Title

Bovine growth hormone releasing hormone gene: Structure, polymorphism and data management

Date of Completion

January 2000

Keywords

Biology, Molecular|Biology, Animal Physiology

Degree

Ph.D.

Abstract

The objective of this study was to sequence the bovine growth hormone releasing hormone (GHRH) gene, to screen for polymorphisms using single strand conformation polymorphism technique, to evaluate the association of any detected polymorphisms with genetic merit for production traits in a group of 200 dairy sires, and to develop a relational database program capable of organizing genetic data. ^ Genomic DNA for GHRH gene from three overlapping fragments was cloned and sequenced. The 9356-nucleotide sequence (GenBank accession number: AF242855) contained 306 nucleotides which encode a protein of 102 amino acids. Designing primers from this sequence, we amplified fragments of 200–400 bp covering 95% of the entire bovine GHRH gene, and discovered five polymorphic sites (A: 2063 in intron 1; B: 4193 in intron 1; C: in intron 1; D: 6905 in intron 4 and E: 8074 in intron 4). Four of those polymorphisms (A, B, D and E) were confirmed by sequencing, while the other (C) was not. Two substitutions occurred with restriction enzyme recognition sites (B with Taq I and D with Tfi I), and digestion of DNA samples from putative homologous and heterozygous individuals using those two enzymes agreed with our SSCP and sequence data. ^ Association between GHRH polymorphic and genetic merit was analyzed using the General Linear Model of the SAS program. Association between polymorphic site B with fat percentage (P = 0.029) was found. No significant differences were detected for all other sites (p > 0.05). ^ Based on the relatively small number half-sibling information, thirteen from sixteen theoretically possible haplotypes had been found, and four of the thirteen constituted 93.2% of the haplotypes observed in this study. Genotypes for 55.7% (98/176) of the bulls were inferred. Haplotype B was found to have an association with protein yield (p < 0.05). ^ A relational database to manage all research data in this study was created using Oracle. Using JAVA and extensive markup language, an intuitive graphic user interface incorporating three levels of user expertise was designed. The database and interfaces allow the user to accomplish the tasks such as extensive viewing, searching, and updating the database. ^