A Single-Step Genome Wide Association Study on Body Size Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

Whole genome and transcriptome analyses identify genetic markers associated with growth traits in Qinchuan black pig

BACKGROUND

Growth traits are economically important traits in pig breeding. However, the genetic mechanism of growth traits is still unclear. Qinchuan Black (QCB) pigs are crossbred and produced by hybridizing Guanzhong Black (GZB) pigs and Large White (LW) pigs, its characteristics include fast growth and excellent meat quality. In this study, whole genome and transcriptome analyses revealed the candidate genes associated with growth traits in QCB pigs based on imputed low-coverage whole-genome resequencing data.

RESULTS

In total, we used 197 low-depth whole-genome resequencing data with an average depth of 3.5X, and then the data were imputed to resequencing data using SWIM reference panel, the imputation accuracy parameters, allele frequency r2 and concordance rate were 0.86 and 95.83%, respectively. We used two methods to investigate the candidate genes affecting the growth traits of QCB pigs, a total of 371 PSGs were identified, which related to muscle tissue development, tissue development and system development. A total of 30,489,782 SNPs were retained. A GWAS of ten growth traits by using fixed and random model circulating probability unification (FarmCPU) model, was performed in QCB pigs. We discovered seven genome wide significant SNPs and eight genome wide suggestive significant SNPs associated with body weight at 2 months (2-BW), body length at 2 months (2-BL), body height at 2 months (2-BH) and body height at 4 months (4-BH), and eighteen potential candidate genes were discovered. Transcriptomic data revealed that 18 differentially expression genes related to muscle and growth and development. Additionally, whole genome and transcriptome analyses found six genes (TENM3, CTNND2, RIMS1, PCDH7, ADGRL3 and CTNNA3) may affect the growth traits in Qinchuan Black pigs.

CONCLUSION

Our study shows that more candidate genes associated with pig growth traits can be identified by whole genome and transcriptome analyses. We found that six genes may be new key candidate genes affecting pig growth traits. In conclusion, this study elucidated the molecular genetic mechanisms of growth traits and identified new molecular breeding targets, offering a robust scientific basis for advancing breeding strategies and genetic investigations within this breed.

Assessing the relationship between the gut microbiota and growth traits in Chinese indigenous pig breeds

BACKGROUND

Gut microbiota plays crucial roles in host metabolism, diseases and development. It has also been reported to be associated with growth performance in pigs. However, the bacterial species influencing pig growth performance have not been isolated, and the mechanisms remain unclear.

RESULTS

In this study, we collected 500 gut microbial samples from two Chinese indigenous pig breeds, including 244 fecal samples from Bamaxiang (BMX) pigs and 256 cecum content samples from Erhualian (EHL) pigs, to investigate the relationship between gut microbiota and pig growth traits. Bacterial compositions were determined by 16 S rRNA gene sequencing, and association analysis was performed using a two-part model. We found that the Firmicutes-to-Bacteroidota ratio in fecal samples from BMX pigs was negatively associated with average daily gain (P = 0.0085). Amplicon sequence variants (ASVs) belonging to Prevotella and three ASVs annotated to Oscillospiraceae were negatively associated with pig growth traits, while ASVs annotated to Muribaculaceae and Rikenellaceae showed positive correlations with growth traits in BMX fecal samples. In cecum content samples from EHL pigs, ASVs belonging to Prevotella, Lactobacillus delbrueckii, and Lachnospiraceae were negatively associated with growth performance, whereas one ASV belonging to Rikenellaceae demonstrated a positive association. Predicted functional capacity analysis revealed that metabolic pathways related to the digestive system, glycan biosynthesis and metabolism, signaling molecules and interactions, and xenobiotics biodegradation and metabolism were positively associated with pig growth traits. Conversely, the excretory system pathway showed a negative correlation. These pathways were found to correlate with growth trait-associated bacterial ASVs, suggesting that alterations in gut bacterial composition led to functional capacity shifts in the gut microbiome, subsequently affecting porcine growth.

CONCLUSIONS

Our results gave significant insights about the effect of gut microbiota on pig growth and provided important evidence to support further isolation of bacterial taxa that influence pig growth for elucidating their mechanisms.

Genome-Wide Runs of Homozygosity Reveal Inbreeding Levels and Trait-Associated Candidate Genes in Diverse Sheep Breeds

BACKGROUND

Quantifying and controlling the inbreeding level in livestock populations is crucial for the long-term sustainability of animal husbandry. However, the extent of inbreeding has not been fully understood in sheep populations on a global scale.

