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

Meta-analysis of six dairy cattle breeds reveals biologically relevant candidate genes for mastitis resistance

BACKGROUND

Mastitis is a disease that incurs significant costs in the dairy industry. A promising approach to mitigate its negative effects is to genetically improve the resistance of dairy cattle to mastitis. A meta-analysis of genome-wide association studies (GWAS) across multiple breeds for clinical mastitis (CM) and its indicator trait, somatic cell score (SCS), is a powerful method to identify functional genetic variants that impact mastitis resistance.

RESULTS

We conducted meta-analyses of eight and fourteen GWAS on CM and SCS, respectively, using 30,689 and 119,438 animals from six dairy cattle breeds. Methods for the meta-analyses were selected to properly account for the multi-breed structure of the GWAS data. Our study revealed 58 lead markers that were associated with mastitis incidence, including 16 loci that did not overlap with previously identified quantitative trait loci (QTL), as curated at the Animal QTLdb. Post-GWAS analysis techniques such as gene-based analysis and genomic feature enrichment analysis enabled prioritization of 31 candidate genes and 14 credible candidate causal variants that affect mastitis.

CONCLUSIONS

Our list of candidate genes can help to elucidate the genetic architecture underlying mastitis resistance and provide better tools for the prevention or treatment of mastitis, ultimately contributing to more sustainable animal production.

A review of the role of epigenetic studies for intramuscular fat deposition in beef cattle

Intramuscular fat (IMF) deposition profoundly influences meat quality and economic value in beef cattle production. Meanwhile, contemporary developments in epigenetics have opened new outlooks for understanding the molecular basics of IMF regulation, and it has become a key area of research for world scholars. Therefore, the aim of this paper was to provide insight and synthesis into the intricate relationship between epigenetic mechanisms and IMF deposition in beef cattle. The methodology involves a thorough analysis of existing literature, including pertinent books, academic journals, and online resources, to provide a comprehensive overview of the role of epigenetic studies in IMF deposition in beef cattle. This review summarizes the contemporary studies in epigenetic mechanisms in IMF regulation, high-resolution epigenomic mapping, single-cell epigenomics, multi-omics integration, epigenome editing approaches, longitudinal studies in cattle growth, environmental epigenetics, machine learning in epigenetics, ethical and regulatory considerations, and translation to industry practices from perspectives of IMF deposition in beef cattle. Moreover, this paper highlights DNA methylation, histone modifications, acetylation, phosphorylation, ubiquitylation, non-coding RNAs, DNA hydroxymethylation, epigenetic readers, writers, and erasers, chromatin immunoprecipitation followed by sequencing, whole genome bisulfite sequencing, epigenome-wide association studies, and their profound impact on the expression of crucial genes governing adipogenesis and lipid metabolism. Nutrition and stress also have significant influences on epigenetic modifications and IMF deposition. The key findings underscore the pivotal role of epigenetic studies in understanding and enhancing IMF deposition in beef cattle, with implications for precision livestock farming and ethical livestock management. In conclusion, this review highlights the crucial significance of epigenetic pathways and environmental factors in affecting IMF deposition in beef cattle, providing insightful information for improving the economics and meat quality of cattle production.

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

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

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 Analysis Reveals Novel Loci Related with Visual Score Traits in Nellore Cattle Raised in Pasture-Based Systems

Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1, RXRG, RAB2A, and CYP7A1, involved in lipid metabolism. The genes associated with PREC were ELOVL5, PID1, DNER, TRIP12, and PLCB4, which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A, TIAM2, UNC5A, and UIMC1. The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.

Bibliometric Analysis of Research on the Main Genes Involved in Meat Tenderness

Simple Summary

A bibliometric analysis was carried out to know the evolution of research on genes associated with meat tenderness, of interest for the development of selection programs. Since 1993, studies have been limited to a few researchers in high-income countries due to the costs associated with the techniques. The main findings showed that the scientific production had a discontinuous growth because science experienced a significant change since approximately 2010. Marker-assisted selection was widely used, evaluating mainly CAPN (calpain) and CAST (calpastatin) genes for their contribution to meat tenderness, especially in cattle. However, the effects are small; therefore, genomic selection was implemented by genotyping thousands of single nucleotide polymorphisms (SNPs) for further explanation of genetic variation. The results shown are important for scholars to identify emerging methodologies and gaps in the literature and to know who the prolific authors and institutions in the field for possible collaborations, etc., are.

Abstract

Tenderness is one of the main characteristics of meat because it determines its price and acceptability. This is the first bibliometric study on the trend of research on the role of genes in meat tenderness. A total of 175 original and English-language articles published up to 2021 were retrieved from Scopus. The bibliometric analysis was carried out with VOSviewer (version 1.6.18, Eck and Waltman, Leiden, Netherlands) and complemented with the Analyze search results service from Scopus. Erroneous and duplicate data were eliminated, and incomplete information was added to standardize the results. Scientific production was evaluated by means of quantity, quality and structure indicators. As a first glance, 8.816% of authors have published more than 50% of papers mainly related to genes encoding the calpain (CAPN)-calpastatin (CAST) system and single nucleotide polymorphisms (SNPs). Among other findings, a strong link was found between the contribution of the main countries (led by the United States with) and their institutions (led by the USDA Agricultural Research Service with) to their gross domestic product. Most studies on the topic are published in the Journal of Animal Science, and other journals with high impact according to the number of citations and different metrics. Finally, when evaluating the most cited articles, the occurrence and association of the main keywords, it was confirmed that research is focused on the role of CAPN and CAST genes and of SNPs in beef tenderness. The change in science was emphasized; although marker-assisted selection is still used, genes have an infinitesimal effect on complex traits. Therefore, since about 2010, new research groups adopted genomic selection to evaluate dense panels of SNPs and better explain genetic variation in meat tenderness.

