Quantitative trait loci for organ weights and adipose fat composition in Jersey and Limousin back‐cross cattle finished on pasture or feedlot

A QTL study of live animal and carcass traits in beef cattle was carried out in New Zealand and Australia. Back‐cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin backgrounds. This paper reports on weights of eight organs (heart, liver, lungs, kidneys, spleen, gastro‐intestinal tract, fat, and rumen contents) and 12 fat composition traits (fatty acid (FA) percentages, saturated and monounsaturated FA subtotals, and fat melting point). The New Zealand cattle were reared and finished on pasture, whilst Australian cattle were reared on grass and finished on grain for at least 180 days. For organ weights and fat composition traits, 10 and 12 significant QTL locations (P < 0.05), respectively, were detected on a genome‐wide basis, in combined‐sire or within‐sire analyses. Seven QTL significant for organ weights were found at the proximal end of chromosome 2. This chromosome carries a variant myostatin allele (F94L), segregating from the Limousin ancestry, and this is a positional candidate for the QTL. Ten significant QTL for fat composition were found on chromosomes 19 and 26. Fatty acid synthase and stearoyl‐CoA desaturase (SCD1), respectively, are positional candidate genes for these QTL. Two FA QTL found to be common to sire groups in both populations were for percentages of C14:0 and C14:1 (relative to all FAs) on chromosome 26, near the SCD1 candidate gene.     

Genetic mapping of quantitative trait loci for meat quality and muscle metabolic traits in cattle

A whole‐genome scan was carried out in New Zealand and Australia to detect quantitative trait loci (QTL) for live animal and carcass composition traits and meat quality attributes in cattle. Backcross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin backgrounds. The New Zealand cattle were reared and finished on pasture, whilst Australian cattle were reared on grass and finished on grain for at least 180 days. This paper reports on meat quality traits (tenderness measured as shear force at 4–5 ages on two muscles as well as associated traits of meat colour, pH and cooking loss) and a number of metabolic traits. For meat quality traits, 18 significant QTL (P < 0.05), located in nine linkage groups, were detected on a genome‐wise basis, in combined‐sire (seven QTL) or within‐sire analyses (11 QTL). For metabolic traits, 11 significant QTL (P < 0.05), located in eight linkage groups, were detected on a genome‐wise basis, in combined‐sire (five QTL) or within‐sire analyses (six QTL). BTA2 and BTA3 had QTL for both metabolic traits and meat quality traits. Six significant QTL for meat quality and metabolic traits were found at the proximal end of chromosome 2. BTA2 and BTA29 were the most common chromosomes harbouring QTL for meat quality traits; QTL for improved tenderness were associated with Limousin‐derived and Jersey‐derived alleles on these two chromosomes, respectively.     

A whole genome scan for QTL affecting milk protein percentage in Italian Holstein cattle, applying selective milk DNA pooling and multiple marker mapping in a daughter design

We report on a complete genome scan for quantitative trait loci (QTL) affecting milk protein percentage (PP) in the Italian Holstein-Friesian cattle population, applying a selective DNA pooling strategy in a daughter design. Ten Holstein-Friesian sires were chosen, and for each sire, about 200 daughters, each from the high and low tails of estimated breeding value for PP, were used to construct milk DNA pools. Sires and pools were genotyped for 181 dinucleotide microsatellites covering all cattle autosomes. Sire marker allele frequencies in the pools were obtained by shadow correction of peak height in the electropherograms. After quality control, pool data from eight sires were used for all subsequent analyses. The QTL heterozygosity estimate was lower than that of similar studies in other cattle populations. Multiple marker mapping identified 19 QTL located on 14 chromosomes (BTA1, 2, 3, 4, 5, 6, 8, 9, 12, 14, 17, 20, 23 and 27). The sires were also genotyped for seven polymorphic sites in six candidate genes (ABCG2, SPP1, casein kappa, DGAT1, GHR and PRLR) located within QTL regions of BTA6, 14 and 20 found in this study. The results confirmed or excluded the involvement of some of the analysed markers as the causative polymorphic sites of the identified QTL. The QTL identified, combined with genotype data of these candidate genes, will help to identify other quantitative trait genes and clarify the complex QTL patterns observed for a few chromosomes. Overall, the results are consistent with the Italian Holstein population having been under long-term selection for high PP.     

