Accurate information flow is central to living systems. The continuity of genomes through generations as well as the reproducible functioning and survival of the individual organisms require a faithful information transfer during replication, transcription and translation. The differential efficiency of natural selection against “mistakes” results in decreasing fidelity rates for replication, transcription and translation. At each level in the information flow chain (replication, transcription, translation), numerous complex molecular systems have evolved and been selected for preventing, identifying and, when possible, correcting or removing such “mistakes” arising during information transfer.

However, fidelity cannot be improved ad infinitum. First, because of the limits imposed by the physical nature of the processes of copying and recoding information over different molecular supports: all mechanisms ensuring fidelity during biological information transfer ultimately rely on chemical kinetics and thermodynamics. The more accurate a copying process is, the lower the synthesis rate and the higher the energetic cost of correcting errors. Second, because of the limits imposed by random genetic drift: natural selection cannot effectively act on an allele that contributes with a small differential advantage unless effective population size is large. If s <1/Ne (or s <1/(2Ne) in diploids) the allele frequency in the population is de facto subject to neutral drift processes.

In their preprint “Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans”, Bénitière, Necsulea and Duret explore the validity of this last mentioned “drift barrier” hypothesis for the case study of alternative splicing diversity in eukaryotes (Bénitière et al. 2022). Splicing refers to an ensemble of eukaryotic molecular processes mediated by a large number of proteins and ribonucleoproteins and involving nucleotide sequence recognition, that uses as a molecular substrate a precursor messenger RNA (mRNA), directly transcribed from the DNA, and produces a mature mRNA by removing introns and joining exons (Chow et al. 1977). Alternative splicing refers to the case in which different molecular species of mature mRNAs can be produced, either by cis-splicing processes acting on the same precursor mRNA, e.g. by varying the presence/absence of different exons or by varying the exon-exon boundaries, or by trans-splicing processes, joining exons from different precursor mRNA molecules.

The diversity of mRNA molecular species generated by alternative splicing enlarges the molecular phenotypic space that can be generated from the same genotype. In humans, alternative splicing occurs in around 95% of the ca. 20,000 genes, resulting in ca. 100,000 medium-to-high abundance transcripts (Pan et al. 2008). In multicellular organisms, the frequency of alternatively spliced mRNAs varies between tissues and across ontogeny, often in a switch-like pattern (Wang et al. 2008). In the molecular and cell biology community, it is commonly accepted that splice variants contribute with specific functions (Marasco and Kornblihtt 2023) although there exists a discussion around the functional nature of low-frequency splice variants (see for instance the debate between Tress et al. 2017 and Blencowe 2017). The origin, diversity, regulation and evolutionary advantage of alternative splicing constitutes thus a playground of the selectionist-neutralist debate, with one extreme considering that most splice variants are mere “mistakes” of the splicing process (Pickrell et al. 2010), and the other extreme considering that alternative splicing is at the core of complexity in multicellular organisms, as it increases the genome coding potential and allows for a large repertoire of cell types (Chen et al. 2014).

In their manuscript, Bénitière, Necsulea and Duret set the cursor towards the neutralist end of the gradient and test the hypothesis of whether the high alternative splice rate in “complex” organisms corresponds to a high rate of splicing “mistakes”, arising from the limit imposed by the drift barrier effect on the power of natural selection to increase accuracy (Bush et al. 2017). In their preprint, the authors convincingly show that in metazoans a fraction of the variation of alternative splicing rate is explained by variation in proxies of population size, so that species with smaller Ne display higher alternative splice rates. They communicate further that abundant splice variants tend to preserve the reading frame more often than low-frequency splice variants, and that the nucleotide splice signals in abundant splice variants display stronger evidence of purifying selection than those in low-frequency splice variants. From all the evidence presented in the manuscript, the authors interpret that “variation in alternative splicing rate is entirely driven by variation in the efficacy of selection against splicing errors”.

