Genome-wide association analysis for quantitative trait loci influencing Warner-Bratzler shear force in five taurine cattle breeds

Genome-wide scans identify biological and metabolic pathways regulating carcass and meat quality traits in beef cattle

Genome association studies (GWAS) provides knowledge about the genetic architecture of beef-related traits that allow linking the target phenotype to genomic information aiding breeding decision. Thus, the present study aims to uncover the genetic mechanism involved in carcass (REA: rib eye area, BF: backfat thickness, and HCW: hot carcass weight) and meat quality traits (SF: shear-force, MARB: marbling score, and IMF: intramuscular fat content) in Nellore cattle. For this, 6910 young bulls with phenotypic information and 23,859 animals genotyped with 435 k markers were used to perform the weighted single-step GBLUP (WssGBLUP) approach, considering two iterations. The top 10 genomic regions explained 8.13, 11.81, and 9.58% of the additive genetic variance, harboring a total of 119, 143, and 95 positional candidate genes for REA, BF, and HCW, respectively. For meat quality traits, the top 10 windows explained a large proportion of the total genetic variance for SF (14.95%), MARB (17.56%), and IMF (21.41%) surrounding 92, 155, and 111 candidate genes, respectively. Relevant candidate genes (CAST, PLAG1, XKR4, PLAGL2, AQP3/AQP7, MYLK2, WWOX, CARTPT, and PLA2G16) are related to physiological aspects affecting growth, carcass, meat quality, feed intake, and reproductive traits by signaling pathways controlling muscle control, key signal metabolic molecules INS / IGF-1 pathway, lipid metabolism, and adipose tissue development. The GWAS results provided insights into the genetic control of the traits studied and the genes found are potential candidates to be used in the improvement of carcass and meat quality traits.

Genomic diversity and relationship analyses of endangered German Black Pied cattle (DSN) to 68 other taurine breeds based on whole-genome sequencing

German Black Pied cattle (Deutsches Schwarzbuntes Niederungsrind, DSN) are an endangered dual-purpose cattle breed originating from the North Sea region. The population comprises about 2,500 cattle and is considered one of the ancestral populations of the modern Holstein breed. The current study aimed at defining the breeds closest related to DSN cattle, characterizing their genomic diversity and inbreeding. In addition, the detection of selection signatures between DSN and Holstein was a goal. Relationship analyses using fixation index (F_ST), phylogenetic, and admixture analyses were performed between DSN and 68 other breeds from the 1000 Bull Genomes Project. Nucleotide diversity, observed heterozygosity, and expected heterozygosity were calculated as metrics for genomic diversity. Inbreeding was measured as excess of homozygosity (F_Hom) and genomic inbreeding (F_RoH) through runs of homozygosity (RoHs). Region-wide F_ST and cross-population-extended haplotype homozygosity (XP-EHH) between DSN and Holstein were used to detect selection signatures between the two breeds, and RoH islands were used to detect selection signatures within DSN and Holstein. DSN showed a close genetic relationship with breeds from the Netherlands, Belgium, Northern Germany, and Scandinavia, such as Dutch Friesian Red, Dutch Improved Red, Belgian Red White Campine, Red White Dual Purpose, Modern Angler, Modern Danish Red, and Holstein. The nucleotide diversity in DSN (0.151%) was higher than in Holstein (0.147%) and other breeds, e.g., Norwegian Red (0.149%), Red White Dual Purpose (0.149%), Swedish Red (0.149%), Hereford (0.145%), Angus (0.143%), and Jersey (0.136%). The F_Hom and F_RoH values in DSN were among the lowest. Regions with high F_ST between DSN and Holstein, significant XP-EHH regions, and RoH islands detected in both breeds harbor candidate genes that were previously reported for milk, meat, fertility, production, and health traits, including one QTL detected in DSN for endoparasite infection resistance. The selection signatures between DSN and Holstein provide evidence of regions responsible for the dual-purpose properties of DSN and the milk type of Holstein. Despite the small population size, DSN has a high level of diversity and low inbreeding. F_ST supports its relatedness to breeds from the same geographic origin and provides information on potential gene pools that could be used to maintain diversity in DSN.

Fitting Genomic Prediction Models with Different Marker Effects among Prefectures to Carcass Traits in Japanese Black Cattle

We fitted statistical models, which assumed single-nucleotide polymorphism (SNP) marker effects differing across the fattened steers marketed into different prefectures, to the records for cold carcass weight (CW) and marbling score (MS) of 1036, 733, and 279 Japanese Black fattened steers marketed into Tottori, Hiroshima, and Hyogo prefectures in Japan, respectively. Genotype data on 33,059 SNPs was used. Five models that assume only common SNP effects to all the steers (model 1), common effects plus SNP effects differing between the steers marketed into Hyogo prefecture and others (model 2), only the SNP effects differing between Hyogo steers and others (model 3), common effects plus SNP effects specific to each prefecture (model 4), and only the effects specific to each prefecture (model 5) were exploited. For both traits, slightly lower values of residual variance than that of model 1 were estimated when fitting all other models. Estimated genetic correlation among the prefectures in models 2 and 4 ranged to 0.53 to 0.71, all <0.8. These results might support that the SNP effects differ among the prefectures to some degree, although we discussed the necessity of careful consideration to interpret the current results.

Sustained Effects of Muscle Calpain System Genotypes on Tenderness Phenotypes of South African Beef Bulls during Ageing up to 20 Days

Simple Summary

When searching for genetic markers for the selection of more tender beef, it is important to maintain minimal environmental variation from pre-slaughter, right through to the ageing process, to ensure the accuracy of the obtained phenotypes. This is because beef quality traits have a large environmental component that can greatly alter the characteristics of the meat, which would not reflect a true genetic effect. We propose that variable ageing times are especially important in determining whether markers are associated with tenderization or not. Our analyses included candidate genes for the protein degrading enzyme system for calpains, because they contribute the most to tenderization. We were able to validate these markers in South African beef cattle, where they could be useful for selection. The timing of the collection of tenderness data was critical, as only a few (6/134) genetic markers sustained their association with tenderization over ageing to 20 days. A larger tenderization effect earlier in ageing, as shown here for the capn1_187 and capn1_4751 markers, would decrease the length of ageing. This would not only increase profits, but also decrease the energy needed during the storage and refrigeration of aged beef, decreasing the carbon footprint of beef production.

Abstract

The most important factor that determines beef tenderness is its proteolytic activity, and the balance between calpain-1 protease activity and calpastatin inhibition is especially important, while contributions can also arise from calpain-2 and, possibly, calpain-3. The meat ageing process itself affects these processes. To determine whether genotypes in the calpain–calpastatin system can enhance tenderness through a 20-day ageing period, South African purebred beef bulls (n = 166) were genotyped using the Illumina BovineHD SNP BeadChip through a gene-based association analysis targeting the cast, capn3, capn2 and capn1 genes. The Warner–Bratzler shear force (WBSF) and myofibril fragment length (MFL) of Longissimus thoracis et lumborum (LTL) steaks were evaluated between d 3 and d 20 of ageing, with protease enzyme activity in the first 20 h post-mortem. Although several of the 134 SNPs are associated with tenderness, only seven SNP in the cast, capn2 and capn1 genes sustained genetic associations, additive to the ageing-associated increases in tenderness for at least three of the four ageing periods. While most genomic associations were relatively stable over time, some genotypes within the SNP responded differently to ageing, resulting in altered genomic effects over time. The level of ageing at which genomic associations are performed is an important factor that determines whether SNPs affect tenderness phenotypes.

The Meat Quality Characteristics of Holstein Calves: The Story of Israeli 'Dairy Beef'

Global animal production systems are often criticized for their lack of sustainability and insufficient resilience to ensure food security. The ‘farm-to-fork’ approach aims at orienting food systems towards the creation of a positive environmental impact, nutritious, healthy, safe and sufficient foods, and fairer economic returns for primary producers. Many countries rely on an imported supply of live animals to fulfill their needs for fresh meat. In Israel, ~60% of the sources of fresh beef come from the import of live animals. In order to encourage sustainable beef production in Israel, the proportion of local beef should be raised at the expense of imported animals. However, for this to be achieved, the superior performance of local beef should be justified. The current study was conducted to compare between the meat quality characteristics of local (Israeli Holstein; N = 205) vs. imported (Australian; N = 169) animals. Generally, while the imported calves presented a higher dressing percentage (p < 0.0001), the local animals were characterized by tenderer meat (p < 0.0001), longer sarcomeres (p < 0.0001), higher a* color attributes and pH (p < 0.001), superior cooking (p = 0.002) and thawing loss (p < 0.0001), higher intra-muscular fat (IMF) content, and a higher PUFA proportion (p < 0.01 and p < 0.0001, respectively) and PUFA:SFA ratio. The findings shown herein may provide sound arguments for stakeholders and policy makers to facilitate sustainable local beef production in Israel.

