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Could homoplasy occur within a clade?


Consider the below phylogeny. taxon1 and 2 are sister taxa but: - share a brown color coat - differ from their closest common ancestor (light color coat)

Is this a case of homoplasy (Analogous trait)?


Could homoplasy occur within a clade?

Note that the all of life is a clade! A clade is any mono-phyletic tree. So any homoplasy observed on earth is necessarily within a clade!

Let's replace the term clade by species to further the discussion

Could homoplasy occur within a species?

Wether you consider two lineages as being part of the same species or not changes nothing to the question of whether their shared trait was already present in the common ancestor or not. You can have homoplasy within a species and even within a population. Of course, the lower level you go, the less likely it is to observe a clear case of homoplasy.

It is important not to view a clade (incl. species and subspecies) as something too atomic. As a whole and single clearly defined entity but rather a whole complex tree (or network) of lineages. Any lineage may have evolved a trait that has already evolved independently in another lineage whether the two lineages are very closely related (within the same subspecies) or very distantly related. In this regard, you might want to have a look at this post.

So, yes you can observe homoplasy when comparing lineages within a clade.


According to Furtado and Pessoa (2014):

Homology: A similarity due to common ancestry.

Homoplasy: A similarity not due to common ancestry.

And, according to Futuyma (2006):

Homology: Possession by two or more species of a character state derived, with or without modification, from their common ancestor.

Homoplasy: Possession by two or more species of similar or identical character state that has not been derived by both species from their common ancestor

Therefore, the answer is quite clear: the trait here is an homoplasy, since it's not present in the common ancestor of A and B.

PS: Homoplasy and analogy are not, technically speaking, synonyms. Analogy is a special case of homoplasy.

PPS: A clade is just a monophyletic group. For instance, the hominids form a clade, Mammalia is also a clade, Vertebrata is a clade, even Animalia is a clade. Therefore, a clade can be very exclusive or very inclusive. Because of that, I'm skipping the title of the question ("Could homoplasy occur within a clade?"), whose answer is obviously yes1, and focusing only on your second question: "Is this [image] a case of homoplasy?"

PPPS: Furtado is me, and that quote was translated from the original.

Sources:

  • Furtado, G. and Pessoa, F. (2014). Liçoes sobre sete conceitos fundamentais da biologia evolutiva. Brasília: Editora UnB. (translation: On seven fundamental concepts of evolutionary biology)
  • Futuyma, D. (2006). Evolutionary biology. New York: W.H. Freeman.

1For instance, my metamery and the metamery of an earthworm is an example of homoplasy. Both myself and the earthworm belong to a clade called Animalia. Therefore, there is homoplasy within a clade


HOMOLOGY AND HOMOPLASY

Homology and analogy both refers to similar parts (features) of organisms. Homology at the level of the phenotype (phenotypic or structural homology) is the continuous occurrence of the same feature (be it gene, gene network, cell type, tissue, organ, structure, or behavior) in two organisms whose common ancestor possessed the feature. Homologous features need not be identical but must share sufficient “similarity” to be recognizable as homologous. Homology is similarity that reflects common descent and ancestry. Another way of comparing and classifying features among organisms is homoplasy. Homoplasy is similarity (some might say superficial similarity) arrived at via independent evolution. Homology may or may not imply conserved development. Homoplasy implies divergent development. Consequently, divergence in developmental pathways is not an adequate criterion to establish features as homoplastic. Homoplastic features (independent evolution) can share an affiliation (shared developmental processes) with homologous features. The common basis for considering features as homoplastic is their independent evolution one from the other. However, homoplasy is a portmanteau term for classes of similarity otherwise subsumed under terms such as convergence, parallelisms, reversals, rudiments, vestiges, and atavisms.


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Results

Animal phylogeny under the RGC_CAM approach

The animal phylogeny adopted in this study is shown in Figure 1. The branch lengths were estimated in RGC_CAM units. In agreement with previous findings [18], it was found that the three available nematode gene sets comprise a fast-evolving lineage (Figure 1) which would often lead to errors when conventional phylogenetic methods are applied [5, 19, 20]. Mammals represent the most slowly evolving clade but the deuterostome clade shows high variability of evolutionary rates owing to the fast evolving sea urchin and Ciona lineages (Figure 1). Insects have slower evolutionary rates compared to nematodes, and the insect and nematode clades show relatively little variation of evolutionary rates (Figure 1).

Animal phylogeny adopted in this study. The numbers at branches indicated the number of RGC_CAMs which is the measure of branch length. L1 and L2 are internal branch lengths. L3 is the terminal branch length. Tc is the known divergence time for two closely related species (calibration time for L3). Te is the estimated time of the worms-insects-vertebrates divergence. Reversals are shown in red and parallel changes are shown in blue. Io indicates the insect internal "old" branch and In indicates the insect internal "new" branch (see text). Species abbreviations: Homo sapiens (Hs), Caenorhabditis elegans(Ce), Drosophila melanogaster (Dm), Saccharomyces cerevisiae (Sc), Schizosaccharomyces pombe (Sp), Arabidopsis thaliana (At), Anopheles gambiae (Ag), Plasmodium falciparum (Pf), Caenorhabditis briggsae (Cb), and Mus musculus (Mm), Brugia malayi (Bm), Aedes aegypti (Aa), Ciona intestinalis (Ci), Apis mellifera (Am), Cryptococcus neoformans (Cn), Dictyostelium discoideum (Dd), Nematostella vectensis (Nv), Strongylocentrotus purpuratus (St), and Trichoplax adhaerens (Ta)

As shown previously, the RGC_CAM approach supported the coelomate clade that unites deuterostomes with arthropods as opposed to the ecdysozoan (molting animals) clade that encompasses arthropods and nematodes [14, 21]. This conclusion is compatible with the results of some of the previous genome-wide phylogenetic analyses [22–26] whereas other such analyses claim support for ecdysozoa [27–29]. Moreover, the ecdysozoan topology is currently favored in the evo-devo community, on the basis of the apparently all-important shared feature, namely, molting [30, 31]. Interestingly, a subsequent re-analysis of RGC_CAMs, with the sequences from the sea anemone Nematostella vectensis included in the set of outgroup species, claimed support for Ecdysozoa [32].

We further explored the support for different topologies from RGC_CAM analysis by performing taxon sampling on the outgroup species set. All combinations of 12 to 19 species, i.e., including from one to 8 outgroup species (255 samples altogether), were analyzed (see Additional File 1). For 85 combinations of species, the raw number of RGC_CAMs compatible with the coelomate topology was greater than the number of RGC_CAMs compatible with the ecdysozoa topology, whereas the reverse was true of 88 combinations, with the remaining 82 combinations showing the same number of RGC_CAMs for both topologies (Additional file 1). The number of RGC_CAMs in favor of the "bizarre" topology (grouping of mammals with nematodes to the exclusion of insects) was markedly smaller (Figure 2 and Additional file 1). Thus, when raw numbers are considered, the levels of support for the coelomate topology and the ecdysozoan topology are nearly the same. However, as shown previously, when the branch lengths are taken into account, the support for the coelomate clade becomes substantially greater than that for ecdysozoa [21].

Distribution of the numbers of RGC_CAMs supporting each of the three compared phylogenetic hypotheses in 255 sampling experiments C = Coelomata, E = Ecdysozoa, and B = 'bizarre' topology (grouping of deuterosomes with nematodes to the exclusion of insects).

Nevertheless, the two conflicting signals remain. The simplest explanation for this conflict is homoplasy, and indeed, it has been shown that, although the RGC_CAM approach is designed to minimize this effect, it is not homoplasy-free [14, 21]. In the following two sections, we directly assess the level of homoplasy among RGC_CAMs.

Homoplasy: parallel changes

There are two types of evolutionary events that would lead to homoplasy in the RGC_CAM analysis, namely, parallel changes and reversals (Figure 1) [14, 21, 32]. The RGC_CAM approach provides for the possibility to estimate the level of homoplasy directly. To obtain an estimate of the number of parallel changes, we employed the scheme shown in Figure 3. We required that the same amino acid is shared by two or three pairs of closely related species (e.g. two mosquitoes and two Caenorhabditis species) (Figure 3) under the condition that the pair (or triple) of species must have a closely related outgroup which contains the ancestral amino acid. In this case, two parallel changes is the most parsimonious explanation for the observed pattern because all other scenarios require at least three events (Figure 3). All combinations of 12 to 19 species, i.e., including from one to 8 outgroup species (255 samples altogether), were analyzed (Additional File 1). For both insects and deuterostomes, we analyzed two internal branches, one of which was closer to the root ("old") and the other one was closer to the leaves ("new") (Figure 1). Parallel changes in these branches were identified by performing taxon sampling of the outgroup species (Additional File 1). Taxon sampling was necessary because both the number of RGC_CAMs supporting a given topology and the number of observed parallel changes critically depend on the composition of the outgroup. When all 8 or any combination of 7 outgroup species are included, there are no RGC_CAMs in the deuterostome branch, the insect branch becomes very short as well, and only one or two parallel changes are seen (Additional File 1). In contrast, for many combinations of smaller numbers of outgroup species, several parallel changes between nematodes (N) and insects, particularly, in the "old" internal branches (Io) were detected (Figure 4 and Additional File 1). The insect "old" branch Io is only slightly longer than the "new" branch In (8 RGC_CAMs and 6 RGC_CAMs, respectively Figure 1), so the substantial excess of parallel changes in the "old" branch was unexpected. The same pattern was seen between the "old" and "new" insect branches and the "new" deuterostome branch, with a much greater number of parallel changes occurring in the "old" insect branch (Figure 5 and Additional File 1). Thus, the rate of parallel changes is not uniform, with deeper, more ancient branches being more prone to parallel changes.

Identification of parallel changes X->Y. The tree is the same as in Figure 1 except that the some of the outgroups were collapsed and species names are not indicated for simplicity.

Distribution of parallel changes between nematodes and deuterostomes in 255 sampling experiments. The branches of the tree are designated: N, nematodes, Io, Insect "old", In, Insect "new", Do, deuterostome "old", Dn, Deuterostome "new" (see text for details).

Distribution of parallel changes between insects and deuterostomes in 255 sampling experiments. The designations of the tree branches are the same as in Figure 4.

We further employed a relaxed scheme for parallel change detection where these changes were detected between terminal branches (species) rather than between internal branches as in the analyses described above. Specifically, the branches leading to the two Caenorhabditis species and those leading to the two mosquito species were compared. The Caenorhabditis terminal branches are approximately three times shorter than the internal nematode branch, whereas the terminal mosquito branches are approximately twice as long as the "new" internal insect branch (Figure 1). Accordingly, one would expect to observe a number of parallel changes close to that in the N_In comparison (Figure 4). However, we detected no parallel changes in any of the 4 comparisons. This result is unlikely to be due to short branch lengths because parallel changes were readily detected for much shorter "old" internal branches, e.g., in the Io_Do comparison (Figure 5). The absence of parallel changes in the terminal branches is consistent with the excess of parallel changes in deep branches of phylogenetic trees described above.

To determine the statistical significance of this trend, we used the following simplified scheme. The number of unique parallel changes in selected branch pairs was tallied from the 255 sampling experiments (all repeated parallel changes were removed from this analysis, thus the resulting number was the union of parallel changes detected in individual experiments). Specifically, the N_Io, N_In, N_Ag, and N_Aa comparisons were analyzed. For N_Io, 6 unique parallel changes were detected, whereas the other three comparisons taken together yielded 3 unique parallel changes (Table 1). The internal nematode branch N is the same for all comparisons, thus the frequency of parallel changes depends on the length of the insect branches only. The ratio of the length of the Io branch to the total length of all involved branches is

0.2 (Table 1). The probability to observe 6 of the total of 9 detected parallel changes in this relatively short branch is 0.003 under the binomial test.

