Novel SNPs of the bovine CACNA2D1 gene and their association with carcass and meat quality traits

Genome-Wide Association Analysis of Growth Traits in Hu Sheep

(1) Background: The Hu sheep is a renowned breed characterized by high reproduction, year-round estrus, and resistance to high humidity and temperature conditions. However, the breed exhibits lower growth rates and meat yields, which necessitate improvements through selective breeding. The integration of molecular markers in sheep breeding programs has the potential to enhance growth performance, reduce breeding cycles, and increase meat production. Currently, the applications of SNP chips for genotyping in conjunction with genome-wide association studies (GWAS) have become a prevalent approach for identifying candidate genes associated with economically significant traits in livestock. (2) Methods: To pinpoint candidate genes influencing growth traits in Hu sheep, we recorded the birth weight, weaning weight, and weights at 3, 4, 5, 6, and 7 months for a total of 567 Hu sheep, and genotyping was performed using the Ovine 40K SNP chip. (3) Results: Through GWAS analysis and KEGG pathway enrichment, we identified three candidate genes associated with birth weight (CAMK2B, CACNA2D1, and CACNA1C). Additionally, we found two candidate genes linked to weaning weight (FGF9 and BMPR1B), with CACNA2D1 also serving as a shared gene between birth weight and weaning weight traits. Furthermore, we identified eight candidate genes related to monthly weight (FIGF, WT1, KCNIP4, JAK2, WWP1, PLCL1, GPRIN3, and CCSER1). (4) Conclusion: Our findings revealed a total of 13 candidate genetic markers that can be utilized for molecular marker-assisted selection, aiming to improve meat production in sheep breeding programs.

Genome-Wide Detection of Copy Number Variations and Their Potential Association with Carcass and Meat Quality Traits in Pingliang Red Cattle

Copy number variation (CNV) serves as a significant source of genetic diversity in mammals and exerts substantial effects on various complex traits. Pingliang red cattle, an outstanding indigenous resource in China, possess remarkable breeding value attributed to their tender meat and superior marbling quality. However, the genetic mechanisms influencing carcass and meat quality traits in Pingliang red cattle are not well understood. We generated a comprehensive genome-wide CNV map for Pingliang red cattle using the GGP Bovine 100K SNP chip. A total of 755 copy number variable regions (CNVRs) spanning 81.03 Mb were identified, accounting for approximately 3.24% of the bovine autosomal genome. Among these, we discovered 270 potentially breed-specific CNVRs in Pingliang red cattle, including 143 gains, 73 losses, and 54 mixed events. Functional annotation analysis revealed significant associations between these specific CNVRs and important traits such as carcass and meat quality, reproduction, exterior traits, growth traits, and health traits. Additionally, our network and transcriptome analysis highlighted CACNA2D1, CYLD, UBXN2B, TG, NADK, and ITGA9 as promising candidate genes associated with carcass weight and intramuscular fat deposition. The current study presents a genome-wide CNV map in Pingliang red cattle, highlighting breed-specific CNVRs, and transcriptome findings provide valuable insights into the underlying genetic characteristics of Pingliang red cattle. These results offer potential avenues for enhancing meat quality through a targeted breeding program.

Distribution of Runs of Homozygosity and Their Relationship with Candidate Genes for Productivity in Kazakh Meat-Wool Sheep Breed

