Dietary and organoleptic qualities of pork products are largely influenced by the profiles of fatty acids (FAs) of meat and fat. The objective of this work was to investigate the potential associations between FA profile in subcutaneous adipose (back fat and leg fat) and muscular (longissimus dorsi and biceps femoris) tissues in heavy pigs (n = 129, 9-month-old) with single nucleotide polymorphisms (SNPs) in six candidate genes involved in fat metabolism: Stearoyl-CoA desaturase (SCD), Diacylglycerol acyltransferase 1 and 2 (DGAT1 & DGAT2), Microsomal Triglyceride Transfer Protein (MTTP), Fatty Acid Synthase (FASN) and Heart- fatty acid binding protein (H-FABP). Preliminary results suggest a putative association between MTTP, DGAT2 and FASN and the FA content in both fat and meat, whereas between DGAT1, SCD and H-FABP the association was found in adipose tissue only. However, the effect of the analyzed genes, needs to be verified in a larger and better characterized pig population to support the hypothesized associations with FA content.

In March 2016, Zoetis Genetics offered the first commercially available evaluation for wellness traits of Holstein dairy cattle. Phenotypic data on health events, pedigree, and genotypes were collected directly from producers upon obtaining their permission. Among all recorded health events, 6 traits were chosen to be included in the evaluation: mastitis, metritis, retained placenta, displaced abomasum, ketosis, and lameness. Each trait was defined as a binary event, having a value of 1 if a cow has been recorded with a disorder at any point during the lactation and zero otherwise. The number of phenotypic records ranged from 1.8 million for ketosis to 4.1 million for mastitis. Over 14 million pedigree records and 114,216 genotypes were included in the evaluation. All traits were analyzed using univariate threshold animal model with repeated observations, including fixed effect of parity and random effects of herd by year by season of calving, animal, and permanent environment. A total of 45,425 single nucleotide polymorphisms were used in the genomic analyses. Animals genotyped with low-density chips were imputed to the required number of single nucleotide polymorphisms. All analyses were based on the single-step genomic BLUP, a method that combines phenotype, pedigree, and genotype information. Predicted transmitting abilities were expressed in percentage points as a difference from the average estimated probability of a disorder in the base population. Reliabilities of breeding values were obtained by approximation based on partitioning of a function of reliability into contributions from records, pedigree, and genotypes. Reliabilities of genomic predicted transmitting abilities for young genotyped and pedigreed females without recorded health events had average values between 50.2% (displaced abomasum) and 51.9% (mastitis). Genomic predictions for wellness traits can provide new information about an animal's genetic potential for health and new selection tools for dairy wellness improvement.

High meat quality is required for dry-cured ham production, which quality depends on meat fat quantity and composition. The aim was to study the polymorphisms of six genes involved in fat metabolism, namely, Stearoyl-CoA desaturase (SCD), Diacylglycerol acyltransferase 1 and 2 (DGAT1 &DGAT2), Microsomal triglyceride transfer protein (MTTP), Fatty acid synthase (FASN) and Heart fatty acid binding protein (H-FABP) in two traditional (Large White or Duroc × (Landrace × Large White)) and two industrial hybrids (Goland and Danbred), which are used for dry-cured ham production. Significant associations of SCD and MTTP were found with carcass weight. DGAT2 was associated with back fat thickness and L* fat colour (objective white colour score). Several genes (DGAT2, MTTP &FASN) were associated with weight loss during salting, first step in dry-cured ham production, affecting final yield. Finally, MTTP was associated with shear force. Our findings suggest that the SCD, DGAT2, MTTP and FASN polymorphisms are associated with quality of heavy pig meat products.

