A high-density SNP genomewide linkage scan for chronic lymphocytic leukemia-susceptibility loci

Chronic lymphocytic leukemia (CLL) and other B-cell lymphoproliferative disorders (LPDs) show clear evidence of familial aggregation, but the inherited basis is largely unknown. To identify a susceptibility gene for CLL, we conducted a genomewide linkage analysis of 115 pedigrees, using a high-density single-nucleotide polymorphism (SNP) array containing 11,560 markers. Multipoint linkage analyses were undertaken using both nonparametric (model-free) and parametric (model-based) methods. Our results confirm that the presence of high linkage disequilibrium (LD) between SNP markers can lead to inflated nonparametric linkage (NPL) and LOD scores. After the removal of high-LD SNPs, we obtained a maximum NPL of 3.14 (P=.0008) on chromosome 11p11. The same genomic position also yielded the highest multipoint heterogeneity LOD (HLOD) score under both dominant (HLOD 1.95) and recessive (HLOD 2.78) models. In addition, four other chromosomal positions (5q22-23, 6p22, 10q25, and 14q32) displayed HLOD scores >1.15 (which corresponds to a nominal P value <.01). None of the regions coincided with areas of common chromosomal abnormalities frequently observed for CLL. These findings strengthen the argument for an inherited predisposition to CLL and related B-cell LPDs.     

High-density single nucleotide polymorphism screen in a large multiplex neural tube defect family refines linkage to loci at 7p21.1-pter and 2q33.1-q35

BACKGROUND: Neural tube defects (NTDs) are considered complex, with both genetic and environmental factors implicated. To date, no major causative genes have been identified in humans despite several investigations. The first genomewide screen in NTDs demonstrated evidence of linkage to chromosomes 7 and 10. This screen included 44 multiplex families and consisted of 402 microsatellite markers spaced approximately 10 cM apart. Further investigation of the genomic screen data identified a single large multiplex family, pedigree 8776, as primarily driving the linkage results on chromosome 7. METHODS: To investigate this family more thoroughly, a high-density single nucleotide polymorphism (SNP) screen was performed. Two-point and multipoint linkage analyses were performed using both parametric and nonparametric methods. RESULTS: For both the microsatellite and SNP markers, linkage analysis suggested the involvement of a locus or loci proximal to the telomeric regions of chromosomes 2q and 7p, with both regions generating a LOD* score of 3.0 using a nonparametric identity by descent relative sharing method. CONCLUSIONS: The regions with the strongest evidence for linkage map proximal to the telomeres on these two chromosomes. In addition to mutations and/or variants in a major gene, these loci may harbor a microdeletion and/or translocation; potentially, polygenic factors may also be involved. This single family may be promising for narrowing the search for NTD susceptibility genes.     

A 3.9-centimorgan-resolution human single-nucleotide polymorphism linkage map and screening set

Recent advances in technologies for high-throughout single-nucleotide polymorphism (SNP)-based genotyping have improved efficiency and cost so that it is now becoming reasonable to consider the use of SNPs for genomewide linkage analysis. However, a suitable screening set of SNPs and a corresponding linkage map have yet to be described. The SNP maps described here fill this void and provide a resource for fast genome scanning for disease genes. We have evaluated 6,297 SNPs in a diversity panel composed of European Americans, African Americans, and Asians. The markers were assessed for assay robustness, suitable allele frequencies, and informativeness of multi-SNP clusters. Individuals from 56 Centre d'Etude du Polymorphisme Humain pedigrees, with >770 potentially informative meioses altogether, were genotyped with a subset of 2,988 SNPs, for map construction. Extensive genotyping-error analysis was performed, and the resulting SNP linkage map has an average map resolution of 3.9 cM, with map positions containing either a single SNP or several tightly linked SNPs. The order of markers on this map compares favorably with several other linkage and physical maps. We compared map distances between the SNP linkage map and the interpolated SNP linkage map constructed by the deCode Genetics group. We also evaluated cM/Mb distance ratios in females and males, along each chromosome, showing broadly defined regions of increased and decreased rates of recombination. Evaluations indicate that this SNP screening set is more informative than the Marshfield Clinic's commonly used microsatellite-based screening set.     