Genome-wide association mapping in Norwegian Red cattle identifies quantitative trait loci for fertility and milk production on BTA12

Reproductive performance is a critical trait in dairy cattle. Poor reproductive performance leads to prolonged calving intervals, higher culling rates and extra expenses related to multiple inseminations, veterinary treatments and replacements. Genetic gain for improved reproduction through traditional selection is often slow because of low heritability and negative correlations with production traits. Detection of DNA markers associated with improved reproductive performance through genome-wide association studies could lead to genetic gain that is more balanced between fertility and production. Norwegian Red cattle are well suited for such studies, as very large numbers of detailed reproduction records are available. We conducted a genome-wide association study for non-return rate, fertility treatments and retained placenta using almost 1 million records on these traits and 17 343 genome-wide single-nucleotide polymorphisms. Genotyping costs were minimized by genotyping the sires of the cows recorded and by using daughter averages as phenotypes. The genotyped sires were assigned to either a discovery or a validation population. Associations were only considered to be validated if they were significant in both groups. Strong associations were found and validated on chromosomes 1, 5, 8, 9, 11 and 12. Several of these were highly supported by findings in other studies. The most important result was an association for non-return rate in heifers in a region of BTA12 where several associations for milk production traits have previously been found. Subsequent fine-mapping verified the presence of a quantitative trait loci (QTL) having opposing effects on non-return rate and milk production at 18 Mb. The other reproduction QTL did not have pleiotropic effects on milk production, and these are therefore of considerable interest for use in marker-assisted selection.     

Genome‐wide association mapping for female fertility traits in Danish and Swedish Holstein cattle

A genome‐wide association study was conducted using a mixed model analysis for QTL for fertility traits in Danish and Swedish Holstein cattle. The analysis incorporated 2,531 progeny tested bulls, and a total of 36 387 SNP markers on 29 bovine autosomes were used. Eleven fertility traits were analyzed for SNP association. Furthermore, mixed model analysis was used for association analyses where a polygenic effect was fitted as a random effect, and genotypes at single SNPs were successively included as a fixed effect in the model. The Bonferroni correction for multiple testing was applied to adjust the significance threshold. Seventy‐four SNP‐trait combinations showed chromosome‐wide significance, and five of these were significant genome‐wide. Twenty‐four QTL regions on 14 chromosomes were detected. Strong evidence for the presence of QTL that affect fertility traits were observed on chromosomes 3, 5, 10, 13, 19, 20, and 24. The QTL intervals were generally smaller than those described in earlier linkage studies. The identification of fertility trait‐associated SNPs and mapping of the corresponding QTL in small chromosomal regions reported here will facilitate searches for candidate genes and candidate polymorphisms.     

Mapping of homoeologous chromosome exchanges influencing quantitative trait variation in Brassica napus

Genomic rearrangements arising during polyploidization are an important source of genetic and phenotypic variation in the recent allopolyploid crop Brassica napus. Exchanges among homoeologous chromosomes, due to interhomoeologue pairing, and deletions without compensating homoeologous duplications are observed in both natural B. napus and synthetic B. napus. Rearrangements of large or small chromosome segments induce gene copy number variation (CNV) and can potentially cause phenotypic changes. Unfortunately, complex genome restructuring is difficult to deal with in linkage mapping studies. Here, we demonstrate how high‐density genetic mapping with codominant, physically anchored SNP markers can detect segmental homoeologous exchanges (HE) as well as deletions and accurately link these to QTL. We validated rearrangements detected in genetic mapping data by whole‐genome resequencing of parental lines along with cytogenetic analysis using fluorescence in situ hybridization with bacterial artificial chromosome probes (BAC‐FISH) coupled with PCR using primers specific to the rearranged region. Using a well‐known QTL region influencing seed quality traits as an example, we confirmed that HE underlies the trait variation in a DH population involving a synthetic B. napus trait donor, and succeeded in narrowing the QTL to a small defined interval that enables delineation of key candidate genes.     