METHODS

Here, we analyzed high-depth genomes of 210 sheep from 20 worldwide breeds to identify the pattern and distribution of genome-wide runs of homozygosity (ROH) and detect candidate selected genes in ROH islands for agronomic and phenotypic traits.

RESULTS

Leveraging whole-genome sequencing data, we found a large number of short ROH (e.g., <1.0 Mb) in all breeds and observed the overall higher values of ROH statistics and inbreeding coefficient in European breeds than in Asian breeds and Dorper sheep. We identified some well-known candidate genes (e.g., CAMK4, HOXA gene family, ALOX12, FGF11, and MTOR) and 40 novel genes (e.g., KLHL1, FGFRL1, WDR62, GDF6, KHDRBS2, and PAX1) that are functionally associated with fecundity, body size, and wool-related traits in sheep. Based on the candidate genes, we revealed different genetic bases for the fecundity traits of European and Asian sheep.

CONCLUSIONS

This study improves the resolution of ROH detection and provides new insights into genomic inbreeding and trait architecture in sheep as well as useful markers for future breeding practice.

Identification of selection signatures and genetic diversity in the sheep

In the study, data obtained from OvineSNP50K SNP chips using the Illumina® iScan platform for Eşme sheep were used. The integrated haplotype score (iHS) and runs of homozygosity (ROH) statistical approaches were used to identify selection signatures. Using the iHS analysis, it was discovered that there are 10 genomic regions and 51 genes on ovine chromosomes 1, 9, 11, and 12 that are under selection. Three genomic regions and 97 genes on ovine chromosomes 6 and 11 were found to be under selection using the ROH analysis. Candidate genes associated with economic and ecological traits were detected using both approaches. Among the genetic diversity parameters considered in this study, the minor allele frequency (MAF), the genetic distance between individuals (D), as well as observed (Ho) and expected heterozygosities (He) values were 0.300, 0.309, 0.388, and 0.390, respectively. The obtained Ho, He and D values indicate a moderate level of genetic diversity. The ratio of polymorphic SNPs (PN) was 0.947, and the average values of FROH and FHOM were 0.030 and 0.029, respectively. Considering the PN value obtained in the study, it is evident that the SNPs in the population exhibit a high level of polymorphism at 94.7%. While the FROH value obtained indicates high genetic diversity among the individuals in the present study, the FHOM value suggests that the population is predominantly composed of heterozygous individuals. As a result, evidence indicating genetic advancements have been made for target traits in breeding programs within the population. Additionally, candidate genes suitable for future molecular marker-supported breeding programs have been identified. In addition, a better understanding of the genetic structure and production potential of the population has been achieved. Findings have shown that Eşme sheep are a breed with high meat production potential and strong adaptation abilities.

Integration of ssGWAS and ROH analyses for uncovering genetic variants associated with reproduction traits in Large White pigs

The low heritability of reproduction traits such as total number born (TNB), number born alive (NBA) and adjusted litter weight until 21 days at weaning (ALW) poses a challenge for genetic improvement. In this study, we aimed to identify genetic variants that influence these traits and evaluate the accuracy of genomic selection (GS) using these variants as genomic features. We performed single-step genome-wide association studies (ssGWAS) on 17 823 Large White (LW) pigs, of which 2770 were genotyped by 50K single nucleotide polymorphism (SNP) chips. Additionally, we analyzed runs of homozygosity (ROH) in the population and tested their effects on the traits. The genomic feature best linear unbiased prediction (GFBLUP) was then carried out in an independent population of 350 LW pigs using identified trait-related SNP subsets as genomic features. As a result, our findings identified five, one and four SNP windows that explaining more than 1% of genetic variance for ALW, TNB, and NBA, respectively and discovered 358 hotspots and nine ROH islands. The ROH SSC1:21814570-27186456 and SSC11:7220366-14276394 were found to be significantly associated with ALW and NBA, respectively. We assessed the genomic estimated breeding value accuracy through 20 replicates of five-fold cross-validation. Our findings demonstrate that GFBLUP, incorporating SNPs located in effective ROH (p-value < 0.05) as genomic features, might enhance GS accuracy for ALW compared with GBLUP. Additionally, using SNPs explaining more than 0.1% of the genetic variance in ssGWAS for NBA as genomic features might improve the GS accuracy, too. However, it is important to note that the incorporation of inappropriate genomic features can significantly reduce GS accuracy. In conclusion, our findings provide valuable insights into the genetic mechanisms of reproductive traits in pigs and suggest that the ssGWAS and ROH have the potential to enhance the accuracy of GS for reproductive traits in LW pigs.

