp. 29.74SRR23869500353.514.7
A. chekiangensis10.02SRR23869499365.711.6
Table 3. Sequence length and genetic variation of genes involved in galactose derivatives metabolism within five oil-tea-specialized Andrena species.
Table 3. Sequence length and genetic variation of genes involved in galactose derivatives metabolism within five oil-tea-specialized Andrena species.
GeneLengthVariable SitesPercent of Variable Sites
Table 4. Branch model analyses of genes involved in galactose derivatives metabolism.
Table 4. Branch model analyses of genes involved in galactose derivatives metabolism.
GeneForegroundBackground2ΔlnLp (df = 1)
NAGA-like0.6800.021145.673<1.000 × 10−10
galK0.8640.16124.2798.336 × 10−7
galT0.3870.08812.7613.540 × 10−4
Table 5. RNASeq clean reads of A. camellia and A. chekiangensis.
Table 5. RNASeq clean reads of A. camellia and A. chekiangensis.
Table 6. Gene expression analyses of genes involved in galactose derivatives metabolism.
Table 6. Gene expression analyses of genes involved in galactose derivatives metabolism.
GeneTPM (Mean ± SD)FCPadj
A. camelliaA. chekiangensis
NAGA574.88 ± 162.33740.45 ± 470.320.6390.387
NAGA-like69,465.93 ± 7690.830+∞−∞
galM537.64 ± 78.69210.82 ±
galK172.87 ± 47.9241.77 ± 34.053.350.016
galT987.77 ± 139.04318.55 ± 57.032.991.781 × 10−12
galE32.45 ± 10.0721.82 ± 14.731.230.624
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Lin, G.; Huang, Z.; He, B.; Jiang, K.; Su, T.; Zhao, F. Evolutionary Adaptation of Genes Involved in Galactose Derivatives Metabolism in Oil-Tea Specialized Andrena Species. Genes 2023, 14, 1117.

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Lin G, Huang Z, He B, Jiang K, Su T, Zhao F. Evolutionary Adaptation of Genes Involved in Galactose Derivatives Metabolism in Oil-Tea Specialized Andrena Species. Genes. 2023; 14(5):1117.

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Lin, Gonghua, Zuhao Huang, Bo He, Kai Jiang, Tianjuan Su, and Fang Zhao. 2023. "Evolutionary Adaptation of Genes Involved in Galactose Derivatives Metabolism in Oil-Tea Specialized Andrena Species" Genes 14, no. 5: 1117.

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