Although the observed excess of parallel changes in internal branches gained unequivocal statistical support, the raw numbers of parallel changes were small. To increase the resolution of the analysis of parallel changes, we relaxed the definition of RGC by allowing all possible amino acid replacements (as opposed to only those that require two or three nucleotide substations in RGC_CAMs). We denote these characters RGC_CAs. Such relaxation of the original RGC definition is expected to result in a dramatic increase of homoplasy. Thus, much larger raw numbers could be obtained for the analysis of parallel changes although alternative explanations involving combinations of more than two parallel changes and/or reversals simultaneously become more likely. Although numerically the excess of parallel changes in deep branches was less dramatic than in the RGC_CAM comparison, the statistical support for this trend was even stronger (P < 10 -7 ) owing to the large number of observations (Table 1). The same trend was found for the other, shorter internal branches, such as D oand D nwhen parallel changes were measured in RGC_CAs (in this case, the lengths of the branches differed greatly, so the effect was not obvious from the comparison of the raw numbers but became apparent after normalization over branch length Table 1).

The estimates of the parallel changes presented here could not be directly factored into the RGC_CAM analysis of the Coelomate-Ecdysozoan problem because the informative RGC_CAMs for addressing this problem and the events leading to homoplasy were located on different branches of the phylogenetic tree (Figures 1, 3, and 6). Extrapolation of the estimated parallel changes for the branches leading to the analyzed trifurcation is complicated by the observed increase in the number of parallel changes from the leaves of the tree toward the analyzed trifurcation. Nevertheless, we attempted a crude estimation using the simplest, linear model of the increase in parallel changes depending on the depth of the tree. Specifically, the number of parallel changes between the branches leading from the trifurcation to insects and nematodes was estimated as:

Identification of reversals X->Y and Y->X. The tree is the same as in Figure 1 except that the some of the outgroups were collapsed and species names are not indicated for simplicity.

P e= P N_Io(N t/N) (I t/I o)C 2

where Pe is the estimated number of parallel changes, P N_Iois the observed number of parallel changes between the insect "old" branch and the internal nematode branch, (N t/N) is the ratio of the lengths of nematodes-to-trifurcation branch and the internal nematode branch, (I t/I o) is the analogous ratio for insects, and C is the coefficient of linear increase in the number of parallel changes from the leaves of the tree toward the analyzed trifurcation and calculated as the ratio of the numbers of parallel changes between the internal nematode branch and the "old" and "new" insect branches, i.e., C = P N_Io/P N_In. In order to obtain more reliable estimates, the N_Io vs. N_In were taken from the RGC_CA data (Table 1): C = 45/22

2. The P evalues were obtained for each of the 255 sampling experiments (Additional file 1) and were compared to the number of characters supporting Ecdysozoa (Figure 2). The two series of values have close mean values (2.96 for P eand 3.46 for the number of RGC_CAMs supporting ecdysozoa) although the difference is statistically significant (P = 0.02) by Student's t-test). Although these estimates are based on simplistic assumptions and should be interpreted with extreme caution, they suggest that the non-negligible support of the Ecdysozoa clade could be, largely, explained by parallel changes, owing, primarily, to the long nematode branch. Analogous estimates for the insect-deuterostome comparison yielded extremely small numbers (0 in most of the sampling experiments) owing to the short deuterostome branch (data not shown) compared to the number of RGC_CAMs supporting the coelomate clade (Figure 2). Thus, parallel changes hardly can explain a substantial fraction of the RGC_CAMs supporting the coelomate clade.

Homoplasy: reversals

Reversals comprise the second potential source of homoplasy (Figure 1). To obtain an estimate of the number of reversals, we employed the scheme shown in Figure 6. We required the same amino acid to be shared by a pair of closely related species (e.g. human-mouse) and the outgroup species (fungi, plant, protist, Nematostella vectensis, and Trichoplax adhaerens) but not the rest of the animals (Figure 6). In this case, a reversal in an internal branch is the most parsimonious scenario, assuming that the tree topology in the node leading to vertebrates, insects and nematodes is a true trifurcation. If this is not the case, two parallel changes also might explain the observed pattern for the "old" branches, one in the internal branch leading to the Coelomata (or Ecdysozoa) clade and the other in a terminal branch on the other side of the tree. Thus, the obtained estimates comprise the upper bound of the number of reversals in the case of the "old" internal branches (including the nematode internal branch). For a "new" internal branch, a reversal is the unequivocal most parsimonious scenario. All combinations of 12 to 19 species, i.e., including from one to eight outgroup species (255 samples altogether), were analyzed (Additional file 1).

A substantial number of reversals were detected in the internal nematode branch (Figure 7) although the number of reversals was significantly (Student's t-test, P < 10 -6 ) smaller than the number of RGC_CAMs supporting the coelomate clade (Additional File 1). Reversals have been invoked by Irimia et al. [32] to explain (away) the observed RGC_CAM support for the coelomate clade. However, the results presented here along with those in a previous study that was performed on a different set of species [21] show that the number of reversals is insufficient to account for this support.

Distribution of reversals on the internal nematode branch in 255 sampling experiments.

Analysis of reversals in insects and deuterostomes revealed a pattern similar to that observed for parallel changes, i.e., the total number of reversals in the "old" internal branch was greater than the number of reversals in the "new" branch (Figures 1, 8 and 9). However, the difference was small and, in the case of insects, potentially could be attributed to the length difference between the "old" and "new" branches (Figure 1). To test the hypothesis that reversals are more prevalent in deep branches, we employed a scheme where only one Caenorhabditis species or one mosquito species shared an RGC_CAM with the outgroup species and other animals. This resulted in a smaller number of probable reversals compared to the internal branches (results not shown), however the pattern was not as obvious as that with parallel changes where none were seen in the terminal branches (see above).

Distribution of reversals on the internal insect branches in 255 sampling experiments. The branch designations are as in Figure 4.

Distribution of reversals on the internal Deuterostome branches in 255 sampling experiments. The branch designations are as in Figure 4.

To determine the statistical significance of the apparent excess of reversal in deep branches, we used the same approach as described above for parallel changes. The number of unique reversals in selected branches was calculated from the 255 sampling experiments (all repeated reversals were removed from this analysis, thus the resulting number was the union of the reversals detected in individual experiments) (Table 2). For this test, we chose the insect clade because the bizarre hypothesis never gained any substantial support in any experimental settings (Figure 2 and [22–29]) and is generally not considered a plausible evolutionary scenario [30, 31]. Thus two parallel changes as an alternative to a reversal can be effectively ruled out. Substantial numbers of reversals were detected in all analyzed insect branches (Table 2). The differences between branches were not significant (results not shown). However, the raw numbers were small (Table 2) which could hamper the statistical analysis. In order to increase the resolution, we again turned to RGC_CAs (see above) which yielded greater raw numbers of reversals (Table 2). In this RGC_CA analysis, a relatively small but statistically significant (P < 10 -9 ) excess of reversals in the "old" branch was observed (Table 2). Thus, reversals seem to show the same, albeit much weaker, evolutionary trend as parallel changes (compare the results in Table 1 and 2).

For RGC_CAMs, we assumed that the conserved amino acid in the outgroup species represents the ancestral state. However, two parallel changes (Y->X in the branch leading to the outgroup species and in the analyzed internal branch) also could explain the pattern in Figure 6, and this effect might be especially important when the number of outgroup species is small. To assess the effect of such parallel changes, we required that the outgroup set included, at least, 2 or 3 species. The results were not significantly different from those obtained with the unrestricted taxon sampling (Table 2), suggesting that the absence of dramatic differences between the "old" and "new" branches is a reliable result that does not depend on the number of outgroup species.

As discussed above, a substantial number of reversals were detected in the internal nematode branch (Figure 7) in principle, these reversals might explain (part of) the observed RGC_CAM support for the coelomate clade. We applied the adjustment procedure described in the preceding section to the reversals in the nematode branch. As expected, the estimated number of reversals on the trifurcation-nematode branch was greater than the observed number of reversals on the internal nematode branch (Figure 7). However, the difference, in this case, was relatively minor (a

1.3-fold increase, on average), and estimated number of reversals was still significantly smaller than the number of RGC_CAMs supporting the coelomate clade (the mean number of reversals was 2.07, and the mean number of supporting RGC_CAMs was 5.54, P < 10 -6 by Student's t-test).


In the Light of Evolution: Volume VI: Brain and Behavior (2013)

How neural circuit evolution relates to behavioral evolution is not well understood. Here the relationship between neural circuits and behavior is explored with respect to the swimming behaviors of the Nudipleura (Mollusca, Gastropoda, Opithobranchia). Nudipleura is a diverse monophyletic clade of sea slugs among which only a small percentage of species can swim. Swimming falls into a limited number of categories, the most prevalent of which are rhythmic left&ndashright body flexions (LR) and rhythmic dorsal&ndashventral body flexions (DV). The phylogenetic distribution of these behaviors suggests a high degree of homoplasy. The central pattern generator (CPG) underlying DV swimming has been well characterized in Tritonia diomedea and in Pleurobranchaea californica. The CPG for LR swimming has been elucidated in Melibe leonina and Dendronotus iris, which are more closely related. The CPGs for the categorically distinct DV and LR swimming behaviors consist of nonoverlapping sets of homologous identified neurons, whereas the categorically similar behaviors share some homologous identified neurons, although the exact composition of neurons and synapses in the neural circuits differ. The roles played by homologous identified neurons in categorically distinct behaviors differ. However, homologous identified neurons also play different roles even in the swim CPGs of the two LR swimming species.

* Department of Biology, New England College, Henniker, NH 03242 and &dagger Neuroscience Institute, Georgia State University, Atlanta, GA 30302. &Dagger To whom correspondence should be addressed. E-mail: [email protected]

Individual neurons can be multifunctional within a species. Some of those functions are shared across species, whereas others are not. The pattern of use and reuse of homologous neurons in various forms of swimming and other behaviors further demonstrates that the composition of neural circuits influences the evolution of behaviors.

B ehavior and neural mechanisms can be considered to represent two different levels of biological organization (Lauder, 1986, 1994 Striedter and Northcutt, 1991 Rendall and Di Fiore, 2007). Nevertheless, the evolution of behavior and the evolution of neural circuits underlying behavior are intertwined. For example, it has been suggested that the properties of neural circuits affect the evolvability of behavior) the evolution of particular behaviors could be constrained or promoted by the organization of neural circuits (Airey et al., 2000 Bendesky and Bargmann, 2011 Carlson et al., 2011 Katz, 2011 Yamamoto and Vernier, 2011). Darwin and the early ethologists recognized that behaviors, like anatomical features, are heritable characters that are amenable to a phylogenetic approach (Darwin, 1876 Whitman, 1899 Heinroth, 1911 Lorenz, 1981). The use of behavioral traits to determine phylogenies has been validated several times (Wenzel, 1992 De Queiroz and Wimberger, 1993 Proctor, 1996 Stuart et al., 2002), and the historical debates about homology and homoplasy of behavior have been thoroughly reviewed (Lauder, 1986, 1994 Wenzel, 1992 Foster et al., 1996 Proctor, 1996 Rendall and Di Fiore, 2007). Examining the neural bases for independently evolved (i.e., homoplastic) behaviors within a clade could provide insight into fundamental aspects of neural circuit organization. However, it is difficult enough to determine the neural basis for behavior in one species. Doing this in several species with quantifiable behaviors is even more challenging.

