- Email: [email protected]
Morris Goodman’s hominoid rate slowdown: The importance of being neutral
Molecular Phylogenetics and Evolution 66 (2013) 569–574
Contents lists available at SciVerse ScienceDirect
Molecular Phylogenetics and Evolution journal homepage: www.elsevier.com/locate/ympev
Review
Morris Goodman’s hominoid rate slowdown: The importance of being neutral Soojin V. Yi ⇑ School of Biology, 310 Ferst Drive, Georgia Institute of Technology, Atlanta, GA 30332, United States
a r t i c l e
i n f o
Article history: Available online 10 August 2012 Keywords: Generation time effect Hominoid rate slowdown Neutral mutations Primate genomics
a b s t r a c t Half a century ago, when the field of molecular evolution did not even exist, Morris Goodman analyzed profiles of immunological interactions between species and reached the following two remarkable conclusions: first, protein evolution slowed down in the human lineage compared to other primate lineages; second, this slowdown was more pronounced for proteins whose functions were likely to be neutral. It took several decades of research to fully grasp these ideas and document the pattern of hominoid rate slowdown. Along the way, studies of hominoid rate slowdown led to major progresses in understanding determinants of neutral molecular evolution, which in turn is used to calibrate rates of adaptive evolution. Furthermore, the growing knowledge on the origin of mutations provides a basis for understanding differential evolutionary rates between sex chromosomes and autosomes, which has deep implications for inferring human evolutionary histories, and other aspects of molecular evolution. Primate genomics in particular stand to provide critical information in these pursuits, due to the abundance of genomic data, relatively rich documentation of life history traits, and several model systems, including our own species. Ó 2012 Elsevier Inc. All rights reserved.
Contents 1. 2. 3. 4. 5.
Morris Goodman’s hominoid rate slowdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Early reception and relationship to the debate between molecular clock hypothesis and generation time effect hypothesis . . . . . . . . . . . . . . . Continued controversy on hominoid rate slowdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genomic analyses of hominoid rate slowdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neutral evolutionary rate variation: current and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Influence of other life history traits on evolutionary rate variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Evolutionary rates of sex chromosomes and autosomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3. Influence of mutational origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Morris Goodman’s hominoid rate slowdown In the late 1950s, Morris Goodman was investigating variation of immunological cross-reactions between species across different proteins. One of his hypotheses was that proteins which function in early developmental stages (such as fetal stages) were more conserved than proteins that function in later developmental stages (such as adult stages) (Goodman, 1961, 1963). Proposed more than five decades ago, this hypothesis is still of significant interest today. In fact, whether evolutionary constraints are stron⇑ Fax: +1 404 894 2295. E-mail address: [email protected] 1055-7903/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ympev.2012.07.031
569 570 570 570 571 571 572 572 573 573
ger for proteins expressed in early versus late developmental stages is a topic of active current research, being tackled by the most recent molecular techniques (Domazet-Loso and Tautz, 2010; Kalinka et al., 2010; Roux and Robinson-Rechavi, 2008). This is an example of a recurring theme when re-visiting Morris Goodman’s work: his scientific hypotheses and insights are, simply put, timeless. From his studies of extensive immunological cross-profiling of different types of proteins, Goodman noticed an interesting general trend among serum proteins. For a wide range of serum proteins, humans generally exhibited only small antigenic differences from orangutans and gibbons, and almost no difference from gorillas and chimpanzees. In comparison, the same proteins showed
570
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
distinctive immunological difference between other mammalian groups. For example, the serum albumins exhibited almost no immunological differences between apes, yet a clear difference was found between humans and Old World monkeys (Goodman, 1961). Based upon these findings, he proposed that rates of molecular evolution were slower in the primate lineage leading to humans compared to in other lineages (Goodman, 1961, 1962a,b, 1963). Importantly, he noted a substantial variation among different types of proteins. For instance, the serum albumin, which functions during pregnancy, evolved at a relatively similar rate in humans and gibbons. In contrast, the gamma globulin evolved at a faster rate than serum albumin, since gibbon and Old World monkey gamma globulins could be distinguished from human gamma globulin (Goodman, 1960). Goodman reasoned that such variation across proteins had to do with the difference in their relative functional importance. For example, while the serum albumin is synthesized during pregnancy and play an important role in immunological crosstalk between the fetus and the mother, gamma globulin is synthesized after birth and may be relatively free from selective pressure during fetal growth. He posited that the difference in the degree of hominoid rate slowdown across proteins was due to their difference in the numbers of functionally ‘neutral’ sites. Thus he interpreted that the hominoid rate slowdown was largely caused by substitutions that were functionally ‘neutral’. This remarkable hypothesis was put forward long before the neutral theory of molecular evolution was first introduced.
2. Early reception and relationship to the debate between molecular clock hypothesis and generation time effect hypothesis Goodman’s first papers on the hominoid rate slowdown, however, were initially not widely accepted. Around the same time, Zukerkandl and Pauling published a paper representing a seemingly contradictory idea to those of Goodman. Combining protein sequence data from hemoglobin, cytochrome C and fibrinopeptides, Zuckerkandl and Pauling (1965) noted that protein sequence changes occur roughly proportional to the time since species divergence. They compared the constant rates of amino acid substitutions over time to regular ‘ticks’ of a clock, and coined the term ‘molecular clock’. This study was received much better than Goodman’s proposal of different rates among lineages. For example, Allan Wilson, a well-known evolutionary biologist, readily accepted the idea of using the molecular clock to date evolutionary events. In a widely cited paper (Sarich and Wilson, 1967), his group directly criticized Goodman’s papers and proposed that serum proteins evolved constantly over time. Another prominent scientific figure who embraced the idea of a constant molecular clock was Motoo Kimura. He proposed that many mutations are in effect ‘neutral’ in terms of the fitness of the individuals, and the evolutionary rates of proteins are largely determined by chance effects on such neutral mutations (Kimura, 1983). In a seminal paper he demonstrated that for neutral mutations, evolutionary rates were approximately equal to the underlying mutation rates (Kimura, 1968). It follows that if neutral mutation rates were constant over time, protein evolutionary rates should also be constant over time. Kimura thus considered the molecular clock observation by Zukerkandl and Pauling as a perfect fit to his neutral theory of molecular evolution (Kimura, 1968, 1969). The idea of a constant molecular clock, or constant mutation rates over time, however, was at odds with the observations from classical genetic studies, which often demonstrated that mutations occurred constantly over generations (Sturtevant, 1965). For example, Haldane (1947) concluded that mutation rates differ between
males and females, indicating that mutation rates correlated with the number of cell divisions in germlines. Muller (1954) further proposed that the majority of spontaneous mutations arose from errors during DNA replication. If germline mutations originated during DNA replication events, then the number of germline mutations would increase with the number of generations each species undergoes per unit time. In other words, mutation rates should be related to the number of generations, rather than the number of years. Consequently, the so-called ‘generation time effect hypothesis’ posits that evolutionary rates are slower for species with longer generation times compared to those with shorter generation times. Hominoid rate slowdown is a prime example of the generation time effect since hominoids (humans and great apes) exhibit markedly long generation times compared to Old World monkeys (Goodman, 1961, 1962a, 1985; Li, 1997). 3. Continued controversy on hominoid rate slowdown Goodman’s group at Wayne State University continued to generate and analyze comparative sequence data to elucidate patterns and causes of evolutionary rate variation among species. In 1981, Goodman analyzed extensive amino acid sequence data available at that time (551 proteins from 233 species) and showed that a constant molecular clock assumption generally underestimated primate divergence times (Goodman, 1981). In particular, the most pronounced discrepancy occurred when dating hominoid divergence. For example, the constant molecular clock method estimated the divergence between humans and chimpanzees as 1.3 MYA, contradictory to fossil records (Goodman, 1981). His group also generated much of the early DNA sequence data from hominoids and other primates (including those from gamma-globin genes and the pseudogene locus near the beta-globin gene clusters), and demonstrated that DNA sequences indeed evolve slowly in hominoids compared to Old World monkeys and other primates (e.g., Koop et al., 1986; Bailey et al., 1991). Data from other lineages also began to support the generation time effect hypothesis. Notably, Wu and Li (1985) analyzed DNA sequence data of eleven genes from rodents and human and showed that rodents evolve significantly faster than human. By then even Kimura himself considered the generation time effect as a better fit to his theory of neutral molecular evolution because mutation rates should be constant over generation, rather than per unit time (personal communication between Wen-Hsiung Li and Motto Kimura). Although data supporting the generation time effect and hominoid slowdown accumulated throughout 1980s and 1990s, the molecular evolution community remained deeply divided over the issue of rate constancy. Many scientists embraced the idea of a constant molecular clock (e.g., Wilson et al., 1987), which was used in several influential papers to date species divergence (e.g., Kumar and Hedges, 1998). Studies demonstrating significant rate differences were criticized for their small sample sizes and potentially inaccurate phylogenies (Easteal, 1988, 1991; Easteal and Collet, 1994). For example, Herbert and Easteal (1996) pointed out that the b-globin gene region exhibits a particularly strong trend toward slower rate in the hominoid lineages, and stated that there is little evidence of a global rate difference between the Old World monkeys and hominoids. The debate continued well into the early 2000s (e.g., Kumar and Subramanian, 2002). 4. Genomic analyses of hominoid rate slowdown Much of the debate on the hominoid rate slowdown was because the numbers of genes analyzed in pre-genomic studies were small, and thus they were potentially susceptible to bias due to a few data points (such as in the b-globin gene region). This problem
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
571
Hominoids human chimpanzee
Old World monkeys baboon macaque
New World monkeys
marmoset Fig. 1. Evolutionary rate differences consistent with generation-time effect in primates. As noted in the text, there are several well-established trends of generation time effect in primates (indicated by ); lower rates in human compared to chimpanzees (Elango et al., 2006); lower evolutionary rates in hominoids versus Old World monkeys (e.g., Yi et al., 2002; Steiper et al., 2004; Kim et al., 2006); significant variation in Old World monkeys concordant with the generation time effect (Elango et al., 2009): and a lower evolutionary rate in Old World monkeys versus the marmoset (Wildman et al., 2003; Steiper and Young, 2006). Different evolutionary rates are depicted as different branch lengths.
