Polymorphisms in twelve candidate genes are associated with growth, muscle lipid profile and meat quality traits in eleven European cattle breeds

Genome-Wide Gene-Environment Interaction Analysis Identifies Novel Candidate Variants for Growth Traits in Beef Cattle

Complex traits are widely considered to be the result of a compound regulation of genes, environmental factors, and genotype-by-environment interaction (G × E). The inclusion of G × E in genome-wide association analyses is essential to understand animal environmental adaptations and improve the efficiency of breeding decisions. Here, we systematically investigated the G × E of growth traits (including weaning weight, yearling weight, 18-month body weight, and 24-month body weight) with environmental factors (farm and temperature) using genome-wide genotype-by-environment interaction association studies (GWEIS) with a dataset of 1350 cattle. We validated the robust estimator's effectiveness in GWEIS and detected 29 independent interacting SNPs with a significance threshold of 1.67 × 10-6, indicating that these SNPs, which do not show main effects in traditional genome-wide association studies (GWAS), may have non-additive effects across genotypes but are obliterated by environmental means. The gene-based analysis using MAGMA identified three genes that overlapped with the GEWIS results exhibiting G × E, namely SMAD2, PALMD, and MECOM. Further, the results of functional exploration in gene-set analysis revealed the bio-mechanisms of how cattle growth responds to environmental changes, such as mitotic or cytokinesis, fatty acid β-oxidation, neurotransmitter activity, gap junction, and keratan sulfate degradation. This study not only reveals novel genetic loci and underlying mechanisms influencing growth traits but also transforms our understanding of environmental adaptation in beef cattle, thereby paving the way for more targeted and efficient breeding strategies.

A network-based approach to understanding gene-biological processes affecting economically important traits of Nelore cattle

This study aimed to build gene-biological process networks with differentially expressed genes associated with economically important traits of Nelore cattle from 17 previous studies. The genes were clustered into three groups by evaluated traits: group 1, production traits; group 2, carcass traits; and group 3, meat quality traits. For each group, a gene-biological process network analysis was performed with the differentially expressed genes in common. For production traits, 37 genes were found in common, of which 13 genes were enriched for six Gene Ontology (GO) terms; these terms were not functionally grouped. However, the enriched GO terms were related to homeostasis, the development of muscles and the immune system. For carcass traits, four genes were found in common. Thus, it was not possible to functionally group these genes into a network. For meat quality traits, the analysis revealed 222 genes in common. CSRP3 was the only gene differentially expressed in all three groups. Non-redundant biological terms for clusters of genes were functionally grouped networks, reflecting the cross-talk between all biological processes and genes involved. Many biological processes and pathways related to muscles, the immune system and lipid metabolism were enriched, such as striated muscle cell development and triglyceride metabolic processes. This study provides insights into the genetic mechanisms of production, carcass and meat quality traits of Nelore cattle. This information is fundamental for a better understanding of the complex traits and could help in planning strategies for the production and selection systems of Nelore cattle.

A genome-wide association analysis for body, udder, and leg conformation traits recorded in Murciano-Granadina goats

Morphological traits are of great importance to dairy goat production given their effect on phenotypes of economic interest. However, their underlying genomic architecture has not yet been extensively characterized. Herein, we aimed to identify genomic regions associated with body, udder, and leg conformation traits recorded in 825 Murciano-Granadina goats. We genotyped this resource population using the GoatSNP50 BeadChip (Illumina Inc., San Diego, CA) and performed genome-wide association analyses using the GEMMA software. We found 2 genome-wide significant associations between markers rs268273468 [Capra hircus (CHI) 16:69617700] and rs268249346 (CHI 28:18321523) and medial suspensory ligament. In contrast, we did not detect any genome-wide significant associations for body and leg traits. Moreover, we found 12, 19, and 7 chromosome-wide significant associations for udder, body, and leg traits, respectively. Comparison of our data with previous studies revealed a low level of positional concordance between regions associated with morphological traits. In addition to technical factors, this lack of concordance could be due to a substantial level of genetic heterogeneity among breeds or to the strong polygenic background of morphological traits, which makes it difficult to detect genetic factors that have small phenotypic effects.

Use of the Multivariate Discriminant Analysis for Genome-Wide Association Studies in Cattle

Simple Summary

In the traditional single marker regression approach for genome-wide association studies, if the number of involved individuals is small and the number of single nucleotide polymorphisms (SNPs) to be tested is very large, the probability of getting a significant association simply due to chance becomes enormous. Other techniques, such as the Bayesian methods, require several a priori assumptions, as an a priori posterior inclusion probability threshold, that can limit their effectiveness. In the present study, a multivariate algorithm able to partially overcome this problem was proposed. On simulated data, with 3000 individuals, only 13 and 3 quantitative trait loci (QTLs) were obtained with the single marker regression and the Bayesian approaches, respectively. On the other hand, the multivariate algorithm detected 65 QTLs in the same scenario. The gap between the single marker regression and the multivariate methods slowly decreased as the number of animals increased. This figure was also confirmed on real data.

