Heterozygosity and homozygosity regions affect reproductive success and the loss of reproduction: a case study with litter traits in pigs

Investigation of cosmopolitan and local Italian beef cattle breeds uncover common patterns of heterozygosity

The analysis of livestock heterozygosity is less common compared to the study of homozygous patterns. Heterozygous-Rich Regions (HRRs) may harbor significant loci for functional traits such as immune response, survival rate, and fertility. For this reason, this study was conducted to investigate and characterize the heterozygosity patterns of four beef cattle breeds, which included two cosmopolitan breeds (Limousine and Charolaise) and two local breeds (Sarda and Sardo Bruna). Our analysis identified regions with a high degree of heterozygosity using a consecutive runs approach, the Tajima D test, nucleotide diversity estimation, and Hardy Weinberg equilibrium test. These regions exhibited recurrent heterozygosity peaks and were consistently found on specific chromosomes across all breeds, specifically autosomes 15, 16, 20, and 23. The cosmopolitan and Sardo Bruna breeds also displayed peaks on autosomes 2 and 21, respectively. Thirty-five top runs shared by more than 25% of the populations were identified. These genomic fragments encompassed 18 genes, two of which are directly linked to male fertility, while four are associated with lactation. Two other genes play roles in survival and immune response. Our study also detected a region related to growth and carcass traits in Limousine breed. Our analysis of heterozygosity-rich regions revealed particular segments of the cattle genome linked to various functional traits. It appears that balancing selection is occurring in specific regions within the four examined breeds, and unexpectedly, they are common across cosmopolitan and local breeds. The genes identified hold potential for applications in breeding programs and conservation studies to investigate the phenotypes associated with these heterozygous genotypes. In addition, Tajima D test, Nucleotide diversity, and Hardy Weinberg equilibrium test confirmed the presence of heterozygous fragments found with Heterozygous-Rich Regions analysis.

Porcine Intestinal Mucosal Peptides Target Macrophage-Modulated Inflammation and Alleviate Intestinal Homeostasis in Dextrose Sodium Sulfate-Induced Colitis in Mice

Porcine intestinal mucosal proteins are novel animal proteins that contain large amounts of free amino acids and peptides. Although porcine intestinal mucosal proteins are widely used in animal nutrition, the peptide bioactivities of their enzymatic products are not yet fully understood. In the present study, we investigated the effect of porcine intestinal mucosal peptides (PIMP) on the RAW264.7 cell model of LPS-induced inflammation. The mRNA expression of inflammatory factors (interleukin 6, tumor necrosis factor-α, and interleukin-1β) and nitrous oxide levels were all measured by quantitative real-time PCR and cyclooxygenase-2 protein expression measured by Western blot. To investigate the modulating effect of PIMP and to establish a model of dextran sodium sulfate (DSS)-induced colitis in mice, we examined the effects of hematoxylin-eosin staining, myeloperoxidase levels, pro-inflammatory factor mRNA content, tight junction protein expression, and changes in intestinal flora. Nuclear factor κB pathway protein levels were also assessed by Western blot. PIMP has been shown in vitro to control inflammatory responses and prevent the activation of key associated signaling pathways. PIMP at doses of 100 and 400 mg/kg/day also alleviated intestinal inflammatory responses, reduced tissue damage caused by DSS, and improved intestinal barrier function. In addition, PIMP at 400 mg/kg/day successfully repaired the dysregulated gut microbiota and increased short-chain fatty acid levels. These findings suggest that PIMP may positively influence inflammatory responses and alleviate colitis. This study is the first to demonstrate the potential of PIMP as a functional food for the prevention and treatment of colitis.

Effect of genotyping density on the detection of runs of homozygosity and heterozygosity in cattle

Runs of homozygosity (ROHom) are contiguous stretches of homozygous regions of the genome. In contrast, runs of heterozygosity (ROHet) are heterozygosity-rich regions. The detection of these two types of genomic regions (ROHom and ROHet) is influenced by the parameters involved in their identification and the number of available single-nucleotide polymorphisms (SNPs). The present study aimed to test the effect of chip density in detecting ROHom and ROHet in the Italian Simmental cattle breed. A sample of 897 animals were genotyped at low density (50k SNP; 397 individuals), medium density (140k SNP; 348 individuals), or high density (800k SNP; 152 individuals). The number of ROHom and ROHet per animal (nROHom and nROHet, respectively) and their average length were calculated. ROHom or ROHet shared by more than one animal and the number of times a particular SNP was inside a run were also computed (SNPROHom and SNPROHet). As the chip density increased, the nROHom increased, whereas their average length decreased. In contrast, the nROHet decreased and the average length increased as the chip density increased. The most repeated ROHom harbored no genes, whereas in the most repeated ROHet four genes (SNRPN, SNURF, UBE3A, and ATP10A) previously associated with reproductive traits were found. Across the 3 datasets, 31 SNP, located on Bos taurus autosome (BTA) 6, and 37 SNP (located on BTA21) exceeded the 99th percentile in the distribution of the SNPROHom and SNPROHet, respectively. The genomic region on BTA6 mapped the SLIT2, PACRGL, and KCNIP4 genes, whereas 19 and 18 genes were mapped on BTA16 and BTA21, respectively. Interestingly, most of genes found through the ROHet analysis were previously reported to be related to health, reproduction, and fitness traits. The results of the present study confirm that the detection of ROHom is more reliable when the chip density increases, whereas the ROHet trend seems to be the opposite. Genes and quantitative trait loci (QTL) mapped in the highlighted regions confirm that ROHet can be due to balancing selection, thus related to fitness traits, health, and reproduction, whereas ROHom are mainly involved in production traits. The results of the present study strengthened the usefulness of these parameters in analyzing the genomes of livestock and their biological meaning.