Genomic Loci Affecting Milk Production in German Black Pied Cattle (DSN)

German Black Pied cattle (DSN) is an endangered population of about 2,550 dual-purpose cattle in Germany. Having a milk yield of about 2,500 kg less than the predominant dairy breed Holstein, the preservation of DSN is supported by the German government and the EU. The identification of the genomic loci affecting milk production in DSN can provide a basis for selection decisions for genetic improvement of DSN in order to increase market chances through the improvement of milk yield. A genome-wide association analysis of 30 milk traits was conducted in different lactation periods and numbers. Association using multiple linear regression models in R was performed on 1,490 DSN cattle genotyped with BovineSNP50 SNP-chip. 41 significant and 20 suggestive SNPs affecting milk production traits in DSN were identified, as well as 15 additional SNPs for protein content which are less reliable due to high inflation. The most significant effects on milk yield in DSN were detected on chromosomes 1, 6, and 20. The region on chromosome 6 was located nearby the casein gene cluster and the corresponding haplotype overlapped the CSN3 gene (casein kappa). Associations for fat and protein yield and content were also detected. High correlation between traits of the same lactation period or number led to some SNPs being significant for multiple investigated traits. Half of all identified SNPs have been reported in other studies, previously. 15 SNPs were associated with the same traits in other breeds. The other associated SNPs have been reported previously for traits such as exterior, health, meat and carcass, production, and reproduction traits. No association could be detected between DGAT1 and other known milk genes with milk production traits despite the close relationship between DSN and Holstein. The results of this study confirmed that many SNPs identified in other breeds as associated with milk traits also affect milk traits in dual-purpose DSN cattle and can be used for further genetic analysis to identify genes and causal variants that affect milk production in DSN cattle.

Breed Ancestry, Divergence, Admixture, and Selection Patterns of the Simbra Crossbreed

In this study, we evaluated an admixed South African Simbra crossbred population, as well as the Brahman (Indicine) and Simmental (Taurine) ancestor populations to understand their genetic architecture and detect genomic regions showing signatures of selection. Animals were genotyped using the Illumina BovineLD v2 BeadChip (7K). Genomic structure analysis confirmed that the South African Simbra cattle have an admixed genome, composed of 5/8 Taurine and 3/8 Indicine, ensuring that the Simbra genome maintains favorable traits from both breeds. Genomic regions that have been targeted by selection were detected using the linkage disequilibrium-based methods iHS and Rsb. These analyses identified 10 candidate regions that are potentially under strong positive selection, containing genes implicated in cattle health and production (e.g., TRIM63, KCNA10, NCAM1, SMIM5, MIER3, and SLC24A4). These adaptive alleles likely contribute to the biological and cellular functions determining phenotype in the Simbra hybrid cattle breed. Our data suggested that these alleles were introgressed from the breed's original indicine and taurine ancestors. The Simbra breed thus possesses derived parental alleles that combine the superior traits of the founder Brahman and Simmental breeds. These regions and genes might represent good targets for ad-hoc physiological studies, selection of breeding material and eventually even gene editing, for improved traits in modern cattle breeds. This study represents an important step toward developing and improving strategies for selection and population breeding to ultimately contribute meaningfully to the beef production industry.

Genome-wide association study between copy number variation regions and carcass- and meat-quality traits in Nellore cattle

Context Indicine breeds are the main source of beef products in tropical and subtropical regions. However, genetic improvement for carcass- and meat-quality traits in zebu cattle have been limited and genomics studies concerning structural variations that influence these traits are essential. Aim The aim of this study was to perform a genome-wide association study between copy number variation regions (CNVRs) and carcass- and meat quality-traits in Nellore cattle. Methods In total, 3794 animals, males and females included, were genotyped using a 777962 single-nucleotide polymorphism platform of BovineHD BeadChip (777k; Illumina Inc.). Of these, 1751 Nellore bulls were slaughtered at 24 months of age for further carcass beef analysis. The following traits were studied: beef tenderness, marbling, rib-eye area, backfat thickness and meat colour (lightness, redness and yellowness). The CNV detection was conducted through PennCNV software. The association analyses were performed using CNVRuler software. Key results Several identified genomic regions were linked to quantitative trait loci associated with fat deposition (FABP7) and lipid metabolism (PPARA; PLA2 family; BCHE), extracellular matrix (INS; COL10A1), contraction (SLC34A3; TRDN) and muscle development (CAPZP). The gene-enrichment analyses highlighted biological mechanisms directly related to the metabolism and synthesis of lipids and fatty acids. Conclusions The large number of potential candidate genes identified within the CNVRs, as well as the functions and pathways identified, should help better elucidate the genetic mechanisms involved in the expression of beef and carcass traits in Nellore cattle. Several CNVRs harboured genes that might have a functional impact to improve the beef and carcass traits. Implications The results obtained contribute to upgrade the sensorial and organoleptic attributes of Nellore cattle and make feasible the genetic improvement of carcass- and meat-quality traits.

RNA-seq analysis identifies cytoskeletal structural genes and pathways for meat quality in beef

RNA sequencing (RNA-seq) has allowed for transcriptional profiling of biological systems through the identification of differentially expressed (DE) genes and pathways. A total of 80 steers with extreme phenotypes were selected from the University of Florida multibreed Angus-Brahman herd. The average slaughter age was 12.91±8.69 months. Tenderness, juiciness and connective tissue assessed by sensory panel, along with marbling, Warner-Bratzler Shear Force (WBSF) and cooking loss, were measured in longissimus dorsi muscle. Total RNA was extracted from muscle and one RNA-seq library per sample was constructed, multiplexed, and sequenced based on protocols by Illumina HiSeq-3000 platform to generate 2×101 bp paired-end reads. The overall read mapping rate using the Btau_4.6.1 reference genome was 63%. A total of 8,799 genes were analyzed using two different methodologies, an expression association and a DE analysis. A gene and exon expression association analysis was carried out using a meat quality index on all 80 samples as a continuous response variable. The expression of 208 genes and 3,280 exons from 1,565 genes was associated with the meat quality index (p-value ≤ 0.05). A gene and isoform DE evaluation was performed analyzing two groups with extreme WBSF, tenderness and marbling. A total of 676 (adjusted p-value≤0.05), 70 (adjusted p-value≤0.1) and 198 (adjusted p-value≤0.1) genes were DE for WBSF, tenderness and marbling, respectively. A total of 106 isoforms from 98 genes for WBSF, 13 isoforms from 13 genes for tenderness and 43 isoforms from 42 genes for marbling (FDR≤0.1) were DE. Cytoskeletal and transmembrane anchoring genes and pathways were identified in the expression association, DE and the gene enrichment analyses; these proteins can have a direct effect on meat quality. Cytoskeletal proteins and transmembrane anchoring molecules can influence meat quality by allowing cytoskeletal interaction with myocyte and organelle membranes, contributing to cytoskeletal structure and architecture maintenance postmortem.

Whole Genome Sequence Data Provides Novel Insights Into the Genetic Architecture of Meat Quality Traits in Beef

Tenderness is a major quality attribute for fresh beef steaks in the United States, and meat quality traits in general are suitable candidates for genomic research. The objectives of the present analysis were to (1) perform genome-wide association (GWA) analysis for marbling, Warner-Bratzler shear force (WBSF), tenderness, and connective tissue using whole-genome data in an Angus population, (2) identify enriched pathways in each GWA analysis; (3) construct a protein-protein interaction network using the associated genes and (4) perform a μ-calpain proteolysis assessment for associated structural proteins. An Angus-sired population of 2,285 individuals was assessed. Animals were transported to a commercial packing plant and harvested at an average age of 457 ± 46 days. After 48 h postmortem, marbling was recorded by graders' visual appraisal. Two 2.54-cm steaks were sampled from each muscle for recording of WBSF, and tenderness, and connective tissue by a sensory panel. The relevance of additive effects on marbling, WBSF, tenderness, and connective tissue was evaluated on a genome-wide scale using a two-step mixed model-based approach in single-trait analysis. A tissue-restricted gene enrichment was performed for each GWA where all polymorphisms with an association p-value lower than 1 × 10-3 were included. The genes identified as associated were included in a protein-protein interaction network and a candidate structural protein assessment of proteolysis analyses. A total of 1,867, 3,181, 3,926, and 3,678 polymorphisms were significantly associated with marbling, WBSF, tenderness, and connective tissue, respectively. The associate region on BTA29 (36,432,655-44,313,046 bp) harbors 13 highly significant markers for meat quality traits. Enrichment for the GO term GO:0005634 (Nucleus), which includes transcription factors, was evident. The final protein-protein network included 431 interations between 349 genes. The 42 most important genes based on significance that encode structural proteins were included in a proteolysis analysis, and 81% of these proteins were potential μ-Calpain substrates. Overall, this comprehensive study unraveled genetic variants, genes and mechanisms of action responsible for the variation in meat quality traits. Our findings can provide opportunities for improving meat quality in beef cattle via marker-assisted selection.

