Stature is affected by many polymorphisms of small effect in humans . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.

Residual feed intake (RFI) is defined as the difference between the observed ADFI and the ADFI predicted from production and maintenance requirements. The objectives of this study were to evaluate RFI as a selection criterion to improve feed efficiency and its potential to reduce N and P excretion in 4 pig breeds. Data were collected between 2000 and 2009 in French central test stations for 2 dam breeds [French Landrace (LR) and Large White (LWD)], and 2 sire breeds [Large White (LWS) and Piétrain (PP)]. Numbers of recorded pigs were 6407, 10,694, 2342, and 2448 for the LR, LWD, LWS, and PP breeds, respectively. All PP animals were genotyped for the halothane mutation. This data set was used to calculate RFI equations for each of the 4 breeds, and to estimate genetic parameters for RFI together with growth, carcass, and meat quality traits, and N and P excretion during the test period (35 to 110 kg BW). The RFI explained 20.1% in PP, 26.5% in LWS, 27.6% in LWD, and 29.5% in LR of the phenotypic variability of ADFI. The PP breed differed from the others in this respect, probably due to a lower impact of the variation of body composition on ADFI. Heritability estimates of RFI ranged from 0.21 ± 0.03 (LWD) to 0.33 ± 0.06 (PP) depending on the breed. Heritabilities of N and P excretion traits ranged from 0.29 ± 0.06 to 0.40 ± 0.06. The RFI showed positive genetic correlations with feed conversion ratio (FCR) and excretion traits, these correlations being greater in the sire breeds (from 0.57 to 0.86) than in the dam breeds (from 0.38 to 0.53). Compared with FCR, RFI had weaker genetic correlations with carcass composition, growth rate, and excretion traits. Estimates of genetic correlations between FCR and excretion traits were very close to 1 for all breeds. Finally, excretion traits were, at the genetic level, correlated positively with ADFI, negatively with growth rate and carcass leanness, whereas the halothane n mutation in PP was shown to reduce N and P excretion levels. To conclude, new selection indexes including RFI can be envisaged to efficiently disentangle the responses to selection on growth rate and body composition from those on feed efficiency, with favorable impacts on N and P excretions, particularly in sire pig breeds. However, the switch from FCR to RFI in selection indexes should not resolve the genetic antagonism between feed efficiency and meat quality.

BackgroundNumerous quantitative trait loci (QTL) have been detected in pigs over the past 20 years using microsatellite markers. However, due to the low density of these markers, the accuracy of QTL location has generally been poor. Since 2009, the dense genome coverage provided by the Illumina PorcineSNP60 BeadChip has made it possible to more accurately map QTL using genome-wide association studies (GWAS). Our objective was to perform high-density GWAS in order to identify genomic regions and corresponding haplotypes associated with production traits in a French Large White population of pigs.MethodsAnimals (385 Large White pigs from 106 sires) were genotyped using the PorcineSNP60 BeadChip and evaluated for 19 traits related to feed intake, growth, carcass composition and meat quality. Of the 64 432 SNPs on the chip, 44 412 were used for GWAS with an animal mixed model that included a regression coefficient for the tested SNPs and a genomic kinship matrix. SNP haplotype effects in QTL regions were then tested for association with phenotypes following phase reconstruction based on the Sscrofa10.2 pig genome assembly.ResultsTwenty-three QTL regions were identified on autosomes and their effects ranged from 0.25 to 0.75 phenotypic standard deviation units for feed intake and feed efficiency (four QTL), carcass (12 QTL) and meat quality traits (seven QTL). The 10 most significant QTL regions had effects on carcass (chromosomes 7, 10, 16, 17 and 18) and meat quality traits (two regions on chromosome 1 and one region on chromosomes 8, 9 and 13). Thirteen of the 23 QTL regions had not been previously described. A haplotype block of 183 kb on chromosome 1 (six SNPs) was identified and displayed three distinct haplotypes with significant (0.0001 < P < 0.03) associations with all evaluated meat quality traits.ConclusionsGWAS analyses with the PorcineSNP60 BeadChip enabled the detection of 23 QTL regions that affect feed consumption, carcass and meat quality traits in a LW population, of which 13 were novel QTL. The proportionally larger number of QTL found for meat quality traits suggests a specific opportunity for improving these traits in the pig by genomic selection.