Limits...
Combining QTL data for HDL cholesterol levels from two different species leads to smaller confidence intervals.

Cox A, Sheehan SM, Klöting I, Paigen B, Korstanje R - Heredity (Edinb) (2010)

Bottom Line: The data are then combined and analyzed; a successful analysis results in a narrowed and more significant QTL.The combinations and analyses resulted in QTL with smaller confidence intervals and increased logarithm of the odds ratio scores.This is the first time that QTL data from different species were successfully combined; this method promises to be a useful tool for narrowing QTL intervals.

View Article: PubMed Central - PubMed

Affiliation: The Jackson Laboratory, Bar Harbor, ME 04609, USA.

ABSTRACT
Quantitative trait locus (QTL) analysis detects regions of a genome that are linked to a complex trait. Once a QTL is detected, the region is narrowed by positional cloning in the hope of determining the underlying candidate gene-methods used include creating congenic strains, comparative genomics and gene expression analysis. Combined cross analysis may also be used for species such as the mouse, if the QTL is detected in multiple crosses. This process involves the recoding of QTL data on a per-chromosome basis, with the genotype recoded on the basis of high- and low-allele status. The data are then combined and analyzed; a successful analysis results in a narrowed and more significant QTL. Using parallel methods, we show that it is possible to narrow a QTL by combining data from two different species, the rat and the mouse. We combined standardized high-density lipoprotein phenotype values and genotype data for the rat and mouse using information from one rat cross and two mouse crosses. We successfully combined data within homologous regions from rat Chr 6 onto mouse Chr 12, and from rat Chr 10 onto mouse Chr 11. The combinations and analyses resulted in QTL with smaller confidence intervals and increased logarithm of the odds ratio scores. The numbers of candidate genes encompassed by the QTL on mouse Chr 11 and 12 were reduced from 1343 to 761 genes and from 613 to 304 genes, respectively. This is the first time that QTL data from different species were successfully combined; this method promises to be a useful tool for narrowing QTL intervals.

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Rat-mouse concordance between cholesterol QTL on two different chromosomes. Genetic maps for rat chromosomes are shown on the left and for mouse chromosomes on the right. Rat markers names are shown in alignment with their genetic positions on the rat genome, and with their homologous positions on the mouse genome. The grey boxes show the original (pre-combination) QTL confidence interval for each species; the black bar represents the QTL peak. The LOD score for each QTL is shown adjacent to the peak. (A) Rat WxDA chr 6 male (most left) and female QTL are aligned with mouse BxD2 Chr 12 QTL. The most proximal rat marker (D6Pas1) is homologous to mouse Chr 17. The remaining markers align to mouse chromosome 12 contiguously. The female rat data was not chosen for this combination as the rat peak positions are not within the rat/mouse overlapping regions. (B) Rat WxDA Chr 10 female QTL is aligned with the mouse PxD2 Chr 11 female QTL. The region immediately surrounding the most distal rat marker, D10Mgh2, is not homologous to the mouse genome; the other markers align to mouse Chr 11 contiguously.
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Figure 2: Rat-mouse concordance between cholesterol QTL on two different chromosomes. Genetic maps for rat chromosomes are shown on the left and for mouse chromosomes on the right. Rat markers names are shown in alignment with their genetic positions on the rat genome, and with their homologous positions on the mouse genome. The grey boxes show the original (pre-combination) QTL confidence interval for each species; the black bar represents the QTL peak. The LOD score for each QTL is shown adjacent to the peak. (A) Rat WxDA chr 6 male (most left) and female QTL are aligned with mouse BxD2 Chr 12 QTL. The most proximal rat marker (D6Pas1) is homologous to mouse Chr 17. The remaining markers align to mouse chromosome 12 contiguously. The female rat data was not chosen for this combination as the rat peak positions are not within the rat/mouse overlapping regions. (B) Rat WxDA Chr 10 female QTL is aligned with the mouse PxD2 Chr 11 female QTL. The region immediately surrounding the most distal rat marker, D10Mgh2, is not homologous to the mouse genome; the other markers align to mouse Chr 11 contiguously.

Mentions: The markers listed for rat Chrs 6 and 10 from the WxDA dataset, along with their rat genetic map positions and mouse genetic map positions on Chrs 12 and 11, are shown in Figure 2. The following rat-mouse QTL HDL data combinations were tested:


Combining QTL data for HDL cholesterol levels from two different species leads to smaller confidence intervals.

