Phenotypic Plasticity: What Has DNA Methylation Got to Do with It?
Abstract
:Simple Summary
Abstract
1. Phenotypic Plasticity in Insects
2. Epigenetics and Plasticity
3. DNA Methylation
4. What Are the Functions of DNA Methylation in Insects?
5. How Does DNA Methylation Respond to Environmental Change and Phenotypic Plasticity?
6. Non-Methylation Functions of the DNMT Genes
7. How Might We Demonstrate a Role of DNA Methylation as a Causative Factor in Plasticity?
8. Conclusions
- A Measurement of DNA methylation:
- The gold standard for measuring DNA methylation is whole genome bisulfite sequencing (WGBS) [115]. This technique is well established and involves chemical treatment of the DNA, converting unmethylated cytosines to uracils that are then detected after sequencing and comparison to the reference genome. Alternative sequencing technologies, such as the Oxford Nanopore, that do not rely on chemical modification of the DNA, are becoming available and are rapidly expanding this field [116] and may allow for the simultaneous detection of 5-methylcytosine and its oxidised derivatives, such as 5-hydroxymethylcytosine.
- B Experimental design:
- Studies need adequate statistical power as a lack of replication has been associated with spurious associations between DNA methylation and differential expression [57]. Biological replicates should consist of as few individuals as possible. If strong genetic differentiation is suspected among samples, this will increase the noise in the experiment, making it more difficult to detect biological signals, and if samples are genetically similar, this may predispose for false positives. Genetically related individuals should be considered as ‘technical’ rather than ‘biological replicates’ to be assured that the differences identified are biological and not simply genotype-specific (e.g., among different colonies of honey bees [65]). In practice, for social insects, this means that one hive/colony is a biological replicate.
- C Analysis of DNA methylation and comparisons with gene expression:
- Careful consideration needs to be given to analysis to ensure their appropriateness for the question asked. Pipelines often use models made for methylation analysis of mammals rather than insects. In mammals DNA methylation is dense enough to approximate a continuous trait (e.g., 76% of cytosines are methylated for house mice, while only 0.4–1.5% are methylated for honey bees). A recent pipeline (BWASP/R) has been developed that is tailored to species with low-levels of DNA methylation [117] and use of a standardised approach specific to insects will certainly facilitate our understanding of the role of DNA methylation in phenotypic plasticity. In species with low levels of methylation, the methylation status of cytosines should be determined on a case-by-case basis using a statistical test against the genomic background. % difference of methylation status has no biological interpretation as individual cytosines are either methylated or not. Gene-level methylation should then be assessed by a summary metric of % cytosines methylated contained within the gene body or within biologically relevant and consistent gene regions. Comparisons between DNA methylation and gene expression need to be modified to account for the fact that differences in DNA methylation may have different functions depending on where in the gene the methylation mark is located and these approaches should also be standardised to facilitate comparison between species and studies. Network based approaches can also be employed as DNA methylation can exhibit network structures just as gene expression can, and these can be preserved in gene co-expression networks [59].
- D Cell-type/Tissue-specific analysis:
- Phenotypic plasticity experiments have often been carried out on whole tissues or bodies that contain multiple cell types. This masks differences in DNA methylation that occurs only in a subset of cells. There have been some approaches to examine ‘bulk WGBS’ data from mammals to identify underlying cell-type-specific patterns [118]. However, such approaches are unlikely to be useful at present in insects as the patterns of DNA methylation differ substantially from mammals. Cell-type-specific assessment of DNA methylation is possible in other animals, using either cell-sorting or single-cell analysis, and could be adapted for use in insects. In the short-term, identification of the smallest amount of and most specific tissues that are affected by plasticity and possibly even regions of those tissues (e.g., mushroom bodies for behavioural plasticity) should be targeted for studies of DNA methylation.
- E Functional analysis:
- Many studies that report differences in DNA methylation associated with plasticity lack a definitive functional experiment. In non-model systems, the tools available to do this are limited, and RNA interference or treatment with pharmacological inhibitors is necessary. Although there are limitations to these approaches (as discussed in Section 7), these are still powerful approaches to examine gene function, but this needs to be linked a priori with discrete phenotypes of interest. Of technical importance is to ensure a meaningful level of reduction of the Dnmt mRNA in the tissue of interest at the appropriate timing and combine this with an assessment of treated individuals to respond plastically. Further, this needs to be combined with techniques (such as WGBS) to demonstrate the reduction in DNA methylation and to locate specific regions of the genome that have altered methylation in response to the treatment and RNA-seq to be able to test the link with changes in gene expression. Although the sequencing we suggest does increase the cost and complexity of any experiments, we believe that these links are necessary to fully interpret and link DNA methylation with gene expression and plasticity. Any experiment that does not demonstrate core mechanistic links (Dmnt gene expression reduction leading to reduced DNA methylation leading to altered gene expression in the appropriate tissue/cell type at the appropriate time leading to predicted changes of phenotypic plasticity) has its ability to speak about causality reduced. Other techniques to manipulate gene expression or DNA methylation are becoming available and should be considered.