was resolved when genomic data became widely available following the genomics revolution during the last decade. One of the first such studies used 880 kbps of non-coding sequence from humans and chimpanzees and 15 kbps of intron sequence data from Old World monkeys and hominoids, and demonstrated that evolutionary rates in the hominoids are approximately 30% lower than in the Old World monkey lineages (Yi et al., 2002). Another study analyzed 150 kbps data from hominoids and Old World monkeys and reported a similar pattern (Steiper et al., 2004). Genome-wide comparison using 28 Mbps of sequence alignments of the human, macaque and the marmoset genomes reached the same conclusion (Kim et al., 2006). Thus, the hominoid rate slowdown hypothesis is unambiguously supported by genomic scale data. Available genome-scale sequence data from primates further allowed comparisons between other primate lineages, and as a result, the generation time effect has been observed in several additional evolutionary scales in primates (Fig. 1). First, the common marmoset, a New World monkey with shorter generation times than hominoids or Old World monkeys, shows even faster evolutionary rates than Old World monkeys (Steiper and Young, 2006). Goodman’s group also demonstrated that rates are slower in hominoids and Old World monkeys than in non-catarrhine primates using genomic comparisons (Wildman et al., 2003). Second, at a smaller scale, rate differences have been observed between humans and chimpanzees. Based upon approximately 63 million base pair alignments between humans and chimpanzees, it was shown that the human genome is evolving slightly but significantly slower than that of the chimpanzee genome (Elango et al., 2006). Since the human generation time has markedly increased since the divergence of humans and chimpanzees, and the long generation time is considered to be a hallmark of human evolution (Wood, 2000; Wood and Collard, 1999), this observation is in accord with the generation time effect. Third, evolutionary rate variation in accord with generation time effect has been observed within Old World monkeys. Elango et al. (2009) analyzed over
8 Mbps of genomic sequence alignments between four Old World monkey species, and observed that evolutionary rates differ significantly among the four different species, in accordance with the generation time effect. For example, baboons, which are larger and have longer lifespans than macaques, evolve slower than the rhesus macaque lineage (Elango et al., 2009; Peng et al., 2009). 5. Neutral evolutionary rate variation: current and future directions Since the initial proposal of the hominoid rate slowdown by Goodman over half a century ago (Goodman, 1961, 1962a,b, 1963), we have come a long way in appreciating the pattern of evolutionary rate variation between lineages. Understanding the variation of neutral mutation rates has become even more important in the genomics age. One of the goals of functional and comparative genomics is to identify regions that are under functional constraint, or adaptive evolution. To determine the significance of such regions, a reliable knowledge of neutral mutation rates is critical (Ellegren et al., 2003; Wolfe and Li, 2003). Studies of hominoid rate slowdown have contributed immensely to our understanding of neutral mutation rate variation among lineages, and also to the rate difference between the sex chromosomes and autosomes (see below). However, even though the generation time effect is relatively well supported, it cannot explain all the variability of evolutionary rates (Huttley et al., 2007). Clearly, factors other than generation times contribute to evolutionary rate variation. Below we discuss several promising directions of current and future research. 5.1. Influence of other life history traits on evolutionary rate variation Life history traits other than strict generation time may affect evolutionary rates (Martin and Palumbi, 1993; Møller and Cuervo, 2003; Santos, 2012; Seluanov et al., 2007; Speakman, 2005; Welch
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
et al., 2008). Metabolic rates may influence evolutionary rates because metabolism increases mutations due to the mutagenic effects of oxygen radicals, or because organisms with higher metabolic rates may have increased rates of DNA synthesis (Martin and Palumbi, 1993; Santos, 2012). Body mass is often used as a proxy for metabolic rates, although there are other factors that influence body mass, such as brain size, population density, and reproductive effort (Kappelman, 1996; LaBarbera, 1989). Maximum lifespan is obviously related to generation time, but also to the efficiency of DNA repair and aging (Seluanov et al., 2007). In addition, sexual selection can increase mutation rates (Agrawal, 2001; Møller and Cuervo, 2003; Siller, 2001). Many of these life history traits are correlated amongst themselves, making it difficult to discern effects of individual variables on evolutionary rates. It is also important to take into account the underlying phylogeny: life history traits may be similar because of shared evolutionary history (phylogeny), and it is necessary to account for this effect (Felsenstein, 1985; Harvey et al., 1987; Nunn and Barton, 2001; Pagel, 1994). In addition, it is desirable to compare closely related species that share similar biology. For example, comparing rodents and primates may be confounded by changes in other developmental and metabolic traits. Until recently, researchers simply did not have suitable data to account for all of these concerns. With the rapid advance of techniques to garner genome-wide sequence data from many species, we may soon be in a position to overcome these difficulties. Primates are a very promising group of organisms in this respect because there are diverse species with ample sequence data, and relatively welldocumented life history variation (e.g., Tsantes and Steiper, 2009). 5.2. Evolutionary rates of sex chromosomes and autosomes Generation time effects share a common molecular mechanism with the so-called ‘male-driven evolution’ phenomenon. Haldane (1947) first proposed that mutation rates are higher in the male germlines compared to the female germlines. If mutations generally arise from errors during DNA replication, then males, who typically undergo a greater number of germline DNA replications during their lifetime compared to females, will accumulate more mutations than females. Miyata et al. (1987) proposed a method to test the degree of male mutation bias by comparing the evolutionary rates of X-lined, Y-linked, and autosomal loci. Studies utilizing this approach generally agreed with the conclusion that mutation rates in mammals are biased toward males (Shimmin et al., 1993; Li et al., 2002). However, most genome-scale analyses of male mutation bias have compared evolutionary rates of the autosomes to the X chromosomes, because most sequenced genomes of primates and mammals are from females. If DNA replication is the main source of mutations, the results from the comparisons of the X chromosome to autosomes should be similar to those from the comparisons between the Y chromosome to autosomes or between X and Y chromosomes (Miyata et al., 1987). In contrast to this prediction, a recent study claimed that the Y chromosome is not necessarily evolving faster than autosomes (Pink et al., 2009), and posited that the data is not consistent with a simple model assuming asymmetric germline DNA replications as the main determinant of rate difference between the sex chromosomes and autosomes. Sequencing of the Y chromosome from other species (e.g., Hughes et al., 2012) should provide an opportunity to examine variation of male driven evolution. Furthermore, the degree of male mutation bias should vary across different taxa due to variations in life history traits. For example, male mutation bias may positively correlate with the degree of sperm competition (Blumenstiel, 2007; Presgraves and Yi, 2009) as well as generation time (Bartosch-Härlid et al., 2003;
Goetting-Minesky and Makova, 2006). Studies have begun to address these questions using genomic data from mammals, in particular primates (Sayres et al., 2011; Xu et al., 2012).
