Reaffirmation of known major genes and the identification of novel candidate genes associated with carcass-related metrics based on whole genome sequence within a large multi-breed cattle population

Genome-wide selection reveals candidate genes associated with multiple teats in Hu sheep

Increasing the number of teats in sheep helps to improve the survival rate of sheep lambs after birth. In order to analyze the candidate genes related to the formation of multiple teats in Hu sheep, the present study was conducted to investigate the genetic pattern of multiple teats in Hu sheep. In this study, based on genome-wide data from 157 Hu sheep, Fst, xp-EHH, Pi and iHS signaling were performed, and the top 5% signal regions of each analyzed result were annotated based on the Oar_v4.0 for sheep. The results show that a total of 142 SNP loci were selected. We found that PTPRG, TMEM117 and LRP1B genes were closely associated with polypodium formation in Hu sheep, in addition, among the candidate genes related to polypodium we found genes such as TMEM117, SLC25A21 and NCKAP5 related to milk traits. The present study screened out candidate genes for the formation of multiple teats at the genomic level in Hu sheep.

A Pilot Detection and Associate Study of Gene Presence-Absence Variation in Holstein Cattle

Presence-absence variations (PAVs) are important structural variations, wherein a genomic segment containing one or more genes is present in some individuals but absent in others. While PAVs have been extensively studied in plants, research in cattle remains limited. This study identified PAVs in 173 Holstein bulls using whole-genome sequencing data and assessed their associations with 46 economically important traits. Out of 28,772 cattle genes (from the longest transcripts), a total of 26,979 (93.77%) core genes were identified (present in all individuals), while variable genes included 928 softcore (present in 95-99% of individuals), 494 shell (present in 5-94%), and 371 cloud genes (present in <5%). Cloud genes were enriched in functions associated with hormonal and antimicrobial activities, while shell genes were enriched in immune functions. PAV-based genome-wide association studies identified associations between gene PAVs and 16 traits including milk, fat, and protein yields, as well as traits related to health and reproduction. Associations were found on multiple chromosomes, illustrating important associations on cattle chromosomes 7 and 15, involving olfactory receptor and immune-related genes, respectively. By examining the PAVs at the population level, the results of this research provided crucial insights into the genetic structures underlying the complex traits of Holstein cattle.

Transcriptional response to an alternative diet on liver, muscle, and rumen of beef cattle

Feed cost represents a major economic determinant within cattle production, amounting to an estimated 75% of the total variable costs. Consequently, comprehensive approaches such as optimizing feed utilization through alternative feed sources, alongside the selection of feed-efficient animals, are of great significance. Here, we investigate the effect of two diets, traditional corn-grain fed and alternative by-product based, on 14 phenotypes related to feed, methane emission and production efficiency and on multi-tissue transcriptomics data from liver, muscle, and rumen wall, derived from 52 Nellore bulls, 26 on each diet. To this end, diets were contrasted at the level of phenotype, gene expression, and gene-phenotype network connectivity. As regards the phenotypic level, at a P value < 0.05, significant differences were found in favour of the alternative diet for average daily weight gain at finishing, dry matter intake at finishing, methane emission, carcass yield and subcutaneous fat thickness at the rib-eye muscle area. In terms of the transcriptional level of the 14,776 genes expressed across the examined tissues, we found 487, 484, and 499 genes differentially expressed due to diet in liver, muscle, and rumen, respectively (P value < 0.01). To explore differentially connected phenotypes across both diet-based networks, we focused on the phenotypes with the largest change in average number of connections within diets and tissues, namely methane emission and carcass yield, highlighting, in particular, gene expression changes involving SREBF2, and revealing the largest differential connectivity in rumen and muscle, respectively. Similarly, from examination of differentially connected genes across diets, the top-ranked most differentially connected regulators within each tissue were MEOX1, PTTG1, and BASP1 in liver, muscle, and rumen, respectively. Changes in gene co-expression patterns suggest activation or suppression of specific biological processes and pathways in response to dietary interventions, consequently impacting the phenotype. The identification of genes that respond differently to diets and their associated phenotypic effects serves as a crucial stepping stone for further investigations, aiming to build upon our discoveries. Ultimately, such advancements hold the promise of improving animal welfare, productivity, and sustainability in livestock farming.

Defining a Haplotype Encompassing the LCORL-NCAPG Locus Associated with Increased Lean Growth in Beef Cattle

Numerous studies have shown genetic variation at the LCORL-NCAPG locus is strongly associated with growth traits in beef cattle. However, a causative molecular variant has yet to be identified. To define all possible candidate variants, 34 Charolais-sired calves were whole-genome sequenced, including 17 homozygous for a long-range haplotype associated with increased growth (QQ) and 17 homozygous for potential ancestral haplotypes for this region (qq). The Q haplotype was refined to an 814 kb region between chr6:37,199,897-38,014,080 and contained 218 variants not found in qq individuals. These variants include an insertion in an intron of NCAPG, a previously documented mutation in NCAPG (rs109570900), two coding sequence mutations in LCORL (rs109696064 and rs384548488), and 15 variants located within ATAC peaks that were predicted to affect transcription factor binding. Notably, rs384548488 is a frameshift variant likely resulting in loss of function for long isoforms of LCORL. To test the association of the coding sequence variants of LCORL with phenotype, 405 cattle from five populations were genotyped. The two variants were in complete linkage disequilibrium. Statistical analysis of the three populations that contained QQ animals revealed significant (p < 0.05) associations with genotype and birth weight, live weight, carcass weight, hip height, and average daily gain. These findings affirm the link between this locus and growth in beef cattle and describe DNA variants that define the haplotype. However, further studies will be required to define the true causative mutation.

Population structure and identification of genomic regions associated with productive traits in five Italian beef cattle breeds

Italy has a long history in beef production, with local breeds such as Marchigiana, Chianina, Romagnola, Maremmana, and Podolica which produce high-quality meat. Selection has improved meat production, precocity, growth ability and muscle development, but the genetic determinism of such traits is mostly unknown. Using 33K SNPs-data from young bulls (N = 4064) belonging to these five Italian breeds, we demonstrated that the Maremmana and Podolica rustic breeds are closely related, while the specialised Marchigiana, Chianina, and Romagnola breeds are more differentiated. A genome-wide association study for growth and muscle development traits (average daily gain during the performance test, weight at 1 year old, muscularity) was conducted in the five Italian breeds. Results indicated a region on chromosome 2, containing the myostatin gene (MSTN), which displayed significant genome-wide associations with muscularity in Marchigiana cattle, a breed in which the muscle hypertrophy phenotype is segregating. Moreover, a significant SNP on chromosome 14 was associated, in the Chianina breed, to muscularity. The identification of diverse genomic regions associated with conformation traits might increase our knowledge about the genomic basis of such traits in Italian beef cattle and, eventually, such information could be used to implement marker-assisted selection of young bulls tested in the performance test.

