Search

Additional file 1: Table S1. Summary statistics of meat quality traits in pigs.

Additional file 3: Table S2. The mean accuracy and bias values of GBLUP for meat quality traits using LD pruned SNPs.

Additional file 4: Table S3. The estimated heritability for meat quality traits using LD pruned SNPs.

Runs of homozygosity (ROH) are widely used to investigate genetic diversity, demographic history, and positive selection signatures of livestock. Commercial breeds provide excellent materials to reveal the landscape of ROH shaped during the intense selection process. Here, we used the GeneSeek Porcine 50K single-nucleotide polymorphism (SNP) Chip data of 3,770 American Duroc (AD) and 2,096 Canadian Duroc (CD) pigs to analyze the genome-wide ROH. First, we showed that AD had a moderate genetic differentiation with CD pigs, and AD had more abundant genetic diversity and significantly lower level of inbreeding than CD pigs. In addition, sows had larger levels of homozygosity than boars in AD pigs. These differences may be caused by differences in the selective intensity. Next, ROH hotspots revealed that many candidate genes are putatively under selection for growth, sperm, and muscle development in two lines. Population-specific ROHs inferred that AD pigs may have a special selection for female reproduction, while CD pigs may have a special selection for immunity. Moreover, in the overlapping ROH hotspots of two Duroc populations, we observed a missense mutation (rs81216249) located in the growth and fat deposition-related supergene (ARSB-DMGDH-BHMT) region. The derived allele of this variant originated from European pigs and was nearly fixed in Duroc pigs. Further selective sweep and association analyses indicated that this supergene was subjected to strong selection and probably contributed to the improvement of body weight and length in Duroc pigs. These findings will enhance our understanding of ROH patterns in different Duroc lines and provide promising trait-related genes and a functional-altering marker that can be used for genetic improvement of pigs.

Additional file 2: Table S2. Chromosome distribution of all 695 CNVRs detected in the porcine genome (based on Sscrofa 11.1 reference genome assembly).

Additional file 4: Table S4. Descriptive statistics and variance components of growth traits in Duroc pigs.

Additional file 1.Table S1. All the positive ion features.

Additional file 3: Figure S1. Principal Component Analysis (PCA) scores plots. The analysis was based on LC/MS data of fecal samples from H-FE (green) and L-FE (red) of (A) positive and (B) negative model. Figure S2. Clustering dendrogram and module-trait correlation plots. Each coloured row represents a colour-coded module which contains a group of highly connected metabolic features. A total of 14 and 14 modules was identified in (A) positive and (B) negative model, respectively. Figure S3. Soft-thresholding values estimation. Scale independence and mean connectivity of various soft-thresholding values (β) in (A) negative and (B) positive model.

To analyze the miRNA expression profiles in Lawsonia intracellularis-infected porcine intestines, infected pigs were first identified using PCR (Polymerase Chain Reaction). Then, RNA from infected intestines and control tissues were isolated and subjected to microarray analysis and RT-PCR. Results showed that a total of 83 miRNAs were differentially expressed between the infected samples and controls, out of which 53 were upregulated and 30 were downregulated. Validation using RT-PCR showed a high degree of confidence for the obtained data. Using the current miRBase release 21.0, nine groups of miRNAs were located in the same cluster, and three groups of miRNAs were found to belong to the same family. Interestingly, except for ssc-miR-10a-5p, all clustered miRNAs and the family members exhibited the same expression patterns. Pathway analysis of the putative gene targets of the differentially expressed miRNAs showed that they were involved in the immune response, amino acid metabolism and cell communication/growth/motility. Thus, the results indicate that altered miRNA expression profiles can affect immunity, metabolism and cellular processes.