Feed efficiency (FE) is one of the most important traits in pig production. However, it is difficult and costly to measure it, limiting the collection of large amount of data for an accurate selection for better FE. Therefore, the identification of single-nucleotide polymorphisms (SNPs) associated with FE-related traits to be used in the genetic evaluation is of great interest of pig breeding programs for increasing the prediction accuracy and the genetic progress of these traits. The objective of this study was to identify SNPs significantly associated with FE-related traits: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). We also aimed to identify potential candidate genes for these traits. Phenotypic information recorded on a population of 2386 three-way crossbreed pigs that were genotyped for 51 468 SNPs was used. We identified three loci of quantitative trait (QTL) regions associated with ADG and three QTL regions associated with ADFI; however, no significant association was found for FCR. A false discovery rate (FDR) ≤ 0.005 was used as the threshold for declaring an association as significant. The QTL regions associated with ADG on Sus scrofa chromosome (SSC) 1 were located between 177.01 and 185.47 Mb, which overlaps with the QTL regions for ADFI on SSC1 (173.26 and 185.47 Mb). The other QTL region for ADG was located on SSC12 (2.87 and 3.22 Mb). The most significant SNPs in these QTL regions explained up to 3.26% of the phenotypic variance of these traits. The non-identification of genomic regions associated with FCR can be explained by the complexity of this trait, which is a ratio between ADG and ADFI. Finally, the genes CDH19, CDH7, RNF152, MC4R, PMAIP1, FEM1B and GAA were the candidate genes found in the 1 Mb window around the QTL regions identified in this study. Among them, the MC4R gene (SSC1) has a well-known function related to ADG and ADFI. In this study, we identified three QTL regions for ADG (SSC1 and SSC12) and three for ADFI (SSC1). These regions were previously described in purebred pig populations; however, to our knowledge, this is the first study to confirm the relevance of these QTL regions in a crossbred pig population. The potential use of the SNPs and genes identified in this study in prediction models that combine genomic selection and marker-assisted selection should be evaluated for increasing the prediction accuracy of these traits in this population.

Nile tilapia is a key aquaculture species with one of the highest production volumes globally. Genetic improvement of feed efficiency via selective breeding is an important goal, and genomic selection may expedite this process. The aims of this study were to 1) dissect the genetic architecture of feed-efficiency traits in a Nile tilapia breeding population, 2) map the genomic regions associated with these traits and identify candidate genes, 3) evaluate the accuracy of breeding value prediction using genomic data, and 4) assess the impact of the genetic marker density on genomic prediction accuracies. Using an experimental video recording trial, feed conversion ratio (FCR), body weight gain (BWG), residual feed intake (RFI) and feed intake (FI) traits were recorded in 40 full-sibling families from the GIFT (Genetically Improved Farmed Tilapia) Nile tilapia breeding population. Fish were genotyped with a ThermoFisher Axiom 65 K Nile tilapia SNP array. Significant heritabilities, ranging from 0.12 to 0.22, were estimated for all the assessed traits using the genomic relationship matrix. A negative but favourable genetic correlation was found between BWG and the feed-efficiency related traits; -0.60 and -0.63 for FCR and RFI, respectively. While the genome-wide association analyses suggested a polygenic genetic architecture for all the measured traits, there were significant QTL identified for BWG and FI on chromosomes seven and five respectively. Candidate genes previously found to be associated with feed-efficiency traits were located in these QTL regions, including ntrk3a, ghrh and eif4e3. The accuracy of breeding value prediction using the genomic data was up to 34% higher than using pedigree records. A SNP density of approximately 5,000 SNPs was sufficient to achieve similar prediction accuracy as the full genotype data set. Our results highlight the potential of genomic selection to improve feed efficiency traits in Nile tilapia breeding programmes.