Cross-population selection signatures in Canchim composite beef cattle

Analyses of livestock genomes have been used to detect selection signatures, which are genomic regions associated with traits under selection leading to a change in allele frequency. The objective of the present study was to characterize selection signatures in Canchim composite beef cattle using cross-population analyses with the founder Nelore and Charolais breeds. High-density single nucleotide polymorphism genotypes were available on 395 Canchim representing the target population, along with genotypes from 809 Nelore and 897 Charolais animals representing the reference populations. Most of the selection signatures were co-located with genes whose functions agree with the expectations of the breeding programs; these genes have previously been reported to associate with meat quality, as well as reproductive traits. Identified genes were related to immunity, adaptation, morphology, as well as behavior, could give new perspectives for understanding the genetic architecture of Canchim. Some selection signatures identified genes that were recently introduced in Canchim, such as the loci related to the polled trait.

Genome-wide association study for meat tenderness in beef cattle identifies patterns of the genetic contribution in different post-mortem stages

The beef tenderization process during the post-mortem period is one of the most important sensorial attributes and it is well-established. The aim of this study was to identify the genetic contribution pattern to meat tenderness at 7-(LMD7), 14-(LMD14), and 21-(LMD21) days post-mortem. The heritabilities for LMD7 (0.194), LMD14 (0.142) and LMD21 (0.048) are well established in the population evaluated here. However, its genetic contribution in terms of genomic candidate regions is still poorly understood. Tenderness was measured in the Longissiums thoracis using Warner-Bratzler shear force in the three post-mortem periods. A total of 4323 crossbred beef cattle were phenotyped and genotyped using the Illumina BovineSNP50K. The percentage of the total genetic variance was estimated using the weighted single-step genomic best linear unbiased prediction method. The main candidate windows for LMD7 were associated with proteolysis of myofibrillar structures and the weakening endomysium and perimysium. Candidate windows for LMD14 and LMD21 were mapped in bovine QTLs for body composition, height and growth. Results presented herein highlight, the largest contribution of proteolysis related processes before 14-days post-mortem and body composition characteristics in later stages for meat tenderness.

A Co-Association Network Analysis Reveals Putative Regulators for Health-Related Traits in Pigs

In recent years, the increase in awareness of antimicrobial resistance together with the societal demand of healthier meat products have driven attention to health-related traits in livestock production. Previous studies have reported medium to high heritabilities for these traits and described genomic regions associated with them. Despite its genetic component, health- and immunity-related traits are complex and its study by association analysis with genomic markers may be missing some information. To analyse multiple phenotypes and gene-by-gene interactions, systems biology approaches, such as the association weight matrix (AWM), allows combining genome wide association study results with network inference algorithms. The present study aimed to identify gene networks, key regulators and candidate genes associated to immunocompetence in pigs by integrating multiple health-related traits, enriched for innate immune phenotypes, using the AWM approach. The co-association network analysis unveiled a network comprised of 3,636 nodes (genes) and 451,407 edges (interactions), including a total of 246 regulators. From these, five genes (ARNT2, BRMS1L, MED12L, SUPT3H and TRIM25) were selected as key regulators as they were associated with the maximum number of genes with the minimum overlapping (1,827 genes in total). The five regulators were involved in pathways related to immunity such as lymphocyte differentiation and activation, platelet activation and degranulation, megakaryocyte differentiation, FcγR-mediated phagocytosis and response to nitric oxide, among others, but also in immunometabolism. Furthermore, we identified genes co-associated with the key regulators previously reported as candidate genes (e.g., ANGPT1, CD4, CD36, DOCK1, PDE4B, PRKCE, PTPRC and SH2B3) for immunity traits in humans and pigs, but also new candidate ones (e.g., ACSL3, CXADR, HBB, MMP12, PTPN6, WLS) that were not previously described. The co-association analysis revealed new regulators associated with health-related traits in pigs. This approach also identified gene-by-gene interactions and candidate genes involved in pathways related to cell fate and metabolic and immune functions. Our results shed new light in the regulatory mechanisms involved in pig immunity and reinforce the use of the pig as biomedical model.

Investigating the growth performance, meat quality, immune function and proteomic profiles of plasmal exosomes in Lactobacillus plantarum-treated broilers with immunological stress

Exosomes are extracellular membranous nanovesicles that carry functional molecules to mediate cell-to-cell communication. To date, whether probiotics improve the immune function of broilers by plasmal exosome cargo is unclear. In this study, 300 broilers were allocated to three treatments: control diet (CON group), control diet + dexamethasone injection (DEX group), and control diet containing 1 × 10⁸ cfu g^-1 P8 + DEX injection (P8 + DEX group). The growth performance, meat quality and immune function of plasma and jejunal mucosa were detected. Exosomes were isolated from the plasma and characterized. Then, the exosome protein profile was determined by proteomic analysis. Correlation analyses between the exosomal proteins and growth performance, meat quality, immune function were performed. Lastly, the related protein levels were verified by multiple reaction monitoring (MRM). Results showed that P8 treatment increased the growth performance, meat quality and immune function of DEX-induced broilers with immunological stress. Moreover, the average diameters, cup-shaped morphology and expressed exosomal proteins confirmed that the isolated extracellular vesicles were exosomes. A total of 784 proteins were identified in the exosomes; among which, 126 differentially expressed proteins (DEPs) were found between the DEX and CON groups and 102 DEPs were found between the P8 + DEX and DEX groups. Gene ontology analysis indicated that DEPs between the DEX and CON groups are mainly involved in the metabolic process, cellular anatomical entity, cytoplasm, etc. DEPs between the P8 + DEX and DEX groups are mainly involved in the multicellular organismal process, response to stimulus, cytoplasm, etc. Pathway analysis revealed that most of the DEPs between the DEX and CON groups participated in the ECM-receptor interaction, focal adhesion, regulation of actin cytoskeleton, etc. Most of the DEPs between the P8 + DEX and DEX groups participated in the ErbB and PPAR signaling pathways. Moreover, many DEPs were correlated with the altered parameters of growth performance, meat quality and immunity in P8-treated broilers. MRM further revealed that the upregulated FABP6 and EPCAM in the DEX group were decreased by P8 + DEX treatment, and the downregulated C1QTNF3 in the DEX group was increased by P8 + DEX treatment. In conclusion, our findings demonstrated that P8 may promote the immune function, growth performance and meat quality of broilers with immunological stress by regulating the plasma exosomal proteins, especially the proteins of FABP6, EPCAM and C1QTNF3 and the pathway of PPAR (ILK/FABP6).

