Genome-wide association study reveals five nucleotide sequence variants for carcass traits in beef cattle

Genome-wide runs of homozygosity signatures in diverse Indian goat breeds

The present study analyzed ROH and consensus ROH regions in 102 animals of eleven diverse Indian goat (Capra hircus) breeds using whole genome sequencing. A total of 51,705 ROH and 21,271 consensus regions were identified. The mean number of ROH per animal was highest in the meat breed, Jharkhand Black (2693) and lowest in the pashmina breed, Changthangi (60). The average length of ROH (ALROH) was maximum in Kanniadu (974.11 Kb) and minimum in Tellicherry (146.98 Kb). Long ROH is typically associated with more recent inbreeding, whereas short ROH is connected to more ancient inbreeding. The overall ROH-based genomic inbreeding (FROH) was highest for Jharkhand Black (0.602) followed by Kanniadu (0.120) and Sangamneri (0.108) among all breeds. FROH of Jharkhand Black was higher than Kanniadu  up to 5 Mb ROH length category. However, in > 20 Mb ROH length category, Kanniadu (0.98)  exhibited significantly higher FROH than Jharkhand Black (0.46). This  implies that Kanniadu had higher levels of recent inbreeding than Jharkhand Black. Despite this, due to the presence of both recent and ancient inbreeding, Jharkhand Black  demonstrated higher overall FROH compared to Kanniadu. ROH patterns revealed dual purpose (meat and dairy) and pashmina breeds as less consanguineous while recent inbreeding was apparent in meat breeds. Analysis of ROH consensus regions identified selection sweeps in key genes governing intramuscular fat deposition, meat tenderisation, lean meat production and carcass weight (CDK4, ALOX15, CASP9, PRDM16, DVL1) in meat breeds; milk fat percentage and mammary gland development (POLD1, NOTCH2, ARHGAP35) in dual purpose (meat and dairy) breeds; while cold adaptation and hair follicle development (APOBEC1, DNAJC3, F2RL1, FGF9) in pashmina breed. MAPK, RAS, BMP and Wnt signaling pathways associated with hair follicle morphogenesis in Changthangi were also identified. PCA analysis based on ROH consensus regions revealed that meat breeds are more diverse than other goat breeds/populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03921-y.

Genomic heritability and correlation between carcass traits in Japanese Black cattle evaluated under different ceilings of relatedness among individuals

The investigation of carcass traits to produce meat with high efficiency has been in focus on Japanese Black cattle since 1972. To implement a successful breeding program in carcass production, a comprehensive understanding of genetic characteristics and relationships between the traits is of paramount importance. In this study, genomic heritability and genomic correlation between carcass traits, including carcass weight (CW), rib eye area (REA), rib thickness (RT), subcutaneous fat thickness (SFT), yield rate (YI), and beef marbling score (BMS) were estimated using the genomic data of 9,850 Japanese Black cattle (4,142 heifers and 5,708 steers). In addition, we investigated the effect of genetic relatedness degree on the estimation of genetic parameters of carcass traits in sub-populations created based on different GRM-cutoff values. Genome-based restricted maximum likelihood (GREML) analysis was applied to estimate genetic parameters. Using all animal data, the heritability values for carcass traits were estimated as moderate to relatively high magnitude, ranging from 0.338 to 0.509 with standard errors, ranging from 0.014 to 0.015. The genetic correlations were obtained low and negative between SFT and REA [-0.198 (0.034)] and between SFT and BMS [-0.096 (0.033)] traits, and high and negative between SFT and YI [-0.634 (0.022)]. REA trait was genetically highly correlated with YI and BMS [0.811 (0.012) and 0.625 (0.022), respectively]. In sub-populations created based on the genetic-relatedness ceiling, the heritability estimates ranged from 0.212 (0.131) to 0.647 (0.066). At the genetic-relatedness ceiling of 0.15, the correlation values between most traits with low genomic correlation were overestimated while the correlations between the traits with relatively moderate to high correlations, ranging from 0.380 to 0.811, were underestimated. The values were steady at the ceilings of 0.30-0.95 (sample size of 5,443-9,850) for most of the highly correlated traits. The results demonstrated that there is considerable genetic variation and also favorable genomic correlations between carcass traits. Therefore, the genetic improvement for the traits can be simultaneously attained through genomic selection. In addition, we observed that depending on the degree of relationship between individuals and sample size, the genomic heritability and correlation estimates for carcass traits may be different.