Transcriptome profiling of longissimus lumborum in Holstein bulls and steers with different beef qualities

Previous research regarding Holstein cows has mainly focused on increasing milk yield. However, in order to maximize the economical profits of Holstein cattle farming, it is necessary to fully take advantage of Holstein bulls to produce high-grade beef. The present study aims to investigate different transcriptomic profiling of Holstein bulls and steers, via high-throughput RNA-sequencing (RNA-seq). The growth and beef quality traits of Holstein steers and bulls were characterized via assessment of weight, rib eye area, marbling score, shear force and intramuscular fat percentage of the longissimus lumborum (LL) muscle. The results indicated that castration improved the meat quality, yet reduced the meat yield. Subsequently, RNA-seq of the LL muscle from Holstein steers and bulls revealed a total of 56 differentially expressed genes (DEGs). We performed the functional enrichment analysis in Gene Ontology (GO) annotations of the DEGs using GOseq R package software and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using KOBAS tool. Through the integrated analysis of DEGs with reported QTLs and SNPs, seven promising candidate genes potentially affecting the beef quality of LL muscle following castration were discovered, including muscle structural protein coding genes (MYH1, MYH4, MYH10) and functional protein coding genes (GADL1, CYP2R1, EEPD1, SHISA3). Among them, MYH10, GADL1, CYP2R1, EEPD1 and SHISA3 were novel candidate genes associated with beef quality traits. Notably, EEPD1 was associated with both meat quality and reproduction traits, thus indicating its overlapping role in responding to hormone change, and subsequently inducing beef quality improvement. Our findings provide a complete dataset of gene expression profile of LL in Holstein bulls and steers, and will aid in understanding how castration influence meat yield and quality.

Genomic regions associated with muscularity in beef cattle differ in five contrasting cattle breeds

BACKGROUND

Linear type traits, which reflect the muscular characteristics of an animal, could provide insight into how, in some cases, morphologically very different animals can yield the same carcass weight. Such variability may contribute to differences in the overall value of the carcass since primal cuts vary greatly in price; such variability may also hinder successful genome-based association studies. Therefore, the objective of our study was to identify genomic regions that are associated with five muscularity linear type traits and to determine if these significant regions are common across five different breeds. Analyses were carried out using linear mixed models on imputed whole-genome sequence data in each of the five breeds, separately. Then, the results of the within-breed analyses were used to conduct an across-breed meta-analysis per trait.

RESULTS

We identified many quantitative trait loci (QTL) that are located across the whole genome and associated with each trait in each breed. The only commonality among the breeds and traits was a large-effect pleiotropic QTL on BTA2 that contained the MSTN gene, which was associated with all traits in the Charolais and Limousin breeds. Other plausible candidate genes were identified for muscularity traits including PDE1A, PPP1R1C and multiple collagen and HOXD genes. In addition, associated (gene ontology) GO terms and KEGG pathways tended to differ between breeds and between traits especially in the numerically smaller populations of Angus, Hereford, and Simmental breeds. Most of the SNPs that were associated with any of the traits were intergenic or intronic SNPs located within regulatory regions of the genome.

CONCLUSIONS

The commonality between the Charolais and Limousin breeds indicates that the genetic architecture of the muscularity traits may be similar in these breeds due to their similar origins. Conversely, there were vast differences in the QTL associated with muscularity in Angus, Hereford, and Simmental. Knowledge of these differences in genetic architecture between breeds is useful to develop accurate genomic prediction equations that can operate effectively across breeds. Overall, the associated QTL differed according to trait, which suggests that breeding for a morphologically different (e.g. longer and wider versus shorter and smaller) more efficient animal may become possible in the future.

Genome-wide association study of milk and reproductive traits in dual-purpose Xinjiang Brown cattle

Background

Dual-purpose cattle are more adaptive to environmental challenges than single-purpose dairy or beef cattle. Balance among milk, reproductive, and mastitis resistance traits in breeding programs is therefore more critical for dual-purpose cattle to increase net income and maintain well-being. With dual-purpose Xinjiang Brown cattle adapted to the Xinjiang Region in northwestern China, we conducted genome-wide association studies (GWAS) to dissect the genetic architecture related to milk, reproductive, and mastitis resistance traits. Phenotypic data were collected for 2410 individuals measured during 1995–2017. By adding another 445 ancestors, a total of 2855 related individuals were used to derive estimated breeding values for all individuals, including the 2410 individuals with phenotypes. Among phenotyped individuals, we genotyped 403 cows with the Illumina 150 K Bovine BeadChip.

Results

GWAS were conducted with the FarmCPU (Fixed and random model circulating probability unification) method. We identified 12 markers significantly associated with six of the 10 traits under the threshold of 5% after a Bonferroni multiple test correction. Seven of these SNPs were in QTL regions previously identified to be associated with related traits. One identified SNP, BovineHD1600006691, was significantly associated with both age at first service and age at first calving. This SNP directly overlapped a QTL previously reported to be associated with calving ease. Within 160 Kb upstream and downstream of each significant SNP identified, we speculated candidate genes based on functionality. Four of the SNPs were located within four candidate genes, including CDH2, which is linked to milk fat percentage, and GABRG2, which is associated with milk protein yield.

Conclusions

These findings are beneficial not only for breeding through marker-assisted selection, but also for genome editing underlying the related traits to enhance the overall performance of dual-purpose cattle.

Multi-breed genome-wide association studies across countries for electronically recorded behavior traits in local dual-purpose cows

Basic bovine behavior is a crucial parameter influencing cattle domestication. In addition, behavior has an impact on cattle productivity, welfare and adaptation. The aim of the present study was to infer quantitative genetic and genomic mechanisms contributing to natural dual-purpose cow behavior in grazing systems. In this regard, we genotyped five dual-purpose breeds for a dense SNP marker panel from four different European countries. All cows from the across-country study were equipped with the same electronic recording devices. In this regard, we analyzed 97,049 longitudinal sensor behavior observations from 319 local dual-purpose cows for rumination, feeding, basic activity, high active, not active and ear temperature. According to the specific sensor behaviors and following a welfare protocol, we computed two different welfare indices. For genomic breed characterizations and multi-breed genome-wide association studies, sensor traits and test-day production records were merged with 35,826 SNP markers per cow. For the estimation of variance components, we used the pedigree relationship matrix and a combined similarity matrix that simultaneously included both pedigree and genotypes. Heritabilities for feeding, high active and not active were in a moderate range from 0.16 to 0.20. Estimates were very similar from both relationship matrix-modeling approaches and had quite small standard errors. Heritabilities for the remaining sensor traits (feeding, basic activity, ear temperature) and welfare indices were lower than 0.09. Five significant SNPs on chromosomes 11, 17, 27 and 29 were associated with rumination, and two different SNPs significantly influenced the sensor traits “not active” (chromosome 13) and “feeding” (chromosome 23). Gene annotation analyses inferred 22 potential candidate genes with a false discovery rate lower than 20%, mostly associated with rumination (13 genes) and feeding (8 genes). Mendelian randomization based on genomic variants (i.e., the instrumental variables) was used to infer causal inference between an exposure and an outcome. Significant regression coefficients among behavior traits indicate that all specific behavioral mechanisms contribute to similar physiological processes. The regression coefficients of rumination and feeding on milk yield were 0.10 kg/% and 0.12 kg/%, respectively, indicating their positive influence on dual-purpose cow productivity. Genomically, an improved welfare behavior of grazing cattle, i.e., a higher score for welfare indices, was significantly associated with increased fat and protein percentages.

