Relationship between the Porcine Stress Syndrome gene and carcass and performance traits in F2 pigs resulting from divergent crosses

Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs

A large number of quantitative trait loci (QTL) for meat quality and carcass traits has been reported in pigs over the past 20 years. However, few QTL have been validated and the biological meaning of the genes associated to these QTL has been underexploited. In this context, a meta-analysis was performed to compare the significant markers with meta-QTL previously reported in literature. Genome association studies were performed for 12 traits, from which 144 SNPs were found out to be significant (P < 0.05). They were validated in the meta-analysis and used to build the Association Weight Matrix, a matrix framework employed to investigate co-association of pairwise SNP across phenotypes enabling to derive a gene network. A total of 45 genes were selected from the Association Weight Matrix analysis, from which 25 significant transcription factors were identified and used to construct the networks associated to meat quality and carcass traits. These networks allowed the identification of key transcription factors, such as SOX5 and NKX2–5, gene–gene interactions (e.g. ATP5A1, JPH1, DPT and NEDD4) and pathways related to the regulation of adipose tissue metabolism and skeletal muscle development. Validated SNPs and knowledge of key genes driving these important industry traits might assist future strategies in pig breeding.

Regularized quantile regression for SNP marker estimation of pig growth curves

Background

Genomic growth curves are generally defined only in terms of population mean; an alternative approach that has not yet been exploited in genomic analyses of growth curves is the Quantile Regression (QR). This methodology allows for the estimation of marker effects at different levels of the variable of interest. We aimed to propose and evaluate a regularized quantile regression for SNP marker effect estimation of pig growth curves, as well as to identify the chromosome regions of the most relevant markers and to estimate the genetic individual weight trajectory over time (genomic growth curve) under different quantiles (levels).

Results

The regularized quantile regression (RQR) enabled the discovery, at different levels of interest (quantiles), of the most relevant markers allowing for the identification of QTL regions. We found the same relevant markers simultaneously affecting different growth curve parameters (mature weight and maturity rate): two (ALGA0096701 and ALGA0029483) for RQR(0.2), one (ALGA0096701) for RQR(0.5), and one (ALGA0003761) for RQR(0.8). Three average genomic growth curves were obtained and the behavior was explained by the curve in quantile 0.2, which differed from the others.

Conclusions

RQR allowed for the construction of genomic growth curves, which is the key to identifying and selecting the most desirable animals for breeding purposes. Furthermore, the proposed model enabled us to find, at different levels of interest (quantiles), the most relevant markers for each trait (growth curve parameter estimates) and their respective chromosomal positions (identification of new QTL regions for growth curves in pigs). These markers can be exploited under the context of marker assisted selection while aiming to change the shape of pig growth curves.

Inferência bayesiana da conversão alimentar em diferentes experimentos animais

O presente trabalho teve por objetivo avaliar a conversão alimentar (CA) por meio da inferência bayesiana considerando-se análises bivariadas. Foram utilizadas diferentes espécies animais de experimentos conduzidos na Universidade Federal de Viçosa, no estado de Minas Gerais, Brasil. O modelo proposto mostrou ser apropriado, uma vez que possibilitou a detecção de diferenças significativas entre níveis de fatores não detectados por procedimentos frequentistas em ANOVA tradicional, principalmente em pequenas amostras. No experimento com codornas, evidenciou-se que aves cujos níveis de proteína bruta eram de 23% e 29%, respectivamente, para machos e fêmeas, apresentaram uma melhor CA, de 2,83±0,03 e 2,66±0,03, respectivamente. No experimento com frangos, no grupo sem o aditivo antibiótico, a inclusão de 0,02% de extrato de ésteres naturais foi o que promoveu a melhor CA (1,72±0,01), e, de modo geral, o uso de antibiótico e a ausência de ésteres naturais promoveram CA de 1,63±0,02. Em caprinos, verificou-se que o aleitamento, seja com leite de cabra ou de vaca, promove igualmente uma melhor CA, respectivamente, no grupo de 60 e 90 dias, de 1,29±0,14 e 1,79±0,11, sugerindo que o aleitamento seja feito até os 60 dias. Em suínos, a dieta com maior nível de energia metabolizável e aminoácidos foi a que promoveu a melhor CA (2,86±0,07), quando comparada a uma dieta com nível nutricional mais baixo. Já o uso de enzimas na dieta com menor nível energético e de aminoácidos proporcionou resultado intermediário (2,90±007). Em bovinos, observou-se que o uso de 1% de concentrado na dieta promoveria uma melhor CA estimada de 7,33±0,35 entre os Nelores e que essa promoção seria de 7,40±0,58 entre os cruzados com o uso de 2% de concentrado na dieta.

