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Human Molecular Genetics, 2004, Vol. 13, No. 10 1049-1056
DOI: 10.1093/hmg/ddh121
Human Molecular Genetics, Vol. 13, No. 10 © Oxford University Press 2004; all rights reserved

Haplotypes in the APOA1-C3-A4-A5 gene cluster affect plasma lipids in both humans and baboons

Qian-fei Wang1, Xin Liu2, Jeff O'Connell3, Ze Peng1, Ronald M. Krauss1,4, David L. Rainwater5, John L. VandeBerg5, Edward. M. Rubin1,6, Jan-Fang Cheng1,6 and Len A. Pennacchio1,6,*

1Genome Sciences Department, Lawrence Berkeley National Laboratory, Berkeley, CA, USA, 2Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA, 3Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA, 4Children's Hospital Oakland Research Institute, Oakland, CA, USA, 5Department of Genetics and Southwest National Primate Research Center, Southwest Foundation for Biomedical Research, San Antonio, TX, USA and 6USA Department of Energy Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, CA, USA

Received January 16, 2004; Accepted March 15, 2004


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Genetic studies in non-human primates serve as a potential strategy for identifying genomic intervals where polymorphisms impact upon human disease-related phenotypes. It remains unclear, however, whether independently arising polymorphisms in orthologous regions of non-human primates leads to similar variation in a quantitative trait found in both species. To explore this paradigm, we studied a baboon apolipoprotein gene cluster (APOA1/C3/A4/A5) for which the human gene orthologs have well-established roles in influencing plasma HDL-cholesterol and triglyceride concentrations. Our extensive polymorphism analysis of this 68 kb gene cluster in 96 pedigreed baboons identified several haplotype blocks each with limited diversity, consistent with haplotype findings in humans. To determine whether baboons, like humans, also have particular haplotypes associated with lipid phenotypes, we genotyped 634 well-characterized baboons using 16 haplotype tagging SNPs. Genetic analysis of single SNPs, as well as haplotypes, revealed an association of APOA5 and APOC3 variants with HDL-cholesterol and triglyceride concentrations, respectively. Thus, independent variation in orthologous genomic intervals does associate with similar quantitative lipid traits in both species, supporting the possibility of uncovering human quantitative trait loci genes in a highly controlled non-human primate model.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Defining the genetic basis for quantitative traits in humans is essential for our better understanding of the vast biological differences found between individuals, including disease susceptibility. Cross-species approaches offer a logical means for leveraging the similarities between organisms to identify genomic intervals where variation may have an impact upon phenotypes in common across species. While quantitative trait loci (QTLs) in humans and rodents have occasionally been mapped to large orthologous intervals (1,2), it is rarely possible to determine if the same gene is involved due to phenotypic and genomic differences between these organisms.

In contrast to rodents, non-human primates are expected to share a larger number of phenotypic traits and associated genetic etiologies with humans due to their close evolutionary relationship and physiology. However, while widespread success has been obtained in identifying the molecular defects in single gene diseases, human genetic studies of complex traits have proved extremely difficult due to the number of genes involved, the small effects of individual polymorphisms, the complicated nature of gene–gene and gene–environment interactions and uncontrolled environmental factors (3,4).

Baboons (Papio hamadryas) are a well-studied non-human primate model with which it is possible to control mating and environment (exercise, life-style, diet, etc), thereby alleviating several of the confounding factors found in human studies (5). Through the recent development of a baboon linkage map (6), several lipoprotein and hypertension QTLs have been physically mapped, some of which overlap with QTLs mapped to orthologous genomic intervals in humans (7,8). To date, however, no fine-scale orthologous sequence analysis has been performed for any quantitative trait to define whether independently arising polymorphisms in the identical genomic interval are responsible for similar phenotypic differences found in both species.

