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Characterization of gene expression and genetic variation of horse ERBB receptor feedback inhibitor 1 in Thoroughbreds.
OBJECTIVE: This study aimed to test the expression patterns of ERBB receptor feedback inhibitor 1 ( ERRFI1 ) before and after exercise and the association of non-synonymous single-nucleotide polymorphisms (nsSNPs) of horse ERRFI1 with racing traits in Thoroughbreds.
METHODS: We performed bioinformatics and gene expression analyses for horse ERRFI1 . Transcription factor (TF) binding sites in the 5'-regulatory region of this gene were identified through a tool for prediction of TF-binding site (PROMO). A general linear model was used to detect the association between the nsSNP (LOC42830758 A to G) and race performance.
RESULTS: Quantitative polymerase chain reaction analysis showed that expression level of ERRFI1 after exercise was 1.6 times higher than that before exercise. Ten transcription factors were predicted from the ERRFI1 regulatory region. A novel nsSNP (LOC42830758 A to G) was found in ERRFI1 , which was associated with three racing traits including average prize money, average racing index, and 3-year-old starts percentile ranking.
CONCLUSION: Our analysis will be helpful as a basis for studying genes and SNPs that affect race performance in racehorses.
METHODS: We performed bioinformatics and gene expression analyses for horse ERRFI1 . Transcription factor (TF) binding sites in the 5'-regulatory region of this gene were identified through a tool for prediction of TF-binding site (PROMO). A general linear model was used to detect the association between the nsSNP (LOC42830758 A to G) and race performance.
RESULTS: Quantitative polymerase chain reaction analysis showed that expression level of ERRFI1 after exercise was 1.6 times higher than that before exercise. Ten transcription factors were predicted from the ERRFI1 regulatory region. A novel nsSNP (LOC42830758 A to G) was found in ERRFI1 , which was associated with three racing traits including average prize money, average racing index, and 3-year-old starts percentile ranking.
CONCLUSION: Our analysis will be helpful as a basis for studying genes and SNPs that affect race performance in racehorses.
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