Estimation of direct and maternal genetic effects and annotation of potential candidate genes for weight and meat quality traits in a genotyped outdoor dual-purpose cattle breed

With regard to potential applications of genomic selection in small numbered breeds, we evaluated genomic models and focused on potential candidate gene annotations for weight and meat quality traits in the local Rotes Höhenvieh (RHV) breed. Traits included 6,003 birth weights (BWT), 5,719 200 d-weights (200dw), 4,594 365 d-weights (365dw), and 547 records for intramuscular fat content (IMF). A total of 581,304 SNP from 370 genotyped cattle with phenotypic records were included in genomic analyses. Model evaluations focused on single- and multiple-trait models with direct and with direct and maternal genetic effects. Genetic relationship matrices were based on pedigree (A-matrix), SNP markers (G-matrix), or both (H-matrix). Genome-wide association studies (GWASs) were carried out using linear mixed models to identify potential candidate genes for the traits of interest. De-regressed proofs (DRP) for direct and maternal genetic components were used as pseudo-phenotypes in the GWAS. Accuracies of direct breeding values were higher from models based on G or on H compared to A. Highest accuracies (> 0.89) were obtained for IMF with multiple-trait models using the G-matrix. Direct heritabilities with maternal genetic effects ranged from 0.62 to 0.66 for BWT, from 0.45 to 0.55 for 200dW, from 0.40 to 0.44 for 365dW, and from 0.48 to 0.75 for IMF. Maternal heritabilities for BWT, 200dW, and 365dW were in a narrow range from 0.21 to 0.24, 0.24 to 0.27, and 0.21 to 0.25, respectively, and from 0.25 to 0.65 for IMF. Direct genetic correlations among body weight traits were positive and favorable, and very similar from different models but showed a stronger variation with 0.31 (A), −0.13 (G), and 0.45 (H) between BWT and IMF. In gene annotations, we identified 6, 3, 1, and 6 potential candidate genes for direct genetic effect on BWT, 200dW, 365dW, and IMF traits, respectively. Regarding maternal genetic effects, four (SHROOM3, ZNF609, PECAM1, and TEX2) and two (TMEM182 and SEC11A) genes were detected as potential candidate genes for BWT and 365dW, respectively. Potential candidate genes for maternal effect on IMF were GRHL2, FGA, FGB, and CTNNA3. As the most important finding from a practical breeding perspective, a small number of genotyped RHV cattle enabled accurate breeding values for high heritability IMF.

Key Genes Regulating Skeletal Muscle Development and Growth in Farm Animals

Simple Summary

Skeletal muscle mass is an important economic trait, and muscle development and growth is a crucial factor to supply enough meat for human consumption. Thus, understanding (candidate) genes regulating skeletal muscle development is crucial for understanding molecular genetic regulation of muscle growth and can be benefit the meat industry toward the goal of increasing meat yields. During the past years, significant progress has been made for understanding these mechanisms, and thus, we decided to write a comprehensive review covering regulators and (candidate) genes crucial for muscle development and growth in farm animals. Detection of these genes and factors increases our understanding of muscle growth and development and is a great help for breeders to satisfy demands for meat production on a global scale.

Abstract

Farm-animal species play crucial roles in satisfying demands for meat on a global scale, and they are genetically being developed to enhance the efficiency of meat production. In particular, one of the important breeders’ aims is to increase skeletal muscle growth in farm animals. The enhancement of muscle development and growth is crucial to meet consumers’ demands regarding meat quality. Fetal skeletal muscle development involves myogenesis (with myoblast proliferation, differentiation, and fusion), fibrogenesis, and adipogenesis. Typically, myogenesis is regulated by a convoluted network of intrinsic and extrinsic factors monitored by myogenic regulatory factor genes in two or three phases, as well as genes that code for kinases. Marker-assisted selection relies on candidate genes related positively or negatively to muscle development and can be a strong supplement to classical selection strategies in farm animals. This comprehensive review covers important (candidate) genes that regulate muscle development and growth in farm animals (cattle, sheep, chicken, and pig). The identification of these genes is an important step toward the goal of increasing meat yields and improves meat quality.

Genomic sequencing analysis reveals copy number variations and their associations with economically important traits in beef cattle

Copy number variation (CNV) represents a major source of genetic variation, which may have potentially large effects, including alternating gene regulation and dosage, as well as contributing to gene expression and risk for normal phenotypic variability. We carried out a comprehensive analysis of CNV based on whole genome sequencing in Chinese Simmental beef cattle. Totally, we found 9313 deletion and 234 duplication events, covering 147.5 Mb autosomal regions. Within them, 257 deletion events of high frequency overlapped with 193 known RefGenes. Among these genes, we observed several genes were related to economically important traits, like residual feed intake, immune responding, pregnancy rate and muscle differentiation. Using a locus-based analysis, we identified 11 deletions and 1 duplication, which were significantly associated with three traits including carcass weight, tenderloin and longissimus muscle area. Our sequencing-based study provided important insights into investigating the association of CNVs with important traits in beef cattle.

