Novel putative causal mutations associated with fat traits in Nellore cattle uncovered by eQTLs located in open chromatin regions.

Intramuscular fat (IMF) and backfat thickness (BFT) are critical economic traits impacting meat quality. However, the genetic variants controlling these traits need to be better understood. To advance knowledge in this area, we integrated RNA-seq and single nucleotide polymorphisms (SNPs) identified in genomic and transcriptomic data to generate a linkage disequilibrium filtered panel of 553,581 variants. Expression quantitative trait loci (eQTL) analysis revealed 36,916 cis-eQTLs and 14,408 trans-eQTLs. Association analysis resulted in three eQTLs associated with BFT and 24 with IMF. Functional enrichment analysis of genes regulated by these 27 eQTLs revealed noteworthy pathways that can play a fundamental role in lipid metabolism and fat deposition, such as immune response, cytoskeleton remodeling, iron transport, and phospholipid metabolism. We next used ATAC-Seq assay to identify and overlap eQTL and open chromatin regions. Six eQTLs were in regulatory regions, four in predicted insulators and possible CCCTC-binding factor DNA binding sites, one in an active enhancer region, and the last in a low signal region. Our results provided novel insights into the transcriptional regulation of IMF and BFT, unraveling putative regulatory variants.

Epidemiology of the SARS-CoV-2 Omicron Variant Emergence in the Southeast Brazilian Population.

The aim of this study was to describe epidemiological characteristics and perform SARS-CoV-2 genomic surveillance in the southeastern region of São Paulo State. During the first months of 2022, we compared weekly SARS-CoV-2 infection prevalence considering age, Ct value, and variants' lineages. An increase in the number of SARS-CoV-2-positive cases until the fourth epidemiological week of 2022 was observed. From the fourth epidemiological week onwards, the number of tests for SARS-CoV-2 diagnosis began to decrease, but the number of positive samples for SARS-CoV-2 remained high, reaching its most expressive level with a rate of 60% of infected individual cases. In this period, we observed a progressive increase in SARS-CoV-2 infection within the 0-10 age group throughout the epidemiological weeks, from 2.8% in the first epidemiological week to 9.2% in the eighth epidemiological week of 2022. We further observed significantly higher Ct values within younger patient samples compared to other older age groups. According to lineage assignment, SARS-CoV-2 (BA.1) was the most prevalent (74.5%) in the younger group, followed by BA.1.1 (23%), BA.2 (1.7%), and Delta (1%). Phylogenetic analysis showed that BA.2 sequences clustered together, indicating sustained transmission of this Omicron VOC sub-lineage by that time. Our results suggest the initial dissemination steps of the Omicron's sub-linage BA.2 into the younger group, due to specific genomic features of the detected sequences. These data provide interesting results related to the spread, emergence, and evolution of the Omicron variant in the southeast Brazilian population.

Phenotypic divergence between broiler and layer chicken lines is regulated at the molecular level during development.

BACKGROUND: Understanding the molecular underpinnings of phenotypic variations is critical for enhancing poultry breeding programs. The Brazilian broiler (TT) and laying hen (CC) lines exhibit striking differences in body weight, growth potential, and muscle mass. Our work aimed to compare the global transcriptome of wing and pectoral tissues during the early development (days 2.5 to 3.5) of these chicken lines, unveiling disparities in gene expression and regulation. RESULTS: Different and bona-fide transcriptomic profiles were identified for the compared lines. A similar number of up- and downregulated differentially expressed genes (DEGs) were identified, considering the broiler line as a reference. Upregulated DEGs displayed an enrichment of protease-encoding genes, whereas downregulated DEGs exhibited a prevalence of receptors and ligands. Gene Ontology analysis revealed that upregulated DEGs were mainly associated with hormone response, mitotic cell cycle, and different metabolic and biosynthetic processes. In contrast, downregulated DEGs were primarily linked to communication, signal transduction, cell differentiation, and nervous system development. Regulatory networks were constructed for the mitotic cell cycle and cell differentiation biological processes, as their contrasting roles may impact the development of distinct postnatal traits. Within the mitotic cell cycle network, key upregulated DEGs included CCND1 and HSP90, with central regulators being NF-κB subunits (RELA and REL) and NFATC2. The cell differentiation network comprises numerous DEGs encoding transcription factors (e.g., HOX genes), receptors, ligands, and histones, while the main regulatory hubs are CREB, AR and epigenetic modifiers. Clustering analyses highlighted PIK3CD as a central player within the differentiation network. CONCLUSIONS: Our study revealed distinct developmental transcriptomes between Brazilian broiler and layer lines. The gene expression profile of broiler embryos seems to favour increased cell proliferation and delayed differentiation, which may contribute to the subsequent enlargement of pectoral tissues during foetal and postnatal development. Our findings pave the way for future functional studies and improvement of targeted traits of economic interest in poultry.

