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SNP haplotype mapping in a small ALS family.

Krueger KA, Tsuji S, Fukuda Y, Takahashi Y, Goto J, Mitsui J, Ishiura H, Dalton JC, Miller MB, Day JW, Ranum LP - PLoS ONE (2009)

Bottom Line: The identification of genes for monogenic disorders has proven to be highly effective for understanding disease mechanisms, pathways and gene function in humans.New tools and approaches are needed to allow researchers to effectively tap into this genetic gold-mine.Our study illustrates how genetic information can be maximized using readily available tools as a first step in mapping single-gene disorders in small families.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, University of Minnesota, Minneapolis, Minnesota, United States of America.

ABSTRACT
The identification of genes for monogenic disorders has proven to be highly effective for understanding disease mechanisms, pathways and gene function in humans. Nevertheless, while thousands of Mendelian disorders have not yet been mapped there has been a trend away from studying single-gene disorders. In part, this is due to the fact that many of the remaining single-gene families are not large enough to map the disease locus to a single site in the genome. New tools and approaches are needed to allow researchers to effectively tap into this genetic gold-mine. Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density single nucleotide polymorphism (SNP) arrays to define genome-wide haplotypes and candidate regions, using a small amyotrophic lateral sclerosis (ALS) family as a prototype. Specifically, we used haploid-cell lines to determine if high-density SNP arrays accurately predict haplotypes across entire chromosomes and show that haplotype information significantly enhances the genetic information in small families. Panels of haploid-cell lines were generated and a 5 centimorgan (cM) short tandem repeat polymorphism (STRP) genome scan was performed. Experimentally derived haplotypes for entire chromosomes were used to directly identify regions of the genome identical-by-descent in 5 affected individuals. Comparisons between experimentally determined and in silico haplotypes predicted from SNP arrays demonstrate that SNP analysis of diploid DNA accurately predicted chromosomal haplotypes. These methods precisely identified 12 candidate intervals, which are shared by all 5 affected individuals. Our study illustrates how genetic information can be maximized using readily available tools as a first step in mapping single-gene disorders in small families.

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Chromosome 1 Comparison of Excluded, Shared or Ambiguous Regions for Haploid Mapping vs. Multipoint Linkage Analysis.Comparison of information obtained from haploid mapping (A) and multipoint linkage analysis of diploid DNA (B) for chromosome 1. Summaries of the LOD scores are presented in B1 and graphs of the actual LOD scores are illustrated in B2. Regions excluded by haploid mapping or multipoint linkage analysis (LOD<−2.0) are white and ambiguous regions are grey (LOD scores between −2 and +3). Shared regions defined as identical by descent through haploid mapping or with a LOD score >3.0 are shown in red.
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pone-0005687-g003: Chromosome 1 Comparison of Excluded, Shared or Ambiguous Regions for Haploid Mapping vs. Multipoint Linkage Analysis.Comparison of information obtained from haploid mapping (A) and multipoint linkage analysis of diploid DNA (B) for chromosome 1. Summaries of the LOD scores are presented in B1 and graphs of the actual LOD scores are illustrated in B2. Regions excluded by haploid mapping or multipoint linkage analysis (LOD<−2.0) are white and ambiguous regions are grey (LOD scores between −2 and +3). Shared regions defined as identical by descent through haploid mapping or with a LOD score >3.0 are shown in red.

Mentions: Figures 3 and 4 show a comparison of the effectiveness of multipoint linkage using STRP markers and haploid mapping to define shared or excluded regions for chromosome 1 and across the entire genome, respectively. Specifically, three positive LOD scores were generated for chromosome 1, which correspond to a shared region (LOD = 0.785) and two regions known to be excluded by haplotype analysis (LOD = 0.557 & 0.76) (Figure 3). This comparison illustrates the problems investigators face when using small families for linkage analysis —shared and excluded regions are not accurately defined and candidate regions are not always easily distinguished. Genome-wide, haploid mapping identified 10 regions (7.4% of the genome) identical by descent or shared among the 5 affected individuals and definitively excluded 83.1% of the genome as unshared (Figure 4). In contrast, traditional multipoint LOD score analysis using STRP markers on diploid DNA excluded only 67.1% (LOD<−2), failed to identify any shared regions (LOD>3), and generated suggestive scores (most between 0.5–1.2) for regions that were both shared and definitively excluded by haploid analysis. In addition to the shared regions, haploid mapping identified 24 ambiguous regions (indicated in grey), which most likely result from an uninformative marker. The use of haploid cell lines increased the amount of the genome that could be excluded (83%) in comparison to the traditional multipoint linkage analysis (67%) and more closely approximated defining the theoretical portion of the genome that should be shared or identical by descent among the affected individuals (7.4% by haploid analysis vs. 3.0% theoretical).


SNP haplotype mapping in a small ALS family.