Abstract

Genome-wide association studies (GWAS) are traditionally carried out by using the single marker regression model that, if a small number of individuals is involved, often lead to very few associations. The Bayesian methods, such as BayesR, have obtained encouraging results when they are applied to the GWAS. However, these approaches, require that an a priori posterior inclusion probability threshold be fixed, thus arbitrarily affecting the obtained associations. To partially overcome these problems, a multivariate statistical algorithm was proposed. The basic idea was that animals with different phenotypic values of a specific trait share different allelic combinations for genes involved in its determinism. Three multivariate techniques were used to highlight the differences between the individuals assembled in high and low phenotype groups: the canonical discriminant analysis, the discriminant analysis and the stepwise discriminant analysis. The multivariate method was tested both on simulated and on real data. The results from the simulation study highlighted that the multivariate GWAS detected a greater number of true associated single nucleotide polymorphisms (SNPs) and Quantitative trait loci (QTLs) than the single marker model and the Bayesian approach. For example, with 3000 animals, the traditional GWAS highlighted only 29 significantly associated markers and 13 QTLs, whereas the multivariate method found 127 associated SNPs and 65 QTLs. The gap between the two approaches slowly decreased as the number of animals increased. The Bayesian method gave worse results than the other two. On average, with the real data, the multivariate GWAS found 108 associated markers for each trait under study and among them, around 63% SNPs were also found in the single marker approach. Among the top 118 associated markers, 76 SNPs harbored putative candidate genes.

Identification of genetic loci associated with growth traits at weaning in yak through a genome-wide association study

A multilocus GWAS was performed to explore the genetic architecture of four growth traits in yak. In total, 354 female yaks for which measurements of body weight (BW), withers height (WH), body length (BL) and chest girth (CG) at weaning were available underwent genotyping with the Illumina BovineHD BeadChip (770K). After quality control, we retained 98 688 SNPs and 354 animals for GWAS analysis. We identified seven, 18, seven and nine SNPs (corresponding to seven, 17, seven and eight candidate genes) associated with BW, WH, BL and CG at weaning respectively. Interestingly, most of these candidate genes were reported to be involved in growth-related processes such as muscle formation, lipid deposition, feed efficiency, carcass composition and development of the central and peripheral nervous system. Our results offer novel insight into the molecular architecture underpinning yak growth traits. Further functional analyses are thus warranted to explore the molecular mechanisms whereby these genes affect these traits of interest.

Genome-Wide Scan Identifies Selection Signatures in Chinese Wagyu Cattle Using a High-Density SNP Array

Selective breeding can lead to genetic diversity and diverse phenotypes in farm animals. Analysis of the genomic regions under selection can provide important insights into the genetic basis of complex traits. In this study, a high-density SNP array was used for analysis of genome selection signatures in Chinese Wagyu cattle. In total, we obtained 478,903 SNPs and 24,820 no-overlap regions for |iHS| (integrated haplotype score) estimations. Under the threshold of the top 1%, 239 regions were finally identified as candidate selected regions and 162 candidate genes were found based on the UMD3.1 genome assembly. These genes were reported to be associated with fatty acids, such as Bos taurus nitric oxide synthase 1 adaptor protein (NOS1AP), Bos taurus hydroxysteroid 17-beta dehydrogenase 7 (HSD17B7), Bos taurus WD repeat domain 7 (WDR7), Bos taurus ELOVL fatty acid elongase 2 (ELOVL2), Bos taurus calpain 1 (CAPN1), Bos taurus parkin RBR E3 ubiquitin protein ligase (PRKN, also known as PARK2), Bos taurus mitogen-activated protein kinase kinase 6 (MAP2K6), meat quality, including Bos taurus ADAM metallopeptidase domain 12 (ADAM12), Bos taurus 5'-aminolevulinate synthase 1 (ALAS1), Bos taurus small integral membrane protein 13 (SMIM13) and Bos taurus potassium two pore domain channel subfamily K member 2 (KCNK2), growth, and developmental traits, such as Bos taurus insulin like growth factor 2 receptor (IGF2R), Bos taurus RAR related orphan receptor A (RORA), Bos taurus fibroblast growth factor 14 (FGF14), Bos taurus paired box 6 (PAX6) and Bos taurus LIM homeobox 6 (LHX6). In addition, we identified several genes that are associated with body size and weight, including Bos taurus sorting nexin 29 (SNX29), Bos taurus zinc finger imprinted 2 (ZIM2), Bos taurus family with sequence similarity 110 member A (FAM110A), immune system, including Bos taurus toll like receptor 9 (TLR9), Bos taurus TAFA chemokine like family member 1 (TAFA1), Bos taurus glutathione peroxidase 8 (putative) (GPX8), Bos taurus interleukin 5 (IL5), Bos taurus PR domain containing 9 (PRDM9), Bos taurus glutamate ionotropic receptor kainate type subunit 2 (GRIK2) and feed intake efficiency, Bos taurus sodium voltage-gated channel alpha subunit 9 (SCN9A), Bos taurus relaxin family peptide/INSL5 receptor 4 (RXFP4), Bos taurus RNA polymerase II associated protein 3 (RPAP3). Moreover, four GO terms of biological regulation (GO:0009987, GO:0008152) and metabolic process (GO:0003824, GO:0005488) were found based on these genes. In addition, we found that 232 candidate regions (~18 Mb) overlapped with the Quantitative trait loci (QTL)regions extracted from cattle QTLdb. Our findings imply that many genes were selected for important traits in Chinese Wagyu cattle. Moreover, these results can contribute to the understanding of the genetic basis of the studied traits during the formation of this population.

