Dental characters used in phylogenetic analyses of mammals show higher rates of evolution, but not reduced independence

Introduction

Accurate reconstructions of phylogenetic relationships are essential for studying the evolutionary history of a clade, with hypotheses being based on molecular or morphological data, or both. While it is comparatively straightforward to observe patterns of evolution in molecular sequence data and therefore develop models more closely representing the evolutionary processes, this is more difficult in the case of morphological characteristics due to a poorer understanding of how novel morphology is evolved from ancestral traits. Nonetheless, morphological data are our only means of reconstructing the phylogenetic relationships of fossil organisms that are too old to preserve DNA or usable proteins. It is therefore imperative that we strive to better understand the evolutionary modes of morphological traits. In recent years many studies have examined how variation in evolutionary patterns of discrete morphological traits, not accounted for by current analyses, may be affecting phylogenetic inferences (e.g., O’Keefe & Wagner, 2001; Scotland, Olmstead & Bennett, 2003; DeGusta, 2004; Sansom, Wills & Williams, 2017; Billet & Bardin, 2018).

The high percentage of dental characters used in the reconstruction of fossil mammal phylogenies has become a particular cause for concern. Numerous studies have highlighted issues such as the non-independent evolution of dental characters (Kangas et al., 2004; Kavanagh, Evans & Jernvall, 2007; Harjunmaa et al., 2014; Dávalos et al., 2014; Billet & Bardin, 2018) and increased convergence relative to other character partitions due to ecological selective pressures (Evans et al., 2007; Kavanagh, Evans & Jernvall, 2007). In a recent meta-analysis, Sansom, Wills & Williams (2017) examined the phylogenetic signal of tooth and osteological character partitions, using phylogenies derived from molecular data as a benchmark. This study found that osteological characters were more consistent with the molecularly-derived phylogenies and contained greater phylogenetic signal than dental characters. Further, parsimony analyses with only dental characters produced results less similar to the molecularly-derived phylogenies than analyses where the same number of characters were selected at random from both partitions (Sansom, Wills & Williams, 2017).

This paper builds on the work of Sansom, Wills & Williams (2017) in two principal ways. Sansom, Wills & Williams (2017) employed two partitions, dental and osteological, to assess the performance of dental characters relative to osteological characters in phylogenetic analyses. As such, while dental characters have been demonstrated to be problematic, an understanding of whether this problem was limited to them, or whether it extends to other partitions, is lacking. We therefore examine phylogenetic signal in six morphological partitions in mammals in order to establish whether any other skeletal regions may be a poor indicator of phylogeny.

Secondly, we also aim to understand why dental characters may be producing phylogenies less congruent with molecularly-derived benchmarks. Many studies have established that morphological characters frequently violate at least some of the principal assumptions of parsimony (see below): between-character rate homogeneity (all characters being just as likely to transition), within-character rate homogeneity (all character states within the same character being similarly likely to transition), and character independence. We test each morphological character partition for variation in these parameters.

In most published phylogenetic analyses performed using parsimony, the characters are weighted equally (Kälersjö, Albert & Farris, 1999; Kluge, 2005; Goloboff et al., 2008). Under such a scheme, a change in any character is given equal influence in determining tree length. However, such a scheme only produces robustly supported results when the characters are all equally likely to change. If, however, there is variation in the rates of character evolution, certain characters will change more frequently and are more likely to show homoplasy (Felsenstein, 1981; Goloboff, 1993). While parsimony analysis does not incorporate an explicit evolutionary model, an equal weights analysis does rely on equal between-character rates for its accuracy.

Furthermore, in most published phylogenetic analyses, transitions between different combinations of character states are given equal weight (i.e., a transition from state 0 to state 1 is just as likely as a transition from state 1 to state 0; an assumption of within-character rate homogeneity). This assumption may be relaxed by incorporating step matrices which give greater weight to particular transitions (Sankoff & Cedergren, 1983), or by ordering (Fitch, 1971), an extreme modification of step matrices, setting the possibility of non-adjacent transitions to 0. However, step matrices are rarely employed, and the use of ordered characters is still heavily debated (see Marjanović & Laurin, 2019 for summary of their history), so most analyses assume equality of within-character rates.