Genome-wide association study for primal cut lean traits in Canadian beef cattle

This study identified genomic variants and underlying candidate genes related to the whole carcass and individual primal cut lean content in Canadian commercial crossbred beef cattle. Genotyping information of 1035 crossbred beef cattle were available alongside estimated and actual carcass lean meat yield and individual primal cut lean content in all carcasses. Significant fixed effects and covariates were identified and included in the animal model. Genome-wide association analysis were implemented using the weighted single-step genomic best linear unbiased prediction (WssGBLUP). A number of candidate genes identified linked to lean tissue production were unrelated to estimated lean meat yield and were specific to the actual lean traits. Among these, 41 genes were common for actual lean traits, on specific regions of BTA4, BTA13 and BTA25 indicating potential involvement in lean mass synthesis. Therefore, the results suggested the inclusion of primal cut lean traits as a selection objective in breeding programs with consideration of further functional studies of the identified genes could help in optimizing lean yield for maximal carcass value.

Genome-Wide Association Study to Identify QTL for Carcass Traits in Korean Hanwoo Cattle

This study aimed to identify genetic associations with carcass traits in Hanwoo cattle using a genome-wide association study. A total of 9302 phenotypes were analyzed, and all animals were genotyped using the Illumina Bovine 50K v.3 SNP chip. Heritabilities for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) were estimated as 0.42, 0.36, 0.36, and 0.47, respectively, using the GBLUP model, and 0.47, 0.37, 0.36, and 0.42, respectively, using the Bayes B model. We identified 129 common SNPs using DGEBV and 118 common SNPs using GEBV on BTA6, BTA13, and BTA14, suggesting their potential association with the traits of interest. No common SNPs were found between the GBLUP and Bayes B methods when using residuals as a response variable in GWAS. The most promising candidate genes for CWT included SLIT2, PACRGL, KCNIP4, RP1, XKR4, LYN, RPS20, MOS, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, TOX, CA8, LAP3, FAM184B, and NCAPG. For EMA, the genes IBSP, LAP3, FAM184B, LCORL, NCAPG, SLC30A9, and BEND4 demonstrated significance. Similarly, CYP7B1, ARMC1, PDE7A, and CRH were associated with BF, while CTSZ, GNAS, VAPB, and RAB22A were associated with MS. This finding offers valuable insights into genomic regions and molecular mechanisms influencing Hanwoo carcass traits, aiding efficient breeding strategies.

Understanding the underlying genetic mechanisms for age at first calving, inter-calving period and scrotal circumference in Bonsmara cattle

BACKGROUND

Reproduction is a key feature of the sustainability of a species and thus represents an important component in livestock genetic improvement programs. Most reproductive traits are lowly heritable. In order to gain a better understanding of the underlying genetic basis of these traits, a genome-wide association was conducted for age at first calving (AFC), first inter-calving period (ICP) and scrotal circumference (SC) within the South African Bonsmara breed. Phenotypes and genotypes (120,692 single nucleotide polymorphisms (SNPs) post editing) were available on 7,128 South African Bonsmara cattle; the association analyses were undertaken using linear mixed models.

RESULTS

Genomic restricted maximum likelihood analysis of the 7,128 SA Bonsmara cattle yielded genomic heritability's of 0.183 (SE = 0.021) for AFC, 0.207 (SE = 0.022) for ICP and 0.209 (SE = 0.019) for SC. A total of 16, 23 and 51 suggestive (P ≤ 4 × 10-6) SNPs were associated with AFC, ICP and SC, while 11, 11 and 44 significant (P ≤ 4 × 10-7) SNPs were associated with AFC, ICP and SC respectively. A total of 11 quantitative trait loci (QTL) and 11 candidate genes were co-located with these associated SNPs for AFC, with 10 QTL harbouring 11 candidate genes for ICP and 41 QTL containing 40 candidate genes for SC. The QTL identified were close to genes previously associated with carcass, fertility, growth and milk-related traits. The biological pathways influenced by these genes include carbohydrate catabolic processes, cellular development, iron homeostasis, lipid metabolism and storage, immune response, ovarian follicle development and the regulation of DNA transcription and RNA translation.

CONCLUSIONS

This was the first attempt to study the underlying polymorphisms associated with reproduction in South African beef cattle. Genes previously reported in cattle breeds for numerous traits bar AFC, ICP or SC were detected in this study. Over 20 different genes have not been previously reported in beef cattle populations and may have been associated due to the unique genetic composite background of the SA Bonsmara breed.

Advanced Skeletal Ossification Is Associated with Genetic Variants in Chronologically Young Beef Heifers

Osteogenesis is a developmental process critical for structural support and the establishment of a dynamic reservoir for calcium and phosphorus. Changes in livestock breeding over the past 100 years have resulted in earlier bone development and increased physical size of cattle. Advanced skeletal maturity is now commonly observed at harvest, with heifers displaying more mature bone than is expected at 30 months of age (MOA). We surmise that selection for growth traits and earlier reproductive maturity resulted in co-selection for accelerated skeletal ossification. This study examines the relationship of single nucleotide polymorphisms (SNPs) in 793 beef heifers under 30 MOA with USDA-graded skeletal maturity phenotypes (A-, B-, C- skeletal maturity). Further, the estrogen content of FDA-approved hormonal implants provided to heifers prior to harvest was evaluated in association with the identified SNPs and maturities. Association tests were performed, and the impact of the implants were evaluated as covariates against genotypes using a logistic regression model. SNPs from the ESR1, ALPL, PPARGC1B, SORCS1 genes, and SNPs near KLF14, ANKRD61, USP42, H1C1, OVCA2, microRNA mir-29a were determined to be associated with the advanced skeletal ossification phenotype in heifers. Higher dosage estrogen implants increased skeletal maturity in heifers with certain SNP genotypes.

Relationship between Some Myostatin Variants and Meat Production Related Calving, Weaning and Muscularity Traits in Charolais Cattle

The slaughter value of live cattle can be assessed during visual conformation scoring, as well as by examining different molecular genetic information, e.g., the myostatin gene, which can be responsible for muscle development. In this study, the F94L, Q204X, nt267, nt324 and nt414 alleles of the myostatin gene (MSTN) were examined in relation to birth weight (BIW), calving ease (CAE), 205-day weaning weight (CWW), muscle score of shoulder (MSS), muscle score of back (MSB), muscle score of thigh (MST), roundness score of thigh (RST), loin thickness score (LTS), and overall muscle development percentage (OMP) of Charolais weaned calves in Hungary. Multi-trait analysis of variance (GLM) and weighted linear regression analysis were used to process the data. Calves carrying the Q204X allele in the heterozygous form achieved approximately 0.14 points higher MSB, MST and LTS, and 1.2% higher OMP, and gained 8.56 kg more CWW than their counterparts not carrying the allele (p < 0.05). As for the F94L allele, there was a difference of 4.08 kg in CWW of the heterozygous animals, but this difference could not be proved statistically. The other alleles had no significant effect on the evaluated traits.

