Genome-wide association study identifies Loci for body composition and structural soundness traits in pigs

Genomic signatures of selection, local adaptation and production type characterisation of East Adriatic sheep breeds

BACKGROUND

The importance of sheep breeding in the Mediterranean part of the eastern Adriatic has a long tradition since its arrival during the Neolithic migrations. Sheep production system is extensive and generally carried out in traditional systems without intensive systematic breeding programmes for high uniform trait production (carcass, wool and milk yield). Therefore, eight indigenous Croatian sheep breeds from eastern Adriatic treated here as metapopulation (EAS), are generally considered as multipurpose breeds (milk, meat and wool), not specialised for a particular type of production, but known for their robustness and resistance to certain environmental conditions. Our objective was to identify genomic regions and genes that exhibit patterns of positive selection signatures, decipher their biological and productive functionality, and provide a "genomic" characterization of EAS adaptation and determine its production type.

RESULTS

We identified positive selection signatures in EAS using several methods based on reduced local variation, linkage disequilibrium and site frequency spectrum (eROHi, iHS, nSL and CLR). Our analyses identified numerous genomic regions and genes (e.g., desmosomal cadherin and desmoglein gene families) associated with environmental adaptation and economically important traits. Most candidate genes were related to meat/production and health/immune response traits, while some of the candidate genes discovered were important for domestication and evolutionary processes (e.g., HOXa gene family and FSIP2). These results were also confirmed by GO and QTL enrichment analysis.

CONCLUSIONS

Our results contribute to a better understanding of the unique adaptive genetic architecture of EAS and define its productive type, ultimately providing a new opportunity for future breeding programmes. At the same time, the numerous genes identified will improve our understanding of ruminant (sheep) robustness and resistance in the harsh and specific Mediterranean environment.

Discovering Genomic Regions Associated with Reproductive Traits and Frame Score in Mexican Simmental and Simbrah Cattle Using Individual SNP and Haplotype Markers

Reproductive efficiency stands as a critical determinant of profitability within beef production systems. The incorporation of molecular markers can expedite advancements in reproductive performance. While the use of SNPs in association analysis is prevalent, approaches centered on haplotypes can offer a more comprehensive insight. The study used registered Simmental and Simbrah cattle genotyped with the GGP Bovine 150 k panel. Phenotypes included scrotal circumference (SC), heifer fertility (HF), stayability (STAY), and frame score (FS). After quality control, 105,129 autosomal SNPs from 967 animals were used. Haplotype blocks were defined based on linkage disequilibrium. Comparison between haplotypes and SNPs for reproductive traits and FS was conducted using Bayesian and frequentist models. 23, 13, 7, and 2 SNPs exhibited associations with FS, SC, HF, and STAY, respectively. In addition, seven, eight, seven, and one haplotypes displayed associations with FS, SC, HF, and STAY, respectively. Within these delineated genomic segments, potential candidate genes were associated.

Genomic selection pressure discovery using site-frequency spectrum and reduced local variability statistics in Pakistani Dera-Din-Panah goat

BACKGROUND

Population geneticists have long sought to comprehend various selection traces accumulated in the goat genome due to natural or human driven artificial selection through breeding practices, which led the wild animals to domestication, so understanding evolutionary process may helpful to utilize the full genetic potential of goat genome.

METHODS AND RESULTS

As a step forward to pinpoint the selection signals in Pakistani Dera-Din-Panah (DDP) goat, whole-genome pooled sequencing (n = 12) was performed, and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signature statistics were applied using four site-frequency spectrum (SFS) methods (Tajima's D ([Formula: see text]), Fay and Wu's H ([Formula: see text]), Zeng's E ([Formula: see text]), [Formula: see text]) and one reduced local variability approach named pooled heterozygosity ([Formula: see text]). The under-selection regions were annotated with significant threshold values of [Formula: see text]≥4.7, [Formula: see text]≥6, [Formula: see text]≥2.5, Pool-HMM ≥ 12, and [Formula: see text]≥5 that resulted in accumulative 364 candidate gene hits. The highest genomic selection signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, and 27 and harbor ADAMTS6, CWC27, RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3, FH, MFHAS1, KLKB1, RRM1, KMO, SPEF2, F11, KIT, KMO, ERI1, ATP8B4, and RHOG genes. Next, the validation of our captured genomic hits was also performed by more than one applied statistics which harbor meat production, immunity, and reproduction associated genes to strengthen our hypothesis of under-selection traits in this Pakistani goat breed. Furthermore, common candidate genes captured by more than one statistical method were subjected to gene ontology and KEGG pathway analysis to get insights of particular biological processes associated with this goat breed.

CONCLUSION

Current perception of genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other economically important traits of medium to large body size, milk, and fiber production by updating the genomic insight driven breeding strategies to boost the livestock and agriculture-based economy of the country.

Genome-Wide Association Study of Body Conformation Traits in a Three-Way Crossbred Commercial Pig Population

Body conformation is the most direct production index, which can fully reflect pig growth status and is closely related to critical economic traits. In this study, we conducted a genome-wide association study (GWAS) on body conformation traits in a population of 1518 Duroc × (Landrace × Yorkshire) commercial pigs. These traits included body length (BL), body height (BH), chest circumference (CC), abdominal circumference (AC), and waist circumference (WC). Both the mixed linear model (MLM) and fixed and random model circulating probability unification (FarmCPU) approaches were employed for the analysis. Our findings revealed 60 significant single nucleotide polymorphisms (SNPs) associated with these body conformation traits in the crossbred pig population. Specifically, sixteen SNPs were significantly associated with BL, three SNPs with BH, thirteen SNPs with CC, twelve SNPs with AC, and sixteen SNPs with WC. Moreover, we identified several promising candidate genes located within the genomic regions associated with body conformation traits. These candidate genes include INTS10, KIRREL3, SOX21, BMP2, MAP4K3, SOD3, FAM160B1, ATL2, SPRED2, SEC16B, and RASAL2. Furthermore, our analysis revealed a novel significant quantitative trait locus (QTL) on SSC7 specifically associated with waist circumference, spanning an 84 kb interval. Overall, the identification of these significant SNPs and potential candidate genes in crossbred commercial pigs enhances our understanding of the genetic basis underlying body conformation traits. Additionally, these findings provide valuable genetic resources for pig breeding programs.

Integrated analysis of genome-wide association studies and 3D epigenomic characteristics reveal the BMP2 gene regulating loin muscle depth in Yorkshire pigs

BACKGROUND

The lack of integrated analysis of genome-wide association studies (GWAS) and 3D epigenomics restricts a deep understanding of the genetic mechanisms of meat-related traits. With the application of techniques as ChIP-seq and Hi-C, the annotations of cis-regulatory elements in the pig genome have been established, which offers a new opportunity to elucidate the genetic mechanisms and identify major genetic variants and candidate genes that are significantly associated with important economic traits. Among these traits, loin muscle depth (LMD) is an important one as it impacts the lean meat content. In this study, we integrated cis-regulatory elements and genome-wide association studies (GWAS) to identify candidate genes and genetic variants regulating LMD.

RESULTS

Five single nucleotide polymorphisms (SNPs) located on porcine chromosome 17 were significantly associated with LMD in Yorkshire pigs. A 10 kb quantitative trait locus (QTL) was identified as a candidate functional genomic region through the integration of linkage disequilibrium and linkage analysis (LDLA) and high-throughput chromosome conformation capture (Hi-C) analysis. The BMP2 gene was identified as a candidate gene for LMD based on the integrated results of GWAS, Hi-C meta-analysis, and cis-regulatory element data. The identified QTL region was further verified through target region sequencing. Furthermore, through using dual-luciferase assays and electrophoretic mobility shift assays (EMSA), two SNPs, including SNP rs321846600, located in the enhancer region, and SNP rs1111440035, located in the promoter region, were identified as candidate SNPs that may be functionally related to the LMD.

CONCLUSIONS

Based on the results of GWAS, Hi-C, and cis-regulatory elements, the BMP2 gene was identified as an important candidate gene regulating variation in LMD. The SNPs rs321846600 and rs1111440035 were identified as candidate SNPs that are functionally related to the LMD of Yorkshire pigs. Our results shed light on the advantages of integrating GWAS with 3D epigenomics in identifying candidate genes for quantitative traits. This study is a pioneering work for the identification of candidate genes and related genetic variants regulating one key production trait (LMD) in pigs by integrating genome-wide association studies and 3D epigenomics.

A genome-wide association study for loin depth and muscle pH in pigs from intensely selected purebred lines

BACKGROUND

Genome-wide association studies (GWAS) aim at identifying genomic regions involved in phenotype expression, but identifying causative variants is difficult. Pig Combined Annotation Dependent Depletion (pCADD) scores provide a measure of the predicted consequences of genetic variants. Incorporating pCADD into the GWAS pipeline may help their identification. Our objective was to identify genomic regions associated with loin depth and muscle pH, and identify regions of interest for fine-mapping and further experimental work. Genotypes for ~ 40,000 single nucleotide morphisms (SNPs) were used to perform GWAS for these two traits, using de-regressed breeding values (dEBV) for 329,964 pigs from four commercial lines. Imputed sequence data was used to identify SNPs in strong ([Formula: see text] 0.80) linkage disequilibrium with lead GWAS SNPs with the highest pCADD scores.

