* Centre de Recherche, Hôpital Sainte-Justine, Montréal, Quebec, Canada
Département de Pédiatrie
Département de Nutrition, Université de Montréal, Québec, Canada
Correspondence: E-mail: damian.labuda{at}umontreal.ca.
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Abstract |
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Key Words: human populations genetic diversity scavenger receptor gene coalescence analysis
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Introduction |
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The SR-BI gene is composed of 13 exons that are spread over 86 kb on chromosome 12q24.3132; its splice variant SR-BII, obtained by skipping the 129-nucleotide-long exon 12, is expressed in rodents and humans (Webb et al. 1997; 1998). Certain hormones have been shown to modulate its splicing (Graf, Roswell, and Smart 2001), consistent with the notion that these isoforms may represent part of the HDL-cholesterol metabolism regulation mechanism. In the context of current efforts to identify and characterize polymorphisms conferring susceptibility alleles associated with disease risk or therapeutic response, genes implicated in cholesterol and lipid metabolism have drawn considerable attention (Clark et al. 1998; Fullerton et al. 2000; 2002). However, except for a few variants identified in individuals of European descent (Acton et al. 1999), there has been no systematic study of the SR-BI/BII locus. We present data on allelic diversity in its coding region and the resulting haplotypes. Our analysis suggests the possible involvement of selection in the evolutionary history of this locus, a finding that could be of potential relevance for genetic epidemiology.
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Materials and Methods |
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Polymerase Chain Reaction Amplification
Polymerase chain reaction (PCR) primer pairs (table 1) were designed for exons 212 outside the exonic borders. For exon 1, where no downstream sequence (intron 1) was available, the reverse primer intrudes 22 nucleotides into the exon (GenBank entries Z22555, gi: 397606 and AC020773 for cDNA and genomic sequence, respectively). According to Cao et al. (1997), the nucleotide 143 positions upstream of initiation codon ATG was considered as a transcription start site, and hence the beginning of exon 1. For exon 13 (932 bp), five overlapping fragments (A to E) were used to cover the sequence with shorter DNA fragments better suited for Single-Strand Conformation Polymorphism (SSCP) analysis (Orita et al. 1989).
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SSCP Analysis, Sequencing, and Genotyping
Conformational DNA variants were analyzed by electrophoresis in a 6% polyacrylamide gel containing 10% glycerol (acrylamide-bisacrylamide ratio of 29:1 and for exon 7 also 50:1) in TBE (0.089 M Tris-borate pH 8, 0.01 M EDTA). The PCR products were mixed (1:2) with 95% formamide, heated at 94°C for 5 min, and cooled on ice. Electrophoresis was carried out at room temperature for 1621 h, at 400 V, in an S2 apparatus (Life Technologies). The dried gel was exposed using X-OMAT AR Kodak film. Gel mobility variants were analyzed by dideoxy-sequencing (Thermo Sequenase Radiolabeled Terminator Cycle Sequencing Kit, USB Corporation, Cleveland, Ohio) according to the manufacturer's protocol. Partial sequences in a subset of the analyzed fragments were determined in the common chimpanzee (DNA sample from BIOS Laboratories) in order to assist the assignment of the ancestral allele in polymorphisms 14, 9, 12, and 13. Because of characteristic gel mobility profiles, alleles were unambiguously assigned for both homozygote and heterozygote individuals. The genotypes obtained in this way were subsequently used to solve the underlying haplotypes.
Haplotype Solving and Networks
Of the 89 individuals examined, 60 were either homozygous or heterozygous at a single site, yielding unambiguous haplotype solutions. Furthermore, 27 individuals were heterozygous at more than one site and 2 had missing genotypes at position 4 or positions 13, respectively. All genotypes were analyzed using the software PHASE, version 1.0 (Stephens, Smith, and Donnelly 2001). Repeated analyses led to stable solutions except for four genotypes consisting of combinations of one known and a new or inferred haplotype. Preference was given to combinations involving known haplotypes of higher regional population frequency. The alternative solutions are reported later (table 3) to indicate that these minor haplotypes are not inferred without ambiguity inherent in the data. A maximum parsimony network of haplotypes was constructed manually, first from the haplotypes connectable by mutations only, and then by addition of the recombinant haplotypes (recurrent mutations were considered unlikely).
