Model comparison to evaluate a shell quality bio-complex in layer hens

Reducing the incidence of egg shell breakage is an important selection goal in egg layer hens breeding. Breaking strength provides an indicator of static shell resistance correlated with shell thickness. Acoustic egg tests combine shell\u27s resonance profile with egg mass to calculate dynamic stiffness (KDyn) a quantitative indicator of integral shell resistance, and a novel direct detection of both cracks and micro-cracks (MCr) making it possible for use in selection programs aiming improvement of shell quality. A shell quality bio-complex was defined to improve overall shell quality, including: breaking strength at equator (BSe) and poles (BSp), KDyn, and MCr, on multiple eggs/hen-age. A total of 81,667; 101,113; and 72,462 records from 4 generations of three pure lines were evaluated. Two models were tested in the brown-egg line: I) four-trait linear repeatability model and II) three-trait linear (BS, KDyn)-threshold (MCr) in the three lines. Models were implemented with AIREMLF90 and THRGIBBS1F90. Heritability and repeatability (Model I) estimates were: h2 = 0.14, 0.18, 0.33, and 0.02; r = 0.16, 0.28, 0.43, and 0.03 for BSe, BSp, KDyn, and MCr, respectively. Corresponding values in White Plymouth Rock were h2 = 0.14, 0.17, 0.33, and 0.02; r = 0.21, 0.33, 0.44, and 0.04, and in White Leghorn were h2 = 0.14, 0.23, 0.36, and 0.02; r = 0.24, 0.38, 0.52, and 0.02. Genetic correlations between BSe and BSp were between 0.51 and 0.68. The BS traits were moderately correlated with KDyn (+0.23 to +0.51), and tended to be negatively correlated with MCr. KDyn, and MCr (−0.46 to −0.62). Model II had similar results; except for increased h2 = 0.06 and r = 0.09 for MCr. Results indicate that BSe and BSp are different traits; while incidence of MCr is low in heritable but showed negative genetic correlations with the other traits. This makes MCr unsuitable for direct selection; but favors indirect selection against MCr via BSe, BSp, and KDyn for a holistic selection to improve shell quality, in particular to achieve the ultimate goal, reduction of egg breakage

Genome wide association study for heat stress induced mortality in a white egg layer line

High environmental temperature is a serious stress affecting economic and biological efficiency of poultry production in tropical and subtropical countries that is expected to become more prominent with global climate change. Iowa experienced 3 acute heat waves of 11, 3, and 4 d of heat index above 38°C in the summer of 2012, which led to production losses and increased bird mortality. For the current study, the proportion of daughters that died from heat stress during this period was calculated for 118 sire families of an elite White Leghorn layer line. The number of daughters per sire ranged from 25 to 111 and averaged 68. Average mortality due to heat stress was 8.2%, ranging from 0 to 24.6%. All sires were genotyped using a 600 K Affymetrix chip. After stringent quality filtering (clustering quality, parentage, missing genotypes, MAF) 113,344 SNPs were retained for the analysis. Method BayesB with π equal to 0.999, for the number of markers fitted not to exceed the number of observations, was applied. Markers explained 8% of the phenotypic variance. One 1-Mb window on chromosome 5 explained 1.2% of genetic variance. When the number of daughters was fitted as a weight in the analysis, the proportion of variance explained by markers dropped to 1%, but 9 1-Mb windows explained more than 1% of genetic variance on chromosomes 1, 3, 5 (the same top window as in the unweighted analysis), 9, 17, and 18. Although the support of the genomic regions associated with heat stress resistance identified in this study was not very strong, they overlapped with previously reported quantitative trait loci regions for immune response and physiological traits in chickens and contained genes that have been associated with response to heat stress in other studies. Further research is needed to validate the results