Validation Study of SNPs in CAPN1-CAST Genes on the Tenderness of Muscles (Longissimus thoracis and Semimembranosus) in Hanwoo (Korean Cattle)

Simple Summary

For meat tenderness, single nucleotide polymorphisms (SNPs) in the μ-calpain (CAPN1) and calpastatin (CAST) genes have been reported to be associated with Warner-Bratzler shear force (WBSF) in different cattle populations, including Korean Hanwoo cattle. In this study, we validated the association of seven SNPs in CAPN1 and CAST genes with meat tenderness in two different muscle cuts tenderness in the Longissimus thoracis (LT) and Semimembranosus (SM) muscles. Two SNPs in CAPN1 and one SNPs in CAST genes showed association with WBSF of both muscle types. Furthermore, of twelve reconstructed haplotypes, six demonstrated significant associations with WBSF values. These findings may be one of the strong evidences that CAPN1 and CAST gene mutations are strongly associated with WBSF. The information of significantly-associated SNPs and the resulted haplotypes could be utilized in the Hanwoo breeding program for further genetic improvement of tenderness traits.

Abstract

Previous studies demonstrated that polymorphisms in the μ-calpain (CAPN1) and calpastatin (CAST) genes had significant effects on meat tenderness in different cattle populations. The aim of this study was to validate the potential association of seven single nucleotide polymorphisms (SNPs) harbored in these two candidate genes with meat tenderness in the Longissimus thoracis (LT) and Semimembranosus (SM) muscles. A total of 1000 animals were genotyped using TaqMan SNP genotyping arrays, and the meat tenderness of two muscle (LT and SM at 7 days post-slaughter) was assessed based on Warner-Bratzler WBSF (WBSF) testing. We observed significant associations of the CAPN1:c.580T>C, CAPN1:c.658T>C and CAST:c.1985G>C polymorphisms (p < 0.05) with the WBSF values in the LT and SM muscles. Additive effects of the C allele in CAPN1:c.580T>C and CAST:c.1985G>C were associated with an increase of 0.16 and 0.15 kg, and 0.08 and 0.26 kg WBSF in the LT and SM, respectively; CAPN1:c.658T>C had negative effects on the WBSFs. Furthermore, six reconstructed haplotypes demonstrated significant associations with WBSF values (p < 0.05). In conclusion, the significant associations identified between the SNPs in CAPN1, CAST and WBSF values could be utilized in marker-assisted selection programs in order to improve the beef tenderness of Hanwoo cattle.

Genome wide association and gene enrichment analysis reveal membrane anchoring and structural proteins associated with meat quality in beef

BACKGROUND

Meat quality related phenotypes are difficult and expensive to measure and predict but are ideal candidates for genomic selection if genetic markers that account for a worthwhile proportion of the phenotypic variation can be identified. The objectives of this study were: 1) to perform genome wide association analyses for Warner-Bratzler Shear Force (WBSF), marbling, cooking loss, tenderness, juiciness, connective tissue and flavor; 2) to determine enriched pathways present in each genome wide association analysis; and 3) to identify potential candidate genes with multiple quantitative trait loci (QTL) associated with meat quality.

RESULTS

The WBSF, marbling and cooking loss traits were measured in longissimus dorsi muscle from 672 steers. Out of these, 495 animals were used to measure tenderness, juiciness, connective tissue and flavor by a sensory panel. All animals were genotyped for 221,077 markers and included in a genome wide association analysis. A total number of 68 genomic regions covering 52 genes were identified using the whole genome association approach; 48% of these genes encode transmembrane proteins or membrane associated molecules. Two enrichment analysis were performed: a tissue restricted gene enrichment applying a correlation analysis between raw associated single nucleotide polymorphisms (SNPs) by trait, and a functional classification analysis performed using the DAVID Bioinformatic Resources 6.8 server. The tissue restricted gene enrichment approach identified eleven pathways including "Endoplasmic reticulum membrane" that influenced multiple traits simultaneously. The DAVID functional classification analysis uncovered eleven clusters related to transmembrane or structural proteins. A gene network was constructed where the number of raw associated uncorrelated SNPs for each gene across all traits was used as a weight. A multiple SNP association analysis was performed for the top five most connected genes in the gene-trait network. The gene network identified the EVC2, ANXA10 and PKHD1 genes as potentially harboring multiple QTLs. Polymorphisms identified in structural proteins can modulate two different processes with direct effect on meat quality: in vivo myocyte cytoskeletal organization and postmortem proteolysis.

CONCLUSION

The main result from the present analysis is the uncovering of several candidate genes associated with meat quality that have structural function in the skeletal muscle.

Sliding window haplotype approaches overcome single SNP analysis limitations in identifying genes for meat tenderness in Nelore cattle

Background

Traditional single nucleotide polymorphism (SNP) genome-wide association analysis (GWAA) can be inefficient because single SNPs provide limited genetic information about genomic regions. On the other hand, using haplotypes in the statistical analysis may increase the extent of linkage disequilibrium (LD) between haplotypes and causal variants and may also potentially capture epistastic interactions between variants within a haplotyped locus, providing an increase in the power and robustness of the association studies. We performed GWAA (413,355 SNP markers) using haplotypes based on variable-sized sliding windows and compared the results to a single-SNP GWAA using Warner-Bratzler shear force measured in the longissimus thorasis muscle of 3161 Nelore bulls to ascertain the optimal window size for identifying the genomic regions that influence meat tenderness.

Results

The GWAA using single SNPs identified eight variants influencing meat tenderness on BTA 3, 4, 9, 10 and 11. However, thirty-three putative meat tenderness QTL were detected on BTA 1, 3, 4, 5, 8, 9, 10, 11, 15, 17, 18, 24, 25, 26 and 29 using variable-sized sliding haplotype windows. Analyses using sliding window haplotypes of 3, 5, 7, 9 and 11 SNPs identified 57, 61, 42, 39, and 21% of all thirty-three putative QTL regions, respectively; however, the analyses using the 3 and 5 SNP haplotypes, cumulatively detected 88% of the putative QTL. The genes associated with variation in meat tenderness participate in myogenesis, neurogenesis, lipid and fatty acid metabolism and skeletal muscle structure or composition processes.

Conclusions

GWAA using haplotypes based on variable-sized sliding windows allowed the detection of more QTL than traditional single-SNP GWAA. Analyses using smaller haplotypes (3 and 5 SNPs) detected a higher proportion of the putative QTL.

Electronic supplementary material

The online version of this article (10.1186/s12863-019-0713-4) contains supplementary material, which is available to authorized users.

Structural Equation Modeling and Whole-Genome Scans Uncover Chromosome Regions and Enriched Pathways for Carcass and Meat Quality in Beef

Structural equation models involving latent variables are useful tools for formulating hypothesized models defined by theoretical variables and causal links between these variables. The objectives of this study were: (1) to identify latent variables underlying carcass and meat quality traits and (2) to perform whole-genome scans for these latent variables in order to identify genomic regions and individual genes with both direct and indirect effects. A total of 726 steers from an Angus-Brahman multibreed population with records for 22 phenotypes were used. A total of 480 animals were genotyped with the GGP Bovine F-250. The single-step genomic best linear unbiased prediction method was used to estimate the amount of genetic variance explained for each latent variable by chromosome regions of 20 adjacent SNP-windows across the genome. Three types of genetic effects were considered: (1) direct effects on a single latent phenotype; (2) direct effects on two latent phenotypes simultaneously; and (3) indirect effects. The final structural model included carcass quality as an independent latent variable and meat quality as a dependent latent variable. Carcass quality was defined by quality grade, fat over the ribeye and marbling, while the meat quality was described by juiciness, tenderness and connective tissue, all of them measured through a taste panel. From 571 associated genomic regions (643 genes), each one explaining at least 0.05% of the additive variance, 159 regions (179 genes) were associated with carcass quality, 106 regions (114 genes) were associated with both carcass and meat quality, 242 regions (266 genes) were associated with meat quality, and 64 regions (84 genes) were associated with carcass quality, having an indirect effect on meat quality. Three biological mechanisms emerged from these findings: postmortem proteolysis of structural proteins and cellular compartmentalization, cellular proliferation and differentiation of adipocytes, and fat deposition.

