Impact of Postovulatory Food Deprivation on the Ova Transport, Hormonal Profiles and Metabolic Changes in Sows

The effect of food deprivation on ova transport, hormonal profiles and metabolic changes was studied in 20 crossbred multiparous sows during their second oestrus after weaning. To determine the time of ovulation, transrectal ultrasonographic examination was performed. The sows were divided into 2 groups, one control group (C-group), which was fed according to Swedish standards, and one experimental group (E-group). The E-group sows were deprived of food from the first morning meal after ovulation until slaughter. Blood samples were collected every second hour from about 12 h before expected ovulation in the second oestrus after weaning until slaughter and were analysed for progesterone, prostaglandin F_2α-metabolite, insulin, glucose, free fatty acids and triglycerides. All sows were slaughtered approximately 48 h after ovulation and the genital tract was recovered. The isthmic part of the oviduct was divided into 3 equally long segments and flushed separately with phosphate buffered saline (PBS). Uterine horns were also flushed with PBS. A significantly greater number of ova were found in the first and second part of the isthmus in the E-group (p = 0.05) while in the C-group most of the ova were found in the third part of the isthmus or the uterus (p = 0.01). The level of prostaglandin F_2α-metabolite was significantly higher in the E-group compared with the C-group. The concentration of progesterone increased in both groups after ovulation but there were no significant differences between the groups. The other blood parameters showed that the food-deprived sows were in a catabolic state. The 48 h period of fasting results, directly or indirectly in an delayed ova transport, which may be due to a delayed relaxation in the smooth circular muscle layer of the isthmus.     

Effect of Metalaxyl on the incidence and severity of Pearl millet downy mildew disease in Northern Nigeria

Pearl millet downy mildew (DM) incidence, severity and yield losses of two pearl millet varieties (local and improved) due to the disease were determined in the field. Significant differences in the disease incidence and severity were recorded in the plots sown with metalaxyl-treated seeds and those sown with non-treated seeds, indicating the efficacy of the fungicide on the fungus. Yield losses due to non-treatment of seeds with metalaxyl was 40.88 and 45.39% in a local variety and 43.00 and 18.60% in an improved variety in the 2000 and 2001 cropping seasons respectively. Significant differences between plots sown with metalaxyl-treated and those sown with non-treated seeds were obtained for other yield components such as 1000-grains weight, panicle length and weight.     

POCUS: mining genomic sequence annotation to predict disease genes

Here we present POCUS (prioritization of candidate genes using statistics), a novel computational approach to prioritize candidate disease genes that is based on over-representation of functional annotation between loci for the same disease. We show that POCUS can provide high (up to 81-fold) enrichment of real disease genes in the candidate-gene shortlists it produces compared with the original large sets of positional candidates. In contrast to existing methods, POCUS can also suggest counterintuitive candidates.     

Selective photostimulation of genetically chARGed neurons.

To permit direct functional analyses of neural circuits, we have developed a method for stimulating groups of genetically designated neurons optically. Coexpression of the Drosophila photoreceptor genes encoding arrestin-2, rhodopsin (formed by liganding opsin with retinal), and the alpha subunit of the cognate heterotrimeric G protein--an explosive combination we term "chARGe"--sensitizes generalist vertebrate neurons to light. Illumination of a mixed population of neurons elicits action potentials selectively and cell-autonomously in its genetically chARGed members. In contrast to bath-applied photostimulants or caged neurotransmitters, which act indiscriminately throughout the illuminated volume, chARGe localizes the responsiveness to light. Distributed activity may thus be fed directly into a circumscribed population of neurons in intact tissue, irrespective of the spatial arrangement of its elements.     

A novel disorder caused by defective biosynthesis of N-linked oligosaccharides due to glucosidase I deficiency