Identification of eQTLs using different sets of single nucleotide polymorphisms associated with carcass and body composition traits in pigs.

BACKGROUND: Mapping expression quantitative trait loci (eQTLs) in skeletal muscle tissue in pigs is crucial for understanding the relationship between genetic variation and phenotypic expression of carcass traits in meat animals. Therefore, the primary objective of this study was to evaluate the impact of different sets of single nucleotide polymorphisms (SNP), including scenarios removing SNPs pruned for linkage disequilibrium (LD) and SNPs derived from SNP chip arrays and RNA-seq data from liver, brain, and skeletal muscle tissues, on the identification of eQTLs in the Longissimus lumborum tissue, associated with carcass and body composition traits in Large White pigs. The SNPs identified from muscle mRNA were combined with SNPs identified in the brain and liver tissue transcriptomes, as well as SNPs from the GGP Porcine 50 K SNP chip array. Cis- and trans-eQTLs were identified based on the skeletal muscle gene expression level, followed by functional genomic analyses and statistical associations with carcass and body composition traits in Large White pigs. RESULTS: The number of cis- and trans-eQTLs identified across different sets of SNPs (scenarios) ranged from 261 to 2,539 and from 29 to 13,721, respectively. Furthermore, 6,180 genes were modulated by eQTLs in at least one of the scenarios evaluated. The eQTLs identified were not significantly associated with carcass and body composition traits but were significantly enriched for many traits in the "Meat and Carcass" type QTL. The scenarios with the highest number of cis- (n = 304) and trans- (n = 5,993) modulated genes were the unpruned and LD-pruned SNP set scenarios identified from the muscle transcriptome. These genes include 84 transcription factor coding genes. CONCLUSIONS: After LD pruning, the set of SNPs identified based on the transcriptome of the skeletal muscle tissue of pigs resulted in the highest number of genes modulated by eQTLs. Most eQTLs are of the trans type and are associated with genes influencing complex traits in pigs, such as transcription factors and enhancers. Furthermore, the incorporation of SNPs from other genomic regions to the set of SNPs identified in the porcine skeletal muscle transcriptome contributed to the identification of eQTLs that had not been identified based on the porcine skeletal muscle transcriptome alone.

Skin transcriptomic analysis reveals candidate genes and pathways associated with thermotolerance in hair sheep.

The skin plays an important role in thermoregulation. Identification of genes on the skin that contribute to increased heat tolerance can be used to select animals with the best performance in warm environments. Our objective was to identify candidate genes associated with the heat stress response in the skin of Santa Ines sheep. A group of 80 sheep assessed for thermotolerance was kept in a climatic chamber for 8 days at a stress level temperature of 36 °C (10 am to 04 pm) and a maintenance temperature of 28 °C (04 pm to 10 am). Two divergent groups, with seven animals each, were formed after ranking them by thermotolerance using rectal temperature. From skin biopsy samples, total RNA was extracted, quantified, and used for RNA-seq analysis. 15,989 genes were expressed in sheep skin samples, of which 4 genes were differentially expressed (DE; FDR < 0.05) and 11 DE (FDR 0.05-0.177) between the two divergent groups. These genes are involved in cellular protection against stress (HSPA1A and HSPA6), ribosome assembly (28S, 18S, and 5S ribosomal RNA), and immune response (IGHG4, GNLY, CXCL1, CAPN14, and SAA-4). The candidate genes and main pathways related to heat tolerance in Santa Ines sheep require further investigation to understand their response to heat stress in different climatic conditions and under solar radiation. It is essential to verify whether these genes and pathways are present in different breeds and to understand the relationship between heat stress and other genes identified in this study.