- F Establishing the consequence of specific changes to the methylome:
- The ultimate test of the effect of DNA methylation is to be able to experimentally manipulate DNA methylation at a particular locus and show that there are predictable downstream consequences for phenotypic plasticity. Tools, such as the CRISPRoff and CRISPRon system [114], can be investigated for this purpose for insects.
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Wagner, D.L.; Grames, E.M.; Forister, M.L.; Berenbaum, M.R.; Stopak, D. Insect decline in the Anthropocene: Death by a thousand cuts. Proc. Natl. Acad. Sci. USA 2021, 118, e2023989118. [Google Scholar] [CrossRef] [PubMed]
- Mann, M.E.; Rahmstorf, S.; Kornhuber, K.; Steinman, B.A.; Miller, S.K.; Coumou, D. Influence of Anthropogenic Climate Change on Planetary Wave Resonance and Extreme Weather Events. Sci. Rep. 2017, 7, 45242. [Google Scholar] [CrossRef] [Green Version]
- Power, S.; Delage, F.; Chung, C.; Kociuba, G.; Keay, K. Robust twenty-first-century projections of El Nino and related precipitation variability. Nature 2013, 502, 541–545. [Google Scholar] [CrossRef] [PubMed]
- West-Eberhard, M.J. Developmental Plasticity and Evolution; Oxford University Press: New York, NY, USA; Oxford, UK, 2003; 794p. [Google Scholar]
- Snell-Rood, E.C.; Kobiela, M.E.; Sikkink, K.L.; Shephard, A.M. Mechanisms of Plastic Rescue in Novel Environments. Annu. Rev. Ecol. Evol. Syst. 2018, 49, 331–354. [Google Scholar] [CrossRef]
- Jones, B.M.; Robinson, G.E. Genetic accommodation and the role of ancestral plasticity in the evolution of insect eusociality. J. Exp. Biol. 2018, 221, jeb153163. [Google Scholar] [CrossRef] [Green Version]
- West-Eberhard, M.J. Phenotypic Plasticity and the Origins of Diversity. Annu. Rev. Ecol. Syst. 1989, 20, 249–278. [Google Scholar] [CrossRef]
- Hendry, A.P. Key Questions on the Role of Phenotypic Plasticity in Eco-Evolutionary Dynamics. J. Hered. 2016, 107, 25–41. [Google Scholar] [CrossRef] [Green Version]
- Pigliucci, M.; Murren, C.J.; Schlichting, C.D. Phenotypic plasticity and evolution by genetic assimilation. J. Exp. Biol. 2006, 209, 2362–2367. [Google Scholar] [CrossRef] [Green Version]
- Brakefield, P.M.; Gates, J.; Keys, D.; Kesbeke, F.; Wijngaarden, P.J.; Monteiro, A.; French, V.; Carroll, S.B. Development, plasticity and evolution of butterfly eyespot patterns. Nature 1996, 384, 236–242. [Google Scholar] [CrossRef]
- Moczek, A.P.; Nijhout, H.F. Developmental mechanisms of threshold evolution in a polyphenic beetle. Evol. Dev. 2002, 4, 252–264. [Google Scholar] [CrossRef]
- Bretman, A.; Gage, M.J.; Chapman, T. Quick-change artists: Male plastic behavioural responses to rivals. Trends Ecol. Evol. 2011, 26, 467–473. [Google Scholar] [CrossRef]
- Parker, D.J.; Cunningham, C.B.; Walling, C.A.; Stamper, C.E.; Head, M.L.; Roy-Zokan, E.M.; McKinney, E.C.; Ritchie, M.G.; Moore, A.J. Transcriptomes of parents identify parenting strategies and sexual conflict in a subsocial beetle. Nat. Commun. 2015, 6, 8449. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Snell-Rood, E.C.; Steck, M.K. Behaviour shapes environmental variation and selection on learning and plasticity: Review of mechanisms and implications. Anim. Behav. 2019, 147, 147–156. [Google Scholar] [CrossRef]
- Roth, O.; Beemelmanns, A.; Barribeau, S.M.; Sadd, B.M. Recent advances in vertebrate and invertebrate transgenerational immunity in the light of ecology and evolution. Heredity 2018, 121, 225–238. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Beldade, P.; Brakefield, P.M. The genetics and evo-devo of butterfly wing patterns. Nat. Rev. Genet. 2002, 3, 442–452. [Google Scholar] [CrossRef] [PubMed]
- Simpson, S.J.; Sword, G.A.; Lo, N. Polyphenism in insects. Curr. Biol. 2011, 21, R738–R749. [Google Scholar] [CrossRef] [Green Version]