Glucosidase I is an important enzyme in N-linked glycoprotein processing, removing specifically distal alpha-1,2-linked glucose from the Glc3Man9GlcNAc2 precursor after its en bloc transfer from dolichyl diphosphate to a nascent polypeptide chain in the endoplasmic reticulum. We have identified a glucosidase I defect in a neonate with severe generalized hypotonia and dysmorphic features. The clinical course was progressive and was characterized by the occurrence of hepatomegaly, hypoventilation, feeding problems, seizures, and fatal outcome at age 74 d. The accumulation of the tetrasaccharide Glc(alpha1-2)Glc(alpha1-3)Glc(alpha1-3)Man in the patient's urine indicated a glycosylation disorder. Enzymological studies on liver tissue and cultured skin fibroblasts revealed a severe glucosidase I deficiency. The residual activity was <3% of that of controls. Glucosidase I activities in cultured skin fibroblasts from both parents were found to be 50% of those of controls. Tissues from the patient subjected to SDS-PAGE followed by immunoblotting revealed strongly decreased amounts of glucosidase I protein in the homogenate of the liver, and a less-severe decrease in cultured skin fibroblasts. Molecular studies showed that the patient was a compound heterozygote for two missense mutations in the glucosidase I gene: (1) one allele harbored a G-->C transition at nucleotide (nt) 1587, resulting in the substitution of Arg at position 486 by Thr (R486T), and (2) on the other allele a T-->C transition at nt 2085 resulted in the substitution of Phe at position 652 by Leu (F652L). The mother was heterozygous for the G-->C transition, whereas the father was heterozygous for the T-->C transition. These base changes were not seen in 100 control DNA samples. A causal relationship between the alpha-glucosidase I deficiency and the disease is postulated.     

Response to genomic selection: The Bulmer effect and the potential of genomic selection when the number of phenotypic records is limiting

Background

Over the last ten years, genomic selection has developed enormously. Simulations and results on real data suggest that breeding values can be predicted with high accuracy using genetic markers alone. However, to reach high accuracies, large reference populations are needed. In many livestock populations or even species, such populations cannot be established when traits are difficult or expensive to record, or when the population size is small. The value of genomic selection is then questionable.

Methods

In this study, we compare traditional breeding schemes based on own performance or progeny information to genomic selection schemes, for which the number of phenotypic records is limiting. Deterministic simulations were performed using selection index theory. Our focus was on the equilibrium response obtained after a few generations of selection. Therefore, we first investigated the magnitude of the Bulmer effect with genomic selection.

Results

Results showed that the reduction in response due to the Bulmer effect is the same for genomic selection as for selection based on traditional BLUP estimated breeding values, and is independent of the accuracy of selection. The reduction in response with genomic selection is greater than with selection based directly on phenotypes without the use of pedigree information, such as mass selection. To maximize the accuracy of genomic estimated breeding values when the number of phenotypic records is limiting, the same individuals should be phenotyped and genotyped, rather than genotyping parents and phenotyping their progeny. When the generation interval cannot be reduced with genomic selection, large reference populations are required to obtain a similar response to that with selection based on BLUP estimated breeding values based on own performance or progeny information. However, when a genomic selection scheme has a moderate decrease in generation interval, relatively small reference population sizes are needed to obtain a similar response to that with selection on traditional BLUP estimated breeding values.

Conclusions

When the trait of interest cannot be recorded on the selection candidate, genomic selection schemes are very attractive even when the number of phenotypic records is limited, because traditional breeding requires progeny testing schemes with long generation intervals in those cases.     

Relationship of aerobic and anaerobic parameters with 400 m front crawl swimming performance

The aims of the present study were to investigate the relationship of aerobic and anaerobic parameters with 400 m performance, and establish which variable better explains long distance performance in swimming. Twenty-two swimmers (19.1±1.5 years, height 173.9±10.0 cm, body mass 71.2±10.2 kg; 76.6±5.3% of 400 m world record) underwent a lactate minimum test to determine lactate minimum speed (LMS) (i.e., aerobic capacity index). Moreover, the swimmers performed a 400 m maximal effort to determine mean speed (S400m), peak oxygen uptake (V.O2PEAK) and total anaerobic contribution (C_ANA). The C_ANA was assumed as the sum of alactic and lactic contributions. Physiological parameters of 400 m were determined using the backward extrapolation technique (V.O2PEAK and alactic contributions of C_ANA) and blood lactate concentration analysis (lactic anaerobic contributions of C_ANA). The Pearson correlation test and backward multiple regression analysis were used to verify the possible correlations between the physiological indices (predictor factors) and S400m (independent variable) (p < 0.05). Values are presented as mean ± standard deviation. Significant correlations were observed between S400m (1.4±0.1 m·s^-1) and LMS (1.3±0.1 m·s^-1; r = 0.80), V.O2PEAK (4.5±3.9 L·min^-1; r = 0.72) and C_ANA (4.7±1.5 L·O₂; r= 0.44). The best model constructed using multiple regression analysis demonstrated that LMS and V.O2PEAK explained 85% of the 400 m performance variance. When backward multiple regression analysis was performed, C_ANA lost significance. Thus, the results demonstrated that both aerobic parameters (capacity and power) can be used to predict 400 m swimming performance.