QTL detection for coccidiosis (Eimeria tenella) resistance in a Fayoumi × Leghorn F2 cross, using a medium-density SNP panel

Abstract

BackgroundCoccidiosis is a major parasitic disease that causes huge economic losses to the poultry industry. Its pathogenicity leads to depression of body weight gain, lesions and, in the most serious cases, death in affected animals. Genetic variability for resistance to coccidiosis in the chicken has been demonstrated and if this natural resistance could be exploited, it would reduce the costs of the disease. Previously, a design to characterize the genetic regulation of Eimeria tenella resistance was set up in a Fayoumi × Leghorn F2 cross. The 860 F2 animals of this design were phenotyped for weight gain, plasma coloration, hematocrit level, intestinal lesion score and body temperature. In the work reported here, the 860 animals were genotyped for a panel of 1393 (157 microsatellites and 1236 single nucleotide polymorphism (SNP) markers that cover the sequenced genome (i.e. the 28 first autosomes and the Z chromosome). In addition, with the aim of finding an index capable of explaining a large amount of the variance associated with resistance to coccidiosis, a composite factor was derived by combining the variables of all these traits in a single variable. QTL detection was performed by linkage analysis using GridQTL and QTLMap. Single and multi-QTL models were applied.ResultsThirty-one QTL were identified i.e. 27 with the single-QTL model and four with the multi-QTL model and the average confidence interval was 5.9 cM. Only a few QTL were common with the previous study that used the same design but focused on the 260 more extreme animals that were genotyped with the 157 microsatellites only. Major differences were also found between results obtained with QTLMap and GridQTL.ConclusionsThe medium-density SNP panel made it possible to genotype new regions of the chicken genome (including micro-chromosomes) that were involved in the genetic control of the traits investigated. This study also highlights the strong variations in QTL detection between different models and marker densities.

Genome-wide association study and biological pathway analysis of the Eimeria maxima response in broilers

“…Previous QTL studies have reported that several genomic regions are associated with BWG in response to coccidiosis [ 15 , 20 ]. Comparing our results with these previous studies, only one highly significant SNP that overlaps with a QTL on GGA3 (between 263 and 282cM; 98.1 and 107.0 Mb), detected by Pinard-van der Laan et al [ 16 ] and Bacciu et al [ 17 ], was observed. However, these different results were not completely unexpected considering that the previously conducted challenge study was performed with animals at a different age and that originated from very different experimental lines.…”

“…The host response to Eimeria is a complex trait controlled by a wide range of biological processes, which are in turn controlled by many genes with a small effect and a small number of genes with a moderate or large effect. Several QTL regions that are significantly associated with traits measured after the response to Eimeria challenge were detected in F 2 crosses obtained from experimental lines with different degrees of susceptibility to coccidiosis [ 16 , 17 , 36 ]. In addition, similar approaches have been used for the identification of genomic regions associated with innate and adaptive immunity in laying hens [ 37 ] as well as survival rate and aimed at improving general robustness, especially in laying hens [ 38 ].…”

“…Likewise, marked differences in the response to Eimeria infection were observed between inbred and outbred lines [ 13 , 14 ]. The availability of genome-wide dense markers has enabled the identification of several quantitative trait loci (QTL) regions associated with resistance to Eimeria tenella and Eimeria maxima in experimental populations [ 15 – 17 ]. In addition, several genes that are located in highly significant previously detected QTL [ 16 ] were also found to be differentially expressed in a follow-up transcriptome study [ 18 ].…”

Genetic Control of Contagious Asexuality in the Pea Aphid

“…Similarly to the reduction of x-LOD when using LOD scores, the maximum LR value was reduced by 3.84 (corresponding to a Chi 2 distribution with one degree of freedom for p <0.05) to determine a threshold. Region boundaries were then defined by the LR locations crossing this threshold upstream and downstream of the peak LR [as described in 50] , [51] to identify the 95% CI of the QTL. After identifying the first QTL (see Results ), we tested for the presence of a second QTL.…”

Eimeria genomics: Where are we now and where are we going?

“…For chickens the disease can be subdivided into haemorrhagic and malabsorptive pathologies loosely related to Eimeria brunetti, Eimeria necatrix and Eimeria tenella, or Eimeria acervulina, Eimeria maxima, Eimeria mitis and Eimeria praecox, respectively (Reid et al, 2014). The severity of disease can be influenced by multiple factors including parasite and host genotype, the size and age of oocyst dose, poultry management system and consequential level of oocyst sporulation, and previous exposure history (Blake et al, 2005;Kim et al, 2008;Williams et al, 2009;Bacciu et al, 2014). Pathognomonic signatures vary between species but poor food conversion ratio, weight loss and diarrhoea are characteristic with high morbidity common and mortality in the absence of intervention.…”