Dataset Information

Heritability and demographic analyses in the large isolated population of Val Borbera suggest advantages in mapping complex traits genes.

ABSTRACT:

Background

Isolated populations are a useful resource for mapping complex traits due to shared stable environment, reduced genetic complexity and extended Linkage Disequilibrium (LD) compared to the general population. Here we describe a large genetic isolate from the North West Apennines, the mountain range that runs through Italy from the North West Alps to the South.

Methodology/principal findings

The study involved 1,803 people living in 7 villages of the upper Borbera Valley. For this large population cohort, data from genealogy reconstruction, medical questionnaires, blood, anthropometric and bone status QUS parameters were evaluated. Demographic and epidemiological analyses indicated a substantial genetic component contributing to each trait variation as well as overlapping genetic determinants and family clustering for some traits.

Conclusions/significance

The data provide evidence for significant heritability of medical relevant traits that will be important in mapping quantitative traits. We suggest that this population isolate is suitable to identify rare variants associated with complex phenotypes that may be difficult to study in larger but more heterogeneous populations.

SUBMITTER: Traglia M

PROVIDER: S-EPMC2761731 | biostudies-literature | 2009 Oct

REPOSITORIES: biostudies-literature

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Publications

Heritability and demographic analyses in the large isolated population of Val Borbera suggest advantages in mapping complex traits genes.

Traglia Michela M Sala Cinzia C Masciullo Corrado C Cverhova Valeria V Lori Francesca F Lori Francesca F Pistis Giorgio G Bione Silvia S Gasparini Paolo P Ulivi Sheila S Ciullo Marina M Nutile Teresa T Bosi Emanuele E Sirtori Marcella M Mignogna Giovanna G Rubinacci Alessandro A Buetti Iwan I Camaschella Clara C Petretto Enrico E Toniolo Daniela D

PloS one 20091022 10

<h4>Background</h4>Isolated populations are a useful resource for mapping complex traits due to shared stable environment, reduced genetic complexity and extended Linkage Disequilibrium (LD) compared to the general population. Here we describe a large genetic isolate from the North West Apennines, the mountain range that runs through Italy from the North West Alps to the South.<h4>Methodology/principal findings</h4>The study involved 1,803 people living in 7 villages of the upper Borbera Valley. ...[more]

PMID: 19847309

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Project description:BackgroundGenome-wide association studies can have limited power to identify QTL, partly due to the stringent correction for multiple testing and low linkage-disequilibrium between SNPs and QTL. Regional Heritability Mapping (RHM) has been advanced as an alternative approach to capture underlying genetic effects. In this study, RHM was used to identify loci underlying variation in the 16(th) QTLMAS workshop simulated traits.MethodsThe method was implemented by fitting a mixed model where a genomic region and the overall genetic background were added as random effects. Heritabilities for the genetic regional effects were estimated, and the presence of a QTL in the region was tested using a likelihood ratio test (LRT). Several region sizes were considered (100, 50 and 20 adjacent SNPs). Bonferroni correction was used to calculate the LRT thresholds for genome-wide (p < 0.05) and suggestive (i.e., one false positive per genome scan) significance.ResultsGenomic heritabilities (0.31, 0.32 and 0.48, respectively) and genetic correlations (0.80, -0.42 and 0.19, between trait-pairs 1&2, 1&3 and 2&3) were similar to the simulated ones. RHM identified 7 QTL (4 at genome-wide and 3 at suggestive level) for Trait1; 4 (2 genome-wide and 2 suggestive) for Trait2; and 7 (6 genome-wide and 1 suggestive) for Trait3. Only one of the identified suggestive QTL was a false-positive. The position of these QTL tended to coincide with the position where the largest QTL (or several of them) were simulated. Several signals were detected for the simulated QTL with smaller effect. A combined analysis including all significant regions showed that they explain more than half of the total genetic variance of the traits. However, this might be overestimated, due to Beavis effect. All QTL affecting traits 1&2 and 2&3 had positive correlations, following the trend of the overall correlation of both trait-pairs. All but one QTL affecting traits 1&3 were negatively correlated, in agreement with the simulated situation. Moreover, RHM identified extra loci that were not found by association and linkage analysis, highlighting the improved power of this approach.ConclusionsRHM identified the largest QTL among the simulated ones, with some signals for the ones with small effect. Moreover, RHM performed better than association and linkage analysis, in terms of both power and resolution.

Dataset Information

Heritability and demographic analyses in the large isolated population of Val Borbera suggest advantages in mapping complex traits genes.

Background

Methodology/principal findings

Conclusions/significance

Publications

Heritability and demographic analyses in the large isolated population of Val Borbera suggest advantages in mapping complex traits genes.

Similar Datasets

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