- Brisson, J.A. Aphid wing dimorphisms: Linking environmental and genetic control of trait variation. Philos Trans. R. Soc. Lond. B Biol. Sci. 2010, 365, 605–616. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cridge, A.G.; Leask, M.P.; Duncan, E.J.; Dearden, P.K. What do studies of insect polyphenisms tell us about nutritionally-triggered epigenomic changes and their consequences? Nutrients 2015, 7, 1787–1797. [Google Scholar] [CrossRef] [Green Version]
- Ogawa, K.; Miura, T. Aphid polyphenisms: Trans-generational developmental regulation through viviparity. Front. Physiol. 2014, 5, 1. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Duncan, E.J.; Leask, M.P.; Dearden, P.K. The pea aphid (Acyrthosiphon pisum) genome encodes two divergent early developmental programs. Dev. Biol. 2013, 377, 262–274. [Google Scholar] [CrossRef] [Green Version]
- Duncan, E.J.; Gluckman, P.D.; Dearden, P.K. Epigenetics, plasticity, and evolution: How do we link epigenetic change to phenotype? J. Exp. Zool. B Mol. Dev. Evol. 2014, 322, 208–220. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Cavalieri, V. The Expanding Constellation of Histone Post-Translational Modifications in the Epigenetic Landscape. Genes 2021, 12, 1596. [Google Scholar] [CrossRef] [PubMed]
- Choudhary, C.; Sharma, S.; Meghwanshi, K.K.; Patel, S.; Mehta, P.; Shukla, N.; Do, D.N.; Rajpurohit, S.; Suravajhala, P.; Shukla, J.N. Long Non-Coding RNAs in Insects. Animal 2021, 11, 1118. [Google Scholar] [CrossRef]
- Lezcano, O.M.; Sanchez-Polo, M.; Ruiz, J.L.; Gomez-Diaz, E. Chromatin Structure and Function in Mosquitoes. Front. Genet. 2020, 11, 602949. [Google Scholar] [CrossRef] [PubMed]
- Nilsson, E.E.; Sadler-Riggleman, I.; Skinner, M.K. Environmentally induced epigenetic transgenerational inheritance of disease. Env. Epigenet. 2018, 4, dvy016. [Google Scholar] [CrossRef] [Green Version]
- Mukherjee, K.; Twyman, R.M.; Vilcinskas, A. Insects as models to study the epigenetic basis of disease. Prog. Biophys. Mol. Biol. 2015, 118, 69–78. [Google Scholar] [CrossRef]
- Bogan, S.N.; Johnson, K.M.; Hofmann, G.E. Changes in Genome-Wide Methylation and Gene Expression in Response to Future pCO2 Extremes in the Antarctic Pteropod Limacina helicina antarctica. Front. Mar. Sci. 2020, 6, 788. [Google Scholar] [CrossRef]
- Morgan, H.D.; Sutherland, H.G.; Martin, D.I.; Whitelaw, E. Epigenetic inheritance at the agouti locus in the mouse. Nat. Genet. 1999, 23, 314–318. [Google Scholar] [CrossRef]
- Waterland, R.A.; Jirtle, R.L. Transposable elements: Targets for early nutritional effects on epigenetic gene regulation. Mol. Cell Biol. 2003, 23, 5293–5300. [Google Scholar] [CrossRef] [Green Version]
- Cropley, J.E.; Suter, C.M.; Beckman, K.B.; Martin, D.I. Germ-line epigenetic modification of the murine A vy allele by nutritional supplementation. Proc. Natl. Acad. Sci. USA 2006, 103, 17308–17312. [Google Scholar] [CrossRef] [Green Version]
- Wolff, G.L.; Kodell, R.L.; Moore, S.R.; Cooney, C.A. Maternal epigenetics and methyl supplements affect agouti gene expression in Avy/a mice. FASEB J. 1998, 12, 949–957. [Google Scholar] [CrossRef] [Green Version]
- Richard, G.; Le Trionnaire, G.; Danchin, E.; Sentis, A. Epigenetics and insect polyphenism: Mechanisms and climate change impacts. Curr. Opin. Insect Sci. 2019, 35, 138–145. [Google Scholar] [CrossRef]
- Oldroyd, B.P.; Yagound, B. The role of epigenetics, particularly DNA methylation, in the evolution of caste in insect societies. Philos Trans. R. Soc. Lond. B Biol. Sci. 2021, 376, 20200115. [Google Scholar] [CrossRef]
- Pajares, M.J.; Palanca-Ballester, C.; Urtasun, R.; Alemany-Cosme, E.; Lahoz, A.; Sandoval, J. Methods for analysis of specific DNA methylation status. Methods 2021, 187, 3–12. [Google Scholar] [CrossRef]
- Zemach, A.; McDaniel, I.E.; Silva, P.; Zilberman, D. Genome-wide evolutionary analysis of eukaryotic DNA methylation. Science 2010, 328, 916–919. [Google Scholar] [CrossRef] [Green Version]