Genome Assembly Anchored QTL Map of Bovine Chromosome 14

Bovine chromosome 14 (BTA14) has been widely explored for quantitative trait loci (QTL) and genes related to economically important traits in both dairy and beef cattle. We reviewed more than 40 investigations and anchored 126 QTL to the current genome assembly (Btau 4_0). Using this anchored QTL map, we observed that, in dairy cattle, the region spanning 0 – 10 Mb on BTA14 has the highest density QTL map with a total of 56 QTL, mainly for milk production traits. It is very likely that both somatic cell score (SCS) and clinical mastitis share some common QTL in two regions: 61.48 Mb - 73.84 Mb and 7.86 Mb – 39.55 Mb, respectively. As well, both ovulation rate and twinning rate might share a common QTL region from 34.16 Mb to 65.38 Mb. However, there are no common QTL locations in three pregnancy related phenotypes: non-return rate, pregnancy rate and daughter pregnancy rate. In beef cattle, the majority of QTL are located in a broad region of 15 Mb – 45 Mb on the chromosome. Functional genes, such as CRH, CYP11B1, DGAT1, FABP4 and TG, as potential candidates for some of these QTL, were also reviewed. Therefore, our review provides a standardized QTL map anchored within the current genome assembly, which would enhance the process of selecting positional and physiological candidate genes for many important traits in cattle.     

Confirmation and fine‐mapping of clinical mastitis and somatic cell score QTL in Nordic Holstein cattle

A genome‐wide association study of 2098 progeny‐tested Nordic Holstein bulls genotyped for 36 387 SNPs on 29 autosomes was conducted to confirm and fine‐map quantitative trait loci (QTL) for mastitis traits identified earlier using linkage analysis with sparse microsatellite markers in the same population. We used linear mixed model analysis where a polygenic genetic effect was fitted as a random effect and single SNPs were successively included as fixed effects in the model. We detected 143 SNP‐by‐trait significant associations (P < 0.0001) on 20 chromosomes affecting mastitis‐related traits. Among them, 21 SNP‐by‐trait combinations exceeded the genome‐wide significant threshold. For 12 chromosomes, both the present association study and the previous linkage study detected QTL, and of these, six were in the same chromosomal locations. Strong associations of SNPs with mastitis traits were observed on bovine autosomes 6, 13, 14 and 20. Possible candidate genes for these QTL were identified. Identification of SNPs in linkage disequilibrium with QTL will enable marker‐based selection for mastitis resistance. The candidate genes identified should be further studied to detect candidate polymorphisms underlying these QTL.     

Validating genome‐wide associated signals for clinical mastitis in German Holstein cattle

A validation study for six genomic regions previously identified by a genome‐wide association study for somatic cell score was conducted with data of clinical mastitis in German Holstein cattle. Out of 10 tested SNPs, five on chromosomes 6, 13 and 19 were significantly associated with clinical mastitis (P < 0.05). Three SNPs on chromosomes 6 and 19 had the same direction of effect as those previously reported in the initial genome‐wide association study for somatic cell score. The other two SNPs on chromosome 13 had opposite effects. As well as validating associations within known QTL from previous studies, e.g. chromosomes 6 and 19, novel loci on chromosome 13 were confirmed. Promising candidate genes are, for example: deoxycytidine kinase, immunoglobulin J chain, vitamin D binding protein, forkhead box K2, sodium/hydrogen exchanger 8 and cytoplasmic nuclear factor of activated T‐cells 2. Our confirmation study provides additional evidence for the functional role of the linked genomic regions to immune response. This information can be used as a basis for further functional studies for those potential genes.     

