Mammalian Molar Complexity Follows Simple, Predictable Patterns
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Mammalian molar complexity follows simple, predictable patterns Keegan R. Seliga,1, Waqqas Khalida, and Mary T. Silcoxa aDepartment of Anthropology, University of Toronto Scarborough, Toronto, ON M1C 1A4, Canada Edited by Nils Chr. Stenseth, University of Oslo, Oslo, Norway, and approved November 19, 2020 (received for review May 4, 2020) Identifying developmental explanations for the evolution of com- been demonstrated that there are strong genetic controls that plex structures like mammalian molars is fundamental to studying account for the developmental cascade, with research linking the phenotypic variation. Previous study showed that a “morphoge- ICM and the sonic hedgehog (Shh) gene, among others (10). It netic gradient” of molar proportions was explained by a balance should be noted that there are cases where the ICM does between inhibiting/activating activity from earlier developing mo- not seem to account for molar size covariation. For example, lars, termed the inhibitory cascade model (ICM). Although this Roseman and Delezene (11) found that gorillas do not meet any model provides an explanation for variation in molar proportions, of the predictions of the ICM, and Carter and Worthington (12) what remains poorly understood is if molar shape, or specifically demonstrate that some hominoids and cercopithecins do not complexity (i.e., the number of cusps, crests), can be explained by meet all of the predictions either. However, Evans et al. (2) also the same developmental model. Here, we show that molar com- analyzed the ICM in apes and hominids and considered both the plexity conforms to the ICM, following a linear, morphogenetic deciduous premolars and a reversal of the inhibitory cascade gradient along the molar row. Moreover, differing levels of inhib- patterns in their analysis. By considering these two additional iting/activating activity produce contrasting patterns of molar factors, Evans et al. (2) demonstrated that hominoids do actually complexity depending on diet. This study corroborates a model meet the expectations of the ICM. for the evolution of molar complexity that is developmentally sim- The ICM provides a model to explain molar size covariation in ple, where only small-scale developmental changes need to occur many taxa. What it does not consider, however, is the potential to produce change across the entire molar row, with this process for adaptation in patterns of molar complexity. Molar shape, and being mediated by an animal’s ecology. The ICM therefore pro- particularly the number of features present on the occlusal sur- EVOLUTION vides a developmental framework for explaining variation in mo- face such as crests, cusps, and crenules (i.e., occlusal complexity) lar complexity and a means for testing developmental hypotheses covaries with feeding behavior (13–20). Kavanagh et al. (1) ob- in the broader context of mammalian evolution. served some apparent morphological differences in the dentition of murines: Taxa that had more equally sized molars were gen- Euarchonta | three-dimensional orientation patch count rotated | erally herbivorous and had relatively more complex teeth, occlusal morphology whereas faunivorous taxa had simple teeth that became relatively reduced in size moving distally. Following on this result, we ammalian molars develop from mesial to distal, with the provide further, empirical evidence that that differences in levels Mdental lamina of the first molar (M1) extending posteri- of inhibition/activation in the molar row in other mammals can orly, giving rise to the second molar (M2). This means that in- be explained by differences in diet (1). There is some indication hibition/activation of earlier structures has a cumulative effect on later developing teeth, as more developmental events must take Significance place for later structures to develop (1–3). A relationship has been identified between the size (surface area) of the earlier Recent studies have sought simple developmental models to developing molars and that of the later developing molars, be- explain variation in complex structures like mammalian teeth. lieved to be a product of the balance between inhibitors (sig- The inhibitory cascade model (ICM) provides an explanation for naling molecules that impede the development of subsequent the “morphogenetic gradient” of molar size, where a balance teeth) and activators (signaling molecules that promote the de- between signaling molecules in developing teeth produces velopment of subsequent teeth) in the earlier developing struc- predictable, linear proportions across the molars. However, it tures (1). The M1 acts as an inhibitor on the M2, reducing the is unknown if molar form (specifically complexity) can be size of the later developing tooth in vivo. When the developing explained by the ICM. We demonstrate that molar complexity M2 is cut from the posterior end of the M1 in vitro