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Mol Biol Evol molbiolevol molbev Molecular Biology and Evolution 0737-4038 1537-1719 Oxford University Press PMC2464741 PMC2464741 2464741 18535014 10.1093/molbev/msn126 18535014 Research Articles Programmed Genetic Instability: A Tumor-Permissive Mechanism for Maintaining the Evolvability of Higher Species through Methylation-Dependent Mutation of DNA Repair Genes in the Male Germ Line Zhao Yongzhong 1 Epstein Richard J. Laboratory of Computational Oncology, Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong E-mail: repstein@hku.hk

Present address: NE20, Department of Molecular Genetics, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH

Takashi Gojobori, Associate Editor

8 2008 4 6 2008 4 6 2008 25 8 1737 1749 26 5 2008 © 2008 The Authors 2008

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Tumor suppressor genes are classified by their somatic behavior either as caretakers (CTs) that maintain DNA integrity or as gatekeepers (GKs) that regulate cell survival, but the germ line role of these disease-related gene subgroups may differ. To test this hypothesis, we have used genomic data mining to compare the features of human CTs (n = 38), GKs (n = 36), DNA repair genes (n = 165), apoptosis genes (n = 622), and their orthologs. This analysis reveals that repair genes are numerically less common than apoptosis genes in the genomes of multicellular organisms (P < 0.01), whereas CT orthologs are commoner than GK orthologs in unicellular organisms (P < 0.05). Gene targeting data show that CTs are less essential than GKs for survival of multicellular organisms (P < 0.0005) and that CT knockouts often permit offspring viability at the cost of male sterility. Patterns of human familial oncogenic mutations confirm that isolated CT loss is commoner than is isolated GK loss (P < 0.00001). In sexually reproducing species, CTs appear subject to less efficient purifying selection (i.e., higher Ka/Ks) than GKs (P = 0.000003); the faster evolution of CTs seems likely to be mediated by gene methylation and reduced transcription-coupled repair, based on differences in dinucleotide patterns (P = 0.001). These data suggest that germ line CT/repair gene function is relatively dispensable for survival, and imply that milder (e.g., epimutational) male prezygotic repair defects could enhance sperm variation—and hence environmental adaptation and speciation—while sparing fertility. We submit that CTs and repair genes are general targets for epigenetically initiated adaptive evolution, and propose a model in which human cancers arise in part as an evolutionarily programmed side effect of age- and damage-inducible genetic instability affecting both somatic and germ line lineages.

molecular evolution adaptive evolution carcinogenesis DNA repair
Introduction

A longstanding debate in evolutionary biology concerns how species of increasing structural complexity maintain their capacity for genetic variation—and, hence, adaptation and divergence—despite a predictably increasing need for genetic fidelity (Gulick 1893; Gould JL and Gould CG 1997). Relevant to this conflict, Cope's rule postulates that increasing body size creates a short-term reproductive advantage for the individual organism (Kingsolver and Pfennig 2004) while worsening long-term extinction risk for the clade (Van Valkenburgh et al. 2004; Hone and Benton 2005). This trade-off suggests that higher evolving organisms are subject to a progressive “Red Queen”–type clash between intensifying negative selection for phenotypic stability and weakening positive selection for genotypic variability (Markov 2000)—consistent with the modest proportion (0.03%) of coding sequence estimated to have been positively selected in humans, when compared with that negatively selected (2.5–5%) in humans or positively selected in simpler species such as Drosophila (20%) (Ponting and Lunter 2006). Indeed, prevailing theory teaches that most genetic novelty results from fixation of random (nonadaptive) drift affecting neutral (Kimura 1968) or near-neutral (Ohta 1998) alleles, rejecting the Lamarckian doctrine that environmental pressures can drive (i.e., not merely fix) beneficial mutations.

In previous work, we showed that silent mutations may nonrandomly affect intragenic sites of differing functional importance (Epstein et al. 2000; Lin et al. 2003) and that such mutational patterns vary with both strand-specific transcription-related DNA repair (Tang et al. 2006) and gene expression levels (Tang and Epstein 2007). It therefore remains plausible that ambient stressors such as heat (Maresca and Schwartz 2006), starvation (Hastings et al. 2004), inflammation (Blanco et al. 2007; Lavon et al. 2007), toxins (Salnikow and Zhitkovich 2008), free radical injury (Cerda and Weitzman 1997), or other sources of DNA damage (Ponder et al. 2005) could modify gene transcription and thus alter the rate of mutations affecting fitness (Galhardo et al. 2007)—including the occasional generation of beneficial mutations (Monk 1995; Elena and de Visser 2003; Nei 2005). Clues favoring this inducible (adaptive) evolutionary paradigm over neutrality for metazoan genomes—as is already accepted for bacterial (Ponder et al. 2005; Cirz and Romesberg 2007) and plant genomes (Galloway and Etterson 2007)—include faster-than-expected rates of phenotype acquisition, close temporal correlation with environmental changes, proof of improved fitness, or convergence (Levasseur et al. 2007).

A mechanism for such non-Darwinian genomic plasticity has been suggested in recent times by the discovery of heritable epigenetic changes capable of reprogramming developmental and adult gene expression (Martin et al. 2005; Morgan et al. 2005), coupled with the predisposition of such changes to cause germ line mutations (Cooper and Krawczak 1989) or postzygotic mosaicism (Ohlsson et al. 1999) that sometimes cause disease (Andrews et al. 1996; Smith and Hurst 1998; Esteller et al. 2001). The frequency of germ line epimutations or imprinting errors—estimated to be an order of magnitude higher than that of germ line mutations (Horsthemke 2006)—can be either environmentally regulated (Dolinoy and Jirtle 2008), as illustrated by the inducibility of spermatogonial stem cell DNA hypermethylation by air pollution (Yauk et al. 2008), or parentally age dependent (Oakes et al. 2003; Perrin et al. 2007). If such epimutations affect modifier genes involved in DNA repair, a “slippery slope” of somatic and transgenerational genetic instability (i.e., a mutator phenotype) may result (Jacinto and Esteller 2007), leading not only to an increase in deleterious (purifiable) mutations (Wu et al. 2007; Morak et al. 2008) but also to occasional advantageous (positively selectable) mutations (Sniegowski et al. 2000; Cirz and Romesberg 2007) and/or speciation events (Sniegowski 1998). Selection of such “driver” beneficial mutations may lead in turn to “hitchhiking” of mutator (epi)mutations in modifier genes (Johnson 1999) as “passengers” (Frohling et al. 2007). Such mutational buffering could enhance evolvability (Wagner 2008)—consistent with the idea that error-free DNA repair may be maladaptive in mutagenic or stressful environments (Breivik and Gaudernack 2004; Ponder et al. 2005; Siegl-Cachedenier et al. 2007)—yet may also impair performance and hence robustness (Lenski et al. 2006; Frank 2007; Petrie and Roberts 2007). The “evo-devo” conundrum thus remains as to whether evolvability is indeed selectable (Hendrikse et al. 2007; Lynch 2007), and if so, by what mechanism (Colegrave and Collins 2008; Pigliucci 2008). Even if such a mechanism exists (King and Jukes 1969; Monk 1995), traditional thinking predicts that such selection may act only very weakly at a “good-for-the-species” level (Hiraiwa-Hasegawa 2000).

We have addressed this dilemma by comparing 2 classes of human genes implicated in prevention of cancer, a disease of disordered microevolution (Gatenby and Vincent 2003; Iwasa et al. 2004; Breivik 2005). Tumorigenesis is potentiated by genomic instability (Schneider and Kulesz-Martin 2004; Bielas et al. 2006) arising via multistep inactivation of so-called tumor suppressor genes (Nowak et al. 2004), which, like proto-oncogenes, have been reported to be under strong negative selection pressure (Thomas et al. 2003). These carcinogenic loss-of-function events mainly affect DNA repair—mediated by caretaker genes (CTs) such as BRCA1 and MLH1—or apoptosis, mediated by gatekeeper genes (GKs) such as TP53 and Rb (Kinzler and Vogelstein 1997). These suppressor gene subsets, as well as their disease-causing mutations (Futreal et al. 2004; University Medical Center Groningen 2006), are distinguishable using gene databases (Doctor et al. 2003; Wood et al. 2005). Although long regarded as recessive oncogenes that require 2 “hits” for disease expression (Knudson 2000), suppressor genes are increasingly recognized to exhibit clonal haploinsufficiency in tumors (Santarosa and Ashworth 2004; Smilenov 2006). Given recent evidence for the role of adaptive evolution in cancer progression (Babenko et al. 2006; Crespi and Summers 2006), the occurrence of such haploinsufficiency supports the view that gene loss and pseudogenization (“less is more”) can accelerate genome evolution in certain contexts (Olson 1999). Because deleterious mutations (those causing genetic death) are purged by negative selection, whereas nondeleterious mutations may be positively selected, systematic comparison of CT and GK evolutionary rates should clarify whether these repair and apoptosis gene subsets are subject to distinct evolutionary forces. Consistent with this possibility, comparisons of human and chimpanzee genomes have confirmed different evolutionary rates in functionally distinct gene categories related to tumorigenesis (Clark et al. 2003; Bustamante et al. 2005; Nielsen et al. 2005; Kelley et al. 2006; Voight et al. 2006), whereas adaptive evolution of the BRCA1 CT has been well documented (Huttley et al. 2000; Fleming et al. 2003; Pavlicek et al. 2004). Here, we use genomic data mining to test the hypothesis that germ line CTs are commoner targets for methylation-dependent mutational inactivation than are GKs and, hence, that repair gene dysfunction contributes both to germ line evolvability and somatic tumor progression. A male-dependent prezygotic mechanism for this process, which we have termed programmed genetic instability or PGI (Epstein and Zhao 2006a), is also presented.