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Coalescence analysis was carried out according to the method of Griffiths and Tavaré (1994) using genetree (v. 8.3) on the full data set (excluding recombinant haplotypesi.e., 12 out of 178 chromosomes in the analyzed sample); maximum likelihood estimates of (i.e.,
ML), the time to the most recent common ancestor (TMRCA), and the ages of mutations were obtained conditional on the haplotype tree, assuming an infinite-sites model, constant population size, and random mating. The number of iterations per run was sufficiently large for estimates to remain constant over repeated runs, which only differed in the random number seed. Estimates of
ML were also obtained under a model of exponential growth, concurrently yielding an estimate of growth rate ß. Particularly in this model the population size exponentially declines backward in time at rate ß from a current size Ne(0), such that the size of the population at time t is N(t) = Ne(0) e-ßt (note that t = g/2Ne(0), where g is the number of generations ago). To calculate effective population sizes, we used the mutation rate estimate of Fan et al. (2002) of 1.04 x 10-8 per nucleotide per generation (or 5.2 x 10-10 per nucleotide per year), obtained from a comparison of 108-kb human expressed sequence tags (ESTs) with the corresponding great and lesser ape sequences. This rate compares well with the mutation rate of 10-9 per nucleotide per year based on the divergence of 0.15 between human and bovine SR-BI/II cDNAs, taking into account the slowing down of the mutation rate and extended generation time in primate lineages (Koop et al. 1989; Yi, Ellsworth, and Li 2002). Note that use of the value of 10-9, twice as large as the Fan et al. (2002) estimate, would result in a twofold decrease of the reported Ne and, consequently, the TMRCA and mutation age estimates. From the genetic map of Kong et al. (2002), we obtained an average recombination rate of about 3.1% per Mb per generation.
Interspecies Comparative Analysis
Amino acid sequence of the human protein was compared to the corresponding sequences of rat, mouse, bovine, Chinese hamster, and pig (GenBank entries NP 113729, NP 058021, AAB70920.1, AAA61572, and AAL75567.1, respectively) to assess evolutionary conservation of amino acid substitution polymorphisms.
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Results |
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Age of Mutations
We used a coalescent model to infer the time scale of the origin and evolution of the variation within SR-BI/II locus. The underlying gene tree used in this analysis (fig. 4) was rooted by assuming that haplotype H2 was ancestral (table 3); five recombinant haplotypes representing 12 of the 178 chromosomes analyzed were not included in this analysis (see Materials and Methods). Given = 4Neµ, and µ = 3.5 x 10-5 as mutation rate per analyzed SR-BI/II segment per generation, we evaluated Ne at 8,500, 17,500, and 21,900 from
,
S and
ML, respectively, comparable to values reported in the literature (Li and Sadler 1991; Harding et al. 1997; Jaruzelska et al. 1999; Fan et al. 2002). For a generation time of 20 years, assuming
to be known and setting it equal to
ML, we obtained an estimate of TMRCA of 1.04 (standard deviation of 0.36) in coalescence units (or 2Ne generations; fig. 4), corresponding to a TMRCA of 910 ± 320 Kyr (thousand of years). Using
yields a TMRCA of 1.55 ± 0.5 coalescence units, which corresponds to a time depth of 530 ± 170 Kyr, and thus a shallower tree than the one based on
ML. Time estimates based on
S are between those using
ML and
(see
values in table 2). From this point forward, we will only refer to the values obtained based on
ML (table 2). The age of mutation 9 is 0.42 ± 0.25 in 2Ne generations (fig. 4) or 370 ± 220 Kyr. The estimates for mutations 13, 5, 1, and 12 were 250 ± 210, 250 ± 200, 140 ± 135, and 90 ± 75 Kyr, respectively. Other mutations appeared younger, most less than 50 or even 10 Kyr old (fig. 4, filled circles). On a relative scale, the oldest mutation, 9, which splits the diversity between H2-derived and H1-derived branches, occurs closer to the present than the half-time to the TMRCA. In contrast to a multiplicity of H2-derived branches, only two branches, those marked by mutations 6 and 11, follow mutation 9. This suggests that mutation 9 could be younger than it appears, either because of recent rapid growth or because of a founder effect in its carrier population(s) of Europe, the Middle East, and the Americas (note that the estimated mutation age is a function of the new allele's frequency). In Africa and East Asia the prevalent H2 gave rise to much greater haplotype diversity. Are these latter continental populations relatively older or were the effective sizes of their human populations relatively larger?
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Discussion |
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The silent polymorphism C1193T in exon 8, which is the oldest SNP and effectively partitions the SR-BI/II variability almost in half (table 4), is associated with low plasma LDL cholesterol in healthy Caucasian women (Acton et al. 1999) as well as with high plasma HDL cholesterol and a lower risk of coronary artery disease in Koreans (Hong et al. 2002). As a result, all functional variability that arose on the background of H1 and H2 will be in linkage disequilibrium with the 1193T allele and the C allele, respectively. Hence, these associations do not necessarily indicate functional significance of this apparently silent T to C polymorphism, but rather point to its linkage with other polymorphisms such as the observed amino acid substitutions that are more likely to affect the protein function. Knowledge of the haplotype network can therefore assist in the design of an epidemiological survey (i.e., how to choose informative markers for genotyping) and in the subsequent functional interpretation of the underlying variation.