RESULTS

Fifteen distinct regions were associated with loin depth and one with loin pH at genome-wide significance. Regions on chromosomes 1, 2, 5, 7, and 16, explained between 0.06 and 3.55% of the additive genetic variance and were strongly associated with loin depth. Only a small part of the additive genetic variance in muscle pH was attributed to SNPs. The results of our pCADD analysis suggests that high-scoring pCADD variants are enriched for missense mutations. Two close but distinct regions on SSC1 were associated with loin depth, and pCADD identified the previously identified missense variant within the MC4R gene for one of the lines. For loin pH, pCADD identified a synonymous variant in the RNF25 gene (SSC15) as the most likely candidate for the muscle pH association. The missense mutation in the PRKAG3 gene known to affect glycogen content was not prioritised by pCADD for loin pH.

CONCLUSIONS

For loin depth, we identified several strong candidate regions for further statistical fine-mapping that are supported in the literature, and two novel regions. For loin muscle pH, we identified one previously identified associated region. We found mixed evidence for the utility of pCADD as an extension of heuristic fine-mapping. The next step is to perform more sophisticated fine-mapping and expression quantitative trait loci (eQTL) analysis, and then interrogate candidate variants in vitro by perturbation-CRISPR assays.

Genome-wide association analysis of hyperspectral reflectance data to dissect the genetic architecture of growth-related traits in maize under plant growth-promoting bacteria inoculation

Plant growth-promoting bacteria (PGPB) may be of use for increasing crop yield and plant resilience to biotic and abiotic stressors. Using hyperspectral reflectance data to assess growth-related traits may shed light on the underlying genetics as such data can help assess biochemical and physiological traits. This study aimed to integrate hyperspectral reflectance data with genome-wide association analyses to examine maize growth-related traits under PGPB inoculation. A total of 360 inbred maize lines with 13,826 single nucleotide polymorphisms (SNPs) were evaluated with and without PGPB inoculation; 150 hyperspectral wavelength reflectances at 386-1021 nm and 131 hyperspectral indices were used in the analysis. Plant height, stalk diameter, and shoot dry mass were measured manually. Overall, hyperspectral signatures produced similar or higher genomic heritability estimates than those of manually measured phenotypes, and they were genetically correlated with manually measured phenotypes. Furthermore, several hyperspectral reflectance values and spectral indices were identified by genome-wide association analysis as potential markers for growth-related traits under PGPB inoculation. Eight SNPs were detected, which were commonly associated with manually measured and hyperspectral phenotypes. Different genomic regions were found for plant growth and hyperspectral phenotypes between with and without PGPB inoculation. Moreover, the hyperspectral phenotypes were associated with genes previously reported as candidates for nitrogen uptake efficiency, tolerance to abiotic stressors, and kernel size. In addition, a Shiny web application was developed to explore multiphenotype genome-wide association results interactively. Taken together, our results demonstrate the usefulness of hyperspectral-based phenotyping for studying maize growth-related traits in response to PGPB inoculation.

Genome-wide association studies for additive and dominance effects for body composition traits in commercial crossbred Piétrain pigs

Fat depth (FD) and muscle depth (MD) are economically important traits and used to estimate carcass lean content (LMP), which is one of the main breeding objectives in pig breeding programmes. We assessed the genetic architectures of body composition traits for additive and dominance effects in commercial crossbred Piétrain pigs using both 50 K array and sequence genotypes. We first performed a genome-wide association study (GWAS) using single-marker association analysis with a false discovery rate of 0.1. Then, we estimated the additive and dominance effects of the most significant variant in the quantitative trait loci (QTL) regions. It was investigated whether the use of whole-genome sequence (WGS) will improve the QTL detection (both additive and dominance) with a higher power compared with lower density SNP arrays. Our results showed that more QTL regions were detected by WGS compared with 50 K array (n = 54 vs. n = 17). Of the novel associated regions associated with FD and LMP and detected by WGS, the most pronounced peak was on SSC13, situated at ~116-118, 121-127 and 129-134 Mbp. Additionally, we found that only additive effects contributed to the genetic architecture of the analysed traits and no significant dominance effects were found for the tested SNPs at QTL regions, regardless of panel density. The associated SNPs are located in or near several relevant candidate genes. Of these genes, GABRR2, GALR1, RNGTT, CDH20 and MC4R have been previously reported as being associated with fat deposition traits. However, the genes on SSC1 (ZNF292, ORC3, CNR1, SRSF12, MDN1, TSHZ1, RELCH and RNF152) and SSC18 (TTC26 and KIAA1549) have not been reported previously to our best knowledge. Our current findings provide insights into the genomic regions influencing composition traits in Piétrain pigs.

Relationships of genomic estimated breeding values for age at puberty, birth weight, and growth during development in normal cyclic and acyclic gilts

Managing replacement gilts to reach optimal body weight and growth rate for boar stimulation and first breeding is a key component for sow reproductive longevity and producer profitability. Failure to display pubertal estrus remains a major reason that gilts are culled from the herd. Puberty is metabolically gated so evaluating phenotypic and genetic relationships between birth weight and growth traits with age at puberty and acyclicity can provide valuable insight for efficient gilt development. Data on a litter of origin of the gilt, average daily gain at different stages of development, and age at puberty were available for age-matched cyclic (n = 4,861) and acyclic gilts (prepubertal anestrus, n = 578; behavioral anestrus, n = 428). Genomic estimated breeding values were predicted for each trait using genomic best linear unbiased prediction. Primiparous sows produced more acyclic gilts than multiparous sows (P < 0.05). Accounting for effects of parity and litter size, prepubertal anestrus gilts were heavier at birth and behaviorally anestrus gilts grew faster during the finisher period compared to cyclic gilts (P < 0.05), reflecting possible prenatal programming that negatively affects optimal pubertal development and antagonistic effects between adolescent growth and expression of estrus of gilts from first parity sows. Regression of phenotypic age at puberty with lifetime growth rate (birth to selection) showed a negative linear relationship whereas genomic estimated breeding values showed a negative quadratic relationship indicating that gilts with the least and greatest growth are less optimal as replacements. The slopes of these relationships are small with low negative phenotypic (r = -0.06) and genetic correlations (r = -0.13). The addition of data from acyclic gilts did not substantially change the estimates for genetic relationships between growth and pubertal onset. Although this study identified differences in birth weight and growth rate between cyclic and acyclic gilts the genetic relationships are weak, suggesting that genetic selection for these traits can be achieved separately. Avoiding the smallest and largest gilts in a cohort born to first parity sows could result in gilts with optimal development and reduce the proportion of replacement gilts that are acyclic.

Meta-analysis of genome-wide association studies uncovers shared candidate genes across breeds for pig fatness trait

Background

Average backfat thickness (BFT) is a critical complex trait in pig and an important indicator for fat deposition and lean rate. Usually, genome-wide association study (GWAS) was used to discover quantitative trait loci (QTLs) of BFT in a single population. However, the power of GWAS is limited by sample size in a single population. Alternatively, meta-analysis of GWAS (metaGWAS) is an attractive method to increase the statistical power by integrating data from multiple breeds and populations. The aim of this study is to identify shared genetic characterization of BFT across breeds in pigs via metaGWAS. 

Results

In this study, we performed metaGWAS on BFT using 15,353 pigs (5,143 Duroc, 7,275 Yorkshire, and 2,935 Landrace) from 19 populations. We detected 40 genome-wide significant SNPs (Bonferroni corrected P < 0.05) and defined five breed-shared QTLs in across-breed metaGWAS. Markers within the five QTL regions explained 7 ~ 9% additive genetic variance and showed strong heritability enrichment. Furthermore, by integrating information from multiple bioinformatics databases, we annotated 46 candidate genes located in the five QTLs. Among them, three important (MC4R, PPARD, and SLC27A1) and seven suggestive candidate genes (PHLPP1, NUDT3, ILRUN, RELCH, KCNQ5, ITPR3, and U3) were identified.

Conclusion

QTLs and candidate genes underlying BFT across breeds were identified via metaGWAS from multiple populations. Our findings contribute to the understanding of the genetic architecture of BFT and the regulating mechanism underlying fat deposition in pigs.

