Milk and meat fatty acids from sheep fed a plantain–chicory mixture or a grass-based permanent sward

Plantain and chicory are interesting forage species since they present good nutritional quality and are more resistant to drought than many temperate grasses. The fatty acid (FA) profile in milk and meat is related to a growing concern for the consumption of healthy foods, that is, with a lower content of saturated FA, higher polyunsaturated FA (PUFA) and a favourable n-6 : n-3 FAs ratio. Our objective was to evaluate the FA content in ewe’s milk and lamb’s meat fed a plantain–chicory mixture (PCH) or a grass-based permanent sward (GBS) dominated by perennial ryegrass. Eighteen Austral ewes in mid-lactation were allocated to PCH and GBS treatments. Milk samples were obtained during September (spring). Thirty weaned lambs were finished on both treatments from November to December (7 weeks), slaughtered and their meat sampled. Fat from milk and meat samples was extracted and stored until analysed by gas chromatography. Milk fat from GBS was higher than from PCH (P < 0.05) in C18:0 (11 385 v. 5874 mg/100 g FA), 9c-18:1 (15 750 v. 8565 mg/100 g FA), 11 t-18:1 (4576 v. 2703 mg/100 g FA) and 9c,11 t-18:2 (1405 v. 921 mg/100 g FA) and lower in 18:2n-6 (827 v. 1529 mg/100 g FA) and 18:3n-3 (943 v. 1318 mg/100 g FA) FA. Total mono-unsaturated FA was higher in GBS than PCH (P < 0.05). Meat fat from PCH swards presented a higher (P < 0.05) content than GBS for 18:2n-6 (46.8 v. 28.2 mg/100 g FA), linolenic (24.6 v. 14.2 mg/100 g FA), polyunsaturated FA (119.7 v. 73.4 mg/100 g FA), n-6 (65.9 v. 40.8 mg/100 g FA) and n-3 (53.8 v. 32.5 mg/100 g FA), respectively. No effect of treatment (P > 0.05) was detected for 9c-18:1 (283.9 v. 205.8 mg/100 g FA), 11 t-18:1 (26.2 v. 19.3 mg/100 g FA) and 9c,11 t-18:2 (10.1 v. 7.6 mg/100 g FA), for PCH and GBS. These results suggest that grazing a PCH mixture results in a higher concentration of PUFA in ewes’ milk and in lambs’ fat, as compared to a GBS sward.     

DGAT1 underlies large genetic variation in milk-fat composition of dairy cows

Dietary fat may play a role in the aetiology of many chronic diseases. Milk and milk-derived foods contribute substantially to dietary fat, but have a fat composition that is not optimal for human health. We measured the fat composition of milk samples in 1918 Dutch Holstein Friesian cows in their first lactation and estimated genetic parameters for fatty acids. Substantial genetic variation in milk-fat composition was found: heritabilities were high for short- and medium-chain fatty acids (C4:0-C16:0) and moderate for long-chain fatty acids (saturated and unsaturated C18). We genotyped 1762 cows for the DGAT1 K232A polymorphism, which is known to affect milk-fat percentage, to study the effect of the polymorphism on milk-fat composition. We found that the DGAT1 K232A polymorphism has a clear influence on milk-fat composition. The DGAT1 allele that encodes lysine (K) at position 232 (232K) is associated with more saturated fat; a larger fraction of C16:0; and smaller fractions of C14:0, unsaturated C18 and conjugated linoleic acid (P < 0.001). We conclude that selective breeding can make a significant contribution to change the fat composition of cow's milk.     

Enhanced process understanding and multivariate prediction of the relationship between cell culture process and monoclonal antibody quality

This work investigates the insights and understanding which can be deduced from predictive process models for the product quality of a monoclonal antibody based on designed high‐throughput cell culture experiments performed at milliliter (ambr‐15^®) scale. The investigated process conditions include various media supplements as well as pH and temperature shifts applied during the process. First, principal component analysis (PCA) is used to show the strong correlation characteristics among the product quality attributes including aggregates, fragments, charge variants, and glycans. Then, partial least square regression (PLS1 and PLS2) is applied to predict the product quality variables based on process information (one by one or simultaneously). The comparison of those two modeling techniques shows that a single (PLS2) model is capable of revealing the interrelationship of the process characteristics to the large set product quality variables. In order to show the dynamic evolution of the process predictability separate models are defined at different time points showing that several product quality attributes are mainly driven by the media composition and, hence, can be decently predicted from early on in the process, while others are strongly affected by process parameter changes during the process. Finally, by coupling the PLS2 models with a genetic algorithm first the model performance can be further improved and, most importantly, the interpretation of the large‐dimensioned process–product‐interrelationship can be significantly simplified. The generally applicable toolset presented in this case study provides a solid basis for decision making and process optimization throughout process development. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 33:1368–1380, 2017     