5.3. Influence of mutational origin The generation time effect hypothesis is based upon the idea that most mutations arise via errors during DNA replication. However, some mutations originate via molecular mechanisms that are relatively independent of DNA replication. A notable example is mutations caused by DNA methylation. In animal genomes, DNA methylation predominantly occurs at cytosines followed by guanine (called ‘CpG’ dinucleotides). Methylated cytosines are subject to spontaneous deamination to thymines, causing C to T mutations (Duncan and Miller, 1980). This type of mutation is a prominent source of point mutations in mammals and other vertebrates. In particular, they occur over an order of magnitude more frequently than other types of mutations in the human genome (Elango et al., 2008), and account for nearly a quarter of all point mutations between the human and chimpanzee genomes (The Chimpanzee Sequencing and Analysis Consortium, 2005). Since DNA methylation is not confined to replicating DNA, such mutations may exhibit different patterns of evolutionary rate variation compared to other mutations. To test this prediction, one study analyzed mutations at CpGs (predominantly caused by DNA methylation) and those at non-CpGs (predominantly caused by DNA replication) in hominoids and Old World monkeys separately (Kim et al., 2006). Mutations occurring at non-CpGs exhibited significant rate difference between hominoids and Old World monkeys, concordant with the hominoid rate slowdown. In contrast, mutations at CpGs showed no rate difference between hominoids and Old World monkeys (Fig. 2). Thus, rate differences are highly dependent on their mutational origins (Kim et al., 2006). On the other hand, there is some indication that mutation rates caused by DNA methylation vary according to factors such as body temperature (Fryxell and Zuckerkandl, 2000; Varriale and Bernardi, 2006) and/or other physiological factors. Accounting for suscepti-
Mutations predominantly arise due to DNA methylation Other mutations
1.5 1.25
KO/KH
572
1 0.75 0.5 0.25 0
repetitive
non-repetitive
total
Fig. 2. Contrasting patterns of hominoid rate slowdown for mutations arising due to distinctive molecular mechanisms. The Y-axis represents the ratio of evolutionary distance between two Old World monkeys (baboon and macaque) and between two hominoids (human and chimpanzee), species pairs that have diverged approximately the same amount of time ago. Thus this ratio captures the ratio of evolutionary rates in Old World monkeys and hominoids during approximately similar evolutionary times (Kim et al., 2006). Mutations at CpGs, which mainly arise due to DNA methylation, exhibit no difference between the Old World monkeys and the hominoids (KO/KH is approximately 1). Other types of mutations, presumably arising during DNA replication, however exhibit strong hominoid rate slowdown (KO/KH is approximately 1.3). Figure modified from Kim et al. (2006).
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
bility toward different types of mutations in different genomic regions and across different taxa should increase our ability to interpret, and ultimately model, genomic evolutionary rate variation. Acknowledgement This study is supported by NSF grants (MCB-0950896 and BCS0751481) to SVY. References Agrawal, A.F., 2001. Sexual selection and the maintenance of sexual reproduction. Nature 411, 692–695. Bailey, W., Fitch, D., Tagle, D., Czelusniak, J., Slightom, J., Goodman, M., 1991. Molecular evolution of the psi eta-globin gene locus: gibbon phylogeny and the hominoid slowdown. Mol. Biol. Evol. 8, 155–184. Bartosch-Härlid, A., Berlin, S., Smith, N.G.C., Møller, A.P., Ellegren, H., 2003. Life history and the male mutation bias. Evolution 57, 2398–2406. Blumenstiel, J.P., 2007. Sperm competition can drive a male-biased mutation rate. J. Theor. Biol. 249, 624–632. The Chimpanzee Sequencing and Analysis Consortium, 2005. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 437, 69– 87. Domazet-Loso, T., Tautz, D., 2010. A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns. Nature 468, 815–818. Duncan, B.K., Miller, J.H., 1980. Mutagenic deamination of cytosine residues in DNA. Nature 287, 560–561. Easteal, S., 1988. Rate constancy of globin gene evolution in placental mammals. Proc. Natl. Acad. Sci. USA 85, 7622–7636. Easteal, S., 1991. The relative rate of DNA evolution in primates. Mol. Biol. Evol. 8, 115–127. Easteal, S., Collet, C., 1994. Consistent variation in amino-acid substitution rate, despite uniformity of mutation rate: protein evolution in mammals is not neutral. Mol. Biol. Evol. 11, 643–647. Elango, N., Kim, S.-H., Program, N.C.S., Vigoda, E., Yi, S.V., 2008. Mutations of different molecular origins exhibit contrasting patterns of regional substitution rate variation. PLoS Comp. Biol. 4, e1000015. Elango, N., Lee, J., Peng, Z., Loh, Y.-H.E., Yi, S.V., 2009. Evolutionary rate variation in Old World monkeys. Biol. Lett. 5, 405–408. Elango, N., Thomas, J.W., Program, N.C.S., Yi, S.V., 2006. Variable molecular clocks in hominoids. Proc. Natl. Acad. Sci. USA 103, 1370–1375. Ellegren, H., Smith, N.G., Webster, M.T., 2003. Mutation rate variation in the mammalian genome. Curr. Opin. Genet. Dev. 13, 562–568. Felsenstein, J., 1985. Phylogenies and the comparative method. Am. Nat. 125, 1–15. Fryxell, K.J., Zuckerkandl, E., 2000. Cytosine deamination plays a primary role in the evolution of mammalian isochores. Mol. Biol. Evol. 17, 1371–1383. Goetting-Minesky, M., Makova, K., 2006. Mammalian male mutation bias: impacts of generation time and regional variation in substitution rates. J. Mol. Evol. 63, 537–544. Goodman, M., 1960. The species specificity of proteins as observed in the wilson comparative analyses plates. Am. Nat. 94, 184–186. Goodman, M., 1961. The role of immunologic differences in the phyletic development of human behavior. Hum. Biol. 33, 131–162. Goodman, M., 1962a. Evolution of the immunologic species specificity of human serum proteins. Hum. Biol. 34, 104–150. Goodman, M., 1962b. Immunochemistry of the primates and primate evolution. Ann. N.Y. Acad. Sci. 102, 219–234. Goodman, M., 1963. Man’s place in the phylogeny of the primates as reflected in serum proteins. In: Washburn, S.L. (Ed.), Classification and Human Evolution. Aldine Press, Chicago, pp. 204–234. Goodman, M., 1981. Decoding the pattern of protein evolution. Prog. Biophys. Mol. Biol. 38, 105–164. Goodman, M., 1985. Rates of molecular evolution: the hominoid slowdown. BioEssays 3, 9–14. Haldane, J.B.S., 1947. The mutation rate of the gene for hemophilia, and its segregation ratios in males and females. Ann. Eugen. 13, 262–272. Harvey, P.H., Martin, R.D., Clutton-Brock, T.H., 1987. Life histories in comparative perspective. In: Al., S.B.B.e. (Ed.), Primate Societies, vol. 4. Springer, berlin, pp. 69–82. Herbert, G., Easteal, S., 1996. Relative rates of nuclear DNA evolution in human and Old World monkey lineages. Mol. Biol. Evol. 13, 1054–1057. Hughes, J.F., Skaletsky, H., Brown, L.G., Pyntikova, T., Graves, T., Fulton, R.S., Dugan, S., Ding, Y., Buhay, C.J., Kremitzki, C., Wang, Q., Shen, H., Holder, M., Villasana, D., Nazareth, L.V., Cree, A., Courtney, L., Veizer, J., Kotkiewicz, H., Cho, T.-J., Koutseva, N., Rozen, S., Muzny, D.M., Warren, W.C., Gibbs, R.A., Wilson, R.K., Page, D.C., 2012. Strict evolutionary conservation followed rapid gene loss on human and rhesus Y chromosomes. Nature 483, 82–86. Huttley, G.A., Wakefield, M.J., Easteal, S., 2007. Rates of genome evolution and branching order from whole genome analysis. Mol. Biol. Evol. 24, 1722–1730. Kalinka, A.T., Varga, K.M., Gerrard, D.T., Preibisch, S., Corcoran, D.L., Jarrells, J., Ohler, U., Bergman, C.M., Tomancak, P., 2010. Gene expression divergence recapitulates the developmental hourglass model. Nature 468, 811–814.