Ruminal and feces metabolites associated with feed efficiency, water intake and methane emission in Nelore bulls.

The objectives of this study were twofold: (1) to identify potential differences in the ruminal and fecal metabolite profiles of Nelore bulls under different nutritional interventions; and (2) to identify metabolites associated with cattle sustainability related-traits. We used different nutritional interventions in the feedlot: conventional (Conv; n = 26), and by-product (ByPr, n = 26). Thirty-eight ruminal fluid and 27 fecal metabolites were significantly different (P < 0.05) between the ByPr and Conv groups. Individual dry matter intake (DMI), residual feed intake (RFI), observed water intake (OWI), predicted water intake (WI), and residual water intake (RWI) phenotypes were lower (P < 0.05) in the Conv group, while the ByPr group exhibited lower methane emission (ME) (P < 0.05). Ruminal fluid dimethylamine was significantly associated (P < 0.05) with DMI, RFI, FE (feed efficiency), OWI and WI. Aspartate was associated (P < 0.05) with DMI, RFI, FE and WI. Fecal C22:1n9 was significantly associated with OWI and RWI (P < 0.05). Fatty acid C14:0 and hypoxanthine were significantly associated with DMI and RFI (P < 0.05). The results demonstrated that different nutritional interventions alter ruminal and fecal metabolites and provided new insights into the relationship of these metabolites with feed efficiency and water intake traits in Nelore bulls.

Genetic parameters for production, quality, and colors from eggs in Brazilian lineages of chickens.

Genetic parameters were estimated for egg production, egg quality, and eggshell colors in eight lineages of Brazilian laying hens. Age at first egg (AFE), total egg production up to the 45th week (PROD), egg weight (EW), albumen height (AH), yolk color (YC), the Haugh units (HU), eggshell strength (ESS), eggshell thickness (EST), yolk weight (YW), eggshell weight (ESW), and eggshell color (L*, a*, and b*) were measured in 2030 eggs obtained from 645 laying hens. Variance components were estimated from a mixed animal model, which included the fixed effects of contemporary groups, cage location, and hen line, and the additive genetic, permanent environmental, and residual as random effects. In general, heritabilities were low to moderate (h2 = 0.11 to 0.48). Genetic correlations among eggshell quality traits were moderate to high (0.36 and 0.69). High genetic correlations were obtained between the eggshell color traits [rg = -0.90 (L* and a*); rg = -0.64 (L* and b*); and rg = 0.65 (a* and b*)]. Results suggest that EW is strongly correlated with ESW, but the genetic correlations between EW and ESS and between EW and EST were low. Genetic correlations between L* and eggshell quality traits were low to moderate, suggesting that L* has little or no relation with external egg quality. However, genetic correlations between a* and b* values and eggshell quality traits were high. The genetic correlations between eggshell color and eggshell quality traits were low, suggesting that the eggshell color does not influence external egg quality. Genetic correlations between PROD and egg quality traits were negative and varied between -0.42 and -0.05. This antagonistic relationship emphasizes the importance of adopting breeding schemes that allow the simultaneous genetic progress of these traits by considering their genetic correlation and economic relevance, such as the selection index.

Transcriptome profile of skeletal muscle using different sources of dietary fatty acids in male pigs.

Pork is of great importance in world trade and represents the largest source of fatty acids in the human diet. Lipid sources such as soybean oil (SOY), canola (CO), and fish oil (FO) are used in pig diets and influence blood parameters and the ratio of deposited fatty acids. In this study, the main objective was to evaluate changes in gene expression in porcine skeletal muscle tissue resulting from the dietary oil sources and to identify metabolic pathways and biological process networks through RNA-Seq. The addition of FO in the diet of pigs led to intramuscular lipid with a higher FA profile composition of C20:5 n-3, C22:6 n-3, and SFA (C16:0 and C18:0). Blood parameters for the FO group showed lower cholesterol and HDL content compared with CO and SOY groups. Skeletal muscle transcriptome analyses revealed 65 differentially expressed genes (DEG, FDR 10%) between CO vs SOY, and 32 DEG for CO vs FO, and 531 DEG for SOY vs FO comparison. Several genes, including AZGP1, PDE3B, APOE, PLIN1, and LIPS, were found to be down-regulated in the diet of the SOY group compared to the FO group. The enrichment analysis revealed DEG involved in lipid metabolism, metabolic diseases, and inflammation between the oil groups, with specific gene functions in each group and altered blood parameters. The results provide mechanisms to help us understand the behavior of genes according to fatty acids.

