Human Molecular Genetics, 2000, Vol. 9, No. 20 2993-2999
© 2000 Oxford University Press
Allele association studies with SSR and SNP markers at known physical distances within a 1 Mb region embracing the ALDH2 locus in the Japanese, demonstrates linkage disequilibrium extending up to 400 kb
SGDP Research Centre, Institute of Psychiatry, Denmark Hill, London SE5 8AF, UK and 1Kurihama National Hospital, Kanagawa, Japan
Received 26 July 2000; Revised and Accepted 12 October 2000.
 |
ABSTRACT |
|---|
 TOP ABSTRACT INTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
|---|
There has been considerable recent debate concerning the distances over which levels of allelic association useful for genomic quantitative trait locus (QTL) scans can be detected. We have examined simple sequence repeat (SSR) polymorphisms and two single nucleotide polymorphisms (SNPs) in the region flanking the aldehyde dehydrogenase 2 locus, ALDH2, in populations of Japanese alcoholics and controls. These groups differ significantly in the allele frequencies for the functional SNP in exon XII of this gene located on chromosome 12. The results obtained with SSR markers complement recent investigations with SNPs over similar distances at the TCR
/
locus. Significant allelic association with this marker could be detected for SSRs over distances up to 400 kb and over 37 kb for the SNP thereby extending the distance over which LD at this locus could be detected by an order of magnitude. Furthermore, as a proof of principle, we show that comparisons of allele frequency differences for the SSR markers in the case (alcoholics) and control populations would have detected the ALDH2 marker as a putative QTL. Extending the tests to include alleles at two or three flanking loci suggests that the power to detect QTLs through association can be enhanced significantly. |
INTRODUCTION |
|---|
|
TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
|---|
In a powerful alternative to linkage analysis, gene hunting for loci contributing to the aetiology of multi-factorial disorders can be approached through association studies. Multi-factorial disorders have an underlying aetiology derived from multiple genetic and environmental inputs and their predisposing genetic factors are referred to as quantitative trait loci (QTLs). The chromosomal location of QTLs implicated in the aetiology of a disorder can be sought through the identification of the chromosomal segment on which it and a well characterized marker allele have survived in their original combination through long periods of evolution. Until the alleles at both loci are completely randomized, the markers are in linkage disequilibrium (LD).
The simplest model for LD is one where all the current copies of the disease genes in a population are descended from a single ancestral mutation. The haplotype on the ancestral chromosome on which the founder mutation occurred will have been preserved, to varying extents depending on the distance from the mutation, among the descendent copies of the mutant gene in the current population. This model has been successfully used to localize the genes for several rare Mendelian diseases in recently expanded populations (1–5).
An alternative model for LD that may be more appropriate for ancient common alleles is random genetic drift. In this model, the expected value of a standard measure of the magnitude of LD between two biallelic loci is related to the effective population size (N) and the recombination rate (c) by an equation (6–7). The effective sizes of human populations, highly sensitive to ‘bottlenecks’, have been estimated to be in the region of 1000–5000 (8,9). This predicts an expected value of 0.1 at 0.05 cM (
50 kb) and 0.01 at 0.5 cM (500 kb). In large samples, the expected value of the 
2 test of LD is approximately equal to sample size x R2, the range over which LD is detectable with single nucleotide polymorphisms (SNPs) is 50 kb, assuming a sample size of several hundred individuals.
Such theoretical calculations are crucially dependent on underlying assumptions. Recent simulations assuming an initial population size of 10 000 followed by rapid expansion to the size of the current human population suggested that LD for SNPs might be confined to very short intervals of 3 kb (10). This would imply that searching for novel QTLs by association will require several hundred thousand markers to adequately cover the genome. Other estimates of the distances over which association can be detected range from a few kilobases to >1 Mb and there are relatively few data for LD over intervals that have been precisely mapped physically and/or sequenced. Indeed, empirical data available for SNPs indicate that associations over a few tens of kilobases may often persist in Caucasian populations (11). Jorde et al. (12) related physical distance to LD among seven polymorphisms in a 550 kb region on chromosome 5 in the CEPH kindreds and found values ranging from 0.8 at very short distances to 0.01 at 500 kb. Within the UK population, Cox et al. (13) recently performed an analysis of LD between eight simple sequence repeat (SSR) markers in the interleukin-1 gene cluster on chromosome 2q in a sample of 212 Caucasian blood donors from Manchester and Sheffield. Significant LD was demonstrated across a 400 kb chromosomal region, with a significant negative correlation between physical distance and LD (r = –0.540, P = 0.001, one-tailed test).