Immortalizing Cells for Human Consumption

The need to produce immortal, food-relevant cell lines is one of the most pressing challenges of cellular agriculture, the field which seeks to produce meat and other animal products via tissue engineering and synthetic biology. Immortal cell lines have a long and complicated story, from the first recognized immortal human cell lines taken from Henrietta Lacks, to today, where they are used to assay toxicity and produce therapeutics, to the future, where they could be used to create meat without harming an animal. Although work in immortal cell lines began more than 50 years ago, there are few existing cell lines made of species and cell types appropriate for cultured meat. Cells in cultured meat will be eaten by consumers; therefore, cultured meat cell lines will also require unique attributes not selected for in other cell line applications. Specifically, cultured meat cell lines will need to be approved as safe for consumption as food, proliferate and differentiate efficiently at industrial scales, and have desirable taste, texture, and nutrition characteristics for consumers. This paper defines what cell lines are needed, the existing methods to produce new cell lines and their limitations, and the unique considerations of cell lines used in cultured meat.

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.

Genomic Approaches Reveal Pleiotropic Effects in Crossbred Beef Cattle

Carcass and meat quality are two important attributes for the beef industry because they drive profitability and consumer demand. These traits are of even greater importance in crossbred cattle used in subtropical and tropical regions for their superior adaptability because they tend to underperform compared to their purebred counterparts. Many of these traits are challenging and expensive to measure and unavailable until late in life or after the animal is harvested, hence unrealistic to improve through traditional phenotypic selection, but perfect candidates for genomic selection. Before genomic selection can be implemented in crossbred populations, it is important to explore if pleiotropic effects exist between carcass and meat quality traits. Therefore, the objective of this study was to identify genomic regions with pleiotropic effects on carcass and meat quality traits in a multibreed Angus-Brahman population that included purebred and crossbred animals. Data included phenotypes for 10 carcass and meat quality traits from 2,384 steers, of which 1,038 were genotyped with the GGP Bovine F-250. Single-trait genome-wide association studies were first used to investigate the relevance of direct additive genetic effects on each carcass, sensory and visual meat quality traits. A second analysis for each trait included all other phenotypes as covariates to correct for direct causal effects from identified genomic regions with pure direct effects on the trait under analysis. Five genomic windows on chromosomes BTA5, BTA7, BTA18, and BTA29 explained more than 1% of additive genetic variance of two or more traits. Moreover, three suggestive pleiotropic regions were identified on BTA10 and BTA19. The 317 genes uncovered in pleiotropic regions included anchoring and cytoskeletal proteins, key players in cell growth, muscle development, lipid metabolism and fat deposition, and important factors in muscle proteolysis. A functional analysis of these genes revealed GO terms directly related to carcass quality, meat quality, and tenderness in beef cattle, including calcium-related processes, cell signaling, and modulation of cell-cell adhesion. These results contribute with novel information about the complex genetic architecture and pleiotropic effects of carcass and meat quality traits in crossbred beef cattle.

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

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

A systems biology framework integrating GWAS and RNA-seq to shed light on the molecular basis of sperm quality in swine

BACKGROUND

Genetic pressure in animal breeding is sparking the interest of breeders for selecting elite boars with higher sperm quality to optimize ejaculate doses and fertility rates. However, the molecular basis of sperm quality is not yet fully understood. Our aim was to identify candidate genes, pathways and DNA variants associated to sperm quality in swine by analysing 25 sperm-related phenotypes and integrating genome-wide association studies (GWAS) and RNA-seq under a systems biology framework.

RESULTS

By GWAS, we identified 12 quantitative trait loci (QTL) associated to the percentage of head and neck abnormalities, abnormal acrosomes and motile spermatozoa. Candidate genes included CHD2, KATNAL2, SLC14A2 and ABCA1. By RNA-seq, we identified a wide repertoire of mRNAs (e.g. PRM1, OAZ3, DNAJB8, TPPP2 and TNP1) and miRNAs (e.g. ssc-miR-30d, ssc-miR-34c, ssc-miR-30c-5p, ssc-miR-191, members of the let-7 family and ssc-miR-425-5p) with functions related to sperm biology. We detected 6128 significant correlations (P-value ≤ 0.05) between sperm traits and mRNA abundances. By expression (e)GWAS, we identified three trans-expression QTL involving the genes IQCJ, ACTR2 and HARS. Using the GWAS and RNA-seq data, we built a gene interaction network. We considered that the genes and interactions that were present in both the GWAS and RNA-seq networks had a higher probability of being actually involved in sperm quality and used them to build a robust gene interaction network. In addition, in the final network we included genes with RNA abundances correlated with more than four semen traits and miRNAs interacting with the genes on the network. The final network was enriched for genes involved in gamete generation and development, meiotic cell cycle, DNA repair or embryo implantation. Finally, we designed a panel of 73 SNPs based on the GWAS, eGWAS and final network data, that explains between 5% (for sperm cell concentration) and 36% (for percentage of neck abnormalities) of the phenotypic variance of the sperm traits.

CONCLUSIONS

By applying a systems biology approach, we identified genes that potentially affect sperm quality and constructed a SNP panel that explains a substantial part of the phenotypic variance for semen quality in our study and that should be tested in other swine populations to evaluate its relevance for the pig breeding sector.

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

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

Gene networks for three feed efficiency criteria reveal shared and specific biological processes

Background

French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria.

Results

A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency.