Materials and MethodsIdentification and Classification of CTs and GKs

We mined data to compare the structural and functional characteristics of human CTs and GKs (see supplement 1 [Supplementary Material online] for sources). Given the multigenic interdependence of DNA repair and cellular apoptosis (Wee and Aguda 2006), unambiguous identification of genes that exclusively mediate 1 of these 2 processes is not straightforward. We sought to minimize the “noise” of this functional overlap in 2 ways. First, we used a familial tumor suppressor gene database (Futreal et al. 2004; University Medical Center Groningen 2006) to restrict the choice of genes to those with major neoplastic effects (i.e., heritable cancer syndromes) when deleted in the germ line; this yielded a total of 74 tumor suppressor genes (table 1). Second, by cross-correlating the former data set with a database of DNA repair genes (Wood et al. 2005), we subclassified this familial cancer susceptibility gene subset as CTs (n = 38) and then designated the remainder—the majority of which were confirmed to mediate apoptosis (Doctor et al. 2003)—as GKs (n = 36; table 1).

Classification of CT and GK Suppressor Genes, Listing RefSeq, EntrezGene, and Ensembl Identifiers

CTsRefSeqEntrez GeneEnsemblGKsRefSeqEntrez GeneEnsembl
1ATMNM_000051472ENST00000278616APCNM_000038324ENST00000257430
2BLMNM_000057641ENST00000355112AXIN2NM_0046558313ENST00000307078
3BRCA1NM_007295672ENST00000309486BMPR1ANM_004329657ENST00000372037
4BRCA2NM_000059675ENST00000267071BUB1BNM_001211701ENST00000287598
5BRIP1NM_03204383990ENST00000259008CDC73NM_02452979577ENST00000367436
6DDB2NM_0001071643ENST00000256996CDH1NM_004360999ENST00000268794
7ERCC2NM_0004002068ENST00000221481EXT1NM_0001272131ENST00000378204
8ERCC3NM_0001222071ENST00000285398MEN1NM_1308034221ENST00000337652
9ERCC4NM_0052362072ENST00000311895NF1NM_0002674763ENST00000358273
10ERCC5NM_0001232073ENST00000375971NF2NM_0002684771ENST00000338641
11ERCC6NM_0001242074ENST00000355832PRKAR1ANM_2124725573ENST00000358598
12ERCC8NM_0000821161ENST00000265038PTCHNM_0002645727ENST00000331920
13FANCANM_0001352175ENST00000305699PTENNM_0003145728ENST00000371953
14FANCBNM_0010181132187ENST00000340604RB1NM_0003215925ENST00000267163
15FANCCNM_0001362176ENST00000289081SBDSNM_01603851119ENST00000246868
16FANCD2NM_0330842177ENST00000287647SDHBNM_0030006390ENST00000375499
17FANCENM_0219222178ENST00000229769SDHCNM_0030016391ENST00000367975
18FANCFNM_0227252188ENST00000327470SDHDNM_0030026392ENST00000375549
19FANCGNM_0046292189ENST00000378643SMAD4NM_0053594089ENST00000342988
20FANCLNM_01806255120ENST00000233741SMARCB1NM_0010074686598ENST00000344921
21FANCMNM_02093757697ENST00000267430STK11NM_0004556794ENST00000326873
22LIG4NM_0023123981ENST00000310534SUFUNM_01616951684ENST00000369902
23MLH1NM_0002494292ENST00000231790TCF1NM_0005456927ENST00000257555
24MLH3NM_01438127030ENST00000238662TSC1NM_0003687248ENST00000298552
25MRE11ANM_0055914361ENST00000323929TSC2NM_0005487249ENST00000219476
26MSH2NM_0002514436ENST00000233146TSHRNM_0003697253ENST00000298171
27MSH3NM_0024394437ENST00000265081VHLNM_0005517428ENST00000256474
28MSH6NM_0001792956ENST00000234420WT1NM_0244267490ENST00000379079
29MUTYHNM_0122224595ENST00000372112CDK4NM_0000751019ENST00000257904
30NBNNM_0010246884683ENST00000265433CHEK2NM_00100573511200ENST00000382580
31PMS1NM_0005345378ENST00000342075CYLDNM_0152471540ENST00000311559
32PMS2NM_0005355395ENST00000265849EXT2NM_0004012132ENST00000358681
33POLHNM_0065025429ENST00000372236FHNM_0001432271ENST00000205832
34RAD51NM_0028755888ENST00000382643FLCNNM_144997201163ENST00000285071
35RECQL4NM_0029075965ENST00000314748GPC3NM_0044842719ENST00000370818
36WRNNM_0005537486ENST00000298139TP53NM_0005467157ENST00000269305
37XPANM_0003807507ENST00000259463
38XPCNM_0046287508ENST00000285021
Analyses of Gene Sequences, Mutations, and Evolutionary Rate

Human and mouse reference sequences, and species gene numbers, were downloaded from NCBI Entrez Gene (http://www.ncbi.nlm.nih.gov/Entrez/Gene). Mutation data were downloaded from the Human Gene Mutation Database. K-estimator 6.1 (with window size of 33 codons and step size of 10 codons using Kimura 2-parameter [2p] method) (Comeron 1999) and PAML 3.15 with yn00 model (Yang and Nielsen 2002) were used for evolutionary rate calculations. For analysis of gene evolutionary profiles, we downloaded coding sequences from Ensembl (http://www.ensembl.org). Kendall package from R-gui (http://www.r-project.org) was used for statistical analysis. Other analyses were done using MATLAB (7.6) Statistical Toolbox (5.1) (http://www.mathworks.com) for principal component analysis and nonparametric tests, and R-gui (2.60) for χ2 or Fisher's exact test.

Supergene Concatenation

Orthologous gene sequences of human, mouse, rat, chimpanzee, and rhesus monkey were aligned with amino acid sequences using ClustalW (Thompson et al. 1994), then reverted to codon sequences. In-house Perl scripts (available upon request) were developed for aligned codon concatenation. All the aligned CT and GK sequences were concatenated for supergene construction—23,100 codons for the GK supergene and 32,335 for the CT supergene. The supergene tree was constructed using a neighbor-joining method, with a modified Nei–Gojobori approach, as input in MEGA4 (codon substitution number Molecular Evolutionary Genetics Analysis software, version 4.0), producing 2 types of tree: synonymous and nonsynonymous substitution trees.

Coding Sequence Feature Analysis

We used reference sequences downloaded from NCBI Entrez Gene. For multiple splicing forms, the longest coding sequence was used for analysis. Mono- and dinucleotide composition was assessed using in-house Perl scripts. Additional methodologic details are supplied in the supplements, text, and legends (Supplementary Material online).

ResultsPhylogenetic Comparison of CT and GK Orthologs

As an initial assessment, we quantified the numbers of human CT and GK orthologs among species of differing biological complexity. Table 2 shows that orthologs of human CTs occur more often than those of GKs in unicellular (P = 0.047) than in multicellular organisms (P = 0.192)—suggesting that CTs are phylogenetically older, whereas GKs may be more essential to the evolution of multicellular organisms. Although this phylogenetic rise in GK ortholog frequency may reflect selection for increased developmental complexity as predicted by Cope's rule, it may also reflect the increasing importance of policing rogue elements (either intragenomic elements like meiotic drivers or intercellular outlaws like cancer cells) as multicellularity evolves and organismal cell number increases.

Phylogenetic and Gene Essentiality Profiles of Familial Cancer Syndrome Genes

ParametersCTsGKsP value
Yeast orthologs0.047
    Present3020
    Absent816
Worm orthologs0.192
    Present3033
    Absent83
Yeast essentiality0.63
    Deletion lethal32
    Deletion nonlethal2718
Worm essentiality0.003
    RNAi lethal111
    RNA nonlethal2922
Mouse essentiality<0.00001
    Knockout lethal428
    Normal218
    Male infertility130

NOTE.—.For yeast phylogenetic analysis, CT analysis excludes the numerous Fanconi anemia gene orthologs in order to avoid data confounding. Gene knockout phenotypes were sourced using data mined from http://www.informatics.jax.org/. All P values were computed using Fisher's exact test (2 sided).

