Phylogeny and adaptive evolution of the brain-development gene microcephalin (MCPH1) in cetaceans
© McGowen et al; licensee BioMed Central Ltd. 2011
Received: 27 October 2010
Accepted: 14 April 2011
Published: 14 April 2011
Representatives of Cetacea have the greatest absolute brain size among animals, and the largest relative brain size aside from humans. Despite this, genes implicated in the evolution of large brain size in primates have yet to be surveyed in cetaceans.
We sequenced ~1240 basepairs of the brain development gene microcephalin (MCPH1) in 38 cetacean species. Alignments of these data and a published complete sequence from Tursiops truncatus with primate MCPH1 were utilized in phylogenetic analyses and to estimate ω (rate of nonsynonymous substitution/rate of synonymous substitution) using site and branch models of molecular evolution. We also tested the hypothesis that selection on MCPH1 was correlated with brain size in cetaceans using a continuous regression analysis that accounted for phylogenetic history. Our analyses revealed widespread signals of adaptive evolution in the MCPH1 of Cetacea and in other subclades of Mammalia, however, there was not a significant positive association between ω and brain size within Cetacea.
In conjunction with a recent study of Primates, we find no evidence to support an association between MCPH1 evolution and the evolution of brain size in highly encephalized mammalian species. Our finding of significant positive selection in MCPH1 may be linked to other functions of the gene.
The human brain is arguably one of the most remarkable adaptations in the history of life. Compared to other mammals, the human lineage has undergone a massive expansion in relative brain and forebrain size, cortical surface area, and overall cognitive ability . However, many other vertebrates exhibit increased relative brain and forebrain sizes, as well as complex social and cognitive behaviours. For example, odontocete cetaceans (toothed whales) have some of the largest brains relative to their body mass among extant mammals . Relative brain size in some odontocete species is greater than non-human primates , and in absolute terms, the giant sperm whale (Physeter macrocephalus) has the largest brain of any living organism at a maximum of 10 kg . According to some researchers, high relative brain or forebrain sizes are positively correlated with indices of cognition or "intelligence" [1, 5], although this association has been criticized in the literature [6, 7].
In primates, researchers have documented the association of six genes (MCPH1, ASPM, CDK5RAP2, CENPJ, STIL, WDR62) with the human congenital disorder of primary microcephaly, a disease marked by a two-thirds reduction in brain size and moderate to severe mental retardation [14–22]. All six microcephaly genes identified thus far are involved in control of the neural cell cycle and/or centrosome function, and therefore have a potentially large impact on the proliferation of neural precursor cells [23, 24]. Comparative analyses of protein-coding DNA sequences from primates suggest that these genes have evolved adaptively in primates [14–19, 25].
Multiple recent studies have revealed the importance of one of these genes, microcephalin (MCPH1), in maintaining genomic stability through mediation of the response to double-strand DNA breakage and regulation of chromosome condensation in the cell cycle [26–31]. MCPH1 is expressed in multiple tissues including those of the brain, liver, and kidney, but shows particularly high expression in neural progenitor cells of the forebrain . Microcephaly genes may play a role during development in switching between symmetric and asymmetric mitosis of neural progenitor cells to produce neurons in the cerebral cortex [24, 33]. Specifically, microcephalin may affect the first stage of neural cell division, with decreased MCPH1 function causing premature mitotic entry, eventually leading to a reduced pool of neural progenitor cells . In addition, the developing neuronal tissue in the brain seems particularly vulnerable to apoptosis as a result of DNA damage caused by double-strand breaks, thus potentially bringing about a decrease in viable neurons for individuals with impaired MCPH1 function [34, 35].
Although some lineages of whales and dolphins have experienced profound evolutionary increases in relative brain size, selection on microcephaly genes has not been investigated in detail within Cetacea. Several researchers have indicated the potential value of comparisons between brain genes of primates and other large-brained species for understanding processes underlying neurological novelty in primates including humans [23, 33, 36]. Here we sequenced a large segment of microcephalin (MCPH1) from 38 cetacean species, including 34 toothed whales and four baleen whales, and compared these data with published sequences from primates, which have convergently evolved large brain size. We also downloaded complete MCPH1 protein-coding sequences from Ensembl, including representatives of major primate lineages as well as the common bottlenose dolphin, Tursiops truncatus. We enumerated patterns of site- and branch-specific selection in cetacean MCPH1 and compared these estimates with patterns of selection intensity in primates and other mammals. We also explicitly tested the hypothesis that brain size is positively correlated with the intensity of selection at the nucleotide level in MCPH1 following the approach taken by .
Sampling and DNA Amplification
We sampled 38 species of cetaceans from nine families; twenty-three species belonged to Delphinidae, a family that includes the highest relative brain sizes as measured by the encephalization quotient (EQ) . We also included members of Mysticeti (baleen whales) and Physeteridae (giant sperm whale) that represent taxa with the largest absolute brain sizes that have ever evolved [4, 9, 10]. All cetacean taxa included in this study are listed in Additional File 1: Table S1.