Studies of the neural bases of swimming behaviors in the Nudipleura (Mollusca, Gastropoda, Opisthobranchia) offer such a possibility. These sea slugs exhibit well differentiated categories of swimming behaviors, and their nervous systems have large individually identifiable neurons, allowing the neural circuitry underlying the swimming behaviors to be determined with cellular precision.

Here we will summarize what is known about the phylogeny of Nudipleura, their swimming behaviors, and the neural circuits underlying swimming. We will also provide data comparing the roles of homologous neurons. We find that neural circuits underlying the behaviors of the same category are composed of overlapping sets of neurons even if they most likely evolved independently. In contrast, neural circuits underlying categorically distinct behaviors use nonoverlapping sets of neurons. Furthermore,

homologous neurons can have different functions in different behaviors and even in similar behaviors.

PHYLOGENY OF NUDIPLEURA

The Nudipleura form a monophyletic clade within Opisthobranchia (Gastropoda) that contains two sister clades: Pleurobranchomorpha and Nudibranchia (Waegele and Willan, 2000 Wollscheid-Lengeling et al., 2001 Göbbeler and Klussmann-Kolb, 2010) (Fig. 9.1). Molecular evidence suggests that the two sister groups separated approximately 125 Mya (Göbbeler and Klussmann-Kolb, 2010). Nudibranchia (or, informally, nudibranchs), which are shell-less and have a slug-shaped appearance with &ldquonaked gills,&rdquo were traditionally classified as their own order. The most recently agreed-upon taxonomic classification system for nudibranchs uses unranked clades instead of orders, suborders, and superfamilies (Bouchet and Rocroi, 2005). There are at least 2,000 to 3,000 identified nudibranch species (Behrens, 2005). Studies that used morphological and molecular data support the monophyly of Nudibranchia (Waegele and Willan, 2000 Wollscheid-Lengeling et al., 2001 Vonnemann et al., 2005 Dinapoli and Klussmann-Kolb, 2010 Göbbeler and Klussmann-Kolb, 2010 Pola and Gosliner, 2010).

Within Nudibranchia, there are two monophyletic clades (Waegele and Willan, 2000): Euctenidiacea (Anthobranchia) (Thollesson, 1999 Valdes, 2003) and Cladobranchia (Pola and Gosliner, 2010). Euctenidiacea includes Doridacea, which is larger than Cladobranchia, subdividing into 25 families (Thollesson, 1999). Within Cladobranchia, Bornellidae forms a sister group to the other subclades (Pola and Gosliner, 2010). Aeolidida is a monophyletic clade with Lomanotidae as a sister group (Pola and Gosliner, 2010). What was traditionally called Dendronotida forms a paraphyletic grouping. A recent study was unable to include the nudibranch Melibe in Cladobranchia because of a 12-bp deletion in its genome (Pola and Gosliner, 2010). However, its natural affinity with Tethys in terms of shared derived characteristics strongly suggests that it belongs in Cladobranchia, as we have indicated in Fig. 9.1. There are several additional unresolved relations in Nudibranchia, most notably in Dendronotida and Doridacea. Consideration of locomotor behavior and neural circuits may help resolve these relations.

CATEGORIES OF LOCOMOTOR BEHAVIOR

Crawling is the primary form of locomotion for all Nudipleura (Audesirk, 1978 Audesirk et al., 1979 Chase, 2002). The majority of species crawl via mucociliary locomotion cilia on the bottom of the foot beat

and propel the animal over a surface of secreted mucus. The speed of crawling is affected by efferent serotonergic and peptidergic neurons that control the ciliary beat frequency (Audesirk, 1978 Audesirk et al., 1979 Willows et al., 1997). Some species also use muscular crawling, which relies on waves of contraction or extension and contraction of the foot. Crawling is a trait shared with most Opisthobranchia and is therefore plesiomorphic to the Nudipleura. Only three nudibranch species do not crawl because they are truly pelagic: Phylliroë atlantica, Phylliroë bucephala, and Cephalopyge trematoides (Lalli and Gilmer, 1989). This is also true for gastropods in general there are

40,000 marine gastropod species but only approximately 150 are pelagic (Lalli and Gilmer, 1989).

In addition to crawling, a limited number of benthic species can also swim (Farmer, 1970). We classify swimming in the Nudipleura into seven general categories: (i) left&ndashright flexion (LR), (ii) dorsal&ndashventral flexion (DV), (iii) left&ndashright undulation (LU), (iv) dorsal&ndashventral undulation (DU), (v) asymmetric undulation (AU), (vi) breaststroke (BS), and (vii) flapping (F) (Table 9.1).

LR swimming is characterized by the flattening of the body in the sagittal plane and repeated left&ndashright bending near the midpoint of the body axis with the head and tail coming together laterally (Fig. 9.2A). This movement propels the animal through the water. Some animals, such as Melibe leonina, exhibit foot-first directionality, presumably because the dorsal cerata create drag. Other animals, such as Tambja eliora, proceed headfirst, with the tail lagging slightly, causing the body to take on an &ldquoS&rdquo form (Farmer, 1970). Animals in the genus Plocamopherus typically have a dorsal crest at the posterior end of the body that may act as a paddle and cause the head to proceed the tail (Rudman and Darvell, 1990).

FIGURE 9.1 An abbreviated phylogeny of the Nudipleura with reference to their behavior. Only the genera of the species listed in Table 9.1 are shown here unless species differences exist within the genus. The phylogenic relationships are based on Thollesson (1999), Waegele and Willan (2000), Wollscheid-Lengeling et al. (2001), Vonnemann et al. (2005), Göbbeler and Klussmann-Kolb (2010), and Pola and Gosliner (2010). The references for the behavior are listed in Table 9.1. Note that this figure represents all the known swimming species and only a tiny fraction of the more than 2,000 species that are not capable of swimming or for which there are no published reports of swimming. LR, left&ndashright flexion NS, nonswimmer DV, dorsal&ndashventral flexion LU, left&ndashright undulation BS, breaststroke DU, dorsal&ndashventral undulation AU, asymmetric undulation F, flapping.

TABLE 9.1 Abbreviated Nudipleura Taxonomy with Reference to Swimming

Taxonomy Swim Type References
Nudibranchia
Cladobranchia
Aeolidida
Aeolidioidea
Aeolidiidae
Aeolidiella alba BS Pruvot-Fol (1954), Farmer (1970)
Glaucidae
Hermissenda crassicornis LR Lillvis et al. (2012)
Flabellinoidea
Flabellinidae
Flabellina cynara BS Marcus and Marcus (1967), Farmer (1970)
Flabellina iodinea LR MacFarland (1966), Farmer (1970)
Flabellina telja LR Marcus and Marcus (1967), Farmer (1970), Ferreira and Bertsch (1972)
Flabellina trophina NS a
Cumanotus beaumonti BS Picton and Morrow (1994)
Cumanotus cuenoti BS Tardy and Gantes (1980)
Arminoidea
Armina californica NS a
Dendronotida b
Bornellidae
Bornella anguilla LU Johnson (1984)
Bornella calcarata LR Thompson (1980)
Bornella stellifer LR Risbec (1953), Farmer (1970), Willan and Coleman (1984)
Dendronotidae
Dendronotus albopunctatus LR Robilliard (1972)
Dendronotus albus LR Farmer (1970), Robilliard (1970)
Dendronotus dalli LR Robilliard (1970)
Dendronotus diversicolor LR Robilliard (1970)
Dendronotus frondosus LR Farmer (1970), Robilliard (1970)
Dendronotus iris LR Kjerschow-Agersborg (1922), Haefelfinger and Kress (1967), Marcus and Marcus (1967), Farmer (1970), Robilliard (1970)

Taxonomy Swim Type References
Dendronotus nanus LR Marcus and Marcus (1967), Farmer (1970), Robilliard (1972)
Dendronotus rufus LR Robilliard (1970)
Dendronotus subramosus LR Farmer (1970), Robilliard (1970)
Lomanotidae
Lomanotus genei LR Garstang (1890), Thompson and Brown (1984)
Phylliroidae
Phylliroë atlantica LU Lalli and Gilmer (1989)
Phylliroë bucephala LU Lalli and Gilmer (1989)
Cephalopyge trematoides LU Steinberg (1956), Lance (1968)
Scyllaeidae
Notobryon wardi LR Thompson and Brown (1981)
Scyllaea pelagica LR Collingwood (1879), Pruvot-Fol (1954), Farmer (1970)
Tethydidae
Melibe bucephala LR Schuhmacher (1973)
Melibe engeli LR Risbec (1937)
Melibe fimbriata LR Thompson and Crampton (1984)
Melibe japonica LR Willan and Coleman (1984)
Melibe leonina LR Kjerschow-Agersborg (1921), Hurst (1968), Farmer (1970), Lawrence and Watson (2002)
Melibe megaceras LR Gosliner (1987b)
Melibe pilosa LR Pease (1860), Farmer (1970), Ostergaard (1955)
Tethys fimbria LR Pruvot-Fol (1954), Farmer (1970)
Dironidae
Dirona picta NS a
Dirona albolineata NS a
Tritoniidae
Marionia blainvillea DV c Pontes (2002)
Marionia tethydes DV c Haefelfinger and Kress (1967)
Tritonia diomedea DV Willows (1967), Hume et al. (1982)
Tritonia festiva DV Birkeland (1974)
Tritonia hombergii DV Willows and Dorsett (1975)
Taxonomy Swim Type References
Euctenidiacea
Doridacea
Doridoidea
Dorididae
Aphelodoris antillensis DV Quiroga et al. (2004)
Aphelodoris brunnea DV Gosliner (1987a)
Aphelodoris gigas DV Wilson (2003)
Aphelodoris karpa DV Wilson (2003)
Aphelodoris varia NS Wilson (2003)
Discodorididae
Diaulula sandiegensis NS a
Discodoris evelinae DV Marcus (1955), Marcus and Marcus(1967)
Discodoris pusae DV Marcus (1955)
Sebadoris nubilosa DV/DU d Marcus and Marcus (1967), Farmer (1970)
Chromodoridae
Archidoris odhneri NS a
Archidoris montereyensis NS a
Hypselodoris picta NS a
Cadlina luteomarginata NS a
Onchidoridoidea
Goniodorididae
Trapania velox LR f Cockerell (1901), Farmer (1970)
Polyceroidea
Hexabranchidae
Hexabranchus aureomarginatus DV/DU d Neu (1932), Ostergaard (1955), Farmer (1970)
Hexabranchus morsomus DV/DU d Risbec (1928), Marcus and Marcus (1962)
Hexabranchus sanguineus DV/DU d Risbec (1928), Gohar and Soliman (1963), Vincente (1963), Edmunds (1968), Farmer (1970)
Hexabranchus tinkeri DV/DU d Ostergaard (1955), Farmer (1970)
Polyceridae
Nembrotha megalocera LR Yonow (1990)
Plocamopherus ceylonicus LR Willan and Coleman (1984), Rudman and Darvell (1990)
Taxonomy Swim Type References
Plocamopherus imperialis LR Willan and Coleman (1984), Ellis (1999a), Marshall and Willan (1999)
Plocamopherus maculatus LR Pease (1860)
Plocamopherus maderae LR Lowe (1842)
Plocaompherus tilesii LR Rudman and Darvell (1990), Ellis (1999b)
Tambja blackii LR Pola et al. (2006)
Tambja eliora LR Lance (1968), Farmer (1970)
Tambja morose LR Marshall and Willan (1999)
Triopha fulgurans LR Risbec (1925), Farmer (1970)
Triopha catalinae NS a
Pleurobranchomorpha
Pleurobranchidae
Euselenops luniceps F e Pace (1901), Farmer (1970)
Pleurobranchaea californica DV Gillette et al. (1991), Davis and Mpitsos (1971)
Pleurobranchus membranaceus AU Thompson and Slinn (1959), Farmer (1970)

NOTE: This taxonomy is based upon that of Bouchet and Rocroi (2005). Abbreviations: AU = asymmetric undulation BS = breaststroke DU = dorsal&ndashventral undulation DV = dorsal&ndashventral flexion F = flapping LR = left&ndashright flexion LU = left&ndashright undulation NS = nonswimmer.

a Tested with mechanical and salt stimuli in our laboratories.

b A paraphyletic group (Pola and Gosliner, 2010).

c Farmer (1970) reported that Marionia swim via left&ndashright flexions and cited a German reference (Haefelfinger and Kress, 1967). However, a translation of this reference into English, by P. Katz, indicates that Haefelfinger and Kress reported dorsal&ndashventral flexions.

d Farmer (1970) categorized swimming in Sebadoris and Hexabranchus as &ldquoflapping.&rdquo However, swimming in these species appears to include dorsal&ndashventral flexions of the body, in addition to undulations of the mantle.

f Farmer (1970) classified Trapania velox as an LR swimmer. However, see text for additional discussion.