Increasing the fertility of sheep remains one of the crucial issues of modern sheep breeding. The Kazakh meat-wool sheep is an excellent breed with high meat and wool productivity and well adapted to harsh conditions. Nowadays, runs of homozygosity (ROHs) are considered a suitable approach for studying the genetic characteristics of farm animals. The aims of the study were to analyze the distribution of ROHs, describe autozygosity, and detect genomic regions with high ROH islands. In this study, we genotyped a total of 281 Kazakh meat-wool sheep using the Illumina iScan® system (EquipNet, Canton, MA, USA) via Ovine SNP50 BeadChip array. As a results, a total of 15,069 ROHs were found in the three Kazakh meat-wool sheep populations. The mean number of ROH per animal across populations varied from 40.3 (POP1) to 42.2 (POP2) in the category 1+ Mb. Furthermore, the number of ROH per animal in ROH1-2 Mb were much higher than ROH2-4 Mb and ROH8-16 Mb in the three sheep populations. Most of individuals had small number of ROH>16 Mb. The highest and lowest genomic inbreeding coefficient values were observed in POP2 and POP3, respectively. The estimated FROH presented the impact that recent inbreeding has had in all sheep populations. Furthermore, a set of interesting candidate genes (BMP2, BMPR2, BMPRIB, CLOCK, KDM2B, TIAM1, TASP1, MYBPC1, MYOM1, and CACNA2D1), which are related to the productive traits, were found. Collectively, these findings will contribute to the breeding and conservation strategies of the Kazakh meat-wool sheep breed.

Genome-wide association study for growth traits in Blanco Orejinegro and Romosinuano cattle

Growth traits are economically important characteristics for the genetic improvement of local cattle breeds. Genome-wide association studies (GWAS) provide valuable information to enhance the understanding on the genetics of complex traits. The aim of this study was to perform a GWAS to identify genomic regions and genes associated to birth weight, weaning weight adjusted for 240 days, 16 months, and 24 months weight in Romosinuano (ROMO) and Blanco Orejinegro (BON) cattle. A single-step genomic-BLUP was implemented using 596 BON and 569 ROMO individuals that were genotyped with an Illumina BovineSNP50 BeadChip. There were 25 regions of interest identified on different chromosomes, with few of them simultaneously associated with two or more growth traits and some were common to both breeds. The gene mapping allowed to find 173 annotations on these regions, from which 49 represent potential candidate genes with known growth-related functions in cattle and other species. Among the regions that were associated with several growth traits, that at 24 - 27 MB of BTA14, has important candidate genes such as LYPLA1, XKR4, TMEM68 and PLAG1. Another region of interest at 0.40-0.77 Mb of BTA23 was identified in both breeds, containing KHDRBS2 as a potential candidate gene influencing body weight. Future studies targeting these regions could provide more knowledge to uncover the genetic architecture underlying growth traits in BON and ROMO cattle. The genomic regions and genes identified in this study could be used to improve the prediction of genetic merit for growth traits in these creole cattle breeds.

Molecular mechanisms contributing to the development of beef sensory texture and flavour traits and related biomarkers: Insights from early post-mortem muscle using label-free proteomics

Beef sensory quality comprises a suite of traits, each of which manifests its ultimate phenotype through interaction of muscle physiology with environment, both in vivo and post-mortem. Understanding variability in meat quality remains a persistent challenge, but omics studies to uncover biological connections between natural variability in proteome and phenotype could provide validation for exploratory studies and offer new insights. Multivariate analysis of proteome and meat quality data from Longissimus thoracis et lumborum muscle samples taken early post-mortem from 34 Limousin-sired bulls was conducted. Using for the first-time label-free shotgun proteomics combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS), 85 proteins were found to be related with tenderness, chewiness, stringiness and flavour sensory traits. The putative biomarkers were classified in five interconnected biological pathways; i) muscle contraction, ii) energy metabolism, iii) heat shock proteins, iv) oxidative stress, v) regulation of cellular processes and binding. Among the proteins, PHKA1 and STBD1 correlated with all four traits, as did the GO biological process 'generation of precursor metabolites and energy'. Optimal regression models explained a high level (58-71%) of phenotypic variability with proteomic data for each quality trait. The results of this study propose several regression equations and biomarkers to explain the variability of multiple beef eating quality traits. Thanks to annotation and network analyses, they further suggest protein interactions and mechanisms underpinning the physiological processes regulating these key quality traits. SIGNIFICANCE: The proteomic profiles of animals with divergent quality profiles have been compared in numerous studies; however, a wide range of phenotypic variation is required to better understand the mechanisms underpinning the complex biological pathways correlated with beef quality and protein interactions. We used multivariate regression analyses and bioinformatics to analyse shotgun proteomics data to decipher the molecular signatures involved in beef texture and flavour variations with a focus on multiple quality traits. We developed multiple regression equations to explain beef texture and flavour. Additionally, potential candidate biomarkers correlated with multiple beef quality traits are suggested, which could have utility as indicators of beef overall sensory quality. This study explained the biological process responsible for determining key quality traits such as tenderness, chewiness, stringiness, and flavour in beef, which will provide support for future beef proteomics studies.

