BackgroundMost developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations.ResultsWe describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population.ConclusionsWe present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.
Gastrointestinal nematodes are one of the main health issues in sheep breeding. To identify loci affecting the resistance to Haemonchus contortus, a genome scan was carried out using 1,275 Romane × Martinik Black Belly backcross lambs. The entire population was challenged with Haemonchus contortus in 2 consecutive experimental infections, and fecal egg counts (FEC) and packed cell volumes were measured. A subgroup of 332 lambs with extreme FEC was necropsied to determine the total worm burden, length of female worms, sex ratio in the worm population, abomasal pH, and serum and mucosal G immunoglobulins (IgG) responses. Pepsinogen concentration was measured in another subset of 229 lambs. For QTL detection, 160 microsatellite markers were used as well as the Illumina OvineSNP50 BeadChip that provided 42,469 SNP markers after quality control. Linkage, association, and joint linkage and association analyses were performed with the QTLMAP software. Linkage disequilibrium (LD) was estimated within each pure breed, and association analyses were carried out either considering or not the breed origin of the haplotypes. Four QTL regions on sheep chromosomes (OAR)5, 12, 13, and 21 were identified as key players among many other QTL with small to moderate effects. A QTL on OAR21 affecting pepsinogen concentration exactly matched the pepsinogen (PGA5) locus. A 10-Mbp region affecting FEC after the 1st and 2nd infections was found on OAR12. The SNP markers outperformed microsatellites in the linkage analysis. Taking advantage of the LD helped to refine the locations of the QTL mapped on OAR5 and 13.
A genome-wide association study for osteochondrosis (OC) in French Trotter horses was carried out to detect QTL using genotype data from the Illumina EquineSNP50 BeadChip assay. Analysis data came from 161 sire families of French Trotter horses with 525 progeny and family sizes ranging from 1 to 20. Genotypes were available for progeny (n = 525) and sires with at least 2 progeny (n = 98). Radiographic data were obtained from progeny using at least 10 views to reveal OC. All radiographic findings were described by at least 2 veterinary experts in equine orthopedics, and severity indices (scores) were assigned based on the size and location of the lesion. Traits used were a global score, the sum of all severity scores lesions (GM, quantitative measurement), and the presence or absence of OC on the fetlock (FM), hock (HM), and other sites (other). Data were analyzed using 2 mixed models including fixed effects, polygenic effects, and SNP or haplotype cluster effects. By combining results with both methods at moderate evidence of association threshold P < 5 × 10(-5), this genome-wide association study displayed 1 region for GM on the Equus caballus chromosome (ECA) 13, 2 for HM on ECA 3 and 14, and 1 for other on ECA 15. One region on ECA 3 for HM represented the most significant hit (P = 3 × 10(-6)). By comparing QTL between traits at a decreased threshold (P < 5 × 10(-4)), the 4 QTL detected for GM were associated to a QTL detected for FM or HM but never both. Another interesting result was that no QTL were found in common between HM and FM.
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