Comparative informativeness for linkage of multiple SNPs and single microsatellites

Single nucleotide polymorphisms (SNPs), or biallelic markers, are popular in genetic linkage studies due to their abundance in the genome, stability, and ease of scoring. We determined the 'information ratio' (IR) of closely spaced SNPs in simulated nuclear families and affected sib pairs (ASPs). (The IR is the ratio of actual average maximum lod score to the maximum lod score attainable if the marker were fully informative.) The nuclear families included parental information, whereas the ASPs did not. We analyzed these SNPs in two ways: (1) using multipoint analysis, and (2) treating the SNPs as 'composite markers' (i.e., haplotypes, as assigned by GENEHUNTER). (3) We also calculated the IR of a single microsatellite marker with multiple alleles and compared with the IR from the SNPs. For each set of input conditions, we simulated 1000 nuclear families, of 2, 3, 4, or 5 children each, as well as 1000 ASPs. We generated SNP marker data for strings of k = 1, 2, 3, 5, 7, and 10 SNP loci, with no recombination (theta = 0) and no linkage disequilibrium among the SNPs. The MAF (minor allele frequency) was either 0.5 or 0.25, and allele frequencies were the same for all k loci in any analysis. We also generated marker data for one single-locus microsatellite marker, with m = 3, 4, 5, 6, 7, and 9 equally frequent alleles. In all simulations, the disease was fully penetrant dominant, and there was no recombination or linkage disequilibrium among markers or between marker and disease. When multipoint analysis was used, we found that 5-7 closely spaced SNPs were usually enough to yield an IR of approximately 100%, for nuclear families of any size. However, for the ASPs, even 7-10 SNPs yielded an IR of only 70-80%. A microsatellite with 9 equally frequent alleles yielded about the same IR (86-88%) as a string of 4-5 SNPs, in nuclear families. SNPs analyzed as 'composite markers' analyses performed worse, due to the inherent ambiguity of SNP haplotyping.     

Sequence polymorphism at the human apolipoprotein AII gene (<Emphasis Type="Italic">APOA2</Emphasis>): unexpected deficit of variation in an African-American sample

A 3.3-kb region, encompassing the APOA2 gene and 2 kb of 5' and 3' flanking DNA, was re-sequenced in a "core" sample of 24 individuals, sampled without regard to the health from each of three populations: African-Americans from Jackson (Miss., USA), Europeans from North Karelia (Finland), and non-Hispanic European-Americans from Rochester, (Minn., USA). Fifteen variable sites were identified (14 SNPs and one multi-allelic microsatellite, all silent), and these sites segregated as 18 sequence haplotypes (or nine, if SNPs only are considered). The haplotype distribution in the core African-American sample was unusual, with a deficit of particular haplotypes compared with those found in the other two samples, and a significantly (P<0.05) low level of nucleotide diversity relative to patterns of polymorphism and divergence at other human loci. Six of the 14 SNPs, whose variation captured the haplotype structure of the core data, were then genotyped by oligonucleotide ligation assay in an additional 2183 individuals from the same three populations (n=843, n=452, and n=888, respectively). All six sites varied in each of the larger "epidemiological" samples, and together, they defined 19 SNP haplotypes, seven with relative frequencies greater than 1% in the total sample; all of these common haplotypes had been identified earlier in the core re-sequencing survey. Here also, the African-American sample showed significantly lower SNP heterozygosity and haplotype diversity than the other two samples. The deficit of polymorphism is consistent with a population-specific non-neutral increase in the relative frequency of several haplotypes in Jackson.     

Comparative LD mapping using single SNPs and haplotypes identifies QTL for plant height and biomass as secondary traits of drought tolerance in maize