Expression genome-wide association study identifies key regulatory variants enriched with metabolic and immune functions in four porcine tissues

BACKGROUND

Integration of high throughput DNA genotyping and RNA-sequencing data enables the discovery of genomic regions that regulate gene expression, known as expression quantitative trait loci (eQTL). In pigs, efforts to date have been mainly focused on purebred lines for traits with commercial relevance as such growth and meat quality. However, little is known on genetic variants and mechanisms associated with the robustness of an animal, thus its overall health status. Here, the liver, lung, spleen, and muscle transcriptomes of 100 three-way crossbred female finishers were studied, with the aim of identifying novel eQTL regulatory regions and transcription factors (TFs) associated with regulation of porcine metabolism and health-related traits.

RESULTS

An expression genome-wide association study with 535,896 genotypes and the expression of 12,680 genes in liver, 13,310 genes in lung, 12,650 genes in spleen, and 12,595 genes in muscle resulted in 4,293, 10,630, 4,533, and 6,871 eQTL regions for each of these tissues, respectively. Although only a small fraction of the eQTLs were annotated as cis-eQTLs, these presented a higher number of polymorphisms per region and significantly stronger associations with their target gene compared to trans-eQTLs. Between 20 and 115 eQTL hotspots were identified across the four tissues. Interestingly, these were all enriched for immune-related biological processes. In spleen, two TFs were identified: ERF and ZNF45, with key roles in regulation of gene expression.

CONCLUSIONS

This study provides a comprehensive analysis with more than 26,000 eQTL regions identified that are now publicly available. The genomic regions and their variants were mostly associated with tissue-specific regulatory roles. However, some shared regions provide new insights into the complex regulation of genes and their interactions that are involved with important traits related to metabolism and immunity.

Weighted single-step genome-wide association study for direct and maternal genetic effects associated with birth and weaning weights in sheep

Body weight is an important economic trait for sheep meat production, and its genetic improvement is considered one of the main goals in the sheep breeding program. Identifying genomic regions that are associated with growth-related traits accelerates the process of animal breeding through marker-assisted selection, which leads to increased response to selection. In this study, we conducted a weighted single-step genome-wide association study (WssGWAS) to identify potential candidate genes for direct and maternal genetic effects associated with birth weight (BW) and weaning weight (WW) in Baluchi sheep. The data used in this research included 13,408 birth and 13,170 weaning records collected at Abbas-Abad Baluchi Sheep Breeding Station, Mashhad-Iran. Genotypic data of 94 lambs genotyped by Illumina 50K SNP BeadChip for 54,241 markers were used. The proportion of variance explained by genomic windows was calculated by summing the variance of SNPs within 1 megabase (Mb). The top 10 window genomic regions explaining the highest percentages of additive and maternal genetic variances were selected as candidate window genomic regions associated with body weights. Our findings showed that for BW, the top-ranked genomic regions (1 Mb windows) explained 4.30 and 4.92% of the direct additive and maternal genetic variances, respectively. The direct additive genetic variance explained by the genomic window regions varied from 0.31 on chromosome 1 to 0.59 on chromosome 8. The highest (0.84%) and lowest (0.32%) maternal genetic variances were explained by genomic windows on chromosome 10 and 17, respectively. For WW, the top 10 genomic regions explained 6.38 and 5.76% of the direct additive and maternal genetic variances, respectively. The highest and lowest contribution of direct additive genetic variances were 1.37% and 0.42%, respectively, both explained by genomic regions on chromosome 2. For maternal effects on WW, the highest (1.38%) and lowest (0.41%) genetic variances were explained by genomic windows on chromosome 2. Further investigation of these regions identified several possible candidate genes associated with body weight. Gene ontology analysis using the DAVID database identified several functional terms, such as translation repressor activity, nucleic acid binding, dehydroascorbic acid transporter activity, growth factor activity and SH2 domain binding.

Association analysis between Acetyl-Coenzyme A Acyltransferase-1 gene polymorphism and growth traits in Xiangsu pigs

Introduction

Acetyl-Coenzyme A Acyltransferase-1 (ACAA1) is a peroxisomal acyltransferase involved in fatty acid metabolism. Current evidence does not precisely reveal the effect of the ACAA1 gene on pig growth performance.