Finally, all methods of phylogenetic analysis (parsimony, Bayesian, and likelihood), treat all characters as independent of one another (i.e., an assumption that a change in one character will have no effect on the transition probability in another character). Extensive study has shown this assumption of independence to be frequently violated (e.g., Kangas et al., 2004; Kavanagh, Evans & Jernvall, 2007; Harjunmaa et al., 2014; Dávalos et al., 2014; Billet & Bardin, 2018), with many traits or regions forming integrated modules that change as a unit (Goswami, 2006; Goswami, 2007; Goswami & Polly, 2010).

By analysing phylogenetic signal, between- and within-character rates, and character independence across six morphological partitions, within mammals as a whole and within four mammalian subclades, we aim to better understand how morphological characters can be selected and formulated during phylogenetic analyses of mammals. The results should provide future studies that intend to reconstruct the relationships of fossil mammals with a framework to enable more evidence-based decisions about which characters are more reliable for use in phylogenetic analyses.

Materials and Methods

Results

Results from mammalian subclade datasets

The artiodactyl datasets produced similar results to those of mammals overall, albeit with considerably more variation in phylogenetic signal from the vertebral, forelimb and soft tissue characters (Fig. 2A). The dental characters are the only partition where the GLS analysis found phylogenetic signal to be significantly reduced relative to other partitions (Table S1). Rates of dental evolution are again significantly higher than for other partitions (Fig. 2D, Table S4). There is no significant difference found between the Akaike weights support for the ER model of evolution in teeth (Table S2), nor the support for the independent model of character evolution, compared to other partitions (Table S3). The skull partition shows better support for the independent model, while the forelimb shows statistically significantly reduced independence.

The carnivoran dataset also found dental characters to have significantly lower phylogenetic signal than other partitions (Fig. 3A, Table S7). In this clade the dental character partition also has higher rates than all other partitions except the forelimb (for which there is only one character) (Fig. 3D).

The primate and marsupial datasets produced results conflicting with the other two subclades and mammals as a whole (Figs. 4 and 5). The dental partition in primates has significantly higher phylogenetic signal and significantly lower rates of evolution than other partitions (Fig. 4, Tables S9, S12). The dental partition also has significantly better support for the equal rates model of evolution than other partitions. However, primate characters suffer from being highly integrated: all partitions other than the vertebrae and soft tissue characters show a significantly low fit to the independent model of evolution (Fig. 4C, Table S11).

Table 1:

Results of GLS analyses of Pagel’s λ (phylogenetic signal of character partitions) in mammals.

Rows coloured are those where the partition best fits the H1 model (partition has a different lambda value to all others); blue indicates lower phylogenetic signal, red indicates higher phylogenetic signal.

Partition	Median λ	GLS Coefficient	lnL (null)	lnL (H1)	AIC (null)	AIC (H1)	Akaike weights (null)	Akaike weights (H1)
Teeth	1	−0.15	−103.02	−102.6	210.0	211.1	0.63	0.37
Skull	1	−0.11	−103.02	−101.4	210.0	208.8	0.35	0.65
Vertebrae	1	0.15	−103.02	−103.5	210.0	212.9	0.81	0.19
Forelimb	1	0.16	−103.02	−101.3	210.0	208.5	0.32	0.68
Hindlimb	1	0.07	−103.02	−103.8	210.0	213.6	0.86	0.14
Soft tissue	1	0.15	−103.02	−103.4	210.0	2129	0.81	0.19

DOI: 10.7717/peerj.8744/table-1

Table 2:

Results of GLS analyses of Akaike weight support for the equal rates (ER) model of character evolution in mammals.

Partition	Median weight	GLS Coefficient	lnL (null)	lnL (H1)	AIC (null)	AIC (H1)	Akaike weights (null)	Akaike weights (H1)
Teeth	0.78	0.02	26.77	24.75	−49.55	−43.50	0.95	0.05
Skull	0.71	0.02	26.77	24.45	−49.55	−42.89	0.97	0.03
Vertebrae	0.62	−0.13	26.77	26.60	−49.55	−47.19	0.76	0.24
Forelimb	0.62	−0.09	26.77	26.91	−49.55	−47.82	0.70	0.30
Hindlimb	0.72	0.04	26.77	24.85	−49.55	−43.70	0.95	0.05
Soft tissue	0.67	0.05	26.77	25.69	−49.55	−45.38	0.89	0.11

DOI: 10.7717/peerj.8744/table-2

Table 3:

Results of GLS analyses of Akaike weight support for the independent model of character evolution in mammals.