Integrating Single-Step GWAS and Bipartite Networks Reconstruction Provides Novel Insights into Yearling Weight and Carcass Traits in Hanwoo Beef Cattle

Simple Summary

Hanwoo is an indigenous cattle breed in Korea and popular for meat production owing to its rapid growth and high-quality meat. Its yearling weight and carcass traits (backfat thickness, carcass weight, eye muscle area, and marbling score) are economically important for the selection of young and proven bulls. In recent decades, the advent of high throughput genotyping technologies has made it possible to perform genome-wide association studies (GWAS) for the detection of genomic regions associated with traits of economic interest in different species. In this study, we conducted a weighted single-step genome-wide association study which combines all genotypes, phenotypes and pedigree data in one step (ssGBLUP). It allows for the use of all SNPs simultaneously along with all phenotypes from genotyped and ungenotyped animals. Our results revealed 33 relevant genomic regions related to the traits of interest. Gene set enrichment analysis indicated that the identified candidate genes were related to biological processes and functional terms that were involved in growth and lipid metabolism. In conclusion, these results suggest that the incorporation of GWAS results and network analysis can help us to better understand the genetic bases underlying growth and carcass traits.

Abstract

In recent years, studies on the biological mechanisms underlying complex traits have been facilitated by innovations in high-throughput genotyping technology. We conducted a weighted single-step genome-wide association study (WssGWAS) to evaluate backfat thickness, carcass weight, eye muscle area, marbling score, and yearling weight in a cohort of 1540 Hanwoo beef cattle using BovineSNP50 BeadChip. The WssGWAS uncovered thirty-three genomic regions that explained more than 1% of the additive genetic variance, mostly located on chromosomes 6 and 14. Among the identified window regions, seven quantitative trait loci (QTL) had pleiotropic effects and twenty-six QTL were trait-specific. Significant pathways implicated in the measured traits through Gene Ontology (GO) term enrichment analysis included the following: lipid biosynthetic process, regulation of lipid metabolic process, transport or localization of lipid, regulation of growth, developmental growth, and multicellular organism growth. Integration of GWAS results of the studied traits with pathway and network analyses facilitated the exploration of the respective candidate genes involved in several biological functions, particularly lipid and growth metabolism. This study provides novel insight into the genetic bases underlying complex traits and could be useful in developing breeding schemes aimed at improving growth and carcass traits in Hanwoo beef cattle.

Use of gene expression and whole-genome sequence information to improve the accuracy of genomic prediction for carcass traits in Hanwoo cattle

Background

In this study, we assessed the accuracy of genomic prediction for carcass weight (CWT), marbling score (MS), eye muscle area (EMA) and back fat thickness (BFT) in Hanwoo cattle when using genomic best linear unbiased prediction (GBLUP), weighted GBLUP (wGBLUP), and a BayesR model. For these models, we investigated the potential gain from using pre-selected single nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on imputed sequence data and from gene expression information. We used data on 13,717 animals with carcass phenotypes and imputed sequence genotypes that were split in an independent GWAS discovery set of varying size and a remaining set for validation of prediction. Expression data were used from a Hanwoo gene expression experiment based on 45 animals.

Results

Using a larger number of animals in the reference set increased the accuracy of genomic prediction whereas a larger independent GWAS discovery dataset improved identification of predictive SNPs. Using pre-selected SNPs from GWAS in GBLUP improved accuracy of prediction by 0.02 for EMA and up to 0.05 for BFT, CWT, and MS, compared to a 50 k standard SNP array that gave accuracies of 0.50, 0.47, 0.58, and 0.47, respectively. Accuracy of prediction of BFT and CWT increased when BayesR was applied with the 50 k SNP array (0.02 and 0.03, respectively) and was further improved by combining the 50 k array with the top-SNPs (0.06 and 0.04, respectively). By contrast, using BayesR resulted in limited improvement for EMA and MS. wGBLUP did not improve accuracy but increased prediction bias. Based on the RNA-seq experiment, we identified informative expression quantitative trait loci, which, when used in GBLUP, improved the accuracy of prediction slightly, i.e. between 0.01 and 0.02. SNPs that were located in genes, the expression of which was associated with differences in trait phenotype, did not contribute to a higher prediction accuracy.

Conclusions

Our results show that, in Hanwoo beef cattle, when SNPs are pre-selected from GWAS on imputed sequence data, the accuracy of prediction improves only slightly whereas the contribution of SNPs that are selected based on gene expression is not significant. The benefit of statistical models to prioritize selected SNPs for estimating genomic breeding values is trait-specific and depends on the genetic architecture of each trait.

Identification of markers associated with estimated breeding value and horn colour in Hungarian Grey cattle

OBJECTIVE

This study was conducted to estimate effect of single nucleotide polymorphisms (SNP) on the estimated breeding value of Hungarian Grey (HG) bulls and to find markers associated with horn colour.

METHODS

Genotypes 136 HG animals were determined on Geneseek high-density Bovine SNP 150K BeadChip. A multi-locus mixed-model was applied for statistical analyses.

RESULTS

Six SNPs were identified to be associated (-log10P>10) with green and white horn. These loci are located on chromosome 1, 3, 9, 18, and 25. Seven loci (on chromosome 1, 3, 6, 9, 10, 28) showed considerable association (-log10P>10) with the estimated breeding value.