We next assessed differences in CT and GK gene essentiality (Liao et al. 2006) based on deletion, RNAi, and gene-targeting data (supplement 2, Supplementary Material online). This analysis shows that germ line GK ortholog disruption is more often lethal than CT knockout in multicellular (worm RNAi data and mouse knockouts; P < 0.00001, Fisher's exact test, 2 sided) but not in unicellular organisms (yeast deletions; P = 0.63; table 2). Hence, relative to GK function, germ line CT function appears selectively dispensable in multicellular organisms.

Analysis of mammalian gene-targeting phenotypes further reveals that, unlike GK knockouts, viable CT knockouts are associated with male sterility (table 2). We infer from this finding that CT dysfunction selectively permits (organism) viability at the expense of (genetic) fidelity, severe defects of which might be expected to cause sperm dysfunction or death. As discussed below, however, the possibility is raised that less profound (i.e., nondeletional or epimutational) germ line repair deficiencies could be associated with offspring fertility.

To assess further the impact of repair and apoptotic gene defects transmitted through the germ line, we compared CT and GK mutation frequencies in cancer families and somatic tumors. This shows that isolated germ line CT mutations are commoner than isolated GK mutations (P < 0.00001; table 3), reinforcing the notion that CT/repair function is significantly more dispensable for survival than is GK/apoptosis function.

Mutational Analysis of Familial (germ line) and Sporadic (somatic) Human Tumor Mutations of CTs and GKs (i.e., relative frequencies of familial vs. sporadic human tumor mutations in the germ line and/or somatic lineages)

Germ line versus somatic human tumor mutationsGerm line and somaticGerm line onlyP value
CT (n = 38)632<0.00001
GK (n = 36)2511

NOTE.—Mutation frequencies were determined by mining Cancer Gene Census and PubMed with P values computed using Fisher's exact test (2 sided).

Phylogenetic Analysis of Apoptosis versus Repair

The foregoing data apply only to tumor suppressor genes. To determine whether these results can be generalized, we performed a cross-species quantitation of orthologs implicated in either apoptosis or repair (supplement 1, Supplementary Material online). Based on the assumptions that organism complexity is increasing from yeast to humans and that assignation of gene ontology includes some random effects, we performed Kendall rank test (R-gui Kendall package, www.r-project.org) for correlation analysis of DNA repair genes and apoptosis genes. As shown in figure 1A, phylogenetic differences in apoptosis gene numbers are significant (tau = 1, 2-sided P = 0.008535), whereas for DNA repair genes this is not the case (tau = 0.333, 2-sided P = 0.45237). Considered together with table 2, this difference confirms that increases in biological complexity depend more upon apoptotic than repair gene number.

Evolutionary characteristics of human CTs and GKs. (A) Overall quantitation of apoptotic gene versus repair gene number in different phyla: human (H. sapiens), mouse (Mus musculus), fish (D. rerio), fly (D. melanogaster), worm (C. elegans), and yeast (S. pombe). Blue filled squares, DNA repair genes; red filled circles, apoptosis genes; black stars, total gene number of respective genome from Ensemble 49 (www.ensembl.org). Data were mined as detailed in the Materials and Methods. (B) Relative divergence of CT and GK genes in mammals (human–mouse; divergence time approximately 85 MYA) and worms (C. elegans–C. briggsae; divergence time approximately 100 MYA) quantified using Ka/Ks. Blue squares, CT orthologs; red circles, GK orthologs. (C) Principal component analysis with parameters of Ka/Ks of CTs and GKs. We normalized the computed 10 pairwise divergence of human, chimpanzee, rhesus, monkey, mice, and rats using Ka/Ks analysis. 1st PC, first principal component (x axis); 3rd PC, third principal component (y axis).

Comparison of CT and GK Evolutionary Rates

We then used nonparametric 2-sample Kolmogorov–Smirnov goodness of fit hypothesis testing with kstest2 function (MATLAB, http://www.mathworks.com, statistical toolbox) for Ka/Ks—a positive correlate of positive selection—ortholog analysis. This confirmed that CTs evolve more rapidly than GKs in sexually reproducing (human vs. mouse, estimated divergence time 85 Myr; P = 0.000003) but not in self-fertilizing (2 worm species, estimated divergence time 100 Myr; P = 0.2582) multicellular organisms (fig. 1B; Kruskal–Wallis test, P < 0.004); Ks was different in worms (P = 0.007) but not in mammals (P = 0.091). Consistent with our earlier finding of selective male sterility in CT knockouts, these data support the hypothesis that rapid CT evolution is related in some way to sexual reproduction. Principal component analysis based on evolutionary rate as well as variables such as GC content (see fig. 5) and gene length (see supplement 3, Supplementary Material online) provides further visual evidence that CTs and GKs are distinguishable based on genetic evolutionary parameters (fig. 1C).

We then used neighbor-joining supergene (gene concatenation) trees (Zhang et al. 1998) to characterize CT and GK branches under selection. This methodology, which has been reported to yield more accurate phylogenetic data than multigene approaches (Gadagkar et al. 2005), confirms that accelerated evolution of CTs compared with GKs is evident in human–macaca, human–mouse, and mouse–rat comparisons, though apparently not in human–chimpanzee comparisons (fig. 2A). This difference is further illustrated by a tree diagram showing the distinct divergence parameters of CTs and GKs (fig. 2B). It is noted that the ratio of missense to silent mutations (A/S) encoded by CT single-nucleotide polymorphisms (SNPs) is no higher than in GKs (supplement 1, Supplementary Material online) and that, compared with historical data (Zhang et al. 1998; Fay et al. 2001), larger polymorphisms are present in both rare and common SNPs (P < 0.001, Pearson's χ2). We have also noted that CTs evolve more rapidly than tissue-specific genes, whereas GKs evolve more slowly than housekeeping genes (P < 0.001, Mann–Whitney U test; data not shown), emphasizing the wide class differences in evolutionary rates.

Evolutionary rate comparison of CTs and GKs. (A) Distribution of Ka/Ks in pairwise comparisons between CTs and GKs within 4 lineages including human–chimpanzee (top left), human–macaca (top right), human–mouse (bottom left), and human–rat (bottom right). Bin size 0.05 was used for distribution computation. For this analysis—which compares the different evolutionary rates of human CTs and GKs using a variety of species comparators, as distinct from comparing gene evolutionary rates in multiple species—P values were calculated by ranked 2-sample Mann–Whitney U test using MATLAB Statistical toolbox function rank sum. (B) Lineage-specific comparison of evolutionary rate of CTs and GKs using supergene concatenation. Blue bars, CTs; red bars, GKs.

To explore possible differences of divergence between CTs and GKs, we used a sliding window analysis of concatenated CT (38 genes, 41,169 codons) and GK (36 genes, 25,968 codons) supergenes. A window size of 33 codons and step size of 10 codons was used in conjunction with K-estimator (calculation of the number of nucleotide substitutions per site and the confidence intervals) 6.1, Kimura 2p model. As shown in figure 3A, the Ka/Ks (red), but neither Ka nor Ks (green and blue, respectively), is overrepresented in CTs compared with GKs. We further tested the distribution of these 3 parameters by using the nonparametric 2-sample Kolmogorov–Smirnov test. Figure 3B confirms that only Ka/Ks is significant (P = 0.0000079) but neither Ka nor Ks, which correlate with deleterious mutation and neutral mutation rate, respectively (for further details, see supplement [Supplementary Material online] and fig. 3).

Sliding window analysis of human–mouse CT and GK divergence. (A) Evolutionary rates of CTs (top) and GKs (bottom) using human–mouse alignments (window size 33 codons, step size 10 codons). Red line, Ka/Ks; blue line, Ks; green line, Ka. Most regions with Ka/Ks >1.5, with P value <0.05 (bootstrap threshold computed with K-estimator 6.1). (B) Distribution of Ka, Ks, Ka/Ks in CTs and GKs using bin size 0.05 and nonparametric Kolmogorov–Smirnov test, revealing a significant difference of Ka/Ks (P = 0.0000079), thus confirming more rapid evolution of CTs than GKs.