Until recently, technological limitations have deterred total genome scans for association where no previous indication of location exists; however, rapid genotyping approaches combined with pooling DNA samples from multiple representatives of cases and controls has allowed preliminary investigations to be carried out (14–17).
Given this background, there has been a lively debate concerning the density of marker spacing that will have to be employed for efficient genome scans for association. In an attempt to provide empirical data on the extent of LD detectable at SSR and SNP sites at defined distances flanking a known QTL of significant effect, we have investigated the genomic region embracing the aldehyde dehydrogenase 2 locus (ALDH2).
The major path for ethanol metabolism occurs in the liver where there are high levels of alcohol-metabolizing enzymes. The first step involves the conversion of ethanol to acetaldehyde primarily by alcohol dehydrogenase (ADH) enzymes (18). Subsequently, acetaldehyde is metabolized to acetate by mitochondrial aldehyde dehydrogenase (ALDH2) (19). Polymorphisms exist in several of the genes that encode ADH and that for ALDH2, which demonstrate marked variation in frequency among different ethnic populations (20). ALDH2 exists in two forms that differ in activity due to a G
A mutation in exon XII resulting in a lysine for glutamine substitution at position 487 (21–24). This change reduces the enzymatic activity to virtually zero. Following ethanol intake the resulting accumulation of acetaldehyde, even in heterozygotes, produces the ‘Oriental flush’ reaction (25,26). The low activity variant occurs with high frequency in Oriental populations and it has been demonstrated to confer protection against the development of alcohol dependence syndrome and alcohol-related physical complications (27–32).
We have analysed alleles of SSR polymorphisms and a second SNP in the ALDH2 region on chromosome 12 in Japanese alcoholics and controls. For these markers and for the functional substitution, we have investigated the significance levels of LD in all pair-wise combinations. In addition, we have tested whether or not the functional ‘QTL’ would have been detected had a simple allele frequency comparison been undertaken in a case–control type of strategy.
|
RESULTS |
|---|
|
TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
|---|
SNP genotyping
The allele-specific genotyping for the SNP in exon XII which was based on the primer competition approach described in Materials and Methods was validated and achieved a zero error rate for >100 samples, compared with conventional restriction fragment cleavage typing (S. Higuchi, unpublished data). An analogous protocol employing an appropriate primer set was then applied to the characterization of the exon I SNP.
Allele frequency studies
Table 1 shows the results of testing for allele frequency differences of seven polymorphic markers located at various distances from the functional ALDH2 polymorphism in exon XII between the samples of Japanese alcoholic and control populations. All the highlighted markers show significant differences. It can be seen that all three SSRs (microsatellites) which were within 400 kb of the functional marker (the nominated QTL) showed significant allele frequency differences (P 
0.05). Indeed, ‘clump’ analysis for D12S1344, positioned 80 kb from exon XII, shows highly significant differences in allele frequencies (P = 0.002). In contrast, the bi-allelic SNP positioned 37 kb distant shows a trend to significance only in the divergence of allele frequencies (P = 0.085) between the two populations. No significant differences were observed for allele patterns for SSR markers at distances estimated to be >450 kb from the exon XII SNP.
|
Pair-wise analysis of marker associations
All pair-wise comparisons were examined between allele patterns for the loci listed in Table 1, employing a recently developed model-free, permutation analysis for allelic associations (33). Data were combined from both cases and controls.