Rows coloured are those where the partition best fits the H1 model (partition has a different rate value to all others); blue indicates lower Akaike weights, red indicates higher.

Partition	Median weight	GLS Coefficient	lnL (null)	lnL (H1)	AIC (null)	AIC (H1)	Akaike weights (H0)	Akaike weights (H1)
Teeth	0.69	0.012	1,043.0	1,040.5	−2,082	−2,075	0.97	0.10
Skull	0.73	0.013	1,043.0	1,040.8	−2,082	−2,076	0.76	0.22
Vertebrae	0.50	−0.034	1,043.0	1,041.1	−2,082	−2,076	0.95	0.04
Forelimb	0.57	−0.077	1,043.0	1,073.1	−2,082	−2,140	∼0	∼1
Hindlimb	0.75	0.039	1,043.0	1,050.7	−2,082	−2,095	0.001	0.999
Soft tissue	0.76	0.100	1,043.0	1,042.4	−2,082	−2,079	0.83	0.16

DOI: 10.7717/peerj.8744/table-3

Table 4:

Results of GLS analyses of rates of character evolution in mammals.

Rows coloured are those where the partition best fits the H1 model (partition has a different rate value to all others); red indicates higher rate.

Partition	Median rate	GLS Coefficient	lnL (null)	lnL (H1)	AIC (null)	AIC (H1)	Akaike weights (null)	Akaike weights (H1)
Teeth	0.0016	0.29	−53.01	−43.63	110.03	93.27	0.0002	0.99
Skull	0.0010	0.02	−53.01	−55.19	110.03	116.38	0.96	0.04
Vertebrae	0.0006	−0.20	−53.01	−52.59	110.03	111.19	0.64	0.36
Forelimb	0.0006	−0.08	−53.01	−53.76	110.03	113.52	0.85	0.15
Hindlimb	0.0007	−0.07	−53.01	−53.85	110.03	113.70	0.96	0.04
Soft tissue	0.0006	−0.21	−53.01	−53.12	110.03	112.24	0.75	0.25

DOI: 10.7717/peerj.8744/table-4

In marsupials, while many of the character partitions, including dentition, show a wide range of Pagel’s lambda values, the lambda values of the tooth characters are more concentrated towards higher values compared other partitions (Fig. 5A). The tooth characters show no significant difference in their phylogenetic signal relative to other partitions (Table S13). The dental characters show no significant difference from any other partitions in support for the ER model of evolution (Table S14), and no significant difference in rates (Fig. 5D). In contrast to the other datasets, however, the marsupial dataset does support increased character non-independence of dental characters relative to other partitions, with median Akaike weights support for the independent model of evolution lower than all other partitions (Fig. 5C; Table S15).

Discussion

Mammalian tooth characters have been a source of much discussion over the last two decades, due in part to their dominance of the character lists used in morphological phylogenetic analyses of mammals, itself to an extent a product of their dominance in the mammalian fossil record. Teeth have been shown to suffer from issues such as large amounts of homoplasy (Evans et al., 2007; Dávalos et al., 2014) and non-independence (Kangas et al., 2004; Harjunmaa et al., 2014). While these issues clearly do impact on the utility of dental characters in phylogenetic analysis, what has received less attention is whether dental characters are in fact worse affected than other body partitions in these regards. The majority of studies cited above focus solely on teeth, but issues of homoplasy due to ecological and functional constraints might be expected to affect other character partitions (e.g., limb characters being functionally linked to locomotion). Indeed, ecological constraint and developmental linkage has been demonstrated in cranial and limb characters across various tetrapod groups, including mammals (Ruvinsky & Gibson-Brown, 2000; Young & Hallgrímson, 2005; Sadleir & Makovicky, 2008). The same argument could be made for the issue of character non-independence: while this has been demonstrated to be a problem with mammal dentition, recent work on modularity and integration highlights that this issue might just as strongly impact on non-dental characters (Goswami, 2006; Goswami, 2007; Goswami & Polly, 2010).