Polymorphism of Genes and Their Impact on Beef Quality

The single-nucleotide polymorphism (SNP) form of genes is a valuable source of information regarding their suitability for use as specific markers of desirable traits in beef cattle breeding. For several decades, breeding work focused on improving production efficiency through optimizing the feed conversion ratio and improving daily gains and meat quality. Many research teams previously undertook research work on single-nucleotide polymorphism in myostatin (MSTN), thyroglobulin (TG), calpain (CAPN), and calpastatin (CAST) proteins. The literature review focuses on the most frequently addressed issues concerning these genes in beef cattle production and points to a number of relevant studies on the genes' polymorphic forms. The four genes presented are worth considering during breeding work as a set of genes that can positively influence productivity and production quality.

A new machine learning based computational framework identifies therapeutic targets and unveils influential genes in pancreatic islet cells

Pancreatic islets comprise a group of cells that produce hormones regulating blood glucose levels. Particularly, the alpha and beta islet cells produce glucagon and insulin to stabilize blood glucose. When beta islet cells are dysfunctional, insulin is not secreted, inducing a glucose metabolic disorder. Identifying effective therapeutic targets against the disease is a complicated task and is not yet conclusive. To close the wide gap between understanding the molecular mechanism of pancreatic islet cells and providing effective therapeutic targets, we present a computational framework to identify potential therapeutic targets against pancreatic disorders. First, we downloaded three transcriptome expression profiling datasets pertaining to pancreatic islet cells (GSE87375, GSE79457, GSE110154) from the Gene Expression Omnibus database. For each dataset, we extracted expression profiles for two cell types. We then provided these expression profiles along with the cell types to our proposed constrained optimization problem of a support vector machine and to other existing methods, selecting important genes from the expression profiles. Finally, we performed (1) an evaluation from a classification perspective which showed the superiority of our methods against the baseline; and (2) an enrichment analysis which indicated that our methods achieved better outcomes. Results for the three datasets included 44 unique genes and 10 unique transcription factors (SP1, HDAC1, EGR1, E2F1, AR, STAT6, RELA, SP3, NFKB1, and ESR1) which are reportedly related to pancreatic islet functions, diseases, and therapeutic targets.

A Novel A > G Polymorphism in the Intron 1 of LCORL Gene Is Significantly Associated with Hide Weight and Body Size in Dezhou Donkey

Several studies have shown the association between the ligand-dependent nuclear receptor compression-like protein (LCORL) gene and body size in horses, pigs and donkeys. Based on previous studies, the LCORL gene was hypothesized to be associated with growth traits and hide weight in Dezhou donkeys. In this study, we aimed to reveal the variation of the LCORL gene in the Dezhou donkey and explore whether the gene is associated with hide weight and body size. In this study, genetic polymorphisms in the LCORL gene of the Dezhou donkey were studied using targeted sequencing technology, and single nucleotide polymorphisms (SNPs) of the LCORL gene were analyzed for association with hide weight and body size in Dezhou donkeys. The results showed that there was an SNP locus situated in intron 1 of the LCORL gene. Association analysis revealed that individuals with the GG genotype had significantly higher body height, body length, chest circumference and hide weight than those with the AA genotype (p < 0.05). Therefore, the g.112558859 A > G locus can be used as a potential candidate marker affecting body size and hide weight. This study provides the foundation for breeding high-quality donkeys with high hide yield.

Genome-Wide Associative Study of Phenotypic Parameters of the 3D Body Model of Aberdeen Angus Cattle with Multiple Depth Cameras

Simple Summary

This article aims to develop a new approach to the lifetime evaluation of cattle by 3-D visualization of economic-biological and genetic features. The following indicators were selected as phenotypic features: chest width and chest girth retrieved by 3-D model and meat output on the bones. Correlation analysis showed a reliable positive relationship between chest width and meat output on the bones, which can potentially be used for lifetime evaluation of meat productivity of animals. Genome-wide associations analysis revealed the following potential loci of quantitative traits on cattle chromosomes for chest width, chest girth, and meat output on bones.

Abstract

In beef cattle breeding, genome-wide association studies (GWAS) using single nucleotide polymorphisms (SNPs) arrays can reveal many loci of various production traits, such as growth, productivity, and meat quality. With the development of genome sequencing technologies, new opportunities are opening up for more accurate identification of areas associated with these traits. This article aims to develop a novel approach to the lifetime evaluation of cattle by 3-D visualization of economic-biological and genetic features. The purpose of this study was to identify significant variants underlying differences in the qualitative characteristics of meat, using imputed data on the sequence of the entire genome. Samples of biomaterial of young Aberdeen-Angus breed cattle (n = 96) were the material for carrying out genome-wide SNP genotyping. Genotyping was performed using a high-density DNA chip Bovine GPU HD BeadChip (Illumina Inc., San Diego, CA, USA), containing ~150 thousand SNPs. The following indicators were selected as phenotypic features: chest width and chest girth retrieved by 3-D model and meat output on the bones. Correlation analysis showed a reliable positive relationship between chest width and meat output on the bones, which can potentially be used for lifetime evaluation of meat productivity of animals.

Detection of Genomic Imprinting for Carcass Traits in Cattle Using Imputed High-Density Genotype Data

Genomic imprinting is an epigenetic phenomenon defined as the silencing of an allele, at least partially, at a given locus based on the sex of the transmitting parent. The objective of the present study was to detect the presence of SNP-phenotype imprinting associations for carcass weight (CW), carcass conformation (CC) and carcass fat (CF) in cattle. The data used comprised carcass data, along with imputed, high-density genotype data on 618,837 single nucleotide polymorphisms (SNPs) from 23,687 cattle; all animal genotypes were phased with respect to parent of origin. Based on the phased genotypes and a series of single-locus linear models, 24, 339, and 316 SNPs demonstrated imprinting associations with CW, CC, and CF, respectively. Regardless of the trait in question, no known imprinted gene was located within 0.5 Mb of the SNPs demonstrating imprinting associations in the present study. Since all imprinting associations detected herein were at novel loci, further investigation of these regions may be warranted. Nonetheless, knowledge of these associations might be useful for improving the accuracy of genomic evaluations for these traits, as well as mate allocations systems to exploit the effects of genomic imprinting.

The Association Between Genomic Heterozygosity and Carcass Merit in Cattle

The objective of the present study was to quantify the association between both pedigree and genome-based measures of global heterozygosity and carcass traits, and to identify single nucleotide polymorphisms (SNPs) exhibiting non-additive associations with these traits. The carcass traits of interest were carcass weight (CW), carcass conformation (CC) and carcass fat (CF). To define the genome-based measures of heterozygosity, and to quantify the non-additive associations between SNPs and the carcass traits, imputed, high-density genotype data, comprising of 619,158 SNPs, from 27,213 cattle were used. The correlations between the pedigree-based heterosis coefficient and the three defined genomic measures of heterozygosity ranged from 0.18 to 0.76. The associations between the different measures of heterozygosity and the carcass traits were biologically small, with positive associations for CW and CC, and negative associations for CF. Furthermore, even after accounting for the pedigree-based heterosis coefficient of an animal, part of the remaining variability in some of the carcass traits could be captured by a genomic heterozygosity measure. This signifies that the inclusion of both a heterosis coefficient based on pedigree information and a genome-based measure of heterozygosity could be beneficial to limiting bias in predicting additive genetic merit. Finally, one SNP located on Bos taurus (BTA) chromosome number 5 demonstrated a non-additive association with CW. Furthermore, 182 SNPs (180 SNPs on BTA 2 and two SNPs on BTA 21) demonstrated a non-additive association with CC, while 231 SNPs located on BTA 2, 5, 11, 13, 14, 18, 19 and 21 demonstrated a non-additive association with CF. Results demonstrate that heterozygosity both at a global level and at the level of individual loci contribute little to the variability in carcass merit.