Correlation scan: identifying genomic regions that affect genetic correlations applied to fertility traits

Although the genetic correlations between complex traits have been estimated for more than a century, only recently we have started to map and understand the precise localization of the genomic region(s) that underpin these correlations. Reproductive traits are often genetically correlated. Yet, we don't fully understand the complexities, synergism, or trade-offs between male and female fertility. In this study, we used reproductive traits in two cattle populations (Brahman; BB, Tropical Composite; TC) to develop a novel framework termed correlation scan (CS). This framework was used to identify local regions associated with the genetic correlations between male and female fertility traits. Animals were genotyped with bovine high-density single nucleotide polymorphisms (SNPs) chip assay. The data used consisted of ~1000 individual records measured through frequent ovarian scanning for age at first corpus luteum (AGECL) and a laboratory assay for serum levels of insulin growth hormone (IGF1 measured in bulls, IGF1b, or cows, IGF1c). The methodology developed herein used correlations of 500-SNP effects in a 100-SNPs sliding window in each chromosome to identify local genomic regions that either drive or antagonize the genetic correlations between traits. We used Fisher's Z-statistics through a permutation method to confirm which regions of the genome harboured significant correlations. About 30% of the total genomic regions were identified as driving and antagonizing genetic correlations between male and female fertility traits in the two populations. These regions confirmed the polygenic nature of the traits being studied and pointed to genes of interest. For BB, the most important chromosome in terms of local regions is often located on bovine chromosome (BTA) 14. However, the important regions are spread across few different BTA's in TC. Quantitative trait loci (QTLs) and functional enrichment analysis revealed many significant windows co-localized with known QTLs related to milk production and fertility traits, especially puberty. In general, the enriched reproductive QTLs driving the genetic correlations between male and female fertility are the same for both cattle populations, while the antagonizing regions were population specific. Moreover, most of the antagonizing regions were mapped to chromosome X. These results suggest regions of chromosome X for further investigation into the trade-offs between male and female fertility. We compared the CS with two other recently proposed methods that map local genomic correlations. Some genomic regions were significant across methods. Yet, many significant regions identified with the CS were overlooked by other methods.

Genome-Wide Association Study of Body Weight Trait in Yaks

The yak is the largest meat-producing mammal around the Tibetan Plateau, and it plays an important role in the economic development and maintenance of the ecological environment throughout much of the Asian highlands. Understanding the genetic components of body weight is key for future improvement in yak breeding; therefore, genome-wide association studies (GWAS) were performed, and the results were used to mine plant and animal genetic resources. We conducted whole genome sequencing on 406 Maiwa yaks at 10 × coverage. Using a multiple loci mixed linear model (MLMM), fixed and random model circulating probability unification (FarmCPU), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK), we found that a total of 25,000 single-nucleotide polymorphisms (SNPs) were distributed across chromosomes, and seven markers were identified as significantly (p-values < 3.91 × 10−7) associated with the body weight trait,. Several candidate genes, including MFSD4, LRRC37B, and NCAM2, were identified. This research will help us achieve a better understanding of the genotype−phenotype relationship for body weight.

Associated regions for multiple birth in Brown Swiss and Original Braunvieh cattle on chromosomes 15 and 11

Twin and multiple births have negative effects on the performance and health of cows and calves. To decipher the genetic architecture of this trait in the two Swiss Brown Swiss cattle populations, we performed various association analyses based on de-regressed breeding values. Genome-wide association analyses were executed using ~600 K imputed SNPs for the maternal multiple birth trait in ~3500 Original Braunvieh and ~7800 Brown Swiss animals. Significantly associated QTL were observed on different chromosomes for both breeds. We have identified on chromosome 11 a QTL that explains ~6% of the total genetic variance of the maternal multiple birth trait in Original Braunvieh. For the Brown Swiss breed, we have discovered a QTL on chromosome 15 that accounts for ~4% of the total genetic variance. For Original Braunvieh, subsequent haplotype analysis revealed a 90-kb window on chromosome 11 at 88 Mb, where a likely regulatory region is located close to the ID2 gene. In Brown Swiss, a 130-kb window at 75 Mb on chromosome 15 was identified. Analysis of whole-genome sequence data using linkage-disequilibrium estimation revealed possible causal variants for the identified QTL. A presumably regulatory variant in the non-coding 5' region of the ID2 gene was strongly associated with the haplotype for Original Braunvieh. In Brown Swiss, an intron variant in PRDM11, one 3' UTR variant in SYT13 and three intergenic variants 5' upstream of SYT13 were identified as candidate variants for the trait multiple birth maternal. In this study, we report for the first time QTL for the trait of multiple births in Original Braunvieh and Brown Swiss cattle. Moreover, our findings are another step towards a better understanding of the complex genetic architecture of this polygenic trait.

Mutations in melanocortin-4 receptor: From fish to men

Melanocortin-4 receptor (MC4R), expressed abundantly in the hypothalamus, is a critical regulator of energy homeostasis, including both food intake and energy expenditure. Shortly after the publication in 1997 of the Mc4r knockout phenotypes in mice, including increased food intake and severe obesity, the first mutations in MC4R were reported in humans in 1998. Studies in the subsequent two decades have established MC4R mutation as the most common monogenic form of obesity, especially in early-onset severe obesity. Studies in animals, from fish to mammals, have established the conserved physiological roles of MC4R in all vertebrates in regulating energy balance. Drug targeting MC4R has been recently approved for treating morbid genetic obesity. How the MC4R can be exploited for animal production is highly worthy of active investigation.

Application of Bayesian genomic prediction methods to genome-wide association analyses

Background

Bayesian genomic prediction methods were developed to simultaneously fit all genotyped markers to a set of available phenotypes for prediction of breeding values for quantitative traits, allowing for differences in the genetic architecture (distribution of marker effects) of traits. These methods also provide a flexible and reliable framework for genome-wide association (GWA) studies. The objective here was to review developments in Bayesian hierarchical and variable selection models for GWA analyses.

Results

By fitting all genotyped markers simultaneously, Bayesian GWA methods implicitly account for population structure and the multiple-testing problem of classical single-marker GWA. Implemented using Markov chain Monte Carlo methods, Bayesian GWA methods allow for control of error rates using probabilities obtained from posterior distributions. Power of GWA studies using Bayesian methods can be enhanced by using informative priors based on previous association studies, gene expression analyses, or functional annotation information. Applied to multiple traits, Bayesian GWA analyses can give insight into pleiotropic effects by multi-trait, structural equation, or graphical models. Bayesian methods can also be used to combine genomic, transcriptomic, proteomic, and other -omics data to infer causal genotype to phenotype relationships and to suggest external interventions that can improve performance.

Conclusions

Bayesian hierarchical and variable selection methods provide a unified and powerful framework for genomic prediction, GWA, integration of prior information, and integration of information from other -omics platforms to identify causal mutations for complex quantitative traits.

Weighted single-step GWAS for body mass index and scans for recent signatures of selection in Yorkshire pigs

Controlling extra fat deposition is economically favorable in modern swine industry. Understanding the genetic architecture of fat deposition traits such as body mass index (BMI) can help in improving genomic selection for such traits. We utilized a weighted single-step genome-wide association study (WssGWAS) to detect genetic regions and candidate genes associated with BMI in a Yorkshire pig population. Three extended haplotype homozygosity (EHH)-related statistics were also incorporated within a de-correlated composite of multiple signals (DCMS) framework to detect recent selection signatures signals. Overall, the full pedigree consisted of 7,016 pigs, of which 5,561 had BMI records and 598 pigs were genotyped with an 80 K single nucleotide polymorphism (SNP) array. Results showed that the most significant windows (top 15) explained 9.35% of BMI genetic variance. Several genes were detected in regions previously associated with pig fat deposition traits and treated as potential candidate genes for BMI in Yorkshire pigs: FTMT, SRFBP1, KHDRBS3, FOXG1, SOD3, LRRC32, TSKU, ACER3, B3GNT6, CCDC201, ADCY1, RAMP3, TBRG4, CCM2. Signature of selection analysis revealed multiple candidate genes previously associated with various economic traits. However, BMI genetic variance explained by regions under selection pressure was minimal (1.31%). In conclusion, candidate genes associated with Yorkshire pigs’ BMI trait were identified using WssGWAS. Gene enrichment analysis indicated that the identified candidate genes were enriched in the insulin secretion pathway. We anticipate that these results further advance our understanding of the genetic architecture of BMI in Yorkshire pigs and provide information for genomic selection for fat deposition in this breed.

Identification and validation of a regulatory mutation upstream of the BMP2 gene associated with carcass length in pigs

Background

Carcass length is very important for body size and meat production for swine, thus understanding the genetic mechanisms that underly this trait is of great significance in genetic improvement programs for pigs. Although many quantitative trait loci (QTL) have been detected in pigs, very few have been fine-mapped to the level of the causal mutations. The aim of this study was to identify potential causal single nucleotide polymorphisms (SNPs) for carcass length by integrating a genome-wide association study (GWAS) and functional assays.

Results

Here, we present a GWAS in a commercial Duroc × (Landrace × Yorkshire) (DLY) population that reveals a prominent association signal (P = 4.49E−07) on pig chromosome 17 for carcass length, which was further validated in two other DLY populations. Within the detected 1 Mb region, the BMP2 gene stood out as the most likely causal candidate because of its functions in bone growth and development. Whole-genome gene expression studies showed that the BMP2 gene was differentially expressed in the cartilage tissues of pigs with extreme carcass length. Then, we genotyped an additional 267 SNPs in 500 selected DLY pigs, followed by further whole-genome SNP imputation, combined with deep genome resequencing data on multiple pig breeds. Reassociation analyses using genotyped and imputed SNP data revealed that the rs320706814 SNP, located approximately 123 kb upstream of the BMP2 gene, was the strongest candidate causal mutation, with a large association with carcass length, with a ~ 4.2 cm difference in length across all three DLY populations (N = 1501; P = 3.66E−29). This SNP segregated in all parental lines of the DLY (Duroc, Large White and Landrace) and was also associated with a significant effect on body length in 299 pure Yorkshire pigs (P = 9.2E−4), which indicates that it has a major value for commercial breeding. Functional assays showed that this SNP is likely located within an enhancer and may affect the binding affinity of transcription factors, thereby regulating BMP2 gene expression.