Methods

The present study assessed the mRNA expression levels of the ACAA1 gene in the heart, liver, spleen, lung, kidney of 6-month-old Xiangsu pigs and in the longissimus dorsi muscle at different growth stages (newborn, 6 months and 12 months of age) using RT-qPCR. The relationship between single-nucleotide polymorphisms (SNPs) of ACAA1 gene and growth traits in 6-month-old and 12-month-old Xiangsu pigs was investigated on 184 healthy Xiangsu pigs using Sanger sequencing.

Results

The ACAA1 gene was expressed in heart, liver, spleen, lung, kidney, and longissimus dorsi muscle of 6-month-old pigs, with the highest level of expression in the liver. ACAA1 gene expression in the longissimus dorsi muscle decreased with age (p < 0.01). In addition, four SNPs were identified in the ACAA1 gene, including exon g.48810 A>G (rs343060194), intron g.51546 T>C (rs319197012), exon g.55035 T>C (rs333279910), and exon g.55088 C>T (rs322138947). Hardy-Weinberg equilibrium (p > 0.05) was found for the four SNPs, and linkage disequilibrium (LD) analysis revealed a strong LD between g.55035 T>C (rs333279910) and g.55088 C>T (rs322138947) (r 2 = 1.000). Association analysis showed that g.48810 A>G (rs343060194), g.51546 T>C (rs319197012), g.55035 T>C (rs333279910), and g.55088 C>T (rs322138947) varied in body weight, body length, body height, abdominal circumference, leg and hip circumference and living backfat thickness between 6-month-old and 12-month-old Xiangsu pigs.

Conclusion

These findings strongly demonstrate that the ACAA1 gene can be exploited for marker-assisted selection to improve growth-related phenotypes in Xiangsu pigs and present new candidate genes for molecular pig breeding.

Genome-Wide Association Study of Body Conformation Traits in Tashi Goats (Capra hircus)

Identifying genetic markers of economically valuable traits has practical benefits for the meat goat industry. To better understand the genomic variations influencing body conformation traits, a genome-wide association study was performed on Tashi goats, an indigenous Chinese goat breed. A total of 155 Tashi goats were phenotyped for eight body conformation traits: body height, body length, chest depth, chest width, chest girth, rump width, rump height, and cannon bone circumference. Then, 100 Tashi goats were randomly selected for whole-genome sequencing and genotyped. We obtained 1676.4 Gb of raw data with an average sequencing depth of 6.2X. Clean reads were aligned to the ARS1.2 reference genome, and 11,257,923 single nucleotide polymorphisms (SNPs) were identified. The structure analysis showed that these Tashi goats were almost not genetically related. The 109, 20, 52, 14, 62, 51, 70, and 7 SNPs were significantly associated with body height, body length, chest depth, chest width, chest girth, rump width, rump height, and cannon bone circumference. Within the ±500 kb region of significant SNPs, 183 genes were annotated. The most significantly enriched KEGG pathway was "olfactory transduction", and the most significantly enriched gene ontology (GO) terms were "cellular process", "cellular anatomical entity", and "molecular transducer activity". Interestingly, we found several SNPs on chromosomes 10 and 11 that have been identified multiple times for all eight body conformation traits located in two fragments (114 kb and 1.03 Mb). In chr.10:25988403-26102739, the six SNPs were tightly linked, the TACTAG genotype was the highest at 91.8%, and the FNTB (Farnesyltransferase, CAAX Box Beta) and CHURC1 (Churchill Domain Containing 1) genes were located. In chr.11:88216493-89250659, ten SNPs were identified with several dependent linkage disequilibrium (LD) blocks, and seven related genes were annotated, but no significant SNP was located in them. Our results provide valuable biological information for improving growth performance with practical applications for genomic selection in goats.

Unravelling novel and pleiotropic genes for cannon bone circumference and bone mineral density in Yorkshire pigs

