Biomedical subjects

Hélène Gilbert

Publications and source records attributed to Hélène Gilbert.

3 recordsLinked to original sources

PubMed2007

Detection of novel quantitative trait loci for cutaneous melanoma by genome-wide scan in the MeLiM swine model.

Human cutaneous melanoma is a complex trait inherited in about 10% of cases. Although 2 high-risk genes, CDKN2A and CDK4, and 1 low risk gene, MC1R, have been identified, susceptibility genes remain to be discovered. Here, we attempted to determine new genomic regions linked to melanoma using the pig MeLiM strain, which develops hereditary cutaneous melanomas. We applied quantitative trait loci (QTL) mapping method to a significant genome-wide scan performed on 331 backcross pigs derived from this strain. QTLs were detected at chromosome-wide level for a melanoma synthetic trait corresponding to the development of melanoma. The peak positions on Sus scrofa chromosomes (SSC) were at 49.4 and 88.0 cM (SSC1), 56.0 cM (SSC13), 86.5 cM (SSC15) and 39.8 cM (SSC17), and, on SSC2, at 16.9 cM, in families derived from F1 males only (p < 0.05, except for SSC13, p < 0.01). Analysis of 7 precise specific traits revealed highly significant QTLs on SSC10 (ulceration), on SSC12 (presence of melanoma at birth), on SSC13 (lesion type), and on SSC16 and SSC17 (number of aggressive melanomas) at the respective positions 42.0, 95.6, 81.0, 45.3 and 44.8 cM (p < 0.001 and p < 0.05 respectively at the chromosome- and genome-wide levels). We also showed that MeLiM MC1R*2 allele, which determines black coat colour in pigs, predisposes significantly to melanoma. Interactions were observed between MC1R and markers located on SSC1 (p < 0.05). Taken together, these results indicate that MeLiM swine is a model for human multigenic diseases. Comparative mapping revealed human regions of interest to search for new melanoma susceptibility candidates.

Alleles↗

PubMedDate not supplied

Comparison of three multitrait methods for QTL detection.

A comparison of power and accuracy of estimation of position and QTL effects of three multitrait methods and one single trait method for QTL detection was carried out on simulated data, taking into account the mixture of full and half-sib families. One multitrait method was based on a multivariate function as the penetrance function (MV). The two other multitrait methods were based on univariate analysis of linear combination(s) (LC) of the traits. One was obtained by a principal component analysis (PCA) performed on the phenotypic data. The second was based on a discriminate analysis (DA). It calculates a LC of the traits at each position, maximising the ratio between the genetic and the residual variabilities due to the putative QTL. Due to its number of parameters, MV was less powerful and accurate than the other methods. In general, DA better detected QTL, but it had lower accuracy for the QTL effect estimation when the detection power was low, due to higher bias than the other methods. In this case, PCA was better. Otherwise, PCA was slightly less powerful and accurate than DA. Compared to the single trait method, power can be improved by 30% to 100% with multitrait methods.

Computer Simulation↗

PubMedDate not supplied

Power of three multitrait methods for QTL detection in crossbred populations.

The multitrait detections of QTL applied to a mixture of full- and half-sib families require specific strategies. Indeed, the number of parameters estimated by the multivariate methods is excessive compared with the size of the population. Thus, only multitrait methods based on a univariate analysis of a linear combination (LC) of the traits can be extensively performed. We compared three strategies to obtain the LC of the traits. Two linear transformations were performed on the overall population. The last one was performed within each half-sib family. Their powers were compared on simulated data depending on the frequency of the two QTL alleles in each of the grand parental populations of an intercross design. The transformations from the whole population did not lead to a large loss of power even though the frequency of the QTL alleles was similar in the two grand parental populations. In these cases, applying the within-sire family transformation improved the detection when the number of progeny per sire was greater than 100.

Animals↗