Plocamopherus ceylonicus (Rudman and Darvell, 1990 Marshall and Willan, 1999) and Plocamopherus maderae (Lowe, 1842) swim with LR flexions when dislodged from a substrate or disturbed in some way. Tambja appears to use LR swimming as an escape response contact with the predacious nudibranch Roboastra will elicit swimming in Tambja (Farmer, 1970 Pola et al., 2006). LR swimming in Melibe and Dendronotus iris can be initiated in response to loss of contact with the substrate or in response to the touch of a predatory sea star (Lawrence and Watson, 2002 Sakurai et al., 2011).

FIGURE 9.2 Two examples of swimming behaviors. (A) LR swimming exhibited by M. leonina. The ventral side of the animal is shown with the mouth at the top of the image. During swimming, the foot is narrowed to a strip and the animal rhythmically flexes its body leftward and rightward, bending at a point midway along the body axis. (B) DV swimming exhibited by T. diomedea. The animal starts on the substrate, shown at the bottom with its head to the right. It launches with a ventral flexion, where the head and tail meet under the foot. Then, it flexes so that the head and tail meet above the dorsal body surface. The foot is flattened and expanded to the width of the body. A, anterior P, posterior.

Melibe may also swim seasonally to disperse (Mills, 1994). The flexion cycle period for Melibe and Dendronotus is approximately 3 s, and swim bouts can last many minutes (Lawrence and Watson, 2002 Sakurai et al., 2011).

As its name suggests, Bornella anguilla swims with an eel-like movement caused by waves of muscular contraction (Johnson, 1984). Therefore, unlike other members of its genus, it is classified as an LU swimmer. LU swimming, which otherwise is found mostly in pelagic species, may be a further refinement of LR swimming.

DV swimming involves the animal flattening its body in the horizontal plane and repeatedly bending such that the tail and head meet in alternation above and below the midpoint of the body (Fig. 9.2B). Tritonia diomedea and Pleurobranchaea californica are two examples of DV swimmers that have been extensively studied (Willows, 1967 Davis and Mpitsos, 1971 Gillette and Jing, 2001 Katz, 2009). Swim bouts for Tritonia and Pleurobranchaea last less than 1 min and are triggered by contact with a predatory sea star or in the laboratory by high salt solutions or electric shock (Katz, 2010). The flexion cycle period under natural conditions is 5 to 10 s in Tritonia (Hume et al., 1982) and 3 to 6 s in Pleurobranchaea (Jing and Gillette, 1995).

DU swimming, like DV swimming, involves movement in dorsal and ventral directions, but here there are progressive symmetric waves of body wall or mantle muscular contraction. The Spanish dancer, Hexabranchus sanguineus, and other members of that genus are famous for their flamboyant swimming behavior (Gohar and Soliman, 1963 Edmunds, 1968 Farmer, 1970). Hexabranchus swimming differs in several ways from the DV swimming of Tritonia and Pleurobranchaea in addition to the symmetrical undulation of the lateral fringes of the mantle, it has a shorter flexion

cycle period (2&ndash4 s), swim bouts occur spontaneously, and swimming can last for long periods of time.

F swimming is similar to DV swimming in that the movement is bilaterally symmetric and dorsal&ndashventral in orientation, but instead of the head and tail meeting, the lateral edges of the mantle or foot rise and fall. F swimming is much more common in Opisthobranchia outside of the Nudipleura, such as Clione limacina (Arshavsky et al., 1986) and many species of Aplysia (Bebbington and Hughes, 1973 Donovan et al., 2006).

AU and BS are less common forms of locomotion. AU is characteristic of Pleurobranchus membranaceus (Thompson and Slinn, 1959) in which the animal swims upside down using its mantle as a passive keel while producing alternating muscular waves along its foot. BS involves the use of appendages including cerata and tentacles to stroke the water in a manner similar to a human swimmer&rsquos movements. Only four nudibranch species have been described as exhibiting this type of behavior (Table 9.1).

PHYLOGENETIC DISTRIBUTION OF SWIMMING BEHAVIORS

As noted earlier, we have been unable to find reports of swimming by about 97% of nudibranch species and approximately half the major subfamilies in the Pleurobranchomorpha clade. However, this does not mean they are not capable of swimming. Some species swim only as a high threshold escape response. Still, it is highly probable that the vast majority of the Nudipleura cannot and do not swim. This discussion is limited to species for which the type of swimming has been reported or for which swimming has been explicitly tested and shown not to occur.

LR swimming is by far the most prevalent of the six modes of swimming exhibited by nudibranchs: of the 60 nudibranch species documented to swim in the scientific literature, 40 species use LR or LU (Table 9.1). These 40 species are phylogenetically disparate, encompassing species in Doridacea and Cladobranchia (Fig. 9.1). Within the latter, there are LR swimmers in Aeolidoidea and Dendronotoidea. In Doridacea, all but one of the LR swimmers are in the family Polyceridae. There are no LR swimmers in the Pleurobranchomorpha or, to our knowledge, in any other Opisthobranch clade. This suggests that LR swimming is a derived characteristic of the nudibranch clade.

Unlike LR swimming, DV swimming is found in Nudibranchia and in Pleurobranchomorpha (Fig. 9.1). DV swimming is not present outside of Nudipleura and is therefore likely to be a synapomorphy of this clade. However, it is not widely displayed within Nudibranchia, appearing in just one family of Dendronotida (Tritoniidae) and in three families of Doridacea (Discodorididae, Dorididae, and Hexibranchidae). Discodorididae and Hexibranchidae also exhibit dorsal&ndashventral undulations (i.e., DU).

EVOLUTION OF SWIMMING BEHAVIORS

There are a number of possible scenarios that could account for the phylogenetic distribution of swimming behaviors among the Nudipleura. Considering the extreme rarity of swimming, it is possible, maybe even likely, that swimming evolved on multiple occasions from nonswimming species. The repeated gain of a function such as rhythmic movement could suggest that there is a predisposition toward these behaviors. The repeated appearance of LR and DV swimming may simply indicate that these two basic movements are the most likely to occur in a slug-shaped body with few appendages. When appendages such as moveable cerata are present, they have been repeatedly used for BS swimming. In the absence of such appendages, the only means of swimming are with LR-like or DV-like movements.

Given the presence of swimming across the phylogeny, it is possible that, rather than evolving independently many times from nonswimmers, swimming behaviors were repeatedly lost. Although this may lead to more transformations, it may be easier to lose a character than to gain one, as has been seen in other systems (Whiting et al., 2003 Moczek et al., 2006 Wiens et al., 2007 Harshman et al., 2008 Duboué et al., 2011).

For the moment, we will only consider the possible evolutionary scenarios that include transformations from one swimming state to another and ignore nonswimmers. It is generally the case that members of the same genus and often the same family exhibit the same form of swimming (Table 9.1), allowing us to group them together (Fig. 9.3). Here we will consider potential scenarios involving just the evolution of DV and LR swimming. It is possible that the ancestral species was able to swim using either DV or LR movements. However, this seems unlikely because there are no extant species that exhibit both of these behaviors. It is also unlikely that the ancestral state was LR swimming because of its absence in Pleurobranchomorpha.

Consider scenario 1 (Fig. 9.3A) in which DV swimming arose once at the base of the Nudipleura and LR swimming evolved independently several times. In this scenario, DV swimming behaviors in Pleurobranchomorpha, Doridacea, and Cladobranchia are homologous because they are shared by a common ancestor. Scenario 1 would also suggest that LR swimming evolved independently as many as seven times. Because of the unresolved branches in the phylogeny, there may be fewer switches in phenotype than this. In scenario 2 (Fig. 9.3B), LR swimming evolved once in the Nudibranchia, and DV swimming reevolved independently as many as four times. Again, the number of homoplastic events could be lower if the bifurcations in the phylogeny were better resolved.

The phylogenetic distribution of the swimming behavior suggests a resolution to the Dendronotida phylogeny, with Tritoniidae branching

FIGURE 9.3 Possible evolutionary scenarios explaining the phylogenetic distribution of swimming behaviors. Just the families of the DV and LR swimming animals are shown. (A) In scenario 1, DV swimming is a synapomorphy of the Nudipleura that was lost and replaced six times by LR swimming. (B) In scenario 2, LR swimming is a synapomorphy of the Nudibranchia. DV swimming then reappears four times in different nudibranch lineages. (C) For scenario 3, the phylogenetic tree of Dendronotida is altered to group LR swimmers together. Goniodorididae (asterisk), which includes T. velox, is switched from LR to DV (as discussed in the text). This reduces the number of transitions to LR from six in scenario 1 to four. (D) Scenario 4 is similar to scenario 2, with Goniodorididae (asterisk) switched to DV. This represents the most parsimonious explanation if DV swimming is ancestral, with just three transitions from the basal DV state.

off separately from the LR swimmers. This would reduce the number of homoplastic events in Cladobranchia according to scenario 1 from five to three (scenario 3 Fig. 9.3C).

The phylogenetic distribution of the behavior also calls into question the accuracy of a report about the behavior of Trapania velox. Outside of the family Polyceridae, T. velox (family: Goniodorididae) is the only doridacean reported to swim with left&ndashright flexions. Farmer (1970) categorized T. velox as an LR swimmer based on a previous report by Cockerell (1901), who described T. velox as being, &ldquovery active when swimming with an undulating motion on the surface of the water.&rdquo However, there is no indication as to the plane of movement. Farmer (1970) reported working with this rare species and being unsuccessful at making it swim, and was thus unable to provide any additional information. We were unable to find any other reports of its behavior. If T. velox is reclassified as a DV swimmer, it would further decrease the number of homoplastic events in scenario 1 from seven to four (Fig. 9.3C). Thus, examining the phylogenetic distribution of behavior makes a prediction about the behavior of this rare species.

