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Article

Sexual Selection and Proteinaceous Diversity in the Femoral Gland Secretions of Lacertid Lizards

by
Marco Mangiacotti
1,*,
Simon Baeckens
2,3,
Marco Fumagalli
1,4,
José Martín
5,
Stefano Scali
6 and
Roberto Sacchi
1
1
Department of Earth and Environmental Sciences, University of Pavia, 27100 Pavia, Italy
2
Functional Morphology Lab, Department of Biology, University of Antwerp, 2610 Wilrijk, Belgium
3
Evolution and Optics of Nanostructures Group, Department of Biology, Ghent University, 9000 Gent, Belgium
4
Department of Biology and Biotechnologies “L. Spallanzani”, University of Pavia, 27100 Pavia, Italy
5
Departamento de Ecología Evolutiva, Museo Nacional de Ciencias Naturales, Consejo Superior de Investigaciones Científicas, 28006 Madrid, Spain
6
Museo di Storia Naturale di Milano, 20121 Milano, Italy
*
Author to whom correspondence should be addressed.
Diversity 2023, 15(6), 777; https://doi.org/10.3390/d15060777
Submission received: 30 April 2023 / Revised: 13 June 2023 / Accepted: 14 June 2023 / Published: 15 June 2023
(This article belongs to the Special Issue Ecology and Evolution of Chemical Communication in Lizards)
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Abstract

:
Sexual selection contributes to the diversity of chemical signals in various animal groups. Lizards are good model species to study how sexual selection shapes signal diversity, as they are a chemically oriented taxonomic group with different levels of social interactions. Many lizard species bear epidermal glands secreting a waxy mixture of lipids and proteins, which are used in intraspecific communication. Previous among-species comparative analyses failed to find a relationship between the strength of sexual selection with the composition of the lipid blend in lizards. Here, we extend the investigation to the proteinaceous fraction. By using a phylogenetically informed approach, we correlated the average electrophoretic profiles of the protein from the femoral glands of 36 lacertid lizard species with the level of sexual dimorphism in size and shape, which are proxies for the strength of sexual selection. We found that as sexual size dimorphism advances, five distinct molecular weight regions in the protein profile increased their expression. Using tandem mass spectrometry, we successfully identified one of these five proteins: a carbonic anhydrase—an enzyme catalyzing the reversible hydration of carbon dioxide. Our findings suggest that proteins may be the target of sexual selection, as an active semiochemicals or as a dynamic support to other molecules: sexual selection may act indirectly on semiochemicals (namely lipids) by modifying the matrix (namely proteins).

1. Introduction

While less conspicuous to humans than other sensory modalities, chemical signals are the most ubiquitous form of information exchange in the natural world and their diversity is probably comparable to or even greater than that of visual and acoustic signals [1,2,3,4]. As such, the same questions about the mechanisms responsible for the origin and evolution of signal diversity in the visual and acoustic sensory channels also apply to the chemical modality [5,6,7], and sexual selection should be considered a key driver [8,9,10,11]. Both experimental and correlative studies have indeed shown how sexual selection can influence the evolution and design of chemical signals involved in both mate choice as well as intrasexual competition [9,10,11].
Lizards are a well-known chemically oriented vertebrate group [12,13], and in the last decade, they have increasingly been used as a model system to study chemical communication [14,15]. Recently, the occurrence and degrees of sociality in lizards have been linked to the species’ investment in chemical signaling [16], highlighting the importance of chemical communication in mediating intraspecific interactions. Lizards, indeed, use chemical signals to inform conspecifics about a variety of “socially interesting” features (e.g., territory ownership, individual identity, familiarity, size, parasite loads, health status, fighting ability, immune-response [17,18,19,20,21,22,23,24,25,26,27]). Further, specialized secretory structures show a male-biased sexual dimorphism in most species [28,29], combined with an activity that peaks during the reproductive season [30,31,32]. Together, all these observations lead to the hypothesis that sexual selection may play a pivotal role in the evolution of lizard chemical signals [33].
A first attempt to test whether and how sexual selection has contributed to shaping lizard chemical signal diversity focused on the Lacertidae family [33]. Lacertids are distributed over much of Eurasia and Africa and include about 350 species of typically small-to-medium-sized lizards [34,35,36]. Chemical communication has been extensively studied in lacertids over the last 15 years or so, notably concerning the femoral glands (FG) [14,15,29,37]. FG secretions consist of waxy protein–lipid mixtures [29,38], both components being active in communication [26,37,39,40]. Lipids, being more volatile and easily associated with male quality- and condition-related traits, have been historically considered of superior importance in functioning as semiochemicals compared to proteins [2,29,37,41]. On this basis, Baeckens and colleagues [33] reconstruct the evolutionary history of the lipid fraction of the secretions across the Lacertidae phylogeny but were not able to detect any significant effect of sexual selection on trait evolution: lipid composition, richness, and diversity did not covary with the expression of sexual dimorphism in shape or size, used as proxy for the strength of sexual selection [33]. Among the many possible interpretations of this unexpected outcome proposed by the same authors, it was pointed out that the indirect measures of signal structure (proportion of the main lipid categories) and complexity (number and diversity of compounds) might not have captured the signal features actually targeted by sexual selection [33]. Here, we put forward the possibility that the inclusion of the protein fraction in the analysis may add valuable information to the above-mentioned approach, at least because of three confirmed qualities of FG proteins, i.e.: (i) the occurrence of intraspecific variability at individual level in protein profiles [38,42,43]; (ii) the capability of proteins alone to convey socially relevant information to conspecifics [26,39,40]; and (iii) the seasonal variation in the relative abundance of the protein components, which follows the reproductive cycle and is synchronous to that of lipids [30]. The synchronized variation in protein abundances with lipids leads us to hypothesize that proteins may be involved in sexual signaling [44], therefore also being a potential target for sexual selection to act on, which eventually contributes to the observed diversity of FG proteins [43,45].
With the present study, we aimed to assess whether sexual selection may have contributed to the variability of the protein fraction of FG secretions. Following [33], we applied a phylogenetically informed generalized least square models to the protein profiles of 36 lacertid species [46], using the level of sexual dimorphism as a proxy for the strength of sexual selection [33]. We then used tandem mass spectrometry to identify the potentially involved proteins.

2. Materials and Methods

2.1. Data Collection

We assembled three distinct datasets at the species level for the Lacertidae family, notably concerning: (i) the proteinaceous composition of the femoral gland secretions; (ii) the average body and head measures of males and females, upon which to build sexual dimorphism indexes; and (iii) the phylogenetic tree of the species. Overall, the datasets included complete information about 36 lacertid species.
The information about the composition of the femoral gland proteins were obtained from the already published data [46]. Data consisted of species-level one-dimensional normalized electrophoretic profiles (electrophoretograms, EPGs) from 36 lacertid species. Data came only from males, since they were not available for females, which, at least in the considered species, bear almost vestigial glands [29,47] or produce very little amounts of secretion [48,49]. Each specific EPG corresponds to a sequence of 300 values representing the relative amount of protein clusters ordered by their molecular weight and averaged across individuals from the same species [50]. Although some degree of within-species variability can occur [38,46], such variation is less than the among-species one [46] and typically affects the relative height of some peaks rather than the overall band pattern [46]. Therefore, we can reasonably assume EPGs to represent a raw proxy of species FG protein composition [30,42,46,51]. Indeed, protein identification is still challenging [45,52], and, as far as we are aware, proteins from femoral gland secretions have been characterized in only two lizards [43,45], one of which does not belong to the lacertid family (but see [42]). For the same reason, as a working hypothesis, we assumed that each electrophoretic band corresponded to a single protein.
Following Baeckens et al. [33], for each species, we computed two indexes of sexual dimorphism (SD), which may be used as proxy for the strength of sexual selection [33]. The first is a sexual size dimorphism index (SSD) obtained as the ratio of the snout-to-vent length (SVL) of males compared to females (SVL♂/SVL♀) when males were larger than females, and 2-(SVL♀/SVL♂) if the opposite occurred [53,54]. This way, values larger than one indicate male-biased SSD, while values lower than one are for female-biased SSD. In lizards, male-biased SSD is usually associated with the increase in male–male intrasexual competition [55,56,57], since larger males are favored in male–male combats [58,59]. Besides overall size, head size also affects male fighting abilities [60,61]. Consequently, male-biased SD in relative head dimensions can also be informative about the strength of intrasexual competition and therefore sexual selection [33,57]. We computed the sexual head dimorphism index (SHD) using the same formulas as for SSD, by substituting SVL with the relative head size (head length/trunk length). The morphometric measures needed for the computation of SSD and SHD indexes were obtained from the literature (Table S1).
Finally, the phylogenetic tree of the 36 considered species was obtained by pruning the lacertid phylogenetic available in [36]. We used the keep.tip function of the ape R package [62] to subsample it to match the 36 species included in the study.