Our analyses suggest that increased homoplasy driven by increased rates of evolution may affect dental characters to a greater extent than other partitions. Dental characters from the total Mammalia dataset and the artiodactyl and carnivoran datasets are found to evolve at faster rates than the other character partitions, and so are more likely to transition multiple times. The strong and significant inverse correlations between phylogenetic signal and rates of evolution in all tested datasets indicates that rate variation is likely to be the main driving force behind loss of phylogenetic signal, more so than within-character rate heterogeneity. However, this signal is not consistent across all the tested clades. In the marsupial and primate datasets, dental characters have lower rates (and higher phylogenetic signal) than most other partitions.

Moreover, while the results obtained here seem to suggest that dental characters have lower phylogenetic signal than some other characters when optimised over a molecular-based phylogeny, they are not alone in this respect. The total Mammalia dataset indicates that cranial characters also have low phylogenetic signal. In both primates and marsupials, the soft tissue characters have lower Pagel’s lambda values than any other partition (Figs. 4A, 5A) and in carnivorans both limb partitions perform poorly in this respect (Fig. 3A).

The results observed in artiodactyls raise a possibility that might warrant future study: the increase in rates of dental evolution observed might be due to the dominance of herbivores in this dataset. Herbivory has been suggested to be a driver of dental disparity in mammals (Jernvall, Hunter & Fortelius, 1996; Jernvall, Hunter & Fortelius, 2000) as their morphology tracks a constantly changing resource (plants). Since the functional requirements of eating meat has not changed over time, carnivorous mammals show reduced dental disparity and less evolutionary change (Van Valkenburgh, 1988; Wesley-Hunt, 2005). In an analysis of diversification patterns across all mammals, herbivores showed significantly higher diversification rates than carnivores or omnivores (Price et al., 2012). While this analysis focussed on lineage diversification, the authors cited increased specialisation and niche-subdivision as a potential driving force behind diversification patterns, and morphological diversification patterns should respond to these drivers in the same way.

It is finally worth noting that in the total-Mammalia dataset and two of the three placental subclades tested, there is little evidence that tooth characters are affected by non-independence to any greater extent than the other morphological partitions. The primate and marsupial datasets are the exception, with dental characters showing a weaker fit to the independent model than all other partitions. The integration of the dental characters and their low rates of evolution in marsupials may be due to their unusual development: neonatal marsupials, born extremely early in their development need to attach to the teat, leading to precocial development of the jaw and facial region in marsupials (Smith, 1996; Smith, 2006). This could lead to this region evolving as a more integrated module. Alternatively, it may be a result of character selection: the Beck (2017) dataset contains large numbers of characters relating to the presence or absence of particular dental loci in both upper and lower jaws, likely to be heavily integrated.

Conclusions

The concept pioneered by Sansom, Wills & Williams (2017), of testing morphological discrete characters over a molecular benchmark, is a powerful tool, and it would be highly recommended that researchers studying clades where molecularly-derived phylogenies exist examine the performance of their characters in this manner. But given the extremely wide variation in results found by this study, where different partitions produced different relative phylogenetic signals (with the primates and marsupials in particular producing results conflicting strongly with the other datasets studied), one should perhaps be cautious of basing assumptions of character quality on the results of large meta-analyses. While the latter are useful for identifying broad-scale patterns, it is necessary that each dataset be examined individually, and decisions made based on the macroevolutionary patterns observed in that clade. However, larger-scale meta-analyses do have the advantage in that they are less likely to be affected by idiosyncrasies of individual datasets and the choices/intentions of the researchers. For example, the total-Mammalia dataset includes only three soft-tissue characters relating to the different modes of reproduction, likely intended to separate monotremes, marsupials and placentals, and therefore this is not representative of the total variation in soft tissue evolution. A detailed examination of specific characters and how variation in their formulation affects the results would be an avenue for future research.

A fair and comprehensive sampling of characters across partitions should be the aim; experiments incorporating random sampling of characters show that sampling across partitions leads to a more reliable estimation of phylogenetic relationships than sampling within single partitions (Pattinson et al., 2015). While dental characters have been shown to suffer from issues of homology and non-independence (Kangas et al., 2004; Evans et al., 2007; Harjunmaa et al., 2014), the comparison of the dental characters to finer partitions of data presented here demonstrates that these issues are not unique to teeth. In fact, in some cases other regions perform even worse, and the nature of these issues varies from clade to clade.

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