Genetic evidence for contribution of human dispersal to the genetic diversity of EBA-175 in Plasmodium falciparum
© Yasukochi et al. 2015
Received: 27 January 2015
Accepted: 21 May 2015
Published: 1 August 2015
The 175-kDa erythrocyte binding antigen (EBA-175) of Plasmodium falciparum plays a crucial role in merozoite invasion into human erythrocytes. EBA-175 is believed to have been under diversifying selection; however, there have been no studies investigating the effect of dispersal of humans out of Africa on the genetic variation of EBA-175 in P. falciparum.
The PCR-direct sequencing was performed for a part of the eba-175 gene (regions II and III) using DNA samples obtained from Thai patients infected with P. falciparum. The divergence times for the P. falciparum eba-175 alleles were estimated assuming that P. falciparum/Plasmodium reichenowi divergence occurred 6 million years ago (MYA). To examine the possibility of diversifying selection, nonsynonymous and synonymous substitution rates for Plasmodium species were also estimated.
A total of 32 eba-175 alleles were identified from 131 Thai P. falciparum isolates. Their estimated divergence time was 0.13–0.14 MYA, before the exodus of humans from Africa. A phylogenetic tree for a large sequence dataset of P. falciparum eba-175 alleles from across the world showed the presence of a basal Asian-specific cluster for all P. falciparum sequences. A markedly more nonsynonymous substitutions than synonymous substitutions in region II in P. falciparum was also detected, but not within Plasmodium species parasitizing African apes, suggesting that diversifying selection has acted specifically on P. falciparum eba-175.
Plasmodium falciparum eba-175 genetic diversity appeared to increase following the exodus of Asian ancestors from Africa. Diversifying selection may have played an important role in the diversification of eba-175 allelic lineages. The present results suggest that the dispersals of humans out of Africa influenced significantly the molecular evolution of P. falciparum EBA-175.
Approximately 200 Plasmodium species parasitize different vertebrate groups, including lizards, birds, and mammals . Of them, five Plasmodium species, namely Plasmodium falciparum, Plasmodium vivax, Plasmodium ovale (consisting of two subspecies, Plasmodium ovale curtisi and Plasmodium ovale wallikeri ), Plasmodium malariae, and Plasmodium knowlesi, can infect humans. In particular, P. falciparum causes the most severe form of malaria in humans; however, when compared with Plasmodium reichenowi found in chimpanzees (Pan troglodytes), P. falciparum appears to be phylogenetically distantly related to other human malaria parasites [1, 3–5].
The 175-kDa erythrocyte binding antigen (EBA-175) of P. falciparum binds with a sialic acid on human glycophorin A (GYPA); the interaction of these molecules is the part of a major pathway for malaria parasite invasion into erythrocytes. The primary structure of eba-175 gene is divided into seven regions, region I–VII . Region II is a cysteine-rich region responsible for the interaction between EBA-175 and GYPA on the erythrocyte surface . Previous studies have shown a significant excess of nonsynonymous substitutions over synonymous substitutions in this region in P. falciparum [8–11]; however, no studies have assessed to date the ratio of nonsynonymous to synonymous substitutions in other closely related Plasmodium species. Nonsynonymous substitution rates of host and pathogen are expected to increase synergistically as a consequence of the host-pathogen co-evolutionary arms race. When human and macaque genomes were compared, the gypa gene shows the highest number of nonsynonymous substitutions per nonsynonymous sites among 280 genes . In addition, the rate of nonsynonymous substitutions in eba-175 gene is also the highest among 10 genes compared between P. falciparum and P. reichenowi . Thus, the high level of genetic polymorphisms shown by eba-175 and gypa is likely to result from host–pathogen coevolution.
Amino acid substitutions in region II of eba-175 and gypa seem to have been enhanced by diversifying selection. However, it remains unclear how human evolution has influenced P. falciparum eba-175 genetic diversity. To elucidate this, in the present study, the regions II and III of eba-175 from a Thai P. falciparum population were examined. When compared with P. reichenowi eba-175 sequence, eba-175 alleles from this population can be traced back to approximately 130–140 thousand years ago. A further analysis for a large sequence dataset of P. falciparum eba-175 alleles from across the world revealed an Asian-specific basal cluster in a phylogenetic tree. In addition, an evolutionary analysis detected a significant excess of nonsynonymous substitutions over synonymous substitutions in the region II of eba-175 within the Thai P. falciparum population, but not within Plasmodium populations parasitizing African apes. Thus, the results from the present study suggest that human dispersal out of Africa contributed to the genetic diversification of P. falciparum eba-175.
