Review: Livestock disease resilience: from individual to herd level.

Infectious diseases are a major threat to the sustainable production of high-producing animals. Control efforts, such as vaccination or breeding approaches often target improvements to individual resilience to infections, i.e., they strengthen an animal's ability to cope with infection, rather than preventing infection per se. There is increasing evidence for the contribution of non-clinical carriers (animals that become infected and are infectious but do not develop clinical signs) to the overall health and production of livestock populations for a wide range of infectious diseases. Therefore, we strongly advocate a shift of focus from increasing the disease resilience of individual animals to herd disease resilience as the appropriate target for sustainable disease control in livestock. Herd disease resilience not only captures the direct effects of vaccination or host genetics on the health and production performance of individuals but also the indirect effects on the environmental pathogen load that herd members are exposed to. For diseases primarily caused by infectious pathogens shed by herd members, these indirect effects on herd resilience are mediated both by individual susceptibility to infection and by characteristics (magnitude of infectiousness, duration of infectious period) that influence pathogen shedding from infected individuals. We review what is currently known about how vaccination and selective breeding affect herd disease resilience and its underlying components, and outline the changes required for improvement. To this purpose, we also seek to clarify and harmonise the terminology used in the different animal science disciplines to facilitate future collaborative approaches to infectious disease control in livestock.

Identification of risk factors associated with poor lifetime growth performance in pigs.

During the production period from birth to slaughter there are some pigs that grow markedly slower, despite conditions that seem to support the growth of their contemporaries. This reduction in growth inevitably leads to weight variation within a group, causes difficulties with management, and results in system inefficiencies. By understanding the factors that contribute to poor growth, the performance of these slow growing pigs might be improved, thereby decreasing the overall variability at slaughter. The aim of this paper was to analyze the factors associated with poor growth performance in pigs from birth to slaughter, determine the effect of piglet birth weight (BiW) and weaning weight (WW) on lifetime growth, and investigate the capacity of small piglets to compensate for any BW deficit. Two industry databases, with individual data for approximately 40,000 and 90,000 pigs, respectively, and containing BW profiles and relevant variables, were analyzed. Body weight at birth, weaning, intermediate, and finishing stages were available as well as sex, month of birth, litter size information (number born alive and total born including still born), sow parity number, and length of gestation. Absolute and relative growth rates, based on adjusted BW for age, were calculated for each time interval and 3 types of analysis were performed: a logistic regression, a continuous linear plateau model, and a weight category analysis. For both datasets poor absolute and relative growth from birth to final BW was associated with low BiW (P < 0.001), low WW (P < 0.001), sex (P < 0.001), breed code (P < 0.001), and month of birth (P < 0.001). The linear plateau model suggested that the relationship between BiW and lifetime growth was not linear beyond 1.91 (database 1) or 1.84 (database 2) kg; the same applied to the relationship between WW at 21 d and final BW (FW) growth, which was not linear beyond 7.53 kg. Finally, the weight category analysis revealed that piglets with the lightest BiW were able to exhibit compensatory growth from BiW to FW with 74 (database 1) and 82% (database 2) moving at least 1 BW category. It is concluded that growth performance to slaughter is not solely reliant on pig BiW, with WW also playing a critical role. Additionally, piglets with BiW below the average are capable of some degree of compensatory growth; this provides the opportunity for managing them so as to improve their lifetime growth.

Nitrogen excretion at different stages of growth and its association with production traits in growing pigs.