CONCLUSION

Analysis provides markers for further research of horn colour and supplies markers to achieve more effective selection work regarding estimated breeding value of HG.

Genome-Wide Association Study of Meat Quality Traits in Hanwoo Beef Cattle Using Imputed Whole-Genome Sequence Data

The discovery of single nucleotide polymorphisms (SNP) and the subsequent genotyping of large numbers of animals have enabled large-scale analyses to begin to understand the biological processes that underpin variation in animal populations. In beef cattle, genome-wide association studies using genotype arrays have revealed many quantitative trait loci (QTL) for various production traits such as growth, efficiency and meat quality. Most studies regarding meat quality have focused on marbling, which is a key trait associated with meat eating quality. However, other important traits like meat color, texture and fat color have not commonly been studied. Developments in genome sequencing technologies provide new opportunities to identify regions associated with these traits more precisely. The objective of this study was to estimate variance components and identify significant variants underpinning variation in meat quality traits using imputed whole genome sequence data. Phenotypic and genomic data from 2,110 Hanwoo cattle were used. The estimated heritabilities for the studied traits were 0.01, 0.16, 0.31, and 0.49 for fat color, meat color, meat texture and marbling score, respectively. Marbling score and meat texture were highly correlated. The genome-wide association study revealed 107 significant SNPs located on 14 selected chromosomes (one QTL region per selected chromosome). Four QTL regions were identified on BTA2, 12, 16, and 24 for marbling score and two QTL regions were found for meat texture trait on BTA12 and 29. Similarly, three QTL regions were identified for meat color on BTA2, 14 and 24 and five QTL regions for fat color on BTA7, 10, 12, 16, and 21. Candidate genes were identified for all traits, and their potential influence on the given trait was discussed. The significant SNP will be an important inclusion into commercial genotyping arrays to select new breeding animals more accurately.

Genome-wide association study identifies the PLAG1-OXR1 region on BTA14 for carcass meat yield in cattle

Carcass meat yield is an important carcass trait that contributes to the production efficiency and economic benefits in beef cattle. It is therefore critical to identify quantitative trait loci associated with carcass traits to enable selection. Our previous studies have identified several causal variants within the pleomorphic adenoma gene 1 ( PLAG1) and coiled-coil-helix-coiled-coil-helix domain-containing 7 ( CHCHD7) genes on BTA14 for carcass traits in Chinese Simmental. In the current study, we carried out a genome-wide association study for carcass meat yield in 472 Wagyu cattle with Bovine HD SNP array. Our results showed that 27 single nucleotide polymorphisms (SNPs) were identified for tenderloin weight (TDW), striploin weight (SPW), chuck roll weight (CRW), bicep weight (BPW), knuckle weight (KCW), and flank steak weight (FSW) in Wagyu cattle. Of these SNPs, 10 distinct SNPs were detected within the oxidation resistance 1 ( OXR1), fatty acid binding protein 5 ( FABP5), TNF receptor superfamily member 11b ( TNFRSF11B), and zinc finger CCCH-type containing 3 ( ZC3H3) genes on BTA14. Notably, three significant SNPs, BovineHD1400016738, BovineHD1400016743, and BovineHD1400016665 within OXR1, were shown strong linkage disequilibrium (r2 > 0.8) and significantly associated with CRW ( P = 1.37 × 10−8 ~ 1.94 × 10−8). Moreover, Ingenuity Pathway Analysis showed that OXR1, FABP5, and CAP1A genes were involved in a single network and FABP5 may regulate the expression of OXR1 gene via node gene, peroxisome proliferator-activated receptor gamma ( PPARG). Overall, this study suggests that OXR1 and FABP5 are candidate genes affecting carcass traits in Wagyu and the PLAG1-OXR1 region on BTA14 as a putative susceptibility locus for carcass meat yield for both Chinese Simmental and Wagyu.

Genome-wide association analysis to identify QTL for carcass traits in Hanwoo (Korean native cattle)

A genome-wide association study (GWAS) was performed to investigate the genetic markers associated with carcass traits of Hanwoo (Bos taurus coreanae) steer in the Gangwon region of Korea. Hanwoo steer (139) from the Gangwon region were genotyped with Bovine SNP50K BeadChip, and 35,769 SNPs were analyzed for five specific carcass traits after applying several filters. A total of seven quantitative trait loci were detected, of which four, one, and 2 SNPs were detected on various B. taurus autosomal chromosomes (BTA) by the respective model. The four significant SNPs associated with backfat thickness were ARS-BFGL-NGS–41475 on BTA 5, ARS-BFGLNGS- 36359 on BTA 19, ARS-BFGL-NGS-56813 on BTA 22, and Hapmap25048-BTA-138242 on BTA 25. Among the detected SNPs, one and two SNPs were associated with marbling score (ARS-BFGL-NGS-110066 on BTA 23) and meat colour (BTB-01920239 on BTA 15 and ARS-BFGL-NGS-24934 on BTA 18). In this GWAS, we identified three positional candidate genes for carcass traits, backfat thickness (Fibulin-2, FBLN2; Sorting nexin 29, SNX29) and meat colour (WW domain containing oxidoreductase, WWOX). Our results suggest that the candidate SNP markers do affect the genomic selection of associated carcass traits for Hanwoo in the Gangwon region.