Genome wide QTL mapping to identify candidate genes for carcass traits in Hanwoo (Korean Cattle)

Meat quality traits are the most economically important traits affecting the beef industry in Korea. We performed a whole genome quantitative trait locus (QTL) mapping study of carcass data in Hanwoo Korean cattle. Two hundred sixty-six Hanwoo steers from 65 sires were genotyped using a 10K Affymetrix SNP chip. The average SNP interval across the bovine genome was 1.5Mb. Associations between each individual SNP and four carcass traits [carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling (MAR)] were assessed using a linear mixed model of each trait. Combined linkage and linkage disequilibrium analysis (LDLA) detected six potential QTL on BTA04, 06, 13, 16, 17, and 23 at the chromosome-wise level (P<0.05). Two MAR QTL were detected at 52.2 cM of BTA06 and 46.04 cM of BTA17. We identified three genes (ARAP2, LOC539460, and LOC511424) in the QTL region of BTA06 and seven genes (RPS14, SCARB1, LOC782103, BRI3BP, AACS, DHX37, and UBC) in the QTL region of BTA17. One significant QTL for CWT was detected at 100 cM on BTA04 and the corresponding QTL region spanned 1.7 cM from 99.7 to 101.4 cM. For EMA QTL, one significant QTL was detected at 3.9 cM of BTA23 and the most likely QTL interval was 1.4 cM, placing 15 candidate genes in the marker bracket. Finally, two QTL for BFT were identified at 68 cM on BTA13 and 24 cM on BTA16. The LPIN3 gene, which is functionally associated with lipodystrophy in humans, is located in the BFT QTL on BTA13. Thus, two potential candidate genes, acetoacetyl-CoA synthetase (AACS) and lipin (LPIN), were detected in QTL regions on BTA17 for MAR and BTA13 for BFT, respectively. In conclusion, LDLA analysis can be used to detect chromosome regions harboring QTL and candidate genes with a low density SNP panel, yielding relatively narrow confidence intervals regarding location.     

Genetic and QTL analysis of maize tassel and ear inflorescence architecture

Maize (Zea mays L.) ear inflorescence architecture is directly relevant to grain yield components, and tassel architecture is relevant to hybrid seed production. The objectives of this study were to (1) determine heritabilities and correlations of a comprehensive set of tassel and ear inflorescence architecture traits in a set of (Illinois Low Protein×B73) B73 S₁ families, (2) identify chromosomal positions of QTL affecting tassel and ear architecture, and (3) identify possible candidate genes associated with these QTL. For tassel traits, the number of detected QTL ranged from one to five, and explained between 6.5 and 35.9% of phenotypic variation. For ear traits, the number of detected QTL ranged from one to nine and phenotypic variation explained by those QTL varied between 7.9 and 53.0%. We detected QTL for tassel architecture traits that required calculation of ratios from measured traits. Some of these calculated traits QTL were detected in regions that did not show QTL for the measured traits, suggesting that calculation of ratios may reveal developmentally relevant patterns of tassel architecture. We detected a QTL on chromosome 7 for tassel branch number near the gene ramosa1 (ra1), which is known to control tassel branch number, making ra1 a candidate gene for tassel branch number. We detected QTL for several traits on chromosomes 6, 8, and 9, where no inflorescence architecture genes have been mapped, thus providing initial information towards new gene discovery for control of inflorescence architecture.     

Mapping and fine mapping of quantitative trait loci for the number of vertebrae in a White Duroc × Chinese Erhualian intercross resource population

The number of vertebrae is associated with body size and meat production in pigs. To identify quantitative trait loci (QTL) for the number of vertebrae, phenotypic values were measured in 1029 individuals from a White Duroc × Chinese Erhualian intercross F₂ population. A whole genome scan was performed with 194 microsatellite markers in the F₂ population. Four genome‐wide significant QTL and eight chromosome‐wide significant QTL for the number of vertebrae were identified on pig chromosomes (SSC) 1, 2, 6, 7, 10 and 12. The most significant QTL was detected on SSC7 with a confidence interval of 1 cM, explaining 42.32% of the phenotypic variance in the thoracic vertebral number. The significant QTL on SSC1, 2 and 7 confirmed previous reports. A panel of 276 animals representing seven Western and Chinese breeds was genotyped with 34 microsatellite markers in the SSC7 QTL region. No obvious selective sweep effect was observed in the tested breeds, indicating that intensive selection for enlarged body size in Western commercial breeds did not wipe out the genetic variability in the QTL region. The Q alleles for increased vertebral number originated from both Chinese Erhualian and White Duroc founder animals. A haplotype block of approximately 900 kb was found to be shared by all Q‐bearing chromosomes of F₁ sires except for one distinct Q chromosome. The critical region harbours the newly reported VRTN gene associated with vertebral number. Further investigations are required to confirm whether VRTN or two other positional candidate genes, PROX2 and FOS, cause the QTL effect.     