The authors honestly present some of the limitations of the data used for the analyses, regarding i) the quality of the proxies used for Ne (i.e. body length, longevity and dN/dS ratio); ii) the heterogeneous nature of the RNA sequencing datasets (full organisms, organs or tissues; different life stages, sexes or conditions); and iii) mostly short RNA reads that do not fully span individual introns. Further, data from bacteria do not verify the herein communicated trends, as it has been shown that bacterial species with low population sizes do not display higher transcription error rates (Traverse and Ochman 2016). Finally, it will be extremely interesting to introduce a larger evolutionary perspective on alternative splicing rates encompassing unicellular eukaryotes, in which an intriguing interplay between alternative splicing and gene duplication has been communicated (Hurtig et al. 2020).

The manuscript from Bénitière, Necsulea and Duret makes a significant advance to our understanding of the diversity, the origin and the physiology of post-transcriptional and post-translational mechanisms by emphasising the fundamental role of non-adaptive evolutionary processes and the upper limits to splicing accuracy set by genetic drift.

References

Bénitière F, Necsulea A, Duret L. 2023. Random genetic drift sets an upper limit on mRNA splicing accuracy in metazoans. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.12.09.519597 

Blencowe BJ. 2017. The Relationship between Alternative Splicing and Proteomic Complexity. Trends Biochem Sci 42:407–408. https://doi.org/10.1016/j.tibs.2017.04.001

Bush SJ, Chen L, Tovar-Corona JM, Urrutia AO. 2017. Alternative splicing and the evolution of phenotypic novelty. Philos Trans R Soc Lond B Biol Sci 372:20150474. https://doi.org/10.1098/rstb.2015.0474

Chen L, Bush SJ, Tovar-Corona JM, Castillo-Morales A, Urrutia AO. 2014. Correcting for differential transcript coverage reveals a strong relationship between alternative splicing and organism complexity. Mol Biol Evol 31:1402–1413. https://doi.org/10.1093/molbev/msu083

Chow LT, Gelinas RE, Broker TR, Roberts RJ. 1977. An amazing sequence arrangement at the 5’ ends of adenovirus 2 messenger RNA. Cell 12:1–8. https://doi.org/10.1016/0092-8674(77)90180-5

Hurtig JE, Kim M, Orlando-Coronel LJ, Ewan J, Foreman M, Notice L-A, Steiger MA, van Hoof A. 2020. Origin, conservation, and loss of alternative splicing events that diversify the proteome in Saccharomycotina budding yeasts. RNA 26:1464–1480. https://doi.org/10.1261/rna.075655.120

Marasco LE, Kornblihtt AR. 2023. The physiology of alternative splicing. Nat Rev Mol Cell Biol 24:242–254. https://doi.org/10.1038/s41580-022-00545-z

Pan Q, Shai O, Lee LJ, Frey BJ, Blencowe BJ. 2008. Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing. Nat Genet 40:1413–1415. https://doi.org/10.1038/ng.259

Pickrell JK, Pai AA, Gilad Y, Pritchard JK. 2010. Noisy splicing drives mRNA isoform diversity in human cells. PLoS Genet 6:e1001236. https://doi.org/10.1371/journal.pgen.1001236

Traverse CC, Ochman H. 2016. Conserved rates and patterns of transcription errors across bacterial growth states and lifestyles. Proc Natl Acad Sci U S A 113:3311–3316. https://doi.org/10.1073/pnas.1525329113

Tress ML, Abascal F, Valencia A. 2017. Alternative Splicing May Not Be the Key to Proteome Complexity. Trends Biochem Sci 42:98–110. https://doi.org/10.1016/j.tibs.2016.08.008

Wang ET, Sandberg R, Luo S, Khrebtukova I, Zhang L, Mayr C, Kingsmore SF, Schroth GP, Burge CB. 2008. Alternative isoform regulation in human tissue transcriptomes. Nature 456:470–476. https://doi.org/10.1038/nature07509

Polyploidy, which results in the presence of more than two sets of homologous chromosomes represents a major feature of plant genomes that have undergone successive rounds of duplication followed by more or less rapid diploidization during their evolutionary history. Polyploid complexes containing diploid and derived polyploid taxa are excellent model systems for understanding the short-term consequences of whole genome duplication, and have been particularly well-explored in evolutionary ecology (Ramsey and Ramsey 2014, Rice et al. 2019). Many polyploids (especially when resulting from interspecific hybridization, i.e. allopolyploids) are successful invaders (te Beest et al. 2012) as a result of rapid genome dynamics, functional novelty, and trait evolution. The origin (parental legacy) and modes of formation of polyploids have a critical impact on the subsequent polyploid evolution. Thus, elucidation of the genomic composition of polyploids is fundamental to understanding trait evolution, and such knowledge is still lacking for many invasive species.