Brain fatty acid and transcriptome profiles of pig fed diets with different levels of soybean oil.

BACKGROUND: The high similarity in anatomical and neurophysiological processes between pigs and humans make pigs an excellent model for metabolic diseases and neurological disorders. Lipids are essential for brain structure and function, and the polyunsaturated fatty acids (PUFA) have anti-inflammatory and positive effects against cognitive dysfunction in neurodegenerative diseases. Nutrigenomics studies involving pigs and fatty acids (FA) may help us in better understanding important biological processes. In this study, the main goal was to evaluate the effect of different levels of dietary soybean oil on the lipid profile and transcriptome in pigs' brain tissue. RESULTS: Thirty-six male Large White pigs were used in a 98-day study using two experimental diets corn-soybean meal diet containing 1.5% soybean oil (SOY1.5) and corn-soybean meal diet containing 3.0% soybean oil (SOY3.0). No differences were found for the brain total lipid content and FA profile between the different levels of soybean oil. For differential expression analysis, using the DESeq2 statistical package, a total of 34 differentially expressed genes (DEG, FDR-corrected p-value < 0.05) were identified. Of these 34 DEG, 25 are known-genes, of which 11 were up-regulated (log2 fold change ranging from + 0.25 to + 2.93) and 14 were down-regulated (log2 fold change ranging from - 3.43 to -0.36) for the SOY1.5 group compared to SOY3.0. For the functional enrichment analysis performed using MetaCore with the 34 DEG, four pathway maps were identified (p-value < 0.05), related to the ALOX15B (log2 fold change - 1.489), CALB1 (log2 fold change - 3.431) and CAST (log2 fold change + 0.421) genes. A "calcium transport" network (p-value = 2.303e-2), related to the CAST and CALB1 genes, was also identified. CONCLUSION: The results found in this study contribute to understanding the pathways and networks associated with processes involved in intracellular calcium, lipid metabolism, and oxidative processes in the brain tissue. Moreover, these results may help a better comprehension of the modulating effects of soybean oil and its FA composition on processes and diseases affecting the brain tissue.

Retrospective Insights of the COVID-19 Epidemic in the Major Latin American City, São Paulo, Southeastern Brazil.

São Paulo is the financial center of Brazil, with a population of over 12 million, that receives travelers from all over the world for business and tourism. It was the first city in Brazil to report a case of COVID-19 that rapidly spread across the city despite the implementation of the restriction measures. Despite many reports, much is still unknown regarding the genomic diversity and transmission dynamics of this virus in the city of São Paulo. Thus, in this study, we provide a retrospective overview of the COVID-19 epidemic in São Paulo City, Southeastern, Brazil, by generating a total of 9995 near-complete genome sequences from all the city's different macro-regions (North, West, Central, East, South, and Southeast). Our analysis revealed that multiple independent introduction events of different variants (mainly Gamma, Delta, and Omicron) occurred throughout time. Additionally, our estimates of viral movement within the different macro-regions further suggested that the East and the Southeast regions were the largest contributors to the Gamma and Delta viral exchanges to other regions. Meanwhile, the North region had a higher contribution to the dispersion of the Omicron variant. Together, our results reinforce the importance of increasing SARS-CoV-2 genomic monitoring within the city and the country to track the real-time evolution of the virus and to detect earlier any eventual emergency of new variants of concern that could undermine the fight against COVID-19 in Brazil and worldwide.

RNA-seq transcriptome profiling of pigs' liver in response to diet with different sources of fatty acids.