The apolipoprotein gene cluster (APOA1/C3/A4/A5) on human chromosome 11q23 is among the best characterized regions of the genome for its association with plasma lipid levels, a quantitative trait. A wealth of human mutation and genetic association studies demonstrate that sequence variants in APOC3 and APOA5 are associated with plasma HDL-cholesterol and/or triglyceride concentrations (9–17). In addition, over-expression as well as deletion of these genes provide confirmation that each plays an important role in lipid homeostasis (10,18,19).

We examined the orthologous baboon gene cluster in a large pedigreed population to explore whether independent mutation events at the APOA1/C3/A4/A5 gene cluster might account for quantitative differences in lipid phenotypes in a second primate species. Our goal was to examine the genetic architecture at this site and to determine if polymorphisms within the baboon cluster also influence plasma lipid levels similar to that found in humans. In these studies, we found that baboons also display limited haplotype diversity and show genetic associations between common variants in this apolipoprotein cluster and HDL-cholesterol and triglyceride concentrations. These studies highlight the utility of the environmentally controlled baboon model to uncover genomic intervals where polymorphisms can also impact upon phenotypes relevant to human disease.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
SNP discovery
To systematically characterize linkage disequilibrium and haplotype structure in the baboon APOA1/C3/A4/A5 gene cluster, we performed direct DNA sequencing across the interval in 24 baboons selected from 15 presumably independent pedigrees. We analyzed 68 kb of sequence containing the entire gene cluster plus flanking sequence and detected 381 genetic variation sites (eight in coding exons and six in untranslated regions). Of them, 363 are single nucleotide polymorphisms (SNPs) and 18 (or 4.7%) are insertion/deletion (in/dels) polymorphisms (Table 1). In the human homologous region, 182 SNPs and four in/dels were reported in NCBI dbSNP build 116. As expected, none of the 381 baboon and 186 human polymorphisms were shared between the two primate species. As shown in Table 1, the baboon SNPs average one per 187 bp across the gene cluster; with one in 276 bp in the UTR region, one in 626 bp in the coding region and one in 177 bp in the intron and intergenic regions. The average minor allele frequency of the total number SNPs in 24 baboons is 17.3%. The average minor allele frequency is 18.0%, 19.3% and 17.2% in the UTR region, the coding region and in the intron and intergenic regions, respectively. After removing SNPs that were not in Hardy–Weinberg equilibrium, we selected 248 SNPs that had a minor allele frequency of >8% for subsequent analysis. These SNPs spanned a total of 68 kb of sequence on baboon chromosome 14, resulting in an average distance of 274 bp between neighboring SNPs.


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  		Table 1. Summary of SNPs identified in the 68 kb of the baboon APOA1/C3/A4/A5 gene cluster
 
Selection of representative SNPs across the apolipoprotein gene cluster
In an effort to reduce the numbers of SNPs needed for future genotyping, we analyzed the extent of linkage disequilibrium across these variants in the apolipoprotein gene cluster. Since r2 is an appropriate statistic in determining whether an assayed SNP can detect an unassayed SNP, we calculated r2 for all pairs of SNPs using unphased data from 24 unrelated baboons and thereby clustered SNPs with highly correlated alleles (with r2>0.8) (20,21) (Fig. 1). Within each cluster, several SNPs were selected to represent the correlated group of SNPs. In total, 35 SNPs were selected as displayed in Figure 1.



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  		Figure 1. r2 clustering of 248 SNPs in the baboon gene cluster region. SNPs are clustered such that highly correlated sites (with r2>0.8) are placed near one another. Arrows indicate SNPs which were selected as representative SNPs used in genotyping 96 baboons for haplotype development. The visual clustering was done using the VG2 program developed at the University of Washington. Details on all 248 SNPs can be found at http://pga.lbl.gov/SNP/Baboon/APOA1C3A4A5.html.

