Marcela Maria de Souza

Global liver gene expression differences in Nelore steers with divergent residual feed intake phenotypes

BackgroundEfficiency of feed utilization is important for animal production because it can reduce greenhouse gas emissions and improve industry profitability. However, the genetic basis of feed utilization in livestock remains poorly understood. Recent developments in molecular genetics, such as platforms for genome-wide genotyping and sequencing, provide an opportunity to identify genes and pathways that influence production traits. It is known that transcriptional networks influence feed efficiency-related traits such as growth and energy balance. This study sought to identify differentially expressed genes in animals genetically divergent for Residual Feed Intake (RFI), using RNA sequencing methodology (RNA-seq) to obtain information from genome-wide expression profiles in the liver tissues of Nelore cattle.ResultsDifferential gene expression analysis between high Residual Feed Intake (HRFI, inefficient) and low Residual Feed Intake (LRFI, efficient) groups was performed to provide insights into the molecular mechanisms that underlie feed efficiency-related traits in beef cattle. A total of 112 annotated genes were identified as being differentially expressed between animals with divergent RFI phenotypes. These genes are involved in ion transport and metal ion binding; act as membrane or transmembrane proteins; and belong to gene clusters that are likely related to the transport and catalysis of molecules through the cell membrane and essential mechanisms of nutrient absorption. Genes with functions in cellular signaling, growth and proliferation, cell death and survival were also differentially expressed. Among the over-represented pathways were drug or xenobiotic metabolism, complement and coagulation cascades, NRF2-mediated oxidative stress, melatonin degradation and glutathione metabolism.ConclusionsOur data provide new insights and perspectives on the genetic basis of feed efficiency in cattle. Some previously identified mechanisms were supported and new pathways controlling feed efficiency in Nelore cattle were discovered. We potentially identified genes and pathways that play key roles in hepatic metabolic adaptations to oxidative stress such as those involved in antioxidant mechanisms. These results improve our understanding of the metabolic mechanisms underlying feed efficiency in beef cattle and will help develop strategies for selection towards the desired phenotype.

Calcium and potassium content in beef: Influences on tenderness and associations with molecular markers in Nellore cattle

Calcium (Ca) and potassium (K) are essential nutrients in animal nutrition. Furthermore, the Ca content can influence meat tenderness because it is needed by the proteolytic system of calpains and calpastatins, major factors in postmortem tenderization of skeletal muscles. K content, which is needed for muscle contraction, can also affect meat tenderness. This study showed that K positively affects the Warner-Bratzler shear force (WBSF), measured at 14days of meat aging, which means that higher levels of K are related to lower meat tenderness. Additionally, a significant effect (P≤0.015) of a SNP in the calcium-activated neutral protease 1 (CAPN1) gene on Ca content was observed. Metal content in beef can affect not only nutritional values but also meat quality traits. Part of this effect may be related to variation in specific genes.

Detection of quantitative trait loci for mineral content of Nelore longissimus dorsi muscle

BackgroundBeef cattle require dietary minerals for optimal health, production and reproduction. Concentrations of minerals in tissues are at least partly genetically determined. Mapping genomic regions that affect the mineral content of bovine longissimus dorsi muscle can contribute to the identification of genes that control mineral balance, transportation, absorption and excretion and that could be associated to metabolic disorders.MethodsWe applied a genome-wide association strategy and genotyped 373 Nelore steers from 34 half-sib families with the Illumina BovineHD BeadChip. Genome-wide association analysis was performed for mineral content of longissimus dorsi muscle using a Bayesian approach implemented in the GenSel software.ResultsMuscle mineral content in Bos indicus cattle was moderately heritable, with estimates ranging from 0.29 to 0.36. Our results suggest that variation in mineral content is influenced by numerous small-effect QTL (quantitative trait loci) but a large-effect QTL that explained 6.5% of the additive genetic variance in iron content was detected at 72 Mb on bovine chromosome 12. Most of the candidate genes present in the QTL regions for mineral content were involved in signal transduction, signaling pathways via integral (also called intrinsic) membrane proteins, transcription regulation or metal ion binding.ConclusionsThis study identified QTL and candidate genes that affect the mineral content of skeletal muscle. Our findings provide the first step towards understanding the molecular basis of mineral balance in bovine muscle and can also serve as a basis for the study of mineral balance in other organisms.