The objectives of this study were to determine nitrogen loss at different stages of growth and during the entire growing period and to investigate the associations between nitrogen excretion and production traits in growing pigs. Data from 315 pigs of an F(2) population which originated from crossing Pietrain sires with a commercial dam line were used. Nitrogen retention was derived from protein retention as measured using the deuterium dilution technique during different stages of growth (60 to 90 kg, 90 to 120 kg, and 120 to 140 kg). Pigs were fed ad libitum with 2 pelleted diets containing 17% (60 to 90 kg) and 16.5% (90 to 120 and 120 to 140 kg) CP. Average daily nitrogen excretion (ADNE) within each stage of growth was calculated on the basis of the accumulated difference between average daily nitrogen intake (ADNI) and average daily nitrogen retention (ADNR). Least ADNE, nitrogen excretion per BW gain (NEWG) and total nitrogen excretion (TNE) were observed during growth from 60 to 90 kg. In contrast, the greatest ADNE, NEWG, and TNE were found during growth from 120 to 140 kg. Statistical analyses indicated that gender, housing type, the ryanodine receptor 1 (RYR1) gene, and batch influenced nitrogen excretion (P < 0.05), but the degree and direction of influences differed between growth stages. Gender differences showed that gilts excreted less nitrogen than barrows (P < 0.05), which was associated with decreased feed conversion ratio (FCR; feed:gain) and lipid:protein gain ratio. Single-housed pigs showed reduced nitrogen excretion compared with group-housed pigs (P < 0.05). In comparison to other genotypes, pigs carrying genotype NN (homozygous normal) at the RYR1 locus had the least nitrogen excretion (P < 0.05) at all stages of growth except from 60 to 90 kg. The residual correlations indicated that NEWG and TNE have large positive correlations with FCR (r = 0.99 and 0.91, respectively) and moderate negative correlations with ADG (r = -0.53 and -0.48, respectively), for the entire growing period. Improvement in FCR, increase in ADG and reduction in lipid:protein gain ratio by 1 phenotypic SD reduced TNE per pig by 709 g, 307 g, and 211 g, respectively, over the entire growing period. The results indicate that nitrogen excretion changes substantially during growth, and it can be reduced most effectively by improvement of feed efficiency and to a lesser extent through the improvement of BW gain or body composition or both.

Breeding for robustness: the role of cortisol.

Robustness in farm animals was defined by Knap as 'the ability to combine a high production potential with resilience to stressors, allowing for unproblematic expression of a high production potential in a wide variety of environmental conditions'. The importance of robustness-related traits in breeding objectives is progressively increasing towards the production of animals with a high production level in a wide range of climatic conditions and production systems, together with a high level of animal welfare. Current strategies to increase robustness include selection for 'functional traits', such as skeletal and cardiovascular integrity, disease resistance and mortality in various stages. It is also possible to use global evaluation of sensitivity to the environment (e.g. reaction norm analysis or canalization), but these techniques are difficult to implement in practice. The hypothalamic-pituitary-adrenocortical (HPA) axis is the most important stress-responsive neuroendocrine system. Cortisol (or corticosterone) released by the adrenal cortices exerts a large range of effects on metabolism, the immune system, inflammatory processes and brain function, for example. Large individual variations have been described in the HPA axis activity with important physiopathological consequences. In terms of animal production, higher cortisol levels have negative effects on growth rate and feed efficiency and increase the fat/lean ratio of carcasses. On the contrary, cortisol has positive effects on traits related to robustness and adaptation. For instance, newborn survival was shown to be directly related to plasma cortisol levels at birth, resistance to bacteria and parasites are increased in animals selected for a higher HPA axis response to stress, and tolerance to heat stress is better in those animals that are able to mount a strong stress response. Intense selection for lean tissue growth during the last decades has concomitantly reduced cortisol production, which may be responsible for the negative effects of selection on piglet survival. One strategy to improve robustness is to select animals with higher HPA axis activity. Several sources of genetic polymorphism have been described in the HPA axis. Hormone production by the adrenal cortices under stimulation by adrenocorticotropin hormone is a major source of individual differences. Several candidate genes have been identified by genomic studies and are currently under investigation. Bioavailability of hormones as well as receptor and post-receptor mechanisms are also subject to individual variation. Integration of these different sources of genetic variability will allow the development of a model for marker-assisted selection to improve animal robustness without negative side effects on production traits.

Epistatic analysis of carcass characteristics in pigs reveals genomic interactions between quantitative trait loci attributable to additive and dominance genetic effects.