This study aims to quantify heavy metals (Ni, Pb, Zn, Mn, Cr, Cu and Se) in eggs obtained from poultry farms and backyard raised hens by comparing the concentration of metals in their feed intake. Overall, 90 samples of egg and 12 samples of poultry feed (6 each with food and water) were collected from 3 different poultry farms and backyards located in peri-urban areas of Lahore. A di-acid digestion method was adopted for digestion, after which digested samples were analyzed under atomic absorption spectrophotometer. Results showed that the concentration of Pb, Cr and Se in egg white (Pb = 0.6578, Cr = 0.18 and Se = 0.2161), egg yolk (Pb = 0.7011, Cr = 0.2617 and Se = 0.2656), feed (Pb = 2.585, Cr = 1.3039 and Se = 0.9411) and water (Pb = 0.5483, Cr = 0.1006 and Se = 0.3461) were above permissible limits in both poultry farms (study group 1) and backyards (study group 2). The concentration of metals such as Pb, Mn, Cr, Cu and Se in poultry farms eggs were higher than backyard hen eggs, which may be due to the intake of contaminated feed. So, the current study concluded that the higher concentration of metals in eggs has a positive correlation with the intake of feed contaminated with heavy metals.

The efficiency of feed utilization plays an important role in animal breeding. However, measuring feed intake (FI) is costly on an individual basis under practical conditions. Using group measurements to model FI could be practically feasible and cost-effective. The objectives of this study were to develop a random regression model based on repeated group measurements with consideration of missing phenotypes caused by drop out animals. Focus is on variance components (VC) estimation and genetic evaluation, and to investigate the effect of group composition on VC estimation and genetic evaluation using simulated datasets. Data were simulated based on individual FI in a pig population. Each individual had measurement on FI at 6 different time points, reflecting 6 different weeks during the test period. The simulated phenotypes consisted of additive genetic, permanent environment, and random residual effects. Additive genetic and permanent environmental effects were both simulated and modeled by first order Legendre polynomials. Three grouping scenarios based on genetic relationships among the group members were investigated: (1) medium within and across pen genetic relationship; (2) high within group relationship; (3) low within group relationship. To investigate the effect of the drop out animals during test period, a proportion (15%) of animals with individual phenotypes was set as the drop out animals, and two drop out scenarios within each grouping scenario were assessed: (1) animals were randomly dropped out; (2) animals with lower phenotypes were dropped out based on the ranking at each time point. The results show that using group measurements yielded similar VCs estimates but with larger SDs compared with the corresponding scenario of using individual measurements. Compared to scenarios without drop out, similar VC estimates were observed when animals were dropped out randomly, whereas reduced VC estimates were observed when animals were dropped out by the ranking of phenotypes. Different grouping scenarios produced similar VC estimates. Compared to scenarios without drop out, there were no loss of accuracies of genetic evaluation for drop out scenarios. However, dropping out animals by the ranking of phenotypes produced larger bias of estimated breeding values compared to the scenario without dropped out animals and scenario of dropping out animals by random. In conclusion, with an optimized group structure, the developed model can properly handle group measurements with drop out animals, and can achieve comparable accuracy of genetic evaluation for traits measured at the group level.

Numerous studies have been conducted to explain the biological functions and mechanism of ghrelin (GHRL) action in animals. However, the exact role of ghrelin in the regulation of growth and development in pigs is still unclear. The ghrelin gene is considered to be a good candidate marker for the identification of economically important traits in pig production such as feed intake, growth or carcass quality. The objectives of the present study were to investigate the regulatory regions and coding sequence of the porcine GHRL gene and determine the effect of polymorphisms at the ghrelin gene locus on selected fattening traits. Data were obtained from 346 gilts (pure breeds: Landrace, 188; Duroc, 74; Pietrain, 84). The PCR-RFLP (Polymerase Chain Reaction-Restriction Fragment Length Polymorphism) method was used to detect polymorphisms within GHRL. Three polymorphisms were found, one in the promoter region (c.-93A>G) and two in the 3\'UTR sequence (g.4428T>C; g.4486C>T). A significant (p ≤ 0.01) additive effect on daily gain (negative) and age at slaughter (positive) was obtained at the locus c.-93A>G. However, the most promising mutation was at the locus g.4486C > T, which is associated with total feed intake. Overall, the described GHRL polymorphisms may be useful as molecular markers in pig selection but future studies are required.