- Feng, S.; Cokus, S.J.; Zhang, X.; Chen, P.Y.; Bostick, M.; Goll, M.G.; Hetzel, J.; Jain, J.; Strauss, S.H.; Halpern, M.E.; et al. Conservation and divergence of methylation patterning in plants and animals. Proc. Natl. Acad. Sci. USA 2010, 107, 8689–8694. [Google Scholar] [CrossRef] [Green Version]
- Goll, M.G.; Bestor, T.H. Eukaryotic cytosine methyltransferases. Annu. Rev. Biochem. 2005, 74, 481–514. [Google Scholar] [CrossRef] [Green Version]
- Schmitz, R.J.; Lewis, Z.A.; Goll, M.G. DNA Methylation: Shared and Divergent Features across Eukaryotes. Trends Genet. 2019, 35, 818–827. [Google Scholar] [CrossRef]
- Tahiliani, M.; Koh, K.P.; Shen, Y.; Pastor, W.A.; Bandukwala, H.; Brudno, Y.; Agarwal, S.; Iyer, L.M.; Liu, D.R.; Aravind, L.; et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 2009, 324, 930–935. [Google Scholar] [CrossRef] [Green Version]
- Shen, L.; Song, C.X.; He, C.; Zhang, Y. Mechanism and function of oxidative reversal of DNA and RNA methylation. Annu. Rev. Biochem. 2014, 83, 585–614. [Google Scholar] [CrossRef] [Green Version]
- Klungland, A.; Robertson, A.B. Oxidized C5-methyl cytosine bases in DNA: 5-Hydroxymethylcytosine; 5-formylcytosine; and 5-carboxycytosine. Free Radic. Biol. Med. 2017, 107, 62–68. [Google Scholar] [CrossRef]
- du Preez, P.H.; Breeds, K.; Burger, N.F.V.; Swiegers, H.W.; Truter, J.C.; Botha, A.M. DNA Methylation and Demethylation Are Regulated by Functional DNA Methyltransferases and DnTET Enzymes in Diuraphis noxia. Front. Genet. 2020, 11, 452. [Google Scholar] [CrossRef]
- Rasmussen, E.M.K.; Vagbo, C.B.; Munch, D.; Krokan, H.E.; Klungland, A.; Amdam, G.V.; Dahl, J.A. DNA base modifications in honey bee and fruit fly genomes suggest an active demethylation machinery with species- and tissue-specific turnover rates. Biochem. Biophys. Rep. 2016, 6, 9–15. [Google Scholar] [CrossRef] [Green Version]
- Wojciechowski, M.; Rafalski, D.; Kucharski, R.; Misztal, K.; Maleszka, J.; Bochtler, M.; Maleszka, R. Insights into DNA hydroxymethylation in the honeybee from in-depth analyses of TET dioxygenase. Open Biol. 2014, 4, 140110. [Google Scholar] [CrossRef] [Green Version]
- Wu, H.; Zhang, Y. Reversing DNA methylation: Mechanisms, genomics, and biological functions. Cell 2014, 156, 45–68. [Google Scholar] [CrossRef] [Green Version]
- Bird, A. DNA methylation patterns and epigenetic memory. Genes Dev. 2002, 16, 6–21. [Google Scholar] [CrossRef] [Green Version]
- Zhang, T.; Song, W.; Li, Z.; Qian, W.; Wei, L.; Yang, Y.; Wang, W.; Zhou, X.; Meng, M.; Peng, J.; et al. Kruppel homolog 1 represses insect ecdysone biosynthesis by directly inhibiting the transcription of steroidogenic enzymes. Proc. Natl. Acad. Sci. USA 2018, 115, 3960–3965. [Google Scholar] [CrossRef] [Green Version]
- Lewis, S.H.; Ross, L.; Bain, S.A.; Pahita, E.; Smith, S.A.; Cordaux, R.; Miska, E.A.; Lenhard, B.; Jiggins, F.M.; Sarkies, P. Widespread conservation and lineage-specific diversification of genome-wide DNA methylation patterns across arthropods. PLoS Genet. 2020, 16, e1008864. [Google Scholar] [CrossRef]
- Glastad, K.M.; Hunt, B.G.; Goodisman, M.A. Evolutionary insights into DNA methylation in insects. Curr. Opin. Insect. Sci. 2014, 1, 25–30. [Google Scholar] [CrossRef]
- Bewick, A.J.; Vogel, K.J.; Moore, A.J.; Schmitz, R.J. Evolution of DNA Methylation across Insects. Mol. Biol. Evol. 2017, 34, 654–665. [Google Scholar] [CrossRef] [Green Version]
- Provataris, P.; Meusemann, K.; Niehuis, O.; Grath, S.; Misof, B. Signatures of DNA Methylation across Insects Suggest Reduced DNA Methylation Levels in Holometabola. Genome Biol. Evol. 2018, 10, 1185–1197. [Google Scholar] [CrossRef] [Green Version]
- Dyson, C.J.; Goodisman, M.A.D. Gene Duplication in the Honeybee: Patterns of DNA Methylation, Gene Expression, and Genomic Environment. Mol. Biol. Evol. 2020, 37, 2322–2331. [Google Scholar] [CrossRef]
- Lyko, F.; Foret, S.; Kucharski, R.; Wolf, S.; Falckenhayn, C.; Maleszka, R. The honey bee epigenomes: Differential methylation of brain DNA in queens and workers. PLoS Biol. 2010, 8, e1000506. [Google Scholar] [CrossRef] [Green Version]