573
Kappelman, J., 1996. The evolution of body mass and relative brain size in fossil hominids. J. Hum. Evol. 30, 243–276. Kim, S.-H., Elango, N., Warden, C.W., Vigoda, E., Yi, S., 2006. Heterogeneous genomic molecular clocks in primates. PLoS Genet. 2, e163. Kimura, M., 1968. Evolutionary rate at the molecular level. Nature 217, 624–626. Kimura, M., 1969. The rate of molecular evolution considered from the standpoint of population genetics. Proc. Natl. Acad. Sci. USA 63, 1181–1188. Kimura, M., 1983. The neutral theory of molecular evolution. Cambridge University Press, Cambridge, UK. Koop, B.F., Goodman, M., Xu, P., Chan, K., Slightom, J.L., 1986. Primate [eta]-globin DNA sequences and man’s place among the great apes. Nature 319, 234– 238. Kumar, S., Hedges, S.B., 1998. A molecular timescale for vertebrate evolution. Nature 392, 917–920. Kumar, S., Subramanian, S., 2002. Mutation rates in mammalian genomes. Proc. Natl. Acad. Sci. USA 99, 803–808. LaBarbera, M., 1989. Analyzing body size as a factor in ecology and evolution. Ann. Rev. Ecol. Syst. 20, 97–117. Li, W.-H., 1997. Molecular Evolution. Sinauer, Sunderland, MA. Li, W.-H., Yi, S., Makova, K., 2002. Male-driven evolution. Curr. Opin. Genet. Develop. 12, 650–656. Martin, A.P., Palumbi, S.R., 1993. Body size, metabolic rate, generation time, and the molecular clock. Proc. Natl. Acad. Sci. USA 90, 4087–4091. Miyata, T., Hayashida, H., Kuma, K., Mitsuyasu, K., Yasunaga, T., 1987. Male-driven molecular evolution: a model and nucleotide sequence analysis. Cold Spring Harbor Symp. Quant. Biol. 52, 863–867. Møller, A.P., Cuervo, J.J., 2003. Sexual selection, germline mutation rate and sperm competition. BMC Evol. Biol. 3, 6. Muller, H.J., 1954. The nature of the genetic effects produced by radiation. In: Hollaender, A. (Ed.), Radiation Biology, vol. 4. McGraw-Hill, New York, pp. 351– 473. Nunn, C.L., Barton, R.A., 2001. Comparative methods for studying primate adaptation and allometry. Evol. Anthropol.: Issues News Rev. 10, 81–98. Pagel, M., 1994. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proc. Biol. Sci. 255, 37–45. Peng, Z., Elango, N., Wildman, D., Yi, S., 2009. Primate phylogenomics: developing numerous nuclear non-coding, non-repetitive markers for ecological and phylogenetic applications and analysis of evolutionary rate variation. BMC Genome 10, 247. Pink, C.J., Swaminathan, S.K., Dunham, I., Rogers, J., Ward, A., Hurst, L.D., 2009. Evidence that replication-associated mutation alone does not explain betweenchromosome differences in substitution rates. Genome Biol. Evol. 1, 13–22. Presgraves, D.C., Yi, S., 2009. Doubts about complex speciation between humans and chimpanzees. Trends Ecol. Evol. 24, 533–540. Roux, J., Robinson-Rechavi, M., 2008. Developmental constraints on vertebrate genome evolution. PLoS Genet. 4, e1000311. Santos, J.C., 2012. Fast molecular evolution associated with high active metabolic rates in poison frogs. Mol. Biol. Evol. 29, 2001–2018. Sarich, V.M., Wilson, A.C., 1967. Immunological time scale for hominid evolution. Science 158, 1200–1203. Sayres, M.A.W., Venditti, C., Pagel, M., Makova, K.D., 2011. Do variations in substitution rates and male mutation bias correlate with life-history traits? A study of 32 mammalian genomes. Evolution 65, 2800–2815. Seluanov, A., Chen, Z., Hine, C., Sasahara, T.H.C., Ribeiro, A.A.C.M., Catania, K.C., Presgraves, D.C., Gorbunova, V., 2007. Telomerase activity coevolves with body mass, not lifespan. Aging Cell 6, 45–52. Shimmin, L.C., Chang, B.H.J., Li, W.H., 1993. Male-driven evolution in DNA sequences. Nature 362, 745–747. Siller, S., 2001. Sexual selection and the maintenance of sex. Nature 411, 689– 692. Speakman, J.R., 2005. Correlations between physiology and lifespan – two widely ignored problems with comparative studies. Aging Cell 4, 167–175. Steiper, M.E., Young, N.M., 2006. Primate molecular divergence dates. Mol. Phylogenet. Evol. 41, 384–394. Steiper, M.E., Young, N.M., Sukrarna, T.Y., 2004. Genomic data support the hominoid slowdown and an early Oligocene estimate for the hominoid–cercopithecoid divergence. Proc. Natl. Acad. Sci. USA 101, 17021–17026. Sturtevant, A.H., 1965. A History of Genetics. Harper Low, New York. Tsantes, C., Steiper, M.E., 2009. Age at first reproduction explains rate variation in the strepsirrhine molecular clock. Proc. Natl. Acad. Sci. USA 106, 18165–18170. Varriale, A., Bernardi, G., 2006. DNA methylation and body temperature in fishes. Gene 385, 111–121. Welch, J.J., Bininda-emonds, O.R.P., Bromham, L., 2008. Correlates of substitution rate variation in mammalian protein-coding sequences. BMC Evol. Biol. 8, 53. Wildman, D.E., Uddin, M., Liu, G., Grossman, L.I., Goodman, M., 2003. Implications of natural selection in shaping 99.4% nonsynonymous DNA identity between humans and chimpanzees: enlarging genus Homo. Proc. Natl. Acad. Sci. USA 100, 7181–7188. Wilson, A.C., Ochman, H., Prager, E.M., 1987. Molecular time scale for evolution. Trends Genet. 3, 241–247. Wolfe, K.H., Li, W.-H., 2003. Molecular evolution meets the genomics revolution. Nat. Genet. 33, 255–265. Wood, B., 2000. Investigating human evolutionary history. J. Anat. 197, 3–17. Wood, B., Collard, M., 1999. The human genus. Science 284, 65–71. Wu, C.I., Li, W.H., 1985. Evidence for higher rates of nucleotide substitution in rodents than in man. Proc. Natl. Acad. Sci. USA 82, 1741–1745.
574
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
Xu, K., Oh, S., Park, T., Presgraves, D.C., Yi, S.V., 2012. Lineage-specific variation in slow- and fast-X evolution in primates. Evolution 66, 1751–1761. Yi, S., Ellsworth, D.L., Li, W.H., 2002. Slow molecular clocks in Old World monkeys, apes, and humans. Mol. Biol. Evol. 19, 2191–2198.
Zuckerkandl, E., Pauling, L.B., 1965. Evolutionary divergence and convergence in proteins. In: Bryson, V., Vogel, H.J. (Eds.), Evolving Genes and Proteins. Academic Press, New York, pp. 97–166.