To check whether human–chimpanzee divergences of CTs and GKs are in fact similar, as suggested by the findings in figure 2, we used the McDonald and Kreitman (1991) test for evolutionary rate analysis. Data were mined as described (Bustamante et al. 2005) using a Poisson random field model—a variant of the McDonald–Kreitman test—for divergence versus diversity comparison. Data were obtained from Celera Genomics, which applied exon-specific polymerase chain reaction amplification to 20,362 loci in 39 humans and 1 male chimpanzee. We note, however, that the following genes were not found in this data set: 9 CTs (BRCA2, BRIP1, FANCD2, FANCM, MLH1, MLH3, NBN, PMS2, and RECQL4) and 10 GKs (CDC73, EXT1, NF1, PTCH, SBDS, SDHD, TSHR, WT1, CHEK2, and FH). The following parameters were used: synonymous divergence, synonymous polymorphism, nonsynonymous divergence (DN), nonsynonymous polymorphism (PN), and γ (Poisson random field model parameters). All mined data are supplied (supplement [Supplementary Material online] and fig. 4). In contrast to figure 2, these results—which show a higher frequency of GKs lacking both PN and DN sites relative to CTs (Pearson's χ2, P = 0.0044)—confirm that the rapid evolution of CTs relative to GKs persisted during the human–chimpanzee divergence approximately 10 MYA (fig. 4A–D). Hence, having shown that CTs evolved faster than GKs both during primate–rodent (figs. 1–3) and human–chimpanzee divergence (fig. 4), we conclude that the rapid evolution of CTs is likely independent of timescale.

McDonald–Kreitman testing of CT evolutionary rate relative to GKs during human–chimpanzee divergence. (A) Distributions of synonymous divergence (DS), synonymous polymorphism (PS), nonsynonymous divergence (DN), and nonsynonymous polymorphism (PN) of CTs and GKs using bin size 1 and nonparametric tests (median of 2 unpaired samples, using the MATLAB 7.6 statistical toolbox rank-sum function). This shows that DN is the most significant parameter (P = 0.00016), followed by PN (P = 0.004), with DS and PS not significant, thus confirming rapid CT evolution. (B) R-gui function χ2 test function in terms of the summarized codon changes of CTs and GKs. This also shows that the evolutionary rates of CTs and GKs are different (P = 0.0000037). (C) Poisson random field parametric test. The selection parameters are illustrated using a 95% confidence interval and show no significant difference (P = 0.1913, by nonparametric test of equal distribution of 2 samples using function kstest2), presumably reflecting numerous nonchange genes in terms of the parameters. (D) Parametric retesting of CT and GKs in terms of DS, PS, DN, and PN, confirming that CTs evolved more rapidly than GKs during human–chimpanzee divergence.

Sequence-Based Evidence for Evolutionary CT Gene Methylation

Our previous studies implicated nonrandom CG → TA transitional mutations (CpG decay) as a correlate of adaptive evolution in less transcribed (Tang and Epstein 2007) and/or less essential coding sequences (Epstein et al. 2000); conversely, we have implicated CpG conservation as a correlate of negative selection in more transcribed (Tang et al. 2006) and/or more essential sequences (Lin et al. 2003). These results suggested an evolutionary paradigm in which concomitant promoter and coding sequence methylation accelerate (epi)mutational functional loss of nonessential coding sequences. To test whether any such methylation-dependent signatures distinguish CTs and GKs, we computed the sequence component of the relevant transcribed coding strand and applied a nonparametric 2-sample Kolmogorov–Smirnov goodness of fit hypothesis test with kstest2 function of MATLAB (http://www.mathworks.com) statistical tool box for all parameters compared. Meaningful CT and GK gene expression data were unable to be derived from GNF Expression Atlas 2 based on U133A and GNF1H Chips, perhaps reflecting parametric uncertainty (Su et al. 2004). However, for gene expression-related sequence features relating to CpG mutation and asymmetric transcription-related repair (Tang et al. 2006), we compared GC content ((G + C)/(G + C + A + T), P = 0.0106), TA skew ((T − A)/(T + A), P = 0.5242), GC skew ((G − C)/(G + C), P = 0.0028), and B factor ((G + T − A − C)/(A + T + G + C), P = 0.0860) (Majewski 2003) (fig. 5A). These differences suggest greater methylation-dependent mutation of CTs relative to GKs during recent human evolution. We then compared the methylation-related sequence features of CT/GK transcribed strands, revealing differences in CpG content (CpG count/total dinucleotide count, P = 0.0011), CpA content (CpA count/total dinucleotide count, P = 0.2555), TpG content (TpG count/total dinucleotide count, P = 0.0174), and DNA methylation-related dinucleotide asymmetry (TpG × CpA)/(CpG × CpG), P = 0.00105) (fig. 5B). These results indicate less transcription-related repair of methylated CTs relative to GKs in germ line–coding sequences. Considered together with the gene essentiality differences presented in table 2, the rapid evolution of CTs relative to GKs suggests an epimutational mechanism for CT functional inhibition that escapes purification while accelerating mutation.

Box plot illustration of CT- and GK-coding sequence features relating to DNA methylation and gene expression. The boxes feature lines at the lower quartile, median, and upper quartile values. The whiskers are lines extending from each end of the boxes to show the extent of the data; outliers are values beyond the ends of the whiskers. (A) Comparison of GC content and dinucleotide skew in CTs and GKs. (B) Frequency of methylation-related dinucleotides and asymmetry in CTs versus GKs. Outliers are denoted by plus signs.

Model of changing human male CT and GK function from germ line to somatic contexts. The x axis is divided into the following time frames: T1, prezygotic spermatogonia and spermatocytes; T2, postzygotic embryonic development; T3, prereproductive infancy and childhood; T4, reproductive adult life; and T5, postreproductive senescence. The y axis models the relative extent of either GK functionality (PCD) or CT dysfunctionality (PGI) during these time frames. Damage/stress-inducible prezygotic promoter (CpG island) methylation of spermatogonial/spermatocyte CTs and GKs, respectively, increases PGI while reducing PCD—thus maximizing genetic variability in response to changing environmental selection pressures. Postfertilization male germ line gene demethylation has the opposite effect, causing a sustained decline in PGI and a rise in PCD. During postreproductive adult life, an age-dependent (as well as damage-inducible) methylation clock induces somatic CT/GK gene inactivation, leading in turn to a senescent rise in PGI and decline of PCD that predisposes to sporadic tumor outgrowth.

Discussion

The central finding of this study is that CTs are evolving more rapidly than GKs and that this process—which appears likely to be mediated by methylation-dependent mutation—is confined to higher sexually reproducing species. These CT–GK distinctions are consistent with earlier work showing that apoptosis-regulatory genes are essential for development of higher organisms (Aravind et al. 2001), whereas germ line mutation of DNA repair genes drives species evolution (Fay et al. 2001). However, because loss of DNA repair capacity also contributes to cancer development (Cleaver et al. 1995; Breivik and Gaudernack 2004), it is also reasonable to expect tumor suppressor genes in general to be under strong purifying selection (Thomas et al. 2003). Here, we propose that this apparent discrepancy arises from a complex mix of dualistic variables: 1) the bifunctional evolutionary role of repair genes in either conserving genetic information or permitting genetic variation, depending on selection pressure; 2) the bifunctional ability of sexual reproduction either to promote (prezygotically) variation through repair inhibition and intra- or intermale sperm competition or to conserve (postzygotically) genetic fidelity through repair activation, apoptosis, and miscarriage; and 3) the bifunctional role of CpG dinucleotides and promoter CpG islands in either enhancing transcription and repair (when demethylated) or in repressing transcription and predisposing to mutation (when methylated).

Epigenetic reprogramming occurs not only in the early embryo, where somatic patterns of gene expression are set, but also during germ cell development (Morgan et al. 2005)—which changes can be heritable for at least 2 generations (Anway et al. 2008). The methylation dynamics of sperm/testis DNA are unique (Oakes et al. 2007a); unlike oocyte DNA, prezygotic protamine-compacted male germ cell DNA tends to be methylated in nonpromoter regions (Oakes et al. 2007b) that undergo rapid demethylation following fertilization (Haaf 2006). Such sex-specific DNA methylation appears necessary but not sufficient (El-Maarri et al. 1998) to explain the higher mutation rate of mammalian male germ cells (Agulnik et al. 1997; Hurst and Ellegren 1998; Wyckoff et al. 2000; Makova and Li 2002)—suggesting in turn that exposures of the (external) testes to heat (Nikolopoulos et al. 2007), DNA damage (Barber et al. 2006), or other insults (Hara et al. 1999) could well play an evolutionarily programmed epimutagenic role, consistent with the postnatal timing of male germ cell promoter methylation (Driscoll and Migeon 1990). Notably, this hypothesis differs from the standard view of male-driven evolution reflecting a simple excess of male germ cell divisions, giving rise in turn to more replicative mutations (Drost and Lee 1995).

