Background: Runs of homozygosity (ROHs) are homozygous segments of the genome where the two haplotypes inherited from the parents are identical. The current availability of genotypes for a very large number of single nucleotide polymorphisms (SNPs) is leading to more accurate characterization of ROHs in the whole genome. Here, we investigated the occurrence and distribution of ROHs in 3,692 Large White pigs and compared estimates of inbreeding coefficients calculated based on ROHs (F_ROH), homozygosity (F_HOM), genomic relationship matrix (F_GRM) and pedigree (F_PED). Furthermore, we identified genomic regions with high ROH frequencies and annotated their candidate genes. Results: In total, 176,182 ROHs were identified from 3,569 animals, and all individuals displayed at least one ROH longer than 1 Mb. The ROHs identified were unevenly distributed on the autosomes. The highest and lowest coverages of Sus scrofa chromosomes (SSC) by ROH were on SSC14 and SSC13, respectively. The highest pairwise correlation among the different inbreeding coefficient estimates was 0.95 between F_{ROH_total} and F_HOM, while the lowest was − 0.083 between F_GRM and F_PED. The correlations between F_PED and F_ROH using four classes of ROH lengths ranged from 0.18 to 0.37 and increased with increasing ROH length, except for ROH > 10 Mb. Twelve ROH islands were located on four chromosomes (SSC1, 4, 6 and 14). These ROH islands harboured genes associated with reproduction, muscular development, fat deposition and adaptation, such as SIRT1, MYPN, SETDB1 and PSMD4. Conclusion: F_ROH can be used to accurately assess individual inbreeding levels compared to other inbreeding coefficient estimators. In the absence of pedigree records, F_ROH can provide an alternative to inbreeding estimates. Our findings can be used not only to effectively increase the response to selection by appropriately managing the rate of inbreeding and minimizing the negative effects of inbreeding depression but also to help detect genomic regions with an effect on traits under selection.

Total number born (TNB), number of stillborn (NSB), and gestation length (GL) are economically important traits in pig production, and disentangling the molecular mechanisms associated with traits can provide valuable insights into their genetic structure. Genotype imputation can be used as a practical tool to improve the marker density of single-nucleotide polymorphism (SNP) chips based on sequence data, thereby dramatically improving the power of genome-wide association studies (GWAS). In this study, we applied Beagle software to impute the 50 K chip data to the whole-genome sequencing (WGS) data with average imputation accuracy (R²) of 0.876. The target pigs, 2655 Large White pigs introduced from Canadian and French lines, were genotyped by a GeneSeek Porcine 50K chip. The 30 Large White reference pigs were the key ancestral individuals sequenced by whole-genome resequencing. To avoid population stratification, we identified genetic variants associated with reproductive traits by performing within-population GWAS and cross-population meta-analyses with data before and after imputation. Finally, several genes were detected and regarded as potential candidate genes for each of the traits: for the TNB trait: NOTCH2, KLF3, PLXDC2, NDUFV1, TLR10, CDC14A, EPC2, ORC4, ACVR2A, and GSC; for the NSB trait: NUB1, TGFBR3, ZDHHC14, FGF14, BAIAP2L1, EVI5, TAF1B, and BCAR3; for the GL trait: PPP2R2B, AMBP, MALRD1, HOXA11, and BICC1. In conclusion, expanding the size of the reference population and finding an optimal imputation strategy to ensure that more loci are obtained for GWAS under high imputation accuracy will contribute to the identification of causal mutations in pig breeding.