This study was approved by the Institutional Review Board of the Faculty of Tropical Medicine, Mahidol University, and the Research Ethics Committee of the School of Medicine, The University of Tokyo.
Peripheral blood samples were obtained from 203 P. falciparum-infected patients from Thailand. In addition, a dataset of nucleotide sequences including isolates of human P. falciparum, gorilla (Gorilla gorilla) Plasmodium, chimpanzee Plasmodium, and P. reichenowi was built from data obtained from .
Experimental procedures for DNA sequencing of eba-175
Genomic DNA was extracted from pretreated peripheral blood samples from patients infected with P. falciparum using a QIAamp Blood Kit (Qiagen, Hilden, Germany). DNA fragments covering a part of the eba-175 coding sequence (regions II and III) of P. falciparum were amplified by PCR using the following sets of primers: EBA175-fragment1, 5′-ggaagaaatacttcatctaataacg-3′ (forward) and 5′-catcctttacttctggacacatcg-3′ (reverse), and EBA175-fragment2, 5′-gagactctgaaggttgaatgcaa-3′ (forward) and 5′-aggtgtattagacatatcttggtc-3′ (reverse). These primers were designed based on the eba-175 reference sequence from P. falciparum (GenBank accession no. X52524). PCR amplification was performed in a 13.0-µL reaction mixture containing 0.125 µL (0.125 µM) each of forward and reverse primers, 0.125 µL TAKARA LA Taq™ (5 units/µL), 1.25 µL 10× LA PCR™ Buffer II (Mg2+ free), 1.25 µL 25 mM MgCl2, 1.25 µL 2.5 mM dNTP mixture, 0.5 µL (5 ng) of genomic DNA template, and 8.375 µL dH2O using a GeneAmp® PCR System 9700 (Applied Biosystems, Foster City, CA, USA). The PCR cycling conditions for each primer pair were 60 s initial denaturation at 94°C, followed by 40 cycles of 30 s denaturation at 94°C, 30 s annealing at 56°C, and 150 s extension at 72°C, and a final step of 5 min extension at 72°C. The PCR products were subsequently sequenced using an ABI Prism 3100 Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). Primer sequences used for direct sequencing are available upon request. The isolates showing multiple superimposed electropherogram peaks at a single site following PCR-direct sequencing and a secondary peak greater than 30% of the predominant peak were considered to be mixed infections and excluded from further analyses. Low-quality sequences (i.e., high background noise or too weak signal) were also excluded. As a result, 131 sequences representing the single or most abundant sequence in each DNA sample were included in the analyses.
The nucleotide sequences obtained were aligned and translated into putative amino acid sequences using MEGA v.5.2 . To examine the phylogenetic relations among 32 distinct eba-175 Thai P. falciparum alleles and two eba-175 P. reichenowi alleles (CBXM000000000 and AJ251848), a maximum likelihood (ML) tree was constructed based on the Hasegawa–Kishino–Yano model . To obtain the ML tree, a nearest-neighbor-interchange (NNI) search was applied. In addition, a neighbor-joining (NJ)  tree was generated using 194 eba-175 partial region II sequences from P. falciparum worldwide and two P. reichenowi sequences (CBXM000000000 and AJ251848), based on the Nei–Gojobori (NG) model  and the Jukes–Cantor (JC) correction . The construction of phylogenetic trees and estimation of best-fit substitution model for the ML tree were implemented in MEGA v.5.2 . All the positions containing insertions/deletions were eliminated from the analyses (complete deletion option). Branch support values were computed by bootstrap analyses with 1,000 replications. A network of 194 P. falciparum and two P. reichenowi eba-175 alleles was also constructed based on synonymous substitutions using the neighbor-net method  in SplitsTree4 ver. 4.13.1 .