Identify known and novel candidate genes associated with backfat thickness in Duroc pigs by large-scale genome-wide association analysis

Backfat thickness (BFT) is complex and economically important traits in the pig industry, since it reflects fat deposition and can be used to measure the carcass lean meat percentage in pigs. In this study, all 6,550 pigs were genotyped using the Geneseek Porcine 50K SNP Chip to identify SNPs related to BFT and to search for candidate genes through genome-wide association analysis in two Duroc populations. In total, 80 SNPs, including 39 significant and 41 suggestive SNPs, and 6 QTLs were identified significantly associated with the BFT. In addition, 9 candidate genes, including a proven major gene MC4R, 3 important candidate genes (RYR1, HMGA1, and NUDT3) which were previously described as related to BFT, and 5 novel candidate genes (SIRT2, NKAIN2, AMH, SORCS1, and SORCS3) were found based on their potential functional roles in BFT. The functions of candidate genes and gene set enrichment analysis indicate that most important pathways are related to energy homeostasis and adipogenesis. Finally, our data suggest that most of the candidate genes can be directly used for genetic improvement through molecular markers, except that the MC4R gene has an antagonistic effect on growth rate and carcass lean meat percentage in breeding. Our results will advance our understanding of the complex genetic architecture of BFT traits and laid the foundation for additional genetic studies to increase carcass lean meat percentage of pig through marker-assisted selection and/or genomic selection.

Identification of Candidate Variants Associated With Bone Weight Using Whole Genome Sequence in Beef Cattle

Bone weight is critical to affect body conformation and stature in cattle. In this study, we conducted a genome-wide association study for bone weight in Chinese Simmental beef cattle based on the imputed sequence variants. We identified 364 variants associated with bone weight, while 350 of them were not included in the Illumina BovineHD SNP array, and several candidate genes and GO terms were captured to be associated with bone weight. Remarkably, we identified four potential variants in a candidate region on BTA6 using Bayesian fine-mapping. Several important candidate genes were captured, including LAP3, MED28, NCAPG, LCORL, SLIT2, and IBSP, which have been previously reported to be associated with carcass traits, body measurements, and growth traits. Notably, we found that the transcription factors related to MED28 and LCORL showed high conservation across multiple species. Our findings provide some valuable information for understanding the genetic basis of body stature in beef cattle.

Genome-wide Association Study for Carcass Primal Cut Yields Using Single-step Bayesian Approach in Hanwoo Cattle

The importance of meat and carcass quality is growing in beef cattle production to meet both producer and consumer demands. Primal cut yields, which reflect the body compositions of carcass, could determine the carcass grade and, consequently, command premium prices. Despite its importance, there have been few genome-wide association studies on these traits. This study aimed to identify genomic regions and putative candidate genes related to 10 primal cut traits, including tenderloin, sirloin, striploin, chuck, brisket, top round, bottom round, shank, flank, and rib in Hanwoo cattle using a single-step Bayesian regression (ssBR) approach. After genomic data quality control, 43,987 SNPs from 3,745 genotyped animals were available, of which 3,467 had phenotypic records for the analyzed traits. A total of 16 significant genomic regions (1-Mb window) were identified, of which five large-effect quantitative trait loci (QTLs) located on chromosomes 6 at 38–39 Mb, 11 at 21–22 Mb, 14 at 6–7 Mb and 26–27 Mb, and 19 at 26–27 Mb were associated with more than one trait, while the remaining 11 QTLs were trait-specific. These significant regions were harbored by 154 genes, among which TOX, FAM184B, SPP1, IBSP, PKD2, SDCBP, PIGY, LCORL, NCAPG, and ABCG2 were noteworthy. Enrichment analysis revealed biological processes and functional terms involved in growth and lipid metabolism, such as growth (GO:0040007), muscle structure development (GO:0061061), skeletal system development (GO:0001501), animal organ development (GO:0048513), lipid metabolic process (GO:0006629), response to lipid (GO:0033993), metabolic pathways (bta01100), focal adhesion (bta04510), ECM–receptor interaction (bta04512), fat digestion and absorption (bta04975), and Rap1 signaling pathway (bta04015) being the most significant for the carcass primal cut traits. Thus, identification of quantitative trait loci regions and plausible candidate genes will aid in a better understanding of the genetic and biological mechanisms regulating carcass primal cut yields.

The Contribution of Copy Number Variants and Single Nucleotide Polymorphisms to the Additive Genetic Variance of Carcass Traits in Cattle

The relative contributions of both copy number variants (CNVs) and single nucleotide polymorphisms (SNPs) to the additive genetic variance of carcass traits in cattle is not well understood. A detailed understanding of the relative importance of CNVs in cattle may have implications for study design of both genomic predictions and genome-wide association studies. The first objective of the present study was to quantify the relative contributions of CNV data and SNP genotype data to the additive genetic variance of carcass weight, fat, and conformation for 945 Charolais, 923 Holstein-Friesian, and 974 Limousin sires. The second objective was to jointly consider SNP and CNV data in a least absolute selection and shrinkage operator (LASSO) regression model to identify genomic regions associated with carcass weight, fat, and conformation within each of the three breeds separately. A genomic relationship matrix (GRM) based on just CNV data did not capture any variance in the three carcass traits when jointly evaluated with a SNP-derived GRM. In the LASSO regression analysis, a total of 987 SNPs and 18 CNVs were associated with at least one of the three carcass traits in at least one of the three breeds. The quantitative trait loci (QTLs) corresponding to the associated SNPs and CNVs overlapped with several candidate genes including previously reported candidate genes such as MSTN and RSAD2, and several potential novel candidate genes such as ACTN2 and THOC1. The results of the LASSO regression analysis demonstrated that CNVs can be used to detect associations with carcass traits which were not detected using the set of SNPs available in the present study. Therefore, the CNVs and SNPs available in the present study were not redundant forms of genomic data.