Drought often delays developmental events so that plant height and above-ground biomass are reduced, resulting in yield loss due to inadequate photosynthate. In this study, plant height and biomass measured by the Normalized Difference Vegetation Index (NDVI) were used as criteria for drought tolerance. A total of 305 lines representing temperate, tropical and subtropical maize germplasm were genotyped using two single nucleotide polymorphism (SNP) chips each containing 1536 markers, from which 2052 informative SNPs and 386 haplotypes each constructed with two or more SNPs were used for linkage disequilibrium (LD) or association mapping. Single SNP- and haplotype-based LD mapping identified two significant SNPs and three haplotype loci [a total of four quantitative trait loci (QTL)] for plant height under well-watered and water-stressed conditions. For biomass, 32 SNPs and 12 haplotype loci (30 QTL) were identified using NDVIs measured at seven stages under the two water regimes. Some significant SNP and haplotype loci for NDVI were shared by different stages. Comparing significant loci identified by single SNP- and haplotype-based LD mapping, we found that six out of the 14 chromosomal regions defined by haplotype loci each included at least one significant SNP for the same trait. Significant SNP haplotype loci explained much higher phenotypic variation than individual SNPs. Moreover, we found that two significant SNPs (two QTL) and one haplotype locus were shared by plant height and NDVI. The results indicate the power of comparative LD mapping using single SNPs and SNP haplotypes with QTL shared by plant height and biomass as secondary traits for drought tolerance in maize.     

Estimation of DNA sequence diversity in bovine cytokine genes

DNA sequence variation provides the fundamental material for improving livestock through selection. In cattle, single nucleotide polymorphisms and small insertions/deletions (collectively referred to here as SNPs) have been identified in cytokine genes and scored in a reference population to determine linkage map positions. The aim of the present study was twofold: first, to estimate the SNP frequency in a reference population of beef cattle, and second, to determine cytokine haplotypes in a group of sires from commercial populations. Forty-five SNP markers in DNA segments from nine cytokine gene loci were analyzed in 26 reference parents. Comparison of all 52 haploid genomes at each PCR amplicon locus revealed an average of one SNP per 143 bp of sequence, whereas comparison of any two chromosomes identified heterozygous sites, on average, every 443 bp. The combination of these 45 SNP genotypes was sufficient to uniquely identify each of the 26 animals. The average number of haplotype alleles (4.4) per PCR amplicon (688 bp) and the percentage heterozygosity among founding parents (50%) were similar to those for microsatellite markers in the same population. For 49 sires from seven common breeds of beef cattle, SNP genotypes (1225 total) were obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) at three amplicon loci. All three of the amplicon haplotypes were correctly deduced for each sire without the use of parent or progeny genotypes. The latter allows a wide range of genetic studies in commercial populations of cattle where genotypic information from relatives may not be available. Received: 16 June 2000 / Accepted: 23 August 2000     

A comparison of simple sequence repeat and single nucleotide polymorphism marker technologies for the genotypic analysis of maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.)

We report on the comparative utilities of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers for characterizing maize germplasm in terms of their informativeness, levels of missing data, repeatability and the ability to detect expected alleles in hybrids and DNA pools. Two different SNP chemistries were compared; single-base extension detected by Sequenom MassARRAY, and invasive cleavage detected by Invader chemistry with PCR. A total of 58 maize inbreds and four hybrids were genotyped with 80 SSR markers, 69 Invader SNP markers and 118 MassARRAY SNP markers, with 64 SNP loci being common to the two SNP marker chemistries. Average expected heterozygosity values were 0.62 for SSRs, 0.43 for SNPs (pre-selected for their high level of polymorphism) and 0.63 for the underlying sequence haplotypes. All individual SNP markers within the same set of sequences had an average expected heterozygosity value of 0.26. SNP marker data had more than a fourfold lower level of missing data (2.1-3.1%) compared with SSRs (13.8%). Data repeatability was higher for SNPs (98.1% for MassARRAY SNPs and 99.3% for Invader) than for SSRs (91.7%). Parental alleles were observed in hybrid genotypes in 97.0% of the cases for MassARRAY SNPs, 95.5% for Invader SNPs and 81.9% for SSRs. In pooled samples with mixtures of alleles, SSRs, MassARRAY SNPs and Invader SNPs were equally capable of detecting alleles at mid to high frequencies. However, at low frequencies, alleles were least likely to be detected using Invader SNP markers, and this technology had the highest level of missing data. Collectively, these results showed that SNP technologies can provide increased marker data quality and quantity compared with SSRs. The relative loss in polymorphism compared with SSRs can be compensated by increasing SNP numbers and by using SNP haplotypes. Determining the most appropriate SNP chemistry will be dependent upon matching the technical features of the method within the context of application, particularly in consideration of whether genotypic samples will be pooled or assayed individually.     