In earlier work, we showed that rarely transcribed genes with promoter CpG islands are hot spots for adaptive evolution (Tang and Epstein 2007), raising the possibility that promoter methylation of sperm target gene classes such as CTs could be a mechanistic “missing link” between environmental selection for specific transcriptomes (Su et al. 2004) and/or coding sequence CpG mutations that permit transgenerational propagation of genetic instability (Wu et al. 2007; Morak et al. 2008). Consistent with this, CTs more often contain promoter CpG islands than do GKs (Zhao Y, unpublished data): classic GKs such as TP53 do not contain promoter CpG islands, whereas canonical CTs such as MLH1 and BRCA1 do. Instructively, the latter gene is mutated and not methylated in familial cancer syndromes (Chen et al. 2006), yet is methylated and not mutated in chemotherapy-induced second malignancies (Scardocci et al. 2006); similar exclusivity between repair gene methylation events and oncogenic indels or point mutations in repair-deficient tumors (Esteller et al. 2001; Toyooka et al. 2006) suggests the fluidity of such epimutations. Although in this model extrinsic damage is the major regulator of prezygotic male germ cell CT methylation—as well as being both a cause and effect of progressive suppressor gene repression in precancerous adult somatic tissues (Neri et al. 2007)—age may be as important as damage in the latter process (Kim et al. 2005), with parental (especially paternal) age playing a synergistic role in the former (Oakes et al. 2003).

We define this model of a “methylation clock” regulating the epigenetic inactivation of CT/repair genes in the male germ line and adult somatic tissues—commensurate with extrinsic damage/stress or intrinsic ageing/senescence—as PGI; just as programmed cell death (PCD) is the mechanism of negative selection, so is PGI proposed to be the mechanism of positive selection (fig. 6). We suggest that PGI intensifies genetic divergence during sexual reproduction at the level of sperm–egg fusion, in contrast to PCD which eliminates both oocyte (Suh et al. 2006) and sperm DNA defects after syngamy (Fatehi et al. 2006). This sequence (sperm → ovum, zygote → embryo) of positive followed by negative selection fits with the notion of sexual conflict (Partridge and Hurst 1998), which should enhance biological system robustness and evolvability (Kitano 2004). We also note that heritable, though not necessarily familial, predisposition to carcinogenesis could also be propagated transgenerationally by PGI (Epstein and Zhao 2006b).

What evidence do we have for PGI operating through the male germ line? The original hypothesis arose from prior knowledge, namely, 1) evidence for male-driven evolution from other groups (Agulnik et al. 1997; Hurst and Ellegren 1998; Wyckoff et al. 2000; Makova and Li 2002); 2) evidence for repair genes being speciation genes, implying a permissive role in rapid evolution (Radman and Wagner 1993; Cleaver et al. 1995; Sniegowski 1998); and 3) the external anatomic location of the testis, making male germ cells uniquely vulnerable to mutagenic, yet potentially reparable, environmental damage (Roest et al. 1996; Hsia et al. 2003; Feitsma et al. 2007). Against this background, we needed to integrate the following new data: 1) CT/repair genes are evolving with unexpected rapidity; 2) CT knockouts are relatively dispensable for survival, resulting only in reduced male fertility; and 3) abnormally low CT/repair gene expression is characteristic of teratozoospermia (Zhao Y, unpublished data), a condition of abnormal sperm morphology that does not significantly reduce in vitro fertilization success rates (Keegan et al. 2007). These considerations invited the hypothesis: could the rapid evolution of CT/repair genes reflect selection for a permissive (i.e., causal loss-of-function) role in male-driven evolution? This latter possibility is supported by the finding that heterozygous males and homozygous females can remain fertile when homozygous male repair gene knockouts are sterile (Roest 1996) and that even minimal repair transgene expression suffices to rescue fertility in repair-knockout males (Hsia 2003). Moreover, homozygous repair-deficient males may survive—albeit at the cost of tumor susceptibility—in genetic backgrounds where homozygous females die (Cranston et al. 1997). This striking gender-specific difference strongly suggests a male-specific significance for accelerated CT evolution, which involves interaction of ambient damage with selection for subtle (e.g., epimutational) male germ cell repair defects.

Our gene targeting and familial cancer data confirm that germ line CT defects are less lethal than GK defects (tables 2 and 3). The effects of repair gene targeting depend critically on the extent of functional inhibition and the presence or otherwise of associated mutations; in general, mild (e.g., haploinsufficient) CT/repair defects tend to increase mutation while decreasing apoptosis (Frank et al. 2005; Smilenov et al. 2005) and may even enhance fitness and lifespan (Siegl-Cachedenier et al. 2007), whereas severe repair defects tend to cause increased apoptosis and premature lethality (Henrie et al. 2003). Hence, because low-level sperm DNA damage can be repaired after fertilization of repair-proficient oocytes (Menezo 2006; Marchetti et al. 2007; Fernandez-Gonzalez et al. 2008)—particularly in the setting of prior DNA damage “conditioning” of such oocytes (Agrawal and Wang 2008)—mild nondeletional prezygotic male germ line repair defects could plausibly enhance sperm divergence with minimal fertility compromise, thereby safeguarding species’ evolvability while offsetting transgenerational risks of paternally transmitted birth defects (Marchetti and Wyrobek 2008) or cancer (Zenzes et al. 1999; Yauk et al. 2007). This conclusion is further supported by the finding that chronic exposure of spermatogonia to low-dose damage greatly reduces genetic damage induced by an acute second hit (Cai et al. 1993; Koana et al. 2007). Our findings therefore suggest the evolution of an environmentally interactive genetic program for promoting divergence in the germ line. We note that the related age-dependent predisposition to cancer is not wholly disadvantageous to the species as such mortality may promote redistribution of environmental resources to younger and more fertile individuals.

As an extension of the “immortal strand” hypothesis of stem cell fidelity (Cairns 2006), our findings raise the notion that the transcribed (well repaired, CpG-demethylated) DNA strand represents the “immovable object” of negative selection, whereas the untranscribed (poorly repaired, CpG-methylated) strand provides the “irresistible force” of positive selection. Furthermore, consistent with the notion that sexual conflict selects for distinct gender phenotypes (Hosken et al. 2001), the evolutionary paradigm presented here implies that the usual targets of positive selection—choice and specialization (Barkman 2003; Hamm et al. 2007), discrimination and success (Swanson et al. 2003), and beauty (Morris RD and Morris JA 2004)—are intrinsically male (sperm/PGI dependent) in origin, whereas the targets of negative selection (normality, utility, longevity, and fidelity) are genetically female or oocyte/PCD dependent. Both positively and negatively selected traits are vital for fitness in sexually reproducing species: for example, the reproductive success of butterflies, birds, and peacocks depends on highly variegated yet symmetric surface patterns (Gould JL and Gould CG 1997) that predict a low underlying frequency of deleterious functional mutations (Morris RD and Morris JA 2004). In our model, PGI is driven by sexual selection pressure on the male germ line to optimize as opposed to normalize whatever phenotypes can be optimized—such as sperm velocity (Gage et al. 2004) or ion channel function regulating motility (Podlaha et al. 2005)—while also enhancing variation in species-discriminatory phenotypes such as egg-binding proteins (Moller and Cuervo 2003). Hence, the basis for sexual conflict in our model is that “average” can never be “best” and that “health” may not guarantee “popularity” (Zaidel et al. 2005)—whether with respect to beauty (DeBruine et al. 2007) or to sperm competition (Neff and Pitcher 2005)—thus helping to explain the paradox that mutation rates tend to be reduced by natural selection yet increased by sexual selection (Moller and Cuervo 2003).

In conclusion, we have shown that CTs are less essential for germ line viability and hence more rapidly evolving than GKs. The resulting model of PGI implicates sexual reproduction as an evolutionary masterstroke: uniquely, sex plays off prezygotic positive selection (in which epimutational divergence is accelerated by environmental stress and damage, and efficiently selected and fixed by intra- and/or intermale sperm competition) against the evolutionary safety valves of postzygotic repair and negative selection (Menezo 2006). Via this mechanism, we propose that environmental stressors succeed in the otherwise oxymoronic task of “selecting for divergence” via epigenetic inhibition of DNA repair, thus helping to settle the “4-billion-year struggle of selfish genes to balance the need for variation with the equally important goal of conserving success” (Gould JL and Gould CG 1997). Moreover, if tumors do indeed arise in part as a side effect of PGI, cancer susceptibility may be most accurately viewed as the tumor-permissive “price” paid by multicellular organisms for genetic plasticity, with the species reaping the ultimate evolutionary “reward” of a delayed time to extinction.

Supplementary Material

Supplement 1, 2, and 3 are available at Molecular Biology and Evolution online (http://www.mbe.oxfordjournals.org/).

Supplementary Material [Supplementary Data]

We thank both anonymous reviewers for constructive scrutiny of the manuscript and the Hong Kong Jockey Club for support of the Clinical Research Centre.