Genome-wide association analyses of carcass traits using copy number variants and raw intensity values of single nucleotide polymorphisms in cattle

BACKGROUND

The carcass value of cattle is a function of carcass weight and quality. Given the economic importance of carcass merit to producers, it is routinely included in beef breeding objectives. A detailed understanding of the genetic variants that contribute to carcass merit is useful to maximize the efficiency of breeding for improved carcass merit. The objectives of the present study were two-fold: firstly, to perform genome-wide association analyses of carcass weight, carcass conformation, and carcass fat using copy number variant (CNV) data in a population of 923 Holstein-Friesian, 945 Charolais, and 974 Limousin bulls; and secondly to perform separate association analyses of carcass traits on the same population of cattle using the Log R ratio (LRR) values of 712,555 single nucleotide polymorphisms (SNPs). The LRR value of a SNP is a measure of the signal intensity of the SNP generated during the genotyping process.

RESULTS

A total of 13,969, 3,954, and 2,805 detected CNVs were tested for association with the three carcass traits for the Holstein-Friesian, Charolais, and Limousin, respectively. The copy number of 16 CNVs and the LRR of 34 SNPs were associated with at least one of the three carcass traits in at least one of the three cattle breeds. With the exception of three SNPs, none of the quantitative trait loci detected in the CNV association analyses or the SNP LRR association analyses were also detected using traditional association analyses based on SNP allele counts. Many of the CNVs and SNPs associated with the carcass traits were located near genes related to the structure and function of the spliceosome and the ribosome; in particular, U6 which encodes a spliceosomal subunit and 5S rRNA which encodes a ribosomal subunit.

CONCLUSIONS

The present study demonstrates that CNV data and SNP LRR data can be used to detect genomic regions associated with carcass traits in cattle providing information on quantitative trait loci over and above those detected using just SNP allele counts, as is the approach typically employed in genome-wide association analyses.

Integration of selection signatures and multi-trait GWAS reveals polygenic genetic architecture of carcass traits in beef cattle

Carcass merits are widely considered as economically important traits affecting beef production in the beef cattle industry. However, the genetic basis of carcass traits remains to be well understood. Here, we applied multiple methods, including the Composite of Likelihood Ratio (CLR) and Genome-wide Association Study (GWAS), to explore the selection signatures and candidate variants affecting carcass traits. We identified 11,600 selected regions overlapping with 2214 candidate genes, and most of those were enriched in binding and gene regulation. Notably, we identified 66 and 110 potential variants significantly associated with carcass traits using single-trait and multi-traits analyses, respectively. By integrating selection signatures with single and multi-traits associations, we identified 12 and 27 putative genes, respectively. Several highly conserved missense variants were identified in OR5M13D, NCAPG, and TEX2. Our study supported polygenic genetic architecture of carcass traits and provided novel insights into the genetic basis of complex traits in beef cattle.

Exploiting within-breed variability in the autochthonous Reggiana breed identified several candidate genes affecting pigmentation-related traits, stature and udder defects in cattle

Autochthonous cattle breeds constitute important reservoirs of genetic diversity. Reggiana is an Italian local cattle breed reared in the north of Italy for the production of a mono‐breed Parmigiano–Reggiano cheese. Reggiana cattle usually have a classical solid red coat colour and pale muzzle. As part of the strategies designed for the sustainable conservation of this genetic resource, we investigated at the genome‐wise level the within‐breed detected variability of three pigmentation‐related traits (intensity of red coat colour, based on three classes – light/diluted, normal and dark; spotted patterns/piebaldism that sometime emerge in the breed; muzzle colour – pink/pale, grey and black), stature, presence/absence and number of supernumerary teats and teat length. A total of 1776 Reggiana cattle (about two‐thirds of the extant breed population) were genotyped with the GeneSeek GGP Bovine 150k SNP array and single‐marker and haplotype‐based GWASs were carried out. The results indicated that two main groups of genetic factors affect the intensity of red coat colour: darkening genes (including EDN3 and a few other genes) and diluting genes (including PMEL and a few other genes). Muzzle colour was mainly determined by MC1R gene markers. Piebaldism was mainly associated with KIT gene markers. Stature was associated with BTA6 markers upstream of the NCAPG–LCORL genes. Teat defects were associated with TBX3/TBX5, MCC and LGR5 genes. Overall, the identified genomic regions not only can be directly used in selection plans in the Reggiana breed, but also contribute to clarifying the genetic mechanisms involved in determining exterior traits in cattle.

Detection of Genomic Regions with Pleiotropic Effects for Growth and Carcass Quality Traits in the Rubia Gallega Cattle Breed

Simple Summary

The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. We have developed a ssGWAS by backsolving the SNP effects after implementing a ssGBLUP. The results showed an apparent heterogeneity of the additive genetic variance across the genome. Some of the genomic regions explaining the most of this additive variance were shared across traits, indicating the presence of pleiotropic effects, which were reflected in their genetic correlations.

Abstract

The breeding scheme in the Rubia Gallega cattle population is based upon traits measured in farms and slaughterhouses. In recent years, genomic evaluation has been implemented by using a ssGBLUP (single-step Genomic Best Linear Unbiased Prediction). This procedure can reparameterized to perform ssGWAS (single-step Genome Wide Association Studies) by backsolving the SNP (single nucleotide polymorphisms) effects. Therefore, the objective of this study was to identify genomic regions associated with the genetic variability in growth and carcass quality traits. We implemented a ssGBLUP by using a database that included records for Birth Weight (BW-327,350 records-), Weaning Weight (WW-83,818-), Cold Carcass Weight (CCW-91,621-), Fatness (FAT-91,475-) and Conformation (CON-91,609-). The pedigree included 464,373 individuals, 2449 of which were genotyped. After a process of filtering, we ended up using 43,211 SNP markers. We used the GBLUP and SNPBLUP model equivalences to obtain the effects of the SNPs and then calculated the percentage of variance explained by the regions of the genome between 1 Mb. We identified 7 regions of the genome for CCW; 8 regions for BW, WW, FAT and 9 regions for CON, which explained the percentage of variance above 0.5%. Furthermore, a number of the genome regions had pleiotropic effects, located at: BTA1 (131–132 Mb), BTA2 (1–11 Mb), BTA3 (32–33 Mb), BTA6 (36–38 Mb), BTA16 (24–26 Mb), and BTA 21 (56–57 Mb). These regions contain, amongst others, the following candidate genes: NCK1, MSTN, KCNA3, LCORL, NCAPG, and RIN3.