- Sarda, S.; Zeng, J.; Hunt, B.G.; Yi, S.V. The evolution of invertebrate gene body methylation. Mol. Biol. Evol. 2012, 29, 1907–1916. [Google Scholar] [CrossRef] [Green Version]
- Cunningham, C.B.; Ji, L.; Wiberg, R.A.; Shelton, J.; McKinney, E.C.; Parker, D.J.; Meagher, R.B.; Benowitz, K.M.; Roy-Zokan, E.M.; Ritchie, M.G.; et al. The Genome and Methylome of a Beetle with Complex Social Behavior, Nicrophorus vespilloides (Coleoptera: Silphidae). Genome Biol. Evol. 2015, 7, 3383–3396. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Libbrecht, R.; Oxley, P.R.; Keller, L.; Kronauer, D.J. Robust DNA Methylation in the Clonal Raider Ant Brain. Curr. Biol. 2016, 26, 391–395. [Google Scholar] [CrossRef] [Green Version]
- Bonasio, R.; Li, Q.; Lian, J.; Mutti, N.S.; Jin, L.; Zhao, H.; Zhang, P.; Wen, P.; Xiang, H.; Ding, Y.; et al. Genome-wide and caste-specific DNA methylomes of the ants Camponotus floridanus and Harpegnathos saltator. Curr. Biol. 2012, 22, 1755–1764. [Google Scholar] [CrossRef] [Green Version]
- Morandin, C.; Brendel, V.P.; Sundstrom, L.; Helantera, H.; Mikheyev, A.S. Changes in gene DNA methylation and expression networks accompany caste specialization and age-related physiological changes in a social insect. Mol. Ecol. 2019, 28, 1975–1993. [Google Scholar] [CrossRef] [PubMed]
- Yan, H.; Bonasio, R.; Simola, D.F.; Liebig, J.; Berger, S.L.; Reinberg, D. DNA methylation in social insects: How epigenetics can control behavior and longevity. Annu. Rev. Entomol. 2015, 60, 435–452. [Google Scholar] [CrossRef]
- Cunningham, C.B.; Ji, L.; McKinney, E.C.; Benowitz, K.M.; Schmitz, R.J.; Moore, A.J. Changes of gene expression but not cytosine methylation are associated with male parental care reflecting behavioural state, social context and individual flexibility. J. Exp. Biol. 2019, 222, jeb188649. [Google Scholar] [CrossRef] [Green Version]
- Marshall, H.; Lonsdale, Z.N.; Mallon, E.B. Methylation and gene expression differences between reproductive and sterile bumblebee workers. Evol. Lett. 2019, 3, 485–499. [Google Scholar] [CrossRef] [Green Version]
- Bebane, P.S.A.; Hunt, B.J.; Pegoraro, M.; Jones, A.R.C.; Marshall, H.; Rosato, E.; Mallon, E.B. The effects of the neonicotinoid imidacloprid on gene expression and DNA methylation in the buff-tailed bumblebee Bombus terrestris. Proc. Biol. Sci. 2019, 286, 20190718. [Google Scholar] [CrossRef]
- 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. 2018, 9, 3468. [Google Scholar] [CrossRef] [PubMed]
- Cardoso-Junior, C.A.M.; Yagound, B.; Ronai, I.; Remnant, E.J.; Hartfelder, K.; Oldroyd, B.P. DNA methylation is not a driver of gene expression reprogramming in young honey bee workers. Mol. Ecol. 2021, 30, 4804–4818. [Google Scholar] [CrossRef]
- Li, B.; Hu, P.; Zhu, L.B.; You, L.L.; Cao, H.H.; Wang, J.; Zhang, S.Z.; Liu, M.H.; Toufeeq, S.; Huang, S.J.; et al. DNA Methylation Is Correlated with Gene Expression during Diapause Termination of Early Embryonic Development in the Silkworm (Bombyx mori). Int. J. Mol. Sci. 2020, 21, 671. [Google Scholar] [CrossRef] [Green Version]
- Gegner, J.; Vogel, H.; Billion, A.; Förster, F.; Vilcinskas, A. Complete Metamorphosis in Manduca sexta Involves Specific Changes in DNA Methylation Patterns. Front. Ecol. Evol. 2021, 9, 104. [Google Scholar] [CrossRef]
- Herb, B.R.; Shook, M.S.; Fields, C.J.; Robinson, G.E. Defense against territorial intrusion is associated with DNA methylation changes in the honey bee brain. BMC Genom. 2018, 19, 216. [Google Scholar] [CrossRef] [Green Version]
- Mashoodh, R.; Sarkies, P.; Westoby, J.; Kilner, R.M. Evolved changes in DNA methylation in response to the sustained loss of parental care in the burying beetle. bioRxiv 2021. [Google Scholar] [CrossRef]
- Duncan, E.J.; Leask, M.P.; Dearden, P.K. Genome Architecture Facilitates Phenotypic Plasticity in the Honeybee (Apis mellifera). Mol. Biol. Evol. 2020, 37, 1964–1978. [Google Scholar] [CrossRef] [Green Version]
