BackgroundTranscriptome variability is due to genetic and environmental causes, much like any other complex phenotype. Ascertaining the transcriptome differences between individuals is an important step to understand how selection and genetic drift may affect gene expression. To that end, extant divergent livestock breeds offer an ideal genetic material.ResultsWe have analyzed with microarrays five tissues from the endocrine axis (hypothalamus, adenohypophysis, thyroid gland, gonads and fat tissue) of 16 pigs from both sexes pertaining to four extreme breeds (Duroc, Large White, Iberian and a cross with SinoEuropean hybrid line). Using a Bayesian linear model approach, we observed that the largest breed variability corresponded to the male gonads, and was larger than at the remaining tissues, including ovaries. Measurement of sex hormones in peripheral blood at slaughter did not detect any breed-related differences. Not unexpectedly, the gonads were the tissue with the largest number of sex biased genes. There was a strong correlation between sex and breed bias expression, although the most breed biased genes were not the most sex biased genes. A combined analysis of connectivity and differential expression suggested three biological processes as being primarily different between breeds: spermatogenesis, muscle differentiation and several metabolic processes.ConclusionThese results suggest that differences across breeds in gene expression of the male gonads are larger than in other endocrine tissues in the pig. Nevertheless, the strong presence of breed biased genes in the male gonads cannot be explained solely by changes in spermatogenesis nor by differences in the reproductive tract development.
Impact of breed and sex on porcine endocrine transcriptome: a bayesian biometrical analysis
M. Pérez-Enciso,A. L. Ferraz,A. Ojeda,M. López‐Béjar
Published 2009 in BMC Genomics
ABSTRACT
PUBLICATION RECORD
- Publication year
2009
- Venue
BMC Genomics
- Publication date
2009-02-24
- Fields of study
Agricultural and Food Sciences, Medicine, Biology
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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