Assessing Population Structure and Signatures of Selection in Wanbei Pigs Using Whole Genome Resequencing Data

Wanbei pig (WBP) is one of the indigenous pig resources in China and has many germplasm characteristics. However, research on its genome is lacking. To assess the genomic variation, population structure, and selection signatures, we resequenced 18 WBP for the first time and performed a comprehensive analysis with resequenced data of 10 Asian wild boars. In total, 590.03 Gb of data and approximately 41 million variants were obtained. Polymorphism level (θπ) ratio and genetic differentiation (fixation index)-based cross approaches were applied, and 539 regions, which harbored 176 genes, were selected. Functional analysis of the selected genes revealed that they were associated with lipid metabolism (SCP2, APOA1, APOA4, APOC3, CD36, BCL6, ADCY8), backfat thickness (PLAG1, CACNA2D1), muscle (MYOG), and reproduction (CABS1). Overall, our results provide a valuable resource for characterizing the uniqueness of WBP and a basis for future breeding.

Genome-Wide Identification of RNA Editing Sites Affecting Muscle Development in Yak

Skeletal muscle growth and development is a complicated process that is regulated at multiple steps and by numerous myogenesis genes. RNA editing represents one of the events at the post-transcriptional level, which contributes to the diversity of transcriptome and proteome by altering the nucleotides of RNAs. However, RNA editing events in the skeletal muscle of yaks are still not well defined. This study conducted whole-genome RNA-editing identification in skeletal muscle of yaks at embryonic stage (ES) and adult stage (AS). We found a total of 11,168 unique RNA editing sites, most of which were detected in the intergenic region. After annotation, we totally identified 2,718 editing sites within coding regions, among which 858 were missense changes. Moreover, totally 322 editing sites in the 3′ untranslated regions (UTR) were also predicted to alter the set of miRNA target sites, indicating that RNA editing may be involved in translational repression or mRNA degradation. We found 838 RNA editing sites (involving 244 common genes) that are edited differentially in ES as compared to AS. According to the KEGG enrichment analysis, these differentially edited genes were mainly involved in pathways highly related to skeletal muscle development and myogenesis, including MAPK, AMPK, Wnt, and PI3K-Akt signaling pathways. Altogether, our work presents the first characterization of RNA editing sites within yak skeletal muscles on a genome-wide scale and enhances our understanding of the mechanism of skeletal muscle development and myogenesis.

New insights into genetics underlying of plumage color

Plumage color can be considered as a social signal in chickens and a breeding identification tool among breeders. The relationship between plumage color and trait groups of immunity, growth and fertility is still a controversial issue. This research aimed to determine the genome-wide additive and epistatic variants affecting plumage color variation in chickens using the chicken Illumina 60k high-density SNP array. Two scenarios of genome-wide additive association studies using all SNPs and independent SNPs were carried out. To perform epistatic association analysis, the LD pruning approach was used to reduce the complexity of the analysis. We detected seven novel significant loci using all of the SNPs in the model and 14 SNPs using the LD pruning approach associated with plumage color. Moreover, 89 significantly associated SNP-SNP interactions (P-value <10^-6 ) distributed in 25 chromosomes were identified, indicating that all of the signals together putatively influence the quantitative variation of plumage color. By annotating genes relevant to top SNPs, we have distinguished 18 potential candidate genes comprising HNF4beta, CKMT1B, TBC1D22A, RPL8, CACNA2D1, FZD4, SGMS1, IRF8, OPTN, LOC420362, TRABD, OvoDA1, DAD1, USP6, RBM12B, MIR1772, MIR1709 and MIR6696 and also 89 putative gene-gene combinations responsible for plumage color variation in chickens. Furthermore, several KEGG pathways including metabolic pathway, cytokine-cytokine receptor interaction, focal adhesion, melanogenesis, glycosaminoglycan biosynthesis-keratan sulfate and sphingolipid metabolism were enriched in the gene-set analysis. The results indicated that plumage color is a highly polygenic trait which, in turn, can be affected by multiple coding genes, regulatory genes and gene-gene epistasis interactions. In addition to genes with additive effects, epistatic genes with tiny individual effect sizes but significant effects in a pair have the potential to control plumage coloration in chickens.