The aim of this study was to investigate the metabolic and biochemical changes in plasma that occur in the reproductive rabbit doe close to the parturition, as well as if the number of offspring affects the metabolism and the health status of the doe. At −3, 4 and 12 days from parturition (–D3, D4, and D12, respectively) nine rabbit does at their third parity from a commercial hybrid line (HYPLUS PS 19) selected for high prolificacy were weighted and blood was collected for a wide inflammometabolic profile. According to the number of offspring the does were retrospectively divided in two groups: high litter size group (HI; n=5) and low litter size group (LO; n=4). BW was higher (P<0.01) at –D3 and had the lowest values at D4. At D12, the BW was lower (P<0.05) in LO compared with HI. Several metabolites significantly changed from dry to lactation period. Glucose and cholesterol had the lowest levels at –D3; non-esterified fatty acid (NEFA) and aspartate aminotransferase had the highest values before parturition (P<0.05); creatinine and β-hydroxybutyrate (BHBA) were higher at –D3 with respect to D4 (P<0.05). The lowest value of paraoxonase was observed in does at –D3 (P<0.05), whereas at this time ceruloplasmin and total bilirubin had the highest concentration (P<0.05). The differences for blood profile parameters between does grouped according to litter size were mainly evident before parturition (–D3). In particular, BHBA, NEFA and total bilirubin had higher concentrations (P<0.05) in HI v. LO group, whereas albumin and PON were lower in HI group (P<0.01). After parturition there were no significant differences for the metabolic parameters between the two groups. The results show that for reproductive rabbit doe the last days of gestation are very stressful from a metabolic and inflammatory point of view. The genetic selection of does for higher litter size has increased their ability to mobilize body reserves in order to guarantee the nutrients to a high number of kits. This exposes them to a more severe metabolic and inflammatory challenge during the transition period. Consequently, feeding and managerial strategies for high prolificacy periparturient rabbit does should be revised.

This study aimed to evaluate the influences of hybrids (HYB) and maturity stage (SAMP) on in vitro rumen digestibility of immature corn grain. Four HYB (Gigantic, Y43, Klips and 9575) from the FAO group 700 were grown under identical agronomic conditions. First sampling (T1) was done after 95 days from seedling and then 4, 8, 13, 18 and 27 days later (T2 to T6). In vitro starch digestibility (STD_7h) and gas production (72 h) were measured. Whole plant and grain dry matter (WP_DM and GR_DM, respectively) and zein content were significantly affected (P<0.01) by HYB and SAMP. Starch content was significantly affected by HYB, SAMP and their interaction. It increased from T1 to T4 (from 67.47 to 72.82% of GR_DM) and then tended to plateau. Concurrently, STD_7h significantly decreased with advancing SAMP and was also affected by HYB. With advancing maturity, total volatile fatty acids (VFA) significantly decreased, with an increase of acetate and a decrease of propionate molar proportion (P<0.01). Gas production rate (GP_c) was significantly affected by HYB, SAMP and HYB×SAMP. Whole plant grain DM correlated (P<0.01) positively with grain starch content (r=0.60 and 0.64) but negatively with STD_7h (r=-0.39 and r=-0.63) and VFA concentration (r=-0.59 and -0.75). Zein percentage in crude protein negatively affected (P<0.01) total DM (r=-0.65,), STD_7h (r=-0.73) and GP_c (r=-0.68). Results suggest that genotypes and maturity stages influence DM and rumen starch digestibility of immature corn grain and in this respect zein can play a significant role.

Background Coccidiosis is a major parasitic disease that causes huge economic losses to the poultry industry. Its pathogenicity leads to depression of body weight gain, lesions and, in the most serious cases, death in affected animals. Genetic variability for resistance to coccidiosis in the chicken has been demonstrated and if this natural resistance could be exploited, it would reduce the costs of the disease. Previously, a design to characterize the genetic regulation of Eimeria tenella resistance was set up in a Fayoumi × Leghorn F 2 cross. The 860 F 2 animals of this design were phenotyped for weight gain, plasma coloration, hematocrit level, intestinal lesion score and body temperature. In the work reported here, the 860 animals were genotyped for a panel of 1393 (157 microsatellites and 1236 single nucleotide polymorphism (SNP) markers that cover the sequenced genome (i.e. the 28 first autosomes and the Z chromosome). In addition, with the aim of finding an index capable of explaining a large amount of the variance associated with resistance to coccidiosis, a composite factor was derived by combining the variables of all these traits in a single variable. QTL detection was performed by linkage analysis using GridQTL and QTLMap. Single and multi-QTL models were applied. Results Thirty-one QTL were identified i.e. 27 with the single-QTL model and four with the multi-QTL model and the average confidence interval was 5.9 cM. Only a few QTL were common with the previous study that used the same design but focused on the 260 more extreme animals that were genotyped with the 157 microsatellites only. Major differences were also found between results obtained with QTLMap and GridQTL. Conclusions The medium-density SNP panel made it possible to genotype new regions of the chicken genome (including micro-chromosomes) that were involved in the genetic control of the traits investigated. This study also highlights the strong variations in QTL detection between different models and marker densities.