Conclusions

Taken together, these results suggest that the rs320706814 SNP on pig chromosome 17 is a putative causal mutation for carcass length in the widely used DLY pigs and has great value in breeding for body size in pigs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00689-0.

Regulation of Swine Growth by Backfat Tissue during Growing and Finishing Stages

Simple Summary

Swine have a large influence on livestock animals. In particular, Korean native pigs (KNPs) have unique traits in their body composition including lipids and proteins. In this study, we performed RNA-sequencing analysis to identify porcine transcriptomic changes during growing and finishing stages in the backfat tissue of KNP and Yorkshire pig crossbreeds. Enrichment analysis revealed that differentially expressed genes (DEGs) were significantly influenced by lipid metabolism and hormonal changes. Network analysis showed that the LEP and ACTC1 genes were connected with significant terminologies which resulted from up- and down-regulated DEGs. The results of our analysis indicate that backfat tissue could regulate swine biology during stages of growth. Consequently, our analysis provided comprehensive understanding for transcriptomic changes during growth periods.

Abstract

Recently, interest in the function of pig backfat (BF) has increased in the field of livestock animals, and many transcriptome-based studies using commercial pig breeds have been conducted. However, there is a lack of comprehensive studies regarding the biological mechanisms of Korean native pigs (KNPs) and Yorkshire pig crossbreeds. In this study, therefore, BF samples of F1 crossbreeds of KNPs and Yorkshire pigs were investigated to identify differentially expressed genes (DEGs) and their related terms using RNA-sequencing analysis. DEG analysis identified 611 DEGs, of which 182 were up-regulated and 429 were down-regulated. Lipid metabolism was identified in the up-regulated genes, whereas growth and maturation-related terminologies were identified in the down-regulated genes. LEP and ACTC1 were identified as highly connected core genes during functional gene network analysis. Fat tissue was observed to affect lipid metabolism and organ development due to hormonal changes driven by transcriptional alteration. This study provides a comprehensive understanding of BF contribution to crossbreeds of KNPs and Yorkshire pigs during growth periods.

Genome-Wide Detection of Genetic Loci and Candidate Genes for Body Conformation Traits in Duroc × Landrace × Yorkshire Crossbred Pigs

The Duroc × (Landrace × Yorkshire) hybrid pigs (DLY) are the most popular commercial pigs, providing consumers with the largest source of pork. In order to gain more insights into the genetic architecture of economically important traits in pigs, we performed a genome-wide association study (GWAS) using the GeneSeek Porcine 50 K SNP Chip to map the genetic markers and genes associated with body conformation traits (BCT) in 311 DLY pigs. The quantitative traits analyzed included body weight (BW), carcass length (CL), body length (BL), body height (BH), and body mass index (BMI). BMI was defined as BMI_CL, BMI_BL, and BMI_BH, respectively, based on CL, BL, and BH phenotypic data. We identified 82 SNPs for the seven traits by GEMMA-based and FarmCPU-based GWASs. Both methods detected two quantitative trait loci (QTL) on SSC8 and SSC17 for body conformation traits. Several candidate genes (such as TNFAIP3, KDM4C, HSPG2, BMP2, PLCB4, and GRM5) were found to be associated with body weight and body conformation traits in pigs. Notably, the BMP2 gene had pleiotropic effects on CL, BL, BH, BMI_CL, and BMI_BL and is proposed as a strong candidate gene for body size due to its involvement in growth and bone development. Furthermore, gene set enrichment analysis indicated that most of the pathway terms are associated with regulation of cell growth, negative regulation of cell population proliferation, and chondrocyte differentiation. We anticipate that these results further advance our understanding of the genetic architecture of body conformation traits in the popular commercial DLY pigs and provide new insights into the genetic architecture of BMI in pigs.

Genome-wide association study on milk production and somatic cell score for Thai dairy cattle using weighted single-step approach with random regression test-day model

Genome-wide association studies are a powerful tool to identify genomic regions and variants associated with phenotypes. However, only limited mutual confirmation from different studies is available. The objectives of this study were to identify genomic regions as well as genes and pathways associated with the first-lactation milk, fat, protein, and total solid yields; fat, protein, and total solid percentage; and somatic cell score (SCS) in a Thai dairy cattle population. Effects of SNPs were estimated by a weighted single-step GWAS, which back-solved the genomic breeding values predicted using single-step genomic BLUP (ssGBLUP) fitting a single-trait random regression test-day model. Genomic regions that explained at least 0.5% of the total genetic variance were selected for further analyses of candidate genes. Despite the small number of genotyped animals, genomic predictions led to an improvement in the accuracy over the traditional BLUP. Genomic predictions using weighted ssGBLUP were slightly better than the ssGBLUP. The genomic regions associated with milk production traits contained 210 candidate genes on 19 chromosomes [Bos taurus autosome (BTA) 1 to 7, 9, 11 to 16, 20 to 21, 26 to 27 and 29], whereas 21 candidate genes on 3 chromosomes (BTA 11, 16, and 21) were associated with SCS. Many genomic regions explained a small fraction of the genetic variance, indicating polygenic inheritance of the studied traits. Several candidate genes coincided with previous reports for milk production traits in Holstein cattle, especially a large region of genes on BTA14. We identified 141 and 5 novel genes related to milk production and SCS, respectively. These novel genes were also found to be functionally related to heat tolerance (e.g., SLC45A2, IRAG1, and LOC101902172), longevity (e.g., SYT10 and LOC101903327), and fertility (e.g., PAG1). These findings may be attributed to indirect selection in our population. Identified biological networks including intracellular cell transportation and protein catabolism implicate milk production, whereas the immunological pathways such as lymphocyte activation are closely related to SCS. Further studies are required to validate our findings before exploiting them in genomic selection.

Evidence for and localization of proposed causative variants in cattle and pig genomes

BACKGROUND

This paper reviews the localization of published potential causative variants in contemporary pig and cattle reference genomes, and the evidence for their causality. In spite of the difficulties inherent to the identification of causative variants from genetic mapping and genome-wide association studies, researchers in animal genetics have proposed putative causative variants for several traits relevant to livestock breeding.

RESULTS

For this review, we read the literature that supports potential causative variants in 13 genes (ABCG2, DGAT1, GHR, IGF2, MC4R, MSTN, NR6A1, PHGK1, PRKAG3, PLRL, RYR1, SYNGR2 and VRTN) in cattle and pigs, and localized them in contemporary reference genomes. We review the evidence for their causality, by aiming to separate the evidence for the locus, the proposed causative gene and the proposed causative variant, and report the bioinformatic searches and tactics needed to localize the sequence variants in the cattle or pig genome.

CONCLUSIONS

Taken together, there is usually good evidence for the association at the locus level, some evidence for a specific causative gene at eight of the loci, and some experimental evidence for a specific causative variant at six of the loci. We recommend that researchers who report new potential causative variants use referenced coordinate systems, show local sequence context, and submit variants to repositories.

A major QTL at the LHCGR/FSHR locus for multiple birth in Holstein cattle

BACKGROUND

Twin and multiple births are rare in cattle and have a negative impact on the performance and health of cows and calves. Therefore, selection against multiple birth would be desirable in dairy cattle breeds such as Holstein. We applied different methods to decipher the genetic architecture of this trait using de-regressed breeding values for maternal multiple birth of ~ 2500 Holstein individuals to perform genome-wide association analyses using ~ 600 K imputed single nucleotide polymorphisms (SNPs).

RESULTS

In the population studied, we found no significant genetic trend over time of the estimated breeding values for multiple birth, which indicates that this trait has not been selected for in the past. In addition to several suggestive non-significant quantitative trait loci (QTL) on different chromosomes, we identified a major QTL on chromosome 11 for maternal multiple birth that explains ~ 16% of the total genetic variance. Using a haplotype-based approach, this QTL was fine-mapped to a 70-kb window on chromosome 11 between 31.00 and 31.07 Mb that harbors two functional candidate genes (LHCGR and FSHR). Analysis of whole-genome sequence data by linkage-disequilibrium estimation revealed a regulatory variant in the 5'-region of LHCGR as a possible candidate causal variant for the identified major QTL. Furthermore, the identified haplotype showed significant effects on stillbirth and days to first service.

CONCLUSIONS

QTL detection and subsequent identification of causal variants in livestock species remain challenging in spite of the availability of large-scale genotype and phenotype data. Here, we report for the first time a major QTL for multiple birth in Holstein cattle and provide evidence for a linked variant in the non-coding region of a functional candidate gene. This discovery, which is a first step towards the understanding of the genetic architecture of this polygenic trait, opens the path for future selection against this undesirable trait, and thus contributes to increased animal health and welfare.