We designed primers for exon 8 of MCPH1 from an alignment of sequences from the 2.0 build of the Bos taurus (domestic cow) genome and genomic data for Tursiops truncatus available via Genbank. Exon 8 consists of the highly variable inter-BRCT domain sequence (IBS) and makes up approximately half of the coding region of MCPH1. The IBS region shows evidence of positive selection on the lineage leading to humans [16, 19]. A small portion of intron 7 and most of exon 8 (total amplicon = ~1237 basepairs [bp]) were PCR amplified using MCPH1INT7F1 (5' GCT TTA TCA CGT TAT GGG CGG AC 3') or MCPH1INT7F2 (5' GCT TTA TCA CGT TAT GGG CGG ACT G 3') in the forward direction and MCPH1EX8R1 (5' GAG AGA CCA GTA AAG GAG GTT CAC 3'), MCPH1EX8R2 (5' AGG AGG TTC ACA TAC TTT CAC TAC 3'), or MCPH1RSeq2 (5' CGG GAG AAA AGT AAT CAT CG 3') in the reverse direction. PCR products were sequenced using the above primers, as well as MCPH1F1 (5' AAA ACG AGA AGT GTC CGT CCG C 3'), MCPH1F2 (5' CCT GTC TGC TAC GCC ATC TGT AAC 3'), MCPH1FSeq3 (5' TTT CCA GGA GAG AGA GGA CC 3'), MCPH1R1 (5' TTT CCA CAT CCC AGT CGC CTA C 3'), and MCPH1RSeq1 (5' TCT CCT TGA GAT TAT CGG G 3'). PCR was performed using 1 μl template DNA, 100 pmol of each primer, 1X AccuPrime PCR Buffer I (Invitrogen), and 1 unit AccuPrime Taq DNA Polymerase High Fidelity (Invitrogen) in a 50 μl reaction. PCR conditions consisted of 45 cycles of 1 min denaturation at 94°C, 1 min annealing at 58°C, and 1 min elongation at 68°C. All new sequences were deposited in Genbank (accession numbers HQ873570-HQ873608).
Data Set Compilation and Alignment
Three data sets were assembled. To investigate selection pressure over the whole gene, the "whole-gene" data set was compiled using complete MCPH1 coding sequences downloaded via Ensembl (Homo, Pan, Pongo, Macaca, Callithrix, Tupaia, Rattus, Mus, Canis, Equus, Bos, and the delphinid cetacean, Tursiops). Species were selected due to phylogenetic position, completeness, and quality of available sequence. We also compiled a data set consisting of sequences derived from exon 8 and a small segment of intron 7 (the "exon 8" data set), including those sequenced here and sequences downloaded for a wider range of species, largely primates, from the Ensembl and Genbank databases. Genbank accession numbers for all downloaded sequences are listed in Additional File 1. The third data set ("reduced exon 8") consisted of a reduced set of taxa that excluded sequences that were less than 90% complete (e.g., Balaenoptera acutorostrata, Kogia sima) and sequences from species belonging to Monodontidae due to the presence of a stop codon near the end of the sequence (see Additional File 1). Sequences for all data sets were aligned using CLUSTAL W  with a gap-opening penalty of 10 and a gap-extension penalty of 1. Exonic indels were multiples of 3 bp and were adjusted by eye to reflect the open reading frame.
Please see Additional File 1 for a full account of phylogenetic methods.
Tests for Positive Selection and Selective Constraints
Positive selection acting on the complete coding sequence of MCPH1 was examined by estimating ω (dN/dS, the ratio of the rate of nonsynonymous substitution to the rate of synonymous substitution) using the site models in the codeml program of PAML 4.0 . An unrooted species tree of Boreoeutheria [39–41] was used as an input tree with Rodentia, Primates + Scandentia, and Laurasiatheria positioned as a basal polytomy. Model M1a (nearly-neutral: ω0 < 1, ω1 = 1) was compared to M2a (positive selection: ω0 < 1, ω1 = 1, ω2 > 1) and M8a (nearly neutral; beta distribution: 0 < ω0 < 1 and ω1 = 1) was compared to model M8 (positive selection: beta distribution: 0 < ω0 < 1 and ω1 > 1) by performing likelihood ratio tests (LRTs) and assessing their significance using a χ2 distribution (two degrees of freedom [df] for M1a vs. M2a; one df for M8 vs. M8a). For the comparison of M8 vs. M8a, we halved the p-value as suggested by . A Bayes Empirical Bayes (BEB) analysis was implemented to calculate posterior probabilities of positively selected sites using the M2a and M8 models as described in . An individual site was considered to have undergone positive selection (ω > 1), if the posterior probability was ≥0.95. Variation in ω among branches was examined using the free-ratio model in which each branch of the tree was given a separate ω-value. The fit of the free-ratio model was compared to model M0 in which all branches in the tree were assigned the same ω value using the LRT with 20 degrees of freedom for the whole MCPH1 data set.
To further investigate selection on exon 8 of MCPH1, for which 38 cetacean species were sequenced (Additional File 1: Table S1), all intronic sequence was deleted, as well as sequence downstream of a stop codon found near the 3' end of exon 8 in monodontids (see Additional File 1). All "exon 8" analyses were implemented using a species tree and also a gene tree derived from phylogenetic analysis of the MCPH1 data. The species tree employed was a composite gathered from several sources [39–42]; the gene tree for PAML analyses was the optimal topology recovered by maximum likelihood (ML) analysis and was consistent with the 50% majority rule consensus of Bayesian trees. In both the species tree and the gene tree, Loxodonta, Euarchontoglires, and Laurasiatheria were treated as a basal trichotomy. The ratio ω was then estimated in the codeml program of PAML 4.0 , as described above for the complete coding sequence of MCPH1. Separate analyses were conducted using the site models for all mammals, cetaceans only, odontocetes only, delphinids only, mysticetes only, primates only, and all mammals excepting cetaceans and primates. By analyzing various subclades of mammals using the site models, the goal was to determine whether evidence for positive selection is a general feature of MCPH1 in mammals, or is instead restricted to only certain mammalian lineages. In addition, analyses using the species tree and gene tree were also conducted for the "reduced exon 8" data set (see above).