Fine mapping and single nucleotide polymorphism effects estimation on pig chromosomes 1, 4, 7, 8, 17 and X

Fine mapping of quantitative trait loci (QTL) from previous linkage studies was performed on pig chromosomes 1, 4, 7, 8, 17, and X which were known to harbor QTL. Traits were divided into: growth performance, carcass, internal organs, cut yields, and meat quality. Fifty families were used of a F2 population produced by crossing local Brazilian Piau boars with commercial sows. The linkage map consisted of 237 SNP and 37 microsatellite markers covering 866 centimorgans. QTL were identified by regression interval mapping using GridQTL. Individual marker effects were estimated by Bayesian LASSO regression using R. In total, 32 QTL affecting the evaluated traits were detected along the chromosomes studied. Seven of the QTL were known from previous studies using our F2 population, and 25 novel QTL resulted from the increased marker coverage. Six of the seven QTL that were significant at the 5% genome-wide level had SNPs within their confidence interval whose effects were among the 5% largest effects. The combined use of microsatellites along with SNP markers increased the saturation of the genome map and led to smaller confidence intervals of the QTL. The results showed that the tested models yield similar improvements in QTL mapping accuracy.

Genomic growth curves of an outbred pig population

In the current post-genomic era, the genetic basis of pig growth can be understood by assessing SNP marker effects and genomic breeding values (GEBV) based on estimates of these growth curve parameters as phenotypes. Although various statistical methods, such as random regression (RR-BLUP) and Bayesian LASSO (BL), have been applied to genomic selection (GS), none of these has yet been used in a growth curve approach. In this work, we compared the accuracies of RR-BLUP and BL using empirical weight-age data from an outbred F2 (Brazilian Piau X commercial) population. The phenotypes were determined by parameter estimates using a nonlinear logistic regression model and the halothane gene was considered as a marker for evaluating the assumptions of the GS methods in relation to the genetic variation explained by each locus. BL yielded more accurate values for all of the phenotypes evaluated and was used to estimate SNP effects and GEBV vectors. The latter allowed the construction of genomic growth curves, which showed substantial genetic discrimination among animals in the final growth phase. The SNP effect estimates allowed identification of the most relevant markers for each phenotype, the positions of which were coincident with reported QTL regions for growth traits.

Mapeamento de QTL nos cromossomos 1, 2, 3, 12, 14, 15 e X em suínos: características de carcaça e qualidade de carne

A realização do presente estudo teve como objetivo mapear Quantitative Trait Loci (QTL) de carcaça e qualidade de carne em uma população F2 de suínos desenvolvida pelo cruzamento de dois reprodutores da raça brasileira Piau com 18 fêmeas comerciais (Landrace x Large White x Pietrain). O mapa de ligação para essa população foi construído após a genotipagem de 684 animais para 35 marcadores microssatélites. Os dados foram analisados pelo mapeamento por intervalo usando-se sexo, lote e genótipo halotano como efeitos fixos e peso de carcaça ao abate, peso da carcaça direita e idade ao abate como covariáveis. Um total de 18 QTLs foi encontrado; os QTLs para maior espessura de toucinho na região da copa, na linha dorsolombar, e a perda por cozimento foram significativos em nível de 5% genômico. A característica espessura de toucinho foi essencialmente associada aos alelos da raça Piau, conhecido como porco tipo banha. As informações dos QTLs significativos encontrados servem para futuros estudos de mapeamento fino para identificação de genes a serem usados em conjunto com os métodos tradicionais de seleção, para melhorar a eficiência dos programas de melhoramento, assim como prover informação acerca da fisiologia envolvida no desenvolvimento das características quantitativas dos suínos.