<Emphasis Type="Italic">FMR1</Emphasis> haplotype analyses among Indians: a weak founder effect and other findings

This study on allelic/haplotypic fragile X associations evaluated using STR (DXS548, FRAXAC1, FRAXAC2) and SNP (ATL1) markers flanking the (CGG)(n) locus of FMR1is the first report from the large ethnically complex Indian population. Results have been compared with allele/haplotype distributions reported for other major ethnic groups, including White Caucasians, Africans, and Pacific Asians. Though overall allele frequency distributions at the individual loci are more similar to Western Caucasians compared with others, significant differences are observed in haplotypic associations with the mutated X. The striking findings are: (1) high diversity and heterozygosity of haplotypes among fragile X chromosomes ( n=40) and controls ( n=262), including four haplotypes found exclusively in this study sample; (2) weak association of DXS548-FRAXAC1-FRAXAC2 haplotypes, 2-1-3, 6-3-3+ and 7-4-6+ with the disorder, and absence of White Caucasian fragile X haplotypes 6-4-4 and 6-4-5; (3) weak founder effect for the fragile X expansion mutation in the Indians; (4) lack of a continuum of haplotype-based FMR1 alleles between intermediate (CGG)(n) size ranges and expanded alleles; (5) exclusion of ATL1 as a candidate genetic indicator of FMR1 instability. The high STR-based haplotype diversity observed among fragile X lineages, irrespective of ethnic alliances, strongly suggests the inappropriateness of using STR haplotypes to infer predisposition to instability among ethnically separated fragile X pedigrees and may reiterate the need for identifying newer SNPs from this region to not only determine true founder effects for the fragile X mutation, but also decipher possible mechanisms leading to CGG instability.     

Sequences associated with human iris pigmentation

To determine whether and how common polymorphisms are associated with natural distributions of iris colors, we surveyed 851 individuals of mainly European descent at 335 SNP loci in 13 pigmentation genes and 419 other SNPs distributed throughout the genome and known or thought to be informative for certain elements of population structure. We identified numerous SNPs, haplotypes, and diplotypes (diploid pairs of haplotypes) within the OCA2, MYO5A, TYRP1, AIM, DCT, and TYR genes and the CYP1A2-15q22-ter, CYP1B1-2p21, CYP2C8-10q23, CYP2C9-10q24, and MAOA-Xp11.4 regions as significantly associated with iris colors. Half of the associated SNPs were located on chromosome 15, which corresponds with results that others have previously obtained from linkage analysis. We identified 5 additional genes (ASIP, MC1R, POMC, and SILV) and one additional region (GSTT2-22q11.23) with haplotype and/or diplotypes, but not individual SNP alleles associated with iris colors. For most of the genes, multilocus gene-wise genotype sequences were more strongly associated with iris colors than were haplotypes or SNP alleles. Diplotypes for these genes explain 15% of iris color variation. Apart from representing the first comprehensive candidate gene study for variable iris pigmentation and constituting a first step toward developing a classification model for the inference of iris color from DNA, our results suggest that cryptic population structure might serve as a leverage tool for complex trait gene mapping if genomes are screened with the appropriate ancestry informative markers.     

Combining markers into haplotypes can improve population structure inference

High-throughput genotyping and sequencing technologies can generate dense sets of genetic markers for large numbers of individuals. For most species, these data will contain many markers in linkage disequilibrium (LD). To utilize such data for population structure inference, we investigate the use of haplotypes constructed by combining the alleles at single-nucleotide polymorphisms (SNPs). We introduce a statistic derived from information theory, the gain of informativeness for assignment (GIA), which quantifies the additional information for assigning individuals to populations using haplotype data compared to using individual loci separately. Using a two-loci-two-allele model, we demonstrate that combining markers in linkage equilibrium into haplotypes always leads to nonpositive GIA, suggesting that combining the two markers is not advantageous for ancestry inference. However, for loci in LD, GIA is often positive, suggesting that assignment can be improved by combining markers into haplotypes. Using GIA as a criterion for combining markers into haplotypes, we demonstrate for simulated data a significant improvement of assigning individuals to candidate populations. For the many cases that we investigate, incorrect assignment was reduced between 26% and 97% using haplotype data. For empirical data from French and German individuals, the incorrectly assigned individuals can, for example, be decreased by 73% using haplotypes. Our results can be useful for challenging population structure and assignment problems, in particular for studies where large-scale population-genomic data are available.     