 
Development of the baboon haplotype block structure and selection of tagging SNPs based on common haplotypes
To determine the haplotype structure of the baboon apolipoprotein gene cluster, we genotyped the 35 selected SNPs in 96 pedigreed baboons. Four SNPs did not pass our genotyping quality control assessment (see section on SNP genotyping in Materials and Methods) and were excluded from subsequent analysis. We inferred haplotypes across the gene cluster for each individual and identified blocks and common haplotypes within each block (Fig. 2). Three haplotype blocks were identified in the region (Fig. 2), with APOA1, APOC3/APOA4 and APOA5 falling into separate blocks. Each LD block was on average 11 kb in length and was comprised of four common haplotypes which accounted for 75–85% of all chromosomes. Based on these results, 16 SNPs were selected as haplotype tagging SNPs that suffice to determine the haplotypes accounting for 82–91% of the chromosomes within each haplotype block (Fig. 2).



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  		Figure 2. Haplotype block and common haplotypes in the APOA1/C3/A4/A5 gene cluster region. Genotype data of 31 SNPs for 96 pedigreed baboons were used to identify haplotype blocks in the gene cluster region using HaploblockFinder (see Materials and Methods). A scale in kb is provided on the top of the gene cluster. All genes in this region are depicted by black horizontal block arrows. Gene names are given above the arrow. The approximate location of each SNP is indicated by the vertical lines. The blocks, represented by gray squares, were generated using the chromosome coverage definition with the threshold set at 0.8. The corresponding haplotypes within each block are depicted by the diagrams in the lower panel. The numbers 1, 2, 3 or 4 represent the bases A, T, C and G, respectively. Lines between haplotype blocks represent connections found in the samples. The 16 SNPs used for genotyping the 634 baboons in association studies are marked by vertical arrows. The percentage of chromosomes being covered by listed haplotypes is shown for each block. Individual hapotype frequencies within each block are also listed, in the order of the haplotype from top to bottom.

 
Association analysis of single nucleotide polymorphisms and haplotypes with baboon lipoprotein phenotypes
We genotyped the 16 haplotype tagging SNPs in a study population that consisted of 634 baboons (Table 2). We performed single marker QTDT tests on all 16 SNPs and found six associated with five lipoprotein phenotypes that had an asymptotic P-value<0.01. When permutation tests (m=1000) were performed on all six markers and five traits, the only significant association was between SNP 13 from APOA5 intron 2 and HDL-cholesterol on the chow diet (Table 3).


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  		Table 2. SNPs used for genotyping 634 pedigreed baboons
 

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  		Table 3. QTDT tests of 16 markers within the APOA1/C3/A4/A5 gene cluster for association with nine traits (P<0.01)
 
Since analysis of haplotypes can have stronger statistical power compared to that of single marker polymorphisms, we performed two-locus, three-locus and four-locus haplotype analysis on the APOA1, APOC3, APOA4 and APOA5 genes in the baboon cluster. Lipid traits included in the test were triglycerides and HDL-cholesterol since they are known to be associated with the orthologous gene cluster in humans. Haplotype analysis confirmed the result from single SNP association (Table 3) (empirical P=0.014), further supporting that the APOA5 variant is associated with HDL-cholesterol levels (Table 4). In addition, a four-locus haplotype within the APOA1/C3 block showed significant association with plasma TG levels (empirical P=0.002, Table 4); an effect that was not observed when individual markers from this haplotype were tested. No significant association was detected with APOA4 haplotypes.


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  		Table 4. QTDT tests of APOA1, APOC3 and APOA5 haplotypes for association with TG and HDL-cholesterol
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
In this study, we sought to systematically examine the baboon polymorphism architecture and its relationship to phenotypic data in a region orthologous to humans which has been biologically well characterized. The baboon interval was selected based on orthology to the extensively studied human apolipoprotein gene cluster on chromosome 11q23 which has been repeatedly implicated in contributing to inter-individual differences in plasma lipid levels. Our primary goal was to study variation at this locus and to determine if baboon variants within this region are also associated with quantitative differences in plasma lipid levels.