Redefining T. velox as a DV swimmer also suggests a fourth scenario (Fig. 9.3D), whereby LR swimming arose independently in Cladobranchia and Polyceridae. This would also involve reevolution of DV swimming in Tritoniidae. Scenario 4 would therefore be the most parsimonious explanation for the phylogenetic distribution of swimming behaviors if one does not take into account the hundreds of nonswimming species.

NEURAL CIRCUITS UNDERLYING SWIMMING

With our potential scenarios about the homology and homoplasy of swimming behaviors, it is now of interest to compare the neural mechanisms for these behaviors. The neural activity that underlies rhythmic DV and LR movements originates from central pattern generator (CPG) circuits (Delcomyn, 1980). These swim CPGs are composed of neurons whose anatomical and physiological properties allow them to be individually identifiable from animal to animal within a species. The same sets of characteristics can be used to identify homologous neurons in other species (Croll, 1987). This allows the composition of neural circuits and the roles of homologous neurons to be compared across species. The neural circuits underlying swimming have been determined in two DV swimmers [T. diomedea (Katz, 2009) and P. californica (Gillette and Jing, 2001 Jing and Gillette, 1999)] and two LR swimmers [M. leonina (Sakurai et al., 2011 Thompson and Watson, 2005) and D. iris (Sakurai et al., 2011)]. We can now begin to compare neural circuits underlying behaviors of animals to address phylogenetic and functional hypotheses.

The neural basis for DV swimming was first studied in T. diomedea (Willows, 1967 Dorsett et al., 1969 Getting et al., 1980 Getting, 1981, 1983). The swim CPG consists of just three neuron types (Fig. 9.4A). On each side of the brain, there are three dorsal swim interneurons (DSIs), one ventral swim interneuron (VSI), and one cerebral interneuron 2 (C2), for a total of 10 neurons (Katz, 2009, 2010). The DSIs initiate the dorsal flexion cycle in which C2 participates. C2 then excites VSI, which inhibits DSI and C2 and elicits the ventral phase of the movement. As would be expected for a DV swimmer, the contralateral counterparts for each neuron fire in relative synchrony (Fig. 9.4B).

The neurons comprising the CPG for DV swimming in P. californica include DSI and C2 homologues called As and A1, respectively (Jing and Gillette, 1995, 1999). The connectivity and activity of these homologues is similar in both species (Fig. 9.4C and D). The homologue of the Tritonia VSI has not been identified in Pleurobranchaea, although there is synaptic input to As and A1 during the ventral phase of the motor pattern that may arise from such a neuron (i.e., Ivs neuron) (Jing and Gillette, 1999). Alternatively, ventral-phase synaptic input may arise from a neuron that is not homologous to VSI, but serves a similar role.

There are also Pleurobranchaea swim CPG neurons (A3 and A10) that have not been identified in Tritonia. Despite more than 40 years of electro-physiological study concentrated in the area where the A3 and A10 somata would be, no neurons with equivalent synaptic connectivity or activity have been found in Tritonia. Thus, either these neurons do not exist in Tritonia or they cannot be recognized with electrophysiological criteria.

With the information available about the swim CPGs in Tritonia and Pleurobranchaea, we can currently say that some homologous neurons are used for similar functions in distantly related species. This result is compatible with any of the phylogenetic scenarios (Fig. 9.3). If DV swimming is homologous (scenarios 1 or 3 Fig. 9.3A and C), the similarities in the DV swim CPGs in Tritonia and Pleurobranchaea could be a result of their homology and the potential differences in the swim CPGs could represent divergence of the circuit architecture. The differences in the swim CPGs may just as readily reflect independent evolutionary paths (scenarios 2 or 4 Fig. 9.3B and D), which might suggest a predisposition to use certain neurons to produce these behaviors.

The LR swim CPG was first described in M. leonina (Watson et al., 2001 Thompson and Watson, 2005). The published circuit consists of a pair of bilaterally represented neurons: swim interneuron 1 (Si1) and swim

FIGURE 9.4 Neural circuits and swim motor patterns for the DV swimmers Tritonia and Pleurobranchaea. (A) The Tritonia swim CPG consists of three neuron types: DSI, C2, and VSI. (B) Simultaneous intracellular microelectrode recordings show that two contralateral DSIs fire bursts of action potentials in phase with each other and slightly ahead of the two C2s. VSI (not recorded here) fires action potentials in the interburst interval. The motor pattern is initiated by electrical stimulation of a body wall nerve (stim). (C) The Pleurobranchaea swim CPG contains five types of neurons (Jing and Gillette, 1999). The As neurons are homologues of the DSIs. A1 is homologous to C2. A10 is strongly electrically coupled to A1 and, for simplicity, is shown together with it. A3 is not found in Tritonia. The Ivs neuron has not been found, but has been postulated to exist based on recordings of inhibitory postsynaptic potentials in other neurons. (D) Simultaneous intracellular recordings from an A3, As, and A1. The As neuron leads the A1 neuron just as DSI leads C2. The swim motor pattern is initiated by electrical stimulation of a body wall nerve (stim). In A and C, the small filled circles represent inhibitory synapses, the triangles are excitatory synapses, and combinations are mixed inhibition and excitation. The resistor symbol represents electrical synapses.

interneuron 2 (Si2 Fig. 9.5A). Based on their anatomy and neurochemistry, these neurons are not homologous to any of the Tritonia or Pleurobranchaea swim CPG neurons.

In the Melibe swim CPG, each neuron reciprocally inhibits the two contralateral counterparts (Fig. 9.5B). There is also strong electrical coupling between the ipsilateral Si1 and Si2, causing them to fire in phase with each other and 180° out of phase with the contralateral pair (Fig. 9.5C). This bursting pattern drives the left&ndashright alternations of the swimming behavior (Watson et al., 2002).

Homologues of the Melibe Si1 and Si2 were identified in D. iris based on anatomical, neurochemical, and electrophysiological features (Sakurai et al., 2011). However, there are important differences in the neural circuit formed by these neurons (Fig. 9.5D). Although the contralateral Si2 neurons reciprocally inhibit each other, Si1 does not inhibit or receive inhibition from either contralateral neuron. Instead, Si1 exhibits strong electrical coupling to its contralateral counterpart (Fig. 9.5E). During a swim motor pattern, the contralateral Si2 neurons fire bursts of action potentials in alternation, but the Si1 pair fire irregularly (Fig. 9.5F). Thus, whereas both Si1 and Si2 are members of the LR swim CPG in Melibe, only Si2 is in Dendronotus.

If LR swimming in Melibe and Dendronotus is homologous, as would be expected from scenarios 2, 3, or 4 (Fig. 9.3B&ndashD), this would be an example in which the neural mechanisms diverged while the behavior stayed the same. However, it could be the case that the differences in neural mechanism reflect a different evolutionary origin for LR swimming in Melibe and Dendronotus as in scenario 1 (Fig. 9.3A).

FUNCTIONS OF DV SWIM CPG NEURONS IN OTHER SPECIES

DSI and C2 homologues can be recognized by using neuroanatomical and neurochemical criteria, allowing them to be identified in species that are not DV swimmers (Table 9.2). The DSIs are serotonergic (Katz et al., 1994 McClellan et al., 1994) and have a characteristic axon projection pattern (Getting et al., 1980). They have been identified in 10 different genera, including two opisthobranchs outside of the Nudipleura (Newcomb and Katz, 2007). Electrophysiological traits of the DSI homologues show little correlation with the type of behavior produced by the species (Newcomb and Katz, 2007). C2 has been identified based on peptide immuno-reactivity and characteristic morphology in five genera within the Nudipleura (Lillvis et al., 2012). These DV swim CPG neurons are present regardless of the animal&rsquos mode of locomotion. This suggests that the swimming CPGs were built upon previously existing neural circuits, coopting existing neurons for new functions.

The DV swim CPG neurons are not members of the LR swim CPGs. The DSI and C2 homologs in Melibe are not rhythmically active in phase with the motor pattern (Fig. 9.6A), nor are the DSI homologues rhythmically active during the Dendronotus swim motor pattern (Fig. 9.6B). Thus,

FIGURE 9.5 Neural circuitry and swim motor pattern for the LR swimmers Melibe and Dendronotus. (A) In the Melibe swim CPG (Thompson and Watson, 2005), there are two bilaterally represented neurons Si1 and Si2 that are mutually inhibitory across the midline and exhibit strong electrical coupling ipsilaterally (as indicated by thicker resistor symbol). (B) Depolarization of one Si1 by injecting 2 nA of current into it hyperpolarizes the contralateral counterpart. (C) The Melibe swim motor pattern consists of ipsilateral synchrony and alternation with the contralateral side. (D) In Dendronotus, the inhibitory connections to and from Si1 are absent, and the electrical coupling between the contralateral Si1 pair dominates (Sakurai et al., 2011). (E) Depolarization of an Si1 with 2-nA current injection depolarizes the contralateral counterpart. (F) In the Dendronotus swim motor pattern, the left and right Si2 fire alternating bursts of action potentials, but the Si1s fire irregularly. In A and D, the shaded boxes represent the functional CPGs.

TABLE 9.2 Homologous Neurons Identified in Different Species with Different Behaviors

Nudipleura Other Opisthobranchia
Neuron DV swimmers LR swimmers Nonswimmers
DSI Tritonia (Getting, 1977) Melibe (Newcomb and Katz, 2007) Armina (Newcomb and Katz, 2007) Aplysia (Mackey et al., 1989 Wright et al., 1995 Xin et al., 2001 Jing et al., 2008)
Pleurobranchaea (Jing and Gillette, 1999) Dendronotus (Newcomb and Katz, 2007) Triopha (Newcomb and Katz, 2007) Clione (Panchin et al., 1995 Satterlie and Norekian, 1995)
Hermissenda (Tian et al., 2006) Tochina (Newcomb and Katz, 2007)
C2 Tritonia (Getting, 1977 Taghert and Willows, 1978) Melibe (Lillvis et al., 2012)
Pleurobranchaea (Jing and Gillette, 1995) Hermissenda (Lillvis et al., 2012)
Flabellina (Lillvis et al., 2012)

categorically distinct behaviors are produced by CPGs containing nonoverlapping sets of neurons.

It was shown that the DSI homologues in Melibe do have an effect on the production of the swim motor pattern they can initiate a motor pattern in a quiescent preparation, and hyperpolarization can temporarily halt an ongoing motor pattern (Newcomb and Katz, 2009). In contrast to Tritonia, in which the DSIs are an integral part of the DV swim CPG, in Melibe, they act as extrinsic modulators. Thus, the functions of homologous neurons differ in species with different behaviors.

The DSIs are not dedicated to one function even within a species. In Pleurobranchaea, the DSI homologues synapse onto serotonergic neurons that increase ciliary beating and thereby increase the speed of crawling (Jing and Gillette, 2000). In Tritonia, DSI accelerates crawling through synapses onto the efferent peptidergic pedal neuron Pd5, which in turn increases cilia beat frequency (Popescu and Frost, 2002). DSI homologues in the nonswimming Tochuina tetraquetra and Triopha catalinae also monosynaptically excite homologues of Pd5 and presumably increase the speed of crawling (Newcomb and Katz, 2007). In Hermissenda, which produces LR flexions, the DSI homologues do not increase ciliary beating, but

FIGURE 9.6 Homologues of the Tritonia DV swim CPG neurons are not rhythmically active during LR swim motor patterns. (A) In Melibe, the C2 and DSI homologues do not display any rhythmic bursting in phase with the swim motor pattern reflected in the alternating firing pattern of the left and right Si. (B) In Dendronotus, a contralateral pair of DSI homologues exhibit synchronous irregular spiking that shows no relation to the ongoing LR swim motor pattern displayed by two contralateral pedal motor neurons (L-Pd and R-Pd).

instead excite motor neurons that cause contraction of the anterior foot (Tian et al., 2006). In the more distantly related opisthobranch, Aplysia californica, DSI homologues also initiate muscular crawling (Jing et al., 2008). Whereas, in the pelagic opisthobranch, C. limacina, the DSI homologues increase the frequency of parapodial &ldquowing&rdquo flapping and excite motor neurons that innervate the wings (Arshavsky et al., 1992 Satterlie and Norekian, 1995). Thus, the DSI homologues share common functions in controlling the foot and/or locomotion.