2.2. Statistical Analysis

To assess the occurrence of any effect of the strength of sexual dimorphism on the composition of the protein fraction of the femoral gland secretions, we used multivariate phylogenetic generalized least squares (pGLS) models, adapted to high-dimensional datasets [63]. In such a model, the matrix of normalized EPG (proxy for protein composition) was the response variable, while SSD and SHD entered the model as predictors. Being compositional in their nature, EPGs were centered-log–ratio transformed before entering the analysis [64,65].
To account for the phylogenetic dependency of the data, the correlation structure of the error was set according to five different models of continuous trait evolution: Brownian motion (BM), Ornstein–Uhlenbeck (OU), early burst (EB), late burst (LB), and Pagel’s λ (PA). The best model was then selected according to the Extended Information Criterion (EIC), an equivalent of the Akaike Information Criterion suited for models fitted using penalized likelihood [63]. The significance of the SSD and SHD terms were assessed for the best model using a permutational MANOVA [66]. All the analysis were implemented in R v.4.1.2 [67], using the package mvMORPH [68].

2.3. SSD-Related Protein Identification

Phylogenetic GLS highlighted a significant effect of SSD on EPGs (see results). To identify the potentially involved proteins, we ran novel electrophoretic shots for those samples (Acanthodactylus scutellatus, Gallotia stehlini, see results) showing the highest EPGs peaks just in the molecular region associated with the increase in SSD. Sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) of the selected samples followed the methodology described in [30]. From the fresh gels, we excised the bands of the regions of interest (Figure S1) and individually prepared them for mass spectrometry analysis adapting procedures from [69] (see Supplementary Material M1). Mass spectrometry (MS) analyses were carried out with a LC unit (ExionLCTM AD) equipped with a column oven thermostated at 40 °C, an autosampler cooled at 10 °C, and a binary gradient pump system. The MS instrument consists of a high resolution QTOF mass spectrometer (X500B, AB Sciex LLC, Framingham, MA, USA) equipped with a Turbo V Ion source and a Twin Sprayer ESI (electrospray ionization) probe, controlled by SCIEX OS v2.1 software (AB Sciex LLC, Framingham, MA, USA) (see Supplementary Materials M1 for setting details).
We performed protein identification via peptide-spectrum matching [52,70] using MS-GF+ v2022.01.17 [71,72]. We set the algorithm as follows: tolerance, 20 ppm; charge range, 1–6+; range of peptide length, 6–70; isotope error 0–1 Da; cleavage, tryptic; and post-translational modification, fix carbamidomethylation of cysteine [52,73,74]. Since no ad hoc database was available for the study species, searching was performed against UniProt dataset [75], after filtering for the taxonomic family “Lacertidae” (taxonID = 8522). To control for contaminants, we added pig trypsin sequence (accession: sp|P00761) to the database. The final dataset included 46,935 unique sequences. Only spectra with false detection rate (FDR) ≤ 0.01 were considered. All the above operations were implemented in R v4.1.2 [67], using the packages mzID v 1.28.0 [76], Biostrings v2.46.0 [77] and ad hoc functions to prepare database and call external software (MSGF+).

3. Results

The expression of sexual dimorphism is quite variable across the 36 considered species (Figure 1), both considering body size (SSD) and head size (SHD), with nine cases and one case of female-biased SSD and SHD, respectively. Furthermore, SSD and SHD did not behave coherently, almost showing a negative correlation, which highlights that the two indexes might be related with different behavioral traits (as discussed in [33]).
According to EIC, the best evolutionary model explaining SD-EPG relations was LB, which performed slightly better than OU and much better than EB, PA, and BM (Figure 2).
Permutational MANOVA of the best model highlighted a significant effect of SSD (Pillai’s trace = 0.613, p ≤ 0.046; 9999 permutations), while SHD had no effect (Pillai’s trace = 0.523, p ≤ 0.403; 9999 permutations). Keeping constant SHD, an increase in SSD corresponded to a raise in the concentration of proteins from five main molecular regions of the predicted EPG, approximately at 9.0, 13.5, 17.9, 35.4, and 66.3 kDa (Figure 3).

SSD-Related Protein Identification

The species showing the highest EPG peaks in the region associated by pGLS with SSD were Acanthodactylus scutellatus, for the lower bands, at 9.0 and 13.5 kDa (bands A, B; Figure 3), and Gallotia stehlini, for the upper ones at 17.9, 35.4, 66.3 kDa (bands C, D, E; Figure 3). The novel SDS-PAGE allowed identifying the target bands (Figure S1), which were excised and analyzed by MS.
Peptide-spectrum matching against Lacertidae database allowed identifying peptide sequences from all samples (Table S2). After filtering by contaminants (i.e., pig trypsin) and FDR < 0.01, only bands B, C, and D produced reliable identifications at peptide level (Table 1): two spectra matched three different database entries for band B; a single peptide was selected for band C and D. The above results prevent any identification at protein level. Nonetheless, considering the high scores, the relative coverage, and the approximate correspondence of predicted molecular weights with band positions in the gel, two peptide identifications may be also credible at protein level (Table 1): UPAR/Ly6 domain-containing protein (band B) and carbonic anhydrase (band D). Since the lack of specific databases for the considered species may have lowered the power of peptide-matching search [52,78], we tried refining the analysis of MS data from these bands by building ad hoc protein datasets basing on the outcomes of the first analysis [79]. Notably, we extracted from UniProtKB [75] all those protein sequences sharing at least one third of the amino acids with the two potentially identified proteins (uniprotID: A0A670IP55; A0A670JE51). We used BLASTP v.2.12.0 [80,81], available as an online tool on the uniport.org platform, to retrieve the target sequences. If the protein was correctly identified, we expected peptide-matching to improve its performance and to match more entries than against the Lacertidae database. Therefore, we re-ran the peptide-matching search against the above-obtained UPAR/Ly6 database (372 sequences) for band B, and Carbonic anhydrase database (990 entries) for band D. The approach was revealed as useful for band D (carbonic anhydrase; Table 2), for which three more peptides were identified, matching fish sequences, and making the protein identification credible. The performance was poor for band B (UPAR/Ly6 domain-containing protein; Table 2), with only a single peptide added to the list, thus not providing enough support to protein identification.