Background: For decades, genetic improvement based on measuring growth and body composition traits has been successfully applied in the production of meat-type chickens. However, this conventional approach is hindered by antagonistic genetic correlations between some traits and the high cost of measuring body composition traits. Marker-assisted selection should overcome these problems by selecting loci that have effects on either one trait only or on more than one trait but with a favorable genetic correlation. In the present study, identification of such loci was done by genotyping an F-2 intercross between fat and lean lines divergently selected for abdominal fatness genotyped with a medium-density genetic map (120 microsatellites and 1302 single nucleotide polymorphisms). Genome scan linkage analyses were performed for growth (body weight at 1, 3, 5, and 7 weeks, and shank length and diameter at 9 weeks), body composition at 9 weeks (abdominal fat weight and percentage, breast muscle weight and percentage, and thigh weight and percentage), and for several physiological measurements at 7 weeks in the fasting state, i.e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome.Results: Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter.Conclusions: The medium-density genetic map enabled us to genotype new regions of the chicken genome (including micro-chromosomes) that influenced the traits investigated. With this marker density, confidence intervals were sufficiently small (14 cM on average) to search for candidate genes. Altogether, this new information provides a valuable starting point for the identification of causative genes responsible for important QTL controlling growth, body composition and metabolic traits in the broiler chicken.

More than 80% of Italy's pig production is used in the production of traditional dry cured ham. Dry cured ham production requires fresh legs with at least 15mm of fat coverage. For decades, Italian pigs have been selected for fatness, as legs constitute almost 60% of the commercial value of the animal. Lately, however, thigh prices have dropped, increasing the economic importance of the Longissimus dorsi (L. dorsi) to the pig industry. This research sought to identify genes that can modulate fat repartitioning, resulting in fat legs and lean L. dorsi. As estrogens are known to control the distribution of body fat in humans and rodents, we investigated the polymorphisms in the estrogen receptor 1 (ESRPvuII5700/4200) and estrogen receptor 2 (ESR2 A949G) genes in 612 pigs (278 females, 334 castrated males) and collected the following phenotypical data: carcass weight, lean percentage, leg weight, back fat and leg fat thickness. Castrated males of the ESRPvuII5700/5700 genotype had significantly more back fat (P<0.05) with no significant effect on leg fat. Conversely, ESRPvuII5700/5700 females had significantly less leg fat (P<0.05) with no significant effect on back fat. Both males and females of the ESR2 A949A genotype had less leg fat (P<0.05) without any effect of the polymorphism on back fat. Our findings suggest that ESRPvuII5700/4200 and ESR2 A949G polymorphisms are associated with subcutaneous fat localization in pigs.

Composition of follicular fluid to which the preovulatory follicle is exposed may be one of the major factors determining subsequent fertility, as fatty acids are a precursor of hormones involved in dominance, ovulation and atresia mechanisms. The objective of this paper is to observe fatty acid profiles in various lipid classes according to estrogenic activity of follicles. For each of the 18 cows, we analysed plasma and follicular fluid fatty acid profiles of phospholipids, non-esterified fatty acid (NEFA), cholesteryl esters and triglycerides fractions. Follicles were classified as active (ratio oestrogen to progesterone E2/P4 > 1) and inactive (E2/P4 < 1). For seven cows, we get both types of follicles, six had only one active follicle and five cows had only one inactive follicle. The NEFA profile for palmitic acid, stearic acid, oleic acid, linoleic acid, C20:3n6, arachidonic acid and docosapentaenoic acid (DPA; p < 0.001) is different between inactive and active follicles and plasma. Compared with active follicular fluid and plasma, follicular fluid of inactive follicles showed lower stearic acid, higher oleic acid, arachidonic acid and DPA (p < 0.05) in phospholipids. No significant differences were observed in the cholesteryl ester fraction, which is composted mainly of linoleic acid. Triglyceride concentrations were too low to get reliable results. This study suggests that follicles have a specific fatty acid metabolism depending on oestrogen activity.