Genome-wide association study of carcass weight in commercial Hanwoo cattle

Objective

The objective of the present study was to validate genes and genomic regions associated with carcass weight using a low-density single nucleotide polymorphism (SNP) Chip in Hanwoo cattle breed.

Methods

Commercial Hanwoo steers (n = 220) were genotyped with 20K GeneSeek genomic profiler BeadChip. After applying the quality control of criteria of a call rate ≥90% and minor allele frequency (MAF) ≥0.01, a total of 15,235 autosomal SNPs were left for genome-wide association (GWA) analysis. The GWA tests were performed using single-locus mixed linear model. Age at slaughter was fitted as fixed effect and sire included as a covariate. The level of genome-wide significance was set at 3.28×10⁻⁶ (0.05/15,235), corresponding to Bonferroni correction for 15,235 multiple independent tests.

Results

By employing EMMAX approach which is based on a mixed linear model and accounts for population stratification and relatedness, we identified 17 and 16 loci significantly (p<0.001) associated with carcass weight for the additive and dominant models, respectively. The second most significant (p = 0.000049) SNP (ARS-BFGL-NGS-28234) on bovine chromosome 4 (BTA4) at 21 Mb had an allele substitution effect of 43.45 kg. Some of the identified regions on BTA2, 6, 14, 22, and 24 were previously reported to be associated with quantitative trait loci for carcass weight in several beef cattle breeds.

Conclusion

This is the first genome-wide association study using SNP chips on commercial Hanwoo steers, and some of the loci newly identified in this study may help to better DNA markers that determine increased beef production in commercial Hanwoo cattle. Further studies using a larger sample size will allow confirmation of the candidates identified in this study.

Genome-Wide Association Study Reveals the PLAG1 Gene for Knuckle, Biceps and Shank Weight in Simmental Beef Cattle

Carcass traits of beef cattle have been genetically improved to increase yield of high quality meat. Genome-wide association study (GWAS) is a powerful method to identify genetic variants associated with carcass traits. For the 770K genotyped SNPs from 1141 Chinese Simmental cattle, we used the compressed mixed linear model (CMLM) to perform a genome-wide association study for knuckle, biceps and shank of beef carcass traits. Seventeen significantly associated SNPs were found, which are located on BTA6, BTA14 and BTA15. Interestingly, one pleiotropic quantitative trait nucleotide (QTN), named BovineHD1400007259 (p < 10⁻⁸) within the well-known gene region PLAG1-CHCHD7 on BTA14, was found to govern variation of the knuckle, biceps and shank traits. The QTN accounted for 8.6% of phenotypic variance for biceps. In addition, 16 more SNPs distributed on BTA14 were detected as being associated with the carcass traits.

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.

Genome-wide association study for carcass traits, fatty acid composition, chemical composition, sugar, and the effects of related candidate genes in Japanese Black cattle

We performed a genome-wide association study (GWAS) and candidate gene analysis to: (i) evaluate the effectiveness of the GWAS in our small population by performing GWAS for carcass weight (CW) and fatty acid composition; (ii) detect novel candidate regions affecting non-CW carcass traits, chemical composition and sugar; and (iii) evaluate the association of the candidate genes previously detected in CW and fatty acid composition with other economically important traits. A total of 574 Japanese Black cattle and 40 657 Single nucleotide polymorphisms were used. In addition, candidate gene analyses were performed to evaluate the association of three CW-related genes and two fatty acid-related genes with carcass traits, fatty acid composition, chemical composition and sugar. The significant regions with the candidate genes were detected for CW and fatty acid composition, and these results showed that a significant region would be detectable despite the small sample size. The novel candidate regions were detected on BTA23 for crude protein and on BTA19 for fructose. CW-related genes associated with the rib-eye area and fatty acid composition were identified, and fatty acid-related genes had no relationship with other traits. Moreover, the favorable allele of CW-related genes had an unfavorable effect on fatty acid composition.

Genomic structure and marker-derived gene networks for growth and meat quality traits of Brazilian Nelore beef cattle

BACKGROUND

Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample.

RESULTS

Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches.

CONCLUSIONS

The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.

