A quantitative trait locus for a primary antibody response to keyhole limpet hemocyanin on chicken chromosome 14--confirmation and candidate gene approach

SNP prioritization in targeted sequencing data associated with humoral immune responses in chicken

Our study aimed to identify single nucleotide polymorphisms (SNPs) with a significant impact on the innate immunity represented by antibody response against lipopolysaccharide (LPS) and lipoteichoid acid (LTA) and the adaptive immune response represented toward keyhole limpet hemocyanin (KLH) using the SNP prioritization method. Data set consisted of 288 F2 experimental individuals, created by crossing Green-legged Partridgelike and White Leghorn. The analyzed SNPs were located within 24 short genomic regions of GGA1, GGA2, GGA3, GGA4, GGA9, GGA10, GGA14, GGA18, and GGZ, pre-targeted based on literature references and database information. For the specific antibody response toward KLH at d 0 the most highly prioritized SNP for additive and dominance effects were located on GGA2 in the 3’UTR of MYD88. For the response at d 7, the most highly prioritized SNP pointed at the 3’UTR of MYD88, but potential causal additive variants were located within ADIPOQ and one in PROCR. The highest priority for additive and dominance effects in the antibody response toward lipoteichoic acid at d 0 was attributed to the same SNP, located on GGA2 in the 3’UTR region of MYD88. Two SNPs among the top-10 for additive effect were located in the exon of NOCT. SNPs selected for their additive effect on antibody response toward lipopolysaccharide at d 0 marked 3 genes – NOCT, MYD88, and SNX8, while SNPs selected for their dominance effect marked – NOCT, ADIPOQ, and MYD88. The top-10 variants identified in our study were located in different functional parts of the genome. In the context of causality three groups can be distinguished: variants located in exons of protein coding genes (ADIPOQ, NOCT, PROCR, SNX8), variants within exons of non-coding transcripts, and variants located in genes’ UTR regions. Variants from the first group influence protein structure and variants from both latter groups’ exhibit regulatory roles on DNA (UTR) or RNA (lncRNA).

Sensitivity analysis based on the random forest machine learning algorithm identifies candidate genes for regulation of innate and adaptive immune response of chicken

Two categories of immune responses—innate and adaptive immunity—have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in chickens using machine learning–based sensitivity analysis for single-nucleotide polymorphisms (SNPs) located in candidate genes defined in quantitative trait loci regions. Here the adaptive immunity is represented by the specific antibody response toward keyhole limpet hemocyanin (KLH), whereas the innate immunity was represented by natural antibodies toward lipopolysaccharide (LPS) and lipoteichoic acid (LTA). The analysis consisted of 3 basic steps: an identification of candidate SNPs via feature selection, an optimisation of the feature set using recursive feature elimination, and finally a gene-level sensitivity analysis for final selection of models. The predictive model based on 5 genes (MAPK8IP3 CRLF3, UNC13D, ILR9, and PRCKB) explains 14.9% of variance for KLH adaptive response. The models obtained for LTA and LPS use more genes and have lower predictive power, explaining respectively 7.8 and 4.5% of total variance. In comparison, the linear models built on genes identified by a standard statistical analysis explain 1.5, 0.5, and 0.3% of variance for KLH, LTA, and LPS response, respectively. The present study shows that machine learning methods applied to systems with a complex interaction network can discover phenotype-genotype associations with much higher sensitivity than traditional statistical models. It adds contribution to evidence suggesting a role of MAPK8IP3 in the adaptive immune response. It also indicates that CRLF3 is involved in this process as well. Both findings need additional verification.

Identification of quantitative trait loci affecting production and biochemical traits in a unique Japanese quail resource population