Cox A, Sheehan SM, Klöting I, Paigen B, Korstanje R - Heredity (Edinb) (2010)

Rat-mouse concordance between cholesterol QTL on two different chromosomes. Genetic maps for rat chromosomes are shown on the left and for mouse chromosomes on the right. Rat markers names are shown in alignment with their genetic positions on the rat genome, and with their homologous positions on the mouse genome. The grey boxes show the original (pre-combination) QTL confidence interval for each species; the black bar represents the QTL peak. The LOD score for each QTL is shown adjacent to the peak. (A) Rat WxDA chr 6 male (most left) and female QTL are aligned with mouse BxD2 Chr 12 QTL. The most proximal rat marker (D6Pas1) is homologous to mouse Chr 17. The remaining markers align to mouse chromosome 12 contiguously. The female rat data was not chosen for this combination as the rat peak positions are not within the rat/mouse overlapping regions. (B) Rat WxDA Chr 10 female QTL is aligned with the mouse PxD2 Chr 11 female QTL. The region immediately surrounding the most distal rat marker, D10Mgh2, is not homologous to the mouse genome; the other markers align to mouse Chr 11 contiguously.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2958246&req=5

Figure 2: Rat-mouse concordance between cholesterol QTL on two different chromosomes. Genetic maps for rat chromosomes are shown on the left and for mouse chromosomes on the right. Rat markers names are shown in alignment with their genetic positions on the rat genome, and with their homologous positions on the mouse genome. The grey boxes show the original (pre-combination) QTL confidence interval for each species; the black bar represents the QTL peak. The LOD score for each QTL is shown adjacent to the peak. (A) Rat WxDA chr 6 male (most left) and female QTL are aligned with mouse BxD2 Chr 12 QTL. The most proximal rat marker (D6Pas1) is homologous to mouse Chr 17. The remaining markers align to mouse chromosome 12 contiguously. The female rat data was not chosen for this combination as the rat peak positions are not within the rat/mouse overlapping regions. (B) Rat WxDA Chr 10 female QTL is aligned with the mouse PxD2 Chr 11 female QTL. The region immediately surrounding the most distal rat marker, D10Mgh2, is not homologous to the mouse genome; the other markers align to mouse Chr 11 contiguously.
Mentions: The markers listed for rat Chrs 6 and 10 from the WxDA dataset, along with their rat genetic map positions and mouse genetic map positions on Chrs 12 and 11, are shown in Figure 2. The following rat-mouse QTL HDL data combinations were tested:

Bottom Line: The data are then combined and analyzed; a successful analysis results in a narrowed and more significant QTL.The combinations and analyses resulted in QTL with smaller confidence intervals and increased logarithm of the odds ratio scores.This is the first time that QTL data from different species were successfully combined; this method promises to be a useful tool for narrowing QTL intervals.

View Article: PubMed Central - PubMed

Affiliation: The Jackson Laboratory, Bar Harbor, ME 04609, USA.

ABSTRACT
Quantitative trait locus (QTL) analysis detects regions of a genome that are linked to a complex trait. Once a QTL is detected, the region is narrowed by positional cloning in the hope of determining the underlying candidate gene-methods used include creating congenic strains, comparative genomics and gene expression analysis. Combined cross analysis may also be used for species such as the mouse, if the QTL is detected in multiple crosses. This process involves the recoding of QTL data on a per-chromosome basis, with the genotype recoded on the basis of high- and low-allele status. The data are then combined and analyzed; a successful analysis results in a narrowed and more significant QTL. Using parallel methods, we show that it is possible to narrow a QTL by combining data from two different species, the rat and the mouse. We combined standardized high-density lipoprotein phenotype values and genotype data for the rat and mouse using information from one rat cross and two mouse crosses. We successfully combined data within homologous regions from rat Chr 6 onto mouse Chr 12, and from rat Chr 10 onto mouse Chr 11. The combinations and analyses resulted in QTL with smaller confidence intervals and increased logarithm of the odds ratio scores. The numbers of candidate genes encompassed by the QTL on mouse Chr 11 and 12 were reduced from 1343 to 761 genes and from 613 to 304 genes, respectively. This is the first time that QTL data from different species were successfully combined; this method promises to be a useful tool for narrowing QTL intervals.

Show MeSH
Related in: MedlinePlus