The present study focused on the identification of epistatic QTL pairs for body composition traits (carcass cut, lean tissue, and fat tissue weights) measured at slaughter weight (140 kg of BW) in a 3-generation full-sib population developed by crossing Pietrain sires with a crossbred dam line. Depending on the trait, phenotypic observations were available for 306 to 315 F(2) animals. For the QTL analysis, 386 animals were genotyped for 88 molecular markers covering chromosomes SSC1, SSC2, SSC4, SSC6, SSC7, SSC8, SSC9, SSC10, SSC13, and SSC14. In total, 23 significant epistatic QTL pairs were identified, with the additive x additive genetic interaction being the most prevalent. Epistatic QTL were identified across all chromosomes except for SSC13, and epistatic QTL pairs accounted for between 5.8 and 10.2% of the phenotypic variance. Seven epistatic QTL pairs were between QTL that resided on the same chromosome, and 16 were between QTL that resided on different chromosomes. Sus scrofa chromosome 1, SSC2, SSC4, SSC6, SSC8, and SSC9 harbored the greatest number of epistatic QTL. The epistatic QTL pair with the greatest effect was for the entire loin weight between 2 locations on SSC7, explaining 10.2% of the phenotypic variance. Epistatic associations were identified between regions of the genome that contain the IGF-2 or melanocortin-4 receptor genes, with QTL residing in other genomic locations. Quantitative trait loci in the region of the melanocortin-4 receptor gene and on SSC7 showed significant positive dominance effects for entire belly weight, which were offset by negative dominance x dominance interactions between these QTL. In contrast, the QTL in the region of the IGF-2 gene showed significant negative dominance effects for entire ham weight, which were largely overcompensated for by positive additive x dominance genetic effects with a QTL on SSC9. The study shows that epistasis is of great importance for the genomic regulation of body composition in pigs and contributes substantially to the variation in complex traits.

Genetic parameters of piglet survival and birth weight from a two-generation crossbreeding experiment under outdoor conditions designed to disentangle direct and maternal effects.

Multivariate Bayesian linear-threshold models were used to estimate genetic parameters of peri- and postnatal piglet survival and individual birth weight of piglets reared under outdoor conditions. Data of 21,835 individual piglet observations were available from a 2-generation crossbreeding experiment selected for direct and maternal genetic effects of postnatal piglet survival on piglet and dam levels, respectively. In the first generation, approximately one-half of the Landrace sires used were selected for large or average breeding values of maternal genetic effects on postnatal piglet survival, whereas in the second generation the Large White sires used were selected for direct genetic effects of the same trait. Estimates of direct and maternal heritability were 0.21 and 0.15, 0.24 and 0.14, and 0.36 and 0.28 for piglet survival at birth and during the nursing period, and individual birth weight, respectively. In particular, direct heritabilities are substantially larger than those from the literature estimated for indoor-reared piglets, suggesting that genetic effects of these traits are substantially greater under outdoor conditions. Direct or maternal genetic correlations between survival traits or with birth weight were small (ranging from 0.06 to 0.17), indicating that peri- and postnatal survival are genetically under rather different control, and survival was only slightly positively influenced by birth weight. There were significant (P < 0.05) negative genetic correlations between direct and maternal genetic effects within each of the analyzed traits ranging from -0.36 to -0.45, which have to be considered when selecting for piglet survival. Adjustment of traits for litter size or inclusion of genetic groups showed insignificant effects on the magnitude of the estimated genetic parameters. The magnitude of genetic parameters suggested that there is substantial potential for genetic improvement of survival traits and birth weight in direct and maternal genetic effects, especially when piglets are kept under outdoor conditions.

Quantitative trait loci for chemical body composition traits in pigs and their positional associations with body tissues, growth and feed intake.

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F(2) animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth.

Genotype by environment interaction for litter size in pigs as quantified by reaction norms analysis.

A Bayesian procedure was used to estimate linear reaction norms (i.e. individual G × E plots) on 297 518 litter size records of 121 104 sows, daughters of 2040 sires, recorded on 144 farms in North and Latin America, Europe, Asia and Australia. The method allowed for simultaneous estimation of all parameters involved. The analysis was carried out on three subsets, comprising (i) parity 1 records of 33 641 sows of line B, (ii) all parity records of 52 120 sows of line B and (iii) all parity records of 121 104 sows of lines A, B and A × B. Estimated heritabilities ranged from 0.09 to 0.10 (smallest to largest subset) for the intercept of the reaction norms, and were 0.15, 0.08 and 0.02 (ditto) for the slope. Estimated genetic correlations between intercept and slope were -0.09, +0.26 and +0.69 (ditto). The three subsets therefore showed a progressively lower genetic component to environmental sensitivity, and progressively less re-ranking of genotypes across the environmental (herd-year-season) range. In a genetic evaluation that does not include reaction norms in the statistical model, part of the G × E effect remains confounded with the additive genetic effect, which may lead to errors in the estimates of the additive genetic effect; the reaction norms model removes this confounding. The intercept estimates from the largest data subset show correlations with litter size estimated breeding values (EBV) from routine genetic evaluation (without reaction norms included) of 0.78 to 0.85 for sows with one to seven litter records, and 0.75 for sires. Hence, including reaction norms in genetic evaluation would increase the reliability of the EBV of young selection candidates without own performance or progeny data by considerably more than 100 × (1/0.75-1) = 33%. Reaction norm slope estimates turn out to be very demanding statistics; environmental sensitivity must therefore be classified as a 'hard-to-measure' trait.

