Random regression models to estimate genetic parameters for milk yield, fat, and protein contents in Tunisian Holsteins.

This study aimed to find the parsimonious random regression model (RRM) to evaluate the genetic potential for milk yield (MY), fat content (FC), and protein content (PC) in Tunisian Holstein cows. For this purpose, 551,139; 331,654; and 302,396 test day records for MY, FC, and PC were analysed using various RRMs with different Legendre polynomials (LP) orders on additive genetic (AG) and permanent environmental (PE) effects, and different types of residual variances (RV). The statistical analysis was performed in a Bayesian framework with Gibbs sampling, and the model performances were assessed, mainly, on the predictive ability criteria. The study found that the optimal model for evaluating these traits was an RRM with a third LP order and nine classes of heterogeneous RV. In addition, the study found that heritability estimates for MY, FC, and PC ranged from 0.11 to 0.22, 0.11 to 0.17, and 0.12 to 0.18, respectively, indicating that genetic improvement should be accompanied by improvements in the production environment. The study also suggested that new selection rules could be used to modify lactation curves by exploiting the canonical transformation of the random coefficient covariance (RC) matrix or by using the combination of slopes of individual lactation curves and expected daily breeding values.

Genetic basis of thermotolerance in 2 local dairy sheep populations in the Iberian Peninsula.

Sheep milk production in the Northern Mediterranean countries heavily relies on local breeds subject to selection schemes to improve milk production. Climate change may shift the range of thermal loads on the animals and challenge their adaptation to the new thermal gradient. The objective of this study was to characterize the genetic component of thermal tolerance of 2 local breeds from the Iberian Peninsula, Latxa and Manchega, belonging to different genetic types that have evolved under different climatic environments (Oceanic for Latxa and Continentalized Mediterranean for Manchega). A total of 79,243 and 2,388,853 test day monthly records of milk, fat and protein yields from 12,882 and 277,904 ewes of Latxa and Manchega breeds, respectively, along a 12-yr period, were matched with the value of the average temperature-humidity index (THI) on the day of milk recording of the closest weather station to the flocks. These data were used to fit individual reaction norms (Legendre polynomials) describing changes in yields along the THI gradient. Genetic values for thermal tolerance were obtained from the slopes of those reaction norms under cold or heat stress and variances and covariances between yield and thermal tolerance were derived from the (co)variance matrices of the polynomial random regression coefficients. Results showed differing patterns in the 2 breeds. The Latxa breed showed clearer signs of genotype by environment interaction than did Manchega. Estimated correlations between yields under extremes of cold and heat were always above 0.8 for Manchega and around 0.4 for Latxa for all traits. Estimates of correlations between comfort and thermal stress were again over 0.8 for Manchega and lower for the higher (hot end) values (down to 0.6) than for the lower (cold end) values (down to 0.84) of the THI gradient for Latxa, indicating greater thermal stress expected from high than from low temperatures in this breed. Substantial variability in thermal tolerance under the more extreme THI values was found in both breeds. Estimated genetic correlations between yield and thermal tolerance were close to 0 and 0.2 for Latxa and Manchega in the cold and down to -0.6 and -0.3 in the heat end, although small variation was observed for fat in Latxa. Estimated realized trends from the average estimated breeding value, by year of birth, showed a positive response for yields in both breeds [around 0.1 standard deviation (SD) unit], but a detrimental correlation for thermal tolerance (down to -0.03 SD units for heat tolerance in Latxa). These results can be used to design optimal selection strategies for sustainable improvement of productivity under a rising-temperature scenario associated with climate change.

Disentangling Genetic Variation for Resistance and Endurance to Scuticociliatosis in Turbot Using Pedigree and Genomic Information.

Selective breeding for improving host responses to infectious pathogens is a promising option for disease control. In fact, disease resilience, the ability of a host to survive or cope with infectious challenge, has become a highly desirable breeding goal. However, resilience is a complex trait composed of two different host defence mechanisms, namely resistance (the ability of a host to avoid becoming infected or diseased) and endurance (the ability of an infected host to survive the infection). While both could be targeted for genetic improvement, it is currently unknown how they contribute to survival, as reliable estimates of genetic parameters for both traits obtained simultaneously are scarce. A difficulty lies in obtaining endurance phenotypes for genetic analyses. In this study, we present the results from an innovative challenge test carried out in turbot whose design allowed disentangling the genetic basis of resistance and endurance to Philasterides dicentrarchi, a parasite causing scuticociliatosis that leads to substantial economic losses in the aquaculture industry. A noticeable characteristic of the parasite is that it causes visual signs that can be used for disentangling resistance and endurance. Our results showed the existence of genetic variation for both traits (heritability = 0.26 and 0.12 for resistance and endurance, respectively) and for the composite trait resilience (heritability = 0.15). The genetic correlation between resistance and resilience was very high (0.90) indicating that both are at a large extent the same trait, but no significant genetic correlation was found between resistance and endurance. A total of 18,125 SNPs obtained from 2b-RAD sequencing enabled genome-wide association analyses for detecting QTLs controlling the three traits. A candidate QTL region on linkage group 19 that explains 33% of the additive genetic variance was identified for resilience. The region contains relevant genes related to immune response and defence mechanisms. Although no significant associations were found for resistance, the pattern of association was the same as for resilience. For endurance, one significant association was found on linkage group 2. The accuracy of genomic breeding values was also explored for resilience, showing that it increased by 12% when compared with the accuracy of pedigree-based breeding values. To our knowledge, this is the first study in turbot disentangling the genetic basis of resistance and endurance to scuticociliatosis.