Identification of genomic regions that exhibit sexual dimorphism for size and muscularity in cattle

Sexual dimorphism, the phenomenon whereby males and females of the same species are distinctive in some aspect of appearance or size, has previously been documented in cattle for traits such as growth rate and carcass merit using a quantitative genetics approach. No previous study in cattle has attempted to document sexual dimorphism at a genome level; therefore, the objective of the present study was to determine whether genomic regions associated with size and muscularity in cattle exhibited signs of sexual dimorphism. Analyses were undertaken on 10 linear-type traits that describe the muscular and skeletal characteristics of both males and females of five beef cattle breeds: 1,444 Angus (AA), 6,433 Charolais (CH), 1,129 Hereford, 8,745 Limousin (LM), and 1,698 Simmental. Genome-wide association analyses were undertaken using imputed whole-genome sequence data for each sex separately by breed. For each single-nucleotide polymorphism (SNP) that was segregating in both sexes, the difference between the allele substitution effect sizes for each sex, in each breed separately, was calculated. Suggestively (P ≤ 1 × 10-5) sexually dimorphic SNPs that were segregating in both males and females were detected for all traits in all breeds, although the location of these SNPs differed by both trait and breed. Significantly (P ≤ 1 × 10-8) dimorphic SNPs were detected in just three traits in the AA, seven traits in the CH, and three traits in the LM. The vast majority of all segregating autosomal SNPs (86% in AA to 94% in LM) had the same minor allele in both males and females. Differences (P ≤ 0.05) in allele frequencies between the sexes were observed for between 36% (LM) and 66% (AA) of the total autosomal SNPs that were segregating in both sexes. Dimorphic SNPs were located within a number of genes related to muscularity and/or size including the NAB1, COL5A2, and IWS1 genes on BTA2 that are located close to, and thought to be co-inherited with, the MSTN gene. Overall, sexual dimorphism exists in cattle at the genome level, but it is not consistent by either trait or breed.

Assessing the genetic background and genomic relatedness of red cattle populations originating from Northern Europe

Background

Local cattle breeds need special attention, as they are valuable reservoirs of genetic diversity. Appropriate breeding decisions and adequate genomic management of numerically smaller populations are required for their conservation. At this point, the analysis of dense genome-wide marker arrays provides encompassing insights into the genomic constitution of livestock populations. We have analyzed the genetic characterization of ten cattle breeds originating from Germany, The Netherlands and Denmark belonging to the group of red dairy breeds in Northern Europe. The results are intended to provide initial evidence on whether joint genomic breeding strategies of these populations will be successful.

Results

Traditional Danish Red and Groningen White-Headed were the most genetically differentiated breeds and their populations showed the highest levels of inbreeding. In contrast, close genetic relationships and shared ancestry were observed for the populations of German Red and White Dual-Purpose, Dutch Meuse-Rhine-Yssel, and Dutch Deep Red breeds, reflecting their common histories. A considerable amount of gene flow from Red Holstein to German Angler and to German Red and White Dual-Purpose was revealed, which is consistent with frequent crossbreeding to improve productivity of these local breeds. In Red Holstein, marked genomic signatures of selection were reported on chromosome 18, suggesting directed selection for important breeding goal traits. Furthermore, tests for signatures of selection between Red Holstein, Red and White Dual-Purpose, and Meuse-Rhine-Yssel uncovered signals for all investigated pairs of populations. The corresponding genomic regions, which were putatively under different selection pressures, harboured various genes which are associated with traits such as milk and beef production, mastitis and female fertility.

Conclusions

This study provides comprehensive knowledge on the genetic constitution and genomic connectedness of divergent red cattle populations in Northern Europe. The results will help to design and optimize breeding strategies. A joint genomic evaluation including some of the breeds studied here seems feasible.

Invited review: Beef-on-dairy-The generation of crossbred beef × dairy cattle

Because a growing proportion of the beef output in many countries originates from dairy herds, the most critical decisions about the genetic merit of most carcasses harvested are being made by dairy producers. Interest in the generation of more valuable calves from dairy females is intensifying, and the most likely vehicle is the use of appropriately selected beef bulls for mating to the dairy females. This is especially true given the growing potential to undertake more beef × dairy matings as herd metrics improve (e.g., reproductive performance) and technological advances are more widely adopted (e.g., sexed semen). Clear breed differences (among beef breeds but also compared with dairy breeds) exist for a whole plethora of performance traits, but considerable within-breed variability has also been demonstrated. Although such variability has implications for the choice of bull to mate to dairy females, the fact that dairy females themselves exhibit such genetic variability implies that "one size fits all" may not be appropriate for bull selection. Although differences in a whole series of key performance indicators have been documented between beef and beef-on-dairy animals, of particular note is the reported lower environmental hoofprint associated with beef-on-dairy production systems if the environmental overhead of the mature cow is attributed to the milk she eventually produces. Despite the known contribution of beef (i.e., both surplus calves and cull cows) to the overall gross output of most dairy herds globally, and the fact that each dairy female contributes half her genetic merit to her progeny, proxies for meat yield (i.e., veal or beef) are not directly considered in the vast majority of dairy cow breeding objectives. Breeding objectives to identify beef bulls suitable for dairy production systems are now being developed and validated, demonstrating the financial benefit of using such breeding objectives over and above a focus on dairy bulls or easy-calving, short-gestation beef bulls. When this approach is complemented by management-based decision-support tools, considerable potential exists to improve the profitability and sustainability of modern dairy production systems by exploiting beef-on-dairy breeding strategies using the most appropriate beef bulls.

Concordance rate in cattle and sheep between genotypes differing in Illumina GenCall quality score

Proper quality control of data prior to downstream analyses is fundamental to ensure integrity of results; quality control of genomic data is no exception. While many metrics of quality control of genomic data exist, the objective of the present study was to quantify the genotype and allele concordance rate between called single nucleotide polymorphism (SNP) genotypes differing in GenCall (GC) score; the GC score is a confidence measure assigned to each Illumina genotype call. This objective was achieved using Illumina beadchip genotype data from 771 cattle (12 428 767 genotypes in total post-editing) and 80 sheep (1 557 360 SNPs genotypes in total post-editing) each genotyped in duplicate. The called genotype with the lowest associated GC score was compared to the genotype called for the same SNP in the same duplicated animal sample but with a GC score of >0.90 (assumed to represent the true genotype). The mean genotype concordance rate for a GC score of <0.300, 0.300-0.549, and ≥0.550 in the cattle (sheep in parenthesis) was 0.9467 (0.9864), 0.9707 (0.9953), and 0.9994 (0.99997) respectively; the respective allele concordance rate was 0.9730 (0.9930), 0.9849 (0.9976), and 0.9997 (0.99998). Hence, concordance eroded as the GC score of the called genotype reduced, albeit the impact was not dramatic and was not very noticeable until a GC score of <0.55. Moreover, the impact was greater and more consistent in the cattle population than in the sheep population. Furthermore, an impact of GC score on genotype concordance rate existed even for the same SNP GenTrain value; the GenTrain value is a statistical score that depicts the shape of the genotype clusters and the relative distance between the called genotype clusters.

Genome-wide association study of economically important traits in Charolais and Limousin beef cows

Genomic selection has proven effective for advancing genetic gain for key profit traits in dairy cattle production systems. However, its impact to-date on genetic improvement programs for beef cattle has been less effective. Despite this, the technology is thought to be particularly useful for low heritability traits such as those associated with reproductive efficiency. The objective of this study was to identify genetic variants associated with key determinants of reproductive and overall productive efficiency in beef cows. The analysis employed a large dataset derived from the national genetic evaluation program in Ireland for two of the most predominant beef breeds, viz. Charolais (n = 5 244 cows) and Limousin (n = 7 304 cows). Single nucleotide polymorphisms (SNPs) were identified as being statistically significantly associated (adj. P < 0.05) with both reproductive and productive traits for both breed types. However, there was little across breed commonality, with only two SNPs (rs110240246 and rs110344317; adj. P < 0.05) located within the genomic regions of the LCORL and MSTN genes respectively, identified in both Charolais and Limousin populations, associated with traits including carcass weight, cull-cow weight and live-weight. Significant SNPs within the MSTN gene were also associated with both reproduction and production related traits within each breed. Finally, traits including calving difficulty, calf mortality and calving interval were associated with SNPs within genomic regions comprising genes involved in cellular growth and lipid metabolism. Genetic variants identified as associated with both important reproductive efficiency and production related traits from this study warrant further analyses for their potential incorporation into breeding programmes to support the sustainability of beef cattle production.