In addition, this study supports a higher SNP density in the baboon population relative to humans. While numerous studies indicate that human SNPs are estimated to be spaced at approximately one every 300 bp in the human population (minimum minor allele frequency of 1%) (22–24), we found that baboons display one SNP every 187 bp (minimum minor allele frequency of 2%), and that these SNP alleles display strong patterns of linkage disequilibrium, similar to the findings in humans. Our original direct sequencing analysis identified 363 SNPs in 24 baboons which collapsed into 35 representative SNPs based on the exclusion of redundant SNPs displaying high levels of linkage disequilibrium. Further characterization of 35 SNPs by genotyping in 96 baboons revealed that the baboon APOA1/C3/A4/A5 gene cluster forms block structures with each block exhibiting limited haplotype diversity. Specifically, APOA1, APOC3/APOA4 and APOA5 fell into three separate blocks with an average block size of 11 kb. However, the exact location of haplotype blocks varied depending on the SNP density, SNP frequency and the block definition used (data not shown). A recent analysis of the ~51 kb human APOA1/C3/A4/A5 cluster revealed five haplotype blocks in the orthologous region (25). APOA1, APOC3/APOA4, and APOA5 belong to three different blocks, similar to what we have found in baboons. The 26 kb intergenic region between human APOA5 and APOA4 form two independent blocks, which were not observed in baboons. When block structures derived from different definition parameters were compared, the blocks overlapped significantly, but not completely, for the majority of SNPs. While it is generally not practical to compare block distribution between studies (26), taken together these data support a similar complexity of haplotype patterns in the human and baboon APOA1/C3/A4/A5 regions (25). Our goal, nevertheless, was to capture the general SNP architecture in the baboon region where we found limited diversity and this information proved useful to facilitate our subsequent genetic association analysis.

To study genetic variants in the baboon APOA1/C3/A4/A5 gene cluster and their possible contribution to plasma lipid concentrations, we used the haplotype structure in the APOA1/C3/A4/A5 gene cluster region to select 16 haplotype tagging SNPs (ht SNPs) for genotyping in 634 baboons which had undergone a dietary challenge. Single marker QTDT as well as haplotype analysis supported an association of variation in the APOA5 gene with HDL-cholesterol levels (empirical P-value=0.014), explaining ~1.9% of the variance in HDL-cholesterol concentrations. In humans, associations between APOA5 variants and HDL-cholesterol levels have been reported (11–13), though we did not observe associations with APOA5 variants and triglycerides despite reports in humans (10,27–31). A previous study (32) with these baboons indicated that a substantial proportion of variation in HDL-cholesterol concentrations is explained by the additive effects of multiple genes, with heritabilities ranging from 53 to 61% on the different diets. The association of APOA5 variants with HDL-cholesterol was only found on the basal diet in this study, suggesting that other genes may have greater effects on HDL-cholesterol variation under high fat diet. In addition, a second association was identified between an APOC3 baboon haplotype and triglyceride concentrations, with ~6.7% of the total variance in triglyceride levels attributable to the haplotype. This is entirely consistent with a large number of human studies which have shown strong genetic associations between APOC3 variants and triglyceride levels (9,14–17). At both the APOA5 and APOC3 loci, genetic variants had slightly greater impact on lipid levels than that of the covariates. The combined effect of sex, age and weight contributed ~1 and 5% to the total variance in HDL-cholesterol and triglyceride, respectively (data not shown). Thus, independently arising polymorphisms in humans and baboons can both contribute to quantitative differences in similar plasma traits, but the effects are not completely overlapping.

