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Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome
Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome
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Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome
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Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome
Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome

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Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome
Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome
Journal Article

Sex Differences in Response to Marek’s Disease: Mapping Quantitative Trait Loci Regions (QTLRs) to the Z Chromosome

2022
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Overview
Marek’s Disease (MD) has a significant impact on both the global poultry economy and animal welfare. The disease pathology can include neurological damage and tumour formation. Sexual dimorphism in immunity and known higher susceptibility of females to MD makes the chicken Z chromosome (GGZ) a particularly attractive target to study the chicken MD response. Previously, we used a Hy-Line F6 population from a full-sib advanced intercross line to map MD QTL regions (QTLRs) on all chicken autosomes. Here, we mapped MD QTLRs on GGZ in the previously utilized F6 population with individual genotypes and phenotypes, and in eight elite commercial egg production lines with daughter-tested sires and selective DNA pooling (SDP). Four MD QTLRs were found from each analysis. Some of these QTLRs overlap regions from previous reports. All QTLRs were tested by individuals from the same eight lines used in the SDP and genotyped with markers located within and around the QTLRs. All QTLRs were confirmed. The results exemplify the complexity of MD resistance in chickens and the complex distribution of p-values and Linkage Disequilibrium (LD) pattern and their effect on localization of the causative elements. Considering the fragments and interdigitated LD blocks while using LD to aid localization of causative elements, one must look beyond the non-significant markers, for possible distant markers and blocks in high LD with the significant block. The QTLRs found here may explain at least part of the gender differences in MD tolerance, and provide targets for mitigating the effects of MD.