For the taxon-rich exon 8 alignment, ω was also estimated for individual branches and groups of branches . Several branch model analyses were conducted including a free-ratio model (all branches separate), two-ratio models in which one branch was given a separate ω (repeated for the branch leading to the last common ancestor [LCA] to each of the following groups: Cetacea, Mysticeti, Odontoceti, Delphinoidea, Delphinidae, as well as each of the terminal branches leading to Physeter and Orcinus), and two-ratio models in which one stem-based clade was given a separate ω (repeated for Cetacea, Mysticeti, Odontoceti, Delphinoidea, and Delphinidae). All models listed above were tested against a one-ratio model (M0) using LRTs and 1 df. Branch models with p ≤ 0.004 (0.05/13) after Bonferroni correction for multiple tests were interpreted as having a significantly different ω on the "foreground" branches of interest in comparison to the "background" ω on all remaining branches of the tree. Comparisons between background branches and foreground branch(es) at the base of lineages or within whole clades were conducted to test whether the pattern of selection on these branches was significantly distinct from the rest of the tree. Branches were selected for comparison due to their proposed relation to an evolutionary change in relative and/or absolute brain size. For example, in the case of Odontoceti and Delphinoidea, Marino et al.  proposed that these clades mark shifts associated with increases in relative brain size. Delphinidae was selected due to the high relative brain size of multiple species within the clade . The branches leading to Mysticeti, Physeter, and Orcinus were also tested because these lineages terminate at species with large absolute brain sizes [8, 9] (Figure 1, Additional File 1: Table S2). For all PAML branch models, both a species tree and the MCPH1 gene tree were used as input trees.
Variation of MCPH1within Cetacean Species
We recorded heterozygous sites for each cetacean MCPH1 sequence that was generated in this study. Sites in sequencing chromatograms that showed nearly equal height peaks for two different bases at the same position were considered true heterozygous sites (i.e., due to divergent alleles that were PCR-amplified from that specimen). The position (first, second, or third codon) and the nature (synonymous or nonsynonymous, transition or transversion, etc.) of change at each heterozygous site were noted, and this variation within species was compared to the pattern of nucleotide substitution in MCPH1 between cetacean species. For Tursiops truncatus and Delphinus capensis, we compared sequences derived from two individuals of each species and checked for intraspecific variation in MCPH1.
Analysis of Associations Between ω and Phenotype
To test prior hypotheses of association between ω and phenotype, we compiled data on absolute brain and body mass for 27 cetaceans for which we had molecular data; these traits vary widely among extant cetaceans (Figure 1). Absolute brain and body mass data came from multiple, previously published sources [8, 9, 43, 44]. For Platanista minor, we used measurements derived from the very close relative, Platanista gangetica [42, 43]. Because some body masses above came from individual animals and may not represent the full size range of a particular species, we also gathered data on maximum body size from species accounts in . In addition, a measure of relative brain mass, the encephalization quotient (EQ), was calculated for each species using a standard allometric equation of mammalian brain mass vs. body mass from : EQ = brain mass/0.12 (body mass)0.67. Absolute brain size, body size, maximum body size, and EQ were then log-transformed for statistical analysis (see below). Morphological data were deposited online in Supplemental Table S2.
We used the method of  to assess associations between ω and various phenotypic variables: absolute brain mass, absolute body mass, maximum body mass derived from , and EQ. For each of the 27 cetacean species that were scored for phenotypic data (see above), we calculated the average "root-to-tip" ω along branches extending from the last common ancestor of Cetacea to each extant cetacean species in our dataset. This approach has the advantage of producing a measure of selection that takes the entire evolutionary history of a lineage from a common ancestor into account and which is a property of the species tips in a way that is more comparable with extant phenotypes. This procedure also negates the issue of temporal effects on ω . Root-to-tip ω values were estimated in PAML 4.0  using a 2-rate branch model and the species tree of . Phylogenetically controlled regression analyses of log-transformed root-to-tip ω versus each log-transformed morphological variable were performed using BayesTraits [46, 47] and the time-calibrated tree of  to explicitly test for gene-phenotype associations. The significance of the regression analyses was determined using a one-tailed t-test in the positive direction, in order to test the hypothesis that there is a positive relationship between estimated selection pressure on MCPH1 (ω) and the phenotypic variables as in . Each regression was performed across all cetaceans and just within the Odontoceti.
In addition to the EQ, we also explored two other methods of assessing relative brain size. In the first method, we calculated residuals from a regression between brain and body mass and used these in a subsequent regression analysis with root-to-tip ω. In the second method, we performed a multiple regression of brain and body mass with root-to-tip ω. Both of these approaches produced similar results to the regression using the EQ, and are not shown here.