Leg weakness is a prevalent health condition in pig farms. The augmentation of cannon bone circumference and bone mineral density can effectively improve limb strength in pigs and alleviate leg weakness. This study measured forelimb cannon bone circumference (fCBC) and rear limb cannon bone circumference (rCBC) using an inelastic tapeline and rear limb metatarsal area bone mineral density (raBMD) using a dual-energy X-ray absorptiometry bone density scanner. The samples of Yorkshire castrated boars were genotyped using a 50K single-nucleotide polymorphism (SNP) array. The SNP-chip data were imputed to the level of whole-genome sequencing data (iWGS). This study used iWGS data to perform genome-wide association studies and identified novel significant SNPs associated with fCBC on SSC6, SSC12, and SSC13, rCBC on SSC12 and SSC14, and raBMD on SSC7. Based on the high phenotypic and genetic correlations between CBC and raBMD, multi-trait meta-analysis was performed to identify pleiotropic SNPs. A significant potential pleiotropic quantitative trait locus (QTL) regulating both CBC and raBMD was identified on SSC15. Bayes fine mapping was used to establish the confidence intervals for these novel QTLs with the most refined confidence interval narrowed down to 56 kb (15.11 to 15.17 Mb on SSC12 for fCBC). Furthermore, the confidence interval for the potential pleiotropic QTL on SSC15 in the meta-analysis was narrowed down to 7.45 kb (137.55 to137.56 Mb on SSC15). Based on the biological functions of genes, the following genes were identified as novel regulatory candidates for different phenotypes: DDX42, MYSM1, FTSJ3, and MECOM for fCBC; SMURF2, and STC1 for rCBC; RGMA for raBMD. Additionally, RAMP1, which was determined to be located 23.68 kb upstream of the confidence interval of the QTL on SSC15 in the meta-analysis, was identified as a potential pleiotropic candidate gene regulating both CBC and raBMD. These findings offered valuable insights for identifying pathogenic genes and elucidating the genetic mechanisms underlying CBC and BMD.

Genetic evaluation for production and body size traits using different animal models in purebred-Duroc pigs

Duroc pigs are popular crossbred terminal sires, and accurate assessment of genetic parameters in the population can help to rationalize breeding programmes. The principle aim of this study were to evaluate the genetic parameters of production (birth weight, BW; age at 115 kg, AGE; feed conversion ratio, FCR) and body size (body length, BL; body height, BH; front cannon circumference, FCC) traits of Duroc pigs. The second objective was to analyze the fit of different genetic assessment models. The variance components and correlations of BW (28,348 records), AGE (28,335 records), FCR (11,135 records), BL (31,544 records), BH (21,862 records), and FCC (14,684 records) traits were calculated by using DMU and AIREMLF90 from BLUPF90 package. In the common environment model, the heritability of BW, AGE, FCR, BL, BH, and FCC traits were 0.17 ± 0.014, 0.30 ± 0.019, 0.28 ± 0.024, 0.16 ± 0.013, 0.14 ± 0.017, and 0.081 ± 0.016, with common litter effect values of 0.25, 0.20, 0.18, 0.23, 0.19, and 0.16, respectively. According to the results of the Akaike information criterion (AIC) calculations, models with smaller AIC values have a better fit. We found that the common environment model with litter effects as random effects for estimating genetic parameters had a better fit. In this Model, the estimated genetic correlations between AGE with BW, FCR, BL, BH, and FCC traits were -0.28 (0.040), 0.76 (0.038), -0.71 (0.036), -0.44 (0.060), and -0.60 (0.073), respectively, with phenotypic correlations of -0.17, 0.52, -0.22, -0.13 and -0.24, respectively. In our analysis of genetic trends for six traits in the Duroc population from 2012 to 2021, we observed significant genetic trends for AGE, BL, and BH. Particularly noteworthy is the rapid decline in the genetic trend for AGE, indicating an enhancement in the pig's growth rate through selective breeding. Therefore, we believe that some challenging-to-select traits can benefit from the genetic correlations between traits. By selecting easily measurable traits, they can gain from synergistic selection effects, leading to genetic progress. Conducting population genetic parameter analysis can assist us in devising breeding strategies.

Genetic dissection and genomic prediction for pork cuts and carcass morphology traits in pig

BACKGROUND

As pre-cut and pre-packaged chilled meat becomes increasingly popular, integrating the carcass-cutting process into the pig industry chain has become a trend. Identifying quantitative trait loci (QTLs) of pork cuts would facilitate the selection of pigs with a higher overall value. However, previous studies solely focused on evaluating the phenotypic and genetic parameters of pork cuts, neglecting the investigation of QTLs influencing these traits. This study involved 17 pork cuts and 12 morphology traits from 2,012 pigs across four populations genotyped using CC1 PorcineSNP50 BeadChips. Our aim was to identify QTLs and evaluate the accuracy of genomic estimated breed values (GEBVs) for pork cuts.