Pigs (Sus scrofa) are an animal model for metabolic diseases in humans. Pork is an important source of fatty acids (FAs) in the human diet, as it is one of the most consumed meats worldwide. The effects of dietary inclusion of oils such as canola, fish, and soybean oils on pig gene expression are mostly unknown. Our objective was to evaluate FA composition, identify changes in gene expression in the liver of male pigs fed diets enriched with different FA profiles, and identify impacted metabolic pathways and gene networks to enlighten the biological mechanisms' variation. Large White male pigs were randomly allocated to one of three diets with 18 pigs in each; all diets comprised a base of corn and soybean meal to which either 3% of soybean oil (SOY), 3% canola oil (CO), or 3% fish oil (FO) was added for a 98-day trial during the growing and finishing phases. RNA sequencing was performed on the liver samples of each animal by Illumina technology for differential gene expression analyses, using the R package DESeq2. The diets modified the FA profile, mainly in relation to polyunsaturated and saturated FAs. Comparing SOY vs. FO, 143 differentially expressed genes (DEGs) were identified as being associated with metabolism, metabolic and neurodegenerative disease pathways, inflammatory processes, and immune response networks. Comparing CO vs. SOY, 148 DEGs were identified, with pathways related to FA oxidation, regulation of lipid metabolism, and metabolic and neurodegenerative diseases. Our results help explain the behavior of genes with differential expression in metabolic pathways resulting from feeding different types of oils in pig diets.

Repressive epigenetic mechanisms, such as the H3K27me3 histone modification, were predicted to affect muscle gene expression and its mineral content in Nelore cattle.

Epigenetic repression has been linked to the regulation of different cell states. In this study, we focus on the influence of this repression, mainly by H3K27me3, over gene expression in muscle cells, which may affect mineral content, a phenotype that is relevant to muscle function and beef quality. Based on the inverse relationship between H3K27me3 and gene expression (i.e., epigenetic repression) and on contrasting sample groups, we computationally predicted regulatory genes that affect muscle mineral content. To this end, we applied the TRIAGE predictive method followed by a rank product analysis. This methodology can predict regulatory genes that might be affected by repressive epigenetic regulation related to mineral concentration. Annotation of orthologous genes, between human and bovine, enabled our investigation of gene expression in the Longissimus thoracis muscle of Bos indicus cattle. The animals under study had a contrasting mineral content in their muscle cells. We identified candidate regulatory genes influenced by repressive epigenetic mechanisms, linking histone modification to mineral content in beef samples. The discovered candidate genes take part in multiple biological pathways, i.e., impulse transmission, cell signalling, immunological, and developmental pathways. Some of these genes were previously associated with mineral content or regulatory mechanisms. Our findings indicate that epigenetic repression can partially explain the gene expression profiles observed in muscle samples with contrasting mineral content through the candidate regulators here identified.

A traveling SARS-CoV-2 laboratory as part of a pandemic response among vulnerable Brazilian populations.

BACKGROUND: Brazil has been dramatically hit by the SARS-CoV-2 pandemic and is a world leader in COVID-19 morbidity and mortality. Additionally, the largest country of Latin America has been a continuous source of SARS-CoV-2 variants and shows extraordinary variability of the pandemic strains probably related to the country´s outstanding position as a Latin American economical and transportation hub. Not all regions of the country show sufficient infrastructure for SARS-CoV-2 diagnosis and genotyping which can negatively impact the pandemic response. METHODS: Due to this reason and to disburden the diagnostic system of the inner São Paulo State, the Butantan Institute established the Mobile Laboratory (in Portuguese: LabMovel) for SARS-CoV-2 testing which started a trip of the most important "hotspots" of the most populous Brazilian region. The LabMovel initiated in two important cities of the State: Aparecida do Norte (an important religious center) and the Baixada Santista region which incorporates the port of Santos, the busiest in Latin America. The LabMovel was fully equipped with an automatized system for SARS-CoV-2 diagnosis and sequencing/genotyping. It also integrated the laboratory systems for patient records and results divulgation including in the Federal Brazilian Healthcare System. RESULTS: Currently,16,678 samples were tested, among them 1,217 from Aparecida and 4,564 from Baixada Santista. We tracked the delta introductio in the tested regions with its high diversification. The established mobile SARS-CoV-2 laboratory had a major impact on the Public Health System of the included cities including timely delivery of the results to the healthcare agents and the Federal Healthcare system, evaluation of the vaccination status of the positive individuals in the background of exponential vaccination process in Brazil and scientific and technological divulgation of the fieldwork to the most vulnerable populations. CONCLUSIONS: The SARS-CoV-2 pandemic has demonstrated worldwide the importance of science to fight against this viral agent and the LabMovel shows that it is possible to integrate researchers, clinicians, healthcare workers and patients to take rapid actions that can in fact mitigate this and other epidemiological situations.