Transcriptomic diversity in longissimus thoracis muscles of Barbari and Changthangi goat breeds of India

The present study is an attempt to examine the differential expression of genes in longissimus thoracis muscles between meat and wool type Indian goat breeds. Barbari goat is considered the best meat breed while Changthangi is famous for its fine fibre quality. RNA sequencing data was generated from four biological replicates of longissimus thoracis muscles of Barbari and Changthangi goats. A clear demarcation could be observed between the breeds in terms of expression of genes associated with lipid metabolism (FASN, SCD, THRSP, DGAT2 and FABP3). Most significant genes with high connectivity identified by gene co-expression network analysis were associated with triacylglycerol biosynthesis pathway in Barbari goat. Highly interactive genes identified in Changthangi goat were mainly associated with muscle fibre type. This study provides an insight into the differential expression of genes in longissimus thoracis muscles between Barbari and Changthangi goats that are adapted to and reared in different agro-climatic regions.

Genomic scans for selection signatures revealed candidate genes for adaptation and production traits in a variety of cattle breeds

Domestication and selection are the major driving forces responsible for the determinative genetic variability in livestock. These selection patterns create unique genetic signatures within the genome. BovineSNP50 chip data from 236 animals (seven indicine and five taurine cattle breeds) were analyzed in the present study. We implemented three complementary approaches viz. iHS (Integrated haplotype score), ROH (Runs of homozygosity), and F_ST, to detect selection signatures. A total of 179, 56, and 231 regions revealed 518, 277, and 267 candidate genes identified by iHS, ROH, and F_ST methods, respectively. We found several candidate genes (e.g., NCR3, ARID5A, HIST1H2BN, DEFB4, DEFB7, HSPA1L, HSPA1B, and DNAJB4) related to production traits and the adaptation of indigenous breeds to local environmental constraints such as heat stress and disease susceptibility. However, further studies are warranted to refine the findings using a larger sample size, whole-genome sequencing, and/or high density genotyping.

The Genomic Variation in the Aosta Cattle Breeds Raised in an Extensive Alpine Farming System

The Aosta Red Pied (Valdostana Pezzata Rossa (VRP)), the Aosta Black Pied (Valdostana Pezzata Nera (VBP)) and the Aosta Chestnut (Valdostana Castana (CAS)) are dual-purpose cattle breeds (meat and milk), very well adapted to the harsh environmental conditions of alpine territories: their farming is in fact characterized by summer pasture at very high altitude. A total of 728 individuals were genotyped with the GeenSeek Genomic Profiler® (GGP) Bovine 150K Illumina SNP chip as a part of the DUALBREEDING-PSRN Italian-funded research project. The genetic diversity among populations showed that the three breeds are distinct populations based on the F_ST values, ADMIXTURE and Principal Component Analysis (PCA) results. Runs of Homozygosity (ROH) were obtained for the three populations to disclose recent autozygosity. The genomic inbreeding based on the ROH was calculated and coupled with information derived from the F (inbreeding coefficient) and F_ST parameters. The mean F_ROH values were low: CAS = 0.06, VBP = 0.05 and VRP = 0.07, while the average F values were -0.003, -0.01 and -0.003, respectively. The annotation and enrichment analysis, performed in the identified most frequent ROH (TOP_ROH), showed genes that can be linked to the resilience capacity of these populations to harsh environmental farming conditions, and to the peculiar characteristics searched for by farmers in each breed.