Investigating the genetic determination of clutch traits in laying hens

Clutch traits were proposed as a more detailed description of egg-laying patterns than simple total egg production. In this study, egg production of 23,809 Rhode Island Red (RIR) and 22,210 White Leghorn (WL) hens was described in terms of number of clutches, average and maximum clutch size, age at first egg, total saleable egg production, and percentage of egg defects. Genetic parameters were estimated using a six-trait animal model. Of the phenotyped birds, 1433 RIR hens and 1515 WL hens were genotyped with line specific 50K Affymetrix Axiom single nucleotide polymorphism chips to perform genome-wide association analyses. Moderate heritabilities were estimated for clutch traits of 0.20 to 0.42 in the RIR line and 0.29 to 0.41 in the WL line. Average and maximum clutch size was positively genetically correlated with total saleable egg number in both lines. Genome-wide association analysis identified seven regions that were associated with egg production in the RIR line and 12 regions in the WL line. The regions identified were line and trait specific, except for one region on chromosome 6 from 28 to 29 Mb that influenced number of clutches and maximum and average clutch size in WL hens. Regions associated with egg production identified here overlapped with 260 genes, with some strong positional candidates based on gene ontology including WASH1, which is involved in oocyte maturation, NPVF, involved in regulation of follicle-stimulating hormone secretion, and FOXO3, involved in oocyte maturation and ovulation from the ovarian follicle. Confirmation of the role of these genes in regulation of egg production pattern will require further studies

Research Note: Comparison of chicken blood chemistry and electrolyte parameters between the portable i-STAT1 clinical analyzer and VetScan VS2 serum biochemistry panel using Hy-Line commercial white-egg laying hens

The i-STAT1 clinical analyzer has become an increasingly popular tool in clinical production animal medicine as it can provide pen-side results in a cost effective and timely manner when compared to standard benchtop serum biochemistry blood gas and chemistry analyses. This study compares the results of the portable Abbott i-STAT1 analyzer and the Abaxis VetScan VS2 for glucose (Glu, mg/dL), ionized Ca (mmol/L), Na (mmol/L), and K (mmol/L) values. Three genetically distinct commercial varieties (CV) of Hy-Line white-egg laying hens are used in this study (Hy-Line W-36, Hy-Line W-80, and Hy-Line W-80+). Thirty blood samples (n = 10 per CV) were obtained in the production house from the brachial vein and concurrently analyzed by the i-STAT1 portable device. Serum from 22 of these same samples was analyzed via VetScan VS2, a benchtop serum clinical biochemistry analyzer, using VetScan Avian/Reptilian Profile Plus reagent rotors. A paired T-test was used to test for statistical differences in means between the 2 instruments for each of the parameters. Parameters with significant mean differences were then subject to correlation and regression analysis to further evaluate relationships between the results from the 2 methods. Significant differences between means were found for Glu, Na, and K levels. Ca levels were found to be not directly comparable by the 2 analysis instruments. This comparison elucidates the importance of clinical analyzer validations when applying different strategies of diagnostic medicine in poultry

Accuracy of genomic prediction of shell quality in a White Leghorn line

Several genomic methods were applied for predicting shell quality traits recorded at 4 different hen ages in a White Leghorn line. The accuracies of genomic prediction of single-step GBLUP and single-trait Bayes B were compared with predictions of breeding values based on pedigree-BLUP under single-trait or multitrait models. Breaking strength (BS) and dynamic stiffness (Kdyn) measurements were collected on 18,524 birds from 3 consecutive generations, of which 4,164 animals also had genotypes from an Affymetrix 50K panel containing 49,591 SNPs after quality control edits. All traits had low to moderate heritability, ranging from 0.17 for BS to 0.34 for Kdyn. The highest accuracies of prediction were obtained for the multitrait single-step model. The use of marker information resulted in higher prediction accuracies than pedigree-based models for almost all traits. A genome-wide association study based on a Bayes B model was conducted to detect regions explaining the largest proportion of genetic variance. Across all 8 shell quality traits analyzed, 7 regions each explaining over 2% of genetic variance and 54 regions each explaining over 1% of genetic variance were identified. The windows explaining a large proportion of genetic variance overlapped with several potential candidate genes with biological functions linked to shell formation. A multitrait repeatability model using a single-step method is recommended for genomic evaluation of shell quality in layer chickens