Genetics of High-Value Yield in Broilers

A genomic scan with molecular markers was used to identify regions of the broiler genome that are associated with traits of growth and carcass composition in commercial broiler chickens. Identification of markers that can be used to genetically select broiler populations for better efficiency of growth of high-value yield parts, such as white meat, will enhance the profitability of poultry production and provide consumers with more of the desired type of meat product

Genetics and Genomic Regions Affecting Response to Newcastle Disease Virus Infection under Heat Stress in Layer Chickens.

Newcastle disease virus (NDV) is a highly contagious avian pathogen that poses a tremendous threat to poultry producers in endemic zones due to its epidemic potential. To investigate host genetic resistance to NDV while under the effects of heat stress, a genome-wide association study (GWAS) was performed on Hy-Line Brown layer chickens that were challenged with NDV while under high ambient temperature to identify regions associated with host viral titer, circulating anti-NDV antibody titer, and body weight change. A single nucleotide polymorphism (SNP) on chromosome 1 was associated with viral titer at two days post-infection (dpi), while 30 SNPs spanning a quantitative trait loci (QTL) on chromosome 24 were associated with viral titer at 6 dpi. Immune related genes, such as CAMK1d and CCDC3 on chromosome 1, associated with viral titer at 2 dpi, and TIRAP, ETS1, and KIRREL3, associated with viral titer at 6 dpi, were located in two QTL regions for viral titer that were identified in this study. This study identified genomic regions and candidate genes that are associated with response to NDV during heat stress in Hy-Line Brown layer chickens. Regions identified for viral titer on chromosome 1 and 24, at 2 and 6 dpi, respectively, included several genes that have key roles in regulating the immune response

SNPs in Region of NF-Kappa-B Gene Associated with Expression of Immune-Related Genes

Selection to enhance immune response is difficult. Gene expression was assessed in two advanced intercross lines of chickens for various immune-related genes. Single nucleotide polymorphisms, SNPs, were identified in regions local to each gene and around a distant transcription factor, NF-Kappa-B, NFKB. These SNPs were used to identify expression QTL, eQTL, to aid in selection of immune gene expression. These eQTL may provide effective resources to which marker assisted selection may be applied

Comparison of methods for analysis of selective genotyping survival data

Survival traits and selective genotyping datasets are typically not normally distributed, thus common models used to identify QTL may not be statistically appropriate for their analysis. The objective of the present study was to compare models for identification of QTL associated with survival traits, in particular when combined with selective genotyping. Data were simulated to model the survival distribution of a population of chickens challenged with Marek disease virus. Cox proportional hazards (CPH), linear regression (LR), and Weibull models were compared for their appropriateness to analyze the data, ability to identify associations of marker alleles with survival, and estimation of effects when all individuals were genotyped (full genotyping) and when selective genotyping was used. Little difference in power was found between the CPH and the LR model for low censoring cases for both full and selective genotyping. The simulated data were not transformed to follow a Weibull distribution and, as a result, the Weibull model generally resulted in less power than the other two models and overestimated effects. Effect estimates from LR and CPH were unbiased when all individuals were genotyped, but overestimated when selective genotyping was used. Thus, LR is preferred for analyzing survival data when the amount of censoring is low because of ease of implementation and interpretation. Including phenotypic data of non-genotyped individuals in selective genotyping analysis increased power, but resulted in LR having an inflated false positive rate, and therefore the CPH model is preferred for this scenario, although transformation of the data may also make the Weibull model appropriate for this case. The results from the research presented herein are directly applicable to interval mapping analyses

Commercial Layer-type Chickens and Newcastle Disease Virus Infection:Toward Genetic Selection of More Resilient Chickens

Exotic Newcastle Disease Virus(NDV)causes major losses due to extremely quickmortalityin chickensafter exposure to the virus. In places where this virusis not effectively controlled through vaccination and biosecurity, people rely heavily on poultry to provideprotein and income.Losses from NDV contributeto worldwide hunger and poverty. It may be possible to use genetic selection to produce chickens thatnot onlyhave a stronger immune response in the face of NDV challengebut also respond better to vaccination. In order for genetic selection to be successful,two major elements are required: differences in immune response between chickens and genetic control of these differences. This study clearly demonstrates the existence of both these factors.These findings provide strong possibility for the ability of genetic selection to produce chickens that are more resistant to NDV and thereby lessen the burdens of hunger and poverty

Associations of myostatin gene polymorphisms with performance and mortality traits in broiler chickens

Myostatin is a negative regulator of skeletal muscle growth. We evaluated effects of myostatin polymorphisms in three elite commercial broiler chicken lines on mortality, growth, feed conversion efficiency, ultrasound breast depth, breast percentage, eviscerated carcass weight, leg defects, blood oxygen level, and hen antibody titer to infectious bursal disease virus vaccine. Progeny mean data adjusted for fixed and mate effects and DNA from 100 sires per line were used. Single nucleotide polymorphisms (SNPs) of the myostatin gene segregating in these lines were identified by designing specific primers, amplifying individual DNA in each line by polymerase chain reaction, cloning, sequencing and aligning the corresponding products. Individual sires were genotyped for five identified SNPs which contributed to eight haplotypes. Frequencies of SNP alleles and haplotypes differed between lines. Using the allele substitution effect model, the myostatin SNPs were found to have significant (P < 0.031) associations with growth, mortality, blood oxygen and hen antibody titer to infectious bursal disease virus vaccine, although the associations were not often consistent across lines. These results suggest that the myostatin gene has pleiotropic effects on broiler performance

The Effect of Heritability Estimates on High-Density Single Nucleotide Polymorphism Analyses with Related Animals

Analysis of high-density SNP data in outbred populations to identify SNP that are associated with a quantitative trait requires efficient ways to handle large volumes of data and analyses. When using mixed animal models to account for polygenic effects and relationships, genetic parameters are not known with certainty, but must be chosen to ensure proper evaluation of SNP across chromosomes and lines or breeds. The objectives of this study were to evaluate the influence of heritability on the estimates and significance of SNP effects, to develop efficient computational strategies for analysis of high-density SNP data with uncertain heritability estimates, and to develop strategies to combine SNP test results across lines or breeds. Data included sire SNP genotypes and mean progeny performance from 2 commercial broiler breeding lines. Association analyses were done by fitting each SNP separately as a fixed effect in an animal model, using a range of heritabilities. The heritability used had a limited impact on SNP effect estimates, but affected the SE of estimates and levels of significance. The shape of the frequency distribution of P-values for the test of SNP effects changed from a highly skewed L-shaped curve at low heritability to a right-skewed distribution at high heritability. The P-values for alternative heritabilities could, however, be derived without reanalysis based on a strong linear relationship (R2 = 0.99) between differences in log-likelihood values of models with and without the SNP at different levels of heritabilities. With uncertain estimates of heritability, line-specific heritabilities that ensure proper evaluation of SNP effects across lines were determined by analysis of simulated sire genotypes and by permutation tests. Resulting heritability estimates were between those obtained from the entire breeding populations and those obtained from the data included in the sample data set. In conclusion, the uncertainty of heritability estimates has a limited impact on SNP effect estimates in association analyses, but a large impact on significance tests. The impact of heritability on tests can, however, be dealt with in a computationally efficient manner by using the strong linear relationship between model statistics under alternate levels of heritability. These approaches allow efficient analysis of large numbers of SNP for multiple traits and populations and pooling of results across populations