4. Discussion

Sexual size dimorphism correlates with the protein electrophoretic profiles of femoral glands secretions across the Lacertidae family. Five distinct molecular weight regions in the profile increased their expression with increasing SSD level. Out of these five proteins, one, at 35.4 kDa (band D, Figure 3), was successfully identified via tandem mass spectrometry, namely carbonic anhydrase, an enzyme catalyzing the reversible conversion of carbon dioxide into bicarbonate [82].
The significant relationship between SSD and EPGs suggests that sexual selection contributes to shaping the chemical signal design in lizards. Previous studies that focused on single species found FG secretions to impact both mate choice [18,83,84,85,86,87] and male intrasexual competition [20,23,88,89,90,91]. Further, specific compounds have shown to convey information about male quality-related traits, such as immunity, parasite load, and fighting abilities [17,19,20,27], implying that FG secretions act as sexual signals and, consequently, should be governed by sexual selection. In this light, our findings, based on a multi-species, phylogenetic approach, provide general support to this hypothesis, and bring along more specific underlying questions: i.e., how are proteins involved in sexual signaling, and how does sexual selection act on them. Unfortunately, the lack of a complete identification of the target proteins allows us to just delineate some possible interpretative scenarios.
On the one hand, being active in communication [26,39,40], FG proteins may convey information about male quality, which can be used to drive decision making (i.e., mate selection, rival assessment [14,33,85,90]), thus offering the basis for sexual selection to act on [8,37,92]. Aside from the semiochemical function of proteins, there is weak support for such interpretation: the occurrence of variation in EPGs at inter-individual level [38,42,43]; the EPGs changes between the reproductive and non-reproductive season [30]. Unfortunately, in the few studies investigating this aspect, no direct correlation was found between protein composition and traits linked to the signaler’s quality (e.g., size or body condition [30,38]). Furthermore, in the two lizard species (i.e., the Galapagos marine iguana, Amblyrhynchus cristatus, and the sand lizard, Lacerta agilis) for which FG proteins have been preliminarily characterized, no proteins easily relatable to such functions have been identified [43,45].
Although peptides and proteins may be actually used in sexual communication in other vertebrates (e.g., [44,93,94,95]), in lizards they are more probably involved in conveying identity-related, rather than quality-related, information [26,40,46,69]. From this perspective, it could be argued that proteins associated with SSD increase may allow for a more accurate individual discrimination: it could indeed be expected that distinguishing among very similar individuals may become pivotal when sexual selection is stronger and the cost for inaccuracy higher [25,90,96,97].
An alternative interpretation is suggested by the only identified protein among those associated with SSD increase. Carbonic anhydrase is a basic and ubiquitous enzyme [98], also found in vertebrate secretions (e.g., milk, saliva, tears [99,100,101]). The same enzyme has also been identified in the FG secretions of Galapagos marine iguana [45] and sand lizard [43], making our identification in Gallotia stehlini even more robust and reliable. By catalyzing the hydration of carbonic dioxide, carbonic anhydrase fundamentally acts on system homeostasis [99], conferring FG secretion the potential ability to react to the chemo-physical changes caused by the environmental conditions where it is left [45]. By extension, FG proteins may provide dynamic support to the other components of the mixture, eventually determining the overall chemo-physical characteristics of the signal or influencing the semiochemical properties of specific compounds. In the Asian Elephant [102], for example, female urine is enriched with a serum albumin, which serves for transport, to extend lifespan, and to improve detection by males via the sexual pheromone, (Z)-7-dodecenyl acetate. This way, sexual selection has favored the recruitment of an already available protein for a novel function, supporting that of the semiochemical [102]. Similarly, in mice, major urinary proteins (MUPs), besides working as semiochemicals conveying individual identity information themselves, bind volatile molecules (e.g., dehydro-exo-brevicomin and 2-sec-butyl-4,5-dihydrothiazole) used by females to assess the signaler status and for mate choice [102]. MUPs are able to extend and enhance the effectiveness of the airborne small molecules [103]. In this case, sexual selection has promoted the evolution of proteins with both direct and indirect functions. Applied to lizard FG secretions, sexual selection may have acted indirectly on the semiochemical portion of the signal (namely lipids), by modifying the matrix (namely proteins) of the blend, and our analysis may therefore have detected such an indirect effect.
Although speculative, the above rationale provides a testable prediction. We indeed expect to find a non-random association between the expression in the SSD region of EPG and some lipophilic compounds occurring in the mixture (which should represent the semiochemical counterpart); more precisely, those same lipids showing correlation with mate choice or rival assessment [14,41]. One can argue that such prediction has been already disregarded by the previous analysis performed on FG lipids [33], which failed to track any effect of sexual selection. Yet, the analysis on lipids grouped them into a priori chemical classes. According to our hypothesis, they should be specific semiochemical molecules to undergo sexual selection, and consequently, the class-level categorization of the lipophilic fraction may have masked the relation with SSD. Indeed, different lipids, even from the same chemical category, can follow independent evolutionary trajectories [104]. The same issue probably did not occur in the analysis of the protein counterpart because it has not been a priori reduced into categories, and it is probably less complex than the lipophilic mixture [38,69] (but see [43,45]). At the time of writing, a new study [105] found that the abundance of provitamin D3 (a lipophilic component) in FG secretions is associated with the same increase in the relative expression of two FG proteins: carbonic anhydrase and protein disulfide isomerases, the former corresponding to the one we have identified in the current study, the latter matching the molecular region predicted by our model (band B; Figure 3). High proportions of provitamin D3 in FG secretions are associated with a high-quality immune system in male wall lizards [18] and increases attractiveness towards females [106]. These findings corroborate our predictions and support our hypothesis concerning possible protein roles.
Finally, we found that sexual dimorphism in size and shape showed no apparent correlation. This makes the interpretation of the relation between SSD and SHD with sexual selection more complex. While male-biased sexual size dimorphism is typically linked to male intrasexual competition [55,56,57,107], sexual dimorphism in the relative head/trunk proportion may also possibly reflect other selective forces [55,107], which may eventually weaken or mask the relationship with sexual selection. Baeckens et al. [33], using a larger sample of lacertid species, found SSD and SHD to be negatively correlated, suggesting that a trade-off may occur between the two traits (size and shape). As the same author suggested, this is a noteworthy point which requires further investigation.
In conclusion, we acknowledge the preliminary and correlative nature of our results and interpretations, as well as the simplification we made in assuming a one-to-one relation between protein profiles and protein composition (by corresponding each band to a single protein). Nonetheless, we are cumulating evidence that proteins constitute more than a passive matrix for more volatile compounds, and they may be an important component of the signal. This indicates that further efforts are required to characterize them both chemically and functionally.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d15060777/s1, Methods M1: Protocol details for mass spectrometry analysis; Figure S1: SDS-PAGE of the samples used to excise the bands associated with the SSD increase and analyzed by mass spectrometry; Table S1: Morphometrics measures used for the computation of the sexual dimorphism indexes; Table S2: Complete list of the identified peptides from tandem MS.

Author Contributions

Conceptualization, M.M. and R.S.; formal analysis, M.M.; methodology, M.M., M.F. and R.S.; investigation, M.F.; data curation, M.M., S.B., J.M. and S.S.; resources, R.S. and M.F.; writing—original draft preparation, M.M.; writing—review and editing, M.M., M.F., S.B., J.M., S.S. and R.S. All authors have read and agreed to the published version of the manuscript.

Funding

M.M. was funded by Fondo Sociale Europeo REACT EU—Programma Operativo Nazionale Ricerca e Innovazione 2014–2020 (Italian Ministry for University and Research—MUR—CCI2014IT16M2OP005). S.B. was funded by the Fonds Wetenschappelijk Onderzoek (FWO 12I8822N).

Institutional Review Board Statement

The animal study protocol was approved by the Institutional Review Board of the University of Antwerp (Belgium) (ECD 2014-32) and the experimental design and procedure complied the ARRIVE guidelines (https://arriveguidelines.org/).