Genome variants associated with RNA splicing variations in bovine are extensively shared between tissues

Background

Mammalian phenotypes are shaped by numerous genome variants, many of which may regulate gene transcription or RNA splicing. To identify variants with regulatory functions in cattle, an important economic and model species, we used sequence variants to map a type of expression quantitative trait loci (expression QTLs) that are associated with variations in the RNA splicing, i.e., sQTLs. To further the understanding of regulatory variants, sQTLs were compare with other two types of expression QTLs, 1) variants associated with variations in gene expression, i.e., geQTLs and 2) variants associated with variations in exon expression, i.e., eeQTLs, in different tissues.

Results

Using whole genome and RNA sequence data from four tissues of over 200 cattle, sQTLs identified using exon inclusion ratios were verified by matching their effects on adjacent intron excision ratios. sQTLs contained the highest percentage of variants that are within the intronic region of genes and contained the lowest percentage of variants that are within intergenic regions, compared to eeQTLs and geQTLs. Many geQTLs and sQTLs are also detected as eeQTLs. Many expression QTLs, including sQTLs, were significant in all four tissues and had a similar effect in each tissue. To verify such expression QTL sharing between tissues, variants surrounding (±1 Mb) the exon or gene were used to build local genomic relationship matrices (LGRM) and estimated genetic correlations between tissues. For many exons, the splicing and expression level was determined by the same cis additive genetic variance in different tissues. Thus, an effective but simple-to-implement meta-analysis combining information from three tissues is introduced to increase power to detect and validate sQTLs. sQTLs and eeQTLs together were more enriched for variants associated with cattle complex traits, compared to geQTLs. Several putative causal mutations were identified, including an sQTL at Chr6:87392580 within the 5th exon of kappa casein (CSN3) associated with milk production traits.

Conclusions

Using novel analytical approaches, we report the first identification of numerous bovine sQTLs which are extensively shared between multiple tissue types. The significant overlaps between bovine sQTLs and complex traits QTL highlight the contribution of regulatory mutations to phenotypic variations.

Electronic supplementary material

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A genome-wide scan for signatures of selection in Azeri and Khuzestani buffalo breeds

Background

Identification of genomic regions that have been targets of selection may shed light on the genetic history of livestock populations and help to identify variation controlling commercially important phenotypes. The Azeri and Kuzestani buffalos are the most common indigenous Iranian breeds which have been subjected to divergent selection and are well adapted to completely different regions. Examining the genetic structure of these populations may identify genomic regions associated with adaptation to the different environments and production goals.

Results

A set of 385 water buffalo samples from Azeri (N = 262) and Khuzestani (N = 123) breeds were genotyped using the Axiom® Buffalo Genotyping 90 K Array. The unbiased fixation index method (F_ST) was used to detect signatures of selection. In total, 13 regions with outlier F_ST values (0.1%) were identified. Annotation of these regions using the UMD3.1 Bos taurus Genome Assembly was performed to find putative candidate genes and QTLs within the selected regions. Putative candidate genes identified include FBXO9, NDFIP1, ACTR3, ARHGAP26, SERPINF2, BOLA-DRB3, BOLA-DQB, CLN8, and MYOM2.

Conclusions

Candidate genes identified in regions potentially under selection were associated with physiological pathways including milk production, cytoskeleton organization, growth, metabolic function, apoptosis and domestication-related changes include immune and nervous system development. The QTL identified are involved in economically important traits in buffalo related to milk composition, udder structure, somatic cell count, meat quality, and carcass and body weight.

Electronic supplementary material

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Genome-wide scan reveals population stratification and footprints of recent selection in Nelore cattle

Background

This study aimed at (1) assessing the genomic stratification of experimental lines of Nelore cattle that have experienced different selection regimes for growth traits, and (2) identifying genomic regions that have undergone recent selection. We used a sample of 763 animals genotyped with the Illumina BovineHD BeadChip, among which 674 animals originated from two lines that are maintained under directional selection for increased yearling body weight and 89 animals from a control line that is maintained under stabilizing selection.

Results

Multidimensional analysis of the genomic dissimilarity matrix and admixture analysis revealed a substantial level of population stratification between the directional selection lines and the stabilizing selection control line. Two of the three tests used to detect selection signatures (F_ST, XP-EHH and iHS) revealed six candidate regions with indications of selection, which strongly indicates truly positive signals. The set of identified candidate genes included several genes with roles that are functionally related to growth metabolism, such as COL14A1, CPT1C, CRH, TBC1D1, and XKR4.

Conclusions

The current study identified genetic stratification that resulted from almost four decades of divergent selection in an experimental Nelore population, and highlighted autosomal genomic regions that present patterns of recent selection. Our findings provide a basis for a better understanding of the metabolic mechanism that underlies the growth traits, which are modified by selection for yearling body weight.

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Association of μ-Calpain and Calpastatin Polymorphisms with Meat Tenderness in a Brahman-Angus Population

Autogenous proteolytic enzymes of the calpain family are implicated in myofibrillar protein degradation. As a result, the μ-calpain gene and its specific inhibitor, calpastatin, have been repeatedly investigated for their association with meat quality traits in cattle; however, no functional mutation has been identified for these two genes. The objectives of this study were: (1) to assess breed composition effect on tenderness; (2) to perform a linkage disequilibrium (LD) analysis in μ-calpain and calpastatin genes as well as an association analyses with tenderness; and (3) to analyze putative functional SNPs inside the significant LD block for an effect on tenderness. Tenderness measurements and genotypes for 16 SNPs in μ-calpain gene and 28 SNPs in calpastatin gene from 673 steers were analyzed. A bioinformatic analysis identified “putative functional SNPs” inside the associated LD block – polymorphisms able to produce a physical and/or chemical change in the DNA, mRNA, or translated protein in silico. Breed composition had a significant (P < 0.0001) effect on tenderness where animals with more than 80% Angus composition had the most tender meat. One 11-kb LD-block and three LD-blocks of 37, 17, and 14 kb in length were identified in the μ-calpain and calpastatin genes, respectively. Out of these, the LD-block 3 in calpastatin, tagged by SNPs located at 7-98566391 and 7-98581038, had a significant effect on tenderness with the TG-CG diplotype being approximately 1 kg more tender than the toughest diplotype, TG-CG. A total of 768 SNPs in the LD-block 3 of calpastatin were included in the bioinformatic analysis, and 28 markers were selected as putative functional SNPs inside the LD-block 3 of calpastatin; however, none of them were polymorphic in this population. Out of 15 initial polymorphisms segregating inside the LD-block 3 of calpastatin in this population, markers ARSUSMARC116, Cast5, rs730723459, and rs210861835 were found to be significantly associated with tenderness.

Genomewide association mapping and pathway analysis of meat tenderness in Polled Nellore cattle

Brazil is one of the world's largest beef exporters, although the product has a low price due to quality issues. The meat exported by Brazil is considered medium and low quality by international buyers, mainly due to lack of tenderness. The predominant Zebu breeds (80% Nellore) are known for producing tougher beef than taurine breeds. Nonetheless, some studies have shown that there is substantial genetic variability for tenderness within the Nellore breed, although it is a difficult trait to improve by conventional selection methods. Therefore, the aim of this study was to perform a genomewide association study (GWAS) and a gene set enrichment analysis to identify genomic regions and biologically relevant pathways associated with meat tenderness in Polled Nellore cattle. Data consisted of Warner-Bratzler shear force values of LM from 427 Polled Nellore animals divided into 3 experimental slaughters (years 2005, 2008, and 2010). The animals were genotyped with either the Illumina BovineHD BeadChip (777k, on 61 samples) or the GGP Indicus HD chip (77k, on 366 samples). Single nucleotide polymorphisms were excluded when the call rate was <90%, the Hardy-Weinberg proportions -value was <1% (Fisher exact test, Bonferroni adjusted), and the minor allele frequency was <1%. Imputation from the GGP Indicus HD chip to the Illumina BovineHD BeadChip was performed using the FImput program. Genomewide association analysis was performed using the Efficient Mixed Model Association eXpedited (EMMAx) and the population parameters previously determined (P3D) methods. The GWAS was complemented with a gene set enrichment analysis performed using the FatiGO procedure. Significant markers ( < 0.0001) explaining a larger proportion of variation than other significant SNPs were located on chromosomes 3, 13, 17, 20, 21, and 25, indicating QTL associated with meat tenderness throughout the genome. Additionally, gene set analysis identified 22 Gene Ontology functional terms and 2 InterPro entries that showed significant enrichment of genes associated with tenderness. The functional categories included protein tyrosine and serine/threonine kinase activity, calcium ion binding, lipid metabolic process, and growth factors, among others. These results help to elucidate the genetic architecture and metabolic pathways underlying this trait, which is of extreme economic and social importance to Brazil, because Nellore is the dominant beef cattle breed in the country.

