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Differential display PCR (ddPCR) and complementary DNA microarray analyses were used to evaluate gene expression differences in porcine ovarian follicles between a line of pigs selected for an index of ovulation rate and embryo survival (Line I) and its randomly selected control line (Line C). Follicles (4.0 to 7.0 mm) were dissected from ovaries of multiparous sows (n = 27) at either 2 or 4 d following PGF2α analog injection on d 12 to 14 of the estrous cycle. Using ddPCR, differentially expressed bands (n = 282) were excised from gels and 107 were sequenced, yielding 84 unique porcine follicle expressed sequence tags. Northern hybridization confirmed differential expression (between lines, days, or follicle sizes) for messenger RNA representing the calpain I light subunit, cytochrome C oxidase subunit III, cytochrome P450 aromatase, and cytochrome P450 side chain cleavage genes. For microarray analysis, two mRNA pools representing follicles (d 2; 4.50 to 4.75 mm) from Line I and Line C sows were hybridized to the Incyte UniGEM V1.0 human chip (approximately 7,000 gene probes). A second analysis was performed using mRNA from follicles (d 2; 4.50 to 5.00mm) hybridized to the IncyteUniGEM V2.0 human chip (approximately 9,100 gene probes). A total of 33 and 21 genes were identified with significant expression differences using UniGEM V1.0 and V2.0, respectively (twofold or greater relative expression following adjustment for expression of control probes). However, there was little overlap between results of the two hybridizations. Expression differences between lines for two genes, follistatin and nuclear receptor subfamily 4, group A, member 1, were confirmed using Northern hybridization. These results demonstrate changes in follicular gene expression as the result of long-term selection for enhanced reproduction. These correlated responses may directly represent allelic variation utilized by selection (e.g., quantitative trait loci), or more likely, transcriptional changes in other genes that interact with reproductive QTL. This work represents one of the first applications of gene expression analysis to evaluate long-term selection response in livestock populations.