Genome scan linkage analysis comparing microsatellites and single-nucleotide polymorphisms markers for two measures of alcoholism in chromosomes 1, 4, and 7

Background

We analyzed 143 pedigrees (364 nuclear families) in the Collaborative Study on the Genetics of Alcoholism (COGA) data provided to the participants in the Genetic Analysis Workshop 14 (GAW14) with the goal of comparing results obtained from genome linkage analysis using microsatellite and with results obtained using SNP markers for two measures of alcoholism (maximum number of drinks -MAXDRINK and an electrophysiological measure from EEG -TTTH1). First, we constructed haplotype blocks by using the entire set of single-nucleotide polymorphisms (SNP) in chromosomes 1, 4, and 7. These chromosomes have shown linkage signals for MAXDRINK or EEG-TTTH1 in previous reports. Second, we randomly selected one, two, three, four, and five SNPs from each block (referred to as Rep1 – Rep5, respectively) to conduct linkage analysis using variance component approach. Finally, results of all SNP analyses were compared with those obtained using microsatellite markers.

Results

The LOD scores obtained from SNPs were slightly higher but the curves were not radically different from those obtained from microsatellite analyses. The peaks of linkage regions from SNP sets were slightly shifted to the left when compared to those from microsatellite markers. The reduced sets of SNPs provide signals in the same linkage regions but with a smaller LOD score suggesting a significant impact of the decrease in information content on linkage results. The widths of 1 LOD support interval of linkage regions from SNP sets were smaller when compared to those of microsatellite markers. However, two linkage regions obtained from the microsatellite linkage analysis on chromosome 7 for LOG of TTTH1 were not detected in the SNP based analyses.

Conclusion

The linkage results from SNPs showed narrower linkage regions and slightly higher LOD scores when compared to those of microsatellite markers. The different builds of the genetic maps used in microsatellite and SNPs markers or/and errors in genotyping may account for the microsatellite linkage signals on chromosome 7 that were not identified using SNPs. Also, unresolved map issues between SNPs and microsatellite markers may be partly responsible for the shifted linkage peaks when comparing the two types of markers.

     

Development of highly polymorphic SNP markers from the complexity reduced portion of maize [Zea mays L.] genome for use in marker-assisted breeding

The duplicated and the highly repetitive nature of the maize genome has historically impeded the development of true single nucleotide polymorphism (SNP) markers in this crop. Recent advances in genome complexity reduction methods coupled with sequencing-by-synthesis technologies permit the implementation of efficient genome-wide SNP discovery in maize. In this study, we have applied Complexity Reduction of Polymorphic Sequences technology (Keygene N.V., Wageningen, The Netherlands) for the identification of informative SNPs between two genetically distinct maize inbred lines of North and South American origins. This approach resulted in the discovery of 1,123 putative SNPs representing low and single copy loci. In silico and experimental (Illumina GoldenGate (GG) assay) validation of putative SNPs resulted in mapping of 604 markers, out of which 188 SNPs represented 43 haplotype blocks distributed across all ten chromosomes. We have determined and clearly stated a specific combination of stringent criteria (>0.3 minor allele frequency, >0.8 GenTrainScore and >0.5 Chi_test100 score) necessary for the identification of highly polymorphic and genetically stable SNP markers. Due to these criteria, we identified a subset of 120 high-quality SNP markers to leverage in GG assay-based marker-assisted selection projects. A total of 32 high-quality SNPs represented 21 haplotypes out of 43 identified in this study. The information on the selection criteria of highly polymorphic SNPs in a complex genome such as maize and the public availability of these SNP assays will be of great value for the maize molecular genetics and breeding community.     

Sequence-Level Analysis of the Major European Huntington Disease Haplotype

Huntington disease (HD) reflects the dominant consequences of a CAG-repeat expansion in HTT. Analysis of common SNP-based haplotypes has revealed that most European HD subjects have distinguishable HTT haplotypes on their normal and disease chromosomes and that ∼50% of the latter share the same major HD haplotype. We reasoned that sequence-level investigation of this founder haplotype could provide significant insights into the history of HD and valuable information for gene-targeting approaches. Consequently, we performed whole-genome sequencing of HD and control subjects from four independent families in whom the major European HD haplotype segregates with the disease. Analysis of the full-sequence-based HTT haplotype indicated that these four families share a common ancestor sufficiently distant to have permitted the accumulation of family-specific variants. Confirmation of new CAG-expansion mutations on this haplotype suggests that unlike most founders of human disease, the common ancestor of HD-affected families with the major haplotype most likely did not have HD. Further, availability of the full sequence data validated the use of SNP imputation to predict the optimal variants for capturing heterozygosity in personalized allele-specific gene-silencing approaches. As few as ten SNPs are capable of revealing heterozygosity in more than 97% of European HD subjects. Extension of allele-specific silencing strategies to the few remaining homozygous individuals is likely to be achievable through additional known SNPs and discovery of private variants by complete sequencing of HTT. These data suggest that the current development of gene-based targeting for HD could be extended to personalized allele-specific approaches in essentially all HD individuals of European ancestry.     

