Genetic parameters for production, quality, and colors from eggs in Brazilian lineages of chickens.

Genetic parameters were estimated for egg production, egg quality, and eggshell colors in eight lineages of Brazilian laying hens. Age at first egg (AFE), total egg production up to the 45th week (PROD), egg weight (EW), albumen height (AH), yolk color (YC), the Haugh units (HU), eggshell strength (ESS), eggshell thickness (EST), yolk weight (YW), eggshell weight (ESW), and eggshell color (L*, a*, and b*) were measured in 2030 eggs obtained from 645 laying hens. Variance components were estimated from a mixed animal model, which included the fixed effects of contemporary groups, cage location, and hen line, and the additive genetic, permanent environmental, and residual as random effects. In general, heritabilities were low to moderate (h2 = 0.11 to 0.48). Genetic correlations among eggshell quality traits were moderate to high (0.36 and 0.69). High genetic correlations were obtained between the eggshell color traits [rg = -0.90 (L* and a*); rg = -0.64 (L* and b*); and rg = 0.65 (a* and b*)]. Results suggest that EW is strongly correlated with ESW, but the genetic correlations between EW and ESS and between EW and EST were low. Genetic correlations between L* and eggshell quality traits were low to moderate, suggesting that L* has little or no relation with external egg quality. However, genetic correlations between a* and b* values and eggshell quality traits were high. The genetic correlations between eggshell color and eggshell quality traits were low, suggesting that the eggshell color does not influence external egg quality. Genetic correlations between PROD and egg quality traits were negative and varied between -0.42 and -0.05. This antagonistic relationship emphasizes the importance of adopting breeding schemes that allow the simultaneous genetic progress of these traits by considering their genetic correlation and economic relevance, such as the selection index.

CNV detection and their association with growth, efficiency and carcass traits in Santa Inês sheep.

Copy number variations (CNV) are an important source of genetic variation. CNV has been increasingly studied and frequently associated with diseases and productive traits in livestock animals. However, CNV-based genome-wide association studies (GWAS) in Santa Inês sheep, one of the principal sheep breeds in Brazil, have not yet been reported. Thus, the aim of this study was to investigate the association between CNV and growth, efficiency and carcass traits in sheep. The Illumina OvineSNP50 BeadChip array was used to detect CNV in 491 Santa Inês individuals. Then, CNV-based GWAS was performed with a linear mixed model approach considering a genomic relationship matrix, for ten traits: (1) growth: body weight at three (W3) and six (W6) months of age; (2) efficiency: residual feed intake (RFI) and feed efficiency (FE) and (3) carcass: external carcass length (ECL), leg length (LL), carcass yield (CY), commercial cuts weight (CCW), loin eye area (LEA) and subcutaneous fat thickness (SFT). We identified 1,167 autosomal CNV in 438 sheep, with 294 non-redundant CNV, ranging from 21.8 to 861.9 kb, merged into 216 distinct copy number variation regions (CNVRs). One significant CNV segment (pFDR -value<0.05) in OAR3 was associated with CY, while another significant CNV in OAR6 was associated with RFI. Additionally, another 5 CNV segments were considered relevant for investigation in the future studies. The significant segments overlapped 4 QTLs and spanned 8 genes, including the SPAST,TGFA and ADGRL3 genes, involved in cell differentiation and energy metabolism. Therefore, the results of the present study increase knowledge about CNV in sheep, their possible impacts on productive traits, and provide information for future investigations, being especially useful for those interested in structural variations in the sheep genome.

Comparison of Marker Effects and Breeding Values at Two Levels at THI for Milk Yield and Quality Traits in Brazilian Holstein Cows.

Genomic tools can help in the selection of animals genetically resistant to heat stress, especially the genome-wide association studies (GWAS). The objective of this study was to compare the variance explained by SNPs and direct genomic breeding values (DGVs) at two levels of a temperature and humidity index (THI). Records of milk yield (MY), somatic cell score (SCS), and percentages of casein (CAS), saturated fatty acids (SFA), and unsaturated fatty acids (UFA) in milk from 1157 Holstein cows were used. Traditional breeding values (EBV) were determined in a previous study and used as pseudo-phenotypes. Two levels of THI (heat comfort zone and heat stress zone) were used as environments and were treated as "traits" in a bi-trait model. The GWAS was performed using the genomic best linear unbiased prediction (GBLUP) method. Considering the top 50 SNPs, a total of 36 SNPs were not common between environments, eight of which were located in gene regions related to the evaluated traits. Even for those SNPs that had differences in their explained variances between the two environments, the differences were very small. The animals showed virtually no rank order, with rank correlation values of 0.90, 0.88, 1.00, 0.88, and 0.97 for MY, CAS, SCS, SFA, and UFA, respectively. The small difference between the environments studied can be attributed to the small difference in the pseudo-phenotypes used between the environments, on-farm acclimation, the polygenic nature of the traits, and the THI values studied near the threshold between comfort and heat stress. It is recommended that future studies be conducted with a larger number of animals and at more extreme THI levels.