The time to the most recent common ancestor (tMRCA) of the eba-175 alleles from Thai falciparum was estimated from the linearized tree based on synonymous substitutions among the 32 distinct eba-175 alleles by using the MEGA v5.2 . The neutral substitution rate was calculated assuming that P. falciparum and P. reichenowi diverged 6 million years ago (MYA) [5, 20]. In addition, the MCMCTree program in the PAML 4.8 package  was used to estimate tMRCA based on the amino acid sequences. The minimum and maximum age constraints on the root age (the divergence time between P. falciparum and P. reichenowi) were set to 5 and 7 MYA, respectively. The tMRCA estimation was based on a WAG model  for amino acid substitutions. In the MCMC process, sampling occurred every 100 generations for 10,000 generations and the first 50,000 generations were discarded as burn-in.
To detect the signatures of natural selection, the number of nonsynonymous substitutions per nonsynonymous site (d N) and synonymous substitutions per synonymous site (d S) for all the pairs formed by the 32 distinct Thai P. falciparum alleles, 16 from chimpanzee Plasmodium spp., 11 from gorilla Plasmodium spp., and four from P. reichenowi sequences were estimated using the NG model with the JC correction in MEGA v.5.2 . Significant difference between d N and d S was assessed by Wilcoxon signed-rank test. For all the 131 Thai P. falciparum isolates, the numbers of nonsynonymous substitutions per nonsynonymous site (π N) and synonymous substitutions per synonymous site (π S) were also calculated in the same manner as d N and d S. In addition, the McDonald–Kreitman (MK) test  was performed for detecting natural selection signal using DnaSP v5 software . Tajima’s D test  was performed for 131 Thai P. falciparum eba-175 sequences using DnaSP v5 software , where the test statistic was analytically calculated. A two-sided P value of less than 0.05 was considered statistically significant.
A Wu–Kabat plot was used to estimate the level of amino acid variability for the 32 distinct Thai P. falciparum eba-175 alleles . The Wu–Kabat plot estimates the level of variability for each amino acid position in the sequence alignment, measured as the number of amino acids at each site divided by the maximum frequency of amino acid for all sites.
Detection of eba-175 alleles
Phylogenetic relations among eba-175 alleles
Estimated divergence time
The d s values for regions II and III for all the pairs formed by the 32 distinct eba-175 alleles were calculated to estimate tMRCA of eba-175 alleles in the Thai population. The neutral mutation rate of the eba-175 gene was extrapolated from the calibration point derived from the divergence time of P. falciparum and P. reichenowi (6 MYA) [5, 20] by using the linearized tree of eba-175 alleles in the MEGA program . Thus, the estimated neutral mutation rate was 1.0 × 10−8 per site per year. Accordingly, the estimated tMRCA for eba-175 was approximately 0.14 MYA. The number of synonymous substitutions observed in Thai P. falciparum isolates was small (maximum d S value = 2); consequently, MCMCTree was used to estimate the tMRCA of eba-175 alleles based on amino acid substitutions within region III. In this case, the estimated tMRCA was approximately 0.13 MYA (95% highest posterior density confidential interval = 0.07–0.23 MYA). Notably, these estimations rely on the assumption that P. falciparum and P. reichenowi diverged 6 MYA.
Diversifying selection on eba-175 region II
Comparison of nonsynonymous (d N) and synonymous (d S substitution rates in Plasmodium eba-175 region II)
d N/d S
Human Plasmodium falciparum isolates
0.005 ± 0.001
0.002 ± 0.001
<2.2 × 10−16
0.010 ± 0.004
0.000 ± 0.000
Chimpanzee Plasmodium isolates
0.089 ± 0.013
0.110 ± 0.026
<2.2 × 10−16
Gorilla Plasmodium isolates
0.169 ± 0.019
0.207 ± 0.037
<2.2 × 10−16
0.003 ± 0.002
0.005 ± 0.005
The McDonald–Kreitman (MK) test  for sequences of eba-175 region II in 32 Thai P. falciparum alleles and one in P. reichenowi showed that the ratio of nonsynonymous to synonymous polymorphic sites within species (Pn/Ps = 19/1) was significantly higher than that of fixed sites between species (Dn/Ds = 116/48; P = 0.017, Fisher’s exact test). However, the MK test for Plasmodium isolates from African apes did not show significant differences between Pn/Ps and Dn/Ds (Pn/Ps = 59/23 and Dn/Ds = 14/6, P-value = 1.00 for 16 chimpanzee Plasmodium isolates and one P. reichenowi; Pn/Ps = 81/29 and Dn/Ds = 6/4, P = 0.46 for 11 gorilla Plasmodium isolates and one P. reichenowi). The results from the MK test suggest that either purifying selection or diversifying selection has acted on eba-175 in Thai P. falciparum population.