Sequencing the mosaic genome of Brahman cattle identifies historic and recent introgression including polled

Brahman cattle have a Bos indicus and Bos taurus mosaic genome, as a result of the process used to create the breed (repeat backcrossing of Bos taurus females to Bos indicus bulls). With the aim of identifying Bos taurus segments in the Brahman genome at sequence level resolution, we sequenced the genomes of 46 influential Brahman bulls. Using 36 million variants identified in the sequences, we searched for regions close to fixation for Bos indicus or Bos taurus segments that were longer than expected by chance (from simulation of the breed formation history of Brahman cattle). Regions close to fixation for Bos indicus content were enriched for protein synthesis genes, while regions of higher Bos taurus content included genes of the G-protein coupled receptor family (including genes implicated in puberty, such as THRS). The region with the most extreme Bos taurus enrichment was on chromosome 14 surrounding PLAG1. The introgressed Bos taurus allele at PLAG1 increases stature and the high frequency of the allele likely reflects strong selection for the trait. Finally, we provide evidence that the polled mutation in Brahmans, a desirable trait under very strong recent selection, is of Celtic origin and is introgressed from Bos taurus.

Comparison of transcriptomic landscapes of different lamb muscles using RNA-Seq

Transcriptome deep sequencing is a powerful tool for exploring the genetic architecture of complex traits. Gene expression patterns may explain a high degree of the observed phenotypic differences in histochemical and metabolic parameters related to meat quality among different muscles. In this study, we sequenced by RNA-Seq the whole transcriptome of nine lamb muscles: Semimembranosus (SM), Semitendinosus (ST), Cranial gluteobiceps, Gluteus medius (GM), Rectus femoris, Supraspinatus (SS), Longissimus lumborum (LL), Adductor and Psoas major. Significant gene expression differences were detected between almost all pairwise comparisons, being more pronounced between SS and ST, SM and LL, and ST and GM. These differences can be explained in terms of ATPase and glycolytic activities, muscle fiber typing and oxidative score, clustering muscles as fast glycolytic, intermediate or slow oxidative. ST showed up-regulation of gene pathways related to carbohydrate metabolism, energy generation and protein turnover as expected from a fast white muscle. SS showed myosin isoforms typical of slow muscles and high expression of genes related to calcium homeostasis and vascularization. SM, LL and GM showed in general intermediate gene expression patterns. Several novel transcripts were detected, mostly related to muscle contraction and structure, oxidative metabolism, lipid metabolism and protein phosphorylation. Expression profiles were consistent with previous histochemical and metabolic characterization of these muscles. Up-regulation of ion transport genes may account for significant differences in water holding capacity. High expression of genes related to cell adhesion, cytoskeleton organization, extracellular matrix components and protein phosphorylation may be related to meat yellowness and lower tenderness scores. Differential expression of genes related to glycolytic activity and lactic acid generation among fast, intermediate and slow muscles may explain the detected final meat pH differences. These results reveal new candidate genes associated with lamb meat quality, and give a deeper insight into the genetic architecture of these complex traits.

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

Background

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

Results

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

Conclusions

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

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0381-2) contains supplementary material, which is available to authorized users.