Disease resistance in Atlantic salmon (Salmo salar): coinfection of the intracellular bacterial pathogen Piscirickettsia salmonis and the sea louse Caligus rogercresseyi.

BACKGROUND: Naturally occurring coinfections of pathogens have been reported in salmonids, but their consequences on disease resistance are unclear. We hypothesized that 1) coinfection of Caligus rogercresseyi reduces the resistance of Atlantic salmon to Piscirickettsia salmonis; and 2) coinfection resistance is a heritable trait that does not correlate with resistance to a single infection. METHODOLOGY: In total, 1,634 pedigreed Atlantic salmon were exposed to a single infection (SI) of P. salmonis (primary pathogen) or coinfection with C. rogercresseyi (secondary pathogen). Low and high level of coinfection were evaluated (LC = 44 copepodites per fish; HC = 88 copepodites per fish). Survival and quantitative genetic analyses were performed to determine the resistance to the single infection and coinfections. MAIN FINDINGS: C. rogercresseyi significantly increased the mortality in fish infected with P. salmonis (SI mortality = 251/545; LC mortality = 544/544 and HC mortality = 545/545). Heritability estimates for resistance to P. salmonis were similar and of medium magnitude in all treatments (h2SI = 0.23 ± 0.07; h2LC = 0.17 ± 0.08; h2HC = 0.24 ± 0.07). A large and significant genetic correlation with regard to resistance was observed between coinfection treatments (rg LC-HC = 0.99 ± 0.01) but not between the single and coinfection treatments (rg SI-LC = -0.14 ± 0.33; rg SI-HC = 0.32 ± 0.34). CONCLUSIONS/SIGNIFICANCE: C. rogercresseyi, as a secondary pathogen, reduces the resistance of Atlantic salmon to the pathogen P. salmonis. Resistance to coinfection of Piscirickettsia salmonis and Caligus rogercresseyi in Atlantic salmon is a heritable trait. The absence of a genetic correlation between resistance to a single infection and resistance to coinfection indicates that different genes control these processes. Coinfection of different pathogens and resistance to coinfection needs to be considered in future research on salmon farming, selective breeding and conservation.

Use of Maximum Likelihood-Mixed Models to select stable reference genes: a case of heat stress response in sheep.

BACKGROUND: Reference genes with stable expression are required to normalize expression differences of target genes in qPCR experiments. Several procedures and companion software have been proposed to find the most stable genes. Model based procedures are attractive because they provide a solid statistical framework. NormFinder, a widely used software, uses a model based method. The pairwise comparison procedure implemented in GeNorm is a simpler procedure but one of the most extensively used. In the present work a statistical approach based in Maximum Likelihood estimation under mixed models was tested and compared with NormFinder and geNorm softwares. Sixteen candidate genes were tested in whole blood samples from control and heat stressed sheep. RESULTS: A model including gene and treatment as fixed effects, sample (animal), gene by treatment, gene by sample and treatment by sample interactions as random effects with heteroskedastic residual variance in gene by treatment levels was selected using goodness of fit and predictive ability criteria among a variety of models. Mean Square Error obtained under the selected model was used as indicator of gene expression stability. Genes top and bottom ranked by the three approaches were similar; however, notable differences for the best pair of genes selected for each method and the remaining genes of the rankings were shown. Differences among the expression values of normalized targets for each statistical approach were also found. CONCLUSIONS: Optimal statistical properties of Maximum Likelihood estimation joined to mixed model flexibility allow for more accurate estimation of expression stability of genes under many different situations. Accurate selection of reference genes has a direct impact over the normalized expression values of a given target gene. This may be critical when the aim of the study is to compare expression rate differences among samples under different environmental conditions, tissues, cell types or genotypes. To select reference genes not only statistical but also functional and biological criteria should be considered. Under the method here proposed SDHA/MDH1 have arisen as the best set of reference genes to be used in qPCR assays to study heat shock in ovine blood samples.

Time trends, environmental factors and genetic basis of semen traits collected in Holstein bulls under commercial conditions.