Contents lists available at SciVerse ScienceDirect
Molecular Phylogenetics and Evolution journal homepage: www.elsevier.com/locate/ympev
Review
Morris Goodman’s hominoid rate slowdown: The importance of being neutral Soojin V. Yi ⇑ School of Biology, 310 Ferst Drive, Georgia Institute of Technology, Atlanta, GA 30332, United States
a r t i c l e
i n f o
Article history: Available online 10 August 2012 Keywords: Generation time effect Hominoid rate slowdown Neutral mutations Primate genomics
a b s t r a c t Half a century ago, when the field of molecular evolution did not even exist, Morris Goodman analyzed profiles of immunological interactions between species and reached the following two remarkable conclusions: first, protein evolution slowed down in the human lineage compared to other primate lineages; second, this slowdown was more pronounced for proteins whose functions were likely to be neutral. It took several decades of research to fully grasp these ideas and document the pattern of hominoid rate slowdown. Along the way, studies of hominoid rate slowdown led to major progresses in understanding determinants of neutral molecular evolution, which in turn is used to calibrate rates of adaptive evolution. Furthermore, the growing knowledge on the origin of mutations provides a basis for understanding differential evolutionary rates between sex chromosomes and autosomes, which has deep implications for inferring human evolutionary histories, and other aspects of molecular evolution. Primate genomics in particular stand to provide critical information in these pursuits, due to the abundance of genomic data, relatively rich documentation of life history traits, and several model systems, including our own species. Ó 2012 Elsevier Inc. All rights reserved.
Contents 1. 2. 3. 4. 5.
Morris Goodman’s hominoid rate slowdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Early reception and relationship to the debate between molecular clock hypothesis and generation time effect hypothesis . . . . . . . . . . . . . . . Continued controversy on hominoid rate slowdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Genomic analyses of hominoid rate slowdown . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Neutral evolutionary rate variation: current and future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Influence of other life history traits on evolutionary rate variation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Evolutionary rates of sex chromosomes and autosomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.3. Influence of mutational origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1. Morris Goodman’s hominoid rate slowdown In the late 1950s, Morris Goodman was investigating variation of immunological cross-reactions between species across different proteins. One of his hypotheses was that proteins which function in early developmental stages (such as fetal stages) were more conserved than proteins that function in later developmental stages (such as adult stages) (Goodman, 1961, 1963). Proposed more than five decades ago, this hypothesis is still of significant interest today. In fact, whether evolutionary constraints are stron⇑ Fax: +1 404 894 2295. E-mail address: [email protected] 1055-7903/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ympev.2012.07.031
569 570 570 570 571 571 572 572 573 573
ger for proteins expressed in early versus late developmental stages is a topic of active current research, being tackled by the most recent molecular techniques (Domazet-Loso and Tautz, 2010; Kalinka et al., 2010; Roux and Robinson-Rechavi, 2008). This is an example of a recurring theme when re-visiting Morris Goodman’s work: his scientific hypotheses and insights are, simply put, timeless. From his studies of extensive immunological cross-profiling of different types of proteins, Goodman noticed an interesting general trend among serum proteins. For a wide range of serum proteins, humans generally exhibited only small antigenic differences from orangutans and gibbons, and almost no difference from gorillas and chimpanzees. In comparison, the same proteins showed
570
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
distinctive immunological difference between other mammalian groups. For example, the serum albumins exhibited almost no immunological differences between apes, yet a clear difference was found between humans and Old World monkeys (Goodman, 1961). Based upon these findings, he proposed that rates of molecular evolution were slower in the primate lineage leading to humans compared to in other lineages (Goodman, 1961, 1962a,b, 1963). Importantly, he noted a substantial variation among different types of proteins. For instance, the serum albumin, which functions during pregnancy, evolved at a relatively similar rate in humans and gibbons. In contrast, the gamma globulin evolved at a faster rate than serum albumin, since gibbon and Old World monkey gamma globulins could be distinguished from human gamma globulin (Goodman, 1960). Goodman reasoned that such variation across proteins had to do with the difference in their relative functional importance. For example, while the serum albumin is synthesized during pregnancy and play an important role in immunological crosstalk between the fetus and the mother, gamma globulin is synthesized after birth and may be relatively free from selective pressure during fetal growth. He posited that the difference in the degree of hominoid rate slowdown across proteins was due to their difference in the numbers of functionally ‘neutral’ sites. Thus he interpreted that the hominoid rate slowdown was largely caused by substitutions that were functionally ‘neutral’. This remarkable hypothesis was put forward long before the neutral theory of molecular evolution was first introduced.
2. Early reception and relationship to the debate between molecular clock hypothesis and generation time effect hypothesis Goodman’s first papers on the hominoid rate slowdown, however, were initially not widely accepted. Around the same time, Zukerkandl and Pauling published a paper representing a seemingly contradictory idea to those of Goodman. Combining protein sequence data from hemoglobin, cytochrome C and fibrinopeptides, Zuckerkandl and Pauling (1965) noted that protein sequence changes occur roughly proportional to the time since species divergence. They compared the constant rates of amino acid substitutions over time to regular ‘ticks’ of a clock, and coined the term ‘molecular clock’. This study was received much better than Goodman’s proposal of different rates among lineages. For example, Allan Wilson, a well-known evolutionary biologist, readily accepted the idea of using the molecular clock to date evolutionary events. In a widely cited paper (Sarich and Wilson, 1967), his group directly criticized Goodman’s papers and proposed that serum proteins evolved constantly over time. Another prominent scientific figure who embraced the idea of a constant molecular clock was Motoo Kimura. He proposed that many mutations are in effect ‘neutral’ in terms of the fitness of the individuals, and the evolutionary rates of proteins are largely determined by chance effects on such neutral mutations (Kimura, 1983). In a seminal paper he demonstrated that for neutral mutations, evolutionary rates were approximately equal to the underlying mutation rates (Kimura, 1968). It follows that if neutral mutation rates were constant over time, protein evolutionary rates should also be constant over time. Kimura thus considered the molecular clock observation by Zukerkandl and Pauling as a perfect fit to his neutral theory of molecular evolution (Kimura, 1968, 1969). The idea of a constant molecular clock, or constant mutation rates over time, however, was at odds with the observations from classical genetic studies, which often demonstrated that mutations occurred constantly over generations (Sturtevant, 1965). For example, Haldane (1947) concluded that mutation rates differ between
males and females, indicating that mutation rates correlated with the number of cell divisions in germlines. Muller (1954) further proposed that the majority of spontaneous mutations arose from errors during DNA replication. If germline mutations originated during DNA replication events, then the number of germline mutations would increase with the number of generations each species undergoes per unit time. In other words, mutation rates should be related to the number of generations, rather than the number of years. Consequently, the so-called ‘generation time effect hypothesis’ posits that evolutionary rates are slower for species with longer generation times compared to those with shorter generation times. Hominoid rate slowdown is a prime example of the generation time effect since hominoids (humans and great apes) exhibit markedly long generation times compared to Old World monkeys (Goodman, 1961, 1962a, 1985; Li, 1997). 3. Continued controversy on hominoid rate slowdown Goodman’s group at Wayne State University continued to generate and analyze comparative sequence data to elucidate patterns and causes of evolutionary rate variation among species. In 1981, Goodman analyzed extensive amino acid sequence data available at that time (551 proteins from 233 species) and showed that a constant molecular clock assumption generally underestimated primate divergence times (Goodman, 1981). In particular, the most pronounced discrepancy occurred when dating hominoid divergence. For example, the constant molecular clock method estimated the divergence between humans and chimpanzees as 1.3 MYA, contradictory to fossil records (Goodman, 1981). His group also generated much of the early DNA sequence data from hominoids and other primates (including those from gamma-globin genes and the pseudogene locus near the beta-globin gene clusters), and demonstrated that DNA sequences indeed evolve slowly in hominoids compared to Old World monkeys and other primates (e.g., Koop et al., 1986; Bailey et al., 1991). Data from other lineages also began to support the generation time effect hypothesis. Notably, Wu and Li (1985) analyzed DNA sequence data of eleven genes from rodents and human and showed that rodents evolve significantly faster than human. By then even Kimura himself considered the generation time effect as a better fit to his theory of neutral molecular evolution because mutation rates should be constant over generation, rather than per unit time (personal communication between Wen-Hsiung Li and Motto Kimura). Although data supporting the generation time effect and hominoid slowdown accumulated throughout 1980s and 1990s, the molecular evolution community remained deeply divided over the issue of rate constancy. Many scientists embraced the idea of a constant molecular clock (e.g., Wilson et al., 1987), which was used in several influential papers to date species divergence (e.g., Kumar and Hedges, 1998). Studies demonstrating significant rate differences were criticized for their small sample sizes and potentially inaccurate phylogenies (Easteal, 1988, 1991; Easteal and Collet, 1994). For example, Herbert and Easteal (1996) pointed out that the b-globin gene region exhibits a particularly strong trend toward slower rate in the hominoid lineages, and stated that there is little evidence of a global rate difference between the Old World monkeys and hominoids. The debate continued well into the early 2000s (e.g., Kumar and Subramanian, 2002). 4. Genomic analyses of hominoid rate slowdown Much of the debate on the hominoid rate slowdown was because the numbers of genes analyzed in pre-genomic studies were small, and thus they were potentially susceptible to bias due to a few data points (such as in the b-globin gene region). This problem
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
571
Hominoids human chimpanzee
Old World monkeys baboon macaque
New World monkeys
marmoset Fig. 1. Evolutionary rate differences consistent with generation-time effect in primates. As noted in the text, there are several well-established trends of generation time effect in primates (indicated by ); lower rates in human compared to chimpanzees (Elango et al., 2006); lower evolutionary rates in hominoids versus Old World monkeys (e.g., Yi et al., 2002; Steiper et al., 2004; Kim et al., 2006); significant variation in Old World monkeys concordant with the generation time effect (Elango et al., 2009): and a lower evolutionary rate in Old World monkeys versus the marmoset (Wildman et al., 2003; Steiper and Young, 2006). Different evolutionary rates are depicted as different branch lengths.