Bivariate GWAS reveals pleiotropic regions among feed efficiency and beef quality-related traits in Nelore cattle.

Feed-efficient cattle selection is among the most leading solutions to reduce cost for beef cattle production. However, technical difficulties in measuring feed efficiency traits had limited the application in livestock. Here, we performed a Bivariate Genome-Wide Association Study (Bi-GWAS) and presented candidate biological mechanisms underlying the association between feed efficiency and meat quality traits in a half-sibling design with 353 Nelore steers derived from 34 unrelated sires. A total of 13 Quantitative Trait Loci (QTL) were found explaining part of the phenotypic variations. An important transcription factor of adipogenesis in cattle, the TAL1 (rs133408775) gene located on BTA3 was associated with intramuscular fat and average daily gain (IMF-ADG), and a region located on BTA20, close to CD180 and MAST4 genes, both related to fat accumulation. We observed a low positive genetic correlation between IMF-ADG (r = 0.30 ± 0.0686), indicating that it may respond to selection in the same direction. Our findings contributed to clarifying the pleiotropic modulation of the complex traits, indicating new QTLs for bovine genetic improvement.

Rumen and fecal microbiomes are related to diet and production traits in Bos indicus beef cattle.

Background: Ruminants harbor a complex microbial community within their gastrointestinal tract, which plays major roles in their health and physiology. Brazil is one of the largest producers of beef in the world and more than 90% of the beef cattle herds are composed of pure and crossbred Nelore (Bos indicus). Despite its importance to the Brazilian economy and human feeding, few studies have characterized the Nelore microbiome. Therefore, using shotgun metagenomics, we investigated the impact of diet on the composition and functionality of the Nelore microbiome, and explored the associations between specific microbial taxa and their functionality with feed efficiency and methane emission. Results: The ruminal microbiome exhibited significantly higher microbial diversity, distinctive taxonomic profile and variations in microbial functionality compared to the fecal microbiome, highlighting the distinct contributions of the microbiomes of these environments. Animals subjected to different dietary treatments exhibited significant differences in their microbiomes' archaeal diversity and in the abundance of 89 genera, as well as in the functions associated with the metabolism of components of each diet. Moreover, depending on the diet, feed-efficient animals and low methane emitters displayed higher microbial diversity in their fecal microbiome. Multiple genera were associated with an increase or decrease of the phenotypes. Upon analyzing the functions attributed to these taxa, we observed significant differences on the ruminal taxa associated with feed efficient and inefficient cattle. The ruminal taxa that characterized feed efficient cattle stood out for having significantly more functions related to carbohydrate metabolism, such as monosaccharides, di-/oligosaccharides and amino acids. The taxa associated with methane emission had functions associated with methanogenesis and the production of substrates that may influence methane production, such as hydrogen and formate. Conclusion: Our findings highlight the significant role of diet in shaping Nelore microbiomes and how its composition and functionality may affect production traits such as feed efficiency and methane emission. These insights provide valuable support for the implementation of novel feeding and biotechnological strategies.

Differential Allele-Specific Expression Revealed Functional Variants and Candidate Genes Related to Meat Quality Traits in B. indicus Muscle.