Conclusions

The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

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

Simple Summary

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

Abstract

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

Genome-wide association studies reveal novel loci associated with carcass and body measures in beef cattle

Genomic selection has an essential role in the livestock economy by increasing selection productivity. Genomics provides a mechanism to increase the rate of genetic gain using marker-assisted selection. Various quantitative trait loci (QTL) associated with body, carcass and meat quality traits in beef cattle have been found. It is widely accepted that QTL traits in livestock species are regulated by several genes and factors from the environment. Genome-wide association studies (GWAS) are a powerful approach in identifying QTL and to establish genomic regions harboring the genes and polymorphisms associated with specific characteristics in beef cattle. Due to their impact on economic returns, growth, carcass and meat quality traits of cattle are frequently used as essential criteria in selection in breeding programs., GWAS has been used in beef cattle breeding and genetic program and some progress has been made. Furthermore, numerous genes and markers related to productivity traits in beef cattle have been found. This review summarizes the advances in the use of GWAS in beef cattle production and outlines the associations with growth, carcass, and meat quality.

Measuring quantitative proteomic distance between Spanish beef breeds

Estimates of quantitative proteomic distance between populations have not been reported to date. Here, quantitative proteomic distances between three Spanish bovine breeds (Asturiana de los Valles, AV; Retinta, RE; and Rubia Gallega, RG) were estimated from two-dimensional electrophoresis profiles of meat samples of longissimus thoracis muscle at 2 h post-mortem. Statistically significant distances were detected between AV/RG and the most genetically different RE breed, using the novel QD measure of quantitative proteomic distance. In total, 18 differentially abundant myofibrillar and sarcoplasmic proteins/isoforms contributing to proteomic distances between breeds were confidently identified by tandem mass spectrometry. The fast skeletal myosin regulatory light chain 2 followed by other five interacting proteins exhibited the most pronounced relative change between breeds. In addition, most differentially represented proteins could be associated with variations in meat tenderness. Therefore, they could be candidate biomarkers for molecular breeding programs and authentication of the three Spanish beef breeds.

Single Loci and Haplotypes in CAPN1 and CAST Genes are Associated with Growth, Biometrics, and in Vivo Carcass Traits in Santa Inês Sheep

µ-calpain (CAPN1) and calpastatin (CAST) genes play key roles in protein turnover. The present study aimed to identify the variants in these genes associated with growth and ultrasound carcass traits in Santa Inês sheep. A sample of 192 no full sibling Santa Inês lambs was used. Fragments of the CAST and CAPN1 genes were amplified and next-generation sequencing was performed in the MiSeq platform. Variants in the CAPN1 and CAST sequences were then detected using bioinformatic tools. Withers and croup heights, body length, thoracic and croup widths, thoracic and leg girths, body depth, carcass fat score, rib eye area, fat thickness, body weights were recorded at weaning and at 140 days post-weaning, and average daily gain post-weaning was calculated. Both single-locus and haplotype association analyses were performed with the model as follows: farm (2 levels), year (4 levels), the month of birth (12 levels), and the covariate age of the animal. The fragments amplified included 4,514 bp between the 20th and 23rd exons of CAST as well as 3,927 bp between the 12th and 21st exons of CAPN1. In these regions, 58 (CAST) and 45 (CAPN1) variants were identified. In the CAST gene, the single-locus analysis revealed 22 suggestive additive effects (P<0.05) on several growth and carcass traits. Moreover, haplotype substitutions were associated with rib eye area (–0.689±0.290), average daily gain (–23.6±10.4), thoracic girth (–2.72±1.27), body length (–3.38±1.49), and leg girth (–2.84±1.37). Regarding the CAPN1 gene, the single-locus analysis identified seven suggestive additive effects, while only one haplotype replacement effect on fat thickness (–0.0143±0.0053) was detected. The results of the present study suggest that variants in the CAPN1 and CAST genes are associated with growth and ultrasound carcass traits in Santa Inês sheep, which may be a source of information to improve knowledge regarding the genetic control of these traits.

Identification of Age-Specific and Common Key Regulatory Mechanisms Governing Eggshell Strength in Chicken Using Random Forests

In today's chicken egg industry, maintaining the strength of eggshells in longer laying cycles is pivotal for improving the persistency of egg laying. Eggshell development and mineralization underlie a complex regulatory interplay of various proteins and signaling cascades involving multiple organ systems. Understanding the regulatory mechanisms influencing this dynamic trait over time is imperative, yet scarce. To investigate the temporal changes in the signaling cascades, we considered eggshell strength at two different time points during the egg production cycle and studied the genotype-phenotype associations by employing the Random Forests algorithm on chicken genotypic data. For the analysis of corresponding genes, we adopted a well established systems biology approach to delineate gene regulatory pathways and master regulators underlying this important trait. Our results indicate that, while some of the master regulators (Slc22a1 and Sox11) and pathways are common at different laying stages of chicken, others (e.g., Scn11a, St8sia2, or the TGF- β pathway) represent age-specific functions. Overall, our results provide: (i) significant insights into age-specific and common molecular mechanisms underlying the regulation of eggshell strength; and (ii) new breeding targets to improve the eggshell quality during the later stages of the chicken production cycle.

Aggregation of Omic Data and Secretome Prediction Enable the Discovery of Candidate Plasma Biomarkers for Beef Tenderness

Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome.

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

Background

The high narrow sense heritability of carcass traits suggests that the underlying additive genetic potential of an individual should be strongly correlated with both animal carcass quality and quantity, and therefore, by extension, carcass value. Therefore, the objective of the present study was to detect genomic regions associated with three carcass traits, namely carcass weight, conformation and fat cover, using imputed whole genome sequence in 28,470 dairy and beef sires from six breeds with a total of 2,199,926 phenotyped progeny.