Characterization and Phylogenetic Analysis of MCPH1
Molecular Evolution of MCPH1
ω sites with
Sites under positive selection
ω > 1
ω > 1
(p > 0.95, BEB)
112, 132, 172, 205, 209, 247, 362
M1a v. M2a: df = 2, -2ΔlnL = 23.587, p < 0.001
M8 v. M8a: df = 1, -2ΔlnL = 26.804, p < 0.001
M1a v. M2a: df = 2, -2ΔlnL = 19.551, p < 0.001
M8 v. M8a: df = 1, -2ΔlnL = 19.523, p < 0.001
M1a v. M2a: df = 2, -2ΔlnL = 11.046, p < 0.001
M8 v. M8a: df = 1, -2ΔlnL = 11.044, p < 0.001
20, 89, 195
20, 89, 195
M1a v. M2a: df = 2, -2ΔlnL = 29.496, p < 0.001
M8 v. M8a: df = 1, -2ΔlnL = 29.496, p < 0.001
M1a v. M2a: df = 2, -2ΔlnL = 4.339, p = 0.114
M8 v. M8a: df = 1, -2ΔlnL = 0, p = 1.0
M1a v. M2a: df = 2, -2ΔlnL = 9.553, p = 0.008
M8 v. M8a: df = 1, -2ΔlnL = 9.333, p = 0.005
M1a v. M2a: df = 2, -2ΔlnL = 5.011, p = 0.082
M8 v. M8a: df = 1, -2ΔlnL = 11.010, p = 0.002
We performed further tests to determine whether evidence for positive selection was restricted to different subclades of our tree, or alternatively whether positive selection is a general feature that characterizes the evolution of MCPH1 in the mammalian lineages sampled here. According to models M2a and M8, clades that showed strong evidence for positive selection acting at a subset of sites included Primates, Cetacea, Odontoceti (species tree only), Delphinidae, and all mammals excepting cetaceans and primates (M8 only) (Table 1). Both site models did not indicate positive selection within Mysticeti, but only four mysticete sequences were sampled here, and this is well below the recommended number for robust tests of positive selection using models M2a and M8 .
MCPH1Polymorphism in Cetacea
A total of 38 sites in exon 8 were heterozygous in at least one of the cetacean species sampled here; 14 species showed allelic variation. Parsimony optimization of this variation onto the MCPH1 gene tree (Figure 2) suggests that 22 nonsynonymous and 18 synonymous changes can account for the intraspecific variation (28 transitions and 12 transversions). None of the 40 point mutations included changes to a stop codon. Ten changes were at first codon positions, 10 at second positions, and 20 at third positions; some of the allelic differences were shared among closely related species in our sample (e.g., between Delphinus delphis and D. capensis).
A comparison between substitutions that characterize change among cetacean species and polymorphic mutations within cetacean species indicated that a greater proportion of substitutions among species were nonsynonymous than within species (326 nonsynonymous and 154 synonymous estimated using model M0 for the species tree of  versus 22 nonsynonymous and 18 synonymous changes within species). The larger proportion of nonsynonymous change across the cetacean phylogeny (68%) relative to the proportion of nonsynonymous mutations within species (55%) is consistent with positive selection , but much more extensive sampling of MCPH1 variation within species is necessary to rigorously test this hypothesis in the future.
Association of ω with Phenotype
(1 tailed positive)
ω vs. brain mass
ω vs. EQ
ω vs. body mass
ω vs. max body mass
Toothed Whales only
ω vs. brain mass
ω vs. EQ
ω vs. body mass
ω vs. max body mass
(1 tailed positive)
(1 tailed negative)
Body mass vs. dN &dS
Brain mass vs. dN &dS
MCPH1as a Phylogenetic Marker in Mammals
Despite, or because of its molecular evolutionary dynamics, exon 8 of MCPH1 performed well as a phylogenetic marker at both deep and shallow nodes (Figure 2; Additional File 1: Figure S1, Figure S2). Most relationships among mammalian orders and supraordinal clades in the MCPH1 tree are congruent with analyses supported by much larger data sets [39, 40], and 15 clades within Primates are characterized by high support scores and congruence with comprehensive phylogenetic hypotheses for this group [41, 51] (Additional File 1: Figure S2). We also obtained good resolution within Cetacea (Figure 2), as compared to a recent supermatrix analysis of data from over 50 genes . Overall, the congruence of our MCPH1 topology (Figure 2; Additional File 1: Figure S1, Figure S2) with published results is impressive, and is consistent with some previous studies which showed that highly variable nuclear genes with extensive amino acid replacements and evidence of positive selection can be efficient phylogenetic markers [52, 53].
The Evolution of MCPH1across Mammals
Cetaceans, especially odontocetes, display multiple neuroanatomical and behavioral similarities with primates. Representatives of both groups have evolved large brains relative to their body sizes as well as highly complex cognitive abilities [9, 10], although some researchers dispute this latter point . In addition, cetaceans show similarities with great apes in brain histology, neural connectivity, and enlargement of specific parts of the brain associated with cognition and social awareness , as well as extensive gyrification, or folding of the cerebral cortex [10, 54]. Due to their convergence in multiple neurological and behavioral features, cetaceans present an obvious test of the hypothesis that MCPH1 is related to the evolution of large brain size in mammals.
Analysis of the full coding sequence of MCPH1 (Figure 3) revealed high ωs on the stem branch to hominid primates and also on the terminal branch leading to the bottlenose dolphin Tursiops. Very high average ω over the entire protein-coding sequence of a gene, especially one this long (~2500 bp), is rare, as indicated by comparisons across complete genome sequences of different species (e.g., ). The high ω on the cetacean branch, in combination with the superior fit of positive selection models to the MCPH1 data relative to nearly neutral models, suggests a persistent signal of positive selection since the bottlenose dolphin lineage split from Bos taurus (Ruminantia). Comparative analyses of MCPH1 sequences did not reveal evidence for precise site-specific convergent molecular evolution of MCPH1 between cetaceans and primates at the amino acid level in either the whole gene or exon 8 data sets. However for exon 8, seven sites were identified as evolving under positive selection in Boreoeutheria (Table 1). Changes at positively selected sites, inferred using the site models, were not restricted to either Primates or Cetacea suggesting that the gene may have an important evolutionary role across mammals (Table 1). Further detailed analysis of other mammalian clades will be needed to determine how extensive positive selection has been on MCPH1.
