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Genomic correlates of relationship QTL involved in fore- versus hind limb divergence in mice.

Pavlicev M, Wagner GP, Noonan JP, Hallgrímsson B, Cheverud JM - Genome Biol Evol (2013)

Bottom Line: Using the known polymorphisms (single nucleotide polymorphisms [SNPs]) between the parental strains, we characterized and compared the genomic regions in which the rQTL, as well as their interaction partners (intQTL), reside.This result is consistent with the widely accepted view that protein-coding mutations have broader pleiotropic effects than cis-regulatory polymorphisms.This is the first study to systematically document the population-level molecular variation underlying the evolution of character individuation.

View Article: PubMed Central - PubMed

Affiliation: Konrad Lorenz Institute for Evolution and Cognition Research, Altenberg, Austria.

ABSTRACT
Divergence of serially homologous elements of organisms is a common evolutionary pattern contributing to increased phenotypic complexity. Here, we study the genomic intervals affecting the variational independence of fore- and hind limb traits within an experimental mouse population. We use an advanced intercross of inbred mouse strains to map the loci associated with the degree of autonomy between fore- and hind limb long bone lengths (loci affecting the relationship between traits, relationship quantitative trait loci [rQTL]). These loci have been proposed to interact locally with the products of pleiotropic genes, thereby freeing the local trait from the variational constraint due to pleiotropic mutations. Using the known polymorphisms (single nucleotide polymorphisms [SNPs]) between the parental strains, we characterized and compared the genomic regions in which the rQTL, as well as their interaction partners (intQTL), reside. We find that these two classes of QTL intervals harbor different kinds of molecular variation. SNPs in rQTL intervals more frequently reside in limb-specific cis-regulatory regions than SNPs in intQTL intervals. The intQTL loci modified by the rQTL, in contrast, show the signature of protein-coding variation. This result is consistent with the widely accepted view that protein-coding mutations have broader pleiotropic effects than cis-regulatory polymorphisms. For both types of QTL intervals, the underlying candidate genes are enriched for genes involved in protein binding. This finding suggests that rQTL effects are caused by local interactions among the products of the causal genes harbored in rQTL and intQTL intervals. This is the first study to systematically document the population-level molecular variation underlying the evolution of character individuation.

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SNP densities in rQTL and intQTL. (A) The density of SNPs in subregions, in rQTL and intQTL. Note the low density of SNPs in rQTL nonsynonymous exonic sites, despite a general trend toward higher SNP densities in rQTL. (B) The Pearson correlation between SNP densities within and across interaction partners. Within-QTL type correlations are in the upper left for intQTL and lower right for rQTL and are higher than the correlations between the corresponding interacting loci. All within-intQTL correlations with nonsynonymous SNP density and all within-intQTL correlations with intronic SNP density are low. This implies a divergence of SNP pattern in rQTL introns and intQTL exons (r.: rQTL, int.: intQTL, s.exon: synonymous sites, ns.exon: nonsynonymous sites, sign: significant at the 95% confidence level).
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evt144-F3: SNP densities in rQTL and intQTL. (A) The density of SNPs in subregions, in rQTL and intQTL. Note the low density of SNPs in rQTL nonsynonymous exonic sites, despite a general trend toward higher SNP densities in rQTL. (B) The Pearson correlation between SNP densities within and across interaction partners. Within-QTL type correlations are in the upper left for intQTL and lower right for rQTL and are higher than the correlations between the corresponding interacting loci. All within-intQTL correlations with nonsynonymous SNP density and all within-intQTL correlations with intronic SNP density are low. This implies a divergence of SNP pattern in rQTL introns and intQTL exons (r.: rQTL, int.: intQTL, s.exon: synonymous sites, ns.exon: nonsynonymous sites, sign: significant at the 95% confidence level).

Mentions: To understand whether SNP densities vary consistently across all subregions of the intervals, we tested correlations of SNP densities between the subregions (e.g., exons, introns, and UTRs) within and between the two sets of loci (fig. 3B). If a subregion is related to the function of a QTL type, for example, rQTL, we expect that its SNP density will not follow the overall variation of SNP densities across the other subregions. For rQTL, the SNP densities are highly positively correlated across most subregions, i.e., loci either have high or low SNP densities across all subregions. The exceptions are intronic regions, with lower or no correlation with other regions. This is different in intQTL, where the correlations between the SNP densities in most regions are also uniformly high, the clear exception being the exonic nonsynonymous positions. These are uncorrelated with SNP densities in all other subregions (fig. 3B).