Tests of association based on genomic windows can lead to spurious associations when using genotype panels with heterogeneous SNP densities

Dense single nucleotide polymorphism (SNP) panels are widely used for genome-wide association studies (GWAS). In these panels, SNPs within a genomic segment tend to be highly correlated. Thus, association studies based on testing the significance of single SNPs are not very effective, and genomic-window based tests have been proposed to address this problem. However, when the SNP density on the genotype panel is not homogeneous, genomic-window based tests can lead to the detection of spurious associations by declaring effects of genomic windows that explain a large proportion of genetic variance as significant. We propose two methods to solve this problem.

Pluripotency and Growth Factors in Early Embryonic Development of Mammals: A Comparative Approach

The regulation of early events in mammalian embryonic development is a complex process. In the early stages, pluripotency, cellular differentiation, and growth should occur at specific times and these events are regulated by different genes that are expressed at specific times and locations. The genes related to pluripotency and cellular differentiation, and growth factors that determine successful embryonic development are different (or differentially expressed) among mammalian species. Some genes are fundamental for controlling pluripotency in some species but less fundamental in others, for example, Oct4 is particularly relevant in bovine early embryonic development, whereas Oct4 inhibition does not affect ovine early embryonic development. In addition, some mechanisms that regulate cellular differentiation do not seem to be clear or evolutionarily conserved. After cellular differentiation, growth factors are relevant in early development, and their effects also differ among species, for example, insulin-like growth factor improves the blastocyst development rate in some species but does not have the same effect in mice. Some growth factors influence genes related to pluripotency, and therefore, their role in early embryo development is not limited to cell growth but could also involve the earliest stages of development. In this review, we summarize the differences among mammalian species regarding the regulation of pluripotency, cellular differentiation, and growth factors in the early stages of embryonic development.

Genome-Wide Association Analysis Reveals the Genetic Architecture of Parasite (Cryptocaryon irritans) Resistance in Large Yellow Croaker (Larimichthys crocea)

Large yellow croaker is an important marine culture species in China. Recently, the large yellow croaker industry is threatened by various disease problems, especially for the white spot disease, which is caused by parasite Cryptocaryon irritans. In the current study, we conducted a genome-wide association study (GWAS) for C. irritans resistance in two large yellow croaker populations (n = 264 and n = 480, respectively). We identified 15 QTL with explained genetic variance ranging from 1 to 8% in the two populations. One QTL on chromosome 23 was shared by the two populations, and three QTL had been reported in the previous study. We identified a lot of biological pathways associated with C. irritans resistance, such as hormone transport, response to bacterium, apoptotic process, acute inflammatory response to antigenic stimulus, and NF-kappa B signaling pathway. The genes casp8 and traf6 involved in regulatory network for apoptosis and inflammation were identified to be candidate genes for C. irritans resistance. Our results showed the complex polygenic architecture of resistance of large yellow croaker against C. irritans. These results would be helpful for the researches of the molecular mechanism of C. irritans resistance and genome-assisted breeding of large yellow croaker.

Tracing selection signatures in the pig genome gives evidence for selective pressures on a unique curly hair phenotype in Mangalitza

Selection for desirable traits and breed-specific phenotypes has left distinctive footprints in the genome of pigs. As representative of a breed with strong selective traces aiming for robustness, health and performance, the Mangalitza pig, a native curly-haired pig breed from Hungary, was investigated in this study. Whole genome sequencing and SNP chip genotyping was performed to detect runs of homozygosity (ROH) in Mangalitza and Mangalitza-crossbreeds. We identified breed specific ROH regions harboring genes associated with the development of the curly hair type and further characteristics of this breed. Further analysis of two matings of Mangalitza with straight-coated pig breeds confirmed an autosomal dominant inheritance of curly hair. Subsequent scanning of the genome for variant effects on this trait revealed two variants potentially affecting hair follicle development and differentiation. Validation in a large sample set as well as in imputed SNP data confirmed these variants to be Mangalitza-specific. Herein, we demonstrated how strong artificial selection has shaped the genome in Mangalitza pigs and left traces in the form of selection signatures. This knowledge on genomic variation promoting unique phenotypes like curly hair provides an important resource for futures studies unraveling genetic effects for special characteristics in livestock.

Sicilian Black Pig: An Overview

Simple Summary

The conservation of the genetic variability of animals used for food production and non-food raw materials and services is a problem of primary importance at a global level. In recent years, conservation of biodiversity in livestock species has been favoring the need to preserve genetic variability of the autochthonous breeds, exploiting them in the context of production systems. In this context, a precious genetic reserve is represented by autochthonous breeds used for the production of typical products used in Italian gastronomic traditions, of which some organoleptic properties of their meats that could disappear due to severe selection programs are being recovered. Currently, the survival of autochthonous breeds is linked to various reasons such as their rusticity, i.e., the adaptability to difficult environmental conditions, and to the higher market value of their productions obtained according to traditional methods compared to the industrial production types. As information on autochthonous Italian pigs is limited, further research aims at making better use of these breeds and at increasing the knowledge of their genetic variability.

Abstract

The Sicilian black pig (SB) (Nero Siciliano), also known as the Nero dei Nebrodi, Nero delle Madonie, or Nero dell’Etna pig ecotype, is an autochthonous Italian breed. The origins of this breed date back to Greek and Carthaginian dominations. In ancient times, its breeding was fairly common throughout Sicily, registering only a temporary reduction during the Arab domination. This breed is known primarily for its distinctive black coat, although some individuals display wattles and a partially or wholly white face. The SB pig has a birth rate with an average per sow of 7.6 piglets, each of 1.4 kg live body weight, showing an average daily gain (ADG) of 346 g/day during the fattening period. Slaughter generally takes place at an average age of 390 days, with an average live weight of 95 kg. This breed also appears to withstand adverse climatic conditions and resist disease. The purpose of this manuscript is to offer a general overview regarding the Sicilian Black pig and to consider the recent findings related to genome investigation. The recent application of Next Generation Sequencing (NGS) technologies in the study of the genome of autochthonous breeds showed that polymorphisms of some candidate genes for production performance and phenotypic traits represent important information for selection processes. The protection of autochthonous breeds, intended as sources of genomic diversity for the further improvements of pigs for commercial use, constitutes a valuable opportunity to create new sustainable pig chains.

Selection and validation of differentially expressed metabolic and immune genes in weaned Ghurrah versus crossbred piglets

In the present investigation, differentially expressed genes (DEGs) were studied using RNA sequencing (RNA-seq) technique in porcine peripheral blood mononuclear cells (PBMC) of weaned Ghurrah and crossbred piglets at 3-month age. Transcriptomic analysis was done using three different packages, namely, EBSeq, DESeq2, and edgeR, to identify the DEGs between Ghurrah and crossbred piglets. Total 7717 DEGs were commonly identified by all three packages, out of which 4151 genes found to be up-regulated, and 3566 genes were down-regulated. Functional annotation of these DEGs indicated metabolism as the most commonly enriched category followed by the immune response. Genes related to metabolism and growth were up-regulated in crossbred piglets as compared with Ghurrah piglets, whereas immunity-related genes were up-regulated in Ghurrah piglets elucidating the disease resistance nature of this indigenous breed over crossbred counterparts. Further, eight DEGs, namely, LRP-1, ADCY4, ERRFI1, LDHD, ARG1, OASL, MGARP, and S100A8, were validated by qRT-PCR in a separate set of biological samples and found to be in concordance with RNA-seq results. Finding in the present study provides insight into genes and their molecular mechanisms governing difference in growth performance between Ghurrah and crossbred pigs.

A 17-bp InDel (rs668420586) within goat CHCHD7 gene located in growth-related QTL affecting body measurement traits

The Coiled-Coil-Helix-Coiled-Coil-Helix Domain Containing 7 (CHCHD7) gene was located in a growth-related major QTL that participated in the process of bone cells metabolism in animals by regulating mitochondrial copper homeostasis and cytochrome C oxidase assembly. Therefore, we speculated that CHCHD7 gene might be involved in animal growth and body size. Herein, we discovered a 17-bp insertion/deletion (indel) within the goat CHCHD7 gene. Then, we detected this variation in Shaanbei White Cashmere (SBWC, n = 1055) goats and Inner Mongolia White Cashmere (IMWC, n = 743) goats (Alathai type) using the mathematical expectation (ME) method. We then analyzed the correlation between these genotypes and goat body measurement traits. The results showed that the minor allelic frequency (MAF) was 0.011 in SBWC, and 0.048 in IMWC. In SBWC and IMWC, the reaction time by ME method was reduced by 36.78% and 27.59%, respectively, compared to the traditional method of screening samples one by one. Moreover, in SBWC goats, the 17-bp indel was significantly associated with body measurement traits (e.g. body height, and body length) in adults. In IMWC goats, the 17-bp indel was correlated with body measurement traits (e.g. body height) in weaners. In SBWC and IMWC goat populations, the body measurement traits of the individuals homozygous for 17-bp indel were higher than those in heterozygous individuals, except for the case of cannon circumference in IMWC weaners. These findings showed that the 17-bp insertion mutation within the goat CHCHD7 gene significantly affected body morphometric traits, and could provide a basis for marker-assisted selection (MAS) breeding of cashmere goats.

