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Abstract Background Past selection events left footprints in the genome of domestic animals, which can be traced back by stretches of homozygous genotypes, designated as runs of homozygosity (ROHs). The analysis of common ROH regions within groups or populations displaying potential signatures of selection requires high-quality SNP data as well as carefully adjusted ROH-defining parameters. In this study, we used a simultaneous testing of rule- and model-based approaches to perform strategic ROH calling in genomic data from different pig populations to detect genomic regions under selection for specific phenotypes. Results Our ROH analysis using a rule-based approach offered by PLINK, as well as a model-based approach run by RZooRoH demonstrated a high efficiency of both methods. It underlined the importance of providing a high-quality SNP set as input as well as adjusting parameters based on dataset and population for ROH calling. Particularly, ROHs ≤ 20 kb were called in a high frequency by both tools, but to some extent covered different gene sets in subsequent analysis of ROH regions common for investigated pig groups. Phenotype associated ROH analysis resulted in regions under potential selection characterizing heritage pig breeds, known to harbour a long-established breeding history. In particular, the selection focus on fitness-related traits was underlined by various ROHs harbouring disease resistance or tolerance-associated genes. Moreover, we identified potential selection signatures associated with ear morphology, which confirmed known candidate genes as well as uncovered a missense mutation in the ABCA6 gene potentially supporting ear cartilage formation. Conclusions The results of this study highlight the strengths and unique features of rule- and model-based approaches as well as demonstrate their potential for ROH analysis in animal populations. We provide a workflow for ROH detection, evaluating the major steps from filtering for high-quality SNP sets to intersecting ROH regions. Formula-based estimations defining ROHs for rule-based method show its limits, particularly for efficient detection of smaller ROHs. Moreover, we emphasize the role of ROH detection for the identification of potential footprints of selection in pigs, displaying their breed-specific characteristics or favourable phenotypes.

In Chinese pig populations in which crossbreeding is used, these animals show a level of weakness compared with their original purebred ancestors. For instance, in the Lulai pig, a newly developed Chinese breed that is raised on the basis of the Laiwu pig (a Chinese indigenous breed with exceptionally high intramuscular fat content) and the Yorkshire pig using a method of systematic crossbreeding, both their market acceptance and performance are inferior. To reveal the practical role of these admixed breeds and traditional systematic crossbreeding methods at the genomic level, we explored population structure, genetic signatures, and introgression. We conducted this study based on the SNP chip data of 381 Lulai pigs, 182 Laiwu pigs, and 127 Yorkshires, which showed deficient genome coverage during our study. Therefore, we further selected the Genotyping by Genome Reducing and Sequencing (GGRS) method, which has a high density and suitable genome coverage as a supplement. We applied the GGRS data of 38 Lulai pigs, 75 Laiwu pigs, and 75 Yorkshires. In terms of the SNP chip data, by Fst analysis, we detected 782 significantly different genes between Lulai pigs and Yorkshires, including 3 major genes associated with growth (LEPR) and meat quality (SCD and TBC1D1), and we detected 426 significantly different genes between Lulai pigs and Laiwu pigs. With rIBD, we detected 12 genomic regions that included 182 genes that Yorkshires introgressed to Lulai pigs, and we detected 27 genomic regions that included 229 genes with a major gene (SCD) that Laiwu pigs introgressed to Lulai pigs. Regarding the GGRS data, we detected 601 significantly different genes between Lulai pigs and Yorkshires by Fst analysis, including 3 major genes associated with growth and fat deposits (IGF2 and FTO) and with hair color (KIT), and we detected 634 significantly different genes between Lulai pigs and Laiwu pigs, including 3 major genes related to their body composition (MYPN), hair color (KIT), and ear size (PPARD). By rIBD, we detected 94 deep sections that included 363 genes that Yorkshires introgressed to Lulai pigs, and we detected 149 deep sections that included 727 genes with a major gene (ESR1) that Laiwu pigs introgressed to Lulai pigs. Altogether, this study provides both insight into the molecular background of synthesized breeds of Lulai pigs and a reference for the evaluation of systematic crossbreeding in China. [ABSTRACT FROM AUTHOR]