The 16 SNPs used for association analysis were selected from 248 SNPs to capture the majority of the genetic information in the region. We found a 4-locus haplotype, but not single markers, spanning the APOA1 and APOC3 region was associated with triglyceride levels (Tables 3 and 4). Based on this association, we hypothesized that the causal functional genetic variant(s) influencing this lipid trait resides within this haplotype's boundaries. Within this hapolotype block, 10 SNPs were located in proximity to known gene regulatory regions as well as a single synonymous change within the APOA1 gene. While nine of the potential regulatory SNPs did not fall in any predicted transcription factor (TF) binding motif using a liver-specific TF profile (http://www.gene-regulation.com/cgi-bin/pub/programs/match/bin/match.cgi, data not shown), the SNP at position 18805 resides within a hormone response element (HRE) of the APOC3 enhancer that directs tissue specific expression of APOA1, APOC3 and APOA4 in humans (32–34). The human HRE has been shown to bind nuclear receptors in vitro and is required for full enhancer activity in cell culture (32,35) thereby suggesting a possible functional variant. In our second finding, HDL-cholesterol concentration was found to be associated with SNP13 from APOA5 intron 2 (Table 3). Only two SNPs in LD with SNP13 were suggestive of being casual. This includes a single cSNP (position 57061) in the APOA5 gene which changes an alanine to serine (A217S). This amino acid is perfectly conserved between human and mouse, however, it is only in weak LD with SNP 13 (Table 2) (D'=0.2), thereby questioning the likelihood of this being the functional variant in this study. In addition, there is a second SNP (position 55137) in the uncharacterized APOA5 promoter which has a LD=0.5 with SNP13. Although this SNP is not located within any predicted liver-binding motif (data not shown), its functionality has yet to be examined. Taken together, while potential functional SNPs are proposed here, additional detailed SNP identification, experimental tests of SNP functionality and further genotyping in the baboon population will be required to ultimately prove the casual functional variant(s).

A major assumption underlying studies using non-human primates (and other mammals) to help identify loci contributing to traits that are directly relevant to those found in humans is that independent mutations have occurred at orthologous loci across species and that these polymorphisms have similar effects on a phenotype. In addition to possible physiological differences, this independent origin of polymorphisms in humans and baboons most likely explains the incomplete overlap between genetic variants and plasma phenotypes and additional large studies are needed to clarify the extent to which polymorphisms in orthologous human/baboon genes account for similar quantitative phenotypic variability in both species.

One significant advantage of genetic studies in baboons versus humans is the potential for stringent control of environmental factors which are likely to profoundly impact upon complex phenotypes. In addition, matings in baboons can be planned to specifically facilitate the ability to detect, characterize and localize genes that influence phenotypic variation. As QTL mapping has led to the identification of many genes underlying polygenic traits, it is becoming a promising approach in the genetic dissection of mammalian complex traits (1). With the recent development of a baboon linkage map, current efforts are focused on linkage and segregation analysis with the ultimate goal of uncovering genomic intervals affecting baboon, as well as human, biology. Our results support that the baboon is a valuable resource for uncovering genetic loci of relevance to human phenotypes and that similar fine-scale studies aimed at refining genetically mapped QTLs in non-human primates has the potential to uncover novel genetic contributors to a wide spectrum of shared human traits.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Pedigreed baboons
The baboons (P. hamadryas) used in this study comprised 216 males and 418 females from 10 pedigrees and represent the genetic diversity arising from ~212 founders (36). The animals were maintained at the Southwest Foundation for Biomedical Research, a facility certified by the Association for Assessment and Accreditation of Laboratory Animal Care International. All 634 animals were subjected to a previously-described dietary challenge protocol (36,37). Briefly, animals were fed three diets contrasting in levels of fat and cholesterol: basal diet was low in cholesterol (0.03 mg/kcal) and fat (4% of calories), LCHF was high in fat (40% of calories) but no cholesterol was added, and HCHF diet was the high fat diet with high levels of cholesterol (1.7 mg/kcal). Animals were fasted overnight and bled from the femoral vein. Serum samples taken at the end of each dietary regime were stored as single-use aliquots protected from oxidation and dessication (38). Experimental protocols were supervised by a veterinarian and approved by the Institutional Animal Care and Use Committee at Southwest Foundation for Biomedical Research.