Data Availability Statement

Data associated with the manuscript are available at: https://doi.org/10.5281/zenodo.8036430.

Acknowledgments

We would like to thank Federico Forneris for his technical support and suggestions in analyzing MS data.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Apps, P.J.; Weldon, P.J.; Kramer, M. Chemical Signals in Terrestrial Vertebrates: Search for Design Features. Nat. Prod. Rep. 2015, 32, 1131–1153. [Google Scholar] [CrossRef]
  2. Weldon, P.J.; Flachsbarth, B.; Schulz, S. Natural Products from the Integument of Nonavian Reptiles. Nat. Prod. Rep. 2008, 25, 738–756. [Google Scholar] [CrossRef]
  3. Bradbury, J.W.; Vehrencamp, S.L. Principles of Animal Communication; Sinauer Associates, Inc.: Sunderland, UK, 2011; ISBN 978-0-87893-045-6. [Google Scholar]
  4. Wyatt, T.D. Pheromones and Signature Mixtures: Defining Species-Wide Signals and Variable Cues for Identity in Both Invertebrates and Vertebrates. J. Comp. Physiol. A 2010, 196, 685–700. [Google Scholar] [CrossRef]
  5. Wiens, J.J.; Tuschhoff, E. Songs versus Colours versus Horns: What Explains the Diversity of Sexually Selected Traits? Biol. Rev. 2020, 95, 847–864. [Google Scholar] [CrossRef] [PubMed]
  6. Tibbetts, E.A.; Mullen, S.P.; Dale, J. Signal Function Drives Phenotypic and Genetic Diversity: The Effects of Signalling Individual Identity, Quality or Behavioural Strategy. Philos. Trans. R. Soc. B Biol. Sci. 2017, 372, 20160347. [Google Scholar] [CrossRef] [Green Version]
  7. Symonds, M.R.E.; Elgar, M.A. The Evolution of Pheromone Diversity. Trends Ecol. Evol. 2008, 23, 220–228. [Google Scholar] [CrossRef] [PubMed]
  8. Andersson, M.; Simmons, L.W. Sexual Selection and Mate Choice. Trends Ecol. Evol. 2006, 21, 296–302. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Weber, M.G.; Mitko, L.; Eltz, T.; Ramírez, S.R. Macroevolution of Perfume Signalling in Orchid Bees. Ecol. Lett. 2016, 19, 1314–1323. [Google Scholar] [CrossRef]
  10. Steiger, S.; Stökl, J. The Role of Sexual Selection in the Evolution of Chemical Signals in Insects. Insects 2014, 5, 423–438. [Google Scholar] [CrossRef]
  11. Hunt, J.; Snook, R.R.; Mitchell, C.; Crudgington, H.S.; Moore, A.J. Sexual Selection and Experimental Evolution of Chemical Signals in Drosophila Pseudoobscura. J. Evol. Biol. 2012, 25, 2232–2241. [Google Scholar] [CrossRef]
  12. Schwenk, K. Of Tongues and Noses: Chemoreception in Lizards and Snakes. Trends Ecol. Evol. 1995, 10, 7–12. [Google Scholar] [CrossRef]
  13. Baeckens, S.; Herrel, A.; Broeckhoven, C.; Vasilopoulou-Kampitsi, M.; Huyghe, K.; Goyens, J.; Van Damme, R. Evolutionary Morphology of the Lizard Chemosensory System. Sci. Rep. 2017, 7, 10141. [Google Scholar] [CrossRef] [Green Version]
  14. Martín, J.; López, P. Condition-Dependent Chemosignals in Reproductive Behavior of Lizards. Horm. Behav. 2015, 68, 14–24. [Google Scholar] [CrossRef] [Green Version]
  15. Baeckens, S. Evolution of Animal Chemical Communication: Insights from Non-Model Species and Phylogenetic Comparative Methods. Belg. J. Zool. 2019, 149, 63–93. [Google Scholar] [CrossRef]
  16. Baeckens, S.; Whiting, M.J. Investment in Chemical Signalling Glands Facilitates the Evolution of Sociality in Lizards. Proc. R. Soc. B Biol. Sci. 2021, 288, 20202438. [Google Scholar] [CrossRef] [PubMed]
  17. Kopena, R.; López, P.; Martín, J. Immune Challenged Male Iberian Green Lizards May Increase the Expression of Some Sexual Signals If They Have Supplementary Vitamin, E. Behav. Ecol. Sociobiol. 2017, 71, 173. [Google Scholar] [CrossRef]
  18. López, P.; Martín, J. Female Iberian Wall Lizards Prefer Male Scents That Signal a Better Cell-Mediated Immune Response. Biol. Lett. 2005, 1, 404–406. [Google Scholar] [CrossRef] [PubMed]
  19. Martín, J.; Civantos, E.; Amo, L.; López, P. Chemical Ornaments of Male Lizards Psammodromus algirus May Reveal Their Parasite Load and Health State to Females. Behav. Ecol. Sociobiol. 2007, 62, 173–179. [Google Scholar] [CrossRef]
  20. Labra, A. Chemoreception and the Assessment of Fighting Abilities in the Lizard Liolaemus monticola. Ethology 2006, 112, 993–999. [Google Scholar] [CrossRef]
  21. Martín, J.; López, P. Scent May Signal Fighting Ability in Male Iberian Rock Lizards. Biol. Lett. 2007, 3, 125–127. [Google Scholar] [CrossRef] [Green Version]
  22. López, P.; Martín, J. Male Iberian Rock Lizards May Reduce the Costs of Fighting by Scent Matching of the Resource Holders. Behav. Ecol. Sociobiol. 2011, 65, 1891–1898. [Google Scholar] [CrossRef]
  23. Aragón, P.; López, P.; Martín, J. Size-Dependent Chemosensory Responses to Familiar and Unfamiliar Conspecific Faecal Pellets by the Iberian Rock-Lizard, Lacerta monticola. Ethology 2000, 106, 1115–1128. [Google Scholar] [CrossRef] [Green Version]
  24. Aragón, P.L.; López, P.; Martín, J. Chemosensory Discrimination of Familiar and Unfamiliar Conspecifics by Lizards: Implications of Field Spatial Relationships between Males. Behav. Ecol. Sociobiol. 2001, 50, 128–133. [Google Scholar] [CrossRef]
  25. Carazo, P.; Font, E.; Desfilis, E. Beyond “nasty Neighbours” and “Dear Enemies”? Individual Recognition by Scent Marks in a Lizard (Podarcis hispanica). Anim. Behav. 2008, 76, 1953–1963. [Google Scholar] [CrossRef]
  26. Mangiacotti, M.; Gaggiani, S.; Coladonato, A.J.; Scali, S.; Zuffi, M.A.L.; Sacchi, R. First Experimental Evidence That Proteins from Femoral Glands Convey Identity-Related Information in a Lizard. Acta Ethologica 2019, 22, 57–65. [Google Scholar] [CrossRef]
  27. López, P.; Gabirot, M.; Martín, J. Immune Activation Affects Chemical Sexual Ornaments of Male Iberian Wall Lizards. Naturwissenschaften 2009, 96, 65–69. [Google Scholar] [CrossRef] [PubMed]
  28. Cole, C.J. Femoral Glands in Lizards: A Review. Herpetologica 1966, 22, 199–206. [Google Scholar]
  29. Mayerl, C.; Baeckens, S.; Van Damme, R. Evolution and Role of the Follicular Epidermal Gland System in Non-Ophidian Squamates. Amphib.-Reptil. 2015, 36, 185–206. [Google Scholar] [CrossRef] [Green Version]
  30. Mangiacotti, M.; Pezzi, S.; Fumagalli, M.; Coladonato, A.J.; d’Ettorre, P.; Leroy, C.; Bonnet, X.; Zuffi, M.A.L.; Scali, S.; Sacchi, R. Seasonal Variations in Femoral Gland Secretions Reveals Some Unexpected Correlations Between Protein and Lipid Components in a Lacertid Lizard. J. Chem. Ecol. 2019, 45, 673–683. [Google Scholar] [CrossRef]
  31. Alberts, A.C.; Sharp, T.R.; Werner, D.I.; Weldon, P.J. Seasonal Variation of Lipids in Femoral Gland Secretions of Male Green Iguanas (Iguana iguana). J. Chem. Ecol. 1992, 18, 703–712. [Google Scholar] [CrossRef]
  32. Martins, E.P.; Ord, T.J.; Slaven, J.; Wright, J.L.; Housworth, E.A. Individual, Sexual, Seasonal, and Temporal Variation in the Amount of Sagebrush Lizard Scent Marks. J. Chem. Ecol. 2006, 32, 881–893. [Google Scholar] [CrossRef]
  33. Baeckens, S.; Martín, J.; García-Roa, R.; Van Damme, R. Sexual Selection and the Chemical Signal Design of Lacertid Lizards. Zool. J. Linn. Soc. 2018, 183, 445–457. [Google Scholar] [CrossRef] [Green Version]
  34. Sindaco, R.; Jeremcenko, V.K. The Reptiles of the Western Palearctic: Annotated Checklist and DistriButional Atlas of the Turtles, Crocodiles, Amphisbaenians and Lizards of Europe, North Africa, Middle East and Central Asia; Edizioni Belvedere: Latina, Italy, 2008; Volume 1, ISBN 978-88-89504-14-7. [Google Scholar]
  35. Roll, U.; Feldman, A.; Novosolov, M.; Allison, A.; Bauer, A.M.; Bernard, R.; Böhm, M.; Castro-Herrera, F.; Chirio, L.; Collen, B.; et al. The Global Distribution of Tetrapods Reveals a Need for Targeted Reptile Conservation. Nat. Ecol. Evol. 2017, 1, 1677–1682. [Google Scholar] [CrossRef]