Pathway-Based Genome-Wide Association Studies for Two Meat Production Traits in Simmental Cattle

Most single nucleotide polymorphisms (SNPs) detected by genome-wide association studies (GWAS), explain only a small fraction of phenotypic variation. Pathway-based GWAS were proposed to improve the proportion of genes for some human complex traits that could be explained by enriching a mass of SNPs within genetic groups. However, few attempts have been made to describe the quantitative traits in domestic animals. In this study, we used a dataset with approximately 7,700,000 SNPs from 807 Simmental cattle and analyzed live weight and longissimus muscle area using a modified pathway-based GWAS method to orthogonalise the highly linked SNPs within each gene using principal component analysis (PCA). As a result, of the 262 biological pathways of cattle collected from the KEGG database, the gamma aminobutyric acid (GABA)ergic synapse pathway and the non-alcoholic fatty liver disease (NAFLD) pathway were significantly associated with the two traits analyzed. The GABAergic synapse pathway was biologically applicable to the traits analyzed because of its roles in feed intake and weight gain. The proposed method had high statistical power and a low false discovery rate, compared to those of the smallest P-value and SNP set enrichment analysis methods.

Genetic association of marbling score with intragenic nucleotide variants at selection signals of the bovine genome

Selection signals of Korean cattle might be attributed largely to artificial selection for meat quality. Rapidly increased intragenic markers of newly annotated genes in the bovine genome would help overcome limited findings of genetic markers associated with meat quality at the selection signals in a previous study. The present study examined genetic associations of marbling score (MS) with intragenic nucleotide variants at selection signals of Korean cattle. A total of 39 092 nucleotide variants of 407 Korean cattle were utilized in the association analysis. A total of 129 variants were selected within newly annotated genes in the bovine genome. Their genetic associations were analyzed using the mixed model with random polygenic effects based on identical-by-state genetic relationships among animals in order to control for spurious associations produced by population structure. Genetic associations of MS were found (P<3.88×10-4) with six intragenic nucleotide variants on bovine autosomes 3 (cache domain containing 1, CACHD1), 5 (like-glycosyltransferase, LARGE), 16 (cell division cycle 42 binding protein kinase alpha, CDC42BPA) and 21 (snurportin 1, SNUPN; protein tyrosine phosphatase, non-receptor type 9, PTPN9; chondroitin sulfate proteoglycan 4, CSPG4). In particular, the genetic associations with CDC42BPA and LARGE were confirmed using an independent data set of Korean cattle. The results implied that allele frequencies of functional variants and their proximity variants have been augmented by directional selection for greater MS and remain selection signals in the bovine genome. Further studies of fine mapping would be useful to incorporate favorable alleles in marker-assisted selection for MS of Korean cattle.

Population structure and history of the Welsh sheep breeds determined by whole genome genotyping

Background

One of the most economically important areas within the Welsh agricultural sector is sheep farming, contributing around £230 million to the UK economy annually. Phenotypic selection over several centuries has generated a number of native sheep breeds, which are presumably adapted to the diverse and challenging landscape of Wales. Little is known about the history, genetic diversity and relationships of these breeds with other European breeds. We genotyped 353 individuals from 18 native Welsh sheep breeds using the Illumina OvineSNP50 array and characterised the genetic structure of these breeds. Our genotyping data were then combined with, and compared to, those from a set of 74 worldwide breeds, previously collected during the International Sheep Genome Consortium HapMap project.

Results

Model based clustering of the Welsh and European breeds indicated shared ancestry. This finding was supported by multidimensional scaling analysis (MDS), which revealed separation of the European, African and Asian breeds. As expected, the commercial Texel and Merino breeds appeared to have extensive co-ancestry with most European breeds. Consistently high levels of haplotype sharing were observed between native Welsh and other European breeds. The Welsh breeds did not, however, form a genetically homogeneous group, with pairwise F_ST between breeds averaging 0.107 and ranging between 0.020 and 0.201. Four subpopulations were identified within the 18 native breeds, with high homogeneity observed amongst the majority of mountain breeds. Recent effective population sizes estimated from linkage disequilibrium ranged from 88 to 825.

Conclusions

Welsh breeds are highly diverse with low to moderate effective population sizes and form at least four distinct genetic groups. Our data suggest common ancestry between the native Welsh and European breeds. These findings provide the basis for future genome-wide association studies and a first step towards developing genomics assisted breeding strategies in the UK.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-015-0216-x) contains supplementary material, which is available to authorized users.

Forward LASSO analysis for high-order interactions in genome-wide association study

Previous genome-wide association study (GWAS) focused on low-order interactions between pairwise single-nucleotide polymorphisms (SNPs) with significant main effects. Little is known how high-order interactions effect, especially one among the SNPs without main effects regulates quantitative traits. Within the frameworks of linear model and generalized linear model, the LASSO with coordinate descent step can be used to simultaneously analyze thousands and thousands of SNPs for normal and discrete traits. With consideration of high-order interactions among SNPs, a huge number of genetic effects make the LASSO failing to work under the presented condition of computation. Forward LASSO analysis is, therefore, proposed to shrink most of genetic effects to be zeros stage by stage. Simulation demonstrates that our proposed method could be used instead of the LASSO method for full model in mapping high-order interactions. Application of forward LASSO method is provided to GWAS for carcass traits and meat quality traits in beef cattle.