The fact that results of artificial insemination (AI) are declining in highly selected dairy cattle populations has added a renewed interest to the evaluation of male fertility. Data from 42,348 ejaculates collected from 1990 to 2007 on 502 Holstein bulls were analysed in a Bayesian framework to provide estimates of the evolution of semen traits routinely collected in AI centres throughout the last decades of intense selection for production traits and estimate genetic parameters. The traits under consideration were volume (VOL), concentration (CONC), number of spermatozoa per ejaculate (NESPZ), mass motility score (MM), individual motility (IM), and post-thawing motility (PTM). The environmental factors studied were year-season and week of collection, which account for changes in environmental and technical conditions along time, age at collection, ejaculate order, time from previous collection (TPC) and time between collection and freezing (TCF) (only for PTM). Bull's inbreeding coefficient (Fi), bull's permanent environmental and additive genetic effects were also considered. The use of reduced models was evaluated using the Bayes factor. For all the systematic effects tested, strong or very strong evidence in favour of including the effect in the model was obtained, except for Fi for motility traits and TCF for PTM. No systematic time trends for environment or bull effects were observed, except for PTM, which showed an increasing environmental trend, associated with improvements in freezing-thawing protocols. Heritability estimates were moderate (0.16-0.22), except for IM, which presented a low value (0.07). Genetic correlations among motilities and between motilities and CONC were large and positive [0.38-0.87], VOL showed a negative correlation with CONC (-0.13) but with ample HPD 95%. The magnitude of heritabilities would allow an efficient selection if required and grants the use of these traits as indicators of the sperm viability component of bulls breeding soundness.

Skeletal muscle specific genes networks in cattle.

While physiological differences across skeletal muscles have been described, the differential gene expression underlying them and the discovery of how they interact to perform specific biological processes are largely to be elucidated. The purpose of the present study was, firstly, to profile by cDNA microarrays the differential gene expression between two skeletal muscle types, Psoas major (PM) and Flexor digitorum (FD), in beef cattle and then to interpret the results in the context of a bovine gene coexpression network, detecting possible changes in connectivity across the skeletal muscle system. Eighty four genes were differentially expressed (DE) between muscles. Approximately 54% encoded metabolic enzymes and structural-contractile proteins. DE genes were involved in similar processes and functions, but the proportion of genes in each category varied within each muscle. A correlation matrix was obtained for 61 out of the 84 DE genes from a gene coexpression network. Different groups of coexpression were observed, the largest one having 28 metabolic and contractile genes, up-regulated in PM, and mainly encoding fast-glycolytic fibre structural components and glycolytic enzymes. In FD, genes related to cell support seemed to constitute its identity feature and did not positively correlate to the rest of DE genes in FD. Moreover, changes in connectivity for some DE genes were observed in the different gene ontologies. Our results confirm the existence of a muscle dependent transcription and coexpression pattern and suggest the necessity of integrating different muscle types to perform comprehensive networks for the transcriptional landscape of bovine skeletal muscle.

A comprehensive characterisation of the fibre composition and properties of a limb (flexor digitorum superficialis, membri thoraci) and a trunk (psoas major) muscle in cattle.

BACKGROUND: The fibre type attributes and the relationships among their properties play an important role in the differences in muscle capabilities and features. Comprehensive characterisation of the skeletal muscles should study the degree of association between them and their involvement in muscle functionality. The purposes of the present study were to characterise the fibre type composition of a trunk (Psoas major, PM) and a limb (Flexor digitorum, membri thoraci, FD) muscle in the bovine species and to study the degree of coordination among contractile, metabolic and histological properties of fibre types. Immunohistochemical, histochemical and histological techniques were used. RESULTS: The fibre type composition was delineated immunohistochemically in calf muscle samples, identifying three pure (I, IIA, and IIX) and two hybrid type fibres (I+IIA, and IIAX). Most of the fibres in FD were types I and IIA, while pure IIX were absent. All fibre types were found in PM, the IIX type being the most frequent. Compared to other species, small populations of hybrid fibres were detected. The five fibre types, previously identified, were ascribed to three different acid and alkaline mATPase activity patterns. Type I fibres had the highest oxidative capacity and the lowest glycolytic capacity. The reverse was true for the IIX fibres, whereas the type IIA fibres showed intermediate properties. Regarding the histological properties, type I fibres tended to be more capillarised than the II types. Correlations among contractile, metabolic and histological features on individual fibres were significantly different from zero (r values varied between -0.31 and 0.78). Hybrid fibre values were positioned between their corresponding pure types, and their positions were different regarding their metabolic and contractile properties. CONCLUSION: Coordination among the contractile, metabolic and histological properties of fibres has been observed. However, the magnitude of the correlation among them is always below 0.8, suggesting that the properties of muscles are not fully explained by the fibre composition. These results support the concept that, to some extent, muscle plasticity can be explained by the fibre type composition, and by the properties derived from their metabolic and histological profiles.