SNP identification
A baboon bacterial artificial chromosome (BAC) containing the APOA1/C3/A4/A5 gene cluster was isolated by filter hybridization using human probes (http://bacpac.chori.org/baboon41bac.htm). The sequence of one positive BAC (RPCI-41:109F19, GenBank accession number AC145521) was determined by fluorescent dye-terminator sequencing and was assembled using the Phred-Phrap-Consed assembly suite (39–41). This baboon BAC sequence served as the reference for subsequent polymorphism detection in additional baboon individuals. Briefly, primers were designed to amplify 2–3 kb of overlapping genomic DNA in a 68 kb region containing the APOA1/C3/A4/A5 gene cluster. PCR was performed using 2 ng/µl of genomic DNA, 100 µM of dNTPs, 140 nM of primers, eLONGase and buffer (Invitrogen) for 35 cycles at 94x for 30 s, 60°C for 30 s and 68°C for 2 min. DNA samples amplified from 24 unrelated baboons were sequenced on both strands by BigDye terminators (Applied Biosystems) with custom primers designed every 300 bp. Sequence reads were assembled using Phred-Phrap-Consed suite (39–41) and nucleotide polymorphisms were determined by PolyPhred (42) and then confirmed by visual inspection.

SNP genotyping
Genotyping of pedigreed baboons was carried out using a commercially available primer extension technique, SNaPshot (Applied Biosystems). Five SNPs were genotyped simultaneously in the same reaction. Equal amounts (50 ng each) of PCR amplified genomic DNA fragments containing five surveyed SNPs were pooled and treated with 5 U of SAP (shrimp alkaline phosphatase) and 2 U of Exo I at 37°C for 1 h in a 20 µl reaction to remove the residual primers and free nucleotides. The SAP/Exo I reaction was quenched at 75°C for 15 min. Sequences adjacent to the SNP sites were used to design SNaPshot primers, and five primers with a similar Tm but different length of tail sequences were combined in the same SNaPshot reaction. The SNaPshot reactions contain 3 µl of the pooled PCR products, 0.2 µM each of the five SNaPshot primers, 5 µl of the SNaPshot Multiplx Reaction mix (Applied Biosystems), and ddH2O to adjust to a 10 µl final volume. The SNaPshot reactions were performed using the thermal cycling condition recommended by the manufacturer, and then treated with 1 U of CIP (calf intestinal phosphatase) at 37°C for 1 h and quenched at 75°C for 15 min. Aliquots of 1 µl of the SNaPshot samples were then mixed with the same volume of the GeneScan-120 LIZ size standard (Applied Biosystems), diluted with 18 µl of Hi-Di formamide and denatured at 95°C for 5 min before loading to the ABI Prism 3700 DNA Analyzer. Gel images were analyzed using the GeneScan Analysis Software version 3.7 and the polymorphic nucleotides were called using the Genotyper Software version 3.7. All nucleotide calls were inspected visually by two individuals to ensure accuracy. Thirty-five SNPs in 96 baboons and 16 SNPs in 634 baboons were genotyped using SNaPshot (see Results). To independently evaluate the data quality, we randomly selected 24 baboons from the study population and acquired genotypes at all SNP locations used in Snapshot assays by direct sequencing. In the data analysis, we only included SNPs which have a minimum of 95% consistency between the genotypes from the two methods.

Analysis of LD and haplotypes
The genotypes of 24 unrelated baboons were used to calculate the r2 value using the VG2 software (43,44) (http://pga.gs.washington.edu/VG2.html) and haploview (http://www.genome.wi.mit.edu/personal/jcbarret/haplo/docs.html). To select representative SNPs from each r2 clustering group, we chose a minimum of one SNP to cover each cluster group and SNPs located in the proximity of a gene were preferred over those in intergenic or repetitive DNA regions.

Ninety-six pedigreed baboons were genotyped using SNaPshot (see above). Genotypes in violation with Mendelian expectations (0.18%) were excluded from further analysis. We treated 96 pedigreed baboons as population samples and used the PHASE program [version 2.0 (45)] to infer haplotypes. In two cases, Mendelian inheritance was not found based on inferred haplotypes and these data were excluded from further analysis. The haplotypes were then imported into haploblockFinder [version 0.6 (46) http://cgi.uc.edu/cgi-bin/kzhang/haploBlockFinder.cgi] for block structure determination. The haplotypes of 16 SNPs for the 634 baboons were estimated using the program PHASE.