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle

Improvements in eating satisfaction will benefit consumers and should increase beef demand which is of interest to the beef industry. Tenderness, juiciness, and flavor are major determinants of the palatability of beef and are often used to reflect eating satisfaction. Carcass qualities are used as indicator traits for meat quality, with higher quality grade carcasses expected to relate to more tender and palatable meat. However, meat quality is a complex concept determined by many component traits making interpretation of genome-wide association studies (GWAS) on any one component challenging to interpret. Recent approaches combining traditional GWAS with gene network interactions theory could be more efficient in dissecting the genetic architecture of complex traits. Phenotypic measures of 23 traits reflecting carcass characteristics, components of meat quality, along with mineral and peptide concentrations were used along with Illumina 54k bovine SNP genotypes to derive an annotated gene network associated with meat quality in 2,110 Angus beef cattle. The efficient mixed model association (EMMAX) approach in combination with a genomic relationship matrix was used to directly estimate the associations between 54k SNP genotypes and each of the 23 component traits. Genomic correlated regions were identified by partial correlations which were further used along with an information theory algorithm to derive gene network clusters. Correlated SNP across 23 component traits were subjected to network scoring and visualization software to identify significant SNP. Significant pathways implicated in the meat quality complex through GO term enrichment analysis included angiogenesis, inflammation, transmembrane transporter activity, and receptor activity. These results suggest that network analysis using partial correlations and annotation of significant SNP can reveal the genetic architecture of complex traits and provide novel information regarding biological mechanisms and genes that lead to complex phenotypes, like meat quality, and the nutritional and healthfulness value of beef. Improvements in genome annotation and knowledge of gene function will contribute to more comprehensive analyses that will advance our ability to dissect the complex architecture of complex traits.

Genome-wide mapping of large deletions and their population-genetic properties in dairy cattle

Large genomic deletions are potential candidate for loss-of-function, which could be lethal as homozygote. Analysing whole genome data of 175 cattle, we report 8,480 large deletions (199 bp–773 KB) with an overall false discovery rate of 8.8%; 82% of which are novel compared with deletions in the dbVar database. Breakpoint sequence analyses revealed that majority (24 of 29 tested) of the deletions contain microhomology/homology at breakpoint, and therefore, most likely generated by microhomology-mediated end joining. We observed higher differentiation among breeds for deletions in some genic-regions, such as ABCA12, TTC1, VWA3B, TSHR, DST/BPAG1, and CD1D. The genes overlapping deletions are on average evolutionarily less conserved compared with known mouse lethal genes (P-value = 2.3 × 10⁻⁶). We report 167 natural gene knockouts in cattle that are apparently nonessential as live homozygote individuals are observed. These genes are functionally enriched for immunoglobulin domains, olfactory receptors, and MHC classes (FDR = 2.06 × 10⁻²², 2.06 × 10⁻²², 7.01 × 10⁻⁶, respectively). We also demonstrate that deletions are enriched for health and fertility related quantitative trait loci (2-and 1.5-fold enrichment, Fisher’s P-value = 8.91 × 10⁻¹⁰ and 7.4 × 10⁻¹¹, respectively). Finally, we identified and confirmed the breakpoint of a ∼525 KB deletion on Chr23:12,291,761-12,817,087 (overlapping BTBD9, GLO1 and DNAH8), causing stillbirth in Nordic Red Cattle.

Accuracy of genomic breeding values for meat tenderness in Polled Nellore cattle

Zebu () cattle, mostly of the Nellore breed, comprise more than 80% of the beef cattle in Brazil, given their tolerance of the tropical climate and high resistance to ectoparasites. Despite their advantages for production in tropical environments, zebu cattle tend to produce tougher meat than Bos taurus breeds. Traditional genetic selection to improve meat tenderness is constrained by the difficulty and cost of phenotypic evaluation for meat quality. Therefore, genomic selection may be the best strategy to improve meat quality traits. This study was performed to compare the accuracies of different Bayesian regression models in predicting molecular breeding values for meat tenderness in Polled Nellore cattle. The data set was composed of Warner-Bratzler shear force (WBSF) of longissimus muscle from 205, 141, and 81 animals slaughtered in 2005, 2010, and 2012, respectively, which were selected and mated so as to create extreme segregation for WBSF. The animals were genotyped with either the Illumina BovineHD (HD; 777,000 from 90 samples) chip or the GeneSeek Genomic Profiler (GGP Indicus HD; 77,000 from 337 samples). The quality controls of SNP were Hard-Weinberg Proportion -value ≥ 0.1%, minor allele frequency > 1%, and call rate > 90%. The FImpute program was used for imputation from the GGP Indicus HD chip to the HD chip. The effect of each SNP was estimated using ridge regression, least absolute shrinkage and selection operator (LASSO), Bayes A, Bayes B, and Bayes Cπ methods. Different numbers of SNP were used, with 1, 2, 3, 4, 5, 7, 10, 20, 40, 60, 80, or 100% of the markers preselected based on their significance test (-value from genomewide association studies [GWAS]) or randomly sampled. The prediction accuracy was assessed by the correlation between genomic breeding value and the observed WBSF phenotype, using a leave-one-out cross-validation methodology. The prediction accuracies using all markers were all very similar for all models, ranging from 0.22 (Bayes Cπ) to 0.25 (Bayes B). When preselecting SNP based on GWAS results, the highest correlation (0.27) between WBSF and the genomic breeding value was achieved using the Bayesian LASSO model with 15,030 (3%) markers. Although this study used relatively few animals, the design of the segregating population ensured wide genetic variability for meat tenderness, which was important to achieve acceptable accuracy of genomic prediction. Although all models showed similar levels of prediction accuracy, some small advantages were observed with the Bayes B approach when higher numbers of markers were preselected based on their -values resulting from a GWAS analysis.

Implementing meta-analysis from genome-wide association studies for pork quality traits

Pork quality plays an important role in the meat processing industry. Thus, different methodologies have been implemented to elucidate the genetic architecture of traits affecting meat quality. One of the most common and widely used approaches is to perform genome-wide association (GWA) studies. However, a limitation of many GWA in animal breeding is the limited power due to small sample sizes in animal populations. One alternative is to implement a meta-analysis of GWA (MA-GWA) combining results from independent association studies. The objective of this study was to identify significant genomic regions associated with meat quality traits by performing MA-GWA for 8 different traits in 3 independent pig populations. Results from MA-GWA were used to search for genes possibly associated with the set of evaluated traits. Data from 3 pig data sets (U.S. Meat Animal Research Center, commercial, and Michigan State University Pig Resource Population) were used. A MA was implemented by combining -scores derived for each SNP in every population and then weighting them using the inverse of estimated variance of SNP effects. A search for annotated genes retrieved genes previously reported as candidates for shear force (calpain-1 catalytic subunit [] and calpastatin []), as well as for ultimate pH, purge loss, and cook loss (protein kinase, AMP-activated, γ 3 noncatalytic subunit []). In addition, novel candidate genes were identified for intramuscular fat and cook loss (acyl-CoA synthetase family member 3 mitochondrial []) and for the objective measure of muscle redness, CIE a* (glycogen synthase 1, muscle [] and ferritin, light polypeptide []). Thus, implementation of MA-GWA allowed integration of results for economically relevant traits and identified novel genes to be tested as candidates for meat quality traits in pig populations.

Relationships among and variation within rare breeds of swine

Extinction of rare breeds of livestock threatens to reduce the total genetic variation available for selection in the face of the changing environment and new diseases. Swine breeds facing extinction typically share characteristics such as small size, slow growth rate, and high fat percentage, which limit them from contributing to commercial production. Compounding the risk of loss of variation is the lack of pedigree information for many rare breeds due to inadequate herd books, which increases the chance that producers are breeding closely related individuals. By making genetic data available, producers can make more educated breeding decisions to preserve genetic diversity in future generations, and conservation organizations can prioritize investments in breed preservation. The objective of this study was to characterize genetic variation within and among breeds of swine and prioritize heritage breeds for preservation. Genotypes from the Illumina PorcineSNP60 BeadChip (GeneSeek, Lincoln, NE) were obtained for Guinea, Ossabaw Island, Red Wattle, American Saddleback, Mulefoot, British Saddleback, Duroc, Landrace, Large White, Pietrain, and Tamworth pigs. A whole-genome analysis toolset was used to construct a genomic relationship matrix and to calculate inbreeding coefficients for the animals within each breed. Relatedness and average inbreeding coefficient differed among breeds, and pigs from rare breeds were generally more closely related and more inbred ( < 0.05). A multidimensional scaling diagram was constructed based on the SNP genotypes. Animals within breeds clustered tightly together except for 2 Guinea pigs. Tamworth, Duroc, and Mulefoot tended to not cluster with the other 7 breeds.