Traditional transcriptomics approaches have been used to identify candidate genes affecting economically important livestock traits. Regulatory variants affecting these traits, however, remain under covered. Genomic regions showing allele-specific expression (ASE) are under the effect of cis-regulatory variants, being useful for improving the accuracy of genomic selection models. Taking advantage of the better of these two methods, we investigated single nucleotide polymorphisms (SNPs) in regions showing differential ASE (DASE SNPs) between contrasting groups for beef quality traits. For these analyses, we used RNA sequencing data, imputed genotypes and genomic estimated breeding values of muscle-related traits from 190 Nelore (Bos indicus) steers. We selected 40 contrasting unrelated samples for the analysis (N = 20 animals per contrasting group) and used a beta-binomial model to identify ASE SNPs in only one group (i.e., DASE SNPs). We found 1479 DASE SNPs (FDR ≤ 0.05) associated with 55 beef-quality traits. Most DASE genes were involved with tenderness and muscle homeostasis, presenting a co-expression module enriched for the protein ubiquitination process. The results overlapped with epigenetics and phenotype-associated data, suggesting that DASE SNPs are potentially linked to cis-regulatory variants affecting simultaneously the transcription and phenotype through chromatin state modulation.

Multi-omic data integration for the study of production, carcass, and meat quality traits in Nellore cattle.

Data integration using hierarchical analysis based on the central dogma or common pathway enrichment analysis may not reveal non-obvious relationships among omic data. Here, we applied factor analysis (FA) and Bayesian network (BN) modeling to integrate different omic data and complex traits by latent variables (production, carcass, and meat quality traits). A total of 14 latent variables were identified: five for phenotype, three for miRNA, four for protein, and two for mRNA data. Pearson correlation coefficients showed negative correlations between latent variables miRNA 1 (mirna1) and miRNA 2 (mirna2) (-0.47), ribeye area (REA) and protein 4 (prot4) (-0.33), REA and protein 2 (prot2) (-0.3), carcass and prot4 (-0.31), carcass and prot2 (-0.28), and backfat thickness (BFT) and miRNA 3 (mirna3) (-0.25). Positive correlations were observed among the four protein factors (0.45-0.83): between meat quality and fat content (0.71), fat content and carcass (0.74), fat content and REA (0.76), and REA and carcass (0.99). BN presented arcs from the carcass, meat quality, prot2, and prot4 latent variables to REA; from meat quality, REA, mirna2, and gene expression mRNA1 to fat content; from protein 1 (prot1) and mirna2 to protein 5 (prot5); and from prot5 and carcass to prot2. The relations of protein latent variables suggest new hypotheses about the impact of these proteins on REA. The network also showed relationships among miRNAs and nebulin proteins. REA seems to be the central node in the network, influencing carcass, prot2, prot4, mRNA1, and meat quality, suggesting that REA is a good indicator of meat quality. The connection among miRNA latent variables, BFT, and fat content relates to the influence of miRNAs on lipid metabolism. The relationship between mirna1 and prot5 composed of isoforms of nebulin needs further investigation. The FA identified latent variables, decreasing the dimensionality and complexity of the data. The BN was capable of generating interrelationships among latent variables from different types of data, allowing the integration of omics and complex traits and identifying conditional independencies. Our framework based on FA and BN is capable of generating new hypotheses for molecular research, by integrating different types of data and exploring non-obvious relationships.

Dynamics of SARS-CoV-2 Variants of Concern in Vaccination Model City in the State of Sao Paulo, Brazil.

From a country with one of the highest SARS-CoV-2 morbidity and mortality rates, Brazil has implemented one of the most successful vaccination programs. Brazil's first model city vaccination program was performed by the CoronaVac vaccine (Sinovac Biotech) in the town of Serrana, São Paulo State. To evaluate the vaccination effect on the SARS-CoV-2 molecular dynamics and clinical outcomes, we performed SARS-CoV-2 molecular surveillance on 4375 complete genomes obtained between June 2020 and April 2022 in this location. This study included the period between the initial SARS-CoV-2 introduction and during the vaccination process. We observed that the SARS-CoV-2 substitution dynamics in Serrana followed the viral molecular epidemiology in Brazil, including the initial identification of the ancestral lineages (B.1.1.28 and B.1.1.33) and epidemic waves of variants of concern (VOC) including the Gamma, Delta, and, more recently, Omicron. Most probably, as a result of the immunization campaign, the mortality during the Gamma and Delta VOC was significantly reduced compared to the rest of Brazil, which was also related to lower morbidity. Our phylogenetic analysis revealed the evolutionary history of the SARS-CoV-2 in this location and showed that multiple introduction events have occurred over time. The evaluation of the COVID-19 clinical outcome revealed that most cases were mild (88.9%, 98.1%, 99.1% to Gamma, Delta, and Omicron, respectively) regardless of the infecting VOC. In conclusion, we observed that vaccination was responsible for reducing the death toll rate and related COVID-19 morbidity, especially during the gamma and Delta VOC; however, it does not prevent the rapid substitution rate and morbidity of the Omicron VOC.

