This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Our laboratory is interested in uncovering novel motifs important in the transcriptional regulation of spermatogenesis-specific genes. Computational prediction of novel transcription factor and regulatory protein binding sites is a daunting task due in large part to the small size of the binding sites. However, there are several computational approaches useful for uncovering sites with potential to function as regulatory binding sites. These include motif-finding algorithms (Hidden Markov Models), statistical sampling methods (Gibbs sampling), sequence comparison methods coupled to some type of motif finding or probabilistic analysis methodology (Phylogenetic footprinting), and genetic algorithms. Spermatogenesis is a highly conserved developmental process in vertebrates. We hypothesize that genes with conserved expression during spermatogenesis in disparate vertebrate lineages are controlled by evolutionarily conserved mechanisms. To test our hypothesis, we employ the sequence analysis methods outlined above to search for motifs in the genomic regions upstream of spermatogenesis-specific genes from human as well as various model organisms, including rodents and fish. Evaluating the function of candidate motifs proceeds by means of the electrophoretic mobility shift assay, an assay that tests for the ability of nuclear proteins purified from the testis of mice, skates and the dogfish shark to specifically bind probes containing the candidate motif.
Showing the most recent 10 out of 246 publications
