Host genetics drives differences in cecal microbiota composition and immune traits of laying hens raised in the same environment.

Vaccination is one of the most effective strategies for preventing infectious diseases but individual vaccine responses are highly heterogeneous. Host genetics and gut microbiota composition are 2 likely drivers of this heterogeneity. We studied 94 animals belonging to 4 lines of laying hens: a White Leghorn experimental line genetically selected for a high antibody response against the Newcastle Disease Virus (NDV) vaccine (ND3) and its unselected control line (CTR), and 2 commercial lines (White Leghorn [LEG] and Rhode Island Red [RIR]).

Restriction site-associated DNA sequencing technologies as an alternative to low-density SNP chips for genomic selection: a simulation study in layer chickens.

Background: To reduce the cost of genomic selection, a low-density (LD) single nucleotide polymorphism (SNP) chip can be used in combination with imputation for genotyping selection candidates instead of using a high-density (HD) SNP chip. Next-generation sequencing (NGS) techniques have been increasingly used in livestock species but remain expensive for routine use for genomic selection. An alternative and cost-efficient solution is to use restriction site-associated DNA sequencing (RADseq) techniques to sequence only a fraction of the genome using restriction enzymes.

Nest preference and laying duration traits to select against floor eggs in laying hens.

Background: Floor eggs, which are defined as eggs that hens lay off-nest, are a major issue in cage-free layer poultry systems. They create additional work for farmers because they must be collected by hand. They are also usually soiled or broken, which results in economic losses.

RNA-Seq Data for Reliable SNP Detection and Genotype Calling: Interest for Coding Variant Characterization and -Regulation Analysis by Allele-Specific Expression in Livestock Species.

In addition to their common usages to study gene expression, RNA-seq data accumulated over the last 10 years are a yet-unexploited resource of SNPs in numerous individuals from different populations. SNP detection by RNA-seq is particularly interesting for livestock species since whole genome sequencing is expensive and exome sequencing tools are unavailable. These SNPs detected in expressed regions can be used to characterize variants affecting protein functions, and to study -regulated genes by analyzing allele-specific expression (ASE) in the tissue of interest.

Nest acceptance, clutch, and oviposition traits are promising selection criteria to improve egg production in cage-free system.

In cage-free systems, laying hens must lay their eggs in the nests. Selecting layers based on nesting behavior would be a good strategy for improving egg production in these breeding systems. However, little is known about the genetic determinism of nest-related traits.

Interest of using imputation for genomic evaluation in layer chicken.

With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers.

Reliability of genomic evaluation for egg quality traits in layers.

Background: Genomic evaluation, based on the use of thousands of genetic markers in addition to pedigree and phenotype information, has become the standard evaluation methodology in dairy cattle breeding programmes over the past several years. Despite the many differences between dairy cattle breeding and poultry breeding, genomic selection seems very promising for the avian sector, and studies are currently being conducted to optimize avian selection schemes. In this optimization perspective, one of the key parameters is to properly predict the accuracy of genomic evaluation in pure line layers.

Variations in genome size between wild and domesticated lineages of fowls belonging to the Gallus gallus species.

Efforts to elucidate the causes of biological differences between wild fowls and their domesticated relatives, the chicken, have to date mainly focused on the identification of single nucleotide mutations. Other types of genomic variations have however been demonstrated to be important in avian evolution and associated to variations in phenotype. They include several types of sequences duplicated in tandem that can vary in their repetition number.

Design of low density SNP chips for genotype imputation in layer chicken.

Background: The main goal of selection is to achieve genetic gain for a population by choosing the best breeders among a set of selection candidates. Since 2013, the use of a high density genotyping chip (600K Affymetrix® Axiom® HD genotyping array) for chicken has enabled the implementation of genomic selection in layer and broiler breeding, but the genotyping costs remain high for a routine use on a large number of selection candidates. It has thus been deemed interesting to develop a low density genotyping chip that would induce lower costs.

GWAS analyses reveal QTL in egg layers that differ in response to diet differences.

Background: The genetic architecture of egg production and egg quality traits, i.e. the quantitative trait loci (QTL) that influence these traits, is still poorly known.

Yolk hormones influence in ovo chemosensory learning, growth, and feeding behavior in domestic chicks.

In this study, we assessed whether prenatal exposure to elevated yolk steroid hormones can influence in ovo chemosensory learning and the behavior of domestic chicks. We simulated a maternal environmental challenge by experimentally enhancing yolk progesterone, testosterone, and estradiol concentrations in hen eggs prior to incubation. The embryos from these hormones-treated eggs (HO) as well as sham embryos (O) that had received the vehicle-only were exposed to the odor of fish oil (menhaden) between embryonic Days 11 and 20.

Likelihood and Bayesian analyses reveal major genes affecting body composition, carcass, meat quality and the number of false teats in a Chinese European pig line.

Segregation analyses were performed using both maximum likelihood--via a Quasi Newton algorithm--(ML-QN) and Bayesian--via Gibbs sampling--(Bayesian-GS) approaches in the Chinese European Tiameslan pig line. Major genes were searched for average ultrasonic backfat thickness (ABT), carcass fat (X2 and X4) and lean (X5) depths, days from 20 to 100 kg (D20100), Napole technological yield (NTY), number of false (FTN) and good (GTN) teats, as well as total teat number (TTN). The discrete nature of FTN was additionally considered using a threshold model under ML methodology.