Significant associations (LDs) were observed between the following microsatellite flanking markers and the exon XII functional SNP: D12S821, D12S1344 and D12S2263. Other associations were detected between the exon XII marker and the SNP in exon 1 (P = 0.0002, strength estimate = 0.032). The exon I SNP was also observed to be in LD with the SSR repeat markers D12S2263 (P < 0.0001, strength estimate = 0.411), D12S1344 (P = 0.0000, strength estimate 0.436) and D12S821 (P = 0.0000, strength estimate 0.295).
Extending the analysis to examine patterns of allelic combinations at two or three sites flanking the functional marker (but not including the functional polymorphism itself) shows that considerable improvements to the significance (empirical P values) can be generated (Table 2). For example, combining the allele patterns at the dinucleotide repeat markers 4 (D12S1344) and 7 (D12S2263) gives a P value for heterogeneity (between cases and controls) of 0.0003, a considerable improvement over use of the loci independently (P = 0.002 for marker 4 and P = 0.024 for marker 7). The haplotype that distinguished best between cases and controls is the haplotype of markers 6–7. This haplotype has an estimated frequency of 9.6% in cases and 29.1% in controls (2 = 13.5 and P = 0.0002).
|
The data for both allele frequency comparisons and for the allele associations between the SNP in exon XII and all other markers tested individually are represented graphically with respect to their genomic separation in Figure 1. This illustrates that, whereas the range of significant linkage disequilibrium of markers with the exon XII functional variant extends over 400 kb, including an SNP marker positioned 37 kb distant, only the SSR markers in this range showed significant allele pattern differences between the alcoholic and control populations.
|
|
DISCUSSION |
|---|
|
TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
|---|
Association studies provide a theoretically powerful approach to the discovery of QTLs for multi-factorial disorders, both in case–control comparisons and in allele transmission studies. Greatest efficiency is achieved if the marker under test is coincident with the causative functional mutation. In practice, however, prior knowledge of likely functional variants is generally lacking and screening is carried out with a series of polymorphic markers close to a series of candidate loci. In more general approaches, markers may be chosen to span chromosomal regions implicated by linkage, or to cover large sections of the entire genome (e.g. 15–17). For all of these later strategies, the likely success of the study depends on a range of parameters, one of the most significant being the extent of LD between the test locus and the functional QTL.
The current investigation has sought both to establish the persistence of allele association between a range of test polymorphic markers at known physical distances from a known functional variant and to examine whether or not significant allele frequency differences at these test loci could be detected between populations known to differ in allele frequencies at the functional locus, ALDH2. The flanking markers selected have been physically mapped in YAC and BAC contigs (http://sequence.aecom.yu.edu/chr12/ ) from which we have been able to determine, for most of them, highly accurate estimates of their physical separation from the functional variant under investigation. For others, we have been able to assign minimum distances in kilobases.
We have shown that significant LD persists between various flanking markers and the test locus (ALDH2) known to be under selective constraint in Japanese alcoholic populations. Furthermore, an SNP marker separated by 37 kb from the functional variant shows significant LD. This is consistent with the previous observation that haplotypes of SNPs are conserved across the region (34,35). It is also consistent with theoretical predictions by Sved (7) and others concerning the expected decline of LD with increasing genetic distance, for an effective population size of 10 000.
Significant LD is also observed between the SSR markers D12S821, D12S1344 and D12S2263 and the non-functional SNP in exon I, the SSR loci being positioned at 437, 122 and 1.6 kb distant. Our observations coupled with the known racial distribution of the exon XII mutation causing loss of function of the ALDH2 locus indicate that it is of relatively recent origin in the Japanese and shows strong association with flanking markers. This is highly significant in the non-alcoholic population (data not shown) in which the frequency of the protective allele is substantial; however, combining data from the control and alcoholic populations increases the overall significance of the observations (Table 3).
|
The persistence of LD over distances up to 400 kb for pairs of loci including at least one SSR is of considerable interest. We appreciate, however, that the apparently recent origin of the ALDH2 functional marker is very likely to be a major factor underpinning our observations and the strength of the associations observed in this situation may not be reflected in searches for more ancient QTLs. With regard to the observation of allele frequency pattern differences between the case (alcoholics) and control populations, population demography and allele frequencies themselves are additional important factors in determining the success of genome screens using this type of approach.