The Evolution of MCPH1within Cetacea and its Relation to Brain Size
With the inclusion of more species in the exon 8 data set, estimated ω ratios revealed a more complex pattern of evolution in cetaceans. In general, exon 8 had a relatively high mean ω across mammals (Table 1) and ω within Cetacea was elevated relative to the remaining branches in the tree (Table 2). Both Odontoceti and Delphinoidea represent clades in which shifts to larger relative brain sizes have been proposed, and the highest EQs are restricted to members of Delphinidae . However, our comparative analyses of MCPH1 did not reveal especially high ω scores on the branches leading to the LCAs of Cetacea, Odontoceti, Delphinoidea, or Delphinidae (Table 2). Absence of strong evidence for positive selection in these lineages does not match the evolutionary change of the EQ in which there is a large increase in relative brain size along the lineage leading from the LCA of Cetacea to the LCA of Delphinidae . Regression analyses agreed with these results, finding no robust associations between ω and absolute or relative brain size (Table 3).
Some of the largest ω scores, according to the branch models, were recorded along the branch leading to the LCA of mysticetes and across all mysticete branches (Table 2). This is contrary to the hypothesis that selection in MCPH1 is related to an increase in relative brain size [16, 19], as mysticetes have smaller brains than expected given their body size compared to the mammalian average ; however, it does not rule out that MCPH1 may be linked to overall change in EQ within cetaceans. Although mysticetes have low EQs, the brains of these cetaceans have the largest absolute mass in the animal kingdom, aside from elephants and the odontocete Physeter macrocephalus (giant sperm whale; Figure 1) . It has been argued that the molecular evolution of genes involved in the proliferation of neural progenitor cells should bear a closer relation to absolute brain size than relative brain size ; if MCPH1 has had such an evolutionary role we may then expect it to have high rates of evolution during the evolution of the largest cetaceans (Figure 1). Both the ancestral mysticete branch and the Physeter terminal branch have high ω (Table 2), but the branch leading to the very large delphinid, Orcinus orca which dwarfs most extant and extinct oceanic dolphins (Figure 1), did not show an extreme ω for MCPH1 in comparison to dolphins with much smaller brain and body sizes (Table 2; Additional File 1: Table S2). Our regression analyses do not support a robust association of ω with absolute brain mass, so we cannot confidently say that the high ω in mysticetes is causally related to selection for large brain size. Indeed, a stronger association was found between root-to-tip ω and body mass and therefore we cannot exclude body mass, or other correlated traits, from being the relevant phenotype. Our multiple regressions with dN and dS furthermore suggest that these trends may be driven largely by variation in dS, instead of dN, perhaps related to variation in life history traits which affect the rate at which neutral variants are fixed [49, 50].
The lack of association between brain size and the evolution of MCPH1 found in cetaceans agrees with the conclusions drawn from a recent study of anthropoid primates which showed that MCPH1 is not associated with the evolution of either absolute or relative brain size , despite the clear critical importance of MCPH1 in brain development. Together these studies question the commonly held assumption that this locus has a direct role in the evolution of brain size as a gross measure [16, 19, 56]. While we cannot rule out more nuanced roles in brain evolution, the phenotypic relevance of positive selection on this locus is currently an outstanding issue.
MCPH1 is expressed in many other tissues , and mutations in MCPH1 have been discovered in cancerous tumors . Some mysticetes have very long lifespans , are the largest animals that have yet evolved, and are characterized by a very high fetal growth rate . Given that MCPH1 functions in cell cycle regulation and DNA damage repair , it is plausible that positive selection in mysticetes and other mammals is related to the evolution of other phenotypes such as the rate of growth, absolute number of cells, or tumor suppression in very large organisms with long lifespans, although these hypotheses are currently speculative. Some evidence, presented here, suggests that positive selection has acted on this locus in non-primate, non-cetacean mammals (Table 1 - model M8). It may therefore be possible to study the evolutionary function of MCPH1, and to test these hypotheses, in more experimentally tractable organisms such as rodents.
Extant cetacean species are characterized by a very broad range of body sizes and brain sizes, among the greatest variation seen in any mammalian order (Figure 1). Although this study did not find evidence for a statistically significant association between selection intensity (ω) in MCPH1, a gene associated with microcephaly, and absolute or relative brain size in cetaceans (Table 3), some intriguing patterns emerged from detailed phylogenetic and molecular analyses of MCPH1. Evolutionary models that included parameters for positive selection consistently fit the MCPH1 sequence data significantly better than alternative models of negative selection and neutral change (Table 1). Using complete sequences of MCPH1, we identified ω > 1 in only two cases, along the lineage leading to Tursiops (bottlenose dolphin) and also on the branch leading to Hominidae (human, gorilla, chimp, and orang). Furthermore, analysis of a larger data set of cetacean sequences derived from the hypervariable exon 8 again indicated a very high average ω within Cetacea, with the largest ω values in Mysticeti, a group characterized by low EQ but large absolute brain and body weights. Despite finding strong evidence for positive selection having acted on a gene which has a key role in brain development, we found no compelling evidence to support the hypothesis that there is an association between the evolution of this locus and the evolution of brain size in cetaceans. This is in agreement with results from anthropoid primates, and suggests that positive selection on MCPH1 may be related to change in phenotypes other than gross brain size.
Funding was provided by NSF grants to JG (DEB-0743724, DEB-0640313) and a BBSRC student fellowship to SHM. We thank P. Morin, K. Robertson, S. Chivers, A. Dizon, R. LeDuc, T. Jefferson, G. Braulik, H. Rosenbaum, P. Palsbøll, M. Stanhope, M. Springer, M. Milinkovitch, Southwest Fisheries Science Center, The Marine Mammal Center, Mote Marine Laboratory, Wildlife Conservation Society, World Wildlife Fund, and Smithsonian Institution Division of Mammals for providing DNA samples. R. Meredith, J. Starrett, M. Springer, and C. Hayashi provided helpful comments on previous drafts of this manuscript. C. Buell executed paintings of cetaceans.