Signatures of selection analysis using whole-genome sequence data reveals novel candidate genes for pony and light horse types

Natural selection and domestication have shaped modern horse populations, resulting in a vast range of phenotypically diverse breeds. Horse breeds are classified into three types (pony, light, and draft) generally based on their body type. Understanding the genetic basis of horse type variation and selective pressures related to the evolutionary trend can be particularly important for current selection strategies. Whole-genome sequences were generated for 14 pony and 32 light horses to investigate the genetic signatures of selection of the horse type in pony and light horses. In the overlapping extremes of the fixation index and nucleotide diversity results, we found novel genomic signatures of selective sweeps near key genes previously implicated in body measurements including C4ORF33, CRB1, CPN1, FAM13A, and FGF12 that may influence variation in pony and light horse types. This study contributes to a better understanding of the genetic background of differences between pony and light horse types.

Genomic measures of inbreeding coefficients and genome-wide scan for runs of homozygosity islands in Iranian river buffalo, Bubalus bubalis

Background

Consecutive homozygous fragments of a genome inherited by offspring from a common ancestor are known as runs of homozygosity (ROH). ROH can be used to calculate genomic inbreeding and to identify genomic regions that are potentially under historical selection pressure. The dataset of our study consisted of 254 Azeri (AZ) and 115 Khuzestani (KHZ) river buffalo genotyped for ~ 65,000 SNPs for the following two purposes: 1) to estimate and compare inbreeding calculated using ROH (F_ROH), excess of homozygosity (F_HOM), correlation between uniting gametes (F_UNI), and diagonal elements of the genomic relationship matrix (F_GRM); 2) to identify frequently occurring ROH (i.e. ROH islands) for our selection signature and gene enrichment studies.

Results

In this study, 9102 ROH were identified, with an average number of 21.2 ± 13.1 and 33.2 ± 15.9 segments per animal in AZ and KHZ breeds, respectively. On average in AZ, 4.35% (108.8 ± 120.3 Mb), and in KHZ, 5.96% (149.1 ± 107.7 Mb) of the genome was autozygous. The estimated inbreeding values based on F_HOM, F_UNI and F_GRM were higher in AZ than they were in KHZ, which was in contrast to the F_ROH estimates. We identified 11 ROH islands (four in AZ and seven in KHZ). In the KHZ breed, the genes located in ROH islands were enriched for multiple Gene Ontology (GO) terms (P ≤ 0.05). The genes located in ROH islands were associated with diverse biological functions and traits such as body size and muscle development (BMP2), immune response (CYP27B1), milk production and components (MARS, ADRA1A, and KCTD16), coat colour and pigmentation (PMEL and MYO1A), reproductive traits (INHBC, INHBE, STAT6 and PCNA), and bone development (SUOX).

Conclusion

The calculated F_ROH was in line with expected higher inbreeding in KHZ than in AZ because of the smaller effective population size of KHZ. Thus, we find that F_ROH can be used as a robust estimate of genomic inbreeding. Further, the majority of ROH peaks were overlapped with or in close proximity to the previously reported genomic regions with signatures of selection. This tells us that it is likely that the genes in the ROH islands have been subject to artificial or natural selection.

Genome-wide analyses reveal the regions involved in the phenotypic diversity in Sicilian pigs

Nero Siciliano (Sicilian Black, SB) is a local pig breed generally of uniform black color. In addition to this officially recognized breed, there are animals showing morphological characteristics resembling the SB but with gray hair (Sicilian Grey, SG). The SG, compared with the SB, also shows a more compact structure with greater transverse diameters, higher average daily gains and lower thickness of the back fat. In this study, using the Illumina PorcineSNP60 BeadChip, we run genome-wide analyses to identify regions that may explain the phenotypic differences between SB (n = 21) and SG (n = 27) individuals. Combining the results of the two case-control approaches (GWAS and F_ST ), we identified two significant regions, one on SSC5 (95 401 083 bp) and one on SSC15 (55 051 435 bp), which contains several candidate genes related to growth traits in pig. The results of the Bayesian population differentiation approach identified a marker near the MGAT4C, a gene associated with average daily gain in pigs. Finally, scanning the genome for runs of homozygosity islands, we found that the two groups have different runs of homozygosity islands, with several candidate genes involved in coat color (in SG) or related to different pig performance traits (in SB). In summary, the two analyzed groups differed for several phenotypic traits, and genes involved in these traits (growth, meat traits and coat color) were detected. This study provided another contribution to the identification of genomic regions involved in phenotypic variability in local pig populations.

Evaluation of genotype quality parameters for SowPro90, a new genotyping array for swine1

Understanding early predictors of sow fertility has the potential to improve genomic predictions. A custom SNP array (SowPro90 produced by Affymetrix) was developed to include genetic variants overlapping quantitative trait loci for age at puberty, one of the earliest indicators of sow fertility, as well as variants related to innate and adaptive immunity. The polymorphisms included in the custom genotyping array were identified using multiple genomic approaches including deep genomic and transcriptomic sequencing and genome-wide associations. Animals from research and commercial populations (n = 2,586) were genotyped for 103,476 SNPs included in SowPro90. To assess the quality of data generated, genotype concordance was evaluated between the SowPro90 and Porcine SNP60 BeadArray using a subset of common SNP (n = 44,708) and animals (n = 277). The mean genotype concordance rate per SNP was 98.4%. Differences in distribution of data quality were observed between the platforms indicating the need for platform specific thresholds for quality parameters. The optimal thresholds for SowPro90 (≥97% SNP and ≥93% sample call rate) were obtained by analyzing the data quality distribution and genotype concordance per SNP across platforms. At ≥97% SNP call rate, there were 42,151 SNPs (94.3%) retained with a mean genotype concordance of 98.6% across platforms. Similarly, ≥94% SNPs and ≥85% sample call rates were established as thresholds for Porcine SNP60 BeadArray. At ≥94% SNPs call rate, there were 41,043 SNPs (91.8%) retained with a mean genotype concordance of 98.6% across platforms. Final evaluation of SowPro90 array content (n = 103,476) at ≥97% SNPs and ≥93% sample call rates allowed retention of 89,040 SNPs (86%) for downstream analysis. The findings and strategy for quality control could be helpful in identifying consistent, high-quality genotypes for genomic evaluations, especially when integrating genotype data from different platforms.

A genome-wide association study for feed efficiency-related traits in a crossbred pig population

Feed efficiency (FE) is one of the most important traits in pig production. However, it is difficult and costly to measure it, limiting the collection of large amount of data for an accurate selection for better FE. Therefore, the identification of single-nucleotide polymorphisms (SNPs) associated with FE-related traits to be used in the genetic evaluation is of great interest of pig breeding programs for increasing the prediction accuracy and the genetic progress of these traits. The objective of this study was to identify SNPs significantly associated with FE-related traits: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). We also aimed to identify potential candidate genes for these traits. Phenotypic information recorded on a population of 2386 three-way crossbreed pigs that were genotyped for 51 468 SNPs was used. We identified three loci of quantitative trait (QTL) regions associated with ADG and three QTL regions associated with ADFI; however, no significant association was found for FCR. A false discovery rate (FDR) ≤ 0.005 was used as the threshold for declaring an association as significant. The QTL regions associated with ADG on Sus scrofa chromosome (SSC) 1 were located between 177.01 and 185.47 Mb, which overlaps with the QTL regions for ADFI on SSC1 (173.26 and 185.47 Mb). The other QTL region for ADG was located on SSC12 (2.87 and 3.22 Mb). The most significant SNPs in these QTL regions explained up to 3.26% of the phenotypic variance of these traits. The non-identification of genomic regions associated with FCR can be explained by the complexity of this trait, which is a ratio between ADG and ADFI. Finally, the genes CDH19, CDH7, RNF152, MC4R, PMAIP1, FEM1B and GAA were the candidate genes found in the 1 Mb window around the QTL regions identified in this study. Among them, the MC4R gene (SSC1) has a well-known function related to ADG and ADFI. In this study, we identified three QTL regions for ADG (SSC1 and SSC12) and three for ADFI (SSC1). These regions were previously described in purebred pig populations; however, to our knowledge, this is the first study to confirm the relevance of these QTL regions in a crossbred pig population. The potential use of the SNPs and genes identified in this study in prediction models that combine genomic selection and marker-assisted selection should be evaluated for increasing the prediction accuracy of these traits in this population.

Identification of muscle-specific candidate genes in Simmental beef cattle using imputed next generation sequencing

Genome-wide association studies (GWAS) have commonly been used to identify candidate genes that control economically important traits in livestock. Our objective was to detect potential candidate genes associated mainly with muscle development traits related to dimension of hindquarter in cattle. A next generation sequencing (NGS) dataset to imputed to 12 million single nucleotide polymorphisms (SNPs) (from 1252 Simmental beef cattle) were used to search for genes affecting hindquarter traits using a linear, mixed model approach. We also used haplotype and linkage disequilibrium blocks to further support our identifications. We identified 202 significant SNPs in the bovine BTA4 chromosome region associated with width of hind leg, based on a stringent statistical threshold (p = 0.05/ effective number of SNPs identified). After exploring the region around these SNPs, we found candidate genes that were potentially related to the associated markers. More importantly, we identified a region of approximately 280 Kb on the BTA4 chromosome that harbored several muscle specific candidate genes, genes to be in a potential region for muscle development. However, we also found candidate gene SLC13A1 on BTA4, which seems to be associated with bone disorders (such as chondrodysplasia) in Simmental beef cattle.