Characterization of heterozygosity-rich regions in Italian and worldwide goat breeds

Heterozygosity-rich regions (HRR) are genomic regions of high heterozygosity, which may harbor loci related to key functional traits such as immune response, survival rate, fertility, and other fitness traits. This study considered 30 Italian and 19 worldwide goat breeds genotyped with the Illumina GoatSNP50k BeadChip. The aim of the work was to study inter-breed relationships and HRR patterns using Sliding Window (SW) and Consecutive Runs (CR) detection methods. Genetic relationships highlighted a clear separation between non-European and European breeds, as well as the north-south geographic cline within the latter. The Pearson correlation coefficients between the descriptive HRR parameters obtained with the SW and CR methods were higher than 0.9. A total of 166 HRR islands were detected. CHI1, CHI11, CHI12 and CHI18 were the chromosomes harboring the highest number of HRR islands. The genes annotated in the islands were linked to various factors such as productive, reproductive, immune, and environmental adaptation mechanisms. Notably, the Montecristo feral goat showed the highest number of HRR islands despite the high level of inbreeding, underlining potential balancing selection events characterizing its evolutionary history. Identifying a species-specific HRR pattern could provide a clearer view of the mechanisms regulating the genome modelling following anthropogenic selection combined with environmental interaction.

Genome-wide association studies for economically important traits in mink using copy number variation

Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.

Genome-wide single nucleotide polymorphism (SNP) data reveal potential candidate genes for litter traits in a Yorkshire pig population

The litter trait is one of the most important economic traits, and increasing litter size is of great economic value in the pig industry. However, the molecular mechanisms underlying pig litter traits remain elusive. To identify molecular markers and candidate genes for pig litter traits, a genome-wide association study (GWAS) and selection signature analysis were conducted in a Yorkshire pig population. A total of 518 producing sows were genotyped with Illumina Porcine SNP 50 BeadChip, and 1969 farrowing records for the total number born (TNB), the number born alive (NBA), piglets born dead (PBD), and litter weight born alive (LWB) were collected. Then, a GWAS was performed for the four litter traits using a repeatability model. Based on the estimated breeding values (EBVs) of TNB, 15 high- and 15 low-prolificacy individuals were selected from the 518 sows to implement selection signature analysis. Subsequently, the selection signatures affecting the litter traits of sows were detected by using two methods including the fixation index (FST) and θ π . Combining the results of the GWAS and selection signature analysis, 20 promising candidate genes (NKAIN2, IGF1R, KISS1R, TYRO3, SPINT1, ADGRF5, APC2, PTBP1, CLCN3, CBR4, HPF1, FAM174A, SCP2, CLIC1, ZFYVE9, SPATA33, KIF5C, EPC2, GABRA2, and GABRA4) were identified. These findings provide novel insights into the genetic basis of pig litter traits and will be helpful for improving the reproductive performances of sows in pig breeding.

Genomic Scanning of Inbreeding Depression for Litter Size in Two Varieties of Iberian Pigs

Inbreeding depression is expected to be more pronounced in fitness-related traits, such as pig litter size. Recent studies have suggested that the genetic determinism of inbreeding depression may be heterogeneous across the genome. Therefore, the objective of this study was to conduct a genomic scan of the whole pig autosomal genome to detect the genomic regions that control inbreeding depression for litter size in two varieties of Iberian pigs (Entrepelado and Retinto). The datasets consisted of 2069 (338 sows) and 2028 (327 sows) records of litter size (Total Number Born and Number Born Alive) for the Entrepelado and Retinto varieties. All sows were genotyped using the Geneseek GGP PorcineHD 70 K chip. We employed the Unfavorable Haplotype Finder software to extract runs of homozygosity (ROHs) and conducted a mixed-model analysis to identify highly significant differences between homozygous and heterozygous sows for each specific ROH. A total of eight genomic regions located on SSC2, SSC5, SSC7, SSC8, and SSC13 were significantly associated with inbreeding depression, housing some relevant genes such as FSHR, LHCGR, CORIN, AQP6, and CEP120.

Genome-wide population structure, homozygosity, and heterozygosity patterns of Nero Siciliano pig in the framework of Italian and cosmopolitan breeds

Analysis of genomic data is becoming more and more common for the effective management of livestock breeding programmes, even in the case of local populations. In this work, the genome-wide data of Nero Siciliano pig breed were compared to that of wild boar, Italian local and cosmopolitan breeds to investigate its genetic structure, and runs of homozygosity (ROH) and heterozygosity patterns. The Nero Siciliano has been reported to have the highest rate of genetic diversity among the Italian breeds, and a genetic variability comparable to that of the cosmopolitan breeds. Analyses of genomic structure and relationships underlined its proximity to wild boar, and an internal substructure probably linked to different family lines. The breed showed a low value of inbreeding estimated from ROH, and the highest diversity index among the Italian breeds, even if lower than that of the cosmopolitans. Four ROH islands in three chromosomes (SSC8, SSC11, and SSC14) and one heterozygosity-rich region (SSC1) were identified in Nero Siciliano, highlighting genomic regions related to productive QTL. Across breeds, SSC8 and SSC14 were the chromosomes with most ROH islands, with Mora Romagnola and wild boar showing the highest level of autozygosity. Chromosomes SSC2, SSC6, SSC8 and SSC13 showed the majority of runs of heterozygosity regions, mainly found in the cosmopolitan pig breeds, which reported several genes associated with health-related QTL. The outlined results can help to better identify the genomic profile of this local breed in order to plan matings, maintain adequate internal diversity and exploit the production system.

GWAS of Reproductive Traits in Large White Pigs on Chip and Imputed Whole-Genome Sequencing Data

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.