- Jerison JH: Evolution of the Brain and Intelligence. 1973, New York: Academic PressGoogle Scholar
- Worthy GA, Hickie JP: Relative brain size in marine mammals. Am Nat. 1986, 128: 445-459. 10.1086/284579.View ArticleGoogle Scholar
- Marino L: A comparison of encephalization between odontocete cetaceans and anthropoid primates. Brain Behav Evol. 1998, 51: 230-238. 10.1159/000006540.View ArticlePubMedGoogle Scholar
- Oelschläger HHA: The dolphin brain--a challenge for synthetic neurobiology. Brain Res Bull. 2008, 75: 450-459.View ArticlePubMedGoogle Scholar
- Lefebvre L, Reader SM, Sol D: Brains, innovations and evolution in birds and primates. Brain Behav Evol. 2004, 63: 233-246. 10.1159/000076784.View ArticlePubMedGoogle Scholar
- Healy SD, Rowe C: A critique of comparative studies of brain size. Proc R Soc B. 2007, 274: 453-464. 10.1098/rspb.2006.3748.View ArticlePubMedGoogle Scholar
- Deaner RO, Isler K, Burkhart J, van Schaik C: Overall brain size, and not encephalization quotient, best predicts cognitive ability across non-human primates. Brain Behav Evol. 2007, 70: 115-124. 10.1159/000102973.View ArticlePubMedGoogle Scholar
- Marino L, McShea D, Uhen MD: The origin and evolution of large brains in toothed whales. Anat Rec. 2004, 281A: 1247-1255. 10.1002/ar.a.20128.View ArticleGoogle Scholar
- Marino L: Brain size evolution. Encylcopedia of Marine Mammals. Edited by: Perrin WF, Wursig B, Thewissen JGM. 2002, San Diego: Academic Press, 158-162.Google Scholar
- Marino L, Connor RC, Fordyce RE, Herman LM, Hof PR, Lefebvre L, Lusseau D, McCowan B, Nimchinsky EA, Pack AA, Rendell L, Reidenberg JS, Reiss D, Uhen MD, Van der Gucht E, Whitehead H: Cetaceans have complex brains for complex cognition. PLoS Biol. 2007, 5: e139-10.1371/journal.pbio.0050139.View ArticlePubMedPubMed CentralGoogle Scholar
- Jerison JH: Brain and intelligence in whales. Whales and Whaling. Edited by: Frost S. 1978, Canberra: C. J. Thomson, Australian Commonwealth Government Printer, 2: 159-197.Google Scholar
- Connor RC, Mann J, Tyack PL, Whitehead H: Social evolution in toothed whales. Trends Ecol Evol. 1998, 13: 228-232. 10.1016/S0169-5347(98)01326-3.View ArticlePubMedGoogle Scholar
- Manger PR: An examination of cetacean brain structure with a novel hypothesis correlating thermogenesis to the evolution of a big brain. Biol Rev. 2006, 81: 293-338. 10.1017/S1464793106007019.View ArticlePubMedGoogle Scholar
- Zhang J: Evolution of the human ASPM gene, a major determinant of brain size. Genetics. 2003, 165: 2063-2070.PubMedPubMed CentralGoogle Scholar
- Dorus S, Vallender EJ, Evans PD, Anderson JR, Gilbert SL, Mahowald M, Wyckoff GJ, Malcom CM, Lahn BT: Accelerated evolution of nervous system genes in the origin of Homo sapiens. Cell. 2004, 119: 1027-1040. 10.1016/j.cell.2004.11.040.View ArticlePubMedGoogle Scholar
- Evans PD, Anderson JR, Vallender EJ, Choi SS, Lahn BT: Reconstructing the evolutionary history of microcephalin, a gene controlling human brain size. Hum Mol Genet. 2004, 13: 1139-1145. 10.1093/hmg/ddh126.View ArticlePubMedGoogle Scholar
- Evans PD, Anderson JR, Vallender EJ, Gilbert SL, Malcom CM, Dorus S, Lahn BT: Adaptive evolution of ASPM, a major determinant of cerebral cortical size in humans. Hum Mol Genet. 2004, 13: 489-494. 10.1093/hmg/ddh055.View ArticlePubMedGoogle Scholar
- Kouprina N, Pavlicek A, Mochida GH, Solomon G, Gersch W, Yoon YH, Collura R, Ruvolo M, Barrett JC, Woods CG, Walsh CA, Jurka J, Larlonov : Accelerated evolution of the ASPM gene controlling brain size begins prior to human brain expansion. PLoS Biol. 2004, 2: 653-663. 10.1371/journal.pbio.0020126.View ArticleGoogle Scholar
- Wang Y, Su B: Molecular evolution of microcephalin, a gene determining human brain size. Hum Mol Genet. 2004, 13: 1131-1137. 10.1093/hmg/ddh127.View ArticlePubMedGoogle Scholar
- Evans PD, Vallender EJ, Lahn BT: Molecular evolution of the brain size regulator genes CDK5RAP2 and CENPJ. Gene. 2006, 375: 75-79. 10.1016/j.gene.2006.02.019.View ArticlePubMedGoogle Scholar
- Kumar A, Girimaji SC, Duvvari MR, Blanton SH: Mutations in STIL, encoding a pericentriolar and centrosomal protein cause primary microcephaly. Am J Hum Genet. 2009, 84: 286-290. 10.1016/j.ajhg.2009.01.017.View ArticlePubMedPubMed CentralGoogle Scholar