Bayesian analysis of genetic associations of skin lesions and behavioural traits to identify genetic components of individual aggressiveness in pigs.

There is increasing interest in genetic selection against behavioural traits that impact negatively on welfare and productivity in commercial livestock production. Post-mixing aggressiveness in pigs shows wide phenotypic variation, affects health, welfare and growth performance and is a routine feature of production. A Bayesian approach was used to estimate the heritability of three traits associated with aggressiveness in pigs during the 24 h post-mixing; duration in reciprocal aggression, and in receipt of, or delivery of non-reciprocal aggression (NRA). For the purposes of genetic selection, recording aggressive behaviour is excessively labour intensive. The genetic correlations were quantified between the behavioural traits and an easily measurable indicator trait; the number of skin lesions following mixing (lesion score, LS). The heritabilities for the three behavioural traits ranged from 0.17 to 0.46 (receipt of NRA and reciprocal aggression respectively). The duration in reciprocal aggression and in delivery of NRA showed a strong genetic correlation (r g = 0.79 with 95% Bayesian credibility interval of 0.62-0.94). The genetic correlation between LS and these two behaviours indicated that selection on breeding values of LS could be used to reduce aggressiveness. The duration in receipt of NRA appeared to be regulated by different genes or genomic effects compared with the other behavioural traits and LS. Although duration in receipt of NRA was not genetically associated with LS, it was lowly but significantly environmentally associated with the residuals of central and caudal LS (r e = 0.28-0.32), indicating that pigs that received NRA also received bites on the central and caudal third of the body. The pen that the animals were mixed into was found to be a very important factor for the analysed traits, in particular those representing behavioural characteristics. Based on the estimated genetic parameters, it is concluded that selection on breeding values for reduced LS (especially central LS) is expected to reduce reciprocal aggression and the delivery of NRA but will not change the receipt of NRA directly.

Associations of DNA markers with meat quality traits in pigs with emphasis on drip loss.

Phenotypic information on 1155 market pigs for several pig meat quality traits, was collected. Genotypes on 12 DNA markers, including RYR1 and PRKAG3 I199V, were also obtained on all pigs to investigate the relationship between genetic markers and meat quality. The RYR1 gene had the highest impact on meat quality, however, several other markers showed significant effects on one or more traits. Animals heterozygous at the RYR1 locus were significantly inferior in almost all meat quality traits, except ultimate pH value, initial conductivity and redness of the meat. Drip loss from case-ready meat (measured from 1 to 7 days post-mortem) was 43% higher for heterozygotes than animals of the stress resistant genotype. The homozygous genotype II at position I199V of the PRKAG3 locus also resulted in less drip loss than genotypes IV and VV, regardless of the method and time of measurement. Furthermore, the favourable genotype related to higher ultimate pH and darker meat. Both loci significantly affected the intercept, linear and quadratic terms of fitted drip loss development curves. The favourable genotypes showed a lower drip loss after one day of measurement and a slower increase and a more linear development over time. Whilst the RYR1 and PRKAG3 markers influenced numerous meat quality traits, some of the other markers were also found to have significant effects on one or two meat quality traits. Markers at MC4R and HMGA1 loci significantly affected drip loss, whereas LDHA, CAST (Hpy188I) and ATP2A1 influenced pH value. In addition, the marker ATP2A1 was associated with variation in intramuscular fat content in M. longissimus dorsi. GLUT4 affected temperature 45min post-mortem and several markers (MC4R, LDHA, GLUT4, HMGA1, CAST (Hpy188I and PvuII)) influenced one or two of the different colour measurements. The markers at MC4R, CKM, AGRP, PRKAG3, and HMGA1 loci were tested for their interactions with RYR1 regarding drip loss. Only AGRP showed a significant interaction, but this was based on only a few animals with the homozygous genotype for one allele. Our results suggest that genetic markers provide a useful tool to improve meat quality in pigs independently from RYR1, especially the mutation I199V in the PRKAG3 gene.