The nucleotide diversity of SR-BI/II is similar to that of other genomic segments, particularly coding or expressed regions (Cargill et al. 1999; Fan et al. 2002; Nakajima et al. 2002; Schneider et al. 2003). We observed two common frequent haplotypes (H1 and H2) that dominate over a flat distribution of rare haplotypes due to novel mutations or recent recombinations. However, the total number of 19 haplotypes appears low for a gene spread over 86 kb on the physical map and 0.26 cM on the genetic map (Kong et al. 2002). With a recombination rate of 0.0026 (1/385) per gene segment per generation, a significant fraction of which is informative (estimated at 17% in the world sampledata not shown; see appendix in Zietkiewicz et al. 2003), a greater number of recombinant SR-BI/II haplotypes would be expected given the depth of the coalescence tree. In contrast, the observed recombinants can be considered relatively young given their frequency (fig. 2).
Another particularity is the geographic distribution of the genetic diversity of the SR-BI/II locus. Nucleotide diversity among Asians is equal to or even exceeds that in Africa (0.059% and 0.044%, respectively), an observation rarely reported in other loci (Harding et al. 1997; Jaruzelska et al. 1999). At the haplotype level, both Africa and East Asia are significantly more variable than the other continental samples (table 2). All this could suggest that African and Asian lineages were similarly ancestral to present-day populations. The estimated ages of mutations 5 and 13, East Asian and African specific, respectively, exceed 200 Kyr, and, if taken literally, would indicate an unusually ancient split between the East Asian and African lineages (fig. 4). Continentally restricted recombinant haplotypes H15 and H9 further emphasize isolation of these continental groups. Genetic separation between Africa and East Asia is also reflected in the FST analysis (fig. 3). Even if the genetic history of SR-BI/II followed a trajectory different from that predicted by the recent out-of-Africa model (e.g., Harding et al. 1997; Hammer et al. 1998; Cruciani et al. 2002), one would still expect to observe a recent African influence in East Asia from the Upper Palaeolithic to the present day (Satta and Takahata 2002). In contrast, the deep split between East Asia and Africa seen in our data may actually be as recent as the late Middle or Upper Palaeolithic, and for several reasons.
First, because the haplotypes observed here represent a tight network with no intermediate missing forms (fig. 2). This could indicate a small role played by genetic drift in the evolution of SR-BI/II genetic diversity as observed today (see e.g., Beheregaray et al. 2003). Indeed, over time, and in a finite population, new haplotypes are created while others become extinct. Thus, at a given historical moment, those haplotypes that have arisen through multiple mutation and recombination events represent only a subset of all allelic combinations as is seen in the PDHA1 locus (Harris and Hey 1999), in beta-globin (Harding et al. 1997), dystrophin (Labuda, Zietkiewicz, and Yotova 2000), CYP1A2 (Wooding et al. 2002), subterminal 16p (Alonso and Armour 2001), or APOE (Fullerton et al. 2000). Although tight networks were observed (1) in very short genomic segments (Jaruzelska et al. 1999; Jin et al. 1999), (2) in segments of low recombination rate (Kaessmann et al. 1999), or (3) in segments under selection (Smirnova et al. 2001), in SR-BI/II, extending over 86 kb and with the recombination rate exceeding threefold the genomic average, explanations (1) and (2) hardly apply. Second, when evaluated through a simple model of constant population size, the overall time depth of the history of SR-BI/II (2.08 Ne generationsfig. 4) is about half that expected (4 Ne) for a neutrally evolving autosomal locus. The SR-BI/II tree appears even shallower than those of X-chromosome loci (Harris and Hey 1999; Jaruzelska et al. 1999; Verrelli et al. 2002). Third, population expansion provides a better description of the data than a constant population size model, as seen under the coalescence analysis and based on statistics such as Fu's Fs and Tajima's D (table 2). However, it is noteworthy that slowly accumulating nucleotide variation in nuclear loci has only rarely provided evidence of expansion (Thomson et al. 2000; Alonso and Armour 2001), as the expansion period (Klein 1999) was relatively recent and presumably too short on an evolutionary scale for new variants to accumulate. Thus, the evidence of population expansion in coalescence analysis may likely be due, in fact, to selection as supported by Tajima's D and Fu's FS. Fourth, there is a striking absence of significant nucleotide variability in SR-BI/II that is ancestral to the divergence of continental populations, as well as a shortage of haplotype diversity, due to recombination, given the spread of genetic distances within the locus. Selection is therefore plausible, and if this is the case, the time estimates based on the neutral model are certainly misleading. Considering all findings and in comparison with other similarly analyzed loci, which were "shaped" by the same demogenetic processes, it is conceivable that selection affected the genetic history of the SR-BI/II locus in the lineage leading to modern humans. In summary, we propose that rather than supporting an ancient split between Africa and Asia, our data can be interpreted assuming that the SR-BI/II variability is relatively young and accrued during the period following the recent out-of-Africa expansion (Cavalli-Sforza, Menozzi, and Piazza 1994). A selective sweep at the origin of modern humans could have been responsible for the disappearance of its ancestral diversity. Because the local recombination rate is relatively high, it is possible that SR-BI/II itself could have been under the selection process rather than being affected by the genetic hitchhiking that derived from selection involving a linked gene.
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Acknowledgements |
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Footnotes |
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David B. Goldstein, Associate Editor
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