Genomic heritability of bovine growth using a mixed model

This study investigated heritability for bovine growth estimated with genomewide single nucleotide polymorphism (SNP) information obtained from a DNA microarray chip. Three hundred sixty seven Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,112 SNPs of 364 animals filtered by quality assurance were analyzed to estimate heritability of body weights at 6, 9, 12, 15, 18, 21, and 24 months of age. Restricted maximum likelihood estimate of heritability was obtained using covariance structure of genomic relationships among animals in a mixed model framework. Heritability estimates ranged from 0.58 to 0.76 for body weights at different ages. The heritability estimates using genomic information in this study were larger than those which had been estimated previously using pedigree information. The results revealed a trend that the heritability for body weight increased at a younger age (6 months). This suggests an early genetic evaluation for bovine growth using genomic information to increase genetic merits of animals.

Genome-wide association studies using haplotypes and individual SNPs in Simmental cattle

Recent advances in high-throughput genotyping technologies have provided the opportunity to map genes using associations between complex traits and markers. Genome-wide association studies (GWAS) based on either a single marker or haplotype have identified genetic variants and underlying genetic mechanisms of quantitative traits. Prompted by the achievements of studies examining economic traits in cattle and to verify the consistency of these two methods using real data, the current study was conducted to construct the haplotype structure in the bovine genome and to detect relevant genes genuinely affecting a carcass trait and a meat quality trait. Using the Illumina BovineHD BeadChip, 942 young bulls with genotyping data were introduced as a reference population to identify the genes in the beef cattle genome significantly associated with foreshank weight and triglyceride levels. In total, 92,553 haplotype blocks were detected in the genome. The regions of high linkage disequilibrium extended up to approximately 200 kb, and the size of haplotype blocks ranged from 22 bp to 199,266 bp. Additionally, the individual SNP analysis and the haplotype-based analysis detected similar regions and common SNPs for these two representative traits. A total of 12 and 7 SNPs in the bovine genome were significantly associated with foreshank weight and triglyceride levels, respectively. By comparison, 4 and 5 haplotype blocks containing the majority of significant SNPs were strongly associated with foreshank weight and triglyceride levels, respectively. In addition, 36 SNPs with high linkage disequilibrium were detected in the GNAQ gene, a potential hotspot that may play a crucial role for regulating carcass trait components.

A whole genome association study on meat palatability in hanwoo

A whole genome association (WGA) study was carried out to find quantitative trait loci (QTL) for sensory evaluation traits in Hanwoo. Carcass samples of 250 Hanwoo steers were collected from National Agricultural Cooperative Livestock Research Institute, Ansung, Gyeonggi province, Korea, between 2011 and 2012 and genotyped with the Affymetrix Bovine Axiom Array 640K single nucleotide polymorphism (SNP) chip. Among the SNPs in the chip, a total of 322,160 SNPs were chosen after quality control tests. After adjusting for the effects of age, slaughter-year-season, and polygenic effects using genome relationship matrix, the corrected phenotypes for the sensory evaluation measurements were regressed on each SNP using a simple linear regression additive based model. A total of 1,631 SNPs were detected for color, aroma, tenderness, juiciness and palatability at 0.1% comparison-wise level. Among the significant SNPs, the best set of 52 SNP markers were chosen using a forward regression procedure at 0.05 level, among which the sets of 8, 14, 11, 10, and 9 SNPs were determined for the respectively sensory evaluation traits. The sets of significant SNPs explained 18% to 31% of phenotypic variance. Three SNPs were pleiotropic, i.e. AX-26703353 and AX-26742891 that were located at 101 and 110 Mb of BTA6, respectively, influencing tenderness, juiciness and palatability, while AX-18624743 at 3 Mb of BTA10 affected tenderness and palatability. Our results suggest that some QTL for sensory measures are segregating in a Hanwoo steer population. Additional WGA studies on fatty acid and nutritional components as well as the sensory panels are in process to characterize genetic architecture of meat quality and palatability in Hanwoo.

Multiple-trait genome-wide association study based on principal component analysis for residual covariance matrix

Given the drawbacks of implementing multivariate analysis for mapping multiple traits in genome-wide association study (GWAS), principal component analysis (PCA) has been widely used to generate independent 'super traits' from the original multivariate phenotypic traits for the univariate analysis. However, parameter estimates in this framework may not be the same as those from the joint analysis of all traits, leading to spurious linkage results. In this paper, we propose to perform the PCA for residual covariance matrix instead of the phenotypical covariance matrix, based on which multiple traits are transformed to a group of pseudo principal components. The PCA for residual covariance matrix allows analyzing each pseudo principal component separately. In addition, all parameter estimates are equivalent to those obtained from the joint multivariate analysis under a linear transformation. However, a fast least absolute shrinkage and selection operator (LASSO) for estimating the sparse oversaturated genetic model greatly reduces the computational costs of this procedure. Extensive simulations show statistical and computational efficiencies of the proposed method. We illustrate this method in a GWAS for 20 slaughtering traits and meat quality traits in beef cattle.