RESULTS

We identified 14 QTLs and 112 QTLs for 17 pork cuts by GWAS using haplotype and imputation genotypes, respectively. Specifically, we found that HMGA1, VRTN and BMP2 were associated with body length and weight. Subsequent analysis revealed that HMGA1 primarily affects the size of fore leg bones, VRTN primarily affects the number of vertebrates, and BMP2 primarily affects the length of vertebrae and the size of hind leg bones. The prediction accuracy was defined as the correlation between the adjusted phenotype and GEBVs in the validation population, divided by the square root of the trait's heritability. The prediction accuracy of GEBVs for pork cuts varied from 0.342 to 0.693. Notably, ribs, boneless picnic shoulder, tenderloin, hind leg bones, and scapula bones exhibited prediction accuracies exceeding 0.600. Employing better models, increasing marker density through genotype imputation, and pre-selecting markers significantly improved the prediction accuracy of GEBVs.

CONCLUSIONS

We performed the first study to dissect the genetic mechanism of pork cuts and identified a large number of significant QTLs and potential candidate genes. These findings carry significant implications for the breeding of pork cuts through marker-assisted and genomic selection. Additionally, we have constructed the first reference populations for genomic selection of pork cuts in pigs.

Accurate haplotype construction and detection of selection signatures enabled by high quality pig genome sequences

High-quality whole-genome resequencing in large-scale pig populations with pedigree structure and multiple breeds would enable accurate construction of haplotype and robust selection-signature detection. Here, we sequence 740 pigs, combine with 149 of our previously published resequencing data, retrieve 207 resequencing datasets, and form a panel of worldwide distributed wild boars, aboriginal and highly selected pigs with pedigree structures, amounting to 1096 genomes from 43 breeds. Combining with their haplotype-informative reads and pedigree structure, we accurately construct a panel of 1874 haploid genomes with 41,964,356 genetic variants. We further demonstrate its valuable applications in GWAS by identifying five novel loci for intramuscular fat content, and in genomic selection by increasing the accuracy of estimated breeding value by 36.7%. In evolutionary selection, we detect MUC13 gene under a long-term balancing selection, as well as NPR3 gene under positive selection for pig stature. Our study provides abundant genomic variations for robust selection-signature detection and accurate haplotypes for deciphering complex traits in pigs.

Identifying Genetic Architecture of Carcass and Meat Quality Traits in a Ningxiang Indigenous Pig Population

Ningxiang pig is a breed renowned for its exceptional meat quality, but it possesses suboptimal carcass traits. To elucidate the genetic architecture of meat quality and carcass traits in Ningxiang pigs, we assessed heritability and executed a genome-wide association study (GWAS) concerning carcass length, backfat thickness, meat color parameters (L.LD, a.LD, b.LD), and pH at two postmortem intervals (45 min and 24 h) within a Ningxiang pig population. Heritability estimates ranged from moderate to high (0.30~0.80) for carcass traits and from low to high (0.11~0.48) for meat quality traits. We identified 21 significant SNPs, the majority of which were situated within previously documented QTL regions. Furthermore, the GRM4 gene emerged as a pleiotropic gene that correlated with carcass length and backfat thickness. The ADGRF1, FKBP5, and PRIM2 genes were associated with carcass length, while the NIPBL gene was linked to backfat thickness. These genes hold the potential for use in selective breeding programs targeting carcass traits in Ningxiang pigs.

Genome-Wide Association Analysis Identifies Genomic Regions and Candidate Genes for Growth and Fatness Traits in Diannan Small-Ear (DSE) Pigs

In the livestock industry, the growth and fatness traits are directly related to production efficiency and economic profits. As for Diannan small-ear (DSE) pigs, a unique indigenous breed, the genetic architecture of growth and fatness traits is still elusive. The aim of this study was to search the genetic loci and candidate genes associated with phenotypic traits in DSE pigs using GWAS based on the Geneseek Porcine 50K SNP Chip data. A total of 22,146 single nucleotide polymorphisms (SNPs) were detected in 265 DSE pigs and used for Genome-wide association studies (GWAS) analysis. Seven SNPs were found to be associated with back height, chest circumference, cannon bone circumference, and backfat thickness at the suggestive significance level. Based on gene annotation results, these seven SNPs were, respectively, mapped to the following candidate genes, VIPR2, SLC10A2, NUCKS1, MCT1, CHCHD3, SMOX, and GPR1, which are mainly involved with adipocyte differentiation, lipid metabolism, skeletal muscle development, and average daily weight gain. Our work offers novel insights into the genetic architecture of economically important traits in swine and may play an important role in breeding using molecular markers in the DSE breed.