Genome-wide association study identifies loci and candidate genes for meat quality traits in Simmental beef cattle

Improving meat quality is the best way to enhance profitability and strengthen competitiveness in beef industry. Identification of genetic variants that control beef quality traits can help breeders design optimal breeding programs to achieve this goal. We carried out a genome-wide association study for meat quality traits in 1141 Simmental cattle using the Illumina Bovine HD 770K SNP array to identify the candidate genes and genomic regions associated with meat quality traits for beef cattle, including fat color, meat color, marbling score, longissimus muscle area, and shear force. In our study, we identified twenty significant single-nucleotide polymorphisms (SNPs) (p < 1.47 × 10(-6)) associated with these five meat quality traits. Notably, we observed several SNPs were in or near eleven genes which have been reported previously, including TMEM236, SORL1, TRDN, S100A10, AP2S1, KCTD16, LOC506594, DHX15, LAMA4, PREX1, and BRINP3. We identified a haplotype block on BTA13 containing five significant SNPs associated with fat color trait. We also found one of 19 SNPs was associated with multiple traits (shear force and longissimus muscle area) on BTA7. Our results offer valuable insights to further explore the potential mechanism of meat quality traits in Simmental beef cattle.

Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds

Background

Studies to identify markers associated with beef tenderness have focused on Warner–Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d’Aquitaine beef cattle breeds.

Results

Genome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle.

Conclusions

Our results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.

Electronic supplementary material

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Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure

Background

Saturated fatty acids can be detrimental to human health and have received considerable attention in recent years. Several studies using taurine breeds showed the existence of genetic variability and thus the possibility of genetic improvement of the fatty acid profile in beef. This study identified the regions of the genome associated with saturated, mono- and polyunsaturated fatty acids, and n-6 to n-3 ratios in the Longissimus thoracis of Nellore finished in feedlot, using the single-step method.

Results

The results showed that 115 windows explain more than 1 % of the additive genetic variance for the 22 studied fatty acids. Thirty-one genomic regions that explain more than 1 % of the additive genetic variance were observed for total saturated fatty acids, C12:0, C14:0, C16:0 and C18:0. Nineteen genomic regions, distributed in sixteen different chromosomes accounted for more than 1 % of the additive genetic variance for the monounsaturated fatty acids, such as the sum of monounsaturated fatty acids, C14:1 cis-9, C18:1 trans-11, C18:1 cis-9, and C18:1 trans-9. Forty genomic regions explained more than 1 % of the additive variance for the polyunsaturated fatty acids group, which are related to the total polyunsaturated fatty acids, C20:4 n-6, C18:2 cis-9 cis12 n-6, C18:3 n-3, C18:3 n-6, C22:6 n-3 and C20:3 n-6 cis-8 cis-11 cis-14. Twenty-one genomic regions accounted for more than 1 % of the genetic variance for the group of omega-3, omega-6 and the n-6:n-3 ratio.

Conclusions

The identification of such regions and the respective candidate genes, such as ELOVL5, ESSRG, PCYT1A and genes of the ABC group (ABC5, ABC6 and ABC10), should contribute to form a genetic basis of the fatty acid profile of Nellore (Bos indicus) beef, contributing to better selection of the traits associated with improving human health.

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Genome Wide Association Studies (GWAS) Identify QTL on SSC2 and SSC17 Affecting Loin Peak Shear Force in Crossbred Commercial Pigs

Of all the meat quality traits, tenderness is considered the most important with regard to eating quality and market value. In this study we have utilised genome wide association studies (GWAS) for peak shear force (PSF) of loin muscle as a measure of tenderness for 1,976 crossbred commercial pigs, genotyped for 42,721 informative SNPs using the Illumina PorcineSNP60 Beadchip. Four 1 Mb genomic regions, three on SSC2 (at 4 Mb, 5 Mb and 109 Mb) and one on SSC17 (at 20 Mb), were detected which collectively explained about 15.30% and 3.07% of the total genetic and phenotypic variance for PSF respectively. Markers ASGA0008566, ASGA0008695, DRGA0003285 and ASGA0075615 in the four regions were strongly associated with the effects. Analysis of the reference genome sequence in the region with the most important SNPs for SSC2_5 identified FRMD8, SLC25A45 and LTBP3 as potential candidate genes for meat tenderness on the basis of functional annotation of these genes. The region SSC2_109 was close to a previously reported candidate gene CAST; however, the very weak LD between DRGA0003285 (the best marker representing region SSC2_109) and CAST indicated the potential for additional genes which are distinct from, or interact with, CAST to affect meat tenderness. Limited information of known genes in regions SSC2_109 and SSC17_20 restricts further analysis. Re-sequencing of these regions for informative animals may help to resolve the molecular architecture and identify new candidate genes and causative mutations affecting this trait. These findings contribute significantly to our knowledge of the genomic regions affecting pork shear force and will potentially lead to new insights into the molecular mechanisms regulating meat tenderness.

Detection of selection signatures in Piemontese and Marchigiana cattle, two breeds with similar production aptitudes but different selection histories

BACKGROUND

Domestication and selection are processes that alter the pattern of within- and between-population genetic variability. They can be investigated at the genomic level by tracing the so-called selection signatures. Recently, sequence polymorphisms at the genome-wide level have been investigated in a wide range of animals. A common approach to detect selection signatures is to compare breeds that have been selected for different breeding goals (i.e. dairy and beef cattle). However, genetic variations in different breeds with similar production aptitudes and similar phenotypes can be related to differences in their selection history.

METHODS

In this study, we investigated selection signatures between two Italian beef cattle breeds, Piemontese and Marchigiana, using genotyping data that was obtained with the Illumina BovineSNP50 BeadChip. The comparison was based on the fixation index (Fst), combined with a locally weighted scatterplot smoothing (LOWESS) regression and a control chart approach. In addition, analyses of Fst were carried out to confirm candidate genes. In particular, data were processed using the varLD method, which compares the regional variation of linkage disequilibrium between populations.

RESULTS

Genome scans confirmed the presence of selective sweeps in the genomic regions that harbour candidate genes that are known to affect productive traits in cattle such as DGAT1, ABCG2, CAPN3, MSTN and FTO. In addition, several new putative candidate genes (for example ALAS1, ABCB8, ACADS and SOD1) were detected.

CONCLUSIONS

This study provided evidence on the different selection histories of two cattle breeds and the usefulness of genomic scans to detect selective sweeps even in cattle breeds that are bred for similar production aptitudes.

A genomewide association mapping study using ultrasound-scanned information identifies potential genomic regions and candidate genes affecting carcass traits in Nellore cattle

The aim of this study was to identify candidate genes and genomic regions associated with ultrasound-derived measurements of the rib-eye area (REA), backfat thickness (BFT) and rumpfat thickness (RFT) in Nellore cattle. Data from 640 Nellore steers and young bulls with genotypes for 290 863 single nucleotide polymorphisms (SNPs) were used for genomewide association mapping. Significant SNP associations were explored to find possible candidate genes related to physiological processes. Several of the significant markers detected were mapped onto functional candidate genes including ARFGAP3, CLSTN2 and DPYD for REA; OSBPL3 and SUDS3 for BFT; and RARRES1 and VEPH1 for RFT. The physiological pathway related to lipid metabolism (CLSTN2, OSBPL3, RARRES1 and VEPH1) was identified. The significant markers within previously reported QTLs reinforce the importance of the genomic regions, and the other loci offer candidate genes that have not been related to carcass traits in previous investigations.

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle

Background

While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry.

Results

Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci.

Conclusions

The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.

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The online version of this article (doi:10.1186/s12711-015-0106-8) contains supplementary material, which is available to authorized users.