Gene-centric genomewide association study via entropy

Genes are the functional units in most organisms. Compared to genetic variants located outside genes, genic variants are more likely to affect disease risk. The development of the human HapMap project provides an unprecedented opportunity for genetic association studies at the genomewide level for elucidating disease etiology. Currently, most association studies at the single-nucleotide polymorphism (SNP) or the haplotype level rely on the linkage information between SNP markers and disease variants, with which association findings are difficult to replicate. Moreover, variants in genes might not be sufficiently covered by currently available methods. In this article, we present a gene-centric approach via entropy statistics for a genomewide association study to identify disease genes. The new entropy-based approach considers genic variants within one gene simultaneously and is developed on the basis of a joint genotype distribution among genetic variants for an association test. A grouping algorithm based on a penalized entropy measure is proposed to reduce the dimension of the test statistic. Type I error rates and power of the entropy test are evaluated through extensive simulation studies. The results indicate that the entropy test has stable power under different disease models with a reasonable sample size. Compared to single SNP-based analysis, the gene-centric approach has greater power, especially when there is more than one disease variant in a gene. As the genomewide genic SNPs become available, our entropy-based gene-centric approach would provide a robust and computationally efficient way for gene-based genomewide association study.     

Evaluation of linkage disequilibrium and its effect on non-parametric multipoint linkage analysis using two high density single-nucleotide polymorphism mapping panels

Genotype data from the Illumina Linkage III SNP panel (n = 4,720 SNPs) and the Affymetrix 10 k mapping array (n = 11,120 SNPs) were used to test the effects of linkage disequilibrium (LD) between SNPs in a linkage analysis in the Collaborative Study on the Genetics of Alcoholism pedigree collection (143 pedigrees; 1,614 individuals). The average r2 between adjacent markers across the genetic map was 0.099 +/- 0.003 in the Illumina III panel and 0.17 +/- 0.003 in the Affymetrix 10 k array. In order to determine the effect of LD between marker loci in a nonparametric multipoint linkage analysis, markers in strong LD with another marker (r2 > 0.40) were removed (n = 471 loci in the Illumina panel; n = 1,804 loci in the Affymetrix panel) and the linkage analysis results were compared to the results using the entire marker sets. In all analyses using the ALDX1 phenotype, 8 linkage regions on 5 chromosomes (2, 7, 10, 11, X) were detected (peak markers p < 0.01), and the Illumina panel detected an additional region on chromosome 6. Analysis of the same pedigree set and ALDX1 phenotype using short tandem repeat markers (STRs) resulted in 3 linkage regions on 3 chromosomes (peak markers p < 0.01). These results suggest that in this pedigree set, LD between loci with spacing similar to the SNP panels tested may not significantly affect the overall detection of linkage regions in a genome scan. Moreover, since the data quality and information content are greatly improved in the SNP panels over STR genotyping methods, new linkage regions may be identified due to higher information content and data quality in a dense SNP linkage panel.     

Genome-wide scan for bovine twinning rate QTL using linkage disequilibrium

Twinning is a complex trait with negative impacts on health and reproduction, which cause economic loss in dairy production. Several twinning rate quantitative trait loci (QTL) have been detected in previous studies, but confidence intervals for QTL location are broad and many QTL are unreplicated. To identify genomic regions or genes associated with twinning rate, QTL analysis based on linkage combined with linkage disequilibrium (LLD) and individual marker associations was conducted across the genome using high-throughput single nucleotide polymorphism (SNP) genotypes. A total of 9919 SNP markers were genotyped with 200 sires and sons in 19 half-sib North American Holstein dairy cattle families. After SNPs were genotyped, informative markers were selected for genome-wide association tests and QTL searches. Evidence for twinning rate QTL was found throughout the genome. Thirteen markers significantly associated with twinning rate were detected on chromosomes 2, 5 and 14 ( P  < 2.3 × 10⁻⁵). Twenty-six regions on fourteen chromosomes were identified by LLD analysis at P  < 0.0007. Seven previously reported ovulation or twinning rate QTL were supported by results of single marker association or LLD analyses. Single marker association analysis and LLD mapping were complementary tools for the identification of putative QTL in this genome scan.     

Comparing single-nucleotide polymorphism marker-based and microsatellite marker-based linkage analyses

We compared linkage analysis results for an alcoholism trait, ALDX1 (DSM-III-R and Feigner criteria) using a nonparametric linkage analysis method, which takes into account allele sharing among several affected persons, for both microsatellite and single-nucleotide polymorphism (SNP) markers (Affymetrix and Illumina) in the Collaborative Study on the Genetics of Alcoholism (COGA) dataset provided to participants at the Genetic Analysis Workshop 14 (GAW14). The two sets of linkage results from the dense Affymetrix SNP markers and less densely spaced Illumina SNP markers are very similar. The linkage analysis results from microsatellite and SNP markers are generally similar, but the match is not perfect. Strong linkage peaks were found on chromosome 7 in three sets of linkage analyses using both SNP and microsatellite marker data. We also observed that for SNP markers, using the given genetic map and using the map by converting 1 megabase pair (1 Mb) to 1 centimorgan (cM), did not change the linkage results. We recommend the use of the 1 Mb-to-1 cM converted map in a first round of linkage analysis with SNP markers in which map integration is an issue.     