was resolved when genomic data became widely available following the genomics revolution during the last decade. One of the first such studies used 880 kbps of non-coding sequence from humans and chimpanzees and 15 kbps of intron sequence data from Old World monkeys and hominoids, and demonstrated that evolutionary rates in the hominoids are approximately 30% lower than in the Old World monkey lineages (Yi et al., 2002). Another study analyzed 150 kbps data from hominoids and Old World monkeys and reported a similar pattern (Steiper et al., 2004). Genome-wide comparison using 28 Mbps of sequence alignments of the human, macaque and the marmoset genomes reached the same conclusion (Kim et al., 2006). Thus, the hominoid rate slowdown hypothesis is unambiguously supported by genomic scale data. Available genome-scale sequence data from primates further allowed comparisons between other primate lineages, and as a result, the generation time effect has been observed in several additional evolutionary scales in primates (Fig. 1). First, the common marmoset, a New World monkey with shorter generation times than hominoids or Old World monkeys, shows even faster evolutionary rates than Old World monkeys (Steiper and Young, 2006). Goodman’s group also demonstrated that rates are slower in hominoids and Old World monkeys than in non-catarrhine primates using genomic comparisons (Wildman et al., 2003). Second, at a smaller scale, rate differences have been observed between humans and chimpanzees. Based upon approximately 63 million base pair alignments between humans and chimpanzees, it was shown that the human genome is evolving slightly but significantly slower than that of the chimpanzee genome (Elango et al., 2006). Since the human generation time has markedly increased since the divergence of humans and chimpanzees, and the long generation time is considered to be a hallmark of human evolution (Wood, 2000; Wood and Collard, 1999), this observation is in accord with the generation time effect. Third, evolutionary rate variation in accord with generation time effect has been observed within Old World monkeys. Elango et al. (2009) analyzed over
8 Mbps of genomic sequence alignments between four Old World monkey species, and observed that evolutionary rates differ significantly among the four different species, in accordance with the generation time effect. For example, baboons, which are larger and have longer lifespans than macaques, evolve slower than the rhesus macaque lineage (Elango et al., 2009; Peng et al., 2009). 5. Neutral evolutionary rate variation: current and future directions Since the initial proposal of the hominoid rate slowdown by Goodman over half a century ago (Goodman, 1961, 1962a,b, 1963), we have come a long way in appreciating the pattern of evolutionary rate variation between lineages. Understanding the variation of neutral mutation rates has become even more important in the genomics age. One of the goals of functional and comparative genomics is to identify regions that are under functional constraint, or adaptive evolution. To determine the significance of such regions, a reliable knowledge of neutral mutation rates is critical (Ellegren et al., 2003; Wolfe and Li, 2003). Studies of hominoid rate slowdown have contributed immensely to our understanding of neutral mutation rate variation among lineages, and also to the rate difference between the sex chromosomes and autosomes (see below). However, even though the generation time effect is relatively well supported, it cannot explain all the variability of evolutionary rates (Huttley et al., 2007). Clearly, factors other than generation times contribute to evolutionary rate variation. Below we discuss several promising directions of current and future research. 5.1. Influence of other life history traits on evolutionary rate variation Life history traits other than strict generation time may affect evolutionary rates (Martin and Palumbi, 1993; Møller and Cuervo, 2003; Santos, 2012; Seluanov et al., 2007; Speakman, 2005; Welch
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
et al., 2008). Metabolic rates may influence evolutionary rates because metabolism increases mutations due to the mutagenic effects of oxygen radicals, or because organisms with higher metabolic rates may have increased rates of DNA synthesis (Martin and Palumbi, 1993; Santos, 2012). Body mass is often used as a proxy for metabolic rates, although there are other factors that influence body mass, such as brain size, population density, and reproductive effort (Kappelman, 1996; LaBarbera, 1989). Maximum lifespan is obviously related to generation time, but also to the efficiency of DNA repair and aging (Seluanov et al., 2007). In addition, sexual selection can increase mutation rates (Agrawal, 2001; Møller and Cuervo, 2003; Siller, 2001). Many of these life history traits are correlated amongst themselves, making it difficult to discern effects of individual variables on evolutionary rates. It is also important to take into account the underlying phylogeny: life history traits may be similar because of shared evolutionary history (phylogeny), and it is necessary to account for this effect (Felsenstein, 1985; Harvey et al., 1987; Nunn and Barton, 2001; Pagel, 1994). In addition, it is desirable to compare closely related species that share similar biology. For example, comparing rodents and primates may be confounded by changes in other developmental and metabolic traits. Until recently, researchers simply did not have suitable data to account for all of these concerns. With the rapid advance of techniques to garner genome-wide sequence data from many species, we may soon be in a position to overcome these difficulties. Primates are a very promising group of organisms in this respect because there are diverse species with ample sequence data, and relatively welldocumented life history variation (e.g., Tsantes and Steiper, 2009). 5.2. Evolutionary rates of sex chromosomes and autosomes Generation time effects share a common molecular mechanism with the so-called ‘male-driven evolution’ phenomenon. Haldane (1947) first proposed that mutation rates are higher in the male germlines compared to the female germlines. If mutations generally arise from errors during DNA replication, then males, who typically undergo a greater number of germline DNA replications during their lifetime compared to females, will accumulate more mutations than females. Miyata et al. (1987) proposed a method to test the degree of male mutation bias by comparing the evolutionary rates of X-lined, Y-linked, and autosomal loci. Studies utilizing this approach generally agreed with the conclusion that mutation rates in mammals are biased toward males (Shimmin et al., 1993; Li et al., 2002). However, most genome-scale analyses of male mutation bias have compared evolutionary rates of the autosomes to the X chromosomes, because most sequenced genomes of primates and mammals are from females. If DNA replication is the main source of mutations, the results from the comparisons of the X chromosome to autosomes should be similar to those from the comparisons between the Y chromosome to autosomes or between X and Y chromosomes (Miyata et al., 1987). In contrast to this prediction, a recent study claimed that the Y chromosome is not necessarily evolving faster than autosomes (Pink et al., 2009), and posited that the data is not consistent with a simple model assuming asymmetric germline DNA replications as the main determinant of rate difference between the sex chromosomes and autosomes. Sequencing of the Y chromosome from other species (e.g., Hughes et al., 2012) should provide an opportunity to examine variation of male driven evolution. Furthermore, the degree of male mutation bias should vary across different taxa due to variations in life history traits. For example, male mutation bias may positively correlate with the degree of sperm competition (Blumenstiel, 2007; Presgraves and Yi, 2009) as well as generation time (Bartosch-Härlid et al., 2003;
Goetting-Minesky and Makova, 2006). Studies have begun to address these questions using genomic data from mammals, in particular primates (Sayres et al., 2011; Xu et al., 2012).