Polymorphisms in epigenetic and meat quality related genes in fourteen cattle breeds and association with beef quality and carcass traits

Improvement for carcass traits related to beef quality is the key concern in beef production. Recent reports found that epigenetics mediates the interaction of individuals with environment and nutrition. The present study was designed to analyze the genetic effect of single nucleotide polymorphisms (SNPs) in seven epigenetic-related genes (DNMT1, DNMT3a, DNMT3b, DNMT3L, Ago1, Ago2, and HDAC5) and two meat quality candidate genes (CAPN1 and PRKAG3) on fourteen carcass traits related to beef quality in a Snow Dragon beef population, and also to identify SNPs in a total of fourteen cattle populations. Sixteen SNPs were identified and genotyped in 383 individuals sampled from the 14 cattle breeds, which included 147 samples from the Snow Dragon beef population. Data analysis showed significant association of 8 SNPs within 4 genes related to carcass and/or meat quality traits in the beef populations. SNP1 (13154420A>G) in exon 17 of DNMT1 was significantly associated with rib-eye width and lean meat color score (p<0.05). A novel SNP (SNP4, 76198537A>G) of DNMT3a was significantly associated with six beef quality traits. Those individuals with the wild-type genotype AA of DNMT3a showed an increase in carcass weight, chilled carcass weight, flank thicknesses, chuck short rib thickness, chuck short rib score and in chuck flap weight in contrast to the GG genotype. Five out of six SNPs in DNMT3b gene were significantly associated with three beef quality traits. SNP15 (45219258C>T) in CAPN1 was significantly associated with chuck short rib thickness and lean meat color score (p<0.05). The significant effect of SNP15 on lean meat color score individually and in combination with each of other 14 SNPs qualify this SNP to be used as potential marker for improving the trait. In addition, the frequencies of most wild-type alleles were higher than those of the mutant alleles in the native and foreign cattle breeds. Seven SNPs were identified in the epigenetic-related genes. The SNP15 in CAPN1 could be used as a powerful genetic marker in selection programs for beef quality improvement in the Snow Dragon Beef population.

Susceptibility loci revealed for bovine respiratory disease complex in pre-weaned holstein calves

BACKGROUND

Bovine respiratory disease complex (BRDC) is an infectious disease of cattle that is caused by a combination of viral and/or bacterial pathogens. Selection for cattle with reduced susceptibility to respiratory disease would provide a permanent tool for reducing the prevalence of BRDC. The objective of this study was to identify BRDC susceptibility loci in pre-weaned Holstein calves as a prerequisite to using genetic improvement as a tool for decreasing the prevalence of BRDC. High density SNP genotyping with the Illumina BovineHD BeadChip was conducted on 1257 male and 757 female Holstein calves from California (CA), and 767 calves identified as female from New Mexico (NM). Of these, 1382 were classified as BRDC cases, and 1396 were classified as controls, with all phenotypes assigned using the McGuirk health scoring system. During the acquisition of blood for DNA isolation, two deep pharyngeal and one mid-nasal diagnostic swab were obtained from each calf for the identification of bacterial and viral pathogens. Genome-wide association analyses were conducted using four analytical approaches (EIGENSTRAT, EMMAX-GRM, GBLUP and FvR). The most strongly associated SNPs from each individual analysis were ranked and evaluated for concordance. The heritability of susceptibility to BRDC in pre-weaned Holstein calves was estimated.

RESULTS

The four statistical approaches produced highly concordant results for 373 top ranked SNPs that defined 126 chromosomal regions for the CA population. Similarly, in NM, 370 SNPs defined 138 genomic regions that were identified by all four approaches. When the two populations were combined (i.e., CA + NM) and analyzed, 324 SNPs defined 116 genomic regions that were associated with BRDC across all analytical methods. Heritability estimates for BRDC were 21% for both CA and NM as individual populations, but declined to 13% when the populations were combined.

CONCLUSIONS

Four analytical approaches utilizing both single and multi-marker association methods revealed common genomic regions associated with BRDC susceptibility that can be further characterized and used for genomic selection. Moderate heritability estimates were observed for BRDC susceptibility in pre-weaned Holstein calves, thereby supporting the application of genomic selection to reduce the prevalence of BRDC in U.S. Holsteins.

Rapid screening for phenotype-genotype associations by linear transformations of genomic evaluations

Background

Currently, association studies are analysed using statistical mixed models, with marker effects estimated by a linear transformation of genomic breeding values. The variances of marker effects are needed when performing the tests of association. However, approaches used to estimate the parameters rely on a prior variance or on a constant estimate of the additive variance. Alternatively, we propose a standardized test of association using the variance of each marker effect, which generally differ among each other. Random breeding values from a mixed model including fixed effects and a genomic covariance matrix are linearly transformed to estimate the marker effects.

Results

The standardized test was neither conservative nor liberal with respect to type I error rate (false-positives), compared to a similar test using Predictor Error Variance, a method that was too conservative. Furthermore, genomic predictions are solved efficiently by the procedure, and the p-values are virtually identical to those calculated from tests for one marker effect at a time. Moreover, the standardized test reduces computing time and memory requirements.

The following steps are used to locate genome segments displaying strong association. The marker with the highest − log(p-value) in each chromosome is selected, and the segment is expanded one Mb upstream and one Mb downstream of the marker. A genomic matrix is calculated using the information from those markers only, which is used as the variance-covariance of the segment effects in a model that also includes fixed effects and random genomic breeding values. The likelihood ratio is then calculated to test for the effect in every chromosome against a reduced model with fixed effects and genomic breeding values. In a case study with pigs, a significant segment from chromosome 6 explained 11% of total genetic variance.

Conclusions

The standardized test of marker effects using their own variance helps in detecting specific genomic regions involved in the additive variance, and in reducing false positives. Moreover, genome scanning of candidate segments can be used in meta-analyses of genome-wide association studies, as it enables the detection of specific genome regions that affect an economically relevant trait when using multiple populations.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-246) contains supplementary material, which is available to authorized users.

Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens

The purpose of this study was to compare results obtained from various methodologies for genome-wide association studies, when applied to real data, in terms of number and commonality of regions identified and their genetic variance explained, computational speed, and possible pitfalls in interpretations of results. Methodologies include: two iteratively reweighted single-step genomic BLUP procedures (ssGWAS1 and ssGWAS2), a single-marker model (CGWAS), and BayesB. The ssGWAS methods utilize genomic breeding values (GEBVs) based on combined pedigree, genomic and phenotypic information, while CGWAS and BayesB only utilize phenotypes from genotyped animals or pseudo-phenotypes. In this study, ssGWAS was performed by converting GEBVs to SNP marker effects. Unequal variances for markers were incorporated for calculating weights into a new genomic relationship matrix. SNP weights were refined iteratively. The data was body weight at 6 weeks on 274,776 broiler chickens, of which 4553 were genotyped using a 60 k SNP chip. Comparison of genomic regions was based on genetic variances explained by local SNP regions (20 SNPs). After 3 iterations, the noise was greatly reduced for ssGWAS1 and results are similar to that of CGWAS, with 4 out of the top 10 regions in common. In contrast, for BayesB, the plot was dominated by a single region explaining 23.1% of the genetic variance. This same region was found by ssGWAS1 with the same rank, but the amount of genetic variation attributed to the region was only 3%. These findings emphasize the need for caution when comparing and interpreting results from various methods, and highlight that detected associations, and strength of association, strongly depends on methodologies and details of implementations. BayesB appears to overly shrink regions to zero, while overestimating the amount of genetic variation attributed to the remaining SNP effects. The real world is most likely a compromise between methods and remains to be determined.

Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle

BACKGROUND

Genome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers.

RESULTS

By using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions.

CONCLUSION

Where QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle.

Genome scan for meat quality traits in Nelore beef cattle

Meat quality traits are economically important because they affect consumers' acceptance, which, in turn, influences the demand for beef. However, selection to improve meat quality is limited by the small numbers of animals on which meat tenderness can be evaluated due to the cost of performing shear force analysis and the resultant damage to the carcass. Genome wide-association studies for Warner-Bratzler shear force measured at different times of meat aging, backfat thickness, ribeye muscle area, scanning parameters [lightness, redness (a*), and yellowness] to ascertain color characteristics of meat and fat, water-holding capacity, cooking loss (CL), and muscle pH were conducted using genotype data from the Illumina BovineHD BeadChip array to identify quantitative trait loci (QTL) in all phenotyped Nelore cattle. Phenotype count for these animals ranged from 430 to 536 across traits. Meat quality traits in Nelore are controlled by numerous QTL of small effect, except for a small number of large-effect QTL identified for a*fat, CL, and pH. Genomic regions harboring these QTL and the pathways in which the genes from these regions act appear to differ from those identified in taurine cattle for meat quality traits. These results will guide future QTL mapping studies and the development of models for the prediction of genetic merit to implement genomic selection for meat quality in Nelore cattle.