Tajima’s D test  was used to test for departure from selective neutrality in 131 eba-175 sequences of Thai P. falciparum. This test compares two population genetic parameters, one estimated from mean pairwise nucleotide differences and the other from the number of mutations. The results revealed a significant positive Tajima’s D value (Tajima’s D statistic = 3.01 and P value <0.01), suggesting the balancing selection on eba-175 in Thai P. falciparum. The possibility of a recent reduction in population size that provided the significant positive Tajima’s D statistic may be excluded, since both the d N/d S ratio test and the MK test also suggested the existence of positive diversifying selection.
To assess the relation between amino acid variability and the erythrocyte binding site, the level of amino acid variability at each site was examined using a Wu–Kabat plot (Additional file 2). The Wu–Kabat plot showed that the level of amino acid variability at some codon sites outside the sites of direct interaction between P. falciparum EBA-175 and human GYPA molecules  was higher than the variation level at their interaction sites. These variable sites may be located in regions recognized by human antibodies if the higher degree of variation is caused by diversifying selection favoring mutations to other amino acids.
Modern humans are believed to have emerged in Africa approximately 0.2 MYA and subsequently dispersed and colonized other continents after their exodus from Africa (known as the “out-of-Africa event”) approximately 0.1 MYA, although the accuracy of these estimates remains a contentious issue [29–32]. Here tMRCA for Thai P. falciparum eba-175 was examined, and our results, 0.14 MYA from synonymous substitutions and 0.13 MYA from amino acid substitutions, suggest that the tMRCA of Thai P. falciparum may predate the out-of-Africa event but after the emergence of modern humans. However, this estimation relies largely on the assumption that P. falciparum diverged from P. reichenowi 6 MYA [5, 20]. A recent phylogenetic analysis for Plasmodium infecting Homininae species suggested that Plasmodium infecting gorillas was transmitted to modern humans in recent times . This possible recent evolutionary origin of human P. falciparum is incompatible with the present assumption of that P. falciparum/P. reichenowi divergence time is similar to that of humans/chimpanzees (i.e., ca. 6 MYA [34–37]). However, regardless of the tMRCA estimate, ancestral human dispersal and recent increase in human population size, resulting in the increase in P. falciparum population size, are likely to have contributed to the eba-175 diversification of P. falciparum (i.e., the emergence of Asian-specific clade).
The comparison of d N/d S ratios of eba-175 region II sequences among Plasmodium species showed an excess of nonsynonymous substitutions over synonymous substitutions in human P. falciparum but not in Plasmodium spp. infecting African apes and P. reichenowi. The result suggests that diversifying selection has affected eba-175 region II in Thai P. falciparum, as previously reported [8–11]. The results on π N/π S ratios and MK test  also supported the diversifying selection hypothesis. On the other hand, the estimated d N/d S ratios and MK test  suggested that eba-175 genetic diversities in other Plasmodium relatives have not been affected by diversifying selection. Thus, the EBA-175 protein may be the target for the immune response against P. falciparum malaria only in humans.
In this study, the tMRCA was estimated under the assumption of no inter-allelic recombination. The presence of inter-allelic recombination may affect the estimation of tMRCA. Since the DnaSP program  suggested the existence of recombination among 32 eba-175 alleles (Minimum number of recombination events, Rm: 8), we investigated the possible recombinants by using the GENECONV program , and detected 21 possible recombinants. After the removal of 21 possible recombinants, we recalculated the tMRCA of the remaining 11 eba-175 alleles in Thai P. falciparum. The estimated tMRCA was approximately 0.12 MYA that was roughly equivalent to the tMRCA (0.14 MYA) estimated by using all of 32 alleles. In addition, the d N/d S ratio of 11 sequences not including recombinant sequences (2.46) was not largely different from that of 32 sequences (2.98). Thus, our results seem not to be affected by the presence of possible recombinants.
The genetic diversity in region II of P. falciparum eba-175 seems to have been increased after the exodus from Africa of ancestral modern humans. As a consequence of the human expansion followed by an increase in P. falciparum population size, diversifying selection may have efficiently maintained the nonsynonymous substitutions in region II of Thai P. falciparum eba-175. Human dispersal out of Africa would have had a major impact on molecular evolution of P. falciparum eba-175.