Genus Ludwigia is characterized by a complex taxonomy, with an underexplored evolutionary history. Species from section Jussieae form a polyploid complex with diploids, tetraploids, hexaploids, and decaploids that are notorious invaders in freshwater and riparian ecosystems (Thouvenot et al.2013).   Molecular phylogeny of the genus based on nuclear and chloroplast sequences (Liu et al. 2027) suggested some relationships between diploid and polyploid species, without fully resolving the question of the parentage of the polyploids. In their study, Barloy et al. (2023) have used a combination of molecular cytogenetics (Genomic In situ Hybridization), morphology and experimental crosses to elucidate the genomic compositions of the polyploid species, and show that the examined polyploids are of hybrid origin (allopolyploids). The tetraploid L. stolonifera derives from the diploids L. peploides subsp. montevidensis (AA genome) and L. helminthorhiza (BB genome). The tetraploid L. ascendens also share the BB genome combined with an undetermined different genome. The hexaploid L. grandiflora subsp. grandiflora has inherited the diploid AA genome combined with additional unidentified genomes. The decaploid L. grandiflora subsp. hexapetala has inherited the tetraploid L. stolonifera and the hexaploid L. grandiflora subsp. hexapetala genomes. As the authors point out, further work is needed, including additional related diploid (e.g. other subspecies of L. peploides) or tetraploid (L.  hookeri and L. peduncularis)  taxa that remain to be investigated, to address the nature of the undetermined parental genomes mentioned above. 

The presented work (Barloy et al.  2023) provides significant knowledge of this poorly investigated group with regard to genomic information and polyploid origin, and opens perspectives for future studies. The authors also detect additional diagnostic morphological traits of interest for in-situ discrimination of the taxa when monitoring invasive populations.  

References

Barloy D., Portillo-Lemus L., Krueger-Hadfield S.A., Huteau V., Coriton O. (2024). Genomic relationships among diploid and polyploid species of the genus Ludwigia L. section Jussiaea using a combination of molecular cytogenetic, morphological, and crossing investigations. BioRxiv, ver. 4 peer-reviewed and recommended  by Peer Community in Evolutionary Biology https://doi.org/10.1101/2023.01.02.522458

te Beest M., Le Roux J.J., Richardson D.M., Brysting A.K., Suda J., Kubešová M., Pyšek P. (2012). The more the better? The role of polyploidy in facilitating plant invasions. Annals of Botany, Volume 109, Issue 1 Pages 19–45, https://doi.org/10.1093/aob/mcr277

Ramsey J. and Ramsey T. S. (2014). Ecological studies of polyploidy in the 100 years following its discovery Phil. Trans. R. Soc. B369 1–20  https://doi.org/10.1098/rstb.2013.0352  

Rice, A., Šmarda, P., Novosolov, M. et al. (2019). The global biogeography of polyploid plants. Nat Ecol Evol 3, 265–273. https://doi.org/10.1038/s41559-018-0787-9

Thouvenot L, Haury J, Thiebaut G. (2013). A success story: Water primroses, aquatic plant pests. Aquat. Conserv. Mar. Freshw. Ecosyst. 23:790–803  https://doi.org/10.1002/aqc.2387  

Growth, development and reproduction in animals are all limited by dietary nutrients. Expansion of an organism’s diet to sources not accessible to closely related species reduces food competition, and eases the constraints of nutrient-limited diets. Adult butterflies are herbivorous insects known to feed primarily on nectar from flowers, which is rich in sugars but poor in amino acids.  Only certain species in the genus Heliconius are known to also feed on pollen, which is especially rich in amino acids, and is known to prolong their lives by several months. The ability to digest pollen in Heliconius has been linked to specialized feeding behaviors (Krenn et al. 2009) and extra-oral digestion using enzymes, possibly including duplicated copies of cocoonase (Harpel et al. 2016; Smith et al. 2016 and 2018), a protease used by some moths to digest silk upon eclosion from their cocoons. In this reprint, Pinheiro de Castro and colleagues investigated the impact of artificial and natural diets on egg-laying ability, body weight, and cyanogenic glucoside abundance in adult Heliconius erato butterflies of both sexes. 

