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Genomic Analysis of Eimeria spp. Populations in Relation to Performance Levels of Broiler Chicken Farms in Arkansas and North Carolina

2009/08/01 by Ryan S. Schwarz, Mark C. Jenkins, Spangler Klopp +1 · 83 citations
Agricultural and Biological Sciences · Veterinary · #Animal Nutrition and Physiology #Animal science #Biology #Broiler #Coccidia and coccidiosis research #Coccidiosis #Eimeria #Eimeria acervulina #Eimeria maxima #Gene #Genetic diversity #Genetics #Helminth infection and control #Internal transcribed spacer #Population #Ribosomal RNA #Veterinary medicine

paper · doi:10.1645/ge-1898.1

published in Journal of Parasitology 95(4), 871-880 (American Society of Parasitologists)

openalex publication_date 2009/08/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

The impact of coccidiosis outbreaks on the productivity of broiler chicken farms can be substantial, depending on the severity of disease caused by particular species and strains of Eimeria. We examined the genetic diversity of Eimeria species present in commercial broiler farms in relation to their performance level. Four groups of broiler chicken farms in Arkansas (AR) and North Carolina (NC), having either high or low performance levels, were sampled for Eimeria spp. oocysts. We amplified gDNA from oocysts by using genus-specific primers targeting 18S ribosomal RNA, the first and second internal transcribed spacer regions, and cytochrome c oxidase subunit I as the established species-specific primers. Eimeria spp. diversity was not homogenous among the 4 farm groups, with less-pathogenic species (E. mitis and E. mivati-like) associated with AR and NC high-performance farms, respectively, and a pathogenic species (E. brunetti) associated with AR low-performance farms. Sequence analyses identified multiple E. maxima and E. mitis genetic variants, from which 2 E. maxima variants were unique to low-performance farms. Distinct populations of sequences at the NC high-performance farms were identified as E. mivati-like, based on homology searches. Our study demonstrated the utility of analyzing multiple genomic loci to assess composition and polymorphisms of Eimeria spp. populations.

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