Genome-wide association study for backfat thickness in Canchim beef cattle using Random Forest approach

Background

Meat quality involves many traits, such as marbling, tenderness, juiciness, and backfat thickness, all of which require attention from livestock producers. Backfat thickness improvement by means of traditional selection techniques in Canchim beef cattle has been challenging due to its low heritability, and it is measured late in an animal’s life. Therefore, the implementation of new methodologies for identification of single nucleotide polymorphisms (SNPs) linked to backfat thickness are an important strategy for genetic improvement of carcass and meat quality.

Results

The set of SNPs identified by the random forest approach explained as much as 50% of the deregressed estimated breeding value (dEBV) variance associated with backfat thickness, and a small set of 5 SNPs were able to explain 34% of the dEBV for backfat thickness. Several quantitative trait loci (QTL) for fat-related traits were found in the surrounding areas of the SNPs, as well as many genes with roles in lipid metabolism.

Conclusions

These results provided a better understanding of the backfat deposition and regulation pathways, and can be considered a starting point for future implementation of a genomic selection program for backfat thickness in Canchim beef cattle.

Genome-wide association analysis identifies loci for left-sided displacement of the abomasum in German Holstein cattle

Left-sided displacement of the abomasum (LDA) is one of the most common disorders of the digestive system in many dairy breeds and particularly in Holstein dairy cows. We performed a genome-wide association study for 854 German Holstein cows, including 225 cases and 629 controls. All cows were genotyped using the Illumina Bovine SNP50 BeadChip (Illumina Inc., San Diego, CA). After quality control of genotypes, a total of 36,226 informative single nucleotide polymorphisms (SNP) were left for analysis. We used a mixed linear model approach for a genome-wide association study of LDA. In total, 36 SNP located on 17 bovine (Bos taurus) chromosomes (BTA) showed associations with LDA at nominal -log10P-values >3.0. Two of these SNP, located on BTA11 at 46.70 Mb and BTA20 at 16.67 Mb, showed genome-wide significant associations with LDA at -log10P-values >4.6. Pathway analyses indicated genes involved in calcium metabolism and insulin-dependent diabetes mellitus to be factors in the pathogenesis of LDA in German Holstein cows.

Practical capability and cost effectiveness of a DNA pool-based genome-wide association study using BovineSNP50 array in a cattle population

Genome-wide association mapping for complex traits in cattle populations is a powerful, but expensive, selection tool. The DNA pooling technique can potentially reduce the cost of genome-wide association studies. However, in DNA pooling design, the additional variance generated by pooling-specific errors must be taken into account. Therefore, this study aimed to investigate factors such as: (i) the accuracy of allele frequency estimation; (ii) the magnitude of errors in pooling construction and in the array; and (iii) the effect of the number of replicate arrays on P-values estimated by a genome-wide association study. Results showed that the Illumina correction method is the most effective method to correct the allele frequency estimation; pooling errors, especially array variance, should be taken into account in DNA pooling design; and the risk of a type I error can be reduced by using at least two replicate arrays. These results indicate the practical capability and cost-effectiveness of pool-based genome-wide association studies using the BovineSNP50 array in a cattle population.

Meat Science and Muscle Biology Symposium: stem cell niche and postnatal muscle growth

Stem cell niche plays a critical role in regulating the behavior and function of adult stem cells that underlie tissue growth, maintenance, and regeneration. In the skeletal muscle, stem cells, called satellite cells, contribute to postnatal muscle growth and hypertrophy, and thus, meat production in agricultural animals. Satellite cells are located adjacent to mature muscle fibers underneath a sheath of basal lamina. Microenvironmental signals from extracellular matrix mediated by the basal lamina and from the host myofiber both impinge on satellite cells to regulate their activity. Furthermore, several types of muscle interstitial cells, including intramuscular preadipocytes and connective tissue fibroblasts, have recently been shown to interact with satellite cells and actively regulate the growth and regeneration of postnatal skeletal muscles. From this regard, interstitial adipogenic cells are not only important for marbling and meat quality, but also represent an additional cellular component of the satellite cell niche. At the molecular level, these interstitial cells may interact with satellite cells through cell surface ligands, such as delta-like 1 homolog (Dlk1) protein whose overexpression is thought to be responsible for muscle hypertrophy in callipyge sheep. In fact, extracellular Dlk1 protein has been shown to promote the myogenic differentiation of satellite cells. Understanding the cellular and molecular mechanisms within the stem cell niche that regulate satellite cell differentiation and maintain muscle homeostasis may lead to promising approaches to optimizing muscle growth and composition, thus improving meat production and quality.