- Li-Byarlay, H.; Boncristiani, H.; Howell, G.; Herman, J.; Clark, L.; Strand, M.K.; Tarpy, D.; Rueppell, O. Transcriptomic and Epigenomic Dynamics of Honey Bees in Response to Lethal Viral Infection. Front. Genet. 2020, 11, 566320. [Google Scholar] [CrossRef]
- Arsala, D.; Wu, X.; Yi, S.V.; Lynch, J.A. Dnmt1a is essential for gene body methylation and the regulation of zygotic genome activation in the wasp. bioRxiv 2021. [Google Scholar] [CrossRef]
- Hou, L.; Wang, X.; Yang, P.; Li, B.; Lin, Z.; Kang, L.; Wang, X. DNA methyltransferase 3 participates in behavioral phase change in the migratory locust. Insect Biochem. Mol. Biol. 2020, 121, 103374. [Google Scholar] [CrossRef] [PubMed]
- Li-Byarlay, H.; Li, Y.; Stroud, H.; Feng, S.; Newman, T.C.; Kaneda, M.; Hou, K.K.; Worley, K.C.; Elsik, C.G.; Wickline, S.A.; et al. RNA interference knockdown of DNA methyl-transferase 3 affects gene alternative splicing in the honey bee. Proc. Natl. Acad. Sci. USA 2013, 110, 12750–12755. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bewick, A.J.; Sanchez, Z.; McKinney, E.C.; Moore, A.J.; Moore, P.J.; Schmitz, R.J. Dnmt1 is essential for egg production and embryo viability in the large milkweed bug, Oncopeltus fasciatus. Epigenetics Chromatin 2019, 12, 6. [Google Scholar] [CrossRef]
- Flores, K.; Wolschin, F.; Corneveaux, J.J.; Allen, A.N.; Huentelman, M.J.; Amdam, G.V. Genome-wide association between DNA methylation and alternative splicing in an invertebrate. BMC Genom. 2012, 13, 480. [Google Scholar] [CrossRef] [PubMed]
- Glastad, K.M.; Gokhale, K.; Liebig, J.; Goodisman, M.A. The caste- and sex-specific DNA methylome of the termite Zootermopsis nevadensis. Sci. Rep. 2016, 6, 37110. [Google Scholar] [CrossRef] [Green Version]
- Shukla, S.; Kavak, E.; Gregory, M.; Imashimizu, M.; Shutinoski, B.; Kashlev, M.; Oberdoerffer, P.; Sandberg, R.; Oberdoerffer, S. CTCF-promoted RNA polymerase II pausing links DNA methylation to splicing. Nature 2011, 479, 74–79. [Google Scholar] [CrossRef]
- Jones, P.A. Functions of DNA methylation: Islands, start sites, gene bodies and beyond. Nat. Rev. Genet. 2012, 13, 484–492. [Google Scholar] [CrossRef]
- Harris, K.D.; Lloyd, J.P.B.; Domb, K.; Zilberman, D.; Zemach, A. DNA methylation is maintained with high fidelity in the honey bee germline and exhibits global non-functional fluctuations during somatic development. Epigenetics Chromatin 2019, 12, 62. [Google Scholar] [CrossRef]
- Patalano, S.; Vlasova, A.; Wyatt, C.; Ewels, P.; Camara, F.; Ferreira, P.G.; Asher, C.L.; Jurkowski, T.P.; Segonds-Pichon, A.; Bachman, M.; et al. Molecular signatures of plastic phenotypes in two eusocial insect species with simple societies. Proc. Natl. Acad. Sci. USA 2015, 112, 13970–13975. [Google Scholar] [CrossRef] [Green Version]
- Bludau, A.; Royer, M.; Meister, G.; Neumann, I.D.; Menon, R. Epigenetic Regulation of the Social Brain. Trends Neurosci. 2019, 42, 471–484. [Google Scholar] [CrossRef]
- Bird, A.P. Gene number, noise reduction and biological complexity. Trends Genet. 1995, 11, 94–100. [Google Scholar] [CrossRef]
- Huh, I.; Zeng, J.; Park, T.; Yi, S.V. DNA methylation and transcriptional noise. Epigenetics Chromatin 2013, 6, 9. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Neri, F.; Rapelli, S.; Krepelova, A.; Incarnato, D.; Parlato, C.; Basile, G.; Maldotti, M.; Anselmi, F.; Oliviero, S. Intragenic DNA methylation prevents spurious transcription initiation. Nature 2017, 543, 72–77. [Google Scholar] [CrossRef] [PubMed]
- Xu, G.; Lyu, H.; Yi, Y.; Peng, Y.; Feng, Q.; Song, Q.; Gong, C.; Peng, X.; Palli, S.R.; Zheng, S. Intragenic DNA methylation regulates insect gene expression and reproduction through the MBD/Tip60 complex. iScience 2021, 24, 102040. [Google Scholar] [CrossRef]
- Kumar, S.; Kim, Y. An endoparasitoid wasp influences host DNA methylation. Sci. Rep. 2017, 7, 43287. [Google Scholar] [CrossRef] [PubMed]