Krueger KA, Tsuji S, Fukuda Y, Takahashi Y, Goto J, Mitsui J, Ishiura H, Dalton JC, Miller MB, Day JW, Ranum LP - PLoS ONE (2009)

Chromosome 1 Comparison of Excluded, Shared or Ambiguous Regions for Haploid Mapping vs. Multipoint Linkage Analysis.Comparison of information obtained from haploid mapping (A) and multipoint linkage analysis of diploid DNA (B) for chromosome 1. Summaries of the LOD scores are presented in B1 and graphs of the actual LOD scores are illustrated in B2. Regions excluded by haploid mapping or multipoint linkage analysis (LOD<−2.0) are white and ambiguous regions are grey (LOD scores between −2 and +3). Shared regions defined as identical by descent through haploid mapping or with a LOD score >3.0 are shown in red.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2682655&req=5

pone-0005687-g003: Chromosome 1 Comparison of Excluded, Shared or Ambiguous Regions for Haploid Mapping vs. Multipoint Linkage Analysis.Comparison of information obtained from haploid mapping (A) and multipoint linkage analysis of diploid DNA (B) for chromosome 1. Summaries of the LOD scores are presented in B1 and graphs of the actual LOD scores are illustrated in B2. Regions excluded by haploid mapping or multipoint linkage analysis (LOD<−2.0) are white and ambiguous regions are grey (LOD scores between −2 and +3). Shared regions defined as identical by descent through haploid mapping or with a LOD score >3.0 are shown in red.
Mentions: Figures 3 and 4 show a comparison of the effectiveness of multipoint linkage using STRP markers and haploid mapping to define shared or excluded regions for chromosome 1 and across the entire genome, respectively. Specifically, three positive LOD scores were generated for chromosome 1, which correspond to a shared region (LOD = 0.785) and two regions known to be excluded by haplotype analysis (LOD = 0.557 & 0.76) (Figure 3). This comparison illustrates the problems investigators face when using small families for linkage analysis —shared and excluded regions are not accurately defined and candidate regions are not always easily distinguished. Genome-wide, haploid mapping identified 10 regions (7.4% of the genome) identical by descent or shared among the 5 affected individuals and definitively excluded 83.1% of the genome as unshared (Figure 4). In contrast, traditional multipoint LOD score analysis using STRP markers on diploid DNA excluded only 67.1% (LOD<−2), failed to identify any shared regions (LOD>3), and generated suggestive scores (most between 0.5–1.2) for regions that were both shared and definitively excluded by haploid analysis. In addition to the shared regions, haploid mapping identified 24 ambiguous regions (indicated in grey), which most likely result from an uninformative marker. The use of haploid cell lines increased the amount of the genome that could be excluded (83%) in comparison to the traditional multipoint linkage analysis (67%) and more closely approximated defining the theoretical portion of the genome that should be shared or identical by descent among the affected individuals (7.4% by haploid analysis vs. 3.0% theoretical).

Bottom Line: The identification of genes for monogenic disorders has proven to be highly effective for understanding disease mechanisms, pathways and gene function in humans.New tools and approaches are needed to allow researchers to effectively tap into this genetic gold-mine.Our study illustrates how genetic information can be maximized using readily available tools as a first step in mapping single-gene disorders in small families.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, University of Minnesota, Minneapolis, Minnesota, United States of America.

ABSTRACT
The identification of genes for monogenic disorders has proven to be highly effective for understanding disease mechanisms, pathways and gene function in humans. Nevertheless, while thousands of Mendelian disorders have not yet been mapped there has been a trend away from studying single-gene disorders. In part, this is due to the fact that many of the remaining single-gene families are not large enough to map the disease locus to a single site in the genome. New tools and approaches are needed to allow researchers to effectively tap into this genetic gold-mine. Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density single nucleotide polymorphism (SNP) arrays to define genome-wide haplotypes and candidate regions, using a small amyotrophic lateral sclerosis (ALS) family as a prototype. Specifically, we used haploid-cell lines to determine if high-density SNP arrays accurately predict haplotypes across entire chromosomes and show that haplotype information significantly enhances the genetic information in small families. Panels of haploid-cell lines were generated and a 5 centimorgan (cM) short tandem repeat polymorphism (STRP) genome scan was performed. Experimentally derived haplotypes for entire chromosomes were used to directly identify regions of the genome identical-by-descent in 5 affected individuals. Comparisons between experimentally determined and in silico haplotypes predicted from SNP arrays demonstrate that SNP analysis of diploid DNA accurately predicted chromosomal haplotypes. These methods precisely identified 12 candidate intervals, which are shared by all 5 affected individuals. Our study illustrates how genetic information can be maximized using readily available tools as a first step in mapping single-gene disorders in small families.

Show MeSH
Related in: MedlinePlus