Using mechanistic animal growth models to estimate genetic parameters of biological traits.

Mechanistic animal growth models can incorporate a description of the genotype as represented by underlying biological traits that aim to specify the animal's genetic potential for performance, independent from the environmental factors captured by the models. It can be argued that these traits may therefore be more closely associated to genetic potential, or components of genetic merit that are more robust across environments, than the environmentally dependent phenotypic traits currently used for genetic evaluation. The prediction of merit for underlying biological traits can be valuable for breeding and development of selection strategies across environments.Model inversion has been identified as a valid method for obtaining estimates of phenotypic and genetic components of the biological traits representing the genotype in the mechanistic model. The present study shows how these estimates were obtained for two existing pig breeds based on genetic and phenotypic components of existing performance trait records. Some of the resulting parameter estimates associated with each breed differ substantially, implying that the genetic differences between the breeds are represented in the underlying biological traits. The estimated heritabilities for the genetic potentials for growth, carcass composition and feed efficiency as represented by biological traits exceed the heritability estimates of related phenotypic traits that are currently used in evaluation processes for both breeds. The estimated heritabilities for maintenance energy requirements are however relatively small, suggesting that traits associated with basic survival processes have low heritability, provided that maintenance processes are appropriately represented by the model.The results of this study suggest that mechanistic animal growth models can be useful to animal breeding through the introduction of new biological traits that are less influenced by environmental factors than phenotypic traits currently used. Potential value comes from the estimation of underlying biological trait components and the explicit description of their expression across a range of environments as predicted by the model equations.

Quantitative trait loci associated with AutoFOM grading characteristics, carcass cuts and chemical body composition during growth of Sus scrofa.

A three-generation full-sib resource family was constructed by crossing two commercial pig lines. Genotypes for 37 molecular markers covering chromosomes SSC1, SSC6, SSC7 and SSC13 were obtained for 315 F2 animals of 49 families and their parents and grandparents. Phenotypic records of traits including carcass characteristics measured by the AutoFOM grading system, dissected carcass cuts and meat quality characteristics were recorded at 140 kg slaughter weight. Furthermore, phenotypic records on live animals were obtained for chemical composition of the empty body, protein and lipid accretion (determined by the deuterium dilution technique), daily gain and feed intake during the course of growth from 30 to 140 kg body weight. Quantitative trait loci (QTL) detection was conducted using least-squares regression interval mapping. Highest significance at the 0.1% chromosome-wise level was obtained for five QTL: AutoFOM belly weight on SSC1; ham lean-meat weight, percentage of fat of primal cuts and daily feed intake between 60 and 90 kg live weight on SSC6; and loin lean-meat weight on SSC13. QTL affecting daily gain and protein accretion were found on SSC1 in the same region. QTL for protein and lipid content of empty body at 60 kg liveweight were located close to the ryanodine receptor 1 (RYR1) locus on SSC6. On SSC13, significant QTL for protein accretion and feed conversion ratio were detected during growth from 60 to 90 kg. In general, additive genetic effects of alleles originating from the Piétrain line were associated with lower fatness and larger muscularity as well as lower daily gain and lower protein accretion rates. Most of the QTL for carcass characteristics were found on SSC6 and were estimated after adjustment for the RYR1 gene. QTL for carcass traits, fatness and growth on SSC7 reported in the literature, mainly detected in crosses of commercial lines x obese breeds, were not obtained in the present study using crosses of only commercial lines, suggesting that these QTL are not segregating in the analysed commercial lines.

Association between body composition of growing pigs determined by magnetic resonance imaging, deuterium dilution technique, and chemical analysis.