5.3. Influence of mutational origin The generation time effect hypothesis is based upon the idea that most mutations arise via errors during DNA replication. However, some mutations originate via molecular mechanisms that are relatively independent of DNA replication. A notable example is mutations caused by DNA methylation. In animal genomes, DNA methylation predominantly occurs at cytosines followed by guanine (called ‘CpG’ dinucleotides). Methylated cytosines are subject to spontaneous deamination to thymines, causing C to T mutations (Duncan and Miller, 1980). This type of mutation is a prominent source of point mutations in mammals and other vertebrates. In particular, they occur over an order of magnitude more frequently than other types of mutations in the human genome (Elango et al., 2008), and account for nearly a quarter of all point mutations between the human and chimpanzee genomes (The Chimpanzee Sequencing and Analysis Consortium, 2005). Since DNA methylation is not confined to replicating DNA, such mutations may exhibit different patterns of evolutionary rate variation compared to other mutations. To test this prediction, one study analyzed mutations at CpGs (predominantly caused by DNA methylation) and those at non-CpGs (predominantly caused by DNA replication) in hominoids and Old World monkeys separately (Kim et al., 2006). Mutations occurring at non-CpGs exhibited significant rate difference between hominoids and Old World monkeys, concordant with the hominoid rate slowdown. In contrast, mutations at CpGs showed no rate difference between hominoids and Old World monkeys (Fig. 2). Thus, rate differences are highly dependent on their mutational origins (Kim et al., 2006). On the other hand, there is some indication that mutation rates caused by DNA methylation vary according to factors such as body temperature (Fryxell and Zuckerkandl, 2000; Varriale and Bernardi, 2006) and/or other physiological factors. Accounting for suscepti-
Mutations predominantly arise due to DNA methylation Other mutations
1.5 1.25
KO/KH
572
1 0.75 0.5 0.25 0
repetitive
non-repetitive
total
Fig. 2. Contrasting patterns of hominoid rate slowdown for mutations arising due to distinctive molecular mechanisms. The Y-axis represents the ratio of evolutionary distance between two Old World monkeys (baboon and macaque) and between two hominoids (human and chimpanzee), species pairs that have diverged approximately the same amount of time ago. Thus this ratio captures the ratio of evolutionary rates in Old World monkeys and hominoids during approximately similar evolutionary times (Kim et al., 2006). Mutations at CpGs, which mainly arise due to DNA methylation, exhibit no difference between the Old World monkeys and the hominoids (KO/KH is approximately 1). Other types of mutations, presumably arising during DNA replication, however exhibit strong hominoid rate slowdown (KO/KH is approximately 1.3). Figure modified from Kim et al. (2006).
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
bility toward different types of mutations in different genomic regions and across different taxa should increase our ability to interpret, and ultimately model, genomic evolutionary rate variation. Acknowledgement This study is supported by NSF grants (MCB-0950896 and BCS0751481) to SVY. References Agrawal, A.F., 2001. Sexual selection and the maintenance of sexual reproduction. Nature 411, 692–695. Bailey, W., Fitch, D., Tagle, D., Czelusniak, J., Slightom, J., Goodman, M., 1991. Molecular evolution of the psi eta-globin gene locus: gibbon phylogeny and the hominoid slowdown. Mol. Biol. Evol. 8, 155–184. Bartosch-Härlid, A., Berlin, S., Smith, N.G.C., Møller, A.P., Ellegren, H., 2003. Life history and the male mutation bias. Evolution 57, 2398–2406. Blumenstiel, J.P., 2007. Sperm competition can drive a male-biased mutation rate. J. Theor. Biol. 249, 624–632. The Chimpanzee Sequencing and Analysis Consortium, 2005. Initial sequence of the chimpanzee genome and comparison with the human genome. Nature 437, 69– 87. Domazet-Loso, T., Tautz, D., 2010. A phylogenetically based transcriptome age index mirrors ontogenetic divergence patterns. Nature 468, 815–818. Duncan, B.K., Miller, J.H., 1980. Mutagenic deamination of cytosine residues in DNA. Nature 287, 560–561. Easteal, S., 1988. Rate constancy of globin gene evolution in placental mammals. Proc. Natl. Acad. Sci. USA 85, 7622–7636. Easteal, S., 1991. The relative rate of DNA evolution in primates. Mol. Biol. Evol. 8, 115–127. Easteal, S., Collet, C., 1994. Consistent variation in amino-acid substitution rate, despite uniformity of mutation rate: protein evolution in mammals is not neutral. Mol. Biol. Evol. 11, 643–647. Elango, N., Kim, S.-H., Program, N.C.S., Vigoda, E., Yi, S.V., 2008. Mutations of different molecular origins exhibit contrasting patterns of regional substitution rate variation. PLoS Comp. Biol. 4, e1000015. Elango, N., Lee, J., Peng, Z., Loh, Y.-H.E., Yi, S.V., 2009. Evolutionary rate variation in Old World monkeys. Biol. Lett. 5, 405–408. Elango, N., Thomas, J.W., Program, N.C.S., Yi, S.V., 2006. Variable molecular clocks in hominoids. Proc. Natl. Acad. Sci. USA 103, 1370–1375. Ellegren, H., Smith, N.G., Webster, M.T., 2003. Mutation rate variation in the mammalian genome. Curr. Opin. Genet. Dev. 13, 562–568. Felsenstein, J., 1985. Phylogenies and the comparative method. Am. Nat. 125, 1–15. Fryxell, K.J., Zuckerkandl, E., 2000. Cytosine deamination plays a primary role in the evolution of mammalian isochores. Mol. Biol. Evol. 17, 1371–1383. Goetting-Minesky, M., Makova, K., 2006. Mammalian male mutation bias: impacts of generation time and regional variation in substitution rates. J. Mol. Evol. 63, 537–544. Goodman, M., 1960. The species specificity of proteins as observed in the wilson comparative analyses plates. Am. Nat. 94, 184–186. Goodman, M., 1961. The role of immunologic differences in the phyletic development of human behavior. Hum. Biol. 33, 131–162. Goodman, M., 1962a. Evolution of the immunologic species specificity of human serum proteins. Hum. Biol. 34, 104–150. Goodman, M., 1962b. Immunochemistry of the primates and primate evolution. Ann. N.Y. Acad. Sci. 102, 219–234. Goodman, M., 1963. Man’s place in the phylogeny of the primates as reflected in serum proteins. In: Washburn, S.L. (Ed.), Classification and Human Evolution. Aldine Press, Chicago, pp. 204–234. Goodman, M., 1981. Decoding the pattern of protein evolution. Prog. Biophys. Mol. Biol. 38, 105–164. Goodman, M., 1985. Rates of molecular evolution: the hominoid slowdown. BioEssays 3, 9–14. Haldane, J.B.S., 1947. The mutation rate of the gene for hemophilia, and its segregation ratios in males and females. Ann. Eugen. 13, 262–272. Harvey, P.H., Martin, R.D., Clutton-Brock, T.H., 1987. Life histories in comparative perspective. In: Al., S.B.B.e. (Ed.), Primate Societies, vol. 4. Springer, berlin, pp. 69–82. Herbert, G., Easteal, S., 1996. Relative rates of nuclear DNA evolution in human and Old World monkey lineages. Mol. Biol. Evol. 13, 1054–1057. Hughes, J.F., Skaletsky, H., Brown, L.G., Pyntikova, T., Graves, T., Fulton, R.S., Dugan, S., Ding, Y., Buhay, C.J., Kremitzki, C., Wang, Q., Shen, H., Holder, M., Villasana, D., Nazareth, L.V., Cree, A., Courtney, L., Veizer, J., Kotkiewicz, H., Cho, T.-J., Koutseva, N., Rozen, S., Muzny, D.M., Warren, W.C., Gibbs, R.A., Wilson, R.K., Page, D.C., 2012. Strict evolutionary conservation followed rapid gene loss on human and rhesus Y chromosomes. Nature 483, 82–86. Huttley, G.A., Wakefield, M.J., Easteal, S., 2007. Rates of genome evolution and branching order from whole genome analysis. Mol. Biol. Evol. 24, 1722–1730. Kalinka, A.T., Varga, K.M., Gerrard, D.T., Preibisch, S., Corcoran, D.L., Jarrells, J., Ohler, U., Bergman, C.M., Tomancak, P., 2010. Gene expression divergence recapitulates the developmental hourglass model. Nature 468, 811–814.