- Pegoraro, M.; Bafna, A.; Davies, N.J.; Shuker, D.M.; Tauber, E. DNA methylation changes induced by long and short photoperiods in Nasonia. Genome Res. 2016, 26, 203–210. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kucharski, R.; Maleszka, J.; Foret, S.; Maleszka, R. Nutritional control of reproductive status in honeybees via DNA methylation. Science 2008, 319, 1827–1830. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, H.; Liu, Z.; Wang, Y.; Ma, L.; Zhang, W.; Xu, B. Genome-Wide Differential DNA Methylation in Reproductive, Morphological, and Visual System Differences Between Queen Bee and Worker Bee (Apis mellifera). Front. Genet. 2020, 11, 770. [Google Scholar] [CrossRef]
- Shi, Y.-Y.; Liu, H.; Qiu, Y.-F.; Ma, Z.-Y.; Zeng, Z.-J. DNA methylation comparison between 4-day-old queen and worker larvae of honey bee. J. Asia-Pac. Entomol. 2017, 20, 299–303. [Google Scholar] [CrossRef]
- Foret, S.; Kucharski, R.; Pellegrini, M.; Feng, S.; Jacobsen, S.E.; Robinson, G.E.; Maleszka, R. DNA methylation dynamics, metabolic fluxes, gene splicing, and alternative phenotypes in honey bees. Proc. Natl. Acad. Sci. USA 2012, 109, 4968. [Google Scholar] [CrossRef] [Green Version]
- Hartfelder, K.; Engels, W. 2 Social Insect Polymorphism: Hormonal Regulation of Plasticity in Development and Reproduction in the Honeybee. In Current Topics in Developmental Biology; Pedersen, R.A., Schatten, G.P., Eds.; Academic Press: Cambridge, MA, USA, 1998; Volume 40, pp. 45–77. [Google Scholar]
- Cameron, R.C.; Duncan, E.J.; Dearden, P.K. Biased gene expression in early honeybee larval development. BMC Genom. 2013, 14, 903. [Google Scholar] [CrossRef] [Green Version]
- Weaver, N. Effects of Larval Age on Dimorphic Differentiation of the Female Honey Bee. Ann. Entomol. Soc. Am. 1957, 50, 283–294. [Google Scholar] [CrossRef]
- Schulz, N.K.E.; Wagner, C.I.; Ebeling, J.; Raddatz, G.; Diddens-de Buhr, M.F.; Lyko, F.; Kurtz, J. Dnmt1 has an essential function despite the absence of CpG DNA methylation in the red flour beetle Tribolium castaneum. Sci. Rep. 2018, 8, 16462. [Google Scholar] [CrossRef]
- Washington, J.T.; Cavender, K.R.; Amukamara, A.U.; McKinney, E.C.; Schmitz, R.J.; Moore, P.J. The essential role of Dnmt1 in gametogenesis in the large milkweed bug Oncopeltus fasciatus. Elife 2021, 10, e62202. [Google Scholar] [CrossRef]
- Rodrigues, M.A.; Flatt, T. Endocrine uncoupling of the trade-off between reproduction and somatic maintenance in eusocial insects. Curr. Opin. Insect Sci. 2016, 16, 1–8. [Google Scholar] [CrossRef] [Green Version]
- Duncan, E.J.; Hyink, O.; Dearden, P.K. Notch signalling mediates reproductive constraint in the adult worker honeybee. Nat. Commun. 2016, 7, 12427. [Google Scholar] [CrossRef] [Green Version]
- Amarasinghe, H.E.; Clayton, C.I.; Mallon, E.B. Methylation and worker reproduction in the bumble-bee (Bombus terrestris). Proc. Biol. Sci. 2014, 281, 20132502. [Google Scholar] [CrossRef] [Green Version]
- Richard, G.; Jaquiéry, J.; Le Trionnaire, G. Contribution of Epigenetic Mechanisms in the Regulation of Environmentally-Induced Polyphenism in Insects. Insects 2021, 12, 649. [Google Scholar] [CrossRef]
- Robinson, K.L.; Tohidi-Esfahani, D.; Ponton, F.; Simpson, S.J.; Sword, G.A.; Lo, N. Alternative migratory locust phenotypes are associated with differences in the expression of genes encoding the methylation machinery. Insect Mol. Biol. 2016, 25, 105–115. [Google Scholar] [CrossRef]
- Snell-Rood, E.C.; Troth, A.; Moczek, A.P. DNA methylation as a mechanism of nutritional plasticity: Limited support from horned beetles. J. Exp. Zool. B Mol. Dev. Evol. 2013, 320, 22–34. [Google Scholar] [CrossRef] [Green Version]
- Falckenhayn, C.; Boerjan, B.; Raddatz, G.; Frohme, M.; Schoofs, L.; Lyko, F. Characterization of genome methylation patterns in the desert locust Schistocerca gregaria. J. Exp. Biol. 2013, 216, 1423–1429. [Google Scholar] [CrossRef] [Green Version]