Previous studies (Dunlap-Pianka et al. 1981) in H. charithonia demonstrated that access to dietary pollen led to extended egg-laying ability among adult female butterflies compared to females deprived of pollen, and compared to Dryas iulia females which feed only on nectar. In the current study, Pinheiro de Castro et al. (2023) examine the impact of diet on both young and old H. erato, over a longer period of time than the earlier work, highlighting the importance of extending the time period over which effects are evaluated. In addition to extending egg-laying ability in older females, the authors found that pollen in the diet appeared to maintain older female body weight, presumably because the pollen contained nutrients depleted during egg-laying.

The authors then investigated the effects of nutrition on the production of cyanogenic glycoside defenses. Heliconius are aposematic butterflies that sequester cyanide-forming defense chemicals from food plants as larvae or synthesize these compounds de novo. The authors found the abundance of cyanogenic glycosides to be significantly greater in butterflies with access to pollen, but again only in older females.

Curiously, field studies of male and female H. charithonia butterflies found that females in the wild collected more pollen than males (Mendoza-Cuenca and Macías-Ordóñez 2005). Taken together, these new findings raise the intriguing possibility that females collect more pollen than males, in part, because pollen has a bigger impact on female survival and reproduction. A small limitation of the study is the use of wing length, rather than body weight, at the zero time point. But the trend is clear in both males and females, and it adds supporting detail to the efficacy of pollen feeding as an unusual strategy for increasing fertility and survival in Heliconius butterflies.

References
 
Dunlap-Pianka, Helen, Carol L. Boggs, Lawrence E. Gilbert. (1977) Ovarian dynamics in heliconiine butterflies: Programmed senescence versus eternal youth. Science, 197: 487-490, https://doi.org/10.1126/Science.197.4302.487
 
Pinheiro de Castro, Erika C., Josie McPherson, Glennis Julian, Anniina L. K. Mattila, Søren Bak, Stephen H. Montgomery, Chris Jiggins. (2023) Pollen-feeding delays reproductive senescence and maintains toxicity of Heliconius erato. bioRxiv, 2023.01.13.523799, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2023.01.13.523799
 
Krenn, Harald W., Monika J. B. Eberhard, Stefan H. Eberhard, Anna-Laetitia Hikl, Werner Huber, Lawrence E. Gilbert (2009). Mechanical damage to pollen aids nutrient acquisition in Heliconius butterflies (Nymphalidae).  Arthropod-Plant Interactions, 3: 203–208. https://doi.org/10.1007/s11829-009-9074-7
 
Harpel, Desiree, Darron A. Cullen, Swidbert R. Ott, Chris D. Jiggins, James R. Walters (2015) Pollen feeding proteomics: Salivary proteins of the passion flower butterfly, Heliconius melpomene. Insect Biochemistry and Molecular Biology, 63: 7-13, https://doi.org/10.1016/j.ibmb.2015.04.004
 
Mendoza-Cuenca, Luis, Rogelio Macías-Ordóñez (2005) Foraging polymorphism in Heliconius charitonia (Lepidoptera: Nymphalidae): morphological constraints and behavioral compensation. Journal of Tropical Ecology, 21: 407-415. https://doi.org/10.1017/S0266467405002385
 
Smith, Gilbert, Aide Macias-Muñoz, John Kelly, Carter Butts, Rachel Martin, Adriana D. Briscoe (2018) Evolutionary and structural analyses uncover a role for solvent interactions in the diversification of cocoonases in butterflies. Proceedings of the Royal Society B, 285: 20172037. https://doi.org/10.1098/rspb.2017.2037 
 
Smith, Gilbert, Aide Macias-Muñoz, Adriana D. Briscoe (2016) Gene duplication and gene expression changes play a role in the evolution of candidate pollen-feeding genes in Heliconius butterflies. Genome Biology and Evolution, 8: 2581-2596. https://doi.org/10.1093/gbe/evw180

​Of the four evolutionary forces, three can be straightforwardly summarized both conceptually and mathematically in the context of an allele at a genomic locus.  Mutation (the mutation rate, μ) is simply captured by the per-site, per-generation probability that an allele mutates into a different allele. Recombination (the recombination rate, r) is captured as the probability of recombination between two sites, wherein alleles that are in different genomes in one generation come together in the same genome in the next generation.  Natural selection (the selection coefficient, s) is captured by the probability that an allele is present in the next generation, relative to some reference.  