Identification of Biomarkers Associated with the Rearing Practices, Carcass Characteristics, and Beef Quality: An Integrative Approach

Data from birth to slaughter of cull cows allowed using a PCA-based approach coupled with the iterative K-means algorithm the identification of three rearing practices classes. The classes were different in their carcass characteristics. Old cows raised mainly on pasture have better carcass characteristics, while having an equivalent tenderness, juiciness, flavor, intramuscular fat content, and pHu to those fattened with hay or haylage. The Longissimus thoracis muscle of the cows raised on pasture (with high physical activity) showed greater proportions of IIA fibers at the expense of the fast IIX ones. Accordingly, the meat of these animals have better color characteristics. Superoxide dismutase (SOD1) and αB-crystallin quantified by Dot-Blot were the only other biomarkers to be more abundant in "Grass" class compared to "Hay" and "Haylage" classes. The relationships between the biomarkers and the 6 carcass and 11 meat quality traits were investigated using multiple regression analyses per rearing practices. The associations were rearing practice class and phenotype trait-dependent. ICDH and TP53 were common for the three classes, but the direction of their entrance was different. In addition, rearing practices and carcass traits were not related with Hsp70-Grp75 and μ-calpain abundances. The other relationships were specific for two or one rearing practices class. The rearing practices dependency of the relationships was also found with meat quality traits. Certain proteins were for the first time related with some beef quality traits. MyHC-IIx, PGM1, Hsp40, ICDH, and Hsp70-Grp75 were common for the three rearing practices classes and retained to explain at list one beef quality trait. A positive relationship was found between PGM1 and hue angle irrespective of rearing practices class. This study confirms once again that production-related traits in livestock are the result of sophisticated biological processes finely orchestrated during the life of the animal and soon after slaughter.

Global Metabolic Reconstruction and Metabolic Gene Evolution in the Cattle Genome

The sequence of cattle genome provided a valuable opportunity to systematically link genetic and metabolic traits of cattle. The objectives of this study were 1) to reconstruct genome-scale cattle-specific metabolic pathways based on the most recent and updated cattle genome build and 2) to identify duplicated metabolic genes in the cattle genome for better understanding of metabolic adaptations in cattle. A bioinformatic pipeline of an organism for amalgamating genomic annotations from multiple sources was updated. Using this, an amalgamated cattle genome database based on UMD_3.1, was created. The amalgamated cattle genome database is composed of a total of 33,292 genes: 19,123 consensus genes between NCBI and Ensembl databases, 8,410 and 5,493 genes only found in NCBI or Ensembl, respectively, and 266 genes from NCBI scaffolds. A metabolic reconstruction of the cattle genome and cattle pathway genome database (PGDB) was also developed using Pathway Tools, followed by an intensive manual curation. The manual curation filled or revised 68 pathway holes, deleted 36 metabolic pathways, and added 23 metabolic pathways. Consequently, the curated cattle PGDB contains 304 metabolic pathways, 2,460 reactions including 2,371 enzymatic reactions, and 4,012 enzymes. Furthermore, this study identified eight duplicated genes in 12 metabolic pathways in the cattle genome compared to human and mouse. Some of these duplicated genes are related with specific hormone biosynthesis and detoxifications. The updated genome-scale metabolic reconstruction is a useful tool for understanding biology and metabolic characteristics in cattle. There has been significant improvements in the quality of cattle genome annotations and the MetaCyc database. The duplicated metabolic genes in the cattle genome compared to human and mouse implies evolutionary changes in the cattle genome and provides a useful information for further research on understanding metabolic adaptations of cattle.

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

Background

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

Results

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

Conclusions

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

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2511-y) contains supplementary material, which is available to authorized users.

An interpretive review of selective sweep studies in Bos taurus cattle populations: identification of unique and shared selection signals across breeds

This review compiles the results of 21 genomic studies of European Bos taurus breeds and thus provides a general picture of the selection signatures in taurine cattle identified by genome-wide selection-mapping scans. By performing a comprehensive summary of the results reported in the literature, we compiled a list of 1049 selection sweeps described across 37 cattle breeds (17 beef breeds, 14 dairy breeds, and 6 dual-purpose breeds), and four different beef-vs.-dairy comparisons, which we subsequently grouped into core selective sweep (CSS) regions, defined as consecutive signals within 1 Mb of each other. We defined a total of 409 CSSs across the 29 bovine autosomes, 232 (57%) of which were associated with a single-breed (Single-breed CSSs), 134 CSSs (33%) were associated with a limited number of breeds (Two-to-Four-breed CSSs) and 39 CSSs (9%) were associated with five or more breeds (Multi-breed CSSs). For each CSS, we performed a candidate gene survey that identified 291 genes within the CSS intervals (from the total list of 5183 BioMart-extracted genes) linked to dairy and meat production, stature, and coat color traits. A complementary functional enrichment analysis of the CSS positional candidates highlighted other genes related to pathways underlying behavior, immune response, and reproductive traits. The Single-breed CSSs revealed an over-representation of genes related to dairy and beef production, this was further supported by over-representation of production-related pathway terms in these regions based on a functional enrichment analysis. Overall, this review provides a comparative map of the selection sweeps reported in European cattle breeds and presents for the first time a characterization of the selection sweeps that are found in individual breeds. Based on their uniqueness, these breed-specific signals could be considered as “divergence signals,” which may be useful in characterizing and protecting livestock genetic diversity.