The objective of the current study was to identify QTL associated with body weight, growth rate, egg quality traits, concentration of selected blood plasma, and yolk lipids as well as concentration of selected macro- and microelements, color, pH, basic chemical composition, and drip loss of breast muscle of Japanese quail (Coturnix japonica). Twenty-two meat-type males (line F33) were crossed with twenty-two laying-type females (line S22) to produce a generation of F1 hybrids. The F2 generation was created by mating 44 randomly chosen F1 hybrids, which were full siblings. The birds were individually weighed from the first to eighth week of age. At the age of 19 wk, 2 to 4 eggs were individually collected from each female and an analysis of the egg quality traits was performed. At slaughter, blood and breast muscles were collected from 324 individuals of the resource population. The basic chemical composition, concentration of chosen macro- and microelements, color, pH, and drip loss were determined in the muscle samples. The concentration of chosen lipids was determined in egg yolk and blood plasma. In total, 30 microsatellite markers located on chromosome 1 and 2 were genotyped. QTL mapping including additive and dominance genetic effects revealed 6 loci on chromosome 1 of the Japanese quail affecting the egg number, egg production rate, egg weight, specific gravity, egg shell weight, concentration of Na in breast muscle. In turn, there were 9 loci on chromosome 2 affecting the body weight in the first, fourth, and sixth week of age, growth rate in the second and seventh week of age, specific gravity, concentration of K and Cu in breast muscle, and the levels of triacylglycerols in blood plasma. In this study, QTL with a potential effect on the Na, K, and Cu content in breast muscles in poultry and on specific gravity in the Japanese quail were mapped for the first time.

Identification of candidate genes and mutations in QTL regions for immune responses in chicken

There are two categories of immune responses – innate and adaptive immunity – both having polygenic backgrounds and a significant environmental component. In our study, adaptive immunity was represented by the specific antibody response toward keyhole limpet hemocyanin (KLH); innate immunity was represented by natural antibodies toward lipopolysaccharide (LPS) and lipoteichoic acid (LTA). Defining genetic bases of immune responses leads from defining quantitative trait loci (QTL) toward a single mutation responsible for variation in the phenotypic trait. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in chicken by performing an association study of SNPs located in candidate genes defined in QTL regions. Candidate genes and SNPs in QTL regions were selected in silico. SNP association was based on a custom SNP panel, GoldenGate genotyping assay (Illumina) and two statistical models: random mixed model and CAR score. The most significant SNP for immune response toward KLH was located in the JMJD6 gene located on GGA18. Four SNPs in candidate genes FOXJ1 (GGA18), EPHB1 (GGA9), PTGER4 (GGAZ) and PRKCB (GGA14) showed association with natural antibodies for LPS. A single SNP in ITGB4 (GGA18) was associated with natural antibodies for LTA. All associated SNPs mentioned above showed additive effects.

Meta - and combined - QTL analysis of different experiments on immune traits in chickens

Meta and/or combined QTL analysis from multiple studies can improve quantitative trait loci (QTL) position estimates compared to the individual experiments. Hereby we present results of a meta-analysis of QTL on chicken chromosome 9, 14 and 18 using data from three separate experiments and joint QTL analysis for chromosome 14 and 18. Meta QTL analysis uses information from multiple QTLs studies. Joint QTL analysis is based on combining raw data from different QTL experimental populations. QTLs under the study were related to specific antibody response to keyhole lymphet hemocyanin (KLH), and natural antibodies to environmental antigens, lipopolisaccharide (LPS) and lipoteichoic acid (LTA). Meta QTL analysis resulted in narrowing down the confidence interval for two QTLs on GGA14. The first one for natural antibodies against LTA and the second one for specific antibody response toward KLH. Also, a confidence interval of a QTL for natural antibodies against LPS located on GGA18 was narrowed down. Combined QTL analysis was successful for two QTLs: for specific antibody response toward KLH on GGA14, and for natural antibodies against LPS on GGA18. The greatest statistical power for QTL detection in joint analysis was achieved when raw data from segregating half–sib families from different populations under the study was used.

Insights into the genetic history of Green-legged Partridgelike fowl: mtDNA and genome-wide SNP analysis

The Green-legged Partridgelike (GP) fowl, an old native Polish breed, is characterised by reseda green-coloured shanks rather than yellow, white, slate or black commonly observed across most domestic breeds of chicken. Here, we investigate the origin, genetic relationships and structure of the GP fowl using mtDNA D-loop sequencing and genome-wide SNP analysis. Genome-wide association analysis between breeds enables us to verify the genetic control of the reseda green shank phenotype, a defining trait for the breed. Two mtDNA D-loop haplogroups and three autosomal genetic backgrounds are revealed. Significant associations of SNPs on chromosomes GGA24 and GGAZ indicate that the reseda green leg phenotype is associated with recessive alleles linked to the W and Id loci. Our results provide new insights into the genetic history of European chicken, indicating an admixd origin of East European traditional breeds of chicken on the continent, as supported by the presence of the reseda green phenotype and the knowledge that the GP fowl as a breed was developed before the advent of commercial stocks.