Comparison of the power between microsatellite and single-nucleotide polymorphism markers for linkage and linkage disequilibrium mapping of an electrophysiological phenotype

We performed linkage and linkage disequilibrium (LD) mapping analyses to compare the power between microsatellite and single nucleotide polymorphism (SNP) markers. Chromosome-wide analyses were performed for a quantitative electrophysiological phenotype, ttth1, on chromosome 7. Multipoint analysis of microsatellite markers using the variance component (VC) method showed the highest LOD score of 4.20 at 162 cM, near D7S509 (163.7 cM). Two-point analysis of SNPs using the VC method yielded the highest LOD score of 3.98 in the Illumina SNP data and 3.45 in the Affymetrix SNP data around 152-153 cM. In family-based single SNP and SNP haplotype LD analysis, we identified seven SNPs associated with ttth1. We searched for any potential candidate genes in the location of the seven SNPs. The SNPs rs1476640 and rs768055 are located in the FLJ40852 gene (a hypothetical protein), and SNP rs1859646 is located in the TAS2R5 gene (a taste receptor). The other four SNPs are not located in any known or annotated genes. We found the high density SNP scan to be superior to microsatellites because it is effective in downstream fine mapping due to a better defined linkage region. Our study proves the utility of high density SNP in genome-wide mapping studies.     

The development and characterization of a 57K single nucleotide polymorphism array for rainbow trout

In this study, we describe the development and characterization of the first high‐density single nucleotide polymorphism (SNP) genotyping array for rainbow trout. The SNP array is publically available from a commercial vendor (Affymetrix). The SNP genotyping quality was high, and validation rate was close to 90%. This is comparable to other farm animals and is much higher than previous smaller scale SNP validation studies in rainbow trout. High quality and integrity of the genotypes are evident from sample reproducibility and from nearly 100% agreement in genotyping results from other methods. The array is very useful for rainbow trout aquaculture populations with more than 40 900 polymorphic markers per population. For wild populations that were confounded by a smaller sample size, the number of polymorphic markers was between 10 577 and 24 330. Comparison between genotypes from individual populations suggests good potential for identifying candidate markers for populations' traceability. Linkage analysis and mapping of the SNPs to the reference genome assembly provide strong evidence for a wide distribution throughout the genome with good representation in all 29 chromosomes. A total of 68% of the genome scaffolds and contigs were anchored through linkage analysis using the SNP array genotypes, including ~20% of the genome assembly that has not been previously anchored to chromosomes.     

An interactional network of genes involved in chitin synthesis in Saccharomyces cerevisiae

Background

The identification of disease-associated genes using single nucleotide polymorphisms (SNPs) has been increasingly reported. In particular, the Affymetrix Mapping 10 K SNP microarray platform uses one PCR primer to amplify the DNA samples and determine the genotype of more than 10,000 SNPs in the human genome. This provides the opportunity for large scale, rapid and cost-effective genotyping assays for linkage analysis. However, the analysis of such datasets is nontrivial because of the large number of markers, and visualizing the linkage scores in the context of genome maps remains less automated using the current linkage analysis software packages. For example, the haplotyping results are commonly represented in the text format.

Results

Here we report the development of a novel software tool called CompareLinkage for automated formatting of the Affymetrix Mapping 10 K genotype data into the "Linkage" format and the subsequent analysis with multi-point linkage software programs such as Merlin and Allegro. The new software has the ability to visualize the results for all these programs in dChip in the context of genome annotations and cytoband information. In addition we implemented a variant of the Lander-Green algorithm in the dChipLinkage module of dChip software (V1.3) to perform parametric linkage analysis and haplotyping of SNP array data. These functions are integrated with the existing modules of dChip to visualize SNP genotype data together with LOD score curves. We have analyzed three families with recessive and dominant diseases using the new software programs and the comparison results are presented and discussed.

Conclusions

The CompareLinkage and dChipLinkage software packages are freely available. They provide the visualization tools for high-density oligonucleotide SNP array data, as well as the automated functions for formatting SNP array data for the linkage analysis programs Merlin and Allegro and calling these programs for linkage analysis. The results can be visualized in dChip in the context of genes and cytobands. In addition, a variant of the Lander-Green algorithm is provided that allows parametric linkage analysis and haplotyping.     