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

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

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

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

Systems genetics identifies a role for Cacna2d1 regulation in elevated intraocular pressure and glaucoma susceptibility

Glaucoma is a multi-factorial blinding disease in which genetic factors play an important role. Elevated intraocular pressure is a highly heritable risk factor for primary open angle glaucoma and currently the only target for glaucoma therapy. Our study helps to better understand underlying genetic and molecular mechanisms that regulate intraocular pressure, and identifies a new candidate gene, Cacna2d1, that modulates intraocular pressure and a promising therapeutic, pregabalin, which binds to CACNA2D1 protein and lowers intraocular pressure significantly. Because our study utilizes a genetically diverse population of mice with known sequence variants, we are able to determine that the intraocular pressure-lowering effect of pregabalin is dependent on the Cacna2d1 haplotype. Using human genome-wide association study (GWAS) data, evidence for association of a CACNA2D1 single-nucleotide polymorphism and primary open angle glaucoma is found. Importantly, these results demonstrate that our systems genetics approach represents an efficient method to identify genetic variation that can guide the selection of therapeutic targets.

Elevated intraocular pressure (IOP) is a heritable risk factor for primary open angle glaucoma. Using forward mouse genetics, cell biology, pharmacology and human genetic data, the authors identify CACNA2D1 as an IOP risk gene that can be therapeutically targeted by the drug pregabalin in animal models.

Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

BACKGROUND

Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model.

METHODS

We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms.

RESULTS

WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection of differentially connected genes identified various genes previously identified to be associated with obesity in humans and rodents, e.g. CSF1R and MARC2.

CONCLUSIONS

To our knowledge, this is the first study to apply systems biology approaches using porcine adipose tissue RNA-Sequencing data in a genetically characterized porcine model for obesity. We revealed complex networks, pathways, candidate and regulatory genes related to obesity, confirming the complexity of obesity and its association with immune-related disorders and osteoporosis.

[Artificial selection for cattle based on high-density SNP markers]

With the implementation of genetic improvement in recent years, artificial selection has greatly improved beef cattle production performance and its genetic basis has been dramatically changed. In this study, based on the Illumina BovineSNP50 (54K) and BovineHD (770K) BeadChip and the FST value, we analyzed the genetic differentiation of cattle and screened the imprints of selection in bovine genome. Finally, we found 47104 OUTLIER SNP loci and 3064 candidate genes, for example, CLIC5, TG, CACNA2D1, and FSHR etc. The biological processes and molecular functions of genes were analyzed through gene annotation.The results of this study established a genome-wide map of selection footprints in beef cattle genome and a clue for in-depth study of artificial selection and understanding of biological evolution.Our results indicate that artificial selection has played an important role in cattle breed genetic improvement.

Single nucleotide polymorphism of CACNA2D1 gene and its association with milk somatic cell score in cattle

The objective of the present study was to identify polymorphisms of the CACNA2D1 gene, and to analyze associations between these polymorphisms and mastitis in several cattle breeds. Through PCR-RFLP methods and DNA sequencing, an allelic variant corresponding to the A→G mutations and Aspartic (Asp) to Glycine (Gly) amino acid replacement at positions 526745 in the exon 25 of bovine CACNA2D1 gene could be detected. Two alleles, A and G, and three genotypes, AA, AG and GG were defined. Genetic character in the studied populations indicated that the A526745G loci of CACNA2D1 gene was moderate polymorphism and fitted with Hardy-Weinberg equilibrium (P > 0.05). The effects of CACNA2D1 polymorphisms on somatic cell score (SCS) were analyzed and significant association was found between A526745G and SCS. The mean of genotype GG was significantly lower than those of genotype AG and AA (P = 0.0469). Information provided in this research could be useful in further studies to determine the role of CACNA2D1 gene in the mastitis resistance.