Results

Major genes previously associated with carcass performance were identified, as well as several putative novel candidate genes that likely operate both within and across breeds. The role of MSTN in carcass performance was re-affirmed with the segregating Q204X mutation explaining 1.21, 1.11 and 5.95% of the genetic variance in carcass weight, fat and conformation, respectively in the Charolais population. In addition, a genomic region on BTA6 encompassing the NCAPG/LCORL locus, which is a known candidate locus associated with body size, was associated with carcass weight in Angus, Charolais and Limousin. Novel candidate genes identified included ZFAT in Angus, and SLC40A1 and the olfactory gene cluster on BTA15 in Charolais. Although the majority of associations were breed specific, associations that operated across breeds included SORCS1 on BTA26, MCTP2 on BTA21 and ARL15 on BTA20; these are of particular interest due to their potential informativeness in across-breed genomic evaluations. Genomic regions affecting all three carcass traits were identified in each of the breeds, although these were mainly concentrated on BTA2 and BTA6, surrounding MSTN and NCAPG/LCORL, respectively. This suggests that although major genes may be associated with all three carcass traits, the majority of genes containing significant variants (unadjusted p-value < 10^− 4) may be trait specific associations of small effect.

Conclusions

Although plausible novel candidate genes were identified, the proportion of variance explained by these candidates was minimal thus reaffirming that while carcass performance may be affected by major genes in the form of MSTN and NCAPG/LCORL, the majority of variance is attributed to the additive (and possibly multiplicative) effect of many polymorphisms of small effect.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-6071-9) contains supplementary material, which is available to authorized users.

Integrating genome-wide co-association and gene expression to identify putative regulators and predictors of feed efficiency in pigs

BACKGROUND

Feed efficiency (FE) has a major impact on the economic sustainability of pig production. We used a systems-based approach that integrates single nucleotide polymorphism (SNP) co-association and gene-expression data to identify candidate genes, biological pathways, and potential predictors of FE in a Duroc pig population.

RESULTS

We applied an association weight matrix (AWM) approach to analyse the results from genome-wide association studies (GWAS) for nine FE associated and production traits using 31K SNPs by defining residual feed intake (RFI) as the target phenotype. The resulting co-association network was formed by 829 SNPs. Additive effects of this SNP panel explained 61% of the phenotypic variance of RFI, and the resulting phenotype prediction accuracy estimated by cross-validation was 0.65 (vs. 0.20 using pedigree-based best linear unbiased prediction and 0.12 using the 31K SNPs). Sixty-eight transcription factor (TF) genes were identified in the co-association network; based on the lossless approach, the putative main regulators were COPS5, GTF2H5, RUNX1, HDAC4, ESR1, USP16, SMARCA2 and GTF2F2. Furthermore, gene expression data of the gluteus medius muscle was explored through differential expression and multivariate analyses. A list of candidate genes showing functional and/or structural associations with FE was elaborated based on results from both AWM and gene expression analyses, and included the aforementioned TF genes and other ones that have key roles in metabolism, e.g. ESRRG, RXRG, PPARGC1A, TCF7L2, LHX4, MAML2, NFATC3, NFKBIZ, TCEA1, CDCA7L, LZTFL1 or CBFB. The most enriched biological pathways in this list were associated with behaviour, immunity, nervous system, and neurotransmitters, including melatonin, glutamate receptor, and gustation pathways. Finally, an expression GWAS allowed identifying 269 SNPs associated with the candidate genes' expression (eSNPs). Addition of these eSNPs to the AWM panel of 829 SNPs did not improve the accuracy of genomic predictions.

CONCLUSIONS

Candidate genes that have a direct or indirect effect on FE-related traits belong to various biological processes that are mainly related to immunity, behaviour, energy metabolism, and the nervous system. The pituitary gland, hypothalamus and thyroid axis, and estrogen signalling play fundamental roles in the regulation of FE in pigs. The 829 selected SNPs explained 61% of the phenotypic variance of RFI, which constitutes a promising perspective for applying genetic selection on FE relying on molecular-based prediction.

Genome-wide association and pathway analysis of carcass and meat quality traits in Piemontese young bulls

A key concern in beef production is how to improve carcass and meat quality traits. Identifying the genomic regions and biological pathways that contribute to explaining variability in these traits is of great importance for selection purposes. In this study, genome wide-association (GWAS) and pathway-based analyses of carcass traits (age at slaughter (AS), carcass weight (CW), carcass daily gain (CDG), conformation score and rib-eye muscle area) and meat quality traits (pH, Warner-Bratzler shear force, purge loss, cooking loss and colour parameters (lightness, redness, yellowness, chroma, hue)) were conducted using genotype data from the 'GeneSeek Genomic Profiler Bovine LD' array in a cohort of 1166 double-muscled Piemontese beef cattle. The genome wide-association analysis was based on the GRAMMAR-GC approach and identified 37 significant single nucleotide polymorphisms (SNPs), which were associated with 12 traits (P<5 × 10-5). In particular, 14 SNPs associated with CW, CDG and AS were located at 38.57 to 38.94 Mb on Bos taurus autosome 6 and mapped within four genes, that is, Leucine Aminopeptidase 3, Family with Sequence Similarity 184 Member B, Non-SMC Condensin I Complex Subunit G and Ligand-Dependent Nuclear Receptor Corepressor-Like. Strong pairwise linkage disequilibrium was found in this region. For meat quality traits, most associations were 1 SNP per trait, except for a signal on BTA25 (at ~11.96 Mb), which was significant for four of the five meat colour parameters assessed. Gene-set enrichment analyses yielded significant results for six traits (right-sided hypergeometric test, false discovery rate <0.05). In particular, several pathways related to transmembrane transport (i.e., oxygen, calcium, ion and cation) were overrepresented for meat colour parameters. The results obtained provide useful information for genomic selection for beef production and quality in the Piemontese breed.

Sequence-based GWAS, network and pathway analyses reveal genes co-associated with milk cheese-making properties and milk composition in Montbéliarde cows

BACKGROUND

Milk quality in dairy cattle is routinely assessed via analysis of mid-infrared (MIR) spectra; this approach can also be used to predict the milk's cheese-making properties (CMP) and composition. When this method of high-throughput phenotyping is combined with efficient imputations of whole-genome sequence data from cows' genotyping data, it provides a unique and powerful framework with which to carry out genomic analyses. The goal of this study was to use this approach to identify genes and gene networks associated with milk CMP and composition in the Montbéliarde breed.