Genome-wide association study and pathway analysis for fat deposition traits in nellore cattle raised in pasture-based systems

Genome-wide association study (GWAS) is a powerful tool to identify candidate genes and genomic regions underlying key biological mechanisms associated with economically important traits. In this context, the aim of this study was to identify genomic regions and metabolic pathways associated with backfat thickness (BFT) and rump fat thickness (RFT) in Nellore cattle, raised in pasture-based systems. Ultrasound-based measurements of BFT and RFT (adjusted to 18 months of age) were collected in 11,750 animals, with 39,903 animals in the pedigree file. Additionally, 1,440 animals were genotyped using the GGP-indicus 35K SNP chip, containing 33,623 SNPs after the quality control. The single-step GWAS analyses were performed using the BLUPF90 family programs. Candidate genes were identified through the Ensembl database incorporated in the BioMart tool, while PANTHER and REVIGO were used to identify the key metabolic pathways and gene networks. A total of 18 genomic regions located on 10 different chromosomes and harbouring 23 candidate genes were identified for BFT. For RFT, 22 genomic regions were found on 14 chromosomes, with a total of 29 candidate genes identified. The results of the pathway analyses showed important genes for BFT, including TBL1XR1, AHCYL2, SLC4A7, AADAT, VPS53, IDH2 and ETS1, which are involved in lipid metabolism, synthesis of cellular amino acids, transport of solutes, transport between Golgi Complex membranes, cell differentiation and cellular development. The main genes identified for RFT were GSK3β, LRP1B, EXT1, GRB2, SORCS1 and SLMAP, which are involved in metabolic pathways such as glycogen synthesis, lipid transport and homeostasis, polysaccharide and carbohydrate metabolism. Polymorphisms located in these candidate genes can be incorporated in commercial genotyping platforms to improve the accuracy of imputation and genomic evaluations for carcass fatness. In addition to uncovering biological mechanisms associated with carcass quality, the key gene pathways identified can also be incorporated in biology-driven genomic prediction methods.

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.

Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock

Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher's exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle.

Genetic control of temperament traits across species: association of autism spectrum disorder risk genes with cattle temperament

BACKGROUND

Temperament traits are of high importance across species. In humans, temperament or personality traits correlate with psychological traits and psychiatric disorders. In cattle, they impact animal welfare, product quality and human safety, and are therefore of direct commercial importance. We hypothesized that genetic factors that contribute to variation in temperament among individuals within a species will be shared between humans and cattle. Using imputed whole-genome sequence data from 9223 beef cattle from three cohorts, a series of genome-wide association studies was undertaken on cattle flight time, a temperament phenotype measured as the time taken for an animal to cover a short-fixed distance after release from an enclosure. We also investigated the association of cattle temperament with polymorphisms in bovine orthologs of risk genes for neuroticism, schizophrenia, autism spectrum disorders (ASD), and developmental delay disorders in humans.

RESULTS

Variants with the strongest associations were located in the bovine orthologous region that is involved in several behavioural and cognitive disorders in humans. These variants were also partially validated in independent cattle cohorts. Genes in these regions (BARHL2, NDN, SNRPN, MAGEL2, ABCA12, KIFAP3, TOPAZ1, FZD3, UBE3A, and GABRA5) were enriched for the GO term neuron migration and were differentially expressed in brain and pituitary tissues in humans. Moreover, variants within 100 kb of ASD susceptibility genes were associated with cattle temperament and explained 6.5% of the total additive genetic variance in the largest cattle cohort. The ASD genes with the most significant associations were GABRB3 and CUL3. Using the same 100 kb window, a weak association was found with polymorphisms in schizophrenia risk genes and no association with polymorphisms in neuroticism and developmental delay disorders risk genes.

CONCLUSIONS

Our analysis showed that genes identified in a meta-analysis of cattle temperament contribute to neuron development functions and are differentially expressed in human brain tissues. Furthermore, some ASD susceptibility genes are associated with cattle temperament. These findings provide evidence that genetic control of temperament might be shared between humans and cattle and highlight the potential for future analyses to leverage results between species.

Breed- and trait-specific associations define the genetic architecture of calving performance traits in cattle

Reducing the incidence of both the degree of assistance required at calving, as well as the extent of perinatal mortality (PM) has both economic and societal benefits. The existence of heritable genetic variability in both traits signifies the presence of underlying genomic variability. The objective of the present study was to locate regions of the genome, and by extension putative genes and mutations, that are likely to be underpinning the genetic variability in direct calving difficulty (DCD), maternal calving difficulty (MCD), and PM. Imputed whole-genome single-nucleotide polymorphism (SNP) data on up to 8,304 Angus (AA), 17,175 Charolais (CH), 16,794 Limousin (LM), and 18,474 Holstein-Friesian (HF) sires representing 5,866,712 calving events from descendants were used. Several putative quantitative trait loci (QTL) regions associated with calving performance both within and across dairy and beef breeds were identified, although the majority were both breed- and trait-specific. QTL surrounding and encompassing the myostatin (MSTN) gene were associated (P < 5 × 10⁻⁸) with DCD and PM in both the CH and LM populations. The well-known Q204X mutation was the fifth strongest association with DCD in the CH population and accounted for 5.09% of the genetic variance in DCD. In contrast, none of the 259 segregating variants in MSTN were associated (P > × 10⁻⁶) with DCD in the LM population but a genomic region 617 kb downstream of MSTN was associated (P < 5 × 10⁻⁸). The genetic architecture for DCD differed in the HF population relative to the CH and LM, where two QTL encompassing ZNF613 on Bos taurus autosome (BTA)18 and PLAG1 on BTA14 were identified in the former. Pleiotropic SNP associated with all three calving performance traits were also identified in the three beef breeds; 5 SNP were pleiotropic in AA, 116 in LM, and 882 in CH but no SNP was associated with more than one trait within the HF population. The majority of these pleiotropic SNP were on BTA2 surrounding MSTN and were associated with both DCD and PM. Multiple previously reported, but also novel QTL, associated with calving performance were detected in this large study. These also included QTL regions harboring SNP with the same direction of allele substitution effect for both DCD and MCD thus contributing to a more effective simultaneous selection for both traits.