Agrawal AF Wang AD Increased transmission of mutations by low-condition females: evidence for condition-dependent DNA repair PLoS Biol 2008 6 e30 18271627 Agulnik AI Bishop CE Lerner JL Agulnik SI Solovyev VV Analysis of mutation rates in the SMCY/SMCX genes shows that mammalian evolution is male driven Mamm Genome 1997 8 134 138 9060413 Andrews JD Mancini DN Singh SM Rodenhiser DI Site and sequence specific DNA methylation in the neurofibromatosis (NF1) gene includes C5839T: the site of the recurrent substitution mutation in exon 31 Hum Mol Genet 1996 5 503 507 8845843 Anway MD Rekow SS Skinner MK Transgenerational epigenetic programming of the embryonic testis transcriptome Genomics 2008 91 30 40 18042343 Aravind L Dixit VM Koonin EV Apoptotic molecular machinery: vastly increased complexity in vertebrates revealed by genome comparisons Science 2001 291 1279 1284 11181990 Babenko VN Basu MK Kondrashov FA Rogozin IB Koonin EV Signs of positive selection of somatic mutations in human cancers detected by EST sequence analysis BMC Cancer 2006 6 36 16469093 Barber RC Hickenbotham P Hatch T (11 co-authors) Radiation-induced transgenerational alterations in genome stability and DNA damage Oncogene 2006 25 7336 7342 16751800 Barkman TJ Evidence for positive selection on the floral scent gene isoeugenol-O-methyltransferase Mol Biol Evol 2003 20 168 172 12598682 Bielas JH Loeb KR Rubin BP True LD Loeb LA Human cancers express a mutator phenotype Proc Natl Acad Sci USA 2006 103 18238 18242 17108085 Blanco D Vicent S Fraga MF (11 co-authors) Molecular analysis of a multistep lung cancer model induced by chronic inflammation reveals epigenetic regulation of p16 and activation of the DNA damage response pathway Neoplasia 2007 9 840 852 17971904 Breivik J The evolutionary origin of genetic instability in cancer development Semin Cancer Biol 2005 15 51 60 15613288 Breivik J Gaudernack G Resolving the evolutionary paradox of genetic instability: a cost-benefit analysis of DNA repair in changing environments FEBS Lett 2004 563 7 12 15063714 Bustamante CD Fledel-Alon A Williamson S (14 co-authors) Natural selection on protein-coding genes in the human genome Nature 2005 437 1153 1157 16237444 Cai L Jiang J Wang B Yao H Wang X Induction of an adaptive response to dominant lethality and to chromosome damage of mouse germ cells by low dose radiation Mutat Res 1993 303 157 161 7694133 Cairns J Cancer and the immortal strand hypothesis Genetics 2006 174 1069 1072 17121966 Cerda S Weitzman SA Influence of oxygen radical injury on DNA methylation Mutat Res 1997 386 141 152 9113115 Chen Y Toland AE McLennan J Fridlyand J Crawford B Costello JF Ziegler JL Lack of germ-line promoter methylation in BRCA1-negative families with familial breast cancer Genet Test 2006 10 281 284 17253935 Cirz RT Romesberg FE Controlling mutation: intervening in evolution as a therapeutic strategy Crit Rev Biochem Mol Biol 2007 42 341 354 17917871 Clark AG Glanowski S Nielsen R (17 co-authors) Inferring nonneutral evolution from human-chimp-mouse orthologous gene trios Science 2003 302 1960 1963 14671302 Cleaver JE Speakman JR Volpe JP Nucleotide excision repair: variations associated with cancer development and speciation Cancer Surv 1995 25 125 142 8718515 Colegrave N Collins S Experimental evolution: experimental evolution and evolvability Heredity 2008 100 464 470 18212804 Comeron JM K-Estimator: calculation of the number of nucleotide substitutions per site and the confidence intervals Bioinformatics 1999 15 763 764 10498777 Cooper DN Krawczak M Cytosine methylation and the fate of CpG dinucleotides in vertebrate genomes Hum Genet 1989 83 181 188 2777259 Cranston A Bocker T Reitmair A Palazzo J Wilson T Mak T Fishel R Female embryonic lethality in mice nullizygous for both Msh2 and p53 Nat Genet 1997 17 114 118 9288110 Crespi BJ Summers K Positive selection in the evolution of cancer Biol Rev Camb Philos Soc 2006 81 407 424 16762098 DeBruine LM Jones BC Unger L Little AC Feinberg DR Dissociating averageness and attractiveness: attractive faces are not always average J Exp Psychol Hum Percept Perform 2007 33 1420 1430 18085954 Doctor KS Reed JC Godzik A Bourne PE The apoptosis database Cell Death Differ 2003 10 621 633 12761571 Dolinoy DC Jirtle RL Environmental epigenomics in human health and disease Environ Mol Mutagen 2008 49 4 8 18172876 Driscoll DJ Migeon BR Sex difference in methylation of single-copy genes in human meiotic germ cells: implications for X chromosome inactivation, parental imprinting, and origin of CpG mutations Somat Cell Mol Genet 1990 16 267 282 1694309 Drost JB Lee WR Biological basis of germline mutation: comparisons of spontaneous germline mutation rates among drosophila, mouse, and human Environ Mol Mutagen 1995 25 Suppl. 26 48 64 7789362 Elena SF de Visser JA Environmental stress and the effects of mutation J Biol 2003 2 12 12831400 El-Maarri O Olek A Balaban B Montag M van der Ven H Urman B Olek K Caglayan SH Walter J Oldenburg J Methylation levels at selected CpG sites in the factor VIII and FGFR3 genes, in mature female and male germ cells: implications for male-driven evolution Am J Hum Genet 1998 63 1001 1008 9758623 Epstein RJ Lin K Tan TW A functional significance for codon third bases Gene 2000 245 291 298 10717480 Epstein RJ Zhao Y Programmed genetic instability revealed by adaptive evolution of caretaker tumor suppressor genes AACR Meeting Abstracts 2006a Epstein RJ Zhao Y Racial differences in lung cancer N Engl J Med 2006b 354 1951 1953; author reply 1951–1953 16672710 Esteller M Fraga MF Guo M (24 co-authors) DNA methylation patterns in hereditary human cancers mimic sporadic tumorigenesis Hum Mol Genet 2001 10 3001 3007 11751682 Fatehi AN Bevers MM Schoevers E Roelen BA Colenbrander B Gadella BM DNA damage in bovine sperm does not block fertilization and early embryonic development but induces apoptosis after the first cleavages J Androl 2006 27 176 188 16304212 Fay JC Wyckoff GJ Wu CI Positive and negative selection on the human genome Genetics 2001 158 1227 1234 11454770 Feitsma H Leal MC Moens PB Cuppen E Schulz RW Mlh1 deficiency in zebrafish results in male sterility and aneuploid as well as triploid progeny in females Genetics 2007 175 1561 1569 17237513 Fernandez-Gonzalez R Moreira PN Perez-Crespo M (11 co-authors) Long-term effects of mouse intracytoplasmic sperm injection with DNA-fragmented sperm on health and behavior of adult offspring Biol Reprod 2008 78 761 772 18199884 Fleming MA Potter JD Ramirez CJ Ostrander GK Ostrander EA Understanding missense mutations in the BRCA1 gene: an evolutionary approach Proc Natl Acad Sci USA 2003 100 1151 1156 12531920 Frank SA Maladaptation and the paradox of robustness in evolution PLoS ONE 2007 2 e1021 17925869 Frank SA Chen PC Lipkin SM Kinetics of cancer: a method to test hypotheses of genetic causation BMC Cancer 2005 5 163 16371164 Frohling S Scholl C Levine RL (21 co-authors) Identification of driver and passenger mutations of FLT3 by high-throughput DNA sequence analysis and functional assessment of candidate alleles Cancer Cell 2007 12 501 513 18068628 Futreal PA Coin L Marshall M Down T Hubbard T Wooster R Rahman N Stratton MR A census of human cancer genes Nat Rev Cancer 2004 4 177 183 14993899 Gadagkar SR Rosenberg MS Kumar S Inferring species phylogenies from multiple genes: concatenated sequence tree versus consensus gene tree J Exp Zoolog B Mol Dev Evol 2005 304 64 74 15593277 Gage MJ Macfarlane CP Yeates S Ward RG Searle JB Parker GA Spermatozoal traits and sperm competition in Atlantic salmon: relative sperm velocity is the primary determinant of fertilization success Curr Biol 2004 14 44 47 14711413 Galhardo RS Hastings PJ Rosenberg SM Mutation as a stress response and the regulation of evolvability Crit Rev Biochem Mol Biol 2007 42 399 435 17917874 