RESULTS

Milk cheese yields, coagulation traits, milk pH and contents of proteins, fatty acids, minerals, citrate, and lactose were predicted from MIR spectra. Thirty-six phenotypes from primiparous Montbéliarde cows (1,442,371 test-day records from 189,817 cows) were adjusted for non-genetic effects and averaged per cow. 50 K genotypes, which were available for a subset of 19,586 cows, were imputed at the sequence level using Run6 of the 1000 Bull Genomes Project (comprising 2333 animals). The individual effects of 8.5 million variants were evaluated in a genome-wide association study (GWAS) which led to the detection of 59 QTL regions, most of which had highly significant effects on CMP and milk composition. The results of the GWAS were further subjected to an association weight matrix and the partial correlation and information theory approach and we identified a set of 736 co-associated genes. Among these, the well-known caseins, PAEP and DGAT1, together with dozens of other genes such as SLC37A1, ALPL, MGST1, SEL1L3, GPT, BRI3BP, SCD, GPAT4, FASN, and ANKH, explained from 12 to 30% of the phenotypic variance of CMP traits. We were further able to identify metabolic pathways (e.g., phosphate and phospholipid metabolism and inorganic anion transport) and key regulator genes, such as PPARA, ASXL3, and bta-mir-200c that are functionally linked to milk composition.

CONCLUSIONS

By using an approach that integrated GWAS with network and pathway analyses at the whole-genome sequence level, we propose candidate variants that explain a substantial proportion of the phenotypic variance of CMP traits and could thus be included in genomic evaluation models to improve milk CMP in Montbéliarde cows.

Genome-Wide Association Study Identifies Genomic Loci Affecting Filet Firmness and Protein Content in Rainbow Trout

Filet quality traits determine consumer satisfaction and affect profitability of the aquaculture industry. Soft flesh is a criterion for fish filet downgrades, resulting in loss of value. Filet firmness is influenced by many factors, including rate of protein turnover. A 50K transcribed gene SNP chip was used to genotype 789 rainbow trout, from two consecutive generations, produced in the USDA/NCCCWA selective breeding program. Weighted single-step GBLUP (WssGBLUP) was used to perform genome-wide association (GWA) analyses to identify quantitative trait loci affecting filet firmness and protein content. Applying genomic sliding windows of 50 adjacent SNPs, 212 and 225 SNPs were associated with genetic variation in filet shear force and protein content, respectively. Four common SNPs in the ryanodine receptor 3 gene (RYR3) affected the aforementioned filet traits; this association suggests common mechanisms underlying filet shear force and protein content. Genes harboring SNPs were mostly involved in calcium homeostasis, proteolytic activities, transcriptional regulation, chromatin remodeling, and apoptotic processes. RYR3 harbored the highest number of SNPs (n = 32) affecting genetic variation in shear force (2.29%) and protein content (4.97%). Additionally, based on single-marker analysis, a SNP in RYR3 ranked at the top of all SNPs associated with variation in shear force. Our data suggest a role for RYR3 in muscle firmness that may be considered for genomic- and marker-assisted selection in breeding programs of rainbow trout.

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

BACKGROUND

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

RESULTS

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

CONCLUSION

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

Multitrait meta-analysis identified genomic regions associated with sexual precocity in tropical beef cattle

Multitrait meta-analyses are a strategy to produce more accurate genome-wide association studies, especially for complex phenotypes. We carried out a meta-analysis study for traits related to sexual precocity in tropical beef cattle (Nellore and Brahman) aiming to identify important genomic regions affecting these traits. The traits included in the analyses were age at first calving (AFC), early pregnancy (EP), age at first corpus luteum (AGECL), first postpartum anoestrus interval (PPAI), and scrotal circumference (SC). The traits AFC, EP, and SCN were measured in Nellore cattle, while AGECL, PPAI, and SCB were measured in Brahman cattle. Meta-analysis resulted in 108 significant single-nucleotide polymorphisms (SNPs), at an empirical threshold P-value of 1.39 × 10-5 (false discovery rate [FDR] < 0.05). Within 0.5 Mb of the significant SNP, candidate genes were annotated and analyzed for functional enrichment. Most of the closest genes to the SNP with higher significance in each chromosome have been associated with important roles in reproductive function. They are TSC22D2, KLF7, ARHGAP29, 7SK, MAP3K5, TLE3, WDR5, TAF3, TMEM68, PPP1R15B, NR2F2, GALR1, SUFU, and KCNU1. We did not observe any significant SNP in BTA5, BTA12, BTA17, BTA18, BTA19, BTA20, BTA22, BTA23, BTA25, and BTA28. Although the majority of significant SNPs are in BTA14, it was identified significant associations in multiple chromosomes (19 out of 29 autosomes), which is consistent with the postulation that reproductive traits are complex polygenic phenotypes. Five proposed association regions harbor the majority of the significant SNP (76%) and were distributed over four chromosomes (P < 1.39 × 10-5, FDR < 0.05): BTA2 (5.55%) from 95 to 96 Mb, BTA4 (5.55%) from 94.1 to 94.8 Mb, BTA14 (59.26%) from 24 to 25 Mb and 29 to 30 Mb, and BTA21 (5.55%) from 6.7 Mb to 11.4 Mb. These regions harbored key genes related to reproductive function. Moreover, these genes were enriched for functional groups associated with immune response, maternal-fetal tolerance, pregnancy maintenance, embryo development, fertility, and response to stress. Further studies including other breeds and precocity traits could confirm the importance of these regions and identify new candidate regions for sexual precocity in beef cattle.