Characterizing genic and nongenic molecular markers: comparison of microsatellites and SNPs

The implications of transitioning to single nucleotide polymorphism (SNPs) from microsatellite markers (MSs) have been investigated in a number of population genetics studies, but the effect of genomic location on the amount of information each type of marker reveals has not been explored in detail. We developed novel SNP markers flanking 1 kb regions of 13 genic (within gene or <1 kb away from gene) and 13 nongenic (>10 kb from annotated gene) MSs in the threespine stickleback genome to obtain comparable data for both types of markers. We analysed patterns of genetic diversity and divergence on various geographic scales after converting the SNP loci within each genomic region into haplotypes. Marker type (SNP haplotype or MS) and location (genic or nongenic) significantly affected most estimates of population diversity and divergence. Between‐lineage divergence was significantly higher in SNP haplotypes (genic and nongenic), however, within‐lineage divergence was similar between marker types. Most divergence and diversity measures were uncorrelated between markers, except for population differentiation which was correlated between MSs and SNP haplotypes (both genic and nongenic). Broad‐scale population structure and assignment were similarly resolved by both marker types, however, only the MSs were able to delimit fine‐scale population structuring, particularly when genic and nongenic markers were combined. These results demonstrate that estimates of genetic variability and differentiation among populations can be strongly influenced by marker type, their genomic location in relation to genes and by the interaction of these two factors. This highlights the importance of having an awareness of the inherent strengths and limitations associated with different molecular tools to select the most appropriate methods for accurately addressing various ecological and evolutionary questions.     

Association analysis of the RGS4 gene in Han Chinese and Scottish populations with schizophrenia

We investigated the RGS4 as a susceptibility gene for schizophrenia in Chinese Han (184 trios and 138 sibling pairs, a total of 322 families) and Scottish (580 cases and 620 controls) populations using both a family trio and case-control design. Both the samples had statistical power greater than 70% to detect a heterozygote genotype relative risk of >1.2 for frequent RGS4-risk alleles. We genotyped four single nucleotide polymorphisms (SNPs) which have previously been associated with schizophrenia as either individually or part of haplotypes. Allele frequencies and linkage disequilibrium between the SNPs was similar in the two populations. In the Chinese sample, no individual SNPs or any of their haplotypes were associated with schizophrenia. In the Scottish population, one SNP (SNP7) was significantly over-represented in the cases compared with the controls (0.44 vs. 0.38; A allele; chi(2) 7.08, P = 0.011 after correction for correlation between markers by permutation testing). One two-marker haplotype, composed of alleles T and A of SNP4 and SNP7, respectively, showed individual significance after correction by permutation testing (chi(2) 6.8; P = 0.04). None of the full four-marker haplotypes showed association, including the G-G-G-G haplotype previously associated with schizophrenia in more than one sample and the A-T-A-A haplotype. Thus, our data do not directly replicate previous associations of RGS4, but association with SNP 7 in the Scottish population provides some support for a role in schizophrenia susceptibility. We cannot conclusively exclude RGS4, as associated haplotypes are likely to be surrogates for unknown causative alleles, whose relationship with overlying haplotypes may differ between the population groups. Differences in the association seen across the two populations could result from methodological factors such as diagnostic differences but most likely result from ethnic differences in haplotype structures within RGS4.     