Feed efficiency (FE) is one of the most important traits in pig production. However, it is difficult and costly to measure it, limiting the collection of large amount of data for an accurate selection for better FE. Therefore, the identification of single-nucleotide polymorphisms (SNPs) associated with FE-related traits to be used in the genetic evaluation is of great interest of pig breeding programs for increasing the prediction accuracy and the genetic progress of these traits. The objective of this study was to identify SNPs significantly associated with FE-related traits: average daily gain (ADG), average daily feed intake (ADFI) and feed conversion ratio (FCR). We also aimed to identify potential candidate genes for these traits. Phenotypic information recorded on a population of 2386 three-way crossbreed pigs that were genotyped for 51 468 SNPs was used. We identified three loci of quantitative trait (QTL) regions associated with ADG and three QTL regions associated with ADFI; however, no significant association was found for FCR. A false discovery rate (FDR) ≤ 0.005 was used as the threshold for declaring an association as significant. The QTL regions associated with ADG on Sus scrofa chromosome (SSC) 1 were located between 177.01 and 185.47 Mb, which overlaps with the QTL regions for ADFI on SSC1 (173.26 and 185.47 Mb). The other QTL region for ADG was located on SSC12 (2.87 and 3.22 Mb). The most significant SNPs in these QTL regions explained up to 3.26% of the phenotypic variance of these traits. The non-identification of genomic regions associated with FCR can be explained by the complexity of this trait, which is a ratio between ADG and ADFI. Finally, the genes CDH19, CDH7, RNF152, MC4R, PMAIP1, FEM1B and GAA were the candidate genes found in the 1 Mb window around the QTL regions identified in this study. Among them, the MC4R gene (SSC1) has a well-known function related to ADG and ADFI. In this study, we identified three QTL regions for ADG (SSC1 and SSC12) and three for ADFI (SSC1). These regions were previously described in purebred pig populations; however, to our knowledge, this is the first study to confirm the relevance of these QTL regions in a crossbred pig population. The potential use of the SNPs and genes identified in this study in prediction models that combine genomic selection and marker-assisted selection should be evaluated for increasing the prediction accuracy of these traits in this population.

This study\'s objective was to determine if nutrient restriction during late gestation affected beef heifer feed intake, body weight (BW) gain and endocrine regulation during a 10-week feeding trial. During the last 100 days of gestation, control (CON) dams were fed to increase body condition score (BCS). Whereas, nutrient-restricted dams (NR) and NR dams protein supplemented 3 days/week (NRS) were fed to decrease BCS by 1.2. After parturition, all cow-calf pairs were moved to a common pasture and fed in excess of requirements until weaning. At 15 months of age, heifers were randomly sorted into two pens and adjusted to a commercial total mixed ration over a 2-week period. Blood samples and BW were taken at the initiation of feeding and on a biweekly basis for the duration of the feeding trial. Feed intake was monitored for 10 weeks using a GrowSafe System. After 10 weeks, an intravenous glucose tolerance test (IVGTT) was performed on 21 randomly subsampled heifers. During the feeding trial, NR heifers consumed more feed than CON and NRS heifers. Heifers from NR dams tended to increase BW compared to NRS and CON heifers when adjusted for initial BW. Heifers from NR and NRS dams had a greater increase in BCS compared to heifers from CON dams. Plasma glucose and insulin concentrations during the feeding trial increased in NR heifers compared to the other groups beginning at 2 and 4 weeks respectively. Plasma leptin concentrations were increased in the NR and NRS heifers compared to the CON heifers beginning at week 4 of feeding. During the IVGTT at the conclusion of the feeding challenge, plasma glucose and insulin were increased in NR heifers compared to other treatment groups. These results show that nutrient restriction during late gestation alters appetite and endocrine regulation in heifer offspring.

The relation between plasma leptin and daily ad libitum roughage intake was evaluated during a 14-day period in eight obese Shetland ponies. When the feeding strategy was changed from maintenance feeding to ad libitum feeding, feed intake increased the first day, decreased the second day and increased again during the following days to reach a constant level after 8 days. Plasma leptin concentration increased during the first 2 days, but remained constant afterwards. Although the same pattern was found in all ponies, the magnitude of the increase in leptin on day 1 and the resulting decrease in feed intake on day 2 differed between ponies. A lower anorectic effect was seen in ponies with higher initial leptin concentration, suggesting the presence of different degrees in leptin sensitivity in obese ponies. High leptin production in a attempt to compensate for the decrease in leptin sensitivity might explain large variations in plasma leptin among obese ponies with similar body condition score. Further research is necessary to clarify whether the reduced leptin sensitivity precedes obesity in equines or vice versa.