RNA-seq of muscle from pigs divergent in feed efficiency and product quality identifies differences in immune response, growth, and macronutrient and connective tissue metabolism

BACKGROUND

Feed efficiency (FE) is an indicator of efficiency in converting energy and nutrients from feed into a tissue that is of major environmental and economic significance. The molecular mechanisms contributing to differences in FE are not fully elucidated, therefore the objective of this study was to profile the porcine Longissimus thoracis et lumborum (LTL) muscle transcriptome, examine the product quality from pigs divergent in FE and investigate the functional networks underpinning the potential relationship between product quality and FE.

RESULTS

RNA-Seq (n = 16) and product quality (n = 40) analysis were carried out in the LTL of pigs differing in FE status. A total of 272 annotated genes were differentially expressed with a P < 0.01. Functional annotation revealed a number of biological events related to immune response, growth, carbohydrate & lipid metabolism and connective tissue indicating that these might be the key mechanisms governing differences in FE. Five most significant bio-functions altered in FE groups were 'haematological system development & function', 'lymphoid tissue structure & development', 'tissue morphology', 'cellular movement' and 'immune cell trafficking'. Top significant canonical pathways represented among the differentially expressed genes included 'IL-8 signalling', 'leukocyte extravasation signalling, 'sphingosine-1-phosphate signalling', 'PKCθ signalling in T lymphocytes' and 'fMLP signalling in neutrophils'. A minor impairment in the quality of meat, in relation to texture and water-holding capacity, produced by high-FE pigs was observed. High-FE pigs also had reduced intramuscular fat content and improved nutritional profile in terms of fatty acid composition.

CONCLUSIONS

Ontology analysis revealed enhanced activity of adaptive immunity and phagocytes in high-FE pigs suggesting more efficient conserving of resources, which can be utilised for other important biological processes. Shifts in carbohydrate conversion into glucose in FE-divergent muscle may underpin the divergent evolution of pH profile in meat from the FE-groups. Moreover, altered amino acid metabolism and increased mobilisation & flux of calcium may influence growth in FE-divergent muscle. Furthermore, decreased degradation of fibroblasts in FE-divergent muscle could impact on collagen turnover and alter tenderness of meat, whilst enhanced lipid degradation in high-FE pigs may potentially underlie a more efficient fat metabolism in these animals.

A comprehensive manually-curated compendium of bovine transcription factors

Transcription factors (TFs) are pivotal regulatory proteins that control gene expression in a context-dependent and tissue-specific manner. In contrast to human, where comprehensive curated TF collections exist, bovine TFs are only rudimentary recorded and characterized. In this article, we present a manually-curated compendium of 865 sequence-specific DNA-binding bovines TFs, which we analyzed for domain family distribution, evolutionary conservation, and tissue-specific expression. In addition, we provide a list of putative transcription cofactors derived from known interactions with the identified TFs. Since there is a general lack of knowledge concerning the regulation of gene expression in cattle, the curated list of TF should provide a basis for an improved comprehension of regulatory mechanisms that are specific to the species.

Development and validation of a small SNP panel for feed efficiency in beef cattle

The objective of this study was to develop and validate a customized cost-effective single nucleotide polymorphism (SNP) panel for genetic improvement of feed efficiency in beef cattle. The SNPs identified in previous association studies and through extensive analysis of candidate genomic regions and genes, were screened for their functional impact and allele frequency in Angus and Hereford breeds used as validation candidates for the panel. Association analyses were performed on genotypes of 159 SNPs from new samples of Angus (n = 160), Hereford (n = 329), and Angus-Hereford crossbred (n = 382) cattle using allele substitution and genotypic models in ASReml. Genomic heritabilities were estimated for feed efficiency traits using the full set of SNPs, SNPs associated with at least one of the traits (at P ≤ 0.05 and P < 0.10), as well as the Illumina bovine 50K representing a widely used commercial genotyping panel. A total of 63 SNPs within 43 genes showed association (P ≤ 0.05) with at least one trait. The minor alleles of SNPs located in the GHR and CAST genes were associated with decreasing effects on residual feed intake (RFI) and/or RFI adjusted for backfat (RFIf), whereas minor alleles of SNPs within MKI67 gene were associated with increasing effects on RFI and RFIf. Additionally, the minor allele of rs137400016 SNP within CNTFR was associated with increasing average daily gain (ADG). The SNPs genotypes within UMPS, SMARCAL, CCSER1, and LMCD1 genes showed significant over-dominance effects whereas other SNPs located in SMARCAL1, ANXA2, CACNA1G, and PHYHIPL genes showed additive effects on RFI and RFIf. Gene enrichment analysis indicated that gland development, as well as ion and cation transport are important physiological mechanisms contributing to variation in feed efficiency traits. The study revealed the effect of the Jak-STAT signaling pathway on feed efficiency through the CNTFR, OSMR, and GHR genes. Genomic heritability using the 63 significant (P ≤ 0.05) SNPs was 0.09, 0.09, 0.13, 0.05, 0.05, and 0.07 for ADG, dry matter intake, midpoint metabolic weight, RFI, RFIf, and backfat, respectively. These SNPs contributed to genetic variation in the studied traits and thus can potentially be used or tested to generate cost-effective molecular breeding values for feed efficiency in beef cattle.

Genetic diversity and selection signatures of the beef 'Charolais de Cuba' breed

In this study, we used BovineSNP50 Genotyping BeadChip data to estimate the structure, putative ancestral origin as well as to identify regions with selective sweeps that may have had an important role in the adaptation to tropical conditions of the 'Charolais de Cuba' (CHCU) breed. According to a principal component analysis, CHCU samples cluster together with taurine breeds with an estimated 93% of taurus ancestral alleles. Despite the short period since importation, we detected differentiation (Fst = 0.049) between the French Charolaise (CHA) and CHCU. However, CHA breed was the closest breed to CHCU followed by other hybrids breed with a clear CHA origin. Linkage disequilibrium (r²) decay tends to be lower in CHCU compared to CHA probably due to a less intense artificial selection programs of CHCU. Signals of recent adaptation to tropical conditions between CHCU and CHA were identified. Genes mapping within those regions reflect different functions related to immunity, metabolic changes and heat tolerance (CHCU) and muscle development and meat quality (CHA) that may have had an important role in the phenotypic differentiation of these breeds. Further studies will expand our knowledge on the molecular basis of adaptation of cattle to tropical conditions and molecular process associated with meat quality traits.