The C2 and DSI homologues have additional roles outside of locomotion. In Pleurobranchaea, the C2 homologue (A1) suppresses feeding through its connections to feeding-related interneurons (Jing and Gillette, 1995). In contrast, the DSI homologues (As) have the opposite effect by exciting a number of feeding interneurons (Jing and Gillette, 2000). This is a shared function with other opisthobranchs such as A. californica, in which the DSI homologues (CC9-10) help excite one of the same feeding interneurons as in Pleurobranchaea, the metacerebral cell (Jing et al., 2008). Thus, individual neurons are multifunctional. Some functions are shared across species, whereas other functions are particular to some species.

A phylogenetic analysis of the neural basis for swimming in the Nudipleura has revealed several interesting aspects about the evolution

of behavior. First, the basic building blocks of neural circuits, namely the neurons, are shared across diverse species. For example, DSI homologues are found across Opisthobranchia. Second, neurons, which are multifunctional within a species, appear to take on additional functions over the course of evolution. For instance, the DSI homologues are involved in several behaviors in various species, including generating DV swimming or enhancing other types of locomotion such as enhancing LR swimming or wing flapping. They also accelerate crawling and promote feeding. It is reasonable to expect that highly interconnected interneurons would not be dedicated to a single function, but would dynamically interact with many neurons involved in a variety of different behaviors.

This comparative analysis has also revealed that species with categorically similar behaviors such as the two DV swimmers, Tritonia and Pleurobranchaea, or the two LR swimmers, Melibe and Dendronotus, have overlapping sets of neurons in the swim CPG circuits. In contrast, the CPGs underlying categorically distinct behaviors consist of nonoverlapping sets of neurons. However, even in species that exhibit similar behaviors such as Melibe and Dendronotus, the CPG circuits can differ in neuronal and synaptic composition. Thus, although behavior itself is not a predictor of its underlying neural mechanism, it is a good first approximation.

We do not understand why the circuits in Melibe and Dendronotus differ. There could be functional reasons perhaps Si1, which is not rhythmically active in Dendronotus, has an additional function that is incompatible with swimming in that species. There may also be phylogenetic reasons perhaps Melibe and Dendronotus independently evolved swim CPGs and came up with different circuit organizations. Whatever the reason, the results show that analogous behaviors can be generated by circuits with different circuit architectures. Recent work in invertebrates has shown that there can be variability in neural circuits that is not reflected in the performance of the behavior even across individuals within a species (Goaillard et al., 2009 Roffman et al., 2011).

There is a great degree of behavioral homoplasy. Although scenario 4 (Fig. 9.3D) may be the most parsimonious explanation for the phylogenetic distribution of the swimming behaviors, it should be kept in mind that only approximately 2% to 3% of nudibranch species have been reported to swim. Therefore, there is probably even more behavioral homoplasy than any of the scenarios in Fig. 9.3 indicate. It is conceivable that swimming arose independently in each family where it is found, 16 times in all (Fig. 9.1 and Table 9.1).

Given that Tritonia and Pleurobranchaea are very distantly related within the Nudipleura clade, it is even more likely that they independently evolved DV swim CPGs. If so, the incorporation of DSI and C2 homologues into such a circuit represents parallel evolution, whereby

homologous structures independently came to have similar functions (Sanderson and Hufford, 1996 Hoekstra and Price, 2004 Scotland, 2011 Wake et al., 2011). This has been suggested for other systems as well. For example, homologous brain nuclei appear to be involved in vocal learning in lineages of birds that evolved song independently (Feenders et al., 2008 Hara et al., 2012). Similarly, interaural coincidence detection circuits arose independently in the brainstem nuclei of birds and mammals (Schnupp and Carr, 2009). Finally, the appearance of similar cortical areas are correlates with the independent evolution of precision hand control in primates (Padberg et al., 2007), suggesting that constraints in cortical organization led to the evolution of similar neural mechanisms underlying dexterity (Krubitzer, 2009).

If homologous neurons are repeatedly incorporated into neural circuits for analogous behaviors, it suggests that these neurons may be part of a more readily achievable state for swimming. Thus, the nervous system may affect the evolvability of behavior because some configurations of existing neurons could be more robust than others. The concept of evolvability first arose from genetics (Kirschner and Gerhart, 1998 Masel and Trotter, 2010), but has since been applied to nervous systems (Airey et al., 2000 Bendesky and Bargmann, 2011 Katz, 2011 Yamamoto and Vernier, 2011). Exploring the aspects of neural organization that lead to repeated evolution of particular behaviors will point to the factors that are most important for behavioral output.

We thank Arianna Tamvacakis for feedback on the manuscript. This work was supported by National Science Foundation Integrative Organismal Systems Grants 0814411, 1120950, and 1011476.


Evolution of the Human Brain: From Matter to Mind

Amélie Beaudet , . Bernard Wood , in Progress in Brain Research , 2019

7 Conclusions

The brain has changed dramatically over the course of hominin evolution, and understanding when and how is a key question in any study of the human mind. We have reviewed the available evidence starting with establishing the polarity of primitive and derived traits using what we know about modern chimpanzee and human brains. We described two competing hominin taxonomic philosophies in order to define the relevant taxonomic units of analysis in the fossil record. Brain size increased threefold over the duration of human evolution, and understanding this pattern requires knowing how ECV increased across different taxonomic scales. Between the times of Australopithecus and H. heidelbergensis, clade-level ECV evolution was driven mainly by within-lineage increases (involving both directional selection and stasis/drift), supplemented with the origination of larger-brained species and the extinction of smaller-brained ones. In terms of brain shape, the characteristically globular endocranial shape of modern humans appeared well after the appearance of brains that overlapped the size range of modern humans. However, local changes that potentially occurred much earlier in hominin evolution include the reduction of the visual cortex and associated expansion of the parietal area, reorganization of the inferior frontal area, and structural asymmetries. The timing of the emergence of the modern human post-natal developmental pattern is unresolved.

Achieving a more precise understanding of the when and how of human brain evolution will require new fossil discoveries and innovative methods for gathering new data from existing specimens (e.g., developments in imaging techniques).


Determining Evolutionary Relationships

Scientists must collect accurate information that allows them to make evolutionary connections among organisms. Similar to detective work, scientists must use evidence to uncover the facts. In the case of phylogeny, evolutionary investigations focus on two types of evidence: morphologic (form and function) and genetic.

Two Options for Similarities

In general, organisms that share similar physical features and genomes tend to be more closely related than those that do not. Such features that overlap both morphologically (in form) and genetically are referred to as homologous structures they stem from developmental similarities that are based on evolution. For example, the bones in the wings of bats and birds have homologous structures (Figure 1).

Figure 1: Bat and bird wings are homologous structures, indicating that bats and birds share a common evolutionary past. (credit a: modification of work by Steve Hillebrand, USFWS credit b: modification of work by U.S. DOI BLM. “homologous structures” by OpenStax is licensed under CC BY 4.0)

Notice it is not simply a single bone, but rather a grouping of several bones arranged in a similar way. The more complex the feature, the more likely any kind of overlap is due to a common evolutionary past. Imagine two people from different countries both inventing a car with all the same parts and in exactly the same arrangement without any previous or shared knowledge. That outcome would be highly improbable. However, if two people both invented a hammer, it would be reasonable to conclude that both could have the original idea without the help of the other. The same relationship between complexity and shared evolutionary history is true for homologous structures in organisms.

Misleading Appearances

Some organisms may be very closely related, even though a minor genetic change caused a major morphological difference to make them look quite different. Similarly, unrelated organisms may be distantly related, but appear very much alike. This usually happens because both organisms were in common adaptations that evolved within similar environmental conditions. When similar characteristics occur because of environmental constraints and not due to a close evolutionary relationship, it is called an analogy or homoplasy. For example, insects use wings to fly like bats and birds, but the wing structure and embryonic origin is completely different. These are called analogous structures (Figure 2).

Similar traits can be either homologous or analogous. Homologous structures share a similar embryonic origin analogous organs have a similar function. For example, the bones in the front flipper of a whale are homologous to the bones in the human arm. These structures are not analogous. The wings of a butterfly and the wings of a bird are analogous but not homologous. Some structures are both analogous and homologous: the wings of a bird and the wings of a bat are both homologous and analogous. Scientists must determine which type of similarity a feature exhibits to decipher the phylogeny of the organisms being studied.

Figure 2: The (c) wing of a honeybee is similar in shape to a (b) bird wing and (a) bat wing, and it serves the same function. However, the honeybee wing is not composed of bones and has a distinctly different structure and embryonic origin. These wing types (insect versus bat and bird) illustrate an analogy—similar structures that do not share an evolutionary history. (credit a: modification of work by Steve Hillebrand, USFWS credit b: modification of work by U.S. DOI BLM credit c: modification of work by Jon Sullivan. “analogy” by OpenStax is licensed under CC BY 4.0)

Molecular Comparisons

With the advancement of DNA technology, the area of molecular systematics , which describes the use of information on the molecular level including DNA analysis, has blossomed. New computer programs not only confirm many earlier classified organisms, but also uncover previously made errors. As with physical characteristics, even the DNA sequence can be tricky to read in some cases. For some situations, two very closely related organisms can appear unrelated if a mutation occurred that caused a shift in the genetic code. An insertion or deletion mutation would move each nucleotide base over one place, causing two similar codes to appear unrelated.

Sometimes two segments of DNA code in distantly related organisms randomly share a high percentage of bases in the same locations, causing these organisms to appear closely related when they are not. For both of these situations, computer technologies have been developed to help identify the actual relationships, and, ultimately, the coupled use of both morphologic and molecular information is more effective in determining phylogeny.

Why Does Phylogeny Matter?

Evolutionary biologists could list many reasons why understanding phylogeny is important to everyday life in human society. For botanists, phylogeny acts as a guide to discovering new plants that can be used to benefit people. Think of all the ways humans use plants—food, medicine, and clothing are a few examples. If a plant contains a compound that is effective in treating cancer, scientists might want to examine all of the relatives of that plant for other useful drugs.

A research team in China identified a segment of DNA thought to be common to some medicinal plants in the family Fabaceae (the legume family) and worked to identify which species had this segment (Figure 3). After testing plant species in this family, the team found a DNA marker (a known location on a chromosome that enabled them to identify the species) present. Then, using the DNA to uncover phylogenetic relationships, the team could identify whether a newly discovered plant was in this family and assess its potential medicinal properties.