Genomic correlates of relationship QTL involved in fore- versus hind limb divergence in mice.

Pavlicev M, Wagner GP, Noonan JP, Hallgrímsson B, Cheverud JM - Genome Biol Evol (2013)

SNP densities in rQTL and intQTL. (A) The density of SNPs in subregions, in rQTL and intQTL. Note the low density of SNPs in rQTL nonsynonymous exonic sites, despite a general trend toward higher SNP densities in rQTL. (B) The Pearson correlation between SNP densities within and across interaction partners. Within-QTL type correlations are in the upper left for intQTL and lower right for rQTL and are higher than the correlations between the corresponding interacting loci. All within-intQTL correlations with nonsynonymous SNP density and all within-intQTL correlations with intronic SNP density are low. This implies a divergence of SNP pattern in rQTL introns and intQTL exons (r.: rQTL, int.: intQTL, s.exon: synonymous sites, ns.exon: nonsynonymous sites, sign: significant at the 95% confidence level).
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3814202&req=5

evt144-F3: SNP densities in rQTL and intQTL. (A) The density of SNPs in subregions, in rQTL and intQTL. Note the low density of SNPs in rQTL nonsynonymous exonic sites, despite a general trend toward higher SNP densities in rQTL. (B) The Pearson correlation between SNP densities within and across interaction partners. Within-QTL type correlations are in the upper left for intQTL and lower right for rQTL and are higher than the correlations between the corresponding interacting loci. All within-intQTL correlations with nonsynonymous SNP density and all within-intQTL correlations with intronic SNP density are low. This implies a divergence of SNP pattern in rQTL introns and intQTL exons (r.: rQTL, int.: intQTL, s.exon: synonymous sites, ns.exon: nonsynonymous sites, sign: significant at the 95% confidence level).
Mentions: To understand whether SNP densities vary consistently across all subregions of the intervals, we tested correlations of SNP densities between the subregions (e.g., exons, introns, and UTRs) within and between the two sets of loci (fig. 3B). If a subregion is related to the function of a QTL type, for example, rQTL, we expect that its SNP density will not follow the overall variation of SNP densities across the other subregions. For rQTL, the SNP densities are highly positively correlated across most subregions, i.e., loci either have high or low SNP densities across all subregions. The exceptions are intronic regions, with lower or no correlation with other regions. This is different in intQTL, where the correlations between the SNP densities in most regions are also uniformly high, the clear exception being the exonic nonsynonymous positions. These are uncorrelated with SNP densities in all other subregions (fig. 3B).

Bottom Line: Using the known polymorphisms (single nucleotide polymorphisms [SNPs]) between the parental strains, we characterized and compared the genomic regions in which the rQTL, as well as their interaction partners (intQTL), reside.This result is consistent with the widely accepted view that protein-coding mutations have broader pleiotropic effects than cis-regulatory polymorphisms.This is the first study to systematically document the population-level molecular variation underlying the evolution of character individuation.

View Article: PubMed Central - PubMed

Affiliation: Konrad Lorenz Institute for Evolution and Cognition Research, Altenberg, Austria.

ABSTRACT
Divergence of serially homologous elements of organisms is a common evolutionary pattern contributing to increased phenotypic complexity. Here, we study the genomic intervals affecting the variational independence of fore- and hind limb traits within an experimental mouse population. We use an advanced intercross of inbred mouse strains to map the loci associated with the degree of autonomy between fore- and hind limb long bone lengths (loci affecting the relationship between traits, relationship quantitative trait loci [rQTL]). These loci have been proposed to interact locally with the products of pleiotropic genes, thereby freeing the local trait from the variational constraint due to pleiotropic mutations. Using the known polymorphisms (single nucleotide polymorphisms [SNPs]) between the parental strains, we characterized and compared the genomic regions in which the rQTL, as well as their interaction partners (intQTL), reside. We find that these two classes of QTL intervals harbor different kinds of molecular variation. SNPs in rQTL intervals more frequently reside in limb-specific cis-regulatory regions than SNPs in intQTL intervals. The intQTL loci modified by the rQTL, in contrast, show the signature of protein-coding variation. This result is consistent with the widely accepted view that protein-coding mutations have broader pleiotropic effects than cis-regulatory polymorphisms. For both types of QTL intervals, the underlying candidate genes are enriched for genes involved in protein binding. This finding suggests that rQTL effects are caused by local interactions among the products of the causal genes harbored in rQTL and intQTL intervals. This is the first study to systematically document the population-level molecular variation underlying the evolution of character individuation.

Show MeSH
Related in: MedlinePlus