Genomic structure and marker-derived gene networks for growth and meat quality traits of Brazilian Nelore beef cattle.

BACKGROUND: Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample. RESULTS: Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches. CONCLUSIONS: The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.

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

BACKGROUND: Beef 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. METHODS: We 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. RESULTS: Muscle 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. CONCLUSIONS: This 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.

Evaluation of thermal comfort, physiological, hematological, and seminal features of buffalo bulls in an artificial insemination station in a tropical environment.

This study aimed to assess the variation over time in thermal comfort indices and the behavior of physiological parameters related to thermolysis, blood parameters, and semen in natura of buffalo bulls reared in tropical climate. The study was carried out in an artificial insemination station under a humid tropical climate (Afi according to Köppen). Ten water buffalo bulls (Bubalus bubalis) were used during the 5 months (April to August) of study. The environmental Temperature Humidity Index (THId) and the pen microclimate Temperature Humidity Index (THIp) were calculated. Every 25 days, respiratory rate (RR), heart rate (HR), rectal temperature (RT), and Benezra's thermal comfort index (BTCI) were assessed in the morning and in the afternoon. A blood assay was performed every month, while semen was collected weekly. THIp did not vary over the months (P > 0.05) and was higher in the afternoon than in the morning (77.7 ± 2.6 versus 81.8 ± 2.1, P < 0.05). RR, HR, and BTCI significantly increased over the months and were different between the periods of the day (P > 0.05) but within the physiological limits. RT varied between the periods of the day and decreased over the months, being the lowest in August (37.8 ± 0.7 °C), time-impacted hematocrit, mean corpuscular volume, hemoglobin levels, and spermatic gross motility and vigor (P < 0.05). Thus, buffalo bulls reared under a humid tropical climate may have variations in thermal comfort during the hotter periods but are able to efficiently activate thermoregulatory mechanisms and maintain homeothermy, hence preserving their physiological and seminal parameters at normal levels.

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.

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.

Modelos matemáticos utilizados para descrever curvas de crescimento em aves aplicados ao melhoramento genético animal / Mathematic models applied to describe growth curves in poultry applied to animal breeding

A utilização de funções matemáticas para descrever o crescimento animal é antiga. Elas permitem resumir informações em alguns pontos estratégicos do desenvolvimento ponderal e descrever a evolução do peso em função da idade do animal. Também é possível comparar taxas de crescimento de diferentes indivíduos em estados fisiológicos equivalentes. Os modelos de curvas de crescimento mais utilizados na avicultura são os derivados da função Richards, pois apresentam parâmetros que possibilitam interpretação biológica e portanto podem fornecer subsídios para seleção de uma determinada forma da curva de crescimento em aves. Também pode-se utilizar polinômios segmentados para descrever as mudanças de tendência da curva de crescimento animal. Entretanto, existem importantes fatores de variação para os parâmetros das curvas, como a espécie, o sistema de criação, o sexo e suas interações. A adequação dos modelos pode ser verificada pelos valores do coeficiente de determinação (R2), do quadrado médio do resíduo (QM res), do erro de predição médio (EPm), da facilidade de convergência dos dados e pela possibilidade de interpretação biológica dos parâmetros. Estudos envolvendo modelagem e descrição da curva de crescimento e seus componentes são amplamente discutidos na literatura. Porém, programas de seleção que visem a progressos genéticos para a forma da curva não são mencionados. A importância da avaliação dos parâmetros dos modelos de curvas de crescimento é ainda mais relevante já que os maiores ganhos genéticos para peso estão relacionados com seleção para pesos em idades próximas ao ponto de inflexão. A seleção para precocidade pode ser auxiliada com base nos parâmetros do modelo associados à variáveis que descrevem esta característica genética dos animais. Esses parâmetros estão relacionados a importantes características produtivas e reprodutivas e apresentam magnitudes diferentes, de acordo com a espécie, o sexo e o modelo utilizados na avaliação. ...

The use of mathematical models to describe animal growth is not recent. They are able to summarize information on strategic dots of animal growth development and to describe the evolution of weight according to the animal age. It is also possible to compare different individuals in similar physiologic stages. The growth models most commonly used in poultry breeding are derived from Richards function, and they present parameters that provide biological interpretation and knowledge to select a specific shape of growth curve in poultry. However, it is also possible to use segmented polynomials to describe trend changes during the animal growth. One needs to consider important variables affecting the growth curve parameters estimates, such as, production system, specie, sex and their interactions. Model Goodness-of-fit can be based on many criteria such as coefficient of determination (R2), residual mean squared error, (LSe), estimated predicted mean error (PME), the easiness the analysis to reach convergence and the possibility of biological interpretation of parameters. Studies involving modeling and description of growth curve and their components are described in literature, but, there is no selection programs applied to the growth curve shape. The importance of determinating the parameters of growth curve models is more relevant when considering that most of the genetic gains for growth traits are related to selection, on weights near to the inflexion point. Often, selection to fast growth is important in all breeding programs, and could be based on genetic parameters of the growth curve parameters. These parameters are related to important productive and reproductive traits, and present different values, according to specie, sex and models used in evaluation. Alternatively, other methodology used is random regression models, allowing graduation changes in (co) variances between ages during the time and predicting (co)variances during ...