  36. Garcia-Porta, J.; Irisarri, I.; Kirchner, M.; Rodríguez, A.; Kirchhof, S.; Brown, J.L.; MacLeod, A.; Turner, A.P.; Ahmadzadeh, F.; Albaladejo, G.; et al. Environmental Temperatures Shape Thermal Physiology as Well as Diversification and Genome-Wide Substitution Rates in Lizards. Nat. Commun. 2019, 10, 4077. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  37. Martín, J.; López, P. Pheromones and Chemical Communication in Lizards. In Reproductive Biology and Phylogeny of Lizards and Tuatara; Rheubert, J.L., Siegel, D.S., Trauth, S.E., Eds.; Taylor and Francis Group USA: New York, NY, USA, 2014; pp. 54–88. [Google Scholar]
  38. Mangiacotti, M.; Fumagalli, M.; Scali, S.; Zuffi, M.A.L.; Cagnone, M.; Salvini, R.; Sacchi, R. Inter- and Intra-Population Variability of the Protein Content of Femoral Gland Secretions from a Lacertid Lizard. Curr. Zool. 2017, 63, 657–665. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Alberts, A.C.; Werner, D.I. Chemical Recognition of Unfamiliar Conspecifics by Green Iguanas: Functional Significance of Different Signal Components. Anim. Behav. 1993, 46, 197–199. [Google Scholar] [CrossRef] [Green Version]
  40. Mangiacotti, M.; Martín, J.; López, P.; Reyes-Olivares, C.V.; Rodríguez-Ruiz, G.; Coladonato, A.J.; Scali, S.; Zuffi, M.A.L.; Sacchi, R. Proteins from Femoral Gland Secretions of Male Rock Lizards Iberolacerta cyreni Allow Self—But Not Individual—Recognition of Unfamiliar Males. Behav. Ecol. Sociobiol. 2020, 74, 68. [Google Scholar] [CrossRef]
  41. Martín, J.; López, P. Pheromones and Reproduction in Reptiles. In Hormones and Reproduction of Vertebrates; Lopez, K.H., Norris, D.O., Eds.; Academic Press: London, UK, 2011; pp. 141–167. ISBN 978-0-12-374930-7. [Google Scholar]
  42. Alberts, A.C.; Phillips, J.A.; Werner, D.I. Sources of Intraspecific Variability in the Protein Composition of Lizard Femoral Gland Secretions. Copeia 1993, 1993, 775–781. [Google Scholar] [CrossRef]
  43. Ibáñez, A.; Skupien-rabian, B.; Jankowska, U.; Kędracka-krok, S.; Zając, B. Functional Protein Composition in Femoral Glands of Sand Lizards (Lacerta agilis). Molecules 2022, 27, 2371. [Google Scholar] [CrossRef]
  44. Wyatt, T.D. Proteins and Peptides as Pheromone Signals and Chemical Signatures. Anim. Behav. 2014, 97, 273–280. [Google Scholar] [CrossRef]
  45. Tellkamp, F.; Lang, F.; Ibáñez, A.; Abraham, L.; Quezada, G.; Günther, S.; Looso, M.; Tann, F.J.; Müller, D.; Cemic, F.; et al. Proteomics of Galápagos Marine Iguanas Links Function of Femoral Gland Proteins to the Immune System. Mol. Cell. Proteom. 2020, 19, 1523–1532. [Google Scholar] [CrossRef]
  46. Mangiacotti, M.; Baeckens, S.; Scali, S.; Martín, J.; Van Damme, R.; Sacchi, R. Evolutionary and Biogeographical Support for Species-Specific Proteins in Lizard Chemical Signals. Biol. J. Linn. Soc. 2021, 134, 912–928. [Google Scholar] [CrossRef]
  47. García-Roa, R.; Jara, M.; Baeckens, S.; López, P.; Van Damme, R.; Martín, J.; Pincheira-Donoso, D. Macroevolutionary Diversification of Glands for Chemical Communication in Squamate Reptiles. Sci. Rep. 2017, 7, 9288. [Google Scholar] [CrossRef] [Green Version]
  48. Martín, J.; Castilla, A.M.; López, P.; Al-Jaidah, M.; Al-Mohannadi, S.F.; Al-Hemaidi, A.A.M. Chemical Signals in Desert Lizards: Are Femoral Gland Secretions of Male and Female Spiny-Tailed Lizards, Uromastyx aegyptia microlepis Adapted to Arid Conditions? J. Arid. Environ. 2016, 127, 192–198. [Google Scholar] [CrossRef] [Green Version]
  49. Khannoon, E.R.; Flachsbarth, B.; El-Gendy, A.; Mazik, K.; Hardege, J.D.; Schulz, S. New Compounds, Sexual Differences, and Age-Related Variations in the Femoral Gland Secretions of the Lacertid Lizard Acanthodactylus boskianus. Biochem. Syst. Ecol. 2011, 39, 95–101. [Google Scholar] [CrossRef]
  50. Garfin, D.E. One-Dimensional Gel Electrophoresis. In Methods in Enzymology; Burgess, R.R., Deutscher, M.P.B.T., Eds.; Academic Press: Cambridge, MA, USA, 2009; Volume 463, pp. 497–513. ISBN 978-0-12-374536-1. [Google Scholar]
  51. Alberts, A.C. Phylogenetic and Adaptive Variation in Lizard Femoral Gland Secretions. Copeia 1991, 1991, 69–79. [Google Scholar] [CrossRef]
  52. Eng, J.K.; Searle, B.C.; Clauser, K.R.; Tabb, D.L. A Face in the Crowd: Recognizing Peptides Through Database Search. Mol. Cell. Proteom. 2011, 10, R111.009522. [Google Scholar] [CrossRef] [Green Version]
  53. Lovich, J.E.; Gibbons, J.W. Review of Techniques for Quantifying Sexual Size Dimorphism. Growth Dev. Aging 1992, 56, 269–281. [Google Scholar]
  54. Smith, R.J. Statistics of Sexual Size Dimorphism. J. Hum. Evol. 1999, 36, 423–458. [Google Scholar] [CrossRef]
  55. Braña, F. Sexual Dimorphism in Lacertid Lizards: Male Head Increase vs Female Abdomen Increase? Oikos 1996, 75, 511. [Google Scholar] [CrossRef]
  56. Cox, R.M.; Skelly, S.L.; John-Alder, H.B. A Comparative Test of Adaptive Hypotheses for Sexual Size Dimorphism in Lizards. Evolution 2003, 57, 1653–1669. [Google Scholar] [CrossRef] [PubMed]
  57. Sacchi, R.; Mangiacotti, M.; Scali, S.; Sannolo, M.; Zuffi, M.A.L.; Pellitteri-Rosa, D.; Bellati, A.; Galeotti, P.; Fasola, M. Context-Dependent Expression of Sexual Dimorphism in Island Populations of the Common Wall Lizard (Podarcis muralis). Biol. J. Linn. Soc. 2015, 114, 552–565. [Google Scholar] [CrossRef] [Green Version]
  58. Sacchi, R.; Pupin, F.; Gentilli, A.; Rubolini, D.; Scali, S.; Fasola, M.; Galeotti, P. Male-Male Combats in a Polymorphic Lizard: Residency and Size, but Not Color, Affect Fighting Rules and Contest Outcome. Aggress. Behav. 2009, 35, 274–283. [Google Scholar] [CrossRef] [PubMed]
  59. Titone, V.; Marsiglia, F.; Mangiacotti, M.; Sacchi, R.; Scali, S.; Zuffi, M.A.L. Better to Be Resident, Larger or Coloured? Experimental Analysis on Intraspecific Aggression in the Ruin Lizard. J. Zool. 2018, 304, 260–267. [Google Scholar] [CrossRef]
  60. Gvoždík, L.; Van Damme, R. Evolutionary Maintenance of Sexual Dimorphism in Head Size in the Lizard Zootoca vivipara: A Test of Two Hypotheses. J. Zool. 2003, 259, 7–13. [Google Scholar] [CrossRef]
  61. Huyghe, K.; Vanhooydonck, B.; Scheers, H.; Molina-Borja, M.; Van Damme, R. Morphology, Performance and Fighting Capacity in Male Lizards, Gallotia galloti. Funct. Ecol. 2005, 19, 800–807. [Google Scholar] [CrossRef]
  62. Paradis, E.; Schliep, K. Ape 5.0: An Environment for Modern Phylogenetics and Evolutionary Analyses in R. Bioinformatics 2019, 35, 526–528. [Google Scholar] [CrossRef]
  63. Clavel, J.; Aristide, L.; Morlon, H. A Penalized Likelihood Framework for High-Dimensional Phylogenetic Comparative Methods and an Application to New-World Monkeys Brain Evolution. Syst. Biol. 2019, 68, 93–116. [Google Scholar] [CrossRef] [Green Version]
  64. Aitchison, J. The Statistical Analysis of Compositional Data. J. R. Stat. Society. Ser. B (Methodol.) 1982, 44, 139–177. [Google Scholar] [CrossRef]
  65. van den Boogaart, K.G.; Tolosana-Delgado, R. Analyzing Compositional Data with R; Springer: Berlin/Heidelberg, Germany, 2013; Volume 122, ISBN 978-3-642-36809-7. [Google Scholar]
  66. Clavel, J.; Morlon, H. Reliable Phylogenetic Regressions for Multivariate Comparative Data: Illustration with the MANOVA and Application to the Effect of Diet on Mandible Morphology in Phyllostomid Bats. Syst. Biol. 2020, 69, 927–943. [Google Scholar] [CrossRef]