Testing for association by the conventional case–control approach and searching for allele frequency differences between the two groups shows that microsatellite markers as far distant as 400 kb can give significant results in this model situation, thereby indicating that genome scanning approaches for association employing markers separated by up to 1 Mb should be successful at least for a proportion of potential QTLs. Indeed, as a proof of principle, our data indicate that inspection of the allele frequency differences for the SSR markers in the alcoholics and control populations would have detected the ALDH2 functional polymorphism as a putative QTL protecting against the condition. Our data also indicate that analysis of haplotype frequency differences would have even greater power to detect the effect of ALDH2.
A very recent report has investigated LD of SNPs within the TCR / locus and has demonstrated that significant LD was common over intervals of 250 kb and could be detected even beyond 500 kb (36). The authors suggested that SSR markers may be less useful than SNPs because of comparatively high mutation rates. This will vary with the type and repeat pattern of the marker concerned. Indeed, we have demonstrated that haplotypes obtained at combinations of SSR loci may be very powerful in detecting association of QTLs in their proximity. Nevertheless, we emphasize that LD will vary between different populations and across the genome and that, when effect sizes may be small, much denser maps will be necessary if genome scans are required to retrieve a majority of such functional variants.
|
MATERIALS AND METHODS |
|---|
|
TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
|---|
To investigate LD across the region we have genotyped DNA samples from 130 Japanese alcoholics (DSM IV) and 130 Japanese controls for six microsatellite markers and one SNP in addition to the functional variant in exon XII of the gene (Fig. 2). The two populations were matched for ethnic similarity and extensive surveys with non-chromosome 12 SSR markers showed no evidence for stratification. DNA was extracted by standard methods from blood.
|
SSR genotyping
The following microsatellite polymorphisms were examined (GenBank accession numbers in parentheses): D12S821 (314449), D12S2263 (5886644), D12S1344 (460436), D12S839 (315825), D12S2070 (682649) and D12S1341 (460421).
Sequence data for the estimation of distances separating the markers, identification of additional SSR polymorphisms close to the functional variant in exon XII of the ALDH2 gene and the design of primer sets within the region were accessed through http://sequence.aecom.yu.edu/chr12/ . Each primer pair included one with a 5'-fluorescent label. PCR reactions were optimized for each marker by adjusting magnesium chloride concentrations and annealing temperatures, and all reactions included an extended final extension step (30–60 min) to promote the homogeneous completion of ‘plus A’ PCR products. The products were analysed using the Perkin Elmer ABI 377 gel system and ABI Prism software.
SNP genotyping
Individual genotyping of the exon XII functional mutation in the ALDH2 locus and of the SNP in exon I (34) was undertaken employing a novel method developed from that of Gibbs et al. (37), whereby both allele-specific primers are present in the same reaction and are forced to compete with each other. By generating primers with the allele-specific nucleotide at the 3' end and an individual fluorescent label at the 5' end, PCR products were specific for template genotypes which were detected on an automated fluorescent DNA sequencer (Perkin Elmer ABI 377 or 310). The colour with which the band fluoresces indicates the genotype (38). Genotypes for the original restriction fragment length polymorphism (RFLP) creating the functional variant in exon XII were known for both alcoholic and control populations (S. Higuchi, unpublished data) and used to validate the allele-specific PCR protocol. The PCR conditions were optimized to give equal signal strength from each allele by adjusting the specific primer concentrations.
Data analysis
Allele frequencies were computed for each marker and analysed for statistically significant differences in patterns between cases and controls by either the ‘clump’ program for loci with multiple alleles (39), or by a 2 x 2 2 analysis for biallelic markers. LD was evaluated between pairs of marker loci including the functional ALDH2 polymorphism in exon XII using an extension and modification of Ott’s EH program (33,40).
|
FOOTNOTES |
|---|
+ To whom correspondence should be addressed. Tel: +44 207 848 0018; Fax: +44 207 848 0407; Email: i.craig@iop.kcl.ac.uk
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
|---|
1 Hastbacka, J., de la Chapelle, A., Mahtani, M.M. et al. (1994) The diastropic dysplasia gene encodes a novel sulfate transporter: positional cloning by fine-scale linkage disequilibrium mapping. Cell, 78, 1078–1087.