Development of body composition of 440 growing pigs from a three generation full-sib design to identify quantitative trait loci (QTL) was determined by three different methods. Firstly, the non-invasive method deuterium dilution technique (DT), was applied to all pigs in the experiment at six weights 20, 30, 60, 90, 120 and 140kg. Secondly, at each weight class, eight pigs were slaughtered and their entire body chemically analysed (CA). Thirdly, magnetic resonance imaging (MRI) was applied on 16 live pigs at different weights. For the entire empty body (without content of the gastrointestinal tract and bladder), allometric prediction equations to predict body composition from empty body water content measured by DT were derived from chemically analysed serial slaughtered pigs. These equations showed high correlations of 0.92, 0.90 and 0.85 for the contents of body water, fat-free substance as well as protein in fat-free substance, respectively. For the soft tissue (empty body without bones and viscera), allometric prediction equation of body composition based on DT and CA showed correlations of 0.91, 0.88 and 0.82 for water content, fat-free substance, and protein content of fat free substance, respectively. Fat tissue content, fat tissue mass, and lean tissue mass measured by MRI showed allometric relationships to lipid content, lipid mass, and protein mass determined by DT with correlations of 0.98, 0.87, and 0.98, respectively. Lean (measured by MRI) and protein (determined by DT) content of soft tissue was best fitted by a linear-quadratic polynomial and resulted in a correlation of 0.86. Allometric coefficients for change of percentages of chemical components, water (b=-0.036) and protein (b=0.106) in fat-free substance of empty body during growth were similar to those in the literature indicating the consistency of accretion rates of chemical components of the fat-free substance in different studies. Means for protein- and lipid-deposition rates (determined by DT) as well as lean tissue- and fat tissue-deposition rates (measured by MRI) ranged from 95 to 154, 147 to 328, 373 to 420 and 129 to 254g in the different weight ranges. Variation between animals in protein (lean tissue) and lipid (fat tissue) deposition rate was large which can be exploited in order to identify QTL of these traits.

Reallocation of body resources in lactating mice highly selected for litter size.

The present study investigated differences in the allocation patterns of body stores in lactating female mice from a line selected for high litter size at birth (S-line, average litter size of 20) and dams from a nonselected control line (C-line, average litter size of 10). Body weight, litter size, litter weight, and absolute and relative lipid and protein mass were measured at peak lactation (2 wk in lactation) and at weaning (3 wk in lactation). Body size in S-line females has been increased as a correlated effect of selection for high litter size at birth, allowing for larger litters and higher absolute milk production. However, these dams produce larger litters relative to their own body weight. At peak lactation, lipid and protein percentage did not differ between lines. At weaning, S-line females had a higher protein percentage (P < 0.001) and lower lipid percentage (P < 0.05) than C-line females. Apparently, S-line females produce more offspring but at a greater cost to their own metabolism. This process was insufficient to supply the offspring with adequate resources, resulting in reduced (P < 0.0001) pup development and increased (P < 0.0001) preweaning mortality rates.

Quantitative and molecular genetic determination of protein and fat deposition.

After 30 years of selection, breeding of the pig breed sus scrofa Piétrain has resulted in reduced backfat thickness (from 3.2 to 1.9 mm) and increased loin muscle area (40 to 60 cm2) which indicates high genetic determination of these body composition traits. The use of sophisticated quantitative genetic methods that include all genetic relationships of large populations has led to a high response to selection of these traits. Selection on feed intake, lean and fat tissue growth using nonlinear functions to optimise these traits during the entire growth period in a biological model offers the opportunity to further improve total genetic potential. Protein and lipid deposition rates during the entire growth period have to be known for this biological model to be applied; thus knowledge of the genetic background of these traits is of high economic value. With the use of molecular genetic methods, such as candidate gene and genome scan approaches, the identification of genes for obesity and growth can be obtained. In sus scrofa, candidate genes associated with obesity and growth include Leptin Receptor, Melanocortin-4 Receptor, Agouti related protein, Heart fatty acid binding protein 3, and Insulin-like growth factor 2. Some of these candidate genes also explain variation in obesity levels in humans. Initial genome-wide scans have identified quantitative trait loci (QTL) on chromosomes 1, 4, 5, 7 and X for obesity and on chromosomes 1, 4, 7, 8, 13 and 18 for growth. Physiological candidate genes and predispositional QTL for obesity are not always located on the same chromosome; this is known the "polygenic paradox". Use of a nonlinear growth function is recommended in order to give more insight into the physiological regulation of obesity traits. Sus scrofa is an excellent model organism to examine the genetic regulation of obesity. The conservation of DNA sequence and chromosomal segments between sus scrofa and homo sapiens will permit easy transfer of results to human studies.