  67. R Core Team. R: A Language and Environment for Statistical Computing; R Foundation for Statistical Computing: Vienna, Austria, 2021. [Google Scholar]
  68. Clavel, J.; Escarguel, G.; Merceron, G. MvMORPH: An R Package for Fitting Multivariate Evolutionary Models to Morphometric Data. Methods Ecol. Evol. 2015, 6, 1311–1319. [Google Scholar] [CrossRef]
  69. Mangiacotti, M.; Fumagalli, M.; Cagnone, M.; Viglio, S.; Bardoni, A.M.; Scali, S.; Sacchi, R. Morph-Specific Protein Patterns in the Femoral Gland Secretions of a Colour Polymorphic Lizard. Sci. Rep. 2019, 9, 8412. [Google Scholar] [CrossRef] [Green Version]
  70. Nesvizhskii, A.I. Proteogenomics: Concepts, Applications and Computational Strategies. Nat. Methods 2014, 11, 1114–1125. [Google Scholar] [CrossRef]
  71. Kim, S.; Gupta, N.; Pevzner, P.A. Spectral Probabilities and Generating Functions of Tandem Mass Spectra: A Strike against Decoy Databases. J. Proteome Res. 2008, 7, 3354–3363. [Google Scholar] [CrossRef] [Green Version]
  72. Kim, S.; Pevzner, P.A. MS-GF+ Makes Progress towards a Universal Database Search Tool for Proteomics. Nat. Commun. 2014, 5, 5277. [Google Scholar] [CrossRef] [Green Version]
  73. Creasy, D.M.; Cottrell, J.S. Unimod: Protein Modifications for Mass Spectrometry. Proteomics 2004, 4, 1534–1536. [Google Scholar] [CrossRef]
  74. Schittmayer, M.; Fritz, K.; Liesinger, L.; Griss, J.; Birner-Gruenberger, R. Cleaning out the Litterbox of Proteomic Scientists Favorite Pet: Optimized Data Analysis Avoiding Trypsin Artifacts. J. Proteome Res. 2016, 15, 1222–1229. [Google Scholar] [CrossRef] [Green Version]
  75. Bateman, A.; Martin, M.J.; Orchard, S.; Magrane, M.; Agivetova, R.; Ahmad, S.; Alpi, E.; Bowler-Barnett, E.H.; Britto, R.; Bursteinas, B.; et al. UniProt: The Universal Protein Knowledgebase in 2021. Nucleic Acids Res. 2021, 49, D480–D489. [Google Scholar] [CrossRef]
  76. Pedersen, T. MzID: An MzIdentML Parser for R, v. 1.28.0. 2021. [CrossRef]
  77. Pagès, H.; Aboyoun, P.; Gentleman, R.; DebRoy, S. Biostrings: Efficient Manipulation of Biological Strings, R package version 2.46.0. 2021. [CrossRef]
  78. Carpentler, S.C.; Panis, B.; Vertommen, A.; Swennen, R.; Sergeant, K.; Renaut, J.; Laukens, K.; Witters, E.; Samyn, B.; Devreese, B. Proteome Analysis of Non-Model Plants: A Challenging but Powerful Approach. Mass. Spectrom. Rev. 2008, 27, 354–377. [Google Scholar] [CrossRef] [PubMed]
  79. Everett, L.J.; Bierl, C.; Master, S.R. Unbiased Statistical Analysis for Multi-Stage Proteomic Search Strategies. J. Proteome Res. 2010, 9, 700–707. [Google Scholar] [CrossRef] [PubMed]
  80. Altschul, S.F.; Madden, T.L.; Schäffer, A.A.; Zhang, J.; Zhang, Z.; Miller, W.; Lipman, D.J. Gapped BLAST and PSI-BLAST: A New Generation of Protein Database Search Programs. Nucleic Acids Res. 1997, 25, 3389–3402. [Google Scholar] [CrossRef] [Green Version]
  81. Schäffer, A.A.; Aravind, L.; Madden, T.L.; Shavirin, S.; Spouge, J.L.; Wolf, Y.I.; Koonin, E.V.; Altschul, S.F. Improving the Accuracy of PSI-BLAST Protein Database Searches with Composition-Based Statistics and Other Refinements. Nucleic Acids Res. 2001, 29, 2994–3005. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  82. Frost, S.C. Physiological Functions of the Alpha Class of Carbonic Anhydrases. In Carbonic Anhydrase: Mechanism, Regulation, Links to Disease, and Industrial Applications; Frost, S.C., McKenna, R., Eds.; Springer: Dordrecht, The Netherlands, 2014; pp. 9–30. ISBN 978-94-007-7359-2. [Google Scholar]
  83. Kopena, R.; Martín, J.; López, P.; Herczeg, G. Vitamin E Supplementation Increases the Attractiveness of Males’ Scent for Female European Green Lizards. PLoS ONE 2011, 6, e19410. [Google Scholar] [CrossRef] [Green Version]
  84. Martín, J.; López, P. Chemoreception, Symmetry and Mate Choice in Lizards. Proc. R. Soc. B Biol. Sci. 2000, 267, 1265–1269. [Google Scholar] [CrossRef]
  85. Martín, J.; López, P. Links between Male Quality, Male Chemical Signals, and Female Mate Choice in Iberian Rock Lizards. Funct. Ecol. 2006, 20, 1087–1096. [Google Scholar] [CrossRef]
  86. López, P.; Martín, J. Chemosensory Exploration of Male Scent by Female Rock Lizards Result from Multiple Chemical Signals of Males. Chem. Senses 2012, 37, 47–54. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  87. López, P.; Martín, J.; Cuadrado, M. Pheromone-Mediated Intrasexual Aggression in Male Lizards, Podarcis hispanicus. Aggress. Behav. 2002, 28, 154–163. [Google Scholar] [CrossRef]
  88. Font, E.; Barbosa, D.; Sampedro, C.; Carazo, P. Social Behavior, Chemical Communication, and Adult Neurogenesis: Studies of Scent Mark Function in Podarcis Wall Lizards. Gen. Comp. Endocrinol. 2012, 177, 9–17. [Google Scholar] [CrossRef]
  89. Carazo, P.; Font, E.; Desfilis, E. Chemosensory Assessment of Rival Competitive Ability and Scent-Mark Function in a Lizard, Podarcis hispanica. Anim. Behav. 2007, 74, 895–902. [Google Scholar] [CrossRef]
  90. López, P.; Martín, J. Chemical Rival Recognition Decreases Aggression Levels in Male Iberian Wall Lizards, Podarcis hispanica. Behav. Ecol. Sociobiol. 2002, 51, 461–465. [Google Scholar] [CrossRef]
  91. Martín, J.; Moreira, P.L.; López, P. Status-Signalling Chemical Badges in Male Iberian Rock Lizards. Funct. Ecol. 2007, 21, 568–576. [Google Scholar] [CrossRef]
  92. Whiting, M.J.; While, G.M. Sociality in Lizards. In Comparative Social Evolution; Rubenstein, D.R., Abbot, P., Eds.; Cambridge University Press: Cambridge, MA, USA, 2017; pp. 354–389. ISBN 978-1-107-33831-9. [Google Scholar]
  93. Kikuyama, S.; Toyoda, F.; Ohmiya, Y.; Matsuda, K.; Tanaka, S.; Hayashi, H. Sodefrin: A Female-Attracting Peptide Pheromone in Newt Cloacal Glands. Science 1995, 267, 1643–1645. [Google Scholar] [CrossRef] [PubMed]
  94. Toyoda, F.; Yamamoto, K.; Iwata, T.; Hasunuma, I.; Cardinali, M.; Mosconi, G.; Polzonetti-Magni, A.M.; Kikuyama, S. Peptide Pheromones in Newts. Peptides 2004, 25, 1531–1536. [Google Scholar] [CrossRef]
  95. Mucignat-Caretta, C.; Caretta, A. Message in a Bottle: Major Urinary Proteins and Their Multiple Roles in Mouse Intraspecific Chemical Communication. Anim. Behav. 2014, 97, 255–263. [Google Scholar] [CrossRef]
  96. López, P.; Martin, J. Sexual Selection and Chemoreception in Lacertid Lizards. In The Biology of Lacertid Lizards. Evolutionary and Ecological Perspectives; Pérez-Mellado, V., Riera, V., Perera, A., Eds.; Recerca; Institut Menorquí d’Estudis: Balearic Islands, Spain, 2004; pp. 119–137. [Google Scholar]
  97. Tibbetts, E.A.; Dale, J. Individual Recognition: It Is Good to Be Different. Trends Ecol. Evol. 2007, 22, 529–537. [Google Scholar] [CrossRef]
  98. McKenna, R.; Frost, S.C. Overview of the Carbonic Anhydrase Family. In Carbonic Anhydrase: Mechanism, Regulation, Links to Disease, and Industrial Applications; Frost, S.C., McKenna, R., Eds.; Springer: Dordrecht, The Netherlands, 2014; pp. 3–5. ISBN 978-94-007-7359-2. [Google Scholar]
  99. Supuran, C.T. Structure and Function of Carbonic Anhydrases. Biochem. J. 2016, 473, 2023–2032. [Google Scholar] [CrossRef]
  100. Kitade, K.; Nishita, T.; Yamato, M.; Sakamoto, K.; Hagino, A.; Katoh, K.; Obara, Y. Expression and Localization of Carbonic Anhydrase in Bovine Mammary Gland and Secretion in Milk. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 2003, 134, 349–354. [Google Scholar] [CrossRef]
  101. Yrjänäinen, A.; Patrikainen, M.S.; Azizi, L.; Tolvanen, M.E.E.; Laitaoja, M.; Jänis, J.; Hytönen, V.P.; Nocentini, A.; Supuran, C.T.; Parkkila, S. Biochemical and Biophysical Characterization of Carbonic Anhydrase VI from Human Milk and Saliva. Protein J. 2022, 41, 489–503. [Google Scholar] [CrossRef]