573
Kappelman, J., 1996. The evolution of body mass and relative brain size in fossil hominids. J. Hum. Evol. 30, 243–276. Kim, S.-H., Elango, N., Warden, C.W., Vigoda, E., Yi, S., 2006. Heterogeneous genomic molecular clocks in primates. PLoS Genet. 2, e163. Kimura, M., 1968. Evolutionary rate at the molecular level. Nature 217, 624–626. Kimura, M., 1969. The rate of molecular evolution considered from the standpoint of population genetics. Proc. Natl. Acad. Sci. USA 63, 1181–1188. Kimura, M., 1983. The neutral theory of molecular evolution. Cambridge University Press, Cambridge, UK. Koop, B.F., Goodman, M., Xu, P., Chan, K., Slightom, J.L., 1986. Primate [eta]-globin DNA sequences and man’s place among the great apes. Nature 319, 234– 238. Kumar, S., Hedges, S.B., 1998. A molecular timescale for vertebrate evolution. Nature 392, 917–920. Kumar, S., Subramanian, S., 2002. Mutation rates in mammalian genomes. Proc. Natl. Acad. Sci. USA 99, 803–808. LaBarbera, M., 1989. Analyzing body size as a factor in ecology and evolution. Ann. Rev. Ecol. Syst. 20, 97–117. Li, W.-H., 1997. Molecular Evolution. Sinauer, Sunderland, MA. Li, W.-H., Yi, S., Makova, K., 2002. Male-driven evolution. Curr. Opin. Genet. Develop. 12, 650–656. Martin, A.P., Palumbi, S.R., 1993. Body size, metabolic rate, generation time, and the molecular clock. Proc. Natl. Acad. Sci. USA 90, 4087–4091. Miyata, T., Hayashida, H., Kuma, K., Mitsuyasu, K., Yasunaga, T., 1987. Male-driven molecular evolution: a model and nucleotide sequence analysis. Cold Spring Harbor Symp. Quant. Biol. 52, 863–867. Møller, A.P., Cuervo, J.J., 2003. Sexual selection, germline mutation rate and sperm competition. BMC Evol. Biol. 3, 6. Muller, H.J., 1954. The nature of the genetic effects produced by radiation. In: Hollaender, A. (Ed.), Radiation Biology, vol. 4. McGraw-Hill, New York, pp. 351– 473. Nunn, C.L., Barton, R.A., 2001. Comparative methods for studying primate adaptation and allometry. Evol. Anthropol.: Issues News Rev. 10, 81–98. Pagel, M., 1994. Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters. Proc. Biol. Sci. 255, 37–45. Peng, Z., Elango, N., Wildman, D., Yi, S., 2009. Primate phylogenomics: developing numerous nuclear non-coding, non-repetitive markers for ecological and phylogenetic applications and analysis of evolutionary rate variation. BMC Genome 10, 247. Pink, C.J., Swaminathan, S.K., Dunham, I., Rogers, J., Ward, A., Hurst, L.D., 2009. Evidence that replication-associated mutation alone does not explain betweenchromosome differences in substitution rates. Genome Biol. Evol. 1, 13–22. Presgraves, D.C., Yi, S., 2009. Doubts about complex speciation between humans and chimpanzees. Trends Ecol. Evol. 24, 533–540. Roux, J., Robinson-Rechavi, M., 2008. Developmental constraints on vertebrate genome evolution. PLoS Genet. 4, e1000311. Santos, J.C., 2012. Fast molecular evolution associated with high active metabolic rates in poison frogs. Mol. Biol. Evol. 29, 2001–2018. Sarich, V.M., Wilson, A.C., 1967. Immunological time scale for hominid evolution. Science 158, 1200–1203. Sayres, M.A.W., Venditti, C., Pagel, M., Makova, K.D., 2011. Do variations in substitution rates and male mutation bias correlate with life-history traits? A study of 32 mammalian genomes. Evolution 65, 2800–2815. Seluanov, A., Chen, Z., Hine, C., Sasahara, T.H.C., Ribeiro, A.A.C.M., Catania, K.C., Presgraves, D.C., Gorbunova, V., 2007. Telomerase activity coevolves with body mass, not lifespan. Aging Cell 6, 45–52. Shimmin, L.C., Chang, B.H.J., Li, W.H., 1993. Male-driven evolution in DNA sequences. Nature 362, 745–747. Siller, S., 2001. Sexual selection and the maintenance of sex. Nature 411, 689– 692. Speakman, J.R., 2005. Correlations between physiology and lifespan – two widely ignored problems with comparative studies. Aging Cell 4, 167–175. Steiper, M.E., Young, N.M., 2006. Primate molecular divergence dates. Mol. Phylogenet. Evol. 41, 384–394. Steiper, M.E., Young, N.M., Sukrarna, T.Y., 2004. Genomic data support the hominoid slowdown and an early Oligocene estimate for the hominoid–cercopithecoid divergence. Proc. Natl. Acad. Sci. USA 101, 17021–17026. Sturtevant, A.H., 1965. A History of Genetics. Harper Low, New York. Tsantes, C., Steiper, M.E., 2009. Age at first reproduction explains rate variation in the strepsirrhine molecular clock. Proc. Natl. Acad. Sci. USA 106, 18165–18170. Varriale, A., Bernardi, G., 2006. DNA methylation and body temperature in fishes. Gene 385, 111–121. Welch, J.J., Bininda-emonds, O.R.P., Bromham, L., 2008. Correlates of substitution rate variation in mammalian protein-coding sequences. BMC Evol. Biol. 8, 53. Wildman, D.E., Uddin, M., Liu, G., Grossman, L.I., Goodman, M., 2003. Implications of natural selection in shaping 99.4% nonsynonymous DNA identity between humans and chimpanzees: enlarging genus Homo. Proc. Natl. Acad. Sci. USA 100, 7181–7188. Wilson, A.C., Ochman, H., Prager, E.M., 1987. Molecular time scale for evolution. Trends Genet. 3, 241–247. Wolfe, K.H., Li, W.-H., 2003. Molecular evolution meets the genomics revolution. Nat. Genet. 33, 255–265. Wood, B., 2000. Investigating human evolutionary history. J. Anat. 197, 3–17. Wood, B., Collard, M., 1999. The human genus. Science 284, 65–71. Wu, C.I., Li, W.H., 1985. Evidence for higher rates of nucleotide substitution in rodents than in man. Proc. Natl. Acad. Sci. USA 82, 1741–1745.
574
S.V. Yi / Molecular Phylogenetics and Evolution 66 (2013) 569–574
Xu, K., Oh, S., Park, T., Presgraves, D.C., Yi, S.V., 2012. Lineage-specific variation in slow- and fast-X evolution in primates. Evolution 66, 1751–1761. Yi, S., Ellsworth, D.L., Li, W.H., 2002. Slow molecular clocks in Old World monkeys, apes, and humans. Mol. Biol. Evol. 19, 2191–2198.
Zuckerkandl, E., Pauling, L.B., 1965. Evolutionary divergence and convergence in proteins. In: Bryson, V., Vogel, H.J. (Eds.), Evolving Genes and Proteins. Academic Press, New York, pp. 97–166.