Random genetic drift – the random fluctuation in allele frequency due to sampling in a finite population - is not so straightforwardly summarized.  The first, and most common way of characterizing evolutionary dynamics in a finite population is the Wright-Fisher model, in which the only deviation from the assumptions of Hardy-Weinberg conditions is finite population size.  Importantly, in a W-F population, mating between diploid individuals is random, which implies self-fertile monoecy, and generations are non-overlapping.  In an ideal W-F population, the probability that a gene copy leaves i descendants in the next generation is the result of binomial sampling of uniting gametes (if the locus is biallelic).  The – and the next word is meaningful – magnitude/strength/rate/power/amount of genetic drift is proportional to 1/2N, where N is the size of the population.  All of the following are affected by genetic drift: (1) the probability that a neutral allele ultimately reaches fixation, (2) the rate of loss of genetic variation within a population, (3) the rate of increase of genetic variance among populations, (4) the amount of genetic variation segregating in a population, (5) the probability of fixation/loss of a weakly selected variant.    

Presumably no real population adheres to ideal W-F conditions, which leads to the notion of "effective population size", Ne (Wright 1931), loosely defined as "the size of an ideal W-F population that experiences an equivalent strength of genetic drift".  Almost always, Ne<N, and any violation of W-F assumptions can affect Ne.  Importantly, Ne can be defined in different ways, and the specific formulation of Ne can have different implications for evolution.  Ne was initially defined in terms of the rate of decrease of heterozygosity (inbreeding effective size) and increase in variance among populations (variance effective size).  Ewens (1979) defined the Eigenvalue effective size (equivalent to the "random extinction" effective size) and elaborated on the conditions under which the various formulations of Ne differ (Ewens 1982).  Nordborg and Krone (2002) defined the effective size in terms of the coalescent, and they identified conditions in which genetic drift cannot be described in terms of a W-F model (Sjodin et al. 2005); also see Karasov et al. (2010); Neher and Shraiman (2011).

Distinct from the issue of defining Ne is the issue of calculating Ne from data, which is the focus of this paper by De Meeus and Noûs (2023).  Pudovkin et al. (1996) showed that the Eigenvalue effective size in a dioecious population can be formulated in terms of excess heterozygosity, which the current authors note is equivalent to formulating Ne in terms of Wright's FIS statistic.  As emphasized by the title, the marquee contribution of this paper is to provide a better approximation of the Eigenvalue effective size in a dioecious population.  Science marches onward, although the empirical utility of this advance is obviously limited, given the tremendous inherent sources of uncertainty in real-world estimates of Ne.  Perhaps more valuable, however, is the extensive set of appendixes, in which detailed derivations are provided for the various formulations of effective size.  By way of analogy, the material presented here can be thought of as an extension of the material presented in section 7.6 of Crow and Kimura (1970), in which the Inbreeding and Variance effective population sizes are derived and compared.  The appendixes should serve as a handy go-to source of detailed theoretical information with respect to the different formulations of effective population size.

REFERENCES

Crow, J. F. and M. Kimura. 1970. An Introduction to Population Genetics Theory. The Blackburn Press, Caldwell, NJ.

De Meeûs, T. and Noûs, C. 2023. A new and almost perfectly accurate approximation of the eigenvalue effective population size of a dioecious population: comparisons with other estimates and detailed proofs. Zenodo, ver. 6 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.5281/zenodo.7927968

Ewens, W. J. 1979. Mathematical Population Genetics. Springer-Verlag, Berlin.