The application of gene marker-assisted selection and proteomics for the best meat quality criteria and body measurements in Qinchuan cattle breed

In the past few decades, enhancement of animal productivity has been gaining increasing attention among decisions-makers, politicians, mangers, and breeders, because of the increasing of world population and shortage of natural resources. The selection of high productivity animals is the main goal, through the application of genetic improvement programs. The use of molecular genetics has conferred significant breeding advantages over conventional breeding techniques. In this regard, many economic characteristics are controlled by a small number of multiple gene loci, each of which is responsible for trait diversity and hence they are referred to as quantitative trait loci (QTL). Single-nucleotide polymorphisms (SNPs), which have recently been discovered through DNA sequencing, are considered one of the most useful types of genetic marker. SNPs are found where different nucleotides occur at the same position in the DNA sequence. They are found in both coding and noncoding regions of the genome and are present at one SNP in every 1000 b. Strategies for the identification and application of markers are based on reference to examples of loci that can control various traits. Furthermore, markers for growth, body measurements, and meat quality traits are preferred, because they can be used to predict the performance of animals, via blood samples, in the first few days of animal life. Marker-assisted selection using SNPs, such asSIRT1, SIRT2, LPL, CRTC2, SIX4, UCPs, and ZBTB38as selection criteria of body measurements and meat traits in beef cattle, will be beneficial in selection and breeding programs. The proteomic is a novel marker and a new approache of biotechnology which increases the understanding of the biological processes, besides being a remarkable biomarker that interrelated to growth and meat quality traits. Proteomics is a vigorous tool as usage for deduces molecular processes between quality traits and muscle proteins, which are helpful in analyzing the mechanisms of biochemistry that influence quality. So they could be potential biomarker for some meat quality traits. Among them, Actin, Myosin, Heat shock proteins are used a novel approaches in the field of biotechnology to understand the proteomics changes. This review article highlights the novel findings on the potential use of MAS and proteomics as biomarker for the selection for meat quality and carcass traits in Qinchuan cattle breed.

A system-based analysis of the genetic determinism of udder conformation and health phenotypes across three French dairy cattle breeds

Using GWAS to identify candidate genes associated with cattle morphology traits at a functional level is challenging. The main difficulty of identifying candidate genes and gene interactions associated with such complex traits is the long-range linkage disequilibrium (LD) phenomenon reported widely in dairy cattle. Systems biology approaches, such as combining the Association Weight Matrix (AWM) with a Partial Correlation in an Information Theory (PCIT) algorithm, can assist in overcoming this LD. Used in a multi-breed and multi-phenotype context, the AWM-PCIT could aid in identifying udder traits candidate genes and gene networks with regulatory and functional significance. This study aims to use the AWM-PCIT algorithm as a post-GWAS analysis tool with the goal of identifying candidate genes underlying udder morphology. We used data from 78,440 dairy cows from three breeds and with own phenotypes for five udder morphology traits, five production traits, somatic cell score and clinical mastitis. Cows were genotyped with medium (50k) or low-density (7 to 10k) chips and imputed to 50k. We performed a within breed and trait GWAS. The GWAS showed 9,830 significant SNP across the genome (p < 0.05). Five thousand and ten SNP did not map a gene, and 4,820 SNP were within 10-kb of a gene. After accounting for 1SNP:1gene, 3,651 SNP were within 10-kb of a gene (set1), and 2,673 significant SNP were further than 10-kb of a gene (set2). The two SNP sets formed 6,324 SNP matrix, which was fitted in an AWM-PCIT considering udder depth/ development as the key trait resulting in 1,013 genes associated with udder morphology, mastitis and production phenotypes. The AWM-PCIT detected ten potential candidate genes for udder related traits: ESR1, FGF2, FGFR2, GLI2, IQGAP3, PGR, PRLR, RREB1, BTRC, and TGFBR2.

SNP co-association and network analyses identify E2F3, KDM5A and BACH2 as key regulators of the bovine milk fatty acid profile

The fatty acid (FA) profile has a considerable impact on the nutritional and technological quality of milk and dairy products. The molecular mechanism underlying the regulation of fat metabolism in bovine mammary gland have been not completely elucidated. We conducted genome-wide association studies (GWAS) across 65 milk FAs and fat percentage in 1,152 Brown Swiss cows. In total, we identified 175 significant single nucleotide polymorphism (SNPs) spanning all chromosomes. Pathway analyses revealed that 12:0 was associated with the greatest number of overrepresented categories/pathways (e.g. mitogen-activated protein kinase (MAPK) activity and protein phosphorylation), suggesting that it might play an important biological role in controlling milk fat composition. An Associated Weight Matrix approach based on SNP co-associations predicted a network of 791 genes related to the milk FA profile, which were involved in several connected molecular pathways (e.g., MAPK, lipid metabolism and hormone signalling) and undetectable through standard GWAS. Analysis of transcription factors and their putative target genes within the network identified BACH2, E2F3 and KDM5A as key regulators of milk FA metabolism. These findings contribute to increasing knowledge of FA metabolism and mammary gland functionality in dairy cows and may be useful in developing targeted breeding practices to improve milk quality.

Network Analysis Reveals Putative Genes Affecting Meat Quality in Angus Cattle

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

Potential influence of κ-casein and β-lactoglobulin genes in genetic association studies of milk quality traits

OBJECTIVE

From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes κ-casein (CSN3) and β-lactoglobulin (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh.

METHODS

The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255).

RESULTS

Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 (6.01%±0.19% and 5.98%±0.22%), and LGB (6.02%±0.19% and 5.70%±0.22%) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, 6.04%±0.22% and 5.59%±0.31% than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, 6.05%±0.20% and 5.60%±0.19%, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh.

CONCLUSION

Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.