Galloway LF Etterson JR Transgenerational plasticity is adaptive in the wild Science 2007 318 1134 1136 18006745 Gatenby RA Vincent TL An evolutionary model of carcinogenesis Cancer Res 2003 63 6212 6220 14559806 Gould JL Gould CG Sexual selection: mate choice and courtship in nature 1997 Basingstoke (UK) Macmillan Gulick JT Divergent evolution through cumulative segregation 1893 Westminster (MD) Smithsonian Institute Haaf T Methylation dynamics in the early mammalian embryo: implications of genome reprogramming defects for development Curr Top Microbiol Immunol 2006 310 13 22 16909904 Hamm D Mautz BS Wolfner MF Aquadro CF Swanson WJ Evidence of amino acid diversity-enhancing selection within humans and among primates at the candidate sperm-receptor gene PKDREJ Am J Hum Genet 2007 81 44 52 17564962 Hara T Sui H Kawakami K Shimada Y Shibuya T Partial hepatectomy strongly increased the mutagenicity of N-ethyl-N-nitrosourea in MutaMouse liver Environ Mol Mutagen 1999 34 121 123 10529735 Hastings PJ Slack A Petrosino JF Rosenberg SM Adaptive amplification and point mutation are independent mechanisms: evidence for various stress-inducible mutation mechanisms PLoS Biol 2004 2 e399 15550983 Hendrikse JL Parsons TE Hallgrimsson B Evolvability as the proper focus of evolutionary developmental biology Evol Dev 2007 9 393 401 17651363 Henrie MS Kurimasa A Burma S Menissier-de Murcia J de Murcia G Li GC Chen DJ Lethality in PARP-1/Ku80 double mutant mice reveals physiological synergy during early embryogenesis DNA Repair (Amst) 2003 2 151 158 12531386 Hiraiwa-Hasegawa M The sight of the peacock's tail makes me sick: the early arguments on sexual selection J Biosci 2000 25 11 18 10824193 Hone DW Benton MJ The evolution of large size: how does Cope's rule work? Trends Ecol Evol 2005 20 4 6 16701331 Horsthemke B Epimutations in human disease Curr Top Microbiol Immunol 2006 310 45 59 16909906 Hosken DJ Garner TW Ward PI Sexual conflict selects for male and female reproductive characters Curr Biol 2001 11 489 493 11412998 Hsia KT Millar MR King S Selfridge J Redhead NJ Melton DW Saunders PT DNA repair gene Ercc1 is essential for normal spermatogenesis and oogenesis and for functional integrity of germ cell DNA in the mouse Development 2003 130 369 378 12466203 Hurst LD Ellegren H Sex biases in the mutation rate Trends Genet 1998 14 446 452 9825672 Huttley GA Easteal S Southey MC Tesoriero A Giles GG McCredie MR Hopper JL Venter DJ Adaptive evolution of the tumour suppressor BRCA1 in humans and chimpanzees. Australian Breast Cancer Family Study Nat Genet 2000 25 410 413 10932184 Iwasa Y Michor F Nowak MA Stochastic tunnels in evolutionary dynamics Genetics 2004 166 1571 1579 15082570 Jacinto FV Esteller M Mutator pathways unleashed by epigenetic silencing in human cancer Mutagenesis 2007 22 247 253 17412712 Johnson T Beneficial mutations, hitchhiking and the evolution of mutation rates in sexual populations Genetics 1999 151 1621 1631 10101182 Keegan BR Barton S Sanchez X Berkeley AS Krey LC Grifo J Isolated teratozoospermia does not affect in vitro fertilization outcome and is not an indication for intracytoplasmic sperm injection Fertil Steril 2007 88 1583 1588 17448467 Kelley JL Madeoy J Calhoun JC Swanson W Akey JM Genomic signatures of positive selection in humans and the limits of outlier approaches Genome Res 2006 16 980 989 16825663 Kim JY Beart RW Shibata D Stability of colon stem cell methylation after neo-adjuvant therapy in a patient with attenuated familial adenomatous polyposis BMC Gastroenterol 2005 5 19 15941485 Kimura M Evolutionary rate at the molecular level Nature 1968 217 624 626 5637732 King JL Jukes TH Non-Darwinian evolution Science 1969 164 788 798 5767777 Kingsolver JG Pfennig DW Individual-level selection as a cause of Cope's rule of phyletic size increase Evolution Int J Org Evolution 2004 58 1608 1612 Kinzler KW Vogelstein B Cancer-susceptibility genes. Gatekeepers and caretakers Nature 1997 386 761 763 9126728 Kitano H Biological robustness Nat Rev Genet 2004 5 826 837 15520792 Knudson AG Chasing the cancer demon Annu Rev Genet 2000 34 1 19 11092820 Koana T Okada MO Ogura K Tsujimura H Sakai K Reduction of background mutations by low-dose X irradiation of Drosophila spermatocytes at a low dose rate Radiat Res 2007 167 217 221 17390729 Lavon I Fuchs D Zrihan D Efroni G Zelikovitch B Fellig Y Siegal T Novel mechanism whereby nuclear factor kappaB mediates DNA damage repair through regulation of O(6)-methylguanine-DNA-methyltransferase Cancer Res 2007 67 8952 8959 17875738 Lenski RE Barrick JE Ofria C Balancing robustness and evolvability PLoS Biol 2006 4 e428 17238277 Levasseur A Orlando L Bailly X Milinkovitch MC Danchin EG Pontarotti P Conceptual bases for quantifying the role of the environment on gene evolution: the participation of positive selection and neutral evolution Biol Rev Camb Philos Soc 2007 82 551 572 17944617 Liao BY Scott NM Zhang J Impacts of gene essentiality, expression pattern, and gene compactness on the evolutionary rate of mammalian proteins Mol Biol Evol 2006 23 2072 2080 16887903 Lin K Tan SB Kolatkar PR Epstein RJ Nonrandom intragenic variations in patterns of codon bias implicate a sequential interplay between transitional genetic drift and functional amino acid selection J Mol Evol 2003 57 538 545 14738312 Lynch M The evolution of genetic networks by non-adaptive processes Nat Rev Genet 2007 8 803 813 17878896 Majewski J Dependence of mutational asymmetry on gene-expression levels in the human genome Am J Hum Genet 2003 73 688 692 12881777 Makova KD Li WH Strong male-driven evolution of DNA sequences in humans and apes Nature 2002 416 624 626 11948348 Marchetti F Essers J Kanaar R Wyrobek AJ Disruption of maternal DNA repair increases sperm-derived chromosomal aberrations Proc Natl Acad Sci USA 2007 104 17725 17729 17978187 Marchetti F Wyrobek AJ DNA repair decline during mouse spermiogenesis results in the accumulation of heritable DNA damage DNA Repair (Amst) 2008 7 572 581 18282746 Maresca B Schwartz JH Sudden origins: a general mechanism of evolution based on stress protein concentration and rapid environmental change Anat Rec B New Anat 2006 289 38 46 16437551 Markov AV The return of the Red Queen, or the law of the growth in the mean duration of the existence of genera during evolution Zh Obshch Biol 2000 61 357 370 10999002 Martin DI Ward R Suter CM Germline epimutation: a basis for epigenetic disease in humans Ann N Y Acad Sci 2005 1054 68 77 16339653 McDonald JH Kreitman M Adaptive protein evolution at the Adh locus in Drosophila Nature 1991 351 652 654 1904993 Menezo Y Oocyte capacity to repair DNA damage induced in sperm J Gynecol Obstet Biol Reprod (Paris) 2006 35 2S19 2S23 17057617 Moller AP Cuervo JJ Sexual selection, germline mutation rate and sperm competition BMC Evol Biol 2003 3 6 12702218 Monk M Epigenetic programming of differential gene expression in development and evolution Dev Genet 1995 17 188 197 8565325 Morak M Schackert HK Rahner N (14 co-authors) Further evidence for heritability of an epimutation in one of 12 cases with MLH1 promoter methylation in blood cells clinically displaying HNPCC Eur J Hum Genet 2008 Morgan HD Santos F Green K Dean W Reik W Epigenetic reprogramming in mammals Hum Mol Genet. 