Ewens, W. J. 1982. On the concept of the effective population size. Theoretical Population Biology 21:373-378. https://doi.org/10.1016/0040-5809(82)90024-7

Karasov, T., P. W. Messer, and D. A. Petrov. 2010. Evidence that adaptation in Drosophila Is not limited by mutation at single sites. Plos Genetics 6. https://doi.org/10.1371/journal.pgen.1000924

Neher, R. A. and B. I. Shraiman. 2011. Genetic Draft and Quasi-Neutrality in Large Facultatively Sexual Populations. Genetics 188:975-U370. https://doi.org/10.1534/genetics.111.128876

Nordborg, M. and S. M. Krone. 2002. Separation of time scales and convergence to the coalescent in structured populations. Pp. 194–232 in M. Slatkin, and M. Veuille, eds. Modern Developments in Theoretical Population Genetics: The Legacy of Gustave Malécot. Oxford University Press, Oxford. https://www.webpages.uidaho.edu/~krone/malecot.pdf

Pudovkin, A. I., D. V. Zaykin, and D. Hedgecock. 1996. On the potential for estimating the effective number of breeders from heterozygote-excess in progeny. Genetics 144:383-387. https://doi.org/10.1093/genetics/144.1.383

Sjodin, P., I. Kaj, S. Krone, M. Lascoux, and M. Nordborg. 2005. On the meaning and existence of an effective population size. Genetics 169:1061-1070. https://doi.org/10.1534/genetics.104.026799

Wright, S. 1931. Evolution in Mendelian populations. Genetics 16:0097-0159. https://doi.org/10.1093/genetics/16.2.97

The search for physiological markers of health and survival in wild animal populations is attracting a great deal of interest. At present, there is no (and may never be) consensus on such a single, robust marker but of all the proposed physiological markers, telomere length is undoubtedly the most widely studied in the field of evolutionary ecology (Monaghan et al., 2022). 

Broadly speaking, telomeres are non-coding DNA sequences located at the end of chromosomes in eukaryotes, protecting genomic DNA against oxidative stress and various detrimental processes (e.g. DNA end-joining) and thus maintaining genome stability (Blackburn et al., 2015). However, in most somatic cells from the vast majority of the species, telomere sequences are not replicated and telomere length progressively declines with increased age (Remot et al., 2022). This shortening of telomere length upon a critical level is causally linked to cellular senescence and has been invoked as one of the primary causes of the aging process (López-Otín et al., 2023). Studies performed in both captive and wild populations of animals have further demonstrated that short telomeres (or telomere sequences with a fast attrition rate) are to some extent associated with an increased risk of mortality, even if the magnitude of this association largely differs between species and populations (Wilbourn et al., 2018).

The repeated observations of associations between telomere length and mortality risk have called for studies seeking to identify the ecological and biological factors that – beyond chronological age – shape the between-individual variability in telomere length. A wide spectrum of environmental stressors such as the level of exposure to pathogens or the degree of human disturbances has been proposed as possible modulators of telomere dynamics (see Chatelain et al., 2019). However, within species, the relative contribution of various ecological and biological factors on telomere length has been rarely quantified. In that context, the study of Criscuolo and colleagues (2023) constitutes a timely attempt to decipher the relative contribution of environmental and biological factors driving telomere length in nestlings (i.e. when individuals are between 15 and 35 days of age) from a wild population of little owls, Athene noctua.

In addition to chronological age, Criscuolo and colleagues (2023) analysed the effects of two environmental variables (i.e. cohort and habitat quality) as well as three life history traits (i.e. hatching rank, sex and body condition). Among these traits, sex was found to impact nestling’s telomere length with females carrying longer telomeres than males. Traditionally, the among-individuals variability in telomere length during the juvenile period is interpreted as a direct consequence of differences in growth allocation. Fast-growing individuals are typically supposed to undergo more cell divisions and a higher exposure to oxidative stress, which ultimately shortens telomeres (Monaghan & Ozanne, 2018). Whether - despite a slightly female-biased sexual size dimorphism - male little owls display a condensed period of fast growth that could explain their shorter telomere is yet to be determined. Future studies should also explore the consequences of these sex differences in telomere length in terms of mortality risk. In birds, it has been observed that telomere length during early life can predict lifespan (see Heidinger et al., 2012 in zebra finches, Taeniopygia guttata), suggesting that females little owls might live longer than their conspecific males. Yet, adult mortality is generally female-biased in birds (Liker & Székely, 2005) and whether little owls constitute an exception to this rule - possibly mediated by sex-specific telomere dynamics - remains to be explored.   