Genome-wide association study and genomic predictions for exterior traits in Yorkshire pigs1

The objectives of this study were to identify informative genomic regions that affect the exterior traits of purebred Korean Yorkshire pigs and to investigate and compare the accuracy of genomic prediction for response variables. Phenotypic data on body height (BH), body length (BL), and total teat number (TTN) from 2,432 Yorkshire pigs were used to obtain breeding values including as response variable the estimated breeding value (EBV) and 2 types of deregressed EBVs-one including the parent average (DEBVincPA) and the other excluding it (DEBVexcPA). A final genotype panel comprising 46,199 SNP markers was retained for analysis after quality control for common SNPs. The BayesB and BayesC methods-with various π and weighted response variables (EBV, DEBVincPA, or DEBVexcPA)-were used to estimate SNP effects, through the genome-wide association study. The significance of genomic windows (1 Mb) was obtained at 1.0% additive genetic variance and was subsequently used to identify informative genomic regions. Furthermore, SNPs with a high model frequency (≥0.90) were considered informative. The accuracy of genomic prediction was estimated using a 5-fold cross-validation with the K-means clustering method. Genomic accuracy was measured as the genomic correlation between the molecular breeding value and the individual weighted response variables (EBV, DEBVincPA, or DEBVexcPA). The number of identified informative windows (1 Mb) for BH, BL, and TTN was 4, 3, and 4, respectively. The number of significant SNPs for BH, BL, and TTN was 6, 4, and 5, respectively. Diversity π did not influence the accuracy of genomic prediction. The BayesB method showed slightly higher genomic accuracy for exterior traits than BayesC method in this study. In addition, the genomic accuracy using DEBVincPA as response variable was higher than that using other response variables. Therefore, the genomic accuracy using BayesB (π = 0.90) with DEBVinPA as a response variable was the most effective in this study. The genomic accuracy values for BH, BL, and TTN were calculated to be 0.52, 0.60, and 0.51, respectively.

Marker-trait associations and genomic predictions of interspecific pear (Pyrus) fruit characteristics

Interspecific pear (Pyrus spp.) hybrid populations are often used to develop novel cultivars. Pear cultivar breeding is a lengthy process because of long juvenility and the subsequent time required for reliable fruit phenotyping. Molecular techniques such as genome-wide association (GWA) and genomic selection (GS) provide an opportunity to fast-forward the development of high-value cultivars. We evaluated the genetic architecture of 10 pear fruit phenotypes (including sensory traits) and the potential of GS using genotyping-by-sequencing of 550 hybrid seedlings from nine interrelated full-sib families. Results from GWA suggested a complex polygenic nature of all 10 traits as the maximum variance explained by each marker was less than 4% of the phenotypic variance. The effect-size of SNPs for each trait suggested many genes of small effect and few of moderate effect. Some genomic regions associated with pear sensory traits were similar to those reported for apple – possibly a result of high synteny between the apple and pear genomes. The average (across nine families) GS accuracy varied from 0.32 (for crispness) to 0.62 (for sweetness), with an across-trait average of 0.42. Further efforts are needed to develop larger genotype-phenotype datasets in order to predict fruit phenotypes of untested seedlings with sufficient efficiency.

Genome-wide scan reveals genetic divergence and diverse adaptive selection in Chinese local cattle

Background

Understanding the population structure and genetic bases of well-adapted cattle breeds to local environments is one of the most essential tasks to develop appropriate genetic improvement programs.

Results

We performed a comprehensive study to investigate the population structure, divergence and selection signatures at genome-wide level in diverse Chinese local cattle using Bovine HD SNPs array, including two breeds from North China, one breed from Northwest China, three breeds from Southwest China and two breeds from South China. Population genetic analyses revealed the genetic structures of these populations were mostly related to the geographic locations. Notably, we detected 294 and 1263 candidate regions under selection using the di and iHS approaches, respectively. A series of group-specific and breed-specific candidate genes were identified, which are involved in immune response, sexual maturation, stature related, birth and bone weight, embryonic development, coat colors and adaptation. Furthermore, haplotype diversity and network pattern for candidate genes, including LPGAT1, LCORL, PPP1R8, RXFP2 and FANCA, suggest that these genes have been under differential selection pressures in various environmental conditions.

Conclusions

Our results shed insights into diverse selection during breed formation in Chinese local cattle. These findings may promote the application of genome-assisted breeding for well-adapted local breeds with economic and ecological importance.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5822-y) contains supplementary material, which is available to authorized users.

High-density genotyping reveals signatures of selection related to acclimation and economically important traits in 15 local sheep breeds from Russia

Background

Domestication and centuries of selective breeding have changed genomes of sheep breeds to respond to environmental challenges and human needs. The genomes of local breeds, therefore, are valuable sources of genomic variants to be used to understand mechanisms of response to adaptation and artificial selection. As a step toward this we performed a high-density genotyping and comprehensive scans for signatures of selection in the genomes from 15 local sheep breeds reared across Russia.

Results

Results demonstrated that the genomes of Russian sheep breeds contain multiple regions under putative selection. More than 50% of these regions matched with intervals identified in previous scans for selective sweeps in sheep genomes. These regions contain well-known candidate genes related to morphology, adaptation, and domestication (e.g., KITLG, KIT, MITF, and MC1R), wool quality and quantity (e.g., DSG@, DSC@, and KRT@), growth and feed intake (e.g., HOXA@, HOXC@, LCORL, NCAPG, LAP3, and CCSER1), reproduction (e.g., CMTM6, HTRA1, GNAQ, UBQLN1, and IFT88), and milk-related traits (e.g., ABCG2, SPP1, ACSS1, and ACSS2). In addition, multiple genes that are putatively related to environmental adaptations were top-ranked in selected intervals (e.g., EGFR, HSPH1, NMUR1, EDNRB, PRL, TSHR, and ADAMTS5). Moreover, we observed that multiple key genes involved in human hereditary sensory and autonomic neuropathies, and genetic disorders accompanied with an inability to feel pain and environmental temperatures, were top-ranked in multiple or individual sheep breeds from Russia pointing to a possible mechanism of adaptation to harsh climatic conditions.

Conclusions

Our work represents the first comprehensive scan for signatures of selection in genomes of local sheep breeds from the Russian Federation of both European and Asian origins. We confirmed that the genomes of Russian sheep contain previously identified signatures of selection, demonstrating the robustness of our integrative approach. Multiple novel signatures of selection were found near genes which could be related to adaptation to the harsh environments of Russia. Our study forms a basis for future work on using Russian sheep genomes to spot specific genetic variants or haplotypes to be used in efforts on developing next-generation highly productive breeds, better suited to diverse Eurasian environments.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5537-0) contains supplementary material, which is available to authorized users.

Genome-wide association studies for 30 haematological and blood clinical-biochemical traits in Large White pigs reveal genomic regions affecting intermediate phenotypes

Haematological and clinical-biochemical parameters are considered indicators of the physiological/health status of animals and might serve as intermediate phenotypes to link physiological aspects to production and disease resistance traits. The dissection of the genetic variability affecting these phenotypes might be useful to describe the resilience of the animals and to support the usefulness of the pig as animal model. Here, we analysed 15 haematological and 15 clinical-biochemical traits in 843 Italian Large White pigs, via three genome-wide association scan approaches (single-trait, multi-trait and Bayesian). We identified 52 quantitative trait loci (QTLs) associated with 29 out of 30 analysed blood parameters, with the most significant QTL identified on porcine chromosome 14 for basophil count. Some QTL regions harbour genes that may be the obvious candidates: QTLs for cholesterol parameters identified genes (ADCY8, APOB, ATG5, CDKAL1, PCSK5, PRL and SOX6) that are directly involved in cholesterol metabolism; other QTLs highlighted genes encoding the enzymes being measured [ALT (known also as GPT) and AST (known also as GOT)]. Moreover, the multivariate approach strengthened the association results for several candidate genes. The obtained results can contribute to define new measurable phenotypes that could be applied in breeding programs as proxies for more complex traits.

Optimising the identification of causal variants across varying genetic architectures in crops

Association studies use statistical links between genetic markers and the phenotype variation across many individuals to identify genes controlling variation in the target phenotype. However, this approach, particularly conducted on a genome-wide scale (GWAS), has limited power to identify the genes responsible for variation in traits controlled by complex genetic architectures. In this study, we employ real-world genotype datasets from four crop species with distinct minor allele frequency distributions, population structures and linkage disequilibrium patterns. We demonstrate that different GWAS statistical approaches provide favourable trade-offs between power and accuracy for traits controlled by different types of genetic architectures. FarmCPU provides the most favourable outcomes for moderately complex traits while a Bayesian approach adopted from genomic prediction provides the most favourable outcomes for extremely complex traits. We assert that by estimating the complexity of genetic architectures for target traits and selecting an appropriate statistical approach for the degree of complexity detected, researchers can substantially improve the ability to dissect the genetic factors controlling complex traits such as flowering time, plant height and yield component.