Genome-Wide Association Study on Reproductive Traits Using Imputation-Based Whole-Genome Sequence Data in Yorkshire Pigs

Reproductive traits have a key impact on production efficiency in the pig industry. It is necessary to identify the genetic structure of potential genes that influence reproductive traits. In this study, a genome-wide association study (GWAS) based on chip and imputed data of five reproductive traits, namely, total number born (TNB), number born alive (NBA), litter birth weight (LBW), gestation length (GL), and number of weaned (NW), was performed in Yorkshire pigs. In total, 272 of 2844 pigs with reproductive records were genotyped using KPS Porcine Breeding SNP Chips, and then chip data were imputed to sequencing data using two online software programs: the Pig Haplotype Reference Panel (PHARP v2) and Swine Imputation Server (SWIM 1.0). After quality control, we performed GWAS based on chip data and the two different imputation databases by using fixed and random model circulating probability unification (FarmCPU) models. We discovered 71 genome-wide significant SNPs and 25 potential candidate genes (e.g., SMAD4, RPS6KA2, CAMK2A, NDST1, and ADCY5). Functional enrichment analysis revealed that these genes are mainly enriched in the calcium signaling pathway, ovarian steroidogenesis, and GnRH signaling pathways. In conclusion, our results help to clarify the genetic basis of porcine reproductive traits and provide molecular markers for genomic selection in pig breeding.

Maternal Rumen Bacteriota Shapes the Offspring Rumen Bacteriota, Affecting the Development of Young Ruminants

The maternal rumen microbiota can affect the infantile rumen microbiota and likely offspring growth, and some rumen microbes are heritable and are associated with host traits. However, little is known about the heritable microbes of the maternal rumen microbiota and their role in and effect on the growth of young ruminants. From analyzing the ruminal bacteriota from 128 Hu sheep dams and their 179 offspring lambs, we identified the potential heritable rumen bacteria and developed random forest prediction models to predict birth weight, weaning weight, and preweaning gain of the young ruminants using rumen bacteria as predictors. We showed that the dams tended to shape the bacteriota of the offspring. About 4.0% of the prevalent amplicon sequence variants (ASVs) of rumen bacteria were heritable (h2 > 0.2 and P < 0.05), and together they accounted for 4.8% and 31.5% of the rumen bacteria in relative abundance in the dams and the lambs, respectively. Heritable bacteria classified to Prevotellaceae appeared to play a key role in the rumen niche and contribute to rumen fermentation and the growth performance of lambs. Lamb growth traits could be successfully predicted using some maternal ASVs, and the accuracy of the predictive models was improved when some ASVs from both dams and their offspring were included. IMPORTANCE Using a study design that enabled direct comparison of the rumen microbiota between sheep dams and their lambs, between littermates, and between sheep dams and lambs from other mothers, we identified the heritable subsets of rumen bacteriota in Hu sheep, some of which may play important roles in affecting the growth traits of young lambs. Some maternal rumen bacteria could help predict the growth traits of the young offspring, and they may assist in breeding of and selection for high-performance sheep.

Novel Haplotype in the HHEX Gene Promoter Associated with Body Length in Pigs

The screening of important candidate genes and the identification of genetic markers are important for molecular selection in the pig industry. The hematopoietically expressed homeobox (HHEX) gene plays an important role in embryonic development and organogenesis; however, the genetic variation and expression pattern of the porcine HHEX gene remains to be clarified. In this study, semiquantitative RT-PCR and immunohistochemistry results showed the specific expression of the HHEX gene in porcine cartilage tissues. A novel haplotype consisting of two SNPs rs80901185 (T > C) and rs80934526 (A > G) was detected in the promoter region of the HHEX gene. The expression of the HHEX gene was significantly higher in Yorkshire pigs (TA haplotype) than in Wuzhishan pigs (CG haplotype), and a population analysis showed that this haplotype was significantly associated with body length. An analysis subsequently revealed that the -586 to -1 bp region of the HHEX gene promoter showed the highest activity. Furthermore, we found that the activity of the TA haplotype was significantly higher than that of the CG haplotype by changing the potential binding of transcription factors YY1 and HDAC2. In summary, we conclude that the porcine HHEX gene may contribute to the breeding of pigs for body length traits.