Quite surprisingly, the present study in little owls did not evidence any clear effect of environmental conditions on nestling’s telomere length, at both temporal and special scales. While a trend for a temporal effect was detected with telomere length being slightly shorter for nestling born the last year of the study (out of 4 years analysed), habitat quality (measured by the proportion of meadow and orchards in the nest environment) had absolutely no impact on nestling telomere length. Recently published studies in wild populations of vertebrates have highlighted the detrimental effects of harsh environmental conditions on telomere length (e.g. Dupoué et al., 2022 in common lizards, Zootoca vivipara), arguing for a key role of telomere dynamics in the emerging field of conservation physiology. While we can recognize the relevance of such an integrative approach, especially in the current context of climate change, the study by Criscuolo and colleagues (2023) reminds us that the relationships between environmental conditions and telomere dynamics are far from straightforward. Depending on the species and its life history, telomere length in early life could indeed capture very different environmental signals.

References

Blackburn, E. H., Epel, E. S., & Lin, J. (2015). Human telomere biology: A contributory and interactive factor in aging, disease risks, and protection. Science, 350(6265), 1193-1198. https://doi.org/10.1126/science.aab3389
 
Chatelain, M., Drobniak, S. M., & Szulkin, M. (2019). The association between stressors and telomeres in non-human vertebrates: A meta-analysis. Ecology Letters, 23, 381-398. https://doi.org/10.1111/ele.13426
 
Criscuolo, F., Fache, I., Scaar, B., Zahn, S. & Bleu, J. (2023). Telomere length vary with sex, hatching rank and year of birth in little owls, Athene noctua. EcoEvoRxiv, ver.4, peer-reviewed and recommended by PCI Evol Biol. https://doi.org/10.32942/X2BS3S
 
Dupoué, A., Blaimont, P., Angelier, F., Ribout, C., Rozen-Rechels, D., Richard, M., & Le Galliard, J. F. (2022). Lizards from warm and declining populations are born with extremely short telomeres. Proceedings of the National Academy of Sciences, 119(33), 2201371119. https://doi.org/10.1073/pnas.2201371119
 
Heidinger, B. J., Blount, J. D., Boner, W., Griffiths, K., Metcalfe, N. B., & Monaghan, P. (2012). Telomere length in early life predicts lifespan. Proceedings of the National Academy of Sciences, 109(5), 1743-1748. https://doi.org/10.1073/pnas.1113306109
 
Liker, A., & Székely, T. (2005). Mortality costs of sexual selection and parental care in natural populations of birds. Evolution, 59(4), 890-897. https://doi.org/10.1111/j.0014-3820.2005.tb01762.x
 
López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., & Kroemer, G. (2023). Hallmarks of aging: An expanding universe. Cell, 186(2), 243-278. https://doi.org/10.1016/j.cell.2022.11.001
 
Monaghan, P., Olsson, M., Richardson, D. S., Verhulst, S., & Rogers, S. M. (2022). Integrating telomere biology into the ecology and evolution of natural populations: Progress and prospects. Molecular Ecology, 31(23), 5909-5916. https://doi.org/10.1111/mec.16768
 
Monaghan, P., & Ozanne, S. E. (2018). Somatic growth and telomere dynamics in vertebrates: Relationships, mechanisms and consequences. Phil. Trans. R. Soc. B, 373(1741), 20160446. https://doi.org/10.1098/rstb.2016.0446
 
Remot, F., Ronget, V., Froy, H., Rey, B., Gaillard, J., Nussey, D. H., & Lemaitre, J. (2022). Decline in telomere length with increasing age across nonhuman vertebrates: A meta‐analysis. Molecular Ecology, 31(23), 5917-5932. https://doi.org/10.1111/mec.16145
 
Wilbourn, R. V., Moatt, J. P., Froy, H., Walling, C. A., Nussey, D. H., & Boonekamp, J. J. (2018). The relationship between telomere length and mortality risk in non-model vertebrate systems: A meta-analysis. Phil. Trans. R. Soc. B, 373(1741), 20160447. https://doi.org/10.1098/rstb.2016.0447