  102. Lazar, J.; Rasmussen, L.E.L.; Greenwood, D.R.; Bang, I.S.; Prestwich, G.D. Elephant Albumin: A Multipurpose Pheromone Shuttle. Chem. Biol. 2004, 11, 1093–1100. [Google Scholar] [CrossRef] [Green Version]
  103. Hurst, J.L. Female Recognition and Assessment of Males through Scent. Behav. Brain Res. 2009, 200, 295–303. [Google Scholar] [CrossRef] [PubMed]
  104. García-Roa, R.; Jara, M.; López, P.; Martín, J.; Pincheira-Donoso, D. Heterogeneous Tempo and Mode of Evolutionary Diversification of Compounds in Lizard Chemical Signals. Ecol. Evol. 2017, 7, 1286–1296. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Mangiacotti, M.; Baeckens, S.; Fumagalli, M.; Martín, J.; Scali, S.; Sacchi, R. Protein–Lipid Association in Lizard Chemical Signals. Integr. Org. Biol. 2023, 5, obad016. [Google Scholar] [CrossRef] [PubMed]
  106. Martín, J.; López, P. Vitamin D Supplementation Increases the Attractiveness of Males’ Scent for Female Iberian Rock Lizards. Proc. R. Soc. B Biol. Sci. 2006, 273, 2619–2624. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  107. Cox, R.M.; Butler, M.A.; John-Alder, H.B. The Evolution of Sexual Size Dimorphism in Reptiles. In Sex, Size and Gender Roles: Evolutionary Studies of Sexual Size Dimorphism; Fairbairn, D.J., Blanckenhorn, W.U., Székely, T., Eds.; Oxford University Press: Oxford, UK, 2007; ISBN 978-0-19-920878-4. [Google Scholar]
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Figure 1. Phylogenetic map of the expression of sexual size dimorphism (SSD; left tree) and sexual head dimorphism (SHD; right tree) in the 36 lacertid species included in this study. Light blue and asterisk indicate female-biased dimorphism; the orange gradient represents the intensity of male-biased dimorphism.
Figure 1. Phylogenetic map of the expression of sexual size dimorphism (SSD; left tree) and sexual head dimorphism (SHD; right tree) in the 36 lacertid species included in this study. Light blue and asterisk indicate female-biased dimorphism; the orange gradient represents the intensity of male-biased dimorphism.
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Figure 2. Bootstrapped extended information criterion (EIC) values for the five evolutionary models used to account for the phylogenetic dependences between protein electrophoretic profiles and sexual dimorphism in the phylogenetic generalized least squares model. Solid lines = mean value; shadowed rectangles = ±1 SE interval around the mean; grey points = observed bootstrapped value for each model (100 in total). The best model (lowest EIC) is dark-red colored.
Figure 2. Bootstrapped extended information criterion (EIC) values for the five evolutionary models used to account for the phylogenetic dependences between protein electrophoretic profiles and sexual dimorphism in the phylogenetic generalized least squares model. Solid lines = mean value; shadowed rectangles = ±1 SE interval around the mean; grey points = observed bootstrapped value for each model (100 in total). The best model (lowest EIC) is dark-red colored.
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Figure 3. Predicted protein profiles following male-biased sexual size dimorphism (SSD) increase. Left side: predicted electrophoretic profile (EPG) spanning from the absence of SSD (unit value; light blue) to the maximum (orange) observed SSD. Right side: virtual gel lane corresponding to the predicted EPG at the unit (light blue) and maximum (orange) SSD value, respectively: these are a translation of the relative peak heights of the profiles reported in the left side into a color intensity strip resembling a gel lane theoretically obtainable in a virtual electrophoretic run. Dotted boxes A–E denote the molecular region most associated with the SSD increase, which were the focus of the MS analysis.
Figure 3. Predicted protein profiles following male-biased sexual size dimorphism (SSD) increase. Left side: predicted electrophoretic profile (EPG) spanning from the absence of SSD (unit value; light blue) to the maximum (orange) observed SSD. Right side: virtual gel lane corresponding to the predicted EPG at the unit (light blue) and maximum (orange) SSD value, respectively: these are a translation of the relative peak heights of the profiles reported in the left side into a color intensity strip resembling a gel lane theoretically obtainable in a virtual electrophoretic run. Dotted boxes A–E denote the molecular region most associated with the SSD increase, which were the focus of the MS analysis.
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Table
Table 1. List of the identified peptides with a false detection rate below 0.01. For the complete list, see Table S2. Band = gel region considered in the MS analysis as in Figure 3 and Figure S1; ID = spectrum ID; score = MSGF+ spectrum E-value (−log10 transformed); error = difference between measured and calculated parental ion mass (Da); UniProtID = unique uniprotKB identifier; description = uniprotKB description; coverage = percent protein sequence covered by the identified peptide; MW = predicted molecular weight (kDa) of the corresponding protein.
Table 1. List of the identified peptides with a false detection rate below 0.01. For the complete list, see Table S2. Band = gel region considered in the MS analysis as in Figure 3 and Figure S1; ID = spectrum ID; score = MSGF+ spectrum E-value (−log10 transformed); error = difference between measured and calculated parental ion mass (Da); UniProtID = unique uniprotKB identifier; description = uniprotKB description; coverage = percent protein sequence covered by the identified peptide; MW = predicted molecular weight (kDa) of the corresponding protein.
BandIDPeptideScoreErrorUniProtIDDescriptionCoverage (%)MW
B3544SCIDTELCDVGYGSASITSSMYIQSK9.3740.036A0A670IP55UPAR/Ly6 domain-containing protein17.8115.8
2948AHDGIR8.026−0.009A0A670JC88Zinc finger protein 436-like1.1658.8
2948AHDGLR8.026−0.009A0A670JYQ1SWI/SNF-related matrix-associated actin-dependent regulator of chromatin subfamily A-like protein 10.61109.1
C3168QMIKINFK8.341−0.005A0A670KI84COP9 signalosome complex subunit 21.7852.4
D3157YSMELHIVHTK14.8560.005A0A670JE51Carbonic anhydrase4.2528.4
Table
Table 2. List of the identified peptides with false detection rate below 0.01 using ad hoc databases for UPAR/Ly6 and Carbonic anhydrase. Headings as in Table 1; already identified peptide sequences are italicized; identity = % sequence identity with the query protein in BLASTP.
Table 2. List of the identified peptides with false detection rate below 0.01 using ad hoc databases for UPAR/Ly6 and Carbonic anhydrase. Headings as in Table 1; already identified peptide sequences are italicized; identity = % sequence identity with the query protein in BLASTP.
BandIDPeptideScoreErrorUniProtIDIdentity (%)DescriptionOrganismCoverage (%)MW
B3544SCIDTELCDVGYGSASITSSMYIQSK9.4340.036A0A670IP55100.0UPAR/Ly6 domain-
containing protein		Podarcis muralis17.8115.8
2908REERPR5.558−0.008A0A8C5QXT237.4Leptobrachium leishanense2.7623.1
D3157YSMELHIVHTK14.8360.005A0A670JE51100.0Carbonic anhydrasePodarcis muralis4.2528.4
3184EPITHYIPACRQVNR6.1910.970A0A8C1L80641.4Cyprinus carpio4.4436.9
2893MELHVVNK6.1911.020A0A6P6QLI138.2Carassius auratus2.4835.8
3816ANDSSALAVLGFFIEGTDEADK5.6670.982Q08C2038.6Danio rerio6.7935.1
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MDPI and ACS Style