The selected genes NR6A1, RSAD2-CMPK2, and COL3A1 contribute to body size variation in Meishan pigs through different patterns

The high-fertility Meishan pig is currently categorized into medium sized (MMS) and small sized (SMS) based on body size. To identify causal genes responsible for the variation in body size within the two categories, we sequenced individuals representing the entire consanguinity of the existing Meishan pig. This enabled us to conduct genome selective signal analysis. Our findings revealed the genomes of MMS and SMS are stratified, with selective sweep regions formed by differential genomic intervals between the two categories enriched in multiple pig body size related quantitative trait loci (QTLs). Furthermore, the missense mutation c.575T > C of candidate causal gene NR6A1, accounting for the variation in lumbar vertebrae number in pigs, was positively selected in MMS only, leading to an increase in body length of MMS at 6 months of age. To precisely identify causal genes accounting for body size variation through multi-omics, we collected femoral cartilage and liver transcription data from MMS and SMS respectively, and re-sequencing data from pig breeds exhibiting varying body sizes. We found that two selected regions where the RSAD2-CMPK2 and COL3A1 genes are located, respectively, showed different haplotypes in pig breeds of varying body size, and was associated with body or carcass length in hybridized Suhuai pig. Additionally, the above three hub genes, were significantly greater expressed in SMS femoral cartilage and liver tissues compared to MMS. These three genes could strengthen the pathways related to bone resorption and metabolism in SMS, potentially hindering bone and skeletal development and resulting in a smaller body size in SMS. These findings provide valuable insights into the genetic mechanism of body size variation in Meishan pig population.

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.

Genome-Wide Association Study of Growth Traits in a Four-Way Crossbred Pig Population

Growth traits are crucial economic traits in the commercial pig industry and have a substantial impact on pig production. However, the genetic mechanism of growth traits is not very clear. In this study, we performed a genome-wide association study (GWAS) based on the specific-locus amplified fragment sequencing (SLAF-seq) to analyze ten growth traits on 223 four-way intercross pigs. A total of 227,921 highly consistent single nucleotide polymorphisms (SNPs) uniformly dispersed throughout the entire genome were used to conduct GWAS. A total of 53 SNPs were identified for ten growth traits using the mixed linear model (MLM), of which 18 SNPs were located in previously reported quantitative trait loci (QTL) regions. Two novel QTLs on SSC4 and SSC7 were related to average daily gain from 30 to 60 kg (ADG30-60) and body length (BL), respectively. Furthermore, 13 candidate genes (ATP5O, GHRHR, TRIM55, EIF2AK1, PLEKHA1, BRAP, COL11A2, HMGA1, NHLRC1, SGSM1, NFATC2, MAML1, and PSD3) were found to be associated with growth traits in pigs. The GWAS findings will enhance our comprehension of the genetic architecture of growth traits. We suggested that these detected SNPs and corresponding candidate genes might provide a biological foundation for improving the growth and production performance of pigs in swine breeding.

Identification of TRAPPC9 and BAIAP2 Gene Polymorphisms and Their Association With Fat Deposition-Related Traits in Hu Sheep

Fat deposition is an important economic trait that is closely related to feed efficiency and carcass performance in livestock. In this study, the fat deposition-related traits of 1,293 Hu sheep were measured and descriptive statistical analysis was conducted. The results showed that the coefficient of variation of all fat deposition-related traits was higher than 24%. In addition, single nucleotide polymorphisms and the expression characteristics of TRAPPC9 (encoding trafficking protein particle complex subunit 9) and BAIAP2 (encoding brain-specific Angiogenesis inhibitor 1-associated protein 2) genes in Hu sheep were detected using PCR amplification, Sanger sequencing, KASPar genotyping, and quantitative real-time reverse transcription PCR (qRT-PCR). The associations between SNPs and fat deposition-related traits were also analyzed. Two intronic mutations, TRAPPC9 g.57654 A > G and BAIAP2 g.46061 C > T, were identified in Hu sheep. The result of association analysis showed that TRAPPC9 g.57654 A > G and BAIAP2 g.46061 C > T were both significantly associated with the weight of tail fat, tail fat relative weight (body weight), and tail fat relative weight (carcass) (P < 0.05). Comprehensive effects analysis showed that there were significant differences between the combined genotypes and tail fat and perirenal fat deposition. Moreover, qRT-PCR analysis showed that TRAPPC9 and BAIAP2 are widely expressed, and their expression levels were significantly higher in the small-tail group compared with those in the big-tail group (P < 0.01). These results provided important candidate molecular markers that could be used in strategies to reduce tail fat deposition in Hu sheep.