SNP HiTLink: a high-throughput linkage analysis system employing dense SNP data

Background  

During this recent decade, microarray-based single nucleotide polymorphism (SNP) data are becoming more widely used as markers for linkage analysis in the identification of loci for disease-associated genes. Although microarray-based SNP analyses have markedly reduced genotyping time and cost compared with microsatellite-based analyses, applying these enormous data to linkage analysis programs is a time-consuming step, thus, necessitating a high-throughput platform.     

An autosomal recessive nonsyndromic-hearing-loss locus identified by DNA pooling using two inbred Bedouin kindreds.

Autosomal recessive nonsyndromic hearing loss (ARNSHL) is the most common form of severe inherited childhood deafness. We present the linkage analysis of two inbred Bedouin kindreds from Israel that are affected with ARNSHL. A rapid genomewide screen for markers linked to the disease was performed by using pooled DNA samples. This screen revealed evidence for linkage with markers D9S922 and D9S301 on chromosome 9q. Genotyping of individuals from both kindreds confirmed linkage to chromosome 9q and a maximum combined LOD score of 26.2 (recombination fraction [theta] .025) with marker D9S927. The disease locus was mapped to a 1.6-cM region of chromosome 9ql3-q2l, between markers D9S15 and D9S927. The disease segregates with a common haplotype in the two kindreds, at markers D9S927, D9S175, and D9S284 in the linked interval, supporting the hypothesis that both kindreds inherited the deafness gene from a common ancestor. Although this nonsyndromic-hearing-loss (NSHL) locus maps to the same cytogenetic interval as DFNB7, it does not overlap the currently defined DFNB7 interval and may represent (1) a novel form of NSHL in close proximity to DFNB7 or (2) a relocalization of the DFNB7 interval to a region telomeric to its reported location. This study further demonstrates that DNA pooling is an effective means of quickly identifying regions of linkage in inbred families with heterogeneous autosomal recessive disorders.     

Genomewide high-density SNP linkage analysis of 236 Japanese families supports the existence of schizophrenia susceptibility loci on chromosomes 1p, 14q, and 20p

The Japanese Schizophrenia Sib-Pair Linkage Group (JSSLG) is a multisite collaborative study group that was organized to create a national resource for affected sib pair (ASP) studies of schizophrenia in Japan. We used a high-density single-nucleotide–polymorphism (SNP) genotyping assay, the Illumina BeadArray linkage mapping panel (version 4) comprising 5,861 SNPs, to perform a genomewide linkage analysis of JSSLG samples comprising 236 Japanese families with 268 nonindependent ASPs with schizophrenia. All subjects were Japanese. Among these families, 122 families comprised the same subjects analyzed with short tandem repeat markers. All the probands and their siblings, with the exception of seven siblings with schizoaffective disorder, had schizophrenia. After excluding SNPs with high linkage disequilibrium, we found significant evidence of linkage of schizophrenia to chromosome 1p21.2-1p13.2 (LOD=3.39) and suggestive evidence of linkage to 14q11.2 (LOD=2.87), 14q11.2-q13.2 (LOD=2.33), and 20p12.1-p11.2 (LOD=2.33). Although linkage to these regions has received little attention, these regions are included in or partially overlap the 10 regions reported by Lewis et al. that passed the two aggregate criteria of a meta-analysis. Results of the present study—which, to our knowledge, is the first genomewide analysis of schizophrenia in ASPs of a single Asian ethnicity that is comparable to the analyses done of ASPs of European descent—indicate the existence of schizophrenia susceptibility loci that are common to different ethnic groups but that likely have different ethnicity-specific effects.     

A comparison in association and linkage genome-wide scans for alcoholism susceptibility genes using single-nucleotide polymorphisms

We conducted genome-wide linkage scans using both microsatellite and single-nucleotide polymorphism (SNP) markers. Regions showing the strongest evidence of linkage to alcoholism susceptibility genes were identified. Haplotype analyses using a sliding-window approach for SNPs in these regions were performed. In addition, we performed a genome-wide association scan using SNP data. SNPs in these regions with evidence of association (P 相似文献   

Localisation of merosin-positive congenital muscular dystrophy to chromosome 4p16.3

The congenital muscular dystrophies (CMD) are a heterogeneous group of autosomal recessive disorders, which present within the first 6 months of life with hypotonia, muscle weakness and contractures, associated with dystrophic changes on skeletal muscle biopsy. We have previously reported a large consanguineous family segregating merosin-positive congenital muscular dystrophy, in which involvement of known CMD loci was excluded. A genome-wide linkage search of the family conducted using microsatellite markers spaced at 10-Mb intervals failed to identify a disease locus. A second scan using a high-density SNP array, however, permitted a novel CMD locus on 4p16.3 to be identified (multipoint LOD score 3.4). Four additional consanguineous CMD families with a similar phenotype were evaluated for linkage to a 4.14-Mb interval on 4p16.3; however, none showed any evidence of linkage to the region. Our findings further illustrate the utility of highly informative SNP arrays compared with standard panels of microsatellite markers for the mapping of recessive disease loci.     