Mangiacotti, M.; Baeckens, S.; Fumagalli, M.; Martín, J.; Scali, S.; Sacchi, R. Sexual Selection and Proteinaceous Diversity in the Femoral Gland Secretions of Lacertid Lizards. Diversity 2023, 15, 777. https://doi.org/10.3390/d15060777

AMA Style

Mangiacotti M, Baeckens S, Fumagalli M, Martín J, Scali S, Sacchi R. Sexual Selection and Proteinaceous Diversity in the Femoral Gland Secretions of Lacertid Lizards. Diversity. 2023; 15(6):777. https://doi.org/10.3390/d15060777

Chicago/Turabian Style

Mangiacotti, Marco, Simon Baeckens, Marco Fumagalli, José Martín, Stefano Scali, and Roberto Sacchi. 2023. "Sexual Selection and Proteinaceous Diversity in the Femoral Gland Secretions of Lacertid Lizards" Diversity 15, no. 6: 777. https://doi.org/10.3390/d15060777

APA Style

Mangiacotti, M., Baeckens, S., Fumagalli, M., Martín, J., Scali, S., & Sacchi, R. (2023). Sexual Selection and Proteinaceous Diversity in the Femoral Gland Secretions of Lacertid Lizards. Diversity, 15(6), 777. https://doi.org/10.3390/d15060777

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