Haplotype‐based genotyping‐by‐sequencing in oat genome research

In a de novo genotyping‐by‐sequencing (GBS) analysis of short, 64‐base tag‐level haplotypes in 4657 accessions of cultivated oat, we discovered 164741 tag‐level (TL) genetic variants containing 241224 SNPs. From this, the marker density of an oat consensus map was increased by the addition of more than 70000 loci. The mapped TL genotypes of a 635‐line diversity panel were used to infer chromosome‐level (CL) haplotype maps. These maps revealed differences in the number and size of haplotype blocks, as well as differences in haplotype diversity between chromosomes and subsets of the diversity panel. We then explored potential benefits of SNP vs. TL vs. CL GBS variants for mapping, high‐resolution genome analysis and genomic selection in oats. A combined genome‐wide association study (GWAS) of heading date from multiple locations using both TL haplotypes and individual SNP markers identified 184 significant associations. A comparative GWAS using TL haplotypes, CL haplotype blocks and their combinations demonstrated the superiority of using TL haplotype markers. Using a principal component‐based genome‐wide scan, genomic regions containing signatures of selection were identified. These regions may contain genes that are responsible for the local adaptation of oats to Northern American conditions. Genomic selection for heading date using TL haplotypes or SNP markers gave comparable and promising prediction accuracies of up to r = 0.74. Genomic selection carried out in an independent calibration and test population for heading date gave promising prediction accuracies that ranged between r = 0.42 and 0.67. In conclusion, TL haplotype GBS‐derived markers facilitate genome analysis and genomic selection in oat.     

Accuracy of marker-assisted selection with single markers and marker haplotypes in cattle

A key question for the implementation of marker-assisted selection (MAS) using markers in linkage disequilibrium with quantitative trait loci (QTLs) is how many markers surrounding each QTL should be used to ensure the marker or marker haplotypes are in sufficient linkage disequilibrium (LD) with the QTL. In this paper we compare the accuracy of MAS using either single markers or marker haplotypes in an Angus cattle data set consisting of 9323 genome-wide single nucleotide polymorphisms (SNPs) genotyped in 379 Angus cattle. The extent of LD in the data set was such that the average marker-marker r2 was 0.2 at 200 kb. The accuracy of MAS increased as the number of markers in the haplotype surrounding the QTL increased, although only when the number of markers in the haplotype was 4 or greater did the accuracy exceed that achieved when the SNP in the highest LD with the QTL was used. A large number of phenotypic records (>1000) were required to accurately estimate the effects of the haplotypes.     

Linkage disequilibrium studies in multiple endocrine neoplasia type 1 (MEN1)

Multiple endocrine neoplasia type 1 (MEN1) is an autosomal dominant disorder characterised by tumours of the parathyroids, pancreas and anterior pituitary. The MEN1 gene has been localised to a 2-Mb region of chromosome 11q13 by meiotic mapping studies in MEN1 families. Such studies may have a limited resolution of approximately 1 cM (i.e. 1 Mb) and we have therefore investigated 96 MEN1 families (40 British, 17 French, 12 Finnish, 7 Swedish, 7 Dutch, 7 North American, 2 Australian, 1 New Zealand, 1 German, 1 Spanish and 1 Danish) for linkage disequilibrium, in order to facilitate a finer mapping resolution. We have utilised five microsatellite DNA sequence polymorphisms from the candidate region and have accurately determined their allele sizes, which ranged from 161 bp to 272 bp. The heterozygosity and number of alleles (given in brackets), respectively, at the loci were: D11S1883 (76%, 11), D11S457 (55%, 5), PYGM (94%, 18), D11S1783 (10%, 4) and D11S449 (87%, 16). Allelic association was assessed by Chi-square 2 ×n contingency tables, by Fisher exact 2 ×n contingency tables and by a likelihood-based approach. The results of haplotype analysis revealed 91 different affected haplotypes in the 96 families, an identical affected haplotype being observed in no more than two families. These results indicate the absence of an ancestral affected haplotype. Significant linkage disequilibrium (P < 0.005) could be established amongst the microsatellite loci but not between the loci and MEN1 in either the total population or in any of the geographical sub-populations. The absence of linkage disequilibrium between MEN1 and the polymorphic loci is probably the result of the occurrence of multiple different disease-causing mutations in MEN1. Received: 1 April 1997 / Accepted: 25 June 1997     

A double classification tree search algorithm for index SNP selection

Background  

In population-based studies, it is generally recognized that single nucleotide polymorphism (SNP) markers are not independent. Rather, they are carried by haplotypes, groups of SNPs that tend to be coinherited. It is thus possible to choose a much smaller number of SNPs to use as indices for identifying haplotypes or haplotype blocks in genetic association studies. We refer to these characteristic SNPs as index SNPs. In order to reduce costs and work, a minimum number of index SNPs that can distinguish all SNP and haplotype patterns should be chosen. Unfortunately, this is an NP-complete problem, requiring brute force algorithms that are not feasible for large data sets.