Detection of two QTL on chicken chromosome 14 for keyhole lymphet haemocyanin

A keyhole lymphet haemocyanin is an antigen which triggers Th1 type of immune response. A QTL for a primary immune response towards keyhole lymphet haemocyanin has been detected on chicken chromosome 14 in three populations. The results from the most recent population were inconsistent and varied depending on the applied QTL detection model. The major goal of the current study was the reanalysis of this data using a 2 QTL model. Additionally, in order to provide more accurate estimates of QTL effects and positions, epistasis between the QTL was considered as a potential important contributor to quantitative traits. Four statistical models were assumed: M1: A model assuming marginal additive effects of two QTL; M2: A model assuming marginal and epistatic additive effects of two QTL; M3: A model assuming marginal additive and dominance effects of two QTL; M4: A model assuming marginal additive and dominance effects of two QTL and all possible pairwise epistases. Two QTL with significant additive and dominance effects were detected on chicken chromosome 14 using model M3. One QTL was detected at 63 cM between MCW0123 and ROS0005, another at 76 cM between ROS0005 and MCW0225/NTN2Lsts1 (FDR = 0.0051). Modelling only additive effects resulted in a significantly worse fit. On the other hand, including epistatic effects did not improve fit significantly. The current study confirms previous reports of the QTL location on GGA14. A notable finding of this study is recognition of two closely related QTL for a keyhole lymphet haemocyanin response at the distal part of chicken chromosome 14.

Quantitative trait loci associated with the humoral innate immune response in chickens were confirmed in a cross between Green-Legged Partridgelike and White Leghorn

Natural antibodies (NA) create a crucial barrier at the initial steps of the innate humoral immune response. The main role of NA in the defense system is to bind the pathogens at early stages of infection. Different pathogens are recognized by the presence of highly conserved antigen determinant [e.g., lipopolysaccharide (LPS) in gram-negative bacteria or lipoteichoic acid (LTA) in gram-positive bacteria]. In chickens, a different genetic background of NA binds LPS and LTA antigens, encoded by different QTL. The main objective of this work was to confirm known QTL associated with LPS and LTA NA. For this purpose a chicken reference population was created by crossing 2 breeds: a commercial layer, White Leghorn, and a Polish indigenous chicken, Green-Legged Partridgelike. The chromosomal regions analyzed harbored to GGA3, GGA5, GGA6, GGA8, GGA9, GGA10, GGA14, GGA15, GGA18, and GGAZ. The data collected consisted of the NA titers binding LPS and LTA (determined by ELISA at 12 wk of age) as well as the genotypes (30 short tandem repeat markers; average of 3 markers/chromosome, collected for generations F(0), F(1), and F(2)). The analyses were performed with 3 statistical models (paternal and maternal half-sib, line cross, and linkage analysis and linkage disequilibrium) implemented in GridQTL software (http://www.gridqtl.org.uk/). The QTL study of humoral innate immune response traits resulted in the confirmation of 3 QTL associated with NA titers binding LPS (located on GGA9, GGA18, and GGAZ) and 2 QTL associated with NA titers binding LTA (located on GGA5 and GGA14). A set of candidate genes within the regions of the validated QTL has been proposed.

New QTL for resistance to Salmonella carrier-state identified on fowl microchromosomes

Chicken's ability to carry Salmonella without displaying disease symptoms leads to an invisible propagation of Salmonella in poultry stocks. Using chicken lines more resistant to carrier state could improve both animal health and food safety. Previous studies identified several QTL for resistance to carrier state. To improve genome coverage and QTL detection power we produced a new set of 480 informative SNP markers and genotyped a larger number of animals. Ten additional microchromosomes could be covered when compared with previous studies. These new data led to the identification of 18 QTL significant at the chromosome-wide level. The only QTL significant at the genome-wide level were identified on microchromosomes 14 and 22 and have never been identified previously. Using a higher number of animals improved the power and the precision of QTL detection. Some of the QTL newly identified are located close to candidate genes or microsatellite markers previously identified for their involvement in the genetic control of resistance to Salmonella, which confirms their interest for selection purposes.