2 Kaplan, N.L., Hill, W.G. and Weir, B.S. (1995) Likelihood methods for locating disease genes in non-equilbrium populations. Am. J. Hum. Genet., 56, 18–32.[Web of Science][Medline]
3 Terwilliger, J.D. (1995). A powerful likelihood method for the analysis of linkage disequilibrium between trait loci and one or more polymorphic marker loci. Am. J. Hum. Genet., 56, 777–787.[Web of Science][Medline]
4 Devlin, B., Risch, N. and Roeder, K. (1996) Disequilibrium mapping: composite likelihood for pairwise disequilibrium. Genomics, 36, 1–16.[Web of Science][Medline]
5 Guo, S.W. and Xiong, M. (1997) Genes preserved in relatives. Hum. Hered., 47, 138–154.[Web of Science][Medline]
6 Hill, W.G. and Robertson, A. (1968) Linkage disequilibrium in finite populations. Theoret. Applied Genet., 38, 226–231.
7 Sved, J.A. (1971) Linkage disequilibrium and homozygosity of chromosome segments in finite populations. Theoret. Population Biol., 2, 125–141.
8 Nei, M. and Gaur, D. (1984) Extent of protein polymorphism and the neutral theory. Evolutionary Biol., 73, 118.
9 Wills, C. (1990) Population size bottleneck. Nature, 348, 398.[Medline]
10 Kruglyak, L. (1999) Prospects for whole-genome linkage disequilibrium mapping of common disease genes. Nature Genet., 22, 139–144.[Web of Science][Medline]
11 Cambien, F., Poirier, O., Nicaud, V., Herrmann, S.M., Mallet, C., Ricard, S., Behague, I., Hallet, V., Blanc, H., Loukaci, V. et al. (1999) Sequence diversity in 36 candidate genes for cardiovascular disorders. Am. J. Hum. Genet., 65, 183–191.[Web of Science][Medline]
12 Jorde, L., Watkins, W.S., Carlson, M., Groden, J., Albertsen, H., Thliveris, A. and Leppert, M. (1994) Linkage disequilibrium predicts physical distance in the adenomatous polyposis coli region. Am. J. Hum. Genet., 54, 884–898.[Web of Science][Medline]
13 Cox, A., Camp, N., Nicklin, M., di Giovine, F.S. and Duff, G.W. (1998) An analysis of linkage disequilibrium in the interleukin-1 gene cluster, using a novel grouping method for multiallelic markers. Am. J. Hum. Genet., 62, 1180–1188.[Web of Science][Medline]
14 Barcellos, L.F., Klitz, W., Field, L.L., Tobias, R., Bowcock, A.M., Wilson, R., Nelson, M.P., Nagatomi, J. and Thomson, G. (1998) Association mapping of disease loci, by use of a pooled DNA genomic screen. Am. J. Hum. Genet., 61, 734–747.
15 Simonic, I., Gericke, G.S., Ott, J. and Weber, J.L. (1998) Identification of genetic markers associated with Gilles de la Tourette syndrome in an Afrikaner population. Am. J. Hum. Genet., 63, 839–846.[Web of Science][Medline]
16 Fisher, P.J., Turic, D., Williams, N.M., McGuffin, P., Asherson, P., Ball, D., Craig, I., Eley, T., Hill, L., Chorney, K. et al. (1999) DNA pooling identifies QTLs on chromosome 4 for general cognitive ability in children. Hum. Mol. Genet., 8, 915–922.