Identification of KCNJ11 as a functional candidate gene for bovine meat tenderness

The potassium inwardly rectifying channel, subfamily J, member 11 (KCNJ11) gene was investigated as a candidate for meat tenderness based on the effects reported on muscle for KCNJ11 gene knockout in rat models and its position in a quantitative trait locus (QTL) for meat tenderness in the bovine genome. Sequence variations in the KCNJ11 gene were described by sequencing six amplified fragments, covering almost the entire gene. We identified single nucleotide polymorphisms (SNP) and validated them by different approaches, taking advantage of simultaneous projects that are being developed with the same Nelore population. By sequencing the KCNJ11 in Nelore steers representing extreme phenotypes for Warner-Bratzler shear force (WBSF), it was possible to identify 22 SNPs. We validated two of the identified markers by genotyping the whole population (n = 460). Analysis of association between genotypes and WBSF values revealed a significant additive effect of a SNP at different meat aging times (P ≤ 0.05). In addition, an association between the expression levels of KCNJ11 and WBSF was found, with lower expression levels of KCNJ11 associated with more tender meat (P ≤ 0.05). The results showed that the KCNJ11 gene is a candidate mapped to a QTL for meat tenderness previously identified on BTA15 and may be useful to identify animals with genetic potential to produce tender meat. The effect of KCNJ11 observed on muscle is potentially due to changes in activity of KATP channels, which in turn influence the flow of potassium in the intracellular space, allowing establishment of the membrane potential necessary for muscle contraction.

Polymorphism and parent-of-origin effects on gene expression of CAST, leptin and DGAT1 in cattle

This study aimed to investigate differential allele expression (DAE) and polymorphism and parent-of-origin effects on expression of genes related to beef traits. CAST, related to meat tenderness, and DGAT1 and leptin, related to fat deposition, were evaluated. In bovine fetal tissues CAST was expressed twice as much (P < 0.05) in muscle of homozygous GG than in heterozygous AG. Leptin was expressed about one-tenth as much (P < 0.05) in heterozygous TpCm (allele T of paternal origin and allele C of maternal origin) than in homozygous CC. No DAE was observed. The evidence of polymorphism effect on expression of CAST and parent-of-origin effect on leptin contributes to a better understanding of events controlling the expression of genes of economic interest in cattle. Furthermore, if the parent-of-origin effects observed in fetal tissues are confirmed in adult tissues and associated to phenotypic variation, this parental origin criterion may be considered in marker-assisted selection of beef traits.

Iron Content Affects Lipogenic Gene Expression in the Muscle of Nelore Beef Cattle

Iron (Fe) is an essential mineral for metabolism and plays a central role in a range of biochemical processes. Therefore, this study aimed to identify differentially expressed (DE) genes and metabolic pathways in Longissimus dorsi (LD) muscle from cattle with divergent iron content, as well as to investigate the likely role of these DE genes in biological processes underlying beef quality parameters. Samples for RNA extraction for sequencing and iron, copper, manganese, and zinc determination were collected from LD muscles at slaughter. Eight Nelore steers, with extreme genomic estimated breeding values for iron content (Fe-GEBV), were selected from a reference population of 373 animals. From the 49 annotated DE genes (FDR<0.05) found between the two groups, 18 were up-regulated and 31 down-regulated for the animals in the low Fe-GEBV group. The functional enrichment analyses identified several biological processes, such as lipid transport and metabolism, and cell growth. Lipid metabolism was the main pathway observed in the analysis of metabolic and canonical signaling pathways for the genes identified as DE, including the genes FASN, FABP4, and THRSP, which are functional candidates for beef quality, suggesting reduced lipogenic activities with lower iron content. Our results indicate metabolic pathways that are partially influenced by iron, contributing to a better understanding of its participation in skeletal muscle physiology.

Genome-Enabled Prediction of Breeding Values for Feedlot Average Daily Weight Gain in Nelore Cattle

Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS) could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic-estimated breeding values (GEBV) for average daily weight gain (ADG) in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications [Bayesian GBLUP (BGBLUP), BayesA, and BayesCπ] were performed with four genotype panels [Illumina BovineHD BeadChip, TagSNPs, and GeneSeek High- and Low-density indicus (HDi and LDi, respectively)]. Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesCπ model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44) and sample size (568 animals in the training population). Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement GS at lower costs.