In pig, limb bone length influences ham yield and body height to a great extent and has important economic implications for pig industry. In this study, an intercross population was constructed between the indigenous Chinese Minzhu pig breed and the western commercial Large White pig breed to examine the genetic basis for variation in limb bone length. The aim of this study was to detect potential genetic variants associated with porcine limb bone length. A total of 571 F2 individuals from a Large White and Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip, and phenotyped for femur length (FL), humerus length (HL), hipbone length (HIPL), scapula length (SL), tibia length (TL), and ulna length (UL). A genome-wide association study was performed by applying the previously reported approach of genome-wide rapid association using mixed model and regression. Statistical significance of the associations was based on Bonferroni-corrected P-values. A total of 39 significant SNPs were mapped to a 11.93 Mb long region on pig chromosome 7 (SSC7). Linkage analysis of these significant SNPs revealed three haplotype blocks of 495 kb, 376 kb and 492 kb, respectively, in the 11.93 Mb region. Annotation based on the pig reference genome identified 15 genes that were located near or contained the significant SNPs in these linkage disequilibrium intervals. Conditioned analysis revealed that four SNPs, one on SSC2 and three on SSC4, showed significant associations with SL and HL, respectively. Analysis of the 15 annotated genes that were identified in these three haplotype blocks indicated that HMGA1 and PPARD, which are expressed in limbs and influence chondrocyte cell growth and differentiation, could be considered as relevant biological candidates for limb bone length in pig, with potential applications in breeding programs. Our results may also be useful for the study of the mechanisms that underlie human limb length and body height.

RNA editing is a co/posttranscriptional modification mechanism that increases the diversity of transcripts, with potential functional consequences. The advent of next-generation sequencing technologies has enabled the identification of RNA edits at unprecedented throughput and resolution. However, our knowledge of RNA editing in swine is still limited. Here, we utilized RES-Scanner to identify RNA editing sites in the brain, subcutaneous fat, heart, liver, muscle, lung and ovary in three 180-day-old Large White gilts based on matched strand-specific RNA sequencing and whole-genome resequencing datasets. In total, we identified 74863 editing sites, and 92.1% of these sites caused adenosine-to-guanosine (A-to-G) conversion. Most A-to-G sites were located in noncoding regions and generally had low editing levels. In total, 151 A-to-G sites were detected in coding regions (CDS), including 94 sites that could lead to nonsynonymous amino acid changes. We provide further evidence supporting a previous observation that pig transcriptomes are highly editable at PRE-1 elements. The number of A-to-G editing sites ranged from 4155 (muscle) to 25001 (brain) across the seven tissues. The expression levels of the ADAR enzymes could explain some but not all of this variation across tissues. The functional analysis of the genes with tissue-specific editing sites in each tissue revealed that RNA editing might play important roles in tissue function. Specifically, more pathways showed significant enrichment in the fat and liver than in other tissues, while no pathway was enriched in the muscle. This study identified a total of 74863 nonredundant RNA editing sites in seven tissues and revealed the potential importance of RNA editing in tissue function. Our findings largely extend the porcine editome and enhance our understanding of RNA editing in swine.

Intramuscular fat (IMF) content is a complex trait that affects meat quality and determines pork quality. In order to explore the potential mechanisms that affect the intramuscular fat content of pigs, a Large white × Min pigs F2 resource populations were constructed, then whole-transcriptome profile analysis was carried out for five low-IMF and five high-IMF F2 individuals. In total, 218 messenger RNA (mRNAs), 213 long non-coding RNAs (lncRNAs), 18 microRNAs (miRNAs), and 59 circular RNAs (circRNAs) were found to be differentially expressed in the longissimus dorsi muscle. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes annotations revealed that these differentially expressed (DE) genes or potential target genes (PTGs) of DE regulatory RNAs (lncRNAs, miRNAs, and circRNAs) are mainly involved in cell differentiation, fatty acid synthesis, system development, muscle fiber development, and regulating lipid metabolism. In total, 274 PTGs were found to be differentially expressed between low- and high-IMF pigs, which indicated that some DE regulatory RNAs may contribute to the deposition/metabolism of IMF by regulating their PTGs. In addition, we analyzed the quantitative trait loci (QTLs) of DE RNAs co-located in high- and low-IMF groups. A total of 97 DE regulatory RNAs could be found located in the QTLs related to IMF. Co-expression networks among different types of RNA and competing endogenous RNA (ceRNA) regulatory networks were also constructed, and some genes involved in type I diabetes mellitus were found to play an important role in the complex molecular process of intramuscular fat deposition. This study identified and analyzed some differential RNAs, regulatory RNAs, and PTGs related to IMF, and provided new insights into the study of IMF formation at the level of the genome-wide landscape.