Limits...
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.

Show MeSH

Related in: MedlinePlus

Physical Location of the Shared Regions.The regions that are shared between the five affected individuals are depicted in red. All regions that were identified as ambiguous by the SNP method are shown in grey, along with the any corresponding ambiguous regions identified by the STRP markers. The physical locations of the regions' boundaries were determined by UCSC Genome Browser and approximate positions are shown by each region in Mb. The * indicates the chromosome 13 STRP marker gata73A05, which defines the haploid shared region, is at 62.5 Mb and is not shared by the SNPs at this location. The ‡ symbol denotes an inconsistency between the two methods for the shared region on chromosome 15. While the SNP method identified a shared region, the haploid method identified an ambiguous region with a probability of 1/1000 and was therefore ruled out.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2682655&req=5

pone-0005687-g006: Physical Location of the Shared Regions.The regions that are shared between the five affected individuals are depicted in red. All regions that were identified as ambiguous by the SNP method are shown in grey, along with the any corresponding ambiguous regions identified by the STRP markers. The physical locations of the regions' boundaries were determined by UCSC Genome Browser and approximate positions are shown by each region in Mb. The * indicates the chromosome 13 STRP marker gata73A05, which defines the haploid shared region, is at 62.5 Mb and is not shared by the SNPs at this location. The ‡ symbol denotes an inconsistency between the two methods for the shared region on chromosome 15. While the SNP method identified a shared region, the haploid method identified an ambiguous region with a probability of 1/1000 and was therefore ruled out.

Mentions: Haplotypes determined from the SNP analysis were examined and regions shared between all five affected individuals were then defined across the entire genome. The SNP method identified a total of 10 shared regions (red), eight of which were detected using the haploid mapping approach and an additional 2 regions that were not previously identified (Figure 6, Table 1). The haploid method was unable to detect the shared region on chromosome 15 because this small interval is located between two STRP markers and on chromosome 16 because two corresponding STRP markers were not informative. Conversely, the SNP method did not detect the shared region on chromosome 13 or the telomeric shared region on chromosome 16 that were identified by the haploid STRP method. A significant advantage of the SNP approach was that each of the shared regions identified were significantly refined and the maximal regions were much smaller than those defined by the haploid STRP approach. Furthermore, the SNP method eliminated nearly all of the ambiguous regions detected by the STRP markers and only detected an additional four new ambiguous regions; the high density of SNP markers significantly cleaned up the data and removed nearly all ambiguity. Nearing the theoretical value of 3%, these methods show that approximately 4.7% (142 megabase pairs (Mb)) of the genome is shared among the five affected individuals. Table 1 lists the shared regions identified by the two methods and the ambiguous regions detected by the SNPs, along with the markers and physical positions of the boundaries for each region.


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)

Physical Location of the Shared Regions.The regions that are shared between the five affected individuals are depicted in red. All regions that were identified as ambiguous by the SNP method are shown in grey, along with the any corresponding ambiguous regions identified by the STRP markers. The physical locations of the regions' boundaries were determined by UCSC Genome Browser and approximate positions are shown by each region in Mb. The * indicates the chromosome 13 STRP marker gata73A05, which defines the haploid shared region, is at 62.5 Mb and is not shared by the SNPs at this location. The ‡ symbol denotes an inconsistency between the two methods for the shared region on chromosome 15. While the SNP method identified a shared region, the haploid method identified an ambiguous region with a probability of 1/1000 and was therefore ruled out.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0005687-g006: Physical Location of the Shared Regions.The regions that are shared between the five affected individuals are depicted in red. All regions that were identified as ambiguous by the SNP method are shown in grey, along with the any corresponding ambiguous regions identified by the STRP markers. The physical locations of the regions' boundaries were determined by UCSC Genome Browser and approximate positions are shown by each region in Mb. The * indicates the chromosome 13 STRP marker gata73A05, which defines the haploid shared region, is at 62.5 Mb and is not shared by the SNPs at this location. The ‡ symbol denotes an inconsistency between the two methods for the shared region on chromosome 15. While the SNP method identified a shared region, the haploid method identified an ambiguous region with a probability of 1/1000 and was therefore ruled out.
Mentions: Haplotypes determined from the SNP analysis were examined and regions shared between all five affected individuals were then defined across the entire genome. The SNP method identified a total of 10 shared regions (red), eight of which were detected using the haploid mapping approach and an additional 2 regions that were not previously identified (Figure 6, Table 1). The haploid method was unable to detect the shared region on chromosome 15 because this small interval is located between two STRP markers and on chromosome 16 because two corresponding STRP markers were not informative. Conversely, the SNP method did not detect the shared region on chromosome 13 or the telomeric shared region on chromosome 16 that were identified by the haploid STRP method. A significant advantage of the SNP approach was that each of the shared regions identified were significantly refined and the maximal regions were much smaller than those defined by the haploid STRP approach. Furthermore, the SNP method eliminated nearly all of the ambiguous regions detected by the STRP markers and only detected an additional four new ambiguous regions; the high density of SNP markers significantly cleaned up the data and removed nearly all ambiguity. Nearing the theoretical value of 3%, these methods show that approximately 4.7% (142 megabase pairs (Mb)) of the genome is shared among the five affected individuals. Table 1 lists the shared regions identified by the two methods and the ambiguous regions detected by the SNPs, along with the markers and physical positions of the boundaries for each region.

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