Bayes Factor-Based Regulatory Gene Network Analysis of Genome-Wide Association Study of Economic Traits in a Purebred Swine Population

Early stage prediction of economic trait performance is important and directly linked to profitability of farm pig production. Genome-wide association study (GWAS) has been applied to find causative genomic regions of traits. This study established a regulatory gene network using GWAS for critical economic pig characteristics, centered on easily measurable body fat thickness in live animals. We genotyped 2,681 pigs using Illumina Porcine SNP60, followed by GWAS to calculate Bayes factors for 47,697 single nucleotide polymorphisms (SNPs) of seven traits. Using this information, SNPs were annotated with specific genes near genome locations to establish the association weight matrix. The entire network consisted of 226 nodes and 6,921 significant edges. For in silico validation of their interactions, we conducted regulatory sequence analysis of predicted target genes of transcription factors (TFs). Three key regulatory TFs were identified to guarantee maximum coverage: AT-rich interaction domain 3B (ARID3B), glial cell missing homolog 1 (GCM1), and GLI family zinc finger 2 (GLI2). We identified numerous genes targeted by ARID3B, associated with cellular processes. GCM1 and GLI2 were involved in developmental processes, and their shared target genes regulated multicellular organismal process. This system biology-based function analysis might contribute to enhancing understanding of economic pig traits.

Transcriptome analysis to identify long non coding RNA (lncRNA) and characterize their functional role in back fat tissue of pig

Long non coding RNAs (lncRNA) have been previously found to be involved in important cellular activities like epigenetics, implantation, cell growth etc. in pigs. However, comprehensive analysis of lncRNA in back fat tissues at different developmental stages in pigs is still lacking. In this study we conducted transcriptome analysis in the back fat tissue of a F1 crossbred Korean Native Pig (KNP) × Yorkshire Pig to identify lncRNA. We investigated their role in 16 pigs at two different growth stages; stage 1 (10 weeks, n = 8) and stage 2 (26 weeks, n = 8). After quality assessment of sequencing reads, we got a total of 1,641,165 assembled transcripts out of eight paired end read from each stage. Among them, 6808 lncRNA transcripts were identified by filtering on the basis of multiple parameters like read length ≥ 200 nucleotides, exon numbers ≥2, FPKM ≥0.5, coding potential score < 0 etc. PFAM and RFAM were used to filter out all possible protein coding genes and housekeeping RNAs respectively. A total of 103 lncRNAs and 1057 mRNAs were found to be differentially expressed (DE) between the two stages (|log2FC| > 2, q < 0.05). We also identified 306 genes located around 100 kb upstream and 234 genes downstream around these DE lncRNA transcripts. The expression of top eleven DE lncRNAs (COL4A6, LY7S, MYH2, OXCT1, SMPDL3A, TMEM182, TTC36, RFOOOO4, RFOOO15, RFOOO45, CADM2) had been validating by qRT-PCR. Pathway and GO terms analysis showed that, positive regulation of biosynthetic process, Wnt signaling pathway, cellular protein modification process, and positive regulation of nitrogen compound were differentially enriched. Our results suggested that, KEGG pathways such as protein digestion and absorption, Arrhythmogenic right ventricular cardiomyopathy (ARVC) to be significantly enriched in both DE lncRNAs as well as DE mRNAs and involved in back fat tissues development. It also suggests that, identified lncRNAs are involved in regulation of important adipose tissues development pathways.

Comparison of genome-wide association and genomic prediction methods for milk production traits in Korean Holstein cattle

OBJECTIVE

The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B.

METHODS

Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients.

RESULTS

A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were 1.50±0.21 and 1.18±0.26 for MY305, 1.75±0.33 and 1.14±0.20 for FY305, and 1.59±0.20 and 1.14±0.15 for PY305, respectively.

CONCLUSION

From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.

BLINK: a package for the next level of genome-wide association studies with both individuals and markers in the millions

Big datasets, accumulated from biomedical and agronomic studies, provide the potential to identify genes that control complex human diseases and agriculturally important traits through genome-wide association studies (GWAS). However, big datasets also lead to extreme computational challenges, especially when sophisticated statistical models are employed to simultaneously reduce false positives and false negatives. The newly developed fixed and random model circulating probability unification (FarmCPU) method uses a bin method under the assumption that quantitative trait nucleotides (QTNs) are evenly distributed throughout the genome. The estimated QTNs are used to separate a mixed linear model into a computationally efficient fixed effect model (FEM) and a computationally expensive random effect model (REM), which are then used iteratively. To completely eliminate the computationally expensive REM, we replaced REM with FEM by using Bayesian information criteria. To eliminate the requirement that QTNs be evenly distributed throughout the genome, we replaced the bin method with linkage disequilibrium information. The new method is called Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK). Both real and simulated data analyses demonstrated that BLINK improves statistical power compared to FarmCPU, in addition to remarkably reducing computing time. Now, a dataset with one million individuals and one-half million markers can be analyzed within three hours, instead of one week using FarmCPU.

Empirical Comparisons of Different Statistical Models To Identify and Validate Kernel Row Number-Associated Variants from Structured Multi-parent Mapping Populations of Maize

Advances in next generation sequencing technologies and statistical approaches enable genome-wide dissection of phenotypic traits via genome-wide association studies (GWAS). Although multiple statistical approaches for conducting GWAS are available, the power and cross-validation rates of many approaches have been mostly tested using simulated data. Empirical comparisons of single variant (SV) and multi-variant (MV) GWAS approaches have not been conducted to test if a single approach or a combination of SV and MV is effective, through identification and cross-validation of trait-associated loci. In this study, kernel row number (KRN) data were collected from a set of 6,230 entries derived from the Nested Association Mapping (NAM) population and related populations. Three different types of GWAS analyses were performed: 1) single-variant (SV), 2) stepwise regression (STR) and 3) a Bayesian-based multi-variant (BMV) model. Using SV, STR, and BMV models, 257, 300, and 442 KRN-associated variants (KAVs) were identified in the initial GWAS analyses. Of these, 231 KAVs were subjected to genetic validation using three unrelated populations that were not included in the initial GWAS. Genetic validation results suggest that the three GWAS approaches are complementary. Interestingly, KAVs in low recombination regions were more likely to exhibit associations in independent populations than KAVs in recombinationally active regions, probably as a consequence of linkage disequilibrium. The KAVs identified in this study have the potential to enhance our understanding of the genetic basis of ear development.

Genome-wide scan reveals divergent selection among taurine and zebu cattle populations from different regions

In this study, to identify genomic signatures of divergent selection, we genotyped 10 cattle breeds/populations (n = 275), representing eight Ethiopian cattle populations (n = 229) and two zebu populations (n = 46) adapted to tropical and sub-tropical environments, using the high-density single-nucleotide polymorphisms (SNPs) derived mainly from Bos indicus breeds, and using five reference taurine breeds (n = 212). Population genetic differentiation (F_ST ) values across sliding windows were estimated between zebu and reference combined taurine breeds. The most differentiated regions (F_ST  ≥ 0.53), representing the top 1% smoothed F_ST values, were considered to represent regions under diversifying selection. In total, 285 and 317 genes were identified in the comparisons of Ethiopian cattle with taurine and Asian zebu with taurine respectively. Some of these genes are involved in stress responses/thermo-tolerance and DNA damage repair (HSPA4, HSF1, CMPK1 and EIF2AK4), pigmentation (ERBB3 and MYO1A), reproduction/fertility (UBE2D3, ID3 and PSPC1), immune response (PIK3CD and AKIRIN2) and body stature and size (MBP2, LYN and NPM1). Additionally, the candidate genes were associated with functional terms (e.g. cellular response to stress, DNA repair, inflammatory response) important for physiological adaptation to environmental stresses. The results of our study may shed light on the influence of artificial and natural selection in shaping the genomic diversity of modern cattle breeds and also may serve as a basis for further genetic investigation of traits of tropical adaptation in cattle.

Genome-wide association study of body morphological traits in Sudanese goats

Long-term selection of goats for a certain production system and/or different environmental conditions will be reflected in the body morphology of the animals under selection. To investigate the variation contributing to different morphological traits and to identify genomic regions that are associated with body morphological traits in Sudanese goats, we genotyped 96 females belonging to four Sudanese goat breeds with the SNP52 BeadChip. After quality control of the data, the genome-wide association study was performed using 95 goats and 24 027 informative single nucleotide polymorphisms (SNPs). Bicoastal diameter was significantly associated (LOD = 6.32) with snp10185-scaffold1365-620922 on chromosome 2. The minor allele has an additive effect, increasing the bicoastal diameter by 2.6 cm. A second significant association was found between body length and snp56482-scaffold89-467312 on chromosome 3 (LOD = 5.65). The minor allele is associated with increased body length. Additionally, five regions were suggestive for cannon bone, head width, rump length and withers height (LOD > 5). Only one gene (CNTNAP5) is located within the 1-Mb region surrounding the significant SNP for bicoastal diameter on chromosome 2. The body length QTL on chromosome 3 harbors 49 genes. Further research is required to validate the observed associations and to prioritize candidate genes.