Detection of selection signatures in Limousin cattle using whole-genome resequencing

Limousin, a renowned beef breed originating from central France, has been selectively bred over the last 100 years to improve economically important traits. We used whole-genome sequencing data from 10 unrelated Limousin bull calves to detect polymorphisms and identify regions under selection. A total of 13 943 766 variants were identified. Moreover, 311 852 bi-allelic SNPs and 92 229 indels located on autosomes were fixed for the alternative allele in all sequenced animals, including the previously reported missense deleterious F94L mutation in MSTN. We performed a whole-genome screen to discover genomic regions with excess homozygosity, using the pooled heterozygosity score and identified 171 different candidate selective sweeps. In total, 68 candidate genes were found in only 57 of these regions, indicating that a large fraction of the genome under selection might lie in non-coding regions and suggesting that a majority of adaptive mutations might be regulatory in nature. Many QTL were found within candidate selective sweep regions, including QTL associated with shear force or carcass weight. Among the putative selective sweeps, we located genes (MSTN, NCKAP5, RUNX2) that potentially contribute to important phenotypes in Limousin. Several candidate regions and genes under selection were also found in previous genome-wide selection scans performed in Limousin. In addition, we were able to pinpoint candidate causative regulatory polymorphisms in GRIK3 and RUNX2 that might have been under selection. Our results will contribute to improved understanding of the mechanisms and targets of artificial selection and will facilitate the interpretation of GWASs performed in Limousin.

A Gene-Set Enrichment and Protein-Protein Interaction Network-Based GWAS with Regulatory SNPs Identifies Candidate Genes and Pathways Associated with Carcass Traits in Hanwoo Cattle

Non-synonymous SNPs and protein coding SNPs within the promoter region of genes (regulatory SNPs) might have a significant effect on carcass traits. Imputed sequence level data of 10,215 Hanwoo bulls, annotated and filtered to include only regulatory SNPs (450,062 SNPs), were used in a genome-wide association study (GWAS) to identify loci associated with backfat thickness (BFT), carcass weight (CWT), eye muscle area (EMA), and marbling score (MS). A total of 15, 176, and 1 SNPs were found to be significantly associated (p < 1.11 × 10-7) with BFT, CWT, and EMA, respectively. The significant loci were BTA4 (CWT), BTA6 (CWT), BTA14 (CWT and EMA), and BTA19 (BFT). BayesR estimated that 1.1%~1.9% of the SNPs contributed to more than 0.01% of the phenotypic variance. So, the GWAS was complemented by a gene-set enrichment (GSEA) and protein-protein interaction network (PPIN) analysis in identifying the pathways affecting carcass traits. At p < 0.005 (~2,261 SNPs), 25 GO and 18 KEGG categories, including calcium signaling, cell proliferation, and folate biosynthesis, were found to be enriched through GSEA. The PPIN analysis showed enrichment for 81 candidate genes involved in various pathways, including the PI3K-AKT, calcium, and FoxO signaling pathways. Our finding provides insight into the effects of regulatory SNPs on carcass traits.

Genomic Regions Associated With Skeletal Type Traits in Beef and Dairy Cattle Are Common to Regions Associated With Carcass Traits, Feed Intake and Calving Difficulty

Linear type traits describing the skeletal characteristics of an animal are moderately to strongly genetically correlated with a range of other performance traits in cattle including feed intake, reproduction traits and carcass merit; thus, type traits could also provide useful insights into the morphological differences among animals underpinning phenotypic differences in these complex traits. The objective of the present study was to identify genomic regions associated with five subjectively scored skeletal linear traits, to determine if these associated regions are common in multiple beef and dairy breeds, and also to determine if these regions overlap with those proposed elsewhere to be associated with correlated performance traits. Analyses were carried out using linear mixed models on imputed whole genome sequence data separately in 1,444 Angus, 1,129 Hereford, 6,433 Charolais, 8,745 Limousin, 1,698 Simmental, and 4,494 Holstein-Friesian cattle, all scored for the linear type traits. There was, on average, 18 months difference in age at assessment of the beef versus the dairy animals. While the majority of the identified quantitative trait loci (QTL), and thus genes, were both trait-specific and breed-specific, a large-effect pleiotropic QTL on BTA6 containing the NCAPG and LCORL genes was associated with all skeletal traits in the Limousin population and with wither height in the Angus. Other than that, little overlap existed in detected QTLs for the skeletal type traits in the other breeds. Only two QTLs overlapped the beef and dairy breeds; both QTLs were located on BTA5 and were associated with height in both the Angus and the Holstein-Friesian, despite the difference in age at assessment. Several detected QTLs in the present study overlapped with QTLs documented elsewhere that are associated with carcass traits, feed intake, and calving difficulty. While most breeding programs select for the macro-traits like carcass weight, carcass conformation, and feed intake, the higher degree of granularity with selection on the individual linear type traits in a multi-trait index underpinning the macro-level goal traits, presents an opportunity to help resolve genetic antagonisms among morphological traits in the pursuit of the animal with optimum performance metrics.

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.

Genomic Regions Associated With Gestation Length Detected Using Whole-Genome Sequence Data Differ Between Dairy and Beef Cattle

While many association studies exist that have attempted to relate genomic markers to phenotypic performance in cattle, very few have considered gestation length as a phenotype, and of those that did, none used whole genome sequence data from multiple breeds. The objective of the present study was therefore to relate imputed whole genome sequence data to estimated breeding values for gestation length using 22,566 sires (representing 2,262,706 progeny) of multiple breeds [Angus (AA), Charolais (CH), Holstein-Friesian (HF), and Limousin (LM)]. The associations were undertaken within breed using linear mixed models that accounted for genomic relatedness among sires; a separate association analysis was undertaken with all breeds analysed together but with breed included as a fixed effect in the model. Furthermore, the genome was divided into 500 kb segments and whether or not segments harboured a single nucleotide polymorphism (SNP) with a P ≤ 1 × 10^-4 common to different combinations of breeds was determined. Putative quantitative trait loci (QTL) regions associated with gestation length were detected in all breeds; significant associations with gestation length were only detected in the HF population and in the across-breed analysis of all 22,566 sires. Twenty-five SNPs were significantly associated (P ≤ 5 × 10^-8) with gestation length in the HF population. Of the 25 significant SNPs, 18 were located within three QTLs on Bos taurus autosome number (BTA) 18, six were in two QTL on BTA19, and one was located within a QTL on BTA7. The strongest association was rs381577268, a downstream variant of ZNF613 located within a QTL spanning from 58.06 to 58.19 Mb on BTA18; it accounted for 1.37% of the genetic variance in gestation length. Overall there were 11 HF animals within the edited dataset that were homozygous for the T allele at rs381577268 and these had a 3.3 day longer (P < 0.0001) estimated breeding value (EBV) for gestation length than the heterozygous animals and a 4.7 day longer (P < 0.0001) EBV for gestation length than the homozygous CC animals. The majority of the 500 kb windows harboring a SNP with a P ≤ 1 × 10^-4 were unique to a single breed and no window was shared among all four breeds for gestation length, suggesting any QTLs identified are breed-specific associations.