- Yu TW, Mochida GH, Tischfield DJ, Sgaier SK, Flores-Sarnat L, Sergi CM, Topçu M, McDonald MT, Barry BJ, Felie JM, Sunu C, Dobyns WB, Folkerth RD, Barkovich JA, Walsh CA: Mutations in WDR62, encoding a centrosome-associated protein, cause microcephaly with simplified gyri and abnormal cortical architecture. Nat Genet. 2010, 42: 1015-1020. 10.1038/ng.683.View ArticlePubMedPubMed CentralGoogle Scholar
- Vallender EJ, Mekel-Bobrov N, Lahn BT: Genetic basis of human brain evolution. Trends Neurosci. 2008, 31: 637-644. 10.1016/j.tins.2008.08.010.View ArticlePubMedPubMed CentralGoogle Scholar
- Thornton GK, Woods CG: Primary microcephaly: do all roads lead to Rome?. Trends Genet. 2009, 25: 501-510. 10.1016/j.tig.2009.09.011.View ArticlePubMedPubMed CentralGoogle Scholar
- Montgomery SH, Capellini I, Venditti C, Barton RA, Mundy NI: Adaptive evolution of four microcephaly genes and the evolution of brain size in anthropoid primates. Mol Biol Evol. 2011, 28: 625-638. 10.1093/molbev/msq237.View ArticlePubMedGoogle Scholar
- Lin SY, Rai R, Li K, Xu ZX, Elledge SJ: BRIT/MCPH1 is a DNA damage responsive protein that regulates the Brca1-Chk1 pathway, implicating checkpoint dysfunction in microcephaly. Proc Nat Acad Sci USA. 2005, 102: 15105-15109. 10.1073/pnas.0507722102.View ArticlePubMedPubMed CentralGoogle Scholar
- Rai R, Dal H, Multani AS, Li K, Chin K, Gray J, Lahad JP, Liang J, Mills GB, Meric-Bernstam F, Lin SY: BRIT1 regulates early DNA damage response, chromosomal integrity, and cancer. Cancer Cell. 2006, 10: 145-157. 10.1016/j.ccr.2006.07.002.View ArticlePubMedPubMed CentralGoogle Scholar
- Wood JL, Liang Y, Li K, Chen J: Microcephalin/MCPH1 associates with the Condensin II complex to function in homologous recombination repair. J Biol Chem. 2008, 283: 29586-29592. 10.1074/jbc.M804080200.View ArticlePubMedPubMed CentralGoogle Scholar
- Peng G, Yim EK, Dai H, Jackson AP, van der Burgt I, Pan MR, Hu R, Li K, Lin SY: BRIT1/MCPH1 links chromatin remodeling to DNA damage response. Nat Cell Biol. 2009, 11: 865-872. 10.1038/ncb1895.View ArticlePubMedPubMed CentralGoogle Scholar
- Wu X, Mondal G, Wang X, Wu J, Yang L, Pankratz VS, Rowley M, Couch FJ: Microcephalin regulates BRCA2 and Rad51-associated DNA double-strand break repair. Cancer Res. 2009, 69: 5531-5536. 10.1158/0008-5472.CAN-08-4834.View ArticlePubMedPubMed CentralGoogle Scholar
- Liang Y, Gao H, Lin SY, Peng G, Huang X, Zhang P, Goss JA, Brunicardi FC, Multani AS, Chang S, Li K: BRIT1/MCPH1 is essential for mitotic and meiotic recombination DNA repair and maintaining genomic stability in mice. PLoS Genet. 2010, 6: e1000826-10.1371/journal.pgen.1000826.View ArticlePubMedPubMed CentralGoogle Scholar
- Jackson AP, Eastwood H, Bell SM, Adu J, Toomes C, Carr IM, Roberts E, Hampshire DJ, Crow YJ, Mighell AJ, Karbani G, Jafri H, Rashid Y, Mueller RF, Markham AF, Woods CG: Identification of microcephalin, a protein implicated in determining the size of the human brain. Am J Hum Genet. 2002, 71: 136-142. 10.1086/341283.View ArticlePubMedPubMed CentralGoogle Scholar
- Woods CG, Bond J, Enard W: Autosomal recessive primary microcephaly (MCPH): a review of clinical, molecular, and evolutionary findings. Am J Hum Genet. 2005, 76: 717-728. 10.1086/429930.View ArticlePubMedPubMed CentralGoogle Scholar
- Cox J, Jackson AP, Bond J, Woods CG: What primary microcephaly can tell us about brain growth. Trends Mol Med. 2006, 12: 358-366. 10.1016/j.molmed.2006.06.006.View ArticlePubMedGoogle Scholar
- O'Driscoll M, Jeggo P: The role of double-strand break repair--insights from human genetics. Nat Rev Genet. 2006, 7: 45-54.View ArticlePubMedGoogle Scholar
- Goodman M, Sterner KN, Islam M, Uddin M, Sherwood CC, Hof PR, Hou ZC, Lipovich L, Jia H, Grossman LI, Wildman DE: Phylogenomic analyses reveal convergent patterns of adaptive evolution in elephant and human ancestries. Proc Nat Acad Sci USA. 2009, 106: 20824-20829. 10.1073/pnas.0911239106.View ArticlePubMedPubMed CentralGoogle Scholar
- Thompson JD, Higgins DG, Gibson TJ: CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994, 22: 4673-4680. 10.1093/nar/22.22.4673.View ArticlePubMedPubMed CentralGoogle Scholar
- Yang Z: PAML 4: a program package for phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007, 24: 1586-1591. 10.1093/molbev/msm088.View ArticlePubMedGoogle Scholar
