Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.

The cow mammary transcriptome was explored at −30, −15, 1, 15, 30, 60, 120, 240, and 300 d relative to parturition. A total of 6,382 differentially expressed genes (DEG) at a false discovery rate ≤0.001 were found throughout lactation. The greatest number of DEG (>3,500 DEG) was observed at 60 and 120 d vs. −30 d with the largest change between consecutive time points observed at −15 vs. 1 d and 120 vs. 240 d. Functional analysis of microarray data was performed using the Dynamic Impact Approach (DIA). The DIA analysis of KEGG pathways uncovered as the most impacted and induced ‘Galactose metabolism’, ‘Glycosylphosphatidylinositol (GPI)-anchor biosynthesis’, and ‘PPAR signaling’; whereas, ‘Antigen processing and presentation’ was among the most inhibited. The integrated interpretation of the results suggested an overall increase in metabolism during lactation, particularly synthesis of carbohydrates and lipid. A marked degree of utilization of amino acids as energy source, an increase of protein export, and a decrease of the protein synthesis machinery as well cell cycle also were suggested by the DIA analysis. The DIA analysis of Gene Ontology and other databases uncovered an induction of Golgi apparatus and angiogenesis, and the inhibition of both immune cell activity/migration and chromosome modifications during lactation. All of the highly-impacted and activated functions during lactation were evidently activated at the onset of lactation and inhibited when milk production declined. The overall analysis indicated that the bovine mammary gland relies heavily on a coordinated transcriptional regulation to begin and end lactation. The functional analysis using DIA underscored the importance of genes associated with lactose synthesis, lipid metabolism, protein synthesis, Golgi, transport, cell cycle/death, epigenetic regulation, angiogenesis, and immune function during lactation.

The overrepresented approach (ORA) is the most widely-accepted method for functional analysis of microarray datasets. The ORA is computationally-efficient and robust; however, it suffers from the inability of comparing results from multiple gene lists particularly with time-course experiments or those involving multiple treatments. To overcome such limitation a novel method termed Dynamic Impact Approach (DIA) is proposed. The DIA provides an estimate of the biological impact of the experimental conditions and the direction of the impact. The impact is obtained by combining the proportion of differentially expressed genes (DEG) with the log2 mean fold change and mean –log P-value of genes associated with the biological term. The direction of the impact is calculated as the difference of the impact of up-regulated DEG and down-regulated DEG associated with the biological term. The DIA was validated using microarray data from a time-course experiment of bovine mammary gland across the lactation cycle. Several annotation databases were analyzed with DIA and compared to the same analysis performed by the ORA. The DIA highlighted that during lactation both BTA6 and BTA14 were the most impacted chromosomes; among Uniprot tissues those related with lactating mammary gland were the most positively-impacted; within KEGG pathways ‘Galactose metabolism’ and several metabolism categories related to lipid synthesis were among the most impacted and induced; within Gene Ontology “lactose biosynthesis” among Biological processes and “Lactose synthase activity” and “Stearoyl-CoA 9-desaturase activity” among Molecular processes were the most impacted and induced. With the exception of the terms ‘Milk’, ‘Milk protein’ and ‘Mammary gland’ among Uniprot tissues and SP_PIR_Keyword, the use of ORA failed to capture as significantly-enriched (i.e., biologically relevant) any term known to be associated with lactating mammary gland. Results indicate the DIA is a biologically-sound approach for analysis of time-course experiments. This tool represents an alternative to ORA for functional analysis.