Although redundant SNPs were removed based on our r2 clustering analysis (r2>0.8) (see above and Results), strong linkage disequilibrium (LD) still existed among some of the selected 31 (in 96 baboons) and 16 (in 634 baboons) SNPs (data not shown). As serious concern has been raised as to the use of programs assuming no LD to perform pedigree haplotype inference (47), we did not use GENEHUNTER or SIMWALK2 despite such programs consideration of family relationship in haplotype estimation. We were unable to take advantage of other analytical tools allowing for LD for nuclear families (48) (PHASE-Phamily analysis at http://archimedes.well.ox.ac.uk/pise/phamily-simple.html) based on complications from our extended baboon pedigrees which is structured with inbreedings and multiple mates for a single male.

Genetic association
Both single point and multipoint (haplotype) analyses were performed using the QTDT (Quantitative Transmission Disequilibrium Tests) program [version 2.3.0 (49)]. The QTDT program incorporates variance components methodology in the analysis of family data. As asymptotic P-values can be misleading for non-normal data, we also performed a permutation test (m=1000) for exact estimation of P-value, which provide a global P-value with a built-in adjustment for multiple testing. P-values <0.05 were considered statistically significant. For single marker analysis, 16 markers (Table 2) and eight lipoprotein measurements on three different diets as well as triglyceride levels on chow diet (see sections on Pedigreed baboons and Lipoprotein measurements) were tested.

To perform haplotype-based analysis, two-, three- or four-locus haplotypes in the APOA1/C3, APOA4 and APOA5 region (Table 4) were recoded as single genotypes. For this analysis, traits included only HDL-cholesterol and triglycerides since those were the two measurements which consistently showed association with APOA1/C3 or APOA5 variants in human. Haplotypes with a frequency <0.5% were omitted from further analysis. Haplotypes were determined by the PHASE program [version 2.0 (45)] for each individual and the threshold for phase and allele certainty was set at 95%. If a haplotype contains SNP(s) which had uncertain phase or allele (0.8% of cases), it was treated as missing data in the recoding. Mendelian inconsistencies (<0.4%) from resulted genotypes were resolved by removal of the genotype in question.

Estimate of the variance in lipid levels attributable to each SNP or haplotype was calculated using the QTDT program. The genetic variance is explained as 2xpxqxa2 where a is the estimated effect size, p is the allele frequency and q=1–p. Estimate of the variance explained by covariates was calculated by comparing r2 value under the null hypothesis with and without the covariates in the model. Covariates included sex, age and weight.

Lipoprotein measurements
Measured lipid and apolipoprotein phenotypes at SFBR included concentrations of HDL and LDL (i.e. non-HDL) cholesterol and several apolipoproteins: ApoAI, ApoB and ApoE (8,36). Lipoprotein size distribution phenotypes were based on gradient gel electrophoresis and Sudan black B staining as previously described (50). Triglyceride levels on the basal diet were measured at the Children's Hospital Oakland Research Institute.


   ACKNOWLEDGEMENTS
 
This work was supported in part by the NIH-NHLBI Programs for Genomic Application Grant HL66681, Grant HL071954A through the US Department of Energy under contract nos DE-AC03-76SF00098, P01-HL28972 and P51-RR13086. We thank Dr Goncalo Abecasis of University of Michigan for his help with the QTDT program, Dr Joel Hirschhorn of Harvard Medical School for his comments and suggestions with this study, and Drs Ivan Ovcharenko and Ilya Malinov for data preparation.


   FOOTNOTES
 
* To whom correspondence should be addressed at: Department of Genome Sciences, MS 84-171, One Cyclotron Road, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. Tel: +1 5104867498; Fax: +1 5104864229; Email: lapennacchio{at}lbl.gov


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 

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