- Standage, D.S.; Berens, A.J.; Glastad, K.M.; Severin, A.J.; Brendel, V.P.; Toth, A.L. Genome, transcriptome and methylome sequencing of a primitively eusocial wasp reveal a greatly reduced DNA methylation system in a social insect. Mol. Ecol. 2016, 25, 1769–1784. [Google Scholar] [CrossRef]
- Misof, B.; Liu, S.; Meusemann, K.; Peters, R.S.; Donath, A.; Mayer, C.; Frandsen, P.B.; Ware, J.; Flouri, T.; Beutel, R.G.; et al. Phylogenomics resolves the timing and pattern of insect evolution. Science 2014, 346, 763–767. [Google Scholar] [CrossRef]
- Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol. 1990, 215, 403–410. [Google Scholar] [CrossRef]
- Montgomery, S.H.; Mank, J.E. Inferring regulatory change from gene expression: The confounding effects of tissue scaling. Mol. Ecol. 2016, 25, 5114–5128. [Google Scholar] [CrossRef] [Green Version]
- Duffy, J.B. GAL4 system in Drosophila: A fly geneticist’s Swiss army knife. Genesis 2002, 34, 1–15. [Google Scholar] [CrossRef]
- Scialo, F.; Sriram, A.; Stefanatos, R.; Sanz, A. Practical Recommendations for the Use of the GeneSwitch Gal4 System to Knock-Down Genes in Drosophila melanogaster. PLoS ONE 2016, 11, e0161817. [Google Scholar] [CrossRef]
- Singh, I.K.; Singh, S.; Mogilicherla, K.; Shukla, J.N.; Palli, S.R. Comparative analysis of double-stranded RNA degradation and processing in insects. Sci. Rep. 2017, 7, 17059. [Google Scholar] [CrossRef] [Green Version]
- Vogel, E.; Santos, D.; Mingels, L.; Verdonckt, T.W.; Broeck, J.V. RNA Interference in Insects: Protecting Beneficials and Controlling Pests. Front. Physiol. 2018, 9, 1912. [Google Scholar] [CrossRef] [Green Version]
- Cook, N.; Parker, D.J.; Tauber, E.; Pannebakker, B.A.; Shuker, D.M. Validating the Demethylating Effects of 5-aza-2′-deoxycytidine in Insects Requires a Whole-Genome Approach. Am. Nat. 2019, 194, 432–438. [Google Scholar] [CrossRef] [Green Version]
- Nunez, J.K.; Chen, J.; Pommier, G.C.; Cogan, J.Z.; Replogle, J.M.; Adriaens, C.; Ramadoss, G.N.; Shi, Q.; Hung, K.L.; Samelson, A.J.; et al. Genome-wide programmable transcriptional memory by CRISPR-based epigenome editing. Cell 2021, 184, 2503–2519. [Google Scholar] [CrossRef]
- Frommer, M.; McDonald, L.E.; Millar, D.S.; Collis, C.M.; Watt, F.; Grigg, G.W.; Molloy, P.L.; Paul, C.L. A genomic sequencing protocol that yields a positive display of 5-methylcytosine residues in individual DNA strands. Proc. Natl. Acad. Sci. USA 1992, 89, 1827–1831. [Google Scholar] [CrossRef] [Green Version]
- Ni, P.; Huang, N.; Zhang, Z.; Wang, D.P.; Liang, F.; Miao, Y.; Xiao, C.L.; Luo, F.; Wang, J. DeepSignal: Detecting DNA methylation state from Nanopore sequencing reads using deep-learning. Bioinformatics 2019, 35, 4586–4595. [Google Scholar] [CrossRef]
- Morandin, C.; Brendel, V.P. Tools and applications for integrative analysis of DNA methylation in social insects. Mol. Ecol. Resour. online ahead of print. 2021. [Google Scholar] [CrossRef]
- Rahmani, E.; Schweiger, R.; Rhead, B.; Criswell, L.A.; Barcellos, L.F.; Eskin, E.; Rosset, S.; Sankararaman, S.; Halperin, E. Cell-type-specific resolution epigenetics without the need for cell sorting or single-cell biology. Nat. Commun. 2019, 10, 3417. [Google Scholar] [CrossRef] [Green Version]
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Duncan, E.J.; Cunningham, C.B.; Dearden, P.K. Phenotypic Plasticity: What Has DNA Methylation Got to Do with It? Insects 2022, 13, 110. https://doi.org/10.3390/insects13020110
Duncan EJ, Cunningham CB, Dearden PK. Phenotypic Plasticity: What Has DNA Methylation Got to Do with It? Insects. 2022; 13(2):110. https://doi.org/10.3390/insects13020110
Chicago/Turabian StyleDuncan, Elizabeth J., Christopher B. Cunningham, and Peter K. Dearden. 2022. "Phenotypic Plasticity: What Has DNA Methylation Got to Do with It?" Insects 13, no. 2: 110. https://doi.org/10.3390/insects13020110
APA StyleDuncan, E. J., Cunningham, C. B., & Dearden, P. K. (2022). Phenotypic Plasticity: What Has DNA Methylation Got to Do with It? Insects, 13(2), 110. https://doi.org/10.3390/insects13020110