17 Hill, L., Craig, I.W., Asherson, P., Ball, D., Eley, Y., Ninomiya, T., Fisher, P.J., Turic, D., McGuffin, P., Owen, M. et al. (1999) DNA pooling and dense marker maps: a systematic search for genes for cognitive ability. Neuroreport, 10, 843–848.[Web of Science][Medline]
18 Lieber, C.S. (1988) Biochemical and molecular basis of alcohol-induced injury to liver and other tissues. N. Engl. J. Med., 319, 1639–1650.[Web of Science][Medline]
19 Ehrig, T. and Li, T.-K. (1995) Metabolism of alcohol and metabolic consequences. In Tabakoff, B. and Hoffman, P. (eds), Biological Aspects of Alcoholism: Implications for Prevention, Treatment and Policy. Hogrefe and Huber, Seattle, WA, pp. 23–48.
20 Goedde, H.W., Agarwal, D.P., Fritze, G., Meier-Tackmann, D., Singh, S., Beckmann, G., Bhatia, K., Chen, L.Z., Fang, B., Lisker, R. et al. (1992) Distribution of ADH2 and ALDH2 genotypes in different populations. Hum. Genet., 88, 344–346.[Web of Science][Medline]
21 Hempel, J., Kaiser, R. and Jornvall, H. (1985) Mitochondrial aldehyde dehydrogenase from human liver. Primary structure. Eur. J. Biochem., 153, 13–28.[Web of Science][Medline]
22 Hsu, L.C., Tani, K., Fujiyoshi, T., Kurachi, K. and Yoshida, A. (1985) Cloning of cDNAs for human aldehyde dehydrogenases 1 and 2. Proc. Natl Acad. Sci. USA, 82, 3771–3775.
23 Yoshida, A., Ikawa, M., Hsu, L.C. and Tani, K. (1985) Molecular abnormality and cDNA cloning of human aldehyde dehydrogenases. Alcohol, 2, 103–106.[Web of Science][Medline]
24 Yoshida, A. (1992) Molecular genetics of human aldehyde dehydrogenase. Pharmacogenetics, 2, 139–147.[Web of Science][Medline]
25 Shibuya, A.M., Yasunami, M. and Yoshida, A. (1989) Genotype of alcohol dehydrogenase and aldehyde dehydrogenase loci in Japanese with alcohol liver disease. Hum. Genet., 82, 14–16.[Web of Science][Medline]
26 Enomoto, N., Takase, S., Yasuhara, M. and Takada, A. (1991) Acetaldehyde metabolism in different aldehyde dehydrogenase-2 genotypes. Alcohol. Clin. Exp. Res., 15, 141–144.[Web of Science][Medline]
27 Shibuya, A. and Yoshida, A. (1988). Genotypes of alcohol-metabolizing enzymes in Japanese with alcohol liver disease. Am. J. Hum. Genet., 43, 744–748.[Web of Science][Medline]
28 Thomasson, H.R., Edenberg, H.J., Crabb, D.W., Mai, X.L., Jerome, R.E., Li, T.K., Wang, S.P., Lin, Y.T., Lu, R.B.and Yin, S.J. (1991) Alcohol and aldehyde dehydrogenase genotypes and alcoholism in Chinese men. Am. J. Hum. Genet., 48, 677–681.[Web of Science][Medline]
29 Tanaka, F.M., Omata, M., Tsukada, Y. and Ohto, M. (1993) ADH 2, 3 and ALDH 2 gene frequency in Japanese alcoholics. Jap. J. Clin. Med., 51, 400–406.
30 Maezawa, Y.M., Yamauchi, M., Toda, G., Suzuki, H.and Sakurai, S. (1995) Alcohol-metabolizing enzyme polymorphisms and alcoholism in Japan. Alcohol. Clin. Exp. Res., 19, 951–954.[Web of Science][Medline]
31 Chen, W.J., Loh, E.W., Hsu, Y.P., Chen, C.C., Yu, J.M. and Cheng, A.T. (1996) Alcohol-metabolising genes and alcoholism. Br. J. Psychiat., 168, 762–767.