Allele-specific expression reveals functional SNPs affecting muscle-related genes in bovine.

Single nucleotide polymorphisms showing allele-specific expression (ASE SNPs) are useful for cis-regulatory variants discovery. Despite this potential, there are expensive costs involved in genome-level ASE analysis for large sample sizes. If different data resolutions are available, genotype imputation can be used to mitigate this limitation. Aiming to increase the power to detect regulatory variants, we used a large dataset (>4 million) of imputed SNP genotypes and RNA-Seq data from 190 Nelore steers. Differences between major and minor allele expressions in muscle were tested with a Binomial Test. We identified 38,177 ASE SNPs (FDR ≤ 0.05) within 7304 linkage disequilibrium blocks. After that, we searched for aseQTLs (i.e., neighboring SNPs potentially regulating the ASE SNPs' allelic expression) by comparing the ASE of heterozygous to homozygous sample groups under a Wilcoxon Rank Sum test. We identified 21,543 aseQTLs potentially regulating 430 ASE SNPs (FDR ≤ 0.05). A total of 3333 cis-eQTLs (being 2098 ASE SNPs and 1075 aseQTLs) were associated with the expression of 758 transcripts (FDR ≤ 0.05), demonstrating the cis-regulatory effect of these ASE SNPs and aseQTLs. Data integration showed reproducibility with previous studies in bovine ASE and genomic imprinting. Furthermore, we identified 36,756 novel ASE regions due to the imputation approach. Comparisons with epigenetics data from Functional Annotation of Animal Genomes (FAANG) suggest a regulatory potential of the ASE-related SNPs. The affected genes were enriched in metabolic pathways essential for muscle homeostasis. These findings reinforce the potential of using ASE for discovering cis-regulatory SNPs that may affect muscle-related traits.

Integrative Analysis Between Genome-Wide Association Study and Expression Quantitative Trait Loci Reveals Bovine Muscle Gene Expression Regulatory Polymorphisms Associated With Intramuscular Fat and Backfat Thickness.

Understanding the architecture of gene expression is fundamental to unravel the molecular mechanisms regulating complex traits in bovine, such as intramuscular fat content (IMF) and backfat thickness (BFT). These traits are economically important for the beef industry since they affect carcass and meat quality. Our main goal was to identify gene expression regulatory polymorphisms within genomic regions (QTL) associated with IMF and BFT in Nellore cattle. For that, we used RNA-Seq data from 193 Nellore steers to perform SNP calling analysis. Then, we combined the RNA-Seq SNP and a high-density SNP panel to obtain a new dataset for further genome-wide association analysis (GWAS), totaling 534,928 SNPs. GWAS was performed using the Bayes B model. Twenty-one relevant QTL were associated with our target traits. The expression quantitative trait loci (eQTL) analysis was performed using Matrix eQTL with the complete SNP dataset and 12,991 genes, revealing a total of 71,033 cis and 36,497 trans-eQTL (FDR < 0.05). Intersecting with QTL for IMF, we found 231 eQTL regulating the expression levels of 117 genes. Within those eQTL, three predicted deleterious SNPs were identified. We also identified 109 eQTL associated with BFT and affecting the expression of 54 genes. This study revealed genomic regions and regulatory SNPs associated with fat deposition in Nellore cattle. We highlight the transcription factors FOXP4, FOXO3, ZSCAN2, and EBF4, involved in lipid metabolism-related pathways. These results helped us to improve our knowledge about the genetic architecture behind important traits in cattle.