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.

     

Generalized T2 test for genome association studies

Recent progress in the development of single-nucleotide polymorphism (SNP) maps within genes and across the genome provides a valuable tool for fine-mapping and has led to the suggestion of genomewide association studies to search for susceptibility loci for complex traits. Test statistics for genome association studies that consider a single marker at a time, ignoring the linkage disequilibrium between markers, are inefficient. In this study, we present a generalized T2 statistic for association studies of complex traits, which can utilize multiple SNP markers simultaneously and considers the effects of multiple disease-susceptibility loci. This generalized T2 statistic is a corollary to that originally developed for multivariate analysis and has a close relationship to discriminant analysis and common measure of genetic distance. We evaluate the power of the generalized T2 statistic and show that power to be greater than or equal to those of the traditional chi2 test of association and a similar haplotype-test statistic. Finally, examples are given to evaluate the performance of the proposed T2 statistic for association studies using simulated and real data.     

Development,validation and genetic analysis of a large soybean SNP genotyping array

Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under‐use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high‐density genetic mapping and genome‐wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome‐wide association analyses. More than four million high‐quality SNPs identified from high‐depth genome re‐sequencing of 16 soybean accessions and low‐depth genome re‐sequencing of 31 soybean accessions were used to select 180 961 SNPs for creation of the Axiom^® SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170 223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene‐rich chromosomal regions suggest that this array may be suitable for genome‐wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.     

Whole-genome scan, in a complex disease, using 11,245 single-nucleotide polymorphisms: comparison with microsatellites

Despite the theoretical evidence of the utility of single-nucleotide polymorphisms (SNPs) for linkage analysis, no whole-genome scans of a complex disease have yet been published to directly compare SNPs with microsatellites. Here, we describe a whole-genome screen of 157 families with multiple cases of rheumatoid arthritis (RA), performed using 11,245 genomewide SNPs. The results were compared with those from a 10-cM microsatellite scan in the same cohort. The SNP analysis detected HLA*DRB1, the major RA susceptibility locus (P=.00004), with a linkage interval of 31 cM, compared with a 50-cM linkage interval detected by the microsatellite scan. In addition, four loci were detected at a nominal significance level (P<.05) in the SNP linkage analysis; these were not observed in the microsatellite scan. We demonstrate that variation in information content was the main factor contributing to observed differences in the two scans, with the SNPs providing significantly higher information content than the microsatellites. Reducing the number of SNPs in the marker set to 3,300 (1-cM spacing) caused several loci to drop below nominal significance levels, suggesting that decreases in information content can have significant effects on linkage results. In contrast, differences in maps employed in the analysis, the low detectable rate of genotyping error, and the presence of moderate linkage disequilibrium between markers did not significantly affect the results. We have demonstrated the utility of a dense SNP map for performing linkage analysis in a late-age-at-onset disease, where DNA from parents is not always available. The high SNP density allows loci to be defined more precisely and provides a partial scaffold for association studies, substantially reducing the resource requirement for gene-mapping studies.     

Standard linkage and association methods identify the mechanism of four susceptibility genes for a simulated complex disease

The simulated dataset of the Genetic Analysis Workshop 14 provided affection status and the presence or absence of 12 traits. It was determined that all affected individuals must have traits E, F and H (EFH phenotype) and they must also have either trait B (B subtype) or traits C, D, and G (CDG subtype). A genome screen was performed, and linkage peaks were identified on chromosomes 1, 3, 5, and 9 using microsatellite markers. Dense panels of single-nucleotide polymorphism (SNP) markers were ordered for each of the four linkage peaks. In each case, association analyses identified a single SNP that accounted for the linkage evidence. The SNP on chromosome 1 appeared to primarily influence the B subtype, while the SNPs on chromosomes 5 and 9 primarily influenced the CDG subtype. The chromosome 3 SNP had the strongest effect and influenced both subtypes, as well as the requisite EFH phenotype. Recognizing the two subtypes prior to linkage analysis was key to identifying these loci using only a single replicate. This highlights the need in real life situations for careful examination of the phenotypic data prior to genetic analysis.