Background: Past selection events left footprints in the genome of domestic animals, which can be traced back by stretches of homozygous genotypes, designated as runs of homozygosity (ROHs). The analysis of common ROH regions within groups or populations displaying potential signatures of selection requires high-quality SNP data as well as carefully adjusted ROH-defining parameters. In this study, we used a simultaneous testing of rule- and model-based approaches to perform strategic ROH calling in genomic data from different pig populations to detect genomic regions under selection for specific phenotypes. Results: Our ROH analysis using a rule-based approach offered by PLINK, as well as a model-based approach run by RZooRoH demonstrated a high efficiency of both methods. It underlined the importance of providing a high-quality SNP set as input as well as adjusting parameters based on dataset and population for ROH calling. Particularly, ROHs ≤ 20 kb were called in a high frequency by both tools, but to some extent covered different gene sets in subsequent analysis of ROH regions common for investigated pig groups. Phenotype associated ROH analysis resulted in regions under potential selection characterizing heritage pig breeds, known to harbour a long-established breeding history. In particular, the selection focus on fitness-related traits was underlined by various ROHs harbouring disease resistance or tolerance-associated genes. Moreover, we identified potential selection signatures associated with ear morphology, which confirmed known candidate genes as well as uncovered a missense mutation in the ABCA6 gene potentially supporting ear cartilage formation. Conclusions: The results of this study highlight the strengths and unique features of rule- and model-based approaches as well as demonstrate their potential for ROH analysis in animal populations. We provide a workflow for ROH detection, evaluating the major steps from filtering for high-quality SNP sets to intersecting ROH regions. Formula-based estimations defining ROHs for rule-based method show its limits, particularly for efficient detection of smaller ROHs. Moreover, we emphasize the role of ROH detection for the identification of potential footprints of selection in pigs, displaying their breed-specific characteristics or favourable phenotypes. [ABSTRACT FROM AUTHOR]

Retrotransposons account for more than one-third of the pig reference genome. On account of the genome variability in different breeds, structural variation (SV) caused by retrotranspos-on-generated deletion or insertion (indel) may have a function in the genome. Litter size is one of the most important reproductive traits and significantly impacts profitability in terms of pig production. We used the method of bioinformatics, genetics, and molecular biology to make an analysis among different pig genomes. Predicted 100 SVs were annotated as retrotransposon indel in 20 genes related to reproductive performance. The PCR detection based on these predicted SVs revealed 20 RIPs in 20 genes, that most RIPs (12) were generated by SINE indel, and eight RIPs were generated by the ERV indel. We selected 12 RIPs to make the second round PCR detection in 24 individuals among nine pig breeds. The PCR detection results revealed that the RIP-A1CF-4 insertion in the breed of Bama, Large White, and Meishan only had the homozygous genotype but low to moderately polymorphisms were present in other breeds. We found that RIP-CWH43-9, RIP-IDO2-9, RIP-PRLR-6, RIP-VMP1-12, and RIP-OPN-1 had a rich polymorphism in the breed of Large White pigs. The statistical analysis revealed that RIP-CWH43-9 had a SINE insertion profitable to the reproductive traits of TNB and NBA but was significantly affected (p < 0.01) and (p < 0.05) in the reproductive traits of litter birthweight (LW) in Large White. On the other hand, the SINE insertion in IDO2-9 may be a disadvantage to the reproductive traits of LW, which was significantly affected (p < 0.05) in Large White. These two RIPs are significant in pig genome research and could be useful molecular markers in the breeding system. [ABSTRACT FROM AUTHOR]

The aim of this study was to detect evidence for signatures of recent selection in the Jinhua pig genome. These results can be useful to better understand the regions under selection in Jinhua pigs and might shed some lights on groups of genes that control production traits. In the present study, we performed extended haplotype homozygosity (EHH) tests to identify significant core regions in 202 Jinhua pigs. A total of 26 161 core regions spanning 636.42 Mb were identified, which occupied approximately 28% of the genome across all autosomes, and 1 158 significant (P

Abstract Background Retrotransposons are the major determinants of genome sizes and they have shaped both genes and genomes in mammalian organisms, but their overall activity, diversity, and evolution dynamics, particularly their impact on protein coding and lncRNA genes in pigs remain largely unknown. Results In the present study, we performed de novo detection of retrotransposons in pigs by using multiple pipelines, four distinct families of pig-specific L1 s classified into 51 distinct subfamilies and representing four evolution models and three expansion waves of pig-specific SINEs represented by three distinct families were identified. ERVs were classified into 18 families and found two most “modern” subfamilies in the pig genome. The transposition activity of pig L1 was verified by experiment, the sense and antisense promoter activities of young L1 5′UTRs and ERV LTRs and expression profiles of young retrotransposons in multiple tissues and cell lines were also validated. Furthermore, retrotransposons had an extensive impact on lncRNA and protein coding genes at both the genomic and transcriptomic levels. Most protein coding and lncRNA (> 80%) genes contained retrotransposon insertions, and about half of protein coding genes (44.30%) and one-fourth (24.13%) of lncRNA genes contained the youngest retrotransposon insertions. Nearly half of protein coding genes (43.78%) could generate chimeric transcripts with retrotransposons. Significant distribution bias of retrotransposon composition, location, and orientation in lncRNA and protein coding genes, and their transcripts, were observed. Conclusions In the current study, we characterized the classification and evolution profile of retrotransposons in pigs, experimentally proved the transposition activity of the young pig L1 subfamily, characterized the sense and antisense expression profiles and promoter activities of young retrotransposons, and investigated their impact on lncRNA and protein coding genes by defining the mobilome landscapes at the genomic and transcriptomic levels. These findings help provide a better understanding of retrotransposon evolution in mammal and their impact on the genome and transcriptome.