Figure 3: Dalbergia sissoo (D. sissoo) is in the Fabaceae, or legume family. Scientists found that D. sissoo shares a DNA marker with species within the Fabaceae family that have antifungal properties. Subsequently, D. sissoo was shown to have fungicidal activity, supporting the idea that DNA markers can be used to screen for plants with potential medicinal properties. (credit: “Dalbergia sissoo” by OpenStax is licensed under CC BY 4.0)

Building Phylogenetic Trees

How do scientists construct phylogenetic trees? After the homologous and analogous traits are sorted, scientists often organize the homologous traits using a system called cladistics. This system sorts organisms into clades: groups of organisms that descended from a single ancestor. For example, in Figure 4, all of the organisms in the orange region evolved from a single ancestor that had amniotic eggs. Consequently, all of these organisms also have amniotic eggs and make a single clade, also called a monophyletic group. Clades must include all of the descendants from a branch point.

Figure 4: Lizards, rabbits, and humans all descend from a common ancestor that had an amniotic egg. Thus, lizards, rabbits, and humans all belong to the clade Amniota. Vertebrata is a larger clade that also includes fish and lamprey. (credit:”monophyletic groups” by OpenStax is licensed under CC BY 4.0)

Which animals in this figure belong to a clade that includes animals with hair? Which evolved first, hair or the amniotic egg?

Clades can vary in size depending on which branch point is being referenced. The important factor is that all of the organisms in the clade or monophyletic group stem from a single point on the tree. This can be remembered because monophyletic breaks down into “mono,” meaning one, and “phyletic,” meaning evolutionary relationship. Figure 5 shows various examples of clades. Notice how each clade comes from a single point, whereas the non-clade groups show branches that do not share a single point.

Figure 5: All the organisms within a clade stem from a single point on the tree. A clade may contain multiple groups, as in the case of animals, fungi and plants, or a single group, as in the case of flagellates. Groups that diverge at a different branch point, or that do not include all groups in a single branch point, are not considered clades. (credit: “clades” by OpenStax is licensed under CC BY 4.0)

Groups that do not include all organisms that descended from a single ancestor have different names. A paraphyletic group includes the most recent common ancestor, but not all of its descendants Figure 6. A polyphyletic group includes unrelated organisms descended from more than one ancestor.

Figure 6: A visual representation of monophyletic, polyphyletic, and paraphyletic groups. (Credit: 1999 by Addison Wesley Longman)

Shared Characteristics

Organisms evolve from common ancestors and then diversify. Scientists use the phrase “descent with modification” because even though related organisms have many of the same characteristics and genetic codes, changes occur. This pattern repeats over and over as one goes through the phylogenetic tree of life:

  1. A change in the genetic makeup of an organism leads to a new trait which becomes prevalent in the group.
  2. Many organisms descend from this point and have this trait.
  3. New variations continue to arise: some are adaptive and persist, leading to new traits.
  4. With new traits, a new branch point is determined (go back to step 1 and repeat).

If a characteristic is found in the ancestor of a group, it is considered a shared ancestral character because all of the organisms in the taxon or clade have that trait. The vertebrate in Figure 4 is a shared ancestral character. Now consider the amniotic egg characteristic in the same figure. Only some of the organisms in Figure 4 have this trait, and to those that do, it is called a shared derived character because this trait derived at some point but does not include all of the ancestors in the tree.

The tricky aspect to shared ancestral and shared derived characters is the fact that these terms are relative. The same trait can be considered one or the other depending on the particular diagram being used. Returning to Figure 4, note that the amniotic egg is a shared ancestral character for the Amniota clade, while having hair is a shared derived character for some organisms in this group. These terms help scientists distinguish between clades in the building of phylogenetic trees.

Choosing the Right Relationships

Imagine being the person responsible for organizing all of the items in a department store properly—an overwhelming task. Organizing the evolutionary relationships of all life on Earth proves much more difficult: scientists must span enormous blocks of time and work with information from long-extinct organisms. Trying to decipher the proper connections, especially given the presence of homologies and analogies, makes the task of building an accurate tree of life extraordinarily difficult. Add to that the advancement of DNA technology, which now provides large quantities of genetic sequences to be used and analyzed. Taxonomy is a subjective discipline: many organisms have more than one connection to each other, so each taxonomist will decide the order of connections.

To aid in the tremendous task of describing phylogenies accurately, scientists often use a concept called maximum parsimony, which means that events occurred in the simplest, most obvious way. For example, if a group of people entered a forest preserve to go hiking, based on the principle of maximum parsimony, one could predict that most of the people would hike on established trails rather than forge new ones.

For scientists deciphering evolutionary pathways, the same idea is used: the pathway of evolution probably includes the fewest major events that coincide with the evidence at hand. Starting with all of the homologous traits in a group of organisms, scientists look for the most obvious and simple order of evolutionary events that led to the occurrence of those traits.

These tools and concepts are only a few of the strategies scientists use to tackle the task of revealing the evolutionary history of life on Earth. Recently, newer technologies have uncovered surprising discoveries with unexpected relationships, such as the fact that people seem to be more closely related to fungi than fungi are to plants. Sound unbelievable? As the information about DNA sequences grows, scientists will become closer to mapping the evolutionary history of all life on Earth.

Summary

To build phylogenetic trees, scientists must collect accurate information that allows them to make evolutionary connections between organisms. Using morphologic and molecular data, scientists work to identify homologous characteristics and genes. Similarities between organisms can stem either from shared evolutionary history (homologies) or from separate evolutionary paths (analogies). Newer technologies can be used to help distinguish homologies from analogies. After homologous information is identified, scientists use cladistics to organize these events as a means to determine an evolutionary timeline. Scientists apply the concept of maximum parsimony, which states that the order of events probably occurred in the most obvious and simple way with the least amount of steps. For evolutionary events, this would be the path with the least number of major divergences that correlate with the evidence.


VISUAL CONNECTION

Figure 5: All the organisms within a clade stem from a single point on the tree. A clade may contain multiple groups, as in the case of animals, fungi and plants, or a single group, as in the case of flagellates. Groups that diverge at a different branch point, or that do not include all groups in a single branch point, are not clades.

What is the largest clade in this diagram?


Answer:
The largest clade encompasses the entire tree.

Shared Characteristics

Organisms evolve from common ancestors and then diversify. Scientists use the phrase “descent with modification” because even though related organisms have many of the same characteristics and genetic codes, changes occur. This pattern repeats as one goes through the phylogenetic tree of life:

  1. A change in an organism’s genetic makeup leads to a new trait which becomes prevalent in the group.
  2. Many organisms descend from this point and have this trait.
  3. New variations continue to arise: some are adaptive and persist, leading to new traits.
  4. With new traits, a new branch point is determined (go back to step 1 and repeat).

If a characteristic is found in the ancestor of a group, it is considered a shared ancestral character because all of the organisms in the taxon or clade have that trait. The vertebrate in Figure 4 is a shared ancestral character. Now consider the amniotic egg characteristic in the same figure. Only some of the organisms in Figure 4 have this trait, and to those that do, it is called a shared derived character because this trait derived at some point but does not include all of the ancestors in the tree.

The tricky aspect to shared ancestral and shared derived characters is that these terms are relative. We can consider the same trait one or the other depending on the particular diagram that we use. Returning to Figure 4, note that the amniotic egg is a shared ancestral character for the Amniota clade, while having hair is a shared derived character for some organisms in this group. These terms help scientists distinguish between clades in building phylogenetic trees.

Choosing the Right Relationships

Imagine being the person responsible for organizing all department store items properly—an overwhelming task. Organizing the evolutionary relationships of all life on Earth proves much more difficult: scientists must span enormous blocks of time and work with information from long-extinct organisms. Trying to decipher the proper connections, especially given the presence of homologies and analogies, makes the task of building an accurate tree of life extraordinarily difficult. Add to that advancing DNA technology, which now provides large quantities of genetic sequences for researchers to use and analzye. Taxonomy is a subjective discipline: many organisms have more than one connection to each other, so each taxonomist will decide the order of connections.

To aid in the tremendous task of describing phylogenies accurately, scientists often use the concept of maximum parsimony , which means that events occurred in the simplest, most obvious way. For example, if a group of people entered a forest preserve to hike, based on the principle of maximum parsimony, one could predict that most would hike on established trails rather than forge new ones.

For scientists deciphering evolutionary pathways, the same idea is used: the pathway of evolution probably includes the fewest major events that coincide with the evidence at hand. Starting with all of the homologous traits in a group of organisms, scientists look for the most obvious and simple order of evolutionary events that led to the occurrence of those traits.


Homology and homoplasy :: features and relationships

To test phylogenetic hypotheses, scientists must be able to find out which similarities indicate a close relationship between species and which do not. The key to this process is determining the evolutionary origins of the similar features. Only similarities inherited from the species' common ancestor can provide evidence of phylogenetic relationship, because they are evidence of a genetic continuity from the common ancestor. Such a similarity, inherited in common form from a single common ancestor, is called homology.

The importance of homology in determining relationships is easily illustrated. For example, whales and humans share many homologies that sharks do not have. Lungs, warm-bloodedness, lactation, three middle ear bones and a single jaw bone are all features that humans and whales share because of their common history of descent. These features did not all evolve in the most recent common ancestor of humans and whales--in fact, none of them did. Lungs are common to amphibians, reptiles, mammals, and birds, while lactation and the evolution of three former bones of the jaw into three middle ear bones are shared only by mammals. But all these homologies arose more recently than the common ancestor of humans and whales with sharks, and therefore provide evidence of the close relationship of humans and whales relative to sharks.

Different organisms can evolve in similar ways even if they are not similar by descent from a common ancestor. For example, although humans and whales share many features that sharks lack, sharks and whales share many features also. Like whales, sharks have a streamlined body shape, fins, and an aquatic habitat. Some whales have single-pointed teeth like sharks, and some sharks have live births, like whales. None of these features were inherited by both these species from their most recent common ancestor. Instead, such non-homologous similarities are examples of homoplasy.

Which features are homologous?

Testing whether similarities are homologies or not involves many comparisons. In some cases, we can look directly at the genetic basis of the traits. For example, a number of genes contribute to the hemoglobin protein, which carries oxygen in red blood cells. Mammals and other vertebrates have more of these genes than non-vertebrates, because gene duplications occurred in our distant ancestors. After these ancient duplications, several genes acquired more specialized functions, which are shared among diverse groups of animals. The odds that this complex series of events occurred more than once is so low that the hypothesis of homology among species that share these genes is virtually certain.

In other cases, the physiological basis of the trait compellingly favors homology. For example, the mechanisms of live birth in marsupials and placental mammals are different--marsupial offspring emerge from the mother and enter an external pouch very early in life, where they develop and grow, while placentals remain inside the mother for an equivalent length of time. However, the mechanism of lactation is the same. In both these groups, milk is produced by similar structures, the mammary glands, is transmitted in the same way, by suckling, has a very similar composition, and serves the same purpose. The detailed similarities of this physiological process would be unlikely to arise by chance--after all, there are many possible ways of providing nutrition directly to offspring. Therefore, we can argue quite strongly that lactation is a homology.

In some cases, the fossil record is the ultimate judge of homology. If paleontologists can find traces of the common ancestor of two groups, and can show that a feature existed in this ancestor, then the presence of the feature in the descendants is probably by homology. For example, our closest living relatives, the chimpanzees and gorillas, are both knuckle-walkers. Based on the weight of other evidence, chimpanzees are more closely related to humans than to gorillas, and humans are not knuckle-walkers. Knuckle-walking could have evolved in parallel in chimpanzees and gorillas, or it could be a homology--if humans actually descended from a knuckle-walking ancestor as well as chimpanzees and gorillas. Present-day evidence from anatomy does not strongly support either view. But fossil evidence from some of the earliest human relatives shows features in the wrist that may be signs that humans also evolved from a knuckle-walking ancestor (Richmond and Strait 2000). If these features are marks of a knuckle-walking ancestry, these fossils support the hypothesis of homology for knuckle-walking.