earlier than follows a linear, predictable gradient along the molar row. these structures would naturally separate, inhibition from M1 is Moreover, whether the pattern is of increasing or decreasing reduced, thus M2 and subsequently the third molar (M3) de- complexity moving from front to back is dependent on the velop to be relatively larger (1). Kavanagh et al. (1) recognized animal’s diet. This study provides a developmental framework this mechanism as the inhibitory cascade model (ICM), wherein for explaining patterns of morphological complexity in molars a balance between inhibitors/activators controls molar propor- and for testing developmental and ecological hypotheses tions. Kavanagh et al. (1) argued that if molars follow a mor- in mammals. phogenetic gradient, then a ratio of third molar size to first molar size regressed against a ratio of second molar size to first molar Author contributions: K.R.S. and M.T.S. designed research; K.R.S. performed research; size should produce a positive, linear regression with a slope of K.R.S. and W.K. analyzed data; K.R.S. wrote the paper; W.K and M.T.S. edited the man- 2.0 and an intercept of −1.0. Similarly, Evans et al. (2) suggested uscript; and M.T.S. oversaw the project. that if the size of the M2 is the average of the M1+M3, or the The authors declare no competing interest. relationship between the molars is linear as posited by the ICM, This article is a PNAS Direct Submission. then the relative size of the molars conforms to the ICM as well. Published under the PNAS license. As a whole, the ICM provides both a mechanism and a predictive 1To whom correspondence may be addressed. Email: [email protected]. tool for explaining the patterning of molar proportions. This This article contains supporting information online at https://www.pnas.org/lookup/suppl/ model has been found to be a strong predictor of molar pro- doi:10.1073/pnas.2008850118/-/DCSupplemental. portions across many mammalian clades (2, 4–9). It has also Published December 28, 2020. PNAS 2021 Vol. 118 No. 1 e2008850118 https://doi.org/10.1073/pnas.2008850118 | 1of5 Downloaded by guest on September 26, 2021 that primates of differing diets show contrasts in the pattern of Results dental morphology across the molar row, with complexity either Analysis of 40 extant euarchontan lower molar toothrows increasing or decreasing moving distally (9), but this pattern has (M1–M3, n = 120) shows that molar complexity conforms to the not previously been examined using the ICM. In taxa where predictions of the ICM (see SI Appendix, Table S3 for raw data). higher occlusal complexity in the molar row helps in the break- For the full sample (Euarchonta), there is a linear increase in down of mechanically challenging foods, such as in folivores, we mean complexity moving distally along the molars (ordinary least predict that these taxa will experience lower levels of inhibition/ squares [OLS] regression R2 = 0.9994). Reduced major axis re- higher levels of activation, which will lead to a linear increase in gression of M3/M1 complexity regressed against M2/M1 com- complexity moving distally from M1 to M3. In taxa where greater plexity is positive and significant (P = 0.00433, R2 = 0.34094), molar complexity does not provide as great a functional advan- and the predicted values of the ICM fall within the 95% CI for tage for comminuting food, as in frugivores, we predict that in- our model (Fig. 1 and Table 1). Although molar size does follow hibition will be higher and, therefore, the distal molars will be the predictions of the ICM as well (reduced major axis [RMA] relatively less complex than the mesial molars. regression P ≥ 0.0001, R2 = 0.66097), with the predicted values During the early, patterning period of occlusal development, of the ICM falling within the 95% CI for our model (Fig. 1 and nonmitotic signaling centers present in the tooth germ, known as SI Appendix, Fig. S1 and Table 1), the relationship between enamel knots, influence the formation of the developing dental molar size is not as strongly linear as in the case of molar complexity epithelium by releasing proteins that inhibit or activate cellular (OLS regression R2 = 0.6661), particularly in the case of the fru- development (1, 9, 21–23). In multicuspate teeth, the position, givores (OLS regression R2 = 0.5459) and folivores (OLS regression development, and eventual apoptosis of the primary enamel R2 = 0.4912). Regressions also suggest that there is no relationship knots triggers the formation of the secondary enamel knots, between molar surface area and complexity (M1 RMA regression which also act as signaling centers. The secondary enamel knots P = 0.091228, R2 = 0.13601; M2 P = 0.11669, R2 = 0.11851; M3 P = appear at the sites of future-forming cusps, meaning their loca- 0.14222, R2 = 0.10541), meaning complexity is independent from tion provides the first blueprint of species-specific cuspal pat- surface area (SI Appendix,Fig.S2). The M3 is the smallest tooth in terning (24, 25).