The domestic pig (Sus scrofa) is a species representative of the Suina, one of the four suborders within Cetartiodactyla. In this paper, we reported our analysis of the pig TRG locus in comparison with the loci of species representative of the Ruminantia, Tylopoda, and Cetacea suborders. The pig TRG genomic structure reiterates the peculiarity of the organization of Cetartiodactyla loci in TRGC "cassettes", each containing the basic V-J-J-C unit. Eighteen genes arranged in four TRGC cassettes, form the pig TRG locus. All the functional TRG genes were expressed, and the TRGV genes preferentially rearrange with the TRGJ genes within their own cassette, which correlates the diversity of the γ-chain repertoire with the number of cassettes. Among them, the TRGC5, located at the 5′ end of the locus, is the only cassette that retains a marked homology with the corresponding TRGC cassettes of all the analyzed species. The preservation of the TRGC5 cassette for such a long evolutionary time presumes a highly specialized function of its genes, which could be essential for the survival of species. Therefore, the maintenance of this cassette in pigs confirms that it is the most evolutionarily ancient within Cetartiodactyla, and it has undergone a process of duplication to give rise to the other TRGC cassettes in the different artiodactyl species in a lineage-specific manner. [ABSTRACT FROM AUTHOR]

Background: Beta-defensins (β-defensins) are innate immune peptides with evolutionary conservation across a wide range of species and has been suggested to play important roles in innate immune reactions against pathogens. However, the complete β-defensin repertoire in the pig has not been fully addressed. Result: A BLAST analysis was performed against the available pig genomic sequence in the NCBI database to identify β-defensin-related sequences using previously reported β-defensin sequences of pigs, humans, and cattle. The porcine β-defensin gene clusters were mapped to chromosomes 7, 14, 15 and 17. The gene expression analysis of 17 newly annotated porcine β-defensin genes across 15 tissues using semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) showed differences in their tissue distribution, with the kidney and testis having the largest pBD expression repertoire. We also analyzed single nucleotide polymorphisms (SNPs) in the mature peptide region of pBD genes from 35 pigs of 7 breeds. We found 8 cSNPs in 7 pBDs. Conclusion: We identified 29 porcine β-defensin (pBD) gene-like sequences, including 17 unreported pBDs in the porcine genome. Comparative analysis of β-defensin genes in the pig genome with those in human and cattle genomes showed structural conservation of β-defensin syntenic regions among these species. [ABSTRACT FROM AUTHOR]

Background: The pig is a biomedical model to study human and livestock traits. Many of these traits are controlled by neuropeptides that result from the cleavage of prohormones by prohormone convertases. Only 45 prohormones have been confirmed in the pig. Sequence homology can be ineffective to annotate prohormone genes in sequenced species like the pig due to the multifactorial nature of the prohormone processing. The goal of this study is to undertake the first complete survey of prohormone and prohormone convertases genes in the pig genome. These genes were functionally annotated based on 35 gene expression microarray experiments. The cleavage sites of prohormone sequences into potentially active neuropeptides were predicted. Results: We identified 95 unique prohormone genes, 2 alternative calcitonin-related sequences, 8 prohormone convertases and 1 cleavage facilitator in the pig genome 10.2 assembly and trace archives. Of these, 11 pig prohormone genes have not been reported in the UniProt, UniGene or Gene databases. These genes are intermedin, cortistatin, insulin-like 5, orexigenic neuropeptide QRFP, prokineticin 2, prolactin-releasing peptide, parathyroid hormone 2, urocortin, urocortin 2, urocortin 3, and urotensin 2-related peptide. In addition, a novel neuropeptide S was identified in the pig genome correcting the previously reported pig sequence that is identical to the rabbit sequence. Most differentially expressed prohormone genes were under-expressed in pigs experiencing immune challenge relative to the un-challenged controls, in non-pregnant relative to pregnant sows, in old relative to young embryos, and in non-neural relative to neural tissues. The cleavage prediction based on human sequences had the best performance with a correct classification rate of cleaved and non-cleaved sites of 92% suggesting that the processing of prohormones in pigs is similar to humans. The cleavage prediction models did not find conclusive evidence supporting the production of the bioactive neuropeptides urocortin 2, urocortin 3, torsin family2 member A, tachykinin 4, islet amyloid polypeptide, and calcitonin receptor-stimulating peptide 2 in the pig. Conclusions: The present genomic and functional characterization supports the use of the pig as an effective animal model to gain a deeper understanding of prohormones, prohormone convertases and neuropeptides in biomedical and agricultural research. [ABSTRACT FROM AUTHOR]