32 Nakamura, K., Iwahashi, K., Matsuo, Y., Miyatake, R., Ichikawa, Y. and Suwaki, H. (1996) Characteristics of Japanese alcoholics with the atypical aldehyde dehydrogenase. Alcohol. Clin. Exp. Res., 20, 52–55.[Web of Science][Medline]
33 Zhao, J.-H., Curtis, D. and Sham, P.D. (1999) Model-free and permutation analysis for allelic associations. Hum. Hered., 50, 133–139.
34 Peterson, R.J., Goldman, D. and Long, J. (1999) Nucleotide sequence diversity in non-coding regions of ALDH2 as revealed by restriction enzyme and SSCP analysis. Hum. Genet., 104, 177–187.[Web of Science][Medline]
35 Peterson, R.J., Goldman, D. and Long, J.C. (1999) Effects of worldwide subdivision on ALDH2 linkage disequilibrium. Genome Res., 9, 844–852.
36 Moffat, M.F., Traherne, J.A., Abecasis, G.R. and Cookson, W.O.C.M. (2000) Single nucleotide polymorphism and linkage disequilibrium within the TCR / locus. Hum. Mol. Genet., 7, 1011–1019.
37 Gibbs, R.A., Nguyen, P.-N. and Caskey, C.T. (1989) Detection of single DNA base differences by competitive oligonucleotide priming. Nucleic Acids Res., 17, 2437–2448.
38 Craig, I., McClay, J., Plomin, R. and Freeman, B. (2000) Chasing behaviour genes into the next millennium. Trends Biotechnol., 18, 22–26.[Web of Science][Medline]
39 Sham, P.C. and Curtis, D. (1995) Monte Carlo tests for associations between disease and alleles at highly polymorphic loci. Ann. Hum. Genet., 59, 97–105.[Web of Science][Medline]
40 Xie, X. and Ott, J. (1993) Testing linkage disequilibrium between a disease gene and marker loci. Am. J. Hum. Genet., 53, 1107.[Web of Science][Medline]
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  M. G. Tyshenko and W. Leiss Current trends in publicly available genetic databases Health Informatics Journal, December 1, 2005; 11(4): 295 - 308. [Abstract] [PDF]
|
|
|
|
 |
|
 G. Tamiya, M. Shinya, T. Imanishi, T. Ikuta, S. Makino, K. Okamoto, K. Furugaki, T. Matsumoto, S. Mano, S. Ando, et al. Whole genome association study of rheumatoid arthritis using 27 039 microsatellites Hum. Mol. Genet., August 15, 2005; 14(16): 2305 - 2321. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 N. Yanagitani, T. Kohno, N. Sunaga, H. Kunitoh, T. Tamura, S. Tsuchiya, R. Saito, and J. Yokota Localization of a human lung adenocarcinoma susceptibility locus, possibly syntenic to the mouse Pas1 locus, in the vicinity of the D12S1034 locus on chromosome 12p11.2-p12.1 Carcinogenesis, July 1, 2002; 23(7): 1177 - 1183. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. Tiret, O. Poirier, V. Nicaud, S. Barbaux, S.-M. Herrmann, C. Perret, S. Raoux, C. Francomme, G. Lebard, D. Tregouet, et al. Heterogeneity of linkage disequilibrium in human genes has implications for association studies of common diseases Hum. Mol. Genet., February 1, 2002; 11(4): 419 - 429. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. D. Roses Pharmacogenetics Hum. Mol. Genet., October 1, 2001; 10(20): 2261 - 2267. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. L. Remington, J. M. Thornsberry, Y. Matsuoka, L. M. Wilson, S. R. Whitt, J. Doebley, S. Kresovich, M. M. Goodman, and E. S. Buckler IV Structure of linkage disequilibrium and phenotypic associations in the maize genome PNAS, September 13, 2001; (2001) 201394398. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
D. L. Remington, J. M. Thornsberry, Y. Matsuoka, L. M. Wilson, S. R. Whitt, J. Doebley, S. Kresovich, M. M. Goodman, and E. S. Buckler IV Structure of linkage disequilibrium and phenotypic associations in the maize genome PNAS, September 25, 2001; 98(20): 11479 - 11484. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||