A selective genotyping approach identifies QTL in a simulated population

Moioli, B.; Napolitano, F.; Catillo, G.

doi:10.1186/1753-6561-8-s5-s5

Cited by 2 publications

(1 citation statement)

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“…Both methods were applied to single (RF_ST; GRM_ST) and multiple trait (RF_MT; GRM_MT) estimated breeding values, and on yield deviations (RF_YD; GRM_YD). Moioli et al [ 6 ] applied a selective genotyping (SG) technique based on the comparison of the allele frequencies of sliding windows of 5 consecutive SNPs in two groups divergent for production. Grosse-Brinkhaus et al [ 7 ] performed the GWA with the Genome wide rapid association using Mixed Model and Regression (GRAMMAR).…”

Section: Methodsmentioning

confidence: 99%

XVIth QTLMAS: simulated dataset and comparative analysis of submitted results for QTL mapping and genomic evaluation

et al. 2014

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BackgroundA common dataset was simulated and made available to participants of the XVIth QTL-MAS workshop. Tasks for the participants were to detect QTLs affecting three traits, to assess their possible pleiotropic effects, and to evaluate the breeding values in a candidate population without phenotypes using genomic information.MethodsFour generations consisting of 20 males and 1000 females were generated by mating each male with 50 females. The genome consisted of 5 chromosomes, each of 100 Mb size and carrying 2,000 equally distributed SNPs. Three traits were simulated in order to mimic milk yield, fat yield and fat content. Genetic (co)variances were generated from 50 QTLs with pleiotropic effects. Phenotypes for all traits were expressed only in females, and were provided for the first 3 generations. Fourteen methods for detecting single-trait QTL and 3 methods for investigating their pleiotropic nature were proposed. QTL mapping results were compared according to the following criteria: number of true QTL detected; number of false positives; and the proportion of the true genetic variance explained by submitted positions. Eleven methods for estimating direct genomic values of the candidate population were proposed. Accuracies and bias of predictions were assessed by comparing estimated direct genomic values with true breeding values.ResultsThe number of true detections ranged from 0 to 8 across methods and traits, false positives from 0 to 15, and the proportion of genetic variance captured from 0 to 0.82, respectively. The accuracy and bias of genomic predictions varied from 0.74 to 0.85 and from 0.86 to 1.34 across traits and methods, respectively.ConclusionsThe best results in terms of detection power were obtained by ridge regression that, however, led to a large number of false positives. Good results both in terms of true detections and false positives were obtained by the approaches that fit polygenic effects in the model. The investigation of the pleiotropic nature of the QTL permitted the identification of few additional markers compared to the single-trait analyses. Bayesian and grouped regularized regression methods performed similarly for genomic prediction while GBLUP produced the poorest results.

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Section: Methodsmentioning

confidence: 99%

XVIth QTLMAS: simulated dataset and comparative analysis of submitted results for QTL mapping and genomic evaluation

et al. 2014

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Association of SNPs in dopamine and serotonin pathway genes and their interacting genes with temperament traits in Charolais cows

et al. 2016

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Cattle temperament is a complex trait, and molecular studies aimed at defining this trait are scarce. We used an interaction networks approach to identify new genes (interacting genes) and to estimate their effects and those of 19 dopamine- and serotonin-related genes on the temperament traits of Charolais cattle. The genes proopiomelanocortin (POMC), neuropeptide Y (NPY), solute carrier family 18, member 2 (SLC18A2) and FBJ murine osteosarcoma viral oncogene homologue (FOSFBJ) were identified as new candidates. Their potential to be associated with temperament was estimated according to their reported biological activities, which included interactions with neural activity, receptor function, targeting or synthesis of neurotransmitters and association with behaviour. Pen score (PS) and exit velocity (EV) measures were determined from 412 Charolais cows to calculate their temperament score (TS). Based on the TS, calm (n = 55; TS, 1.09 ± 0.33) and temperamental (n = 58; TS, 2.27 ± 0.639) cows were selected and genotyped using a 248 single-nucleotide variation (SNV) panel. Of the 248 variations in the panel, only 151 were confirmed to be polymorphic (single-nucleotide polymorphisms; SNPs) in the tested population. Single-marker association analyses between genotypes and temperament measures (EV, PS and/or TS) indicated significant associations of six SNPs from four candidate genes. The markers rs109576799 and rs43696138, located in the DRD3 and HTR2A genes, respectively, were significantly associated with both EV and TS traits. Four markers, rs110365063 and rs137756569 from the POMC gene and rs110365063 and rs135155082 located in SLC18A2 and DRD2, respectively, were associated with PS. The variant rs110365063 located in bovine SLC18A2 causes a change in the amino acid sequence from Ala to Thr. Further studies are needed to confirm the association of genetic profile with cattle temperament; however, our study represents important progress in understanding the regulation of cattle temperament by different genes with divergent functions.

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A selective genotyping approach identifies QTL in a simulated population

Cited by 2 publications

References 16 publications

XVIth QTLMAS: simulated dataset and comparative analysis of submitted results for QTL mapping and genomic evaluation

XVIth QTLMAS: simulated dataset and comparative analysis of submitted results for QTL mapping and genomic evaluation

Association of SNPs in dopamine and serotonin pathway genes and their interacting genes with temperament traits in Charolais cows

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