We study the problem of selecting homogeneous variance models vs. heterogeneous variance models in the context of joint analysis of multiple microarray datasets. We provide a modified multiresponse permutation procedure (MRPP), modified cross-validation procedures, and the right AICc (corrected Akaike's information criterion) for choosing a variance model. In a simple univariate setting, our modified MRPP outperforms commonly used competitors. For microarray data analysis, we suggest using the sum of gene-specific selection criteria to choose one best gene-specific model for use with all genes. Through realistic simulations based on three real microarray studies, we evaluated the proposed methods and found that using the correct model does not necessarily provide the best separation between differentially and equivalently expressed genes, but it does control false discovery rates (FDR) at desired levels. A hybrid procedure to decouple FDR control and differential expression detection is recommended.

BACKGROUND:New molecular technologies allow high throughput genotyping for QTL mapping with dense genetic maps. Therefore, the interest of linkage analysis models against linkage disequilibrium could be questioned. As these two strategies are very sensitive to marker density, experimental design structures, linkage disequilibrium extent and QTL effect, we propose to investigate these parameters effects on QTL detection.METHODS:The XIIIth QTLMAS workshop simulated dataset was analysed using three linkage disequilibrium models and a linkage analysis model. Interval mapping, multivariate and interaction between QTL analyses were performed using QTLMAP.RESULTS:The linkage analysis models identified 13 QTL, from which 10 mapped close of the 18 which were simulated and three other positions being falsely mapped as containing a QTL. Most of the QTLs identified by interval mapping analysis are not clearly detected by any linkage disequilibrium model. In addition, QTL effects are evolving during the time which was not observed using the linkage disequilibrium models.CONCLUSIONS:Our results show that for such a marker density the interval mapping strategy is still better than using the linkage disequilibrium only. While the experimental design structure gives a lot of power to both approaches, the marker density and informativity clearly affect linkage disequilibrium efficiency for QTL detection.

The ABCG2 gene codes for a protein that belongs to a trans-membrane proteins superfamily that mediates the ATP-dependent translocation of a variety of lipophilic substrates. The effect of ABCG2 gene on milk yield and composition has been reported in dairy cattle. However, there is limited information on ABCG2 gene structure, expression or functional analysis in dairy goats. This is the rst report on ABCG2 gene coding region nucleotide sequence and expression pattern during the lactation period of the Chinese Xinong Saanen goats. The full sequence of this goat’s gene coding region was sequenced and deposited into the GenBank nucleotide database (Accession number DQ904356). This gene’s complementary DNA contained an open reading frame of 1977 nucleotides that encoded a putative protein of 658 amino acids. The similarities between the nucleotide and peptide sequences of goat ABCG2 gene and putative protein compared with the bovine, human, and mouse homologs were 96%, 89%, 85% and 96%, 85%, 79%, respectively. Further, bioinformatical analysis showed that most of the goat ABCG2’s virtually translated polypeptide sequence were predictably similar to those of bovine’s and human’s. However, the signicant differences that were observed in coil-helix structures and optional motifs were species specic. When Real-time reverse transcription-polymerase chain reaction analysis was employed to explore the gene expression prole during lactation, the result showed a ve-fold increase in expression level during peak yield, compared with the onset of lactation. Overall the results suggested that ABCG2 gene might be involved in goat milk synthesis probably by mediating lipophilic substrates translocation during early, peak, and mid-lactation stages.

Four different normalisation techniques were applied for the corrections of fluorescence data generated by a cDNA microarray experiment. Correction for inaccurate signals and possible bias induced by fluorescence intensity, background intensity and dye effect were used in different combinations. Results of the present study highlight a pronounced role for the normalisation techniques in the absolute number of genes different expressed and a low concordance between different methods. Moreover, a significant effect of the dependent variable used, mean or median fluorescence intensity, was observed.