YY conducted the statistical analyses and wrote the manuscript. JP and HH collected blood samples. IN, JP, and HH extracted DNA from blood samples. IN carried out the experiments. YY, JP, and JO participated in the design of the study. JO was involved in the interpretation of the data and preparation of the manuscript. All authors have read and approved the final manuscript.
The authors deeply thank all the subjects for their participation in the study. This study was partly supported by KAKENHI (25650125) Grant-in-Aid for Challenging Exploratory Research and KAKENHI (26305015) Grant-in-Aid for Scientific Research (B), the Takeda Science Foundation, and KAKENHI (26-1601) Grant-in-Aid for JSPS Fellows.
Compliance with ethical guidelines
Competing interests The authors declare that they have no competing interests.
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- Rich SM, Ayala FJ (2006) Evolutionary origins of human malaria parasites. In: Arese P, Dronamraju KR (eds) Malar Genet Evol Asp. Springer, New York, pp 125–146 (Emerging Infectious Diseases of the 21st Century) View ArticleGoogle Scholar
- Sutherland CJ, Tanomsing N, Nolder D, Oguike M, Jennison C, Pukrittayakamee S et al (2010) Two nonrecombining sympatric forms of the human malaria parasite Plasmodium ovale occur globally. J Infect Dis 201:1544–1550PubMedView ArticleGoogle Scholar
- Vargas-Serrato E, Corredor V, Galinski MR (2003) Phylogenetic analysis of CSP and MSP-9 gene sequences demonstrates the close relationship of Plasmodium coatneyi to Plasmodium knowlesi. Infect Genet Evol 3:67–73PubMedView ArticleGoogle Scholar
- Martinsen ES, Perkins SL, Schall JJ (2008) A three-genome phylogeny of malaria parasites (Plasmodium and closely related genera): evolution of life-history traits and host switches. Mol Phylogenet Evol 47:261–273PubMedView ArticleGoogle Scholar
- Prugnolle F, Durand P, Ollomo B, Duval L, Ariey F, Arnathau C et al (2011) A fresh look at the origin of Plasmodium falciparum, the most malignant malaria agent. PLoS Pathog 7:e1001283PubMed CentralPubMedView ArticleGoogle Scholar
- Adams JH, Sim BK, Dolan SA, Fang X, Kaslow DC, Miller LH (1992) A family of erythrocyte binding proteins of malaria parasites. Proc Natl Acad Sci 89:7085–7089PubMed CentralPubMedView ArticleGoogle Scholar
- Sim B, Chitnis C, Wasniowska K, Hadley T, Miller L (1994) Receptor and ligand domains for invasion of erythrocytes by Plasmodium falciparum. Science 264:1941–1944PubMedView ArticleGoogle Scholar
- Baum J, Thomas AW, Conway DJ (2003) Evidence for diversifying selection on erythrocyte-binding antigens of Plasmodium falciparum and P. vivax. Genetics 163:1327–1336PubMed CentralPubMedGoogle Scholar
- Escalante A, Lal A, Ayala F (1998) Genetic polymorphism and natural selection in the malaria parasite Plasmodium falciparum. Genetics 149:189–202PubMed CentralPubMedGoogle Scholar
- Wang HY, Tang H, Shen CKJ, Wu CI (2003) Rapidly evolving genes in human. I. The glycophorins and their possible role in evading malaria parasites. Mol Biol Evol 20:1795–1804PubMedView ArticleGoogle Scholar
- Verra F, Chokejindachai W, Weedall GD, Polley SD, Mwangi TW, Marsh K et al (2006) Contrasting signatures of selection on the Plasmodium falciparum erythrocyte binding antigen gene family. Mol Biochem Parasitol 149:182–190PubMedView ArticleGoogle Scholar
- Benson DA, Cavanaugh M, Clark K, Karsch-Mizrachi I, Lipman DJ, Ostell J et al (2013) GenBank. Nucleic Acids Res 41:D36–D42PubMed CentralPubMedView ArticleGoogle Scholar
- Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S (2011) MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol 28:2731–2739PubMed CentralPubMedView ArticleGoogle Scholar
- Hasegawa M, Kishino H, Yano T (1985) Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol 22:160–174PubMedView ArticleGoogle Scholar