- Murphy WJ, Eizirik E, Johnson WE, Zhang YP, Ryder OA, O'Brien SJ: Molecular phylogenetics and the origins of placental mammals. Nature. 2001, 409: 614-618. 10.1038/35054550.View ArticlePubMedGoogle Scholar
- Springer MS, Burk-Herrick A, Meredith R, Eizirik E, Teeling E, O'Brien SJ, Murphy WJ: The adequacy of morphology for reconstructing the early history of placental mammals. Syst Biol. 2007, 56: 673-684. 10.1080/10635150701491149.View ArticlePubMedGoogle Scholar
- Fabre PH, Rodrigues A, Douzery EJP: Patterns of macroevolution among Primates inferred from a supermatrix of mitochondrial and nuclear DNA. Mol Phylogenet Evol. 2009, 53: 808-825. 10.1016/j.ympev.2009.08.004.View ArticlePubMedGoogle Scholar
- McGowen MR, Spaulding M, Gatesy J: Divergence date estimation and a comprehensive molecular tree of extant cetaceans. Mol Phylogenet Evol. 2009, 53: 891-906. 10.1016/j.ympev.2009.08.018.View ArticlePubMedGoogle Scholar
- Schwerdtfeger WK, Oelschläger HA, Stephan H: Quantitative neuroanatomy of the brain of the La Plata dolphin, Pontoporia blainvillei. Anat Embryol. 1984, 170: 11-19. 10.1007/BF00319453.View ArticlePubMedGoogle Scholar
- Tarpley RJ, Ridgway SH: Corpus callosum size in delphinid cetaceans. Brain Behav Evol. 1994, 44: 156-165. 10.1159/000113587.View ArticlePubMedGoogle Scholar
- Jefferson TA, Webber MA, Pitman RL: Marine Mammals of the World: A Comprehensive Guide to their Identification. 2008, London: Academic PressGoogle Scholar
- Pagel M: Inferring the historical patterns of biological evolution. Nature. 1999, 401: 877-884. 10.1038/44766.View ArticlePubMedGoogle Scholar
- Pagel M, Meade A, Barker D: Bayesian estimation of ancestral character states on phylogenies. Syst Biol. 2004, 53: 673-684. 10.1080/10635150490522232.View ArticlePubMedGoogle Scholar
- McDonald JH, Kreitman M: Adaptive protein evolution at the Adh locus in Drosophila. Nature. 1991, 351: 652-654. 10.1038/351652a0.View ArticlePubMedGoogle Scholar
- Nikolaev SI, Montoya-Burgos JI, Popadin K, Parand L, Margulies EH, National Institutes of Health Intramural Sequencing Center Comparative Sequencing Program, Antonarakis SE: Life-history traits drive the evolutionary rates of mammalian coding and noncoding genomic elements. Proc Nat Acad Sci USA. 2007, 104: 20443-20448. 10.1073/pnas.0705658104.View ArticlePubMedPubMed CentralGoogle Scholar
- Lartillot N, Poujol R: A phylogenetic model for investigating correlated evolution of substitution rates and continuous phenotypic characters. Mol Biol Evol. 2011, 28: 729-744. 10.1093/molbev/msq244.View ArticlePubMedGoogle Scholar
- Chatterjee HJ, Ho SYW, Barnes I, Groves C: Estimating the phylogeny and divergence times of primates using the supermatrix approach. BMC Evol Biol. 2009, 9: 259-10.1186/1471-2148-9-259.View ArticlePubMedPubMed CentralGoogle Scholar
- Jansa SA, Forsman JF, Voss RS: Different patterns of selection on the nuclear genes IRBP and DMP-1 affect the efficiency but not the outcome of phylogeny estimation for didelphid marsupials. Mol Phylogenet Evol. 2006, 38: 363-380. 10.1016/j.ympev.2005.06.007.View ArticlePubMedGoogle Scholar
- Gatesy J, Swanson W: Adaptive evolution and phylogenetic utility of ACR (acrosin), a rapidly evolving mammalian fertilization gene. J Mammal. 2007, 88: 32-42. 10.1644/05-MAMM-S-345R1.1.View ArticleGoogle Scholar
- Butti C, Sherwood CC, Hakeem AY, Allman JM, Hof PR: : Total number and volume of Von Economo neurons in the cerebral cortex of cetaceans. J Comp Neur. 2009, 515: 243-259. 10.1002/cne.22055.View ArticlePubMedGoogle Scholar
- Gibbs RA, Rate Genome Sequencing Project Consortium, et al: Genome sequence of the brown Norway rat yields insights into mammalian evolution. Nature. 2004, 428: 493-521. 10.1038/nature02426.View ArticlePubMedGoogle Scholar
- Gilbert SL, Dobyns WB, Lahn BT: Genetic links between brain development and brain evolution. Nat Rev Genet. 2005, 6: 581-590. 10.1038/nrg1634.View ArticlePubMedGoogle Scholar
- George JC, Bada J, Zeh J, Scott L, Brown SE, O'Hara T, Suydam R: Age and growth estimates of bowhead whales (Balaena mysticetus) via aspartic acid racemization. Can J Zool. 1999, 77: 571-580. 10.1139/cjz-77-4-571.View ArticleGoogle Scholar
- Frazer JFD, Huggett ASG: Specific foetal growth rates of cetaceans. J Zool Lond. 1973, 169: 111-126. 10.1111/j.1469-7998.1973.tb04656.x.View ArticleGoogle Scholar
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