Patterns of homoplasy

Homoplasy can occur by convergence or by parallelism. Convergence describes similarities between two species that evolved independently from different features in their common ancestor. For example, the wings of birds and the wings of bats are similar in function, but bat wings involve the bones that in humans make up the hands, while bird wings lack many of these bones entirely, and instead include only the bones that in humans make up the arms. Both structures support flight, but because the two lineages had a long evolutionary separation before they independently became fliers, the wings are different in structure, development, and genetics.

Parallelism occurs when two groups independently develop similarities from the same structures. For example, gorillas, orangutans, and some fossil relatives of humans can have bony crests along the top of their skulls, called sagittal crests. These crests, which provide attachment points for massive jaw muscles, do not occur in the earliest human ancestors, and they may not have occurred in the common ancestor of gorillas and orangutans. However, sagittal crests perform the same function and develop from the same anatomical structures for the same reasons in all these animals. Many mammals with large jaw muscles have sagittal crests, including some bears and pigs. Thus, the feature is a case of parallelism. </p>

Because much of the evolution of species is caused by selection, which can affect gene frequencies in different populations in the same ways, homoplasy has been very common in evolutionary history. Convergence can occur whenever different organisms adapt to the same environment. For example, flight has evolved at least four times in the history of life, in birds, bats, pterosaurs, and insects, each time involving different underlying structures. Even very complex structures, like eyes that can focus light, have evolved many times in different groups of organisms. Parallel evolution is also common, because it is a likely result whenever similar species are subjected to the same series of events or sequence of environmental pressures. Closely related species tend to share many genes, because of their common ancestry, and when exposed to the same selective factors they tend to adapt in the same way. Parallelism especially creates challenges for paleontologists attempting to study relationships, because a feature that evolves in parallel in two closely related species is very difficult to distinguish from a homologous feature inherited from their common ancestor. Some groups of species have undergone substantial parallel evolution, and for this reason it can be extremely difficult to sort out their phylogenetic relationships.

See also:

References:

Richmond BG, Strait DS. 2000. Evidence that humans evolved from a knuckle-walking ancestor. Nature 404:382-385.


Biology 171

By the end of this section, you will be able to do the following:

  • Compare homologous and analogous traits
  • Discuss the purpose of cladistics
  • Describe maximum parsimony

Scientists must collect accurate information that allows them to make evolutionary connections among organisms. Similar to detective work, scientists must use evidence to uncover the facts. In the case of phylogeny, evolutionary investigations focus on two types of evidence: morphologic (form and function) and genetic.

Two Options for Similarities

In general, organisms that share similar physical features and genomes are more closely related than those that do not. We refer to such features that overlap both morphologically (in form) and genetically as homologous structures. They stem from developmental similarities that are based on evolution. For example, the bones in bat and bird wings have homologous structures ((Figure)).


Notice it is not simply a single bone, but rather a grouping of several bones arranged in a similar way. The more complex the feature, the more likely any kind of overlap is due to a common evolutionary past. Imagine two people from different countries both inventing a car with all the same parts and in exactly the same arrangement without any previous or shared knowledge. That outcome would be highly improbable. However, if two people both invented a hammer, we can reasonably conclude that both could have the original idea without the help of the other. The same relationship between complexity and shared evolutionary history is true for homologous structures in organisms.

Misleading Appearances

Some organisms may be very closely related, even though a minor genetic change caused a major morphological difference to make them look quite different. Similarly, unrelated organisms may be distantly related, but appear very much alike. This usually happens because both organisms were in common adaptations that evolved within similar environmental conditions. When similar characteristics occur because of environmental constraints and not due to a close evolutionary relationship, it is an analogy or homoplasy. For example, insects use wings to fly like bats and birds, but the wing structure and embryonic origin is completely different. These are analogous structures ((Figure)).

Similar traits can be either homologous or analogous. Homologous structures share a similar embryonic origin. Analogous organs have a similar function. For example, the bones in a whale’s front flipper are homologous to the bones in the human arm. These structures are not analogous. A butterfly or bird’s wings are analogous but not homologous. Some structures are both analogous and homologous: bird and bat wings are both homologous and analogous. Scientists must determine which type of similarity a feature exhibits to decipher the organisms’ phylogeny.


This website has several examples to show how appearances can be misleading in understanding organisms’ phylogenetic relationships.

Molecular Comparisons

The advancement of DNA technology has given rise to molecular systematics , which is use of molecular data in taxonomy and biological geography (biogeography). New computer programs not only confirm many earlier classified organisms, but also uncover previously made errors. As with physical characteristics, even the DNA sequence can be tricky to read in some cases. For some situations, two very closely related organisms can appear unrelated if a mutation occurred that caused a shift in the genetic code. Inserting or deleting a mutation would move each nucleotide base over one place, causing two similar codes to appear unrelated.

Sometimes two segments of DNA code in distantly related organisms randomly share a high percentage of bases in the same locations, causing these organisms to appear closely related when they are not. For both of these situations, computer technologies help identify the actual relationships, and, ultimately, the coupled use of both morphologic and molecular information is more effective in determining phylogeny.

Why Does Phylogeny Matter? Evolutionary biologists could list many reasons why understanding phylogeny is important to everyday life in human society. For botanists, phylogeny acts as a guide to discovering new plants that can be used to benefit people. Think of all the ways humans use plants—food, medicine, and clothing are a few examples. If a plant contains a compound that is effective in treating cancer, scientists might want to examine all of the compounds for other useful drugs.

A research team in China identified a DNA segment that they thought to be common to some medicinal plants in the family Fabaceae (the legume family). They worked to identify which species had this segment ((Figure)). After testing plant species in this family, the team found a DNA marker (a known location on a chromosome that enabled them to identify the species) present. Then, using the DNA to uncover phylogenetic relationships, the team could identify whether a newly discovered plant was in this family and assess its potential medicinal properties.


Building Phylogenetic Trees

How do scientists construct phylogenetic trees? After they sort the homologous and analogous traits, scientists often organize the homologous traits using cladistics . This system sorts organisms into clades: groups of organisms that descended from a single ancestor. For example, in (Figure), all the organisms in the orange region evolved from a single ancestor that had amniotic eggs. Consequently, these organisms also have amniotic eggs and make a single clade, or a monophyletic group . Clades must include all descendants from a branch point.


Which animals in this figure belong to a clade that includes animals with hair? Which evolved first, hair or the amniotic egg?

Clades can vary in size depending on which branch point one references. The important factor is that all organisms in the clade or monophyletic group stem from a single point on the tree. You can remember this because monophyletic breaks down into “mono,” meaning one, and “phyletic,” meaning evolutionary relationship. (Figure) shows various clade examples. Notice how each clade comes from a single point whereas, the non-clade groups show branches that do not share a single point.


What is the largest clade in this diagram?

Shared Characteristics

Organisms evolve from common ancestors and then diversify. Scientists use the phrase “descent with modification” because even though related organisms have many of the same characteristics and genetic codes, changes occur. This pattern repeats as one goes through the phylogenetic tree of life:

  1. A change in an organism’s genetic makeup leads to a new trait which becomes prevalent in the group.
  2. Many organisms descend from this point and have this trait.
  3. New variations continue to arise: some are adaptive and persist, leading to new traits.
  4. With new traits, a new branch point is determined (go back to step 1 and repeat).

If a characteristic is found in the ancestor of a group, it is considered a shared ancestral character because all of the organisms in the taxon or clade have that trait. The vertebrate in (Figure) is a shared ancestral character. Now consider the amniotic egg characteristic in the same figure. Only some of the organisms in (Figure) have this trait, and to those that do, it is called a shared derived character because this trait derived at some point but does not include all of the ancestors in the tree.

The tricky aspect to shared ancestral and shared derived characters is that these terms are relative. We can consider the same trait one or the other depending on the particular diagram that we use. Returning to (Figure), note that the amniotic egg is a shared ancestral character for the Amniota clade, while having hair is a shared derived character for some organisms in this group. These terms help scientists distinguish between clades in building phylogenetic trees.

Choosing the Right Relationships

Imagine being the person responsible for organizing all department store items properly—an overwhelming task. Organizing the evolutionary relationships of all life on Earth proves much more difficult: scientists must span enormous blocks of time and work with information from long-extinct organisms. Trying to decipher the proper connections, especially given the presence of homologies and analogies, makes the task of building an accurate tree of life extraordinarily difficult. Add to that advancing DNA technology, which now provides large quantities of genetic sequences for researchers to use and analzye. Taxonomy is a subjective discipline: many organisms have more than one connection to each other, so each taxonomist will decide the order of connections.

To aid in the tremendous task of describing phylogenies accurately, scientists often use the concept of maximum parsimony , which means that events occurred in the simplest, most obvious way. For example, if a group of people entered a forest preserve to hike, based on the principle of maximum parsimony, one could predict that most would hike on established trails rather than forge new ones.

For scientists deciphering evolutionary pathways, the same idea is used: the pathway of evolution probably includes the fewest major events that coincide with the evidence at hand. Starting with all of the homologous traits in a group of organisms, scientists look for the most obvious and simple order of evolutionary events that led to the occurrence of those traits.

Head to this website to learn how researchers use maximum parsimony to create phylogenetic trees.

These tools and concepts are only a few strategies scientists use to tackle the task of revealing the evolutionary history of life on Earth. Recently, newer technologies have uncovered surprising discoveries with unexpected relationships, such as the fact that people seem to be more closely related to fungi than fungi are to plants. Sound unbelievable? As the information about DNA sequences grows, scientists will become closer to mapping the evolutionary history of all life on Earth.

Section Summary

To build phylogenetic trees, scientists must collect accurate information that allows them to make evolutionary connections between organisms. Using morphologic and molecular data, scientists work to identify homologous characteristics and genes. Similarities between organisms can stem either from shared evolutionary history (homologies) or from separate evolutionary paths (analogies). Scientists can use newer technologies to help distinguish homologies from analogies. After identifying homologous information, scientists use cladistics to organize these events as a means to determine an evolutionary timeline. They then apply the concept of maximum parsimony, which states that the order of events probably occurred in the most obvious and simple way with the least amount of steps. For evolutionary events, this would be the path with the least number of major divergences that correlate with the evidence.

Art Connections

(Figure) Which animals in this figure belong to a clade that includes animals with hair? Which evolved first, hair or the amniotic egg?

(Figure) Rabbits and humans belong in the clade that includes animals with hair. The amniotic egg evolved before hair because the Amniota clade is larger than the clade that encompasses animals with hair.

(Figure) What is the largest clade in this diagram?

(Figure) The largest clade encompasses the entire tree.

Free Response

Dolphins and fish have similar body shapes. Is this feature more likely a homologous or analogous trait?

Dolphins are mammals and fish are not, which means that their evolutionary paths (phylogenies) are quite separate. Dolphins probably adapted to have a similar body plan after returning to an aquatic lifestyle, and, therefore, this trait is probably analogous.

Why is it so important for scientists to distinguish between homologous and analogous characteristics before building phylogenetic trees?

Phylogenetic trees are based on evolutionary connections. If an analogous similarity were used on a tree, this would be erroneous and, furthermore, would cause the subsequent branches to be inaccurate.

Describe maximum parsimony.

Maximum parsimony hypothesizes that events occurred in the simplest, most obvious way, and the pathway of evolution probably includes the fewest major events that coincide with the evidence at hand.

Glossary