- Saitou N, Nei M (1987) The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425PubMedGoogle Scholar
- Nei M, Gojobori T (1986) Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol Biol Evol 3:418–426PubMedGoogle Scholar
- Jukes T, Cantor C (1969) Evolution of protein molecules. In: Munro H (ed) Mamm protein Metab. Academic Press, New York, pp 21–132View ArticleGoogle Scholar
- Bryant D, Moulton V (2004) Neighbor-net: an agglomerative method for the construction of phylogenetic networks. Mol Biol Evol 21:255–265PubMedView ArticleGoogle Scholar
- Huson DH, Bryant D (2006) Application of phylogenetic networks in evolutionary studies. Mol Biol Evol 23:254–267PubMedView ArticleGoogle Scholar
- Escalante AA, Ayala FJ (1994) Phylogeny of the malarial genus Plasmodium, derived from rRNA gene sequences. Proc Natl Acad Sci 91:11373–11377PubMed CentralPubMedView ArticleGoogle Scholar
- Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24:1586–1591PubMedView ArticleGoogle Scholar
- Whelan S, Goldman N (2001) A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Mol Biol Evol 18:691–699PubMedView ArticleGoogle Scholar
- McDonald JH, Kreitman M (1991) Adaptive protein evolution at the Adh locus in Drosophila. Nature 351:652–654PubMedView ArticleGoogle Scholar
- Librado P, Rozas J (2009) DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25:1451–1452PubMedView ArticleGoogle Scholar
- Tajima F (1989) Statistical method for testing the neutral mutation hypothesis by DNA polymorphism. Genetics 123:585–595PubMed CentralPubMedGoogle Scholar
- Wu T, Kabat E (1970) An analysis of the sequences of the variable regions of Bence Jones proteins and myeloma light chains and their implications for antibody complementarity. J Exp Med 132:211–250PubMed CentralPubMedView ArticleGoogle Scholar
- Ware LA, Kain KC, Lee Sim BK, Haynes JD, Baird JK, Lanar DE (1993) Two alleles of the 175-kilodalton Plasmodium falciparum erythrocyte binding antigen. Mol Biochem Parasitol 60:105–109PubMedView ArticleGoogle Scholar
- Tolia NH, Enemark EJ, Sim BKL, Joshua-Tor L (2005) Structural basis for the EBA-175 erythrocyte invasion pathway of the malaria parasite Plasmodium falciparum. Cell 122:183–193PubMedView ArticleGoogle Scholar
- Excoffier L (2002) Human demographic history: refining the recent African origin model. Curr Opin Genet Dev 12:675–682PubMedView ArticleGoogle Scholar
- Stringer C (2002) Modern human origins: progress and prospects. Philos Trans R Soc Lond B Biol Sci 357:563–579PubMed CentralPubMedView ArticleGoogle Scholar
- Stringer C (2003) Human evolution: out of Ethiopia. Nature 423:692–695PubMedView ArticleGoogle Scholar
- Stewart JR, Stringer CB (2012) Human evolution out of Africa: the role of refugia and climate change. Science 335:1317–1321PubMedView ArticleGoogle Scholar
- Liu W, Li Y, Learn GH, Rudicell RS, Robertson JD, Keele BF et al (2010) Origin of the human malaria parasite Plasmodium falciparum in gorillas. Nature 467:420–425PubMed CentralPubMedView ArticleGoogle Scholar
- Satta Y, Hickerson M, Watanabe H, O’hUigi C, Klein J (2004) Ancestral population sizes and species divergence times in the primate lineage on the basis of intron and BAC end sequences. J Mol Evol 59:478–487PubMedView ArticleGoogle Scholar
- Steiper ME, Young NM (2006) Primate molecular divergence dates. Mol Phylogenet Evol 41:384–394PubMedView ArticleGoogle Scholar
- Matsui A, Hasegawa M (2012) Molecular phylogeny and evolution in primates. In: Imai H, Go Y, Hirai H (eds) Post-Genome Biol Primates. Springer Tokyo, Tokyo, pp 243–267 (Primatology Monographs) View ArticleGoogle Scholar
- Scally A, Dutheil JY, Hillier LW, Jordan GE, Goodhead I, Herrero J et al (2012) Insights into hominid evolution from the gorilla genome sequence. Nature 483:169–175PubMed CentralPubMedView ArticleGoogle Scholar
- Sawyer S (1989) Statistical tests for detecting gene conversion. Mol Biol Evol 6:526–538PubMedGoogle Scholar