Spatio-temporal patterns of fish assemblages in a large regulated alluvial river

1. The River Durance, the last alpine tributary of the River Rhône, is a large, braided alluvial hydrosystem. Following large-scale regulation, flow downstream of the Serre-Ponçon dam has been maintained at 1/40th of previous annual mean discharge. To assess the effects of historical disturbances, fish assemblages and habitat use were analysed during five summers in a representative reach of the middle Durance.
2. Habitat availability and use were assessed with a multi-scale approach including the variables water depth, current velocity, roughness height of substratum, amount of woody debris and lateral/longitudinal location. Eighteen fish species were sampled by electrofishing in 289 habitat sample units.
3. Partial least square (PLS) regression showed that taxa were mainly distributed according to relationships between their total length and water depth/velocity variables. Fish assemblage composition was also related to roughness height as well as distance from the bank or to the nearest large woody debris. However, PLS regression revealed no significant differences in habitat selection between two periods of varying hydromorphological stability.
4. Fish distribution patterns and density were related to proximity to the bank and cover, indicating that local scale variables need to be considered in conservation and restoration programmes.     

The constancy of the G matrix through species divergence and the effects of quantitative genetic constraints on phenotypic evolution: a case study in crickets

Long-term phenotypic evolution can be modeled using the response-to-selection equation of quantitative genetics, which incorporates information about genetic constraints (the G matrix). However, little is known about the evolution of G and about its long-term importance in constraining phenotypic evolution. We first investigated the degree of conservation of the G matrix across three species of crickets and qualitatively compared the pattern of variation of G to the phylogeny of the group. Second, we investigated the effect of G on phenotypic evolution by comparing the direction of greatest quantitative genetic variation within species (g(max)) to the direction of phenotypic divergence between species (Delta(z)). Each species, Gryllus veletis, G. firmus, and G. pennsylvanicus, was reared in the laboratory using a full-sib breeding design to extract quantitative genetic information. Five morphological traits related to size were measured. G matrices were compared using three statistical approaches: the T method, the Flury hierarchy, and the MANOVA method. Results revealed that the differences between matrices were small and mostly caused by differences in the magnitude of the genetic variation, not by differences in principal component structure. This suggested that the G matrix structure of this group of species was preserved, despite significant phenotypic divergence across species. The small observed differences in G matrices across species were qualitatively consistent with genetic distances, whereas ecological information did not provide a good prediction of G matrix variation. The comparison of g(max) and Delta(z) revealed that the angle between these two vectors was small in two of three species comparisons, whereas the larger angle corresponding to the third species comparison was caused in large part by one of the five traits. This suggests that multivariate phenotypic divergence occurred mostly in a direction predicted by the direction of greatest genetic variation, although it was not possible to demonstrate the causal relationship from G to Delta(z). Overall, this study provided some support for the validity of the predictive power of quantitative genetics over evolutionary time scales.     

Does natural selection alter genetic architecture? An evaluation of quantitative genetic variation among populations of Allonemobiussocius and A. fasciatus

To make long-term predictions using present quantitative genetic theory it is necessary to assume that the genetic variance–covariance matrix ( G ) remains constant or at least changes by a constant fraction. In this paper we examine the stability of the genetic architecture of two traits known to be subject to natural selection; femur length and ovipositor length in two species of the cricket Allonemobius. Previous studies have shown that in A. fasciatus and A. socius natural selection favours an increased body size southwards but a decreased ovipositor length. Such countergradient selection should tend to favour a change in G . In the total sample of eight populations of A. socius and one of A. fasciatus we show that there is significant variation in all genetic covariance components, i.e. V_A for body size, V_A for ovipositor length, and Cov_A. This variation results entirely from an increase in the covariances of A. fasciatus. However, although larger, these components are approximately proportionally increased, thereby leading to no statistically significant change in the genetic correlation. A proportional increase in the covariance components is consistent with changes resulting from genetic drift. On the other hand, the genetic covariance components are significantly correlated with the length of the growing season suggesting that the change in the genetic architecture is the result of selection and drift.