Genetic (co)variation in skin pigmentation patterns and growth in rainbow trout.

From a physiological-behavioral perspective, it has been shown that fish with a higher density of black eumelanin spots are more dominant, less sensitive to stress, have higher feed intake, better feed efficiency and therefore are larger in size. Thus, we hypothesized that genetic (co)variation between skin pigmentation patterns and growth exists and it is advantageous in rainbow trout. The objective of this study was to determine the genetic relationships between skin pigmentation patterns and BW in a breeding population of rainbow trout. We performed a genetic analysis of pigmentation traits including dorsal color (DC), lateral band (LB) intensity, amount of spotting above (SA) and below (SB) the lateral line, and BW at harvest (HW). Variance components were estimated using a multi-trait linear animal model fitted by restricted maximum likelihood. Estimated heritabilities were 0.08±0.02, 0.17±0.03, 0.44±0.04, 0.17±0.04 and 0.23±0.04 for DC, LB, SA, SB and HW, respectively. Genetic correlations between HW and skin color traits were 0.42±0.13, 0.32±0.14 and 0.25±0.11 for LB, SA and SB, respectively. These results indicate positive, but low to moderate genetic relationships between the amount of spotting and BW in rainbow trout. Thus, higher levels of spotting are genetically associated with better growth performance in this population.

Genetic analysis of vibriosis and viral nervous necrosis resistance in Atlantic cod (Gadus morhua L.) using a cure model.

The aim of this study was to investigate whether observed time-until-death of Atlantic cod (Gadus morhua L.) juveniles in separate challenge tests with Vibrio anguillarum (causes vibriosis) and nodavirus [causes viral nervous necrosis (VNN)] are due to differences in susceptibility (whether at risk or not) or increased endurance (individual hazard, given that the animal is susceptible) using a cure mixture (CURE) model with Gibbs sampling. Observed time-until-death, prepared as sequential binary records, were analyzed with the CURE model and results were compared with cross-sectional threshold (SIMPLE) and an ordinary longitudinal survival score (NAÏVE) model (i.e., assuming that all animals are susceptible). Overall mortality at the end of the test was 86 and 71% for vibriosis and VNN, respectively. But the CURE model estimated 92 and 82% of the population to be susceptible to vibriosis and VNN, respectively. Hence, a substantial fraction among the survivors were considered to be susceptible but with high endurance. The underlying heritability of susceptibility was moderate for vibriosis (0.33) and extremely high for VNN (0.91), somewhat greater compared with classical SIMPLE model (0.19 and 0.76 for vibriosis and VNN, respectively), analyzing end survival as a cross-sectional binary trait. Estimates of the underlying heritability were low for single test-day scores of both endurance (0.02 and 0.15 for vibriosis and VNN, respectively) in the CURE model and for the NAÏVE model (0.02 and 0.18 for vibriosis and VNN, respectively). Based on the CURE model, the genetic correlation between susceptibility and endurance was low to moderately positive and significantly different from unity (P < 0.01) for both vibriosis (0.13) and VNN (0.47). Estimated breeding values from the SIMPLE and NAÏVE models showed moderate to high correlations (0.41 to 0.96) with EBV for susceptibility and endurance in the CURE model. The analyses indicate that susceptibility and endurance are apparently distinct genetic traits. Still, the genetic variation estimated in the SIMPLE and NAÏVE models seems to a large extent to be controlled by susceptibility and an efficient genetic selection for reduced susceptibility to vibriosis and VNN is therefore likely feasible even when using classical (noncure) models. Earlier termination of the challenge test or back truncation of survival data is not recommended as this likely shifts the focus of selection towards endurance rather than susceptibility.

Validation of RNA isolated from milk fat globules to profile mammary epithelial cell expression during lactation and transcriptional response to a bacterial infection.

Mastitis, an inflammation of the mammary gland, is the most costly infectious disease of dairy ruminants worldwide. Although it receives considerable attention, the early steps of the host response remain poorly defined. Here, we report a noninvasive method using milk fat globules (MFG) as a source of mammary RNA to follow the dynamics of the global transcriptional response of mammary epithelial cells (MEC) during the course of a bacterial infection. We first assessed that RNA isolated from MFG were representative of MEC RNA; we then evaluated whether MFG RNA could be used to monitor the MEC response to infection. Sufficiently high yields of good-quality RNA (RNA integrity numbers ranging between 6.7 and 8.7) were obtained from goat MFG for subsequent analyses. Contamination of MFG by macrophages and neutrophils, which can be trapped during creaming, was assessed and when using quantitative real-time PCR for cell-type specific markers, was shown to be weak enough (<8%) to affect MFG gene expression profiling. Using microarrays, we showed that RNA extracted from MFG and from mammary alveolar parenchyma shared approximately 90% of the highlighted probes corresponding in particular to genes encoding milk proteins (CSN, BLG, LALBA) and enzymes involved in milk fat synthesis and secretion (FASN, XDH, ADRP, SCD, and DGAT1). In addition, a gene involved in the acute-phase reaction, coding for the serum amyloid A3 (SAA3) protein, was found within the first 50 most highly expressed genes in a noninfectious context in both mammary alveolar parenchyma and MFG, strongly suggesting that SAA3 is expressed in MEC. We took advantage of this noninvasive RNA sampling to follow the early proinflammatory response of MEC during the course of a bacterial infection and showed that the levels of mRNA encoding SAA3 sharply increased at 24h postinfection. Taken together, our results demonstrate that MFG represent a unique source of MEC RNA to noninvasively sample sufficient amounts of high-quality RNA to assess the dynamics of MEC gene expression in vivo, especially during the first steps of infection, thereby paving the way for the discovery of early biomarkers for the control of intramammary infections. Furthermore, this noninvasive technique could be used to provide mammary transcriptomic data on a large scale, thus filling the gap between genomic and phenotypic data.