14 Spec No 2005 1 R47 R58 Morris RD Morris JA Sexual selection, redundancy and survival of the most beautiful J Biosci 2004 29 359 366 15381858 Neff BD Pitcher TE Genetic quality and sexual selection: an integrated framework for good genes and compatible genes Mol Ecol 2005 14 19 38 15643948 Nei M Selectionism and neutralism in molecular evolution Mol Biol Evol 2005 22 2318 2342 16120807 Neri S Pawelec G Facchini A Mariani E Microsatellite instability and compromised mismatch repair gene expression during in vitro passaging of monoclonal human T lymphocytes Rejuvenation Res 2007 10 145 156 17518701 Nielsen R Bustamante C Clark AG (13 co-authors) A scan for positively selected genes in the genomes of humans and chimpanzees PLoS Biol 2005 3 e170 15869325 Nikolopoulos G Pyrpassopoulos S Thanassoulas A Klimentzou P Zikos C Vlassi M Vorgias CE Yannoukakos D Nounesis G Thermal unfolding of human BRCA1 BRCT-domain variants Biochim Biophys Acta 2007 1774 772 780 17493881 Nowak MA Michor F Komarova NL Iwasa Y Evolutionary dynamics of tumor suppressor gene inactivation Proc Natl Acad Sci USA 2004 101 10635 10638 15252197 Oakes CC La Salle S Smiraglia DJ Robaire B Trasler JM A unique configuration of genome-wide DNA methylation patterns in the testis Proc Natl Acad Sci USA 2007a 104 228 233 17190809 Oakes CC La Salle S Smiraglia DJ Robaire B Trasler JM Developmental acquisition of genome-wide DNA methylation occurs prior to meiosis in male germ cells Dev Biol 2007b 307 368 379 17559830 Oakes CC Smiraglia DJ Plass C Trasler JM Robaire B Aging results in hypermethylation of ribosomal DNA in sperm and liver of male rats Proc Natl Acad Sci USA 2003 100 1775 1780 12574505 Ohlsson R Cui H He L Pfeifer S Malmikumpu H Jiang S Feinberg AP Hedborg F Mosaic allelic insulin-like growth factor 2 expression patterns reveal a link between Wilms’ tumorigenesis and epigenetic heterogeneity Cancer Res 1999 59 3889 3892 10463576 Ohta T Evolution by nearly-neutral mutations Genetica 1998 102–103 83 90 Olson MV When less is more: gene loss as an engine of evolutionary change Am J Hum Genet 1999 64 18 23 9915938 Partridge L Hurst LD Sex and conflict Science 1998 281 2003 2008 9748155 Pavlicek A Noskov VN Kouprina N Barrett JC Jurka J Larionov V Evolution of the tumor suppressor BRCA1 locus in primates: implications for cancer predisposition Hum Mol Genet 2004 13 2737 2751 15385441 Perrin MC Brown AS Malaspina D Aberrant epigenetic regulation could explain the relationship of paternal age to schizophrenia Schizophr Bull 2007 33 1270 1273 17712030 Petrie M Roberts G Sexual selection and the evolution of evolvability Heredity 2007 98 198 205 17119550 Pigliucci M Is evolvability evolvable? Nat Rev Genet 2008 9 75 82 18059367 Podlaha O Webb DM Tucker PK Zhang J Positive selection for indel substitutions in the rodent sperm protein catsper1 Mol Biol Evol 2005 22 1845 1852 15930155 Ponder RG Fonville NC Rosenberg SM A switch from high-fidelity to error-prone DNA double-strand break repair underlies stress-induced mutation Mol Cell 2005 19 791 804 16168374 Ponting CP Lunter G Signatures of adaptive evolution within human non-coding sequence Hum Mol Genet. 15 Spec No 2006 2 R170 R175 Radman M Wagner R Mismatch recognition in chromosomal interactions and speciation Chromosoma 1993 102 369 373 8365347 Roest HP van Klaveren J de Wit J (13 co-authors) Inactivation of the HR6B ubiquitin-conjugating DNA repair enzyme in mice causes male sterility associated with chromatin modification Cell 1996 86 799 810 8797826 Salnikow K Zhitkovich A Genetic and epigenetic mechanisms in metal carcinogenesis and cocarcinogenesis: nickel, arsenic, and chromium Chem Res Toxicol 2008 21 28 44 17970581 Santarosa M Ashworth A Haploinsufficiency for tumour suppressor genes: when you don't need to go all the way Biochim Biophys Acta 2004 1654 105 122 15172699 Scardocci A Guidi F D'Alo F (12 co-authors) Reduced BRCA1 expression due to promoter hypermethylation in therapy-related acute myeloid leukaemia Br J Cancer 2006 95 1108 1113 17047656 Schneider BL Kulesz-Martin M Destructive cycles: the role of genomic instability and adaptation in carcinogenesis Carcinogenesis 2004 25 2033 2044 15180945 Siegl-Cachedenier I Munoz P Flores JM Klatt P Blasco MA Deficient mismatch repair improves organismal fitness and survival of mice with dysfunctional telomeres Genes Dev 2007 21 2234 2247 17785530 Smilenov LB Tumor development: haploinsufficiency and local network assembly Cancer Lett 2006 240 17 28 16223564 Smilenov LB Lieberman HB Mitchell SA Baker RA Hopkins KM Hall EJ Combined haploinsufficiency for ATM and RAD9 as a factor in cell transformation, apoptosis, and DNA lesion repair dynamics Cancer Res 2005 65 933 938 15705893 Smith NG Hurst LD Molecular evolution of an imprinted gene: repeatability of patterns of evolution within the mammalian insulin-like growth factor type II receptor Genetics 1998 150 823 833 9755212 Sniegowski P Mismatch repair: origin of species? Curr Biol 1998 8 R59 R61 9427635 Sniegowski PD Gerrish PJ Johnson T Shaver A The evolution of mutation rates: separating causes from consequences Bioessays 2000 22 1057 1066 11084621 Su AI Wiltshire T Batalov S (13 co-authors) A gene atlas of the mouse and human protein-encoding transcriptomes Proc Natl Acad Sci USA 2004 101 6062 6067 15075390 Suh EK Yang A Kettenbach A Bamberger C Michaelis AH Zhu Z Elvin JA Bronson RT Crum CP McKeon F p63 protects the female germ line during meiotic arrest Nature 2006 444 624 628 17122775 Swanson WJ Nielsen R Yang Q Pervasive adaptive evolution in mammalian fertilization proteins Mol Biol Evol 2003 20 18 20 12519901 Tang CS Epstein RJ A structural split in the human genome PLoS ONE 2007 2 e603 17622348 Tang CS Zhao YZ Smith DK Epstein RJ Intron length and accelerated 3′ gene evolution Genomics 2006 88 682 689 16928427 Thomas MA Weston B Joseph M Wu W Nekrutenko A Tonellato PJ Evolutionary dynamics of oncogenes and tumor suppressor genes: higher intensities of purifying selection than other genes Mol Biol Evol 2003 20 964 968 12716985 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 7984417 Toyooka S Tokumo M Shigematsu H (12 co-authors) Mutational and epigenetic evidence for independent pathways for lung adenocarcinomas arising in smokers and never smokers Cancer Res 2006 66 1371 1375 16452191 University Medical Center Groningen Familial Cancer Database. UICC 2006 http://www.familialcancerdatabase.nl/ Van Valkenburgh B Wang X Damuth J Cope's rule, hypercarnivory, and extinction in North American canids Science 2004 306 101 104 15459388 Voight BF Kudaravalli S Wen X Pritchard JK A map of recent positive selection in the human genome PLoS Biol 2006 4 e72 16494531 Wagner A Robustness and evolvability: a paradox resolved Proc Biol Sci 2008 275 91 100 17971325 Wee KB Aguda BD Akt versus p53 in a network of oncogenes and tumor suppressor genes regulating cell survival and death Biophys J 2006 91 857 865 16648169 Wood RD Mitchell M Lindahl T Human DNA repair genes, 2005 Mutat Res 2005 577 275 283 15922366 Wu YH Tsai Chang JH Cheng YW Wu TC Chen CY Lee H Xeroderma pigmentosum group C gene expression is predominantly regulated by promoter hypermethylation and contributes to p53 mutation in lung cancers Oncogene 2007 26 4761 4773 17325666 Wyckoff GJ Wang W Wu CI Rapid evolution of male reproductive genes in the descent of man Nature 2000 403 304 309 10659848 Yang Z Nielsen R Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages Mol Biol Evol 2002 19 908 917 12032247 Yauk C Polyzos A Rowan-Carroll A (12 co-authors) Germ-line mutations, DNA damage, and global hypermethylation in mice exposed to particulate air pollution in an urban/industrial location Proc Natl Acad Sci USA 2008 105 605 610 18195365 Yauk CL Berndt ML Williams A Rowan-Carroll A Douglas GR Stampfli MR Mainstream tobacco smoke causes paternal germ-line DNA mutation Cancer Res 2007 67 5103 5106 17545587 Zaidel DW Aarde SM Baig K Appearance of symmetry, beauty, and health in human faces Brain Cogn 2005 57 261 263 15780460 Zenzes MT Puy LA Bielecki R Reed TE Detection of benzo[a]pyrene diol epoxide-DNA adducts in embryos from smoking couples: evidence for transmission by spermatozoa Mol Hum Reprod 1999 5 125 131 10065867 Zhang J Rosenberg HF Nei M Positive Darwinian selection after gene duplication in primate ribonuclease genes Proc Natl Acad Sci USA 1998 95 3708 3713 9520431