QTL analysis of white blood cell, platelet and red blood cell-related traits in an F2 intercross between Landrace and Korean native pigs

Haematological traits play important roles in disease resistance and defence functions. The objective of this study was to locate quantitative trait loci (QTL) and the associated positional candidate genes influencing haematological traits in an F₂ intercross between Landrace and Korean native pigs. Eight blood‐related traits (six erythrocyte traits, one leucocyte trait and one platelet trait) were measured in 816 F₂ progeny. All experimental animals were genotyped with 173 informative microsatellite markers located throughout the pig genome. We report that nine chromosomes harboured QTL for the baseline blood parameters: genomic regions on SSC 1, 4, 5, 6, 8, 9, 11, 13 and 17. Eight of twenty identified QTL reached genome‐wide significance. In addition, we evaluated the KIT locus, an obvious candidate gene locus affecting variation in blood‐related traits. Using dense single nucleotide polymorphism marker data on SSC 8 and the marker‐assisted association test, the strong association of the KIT locus with blood phenotypes was confirmed. In conclusion, our study identified both previously reported and novel QTL affecting baseline haematological parameters in pigs. Additionally, the positional candidate genes identified here could play an important role in elucidating the genetic architecture of haematological phenotype variation in swine and in humans.     

Genome-wide scan for bovine twinning rate QTL using linkage disequilibrium

Twinning is a complex trait with negative impacts on health and reproduction, which cause economic loss in dairy production. Several twinning rate quantitative trait loci (QTL) have been detected in previous studies, but confidence intervals for QTL location are broad and many QTL are unreplicated. To identify genomic regions or genes associated with twinning rate, QTL analysis based on linkage combined with linkage disequilibrium (LLD) and individual marker associations was conducted across the genome using high-throughput single nucleotide polymorphism (SNP) genotypes. A total of 9919 SNP markers were genotyped with 200 sires and sons in 19 half-sib North American Holstein dairy cattle families. After SNPs were genotyped, informative markers were selected for genome-wide association tests and QTL searches. Evidence for twinning rate QTL was found throughout the genome. Thirteen markers significantly associated with twinning rate were detected on chromosomes 2, 5 and 14 ( P  < 2.3 × 10⁻⁵). Twenty-six regions on fourteen chromosomes were identified by LLD analysis at P  < 0.0007. Seven previously reported ovulation or twinning rate QTL were supported by results of single marker association or LLD analyses. Single marker association analysis and LLD mapping were complementary tools for the identification of putative QTL in this genome scan.     

Comparative mapping of bovine chromosome 27 with human chromosome 8 near a dairy form QTL in cattle

In the absence of a complete and annotated bovine genome sequence, detailed human-bovine comparative maps are one of the most effective tools for identification of positional candidate genes contributing to quantitative trait loci (QTL) in cattle. In the present study, eight genes from human chromosome 8 were selected for mapping in cattle to improve breakpoint resolution and confirm gene order on the comparative map near the 40 cM region of the BTA27 linkage map where a QTL affecting dairy form had previously been identified. The resulting map identified ADRB3 as a positional candidate gene for the QTL contributing to the dairy form trait based on its estimated position between 40 and 45 cM on the linkage map. It is also a functional candidate gene due to its role in fat metabolism, and polymorphisms in the ADRB3 gene associated with obesity and metabolic disease in humans, as well as, carcass fat in sheep. Further studies are underway to investigate the existence of polymorphisms in the bovine ADRB3 gene and their association with traits related to fat deposition in cattle.     

Quantitative Trait Loci for Interhemispheric Commissure Development and Social Behaviors in the BTBR T+ tf/J Mouse Model of Autism

Background

Autism and Agenesis of the Corpus Callosum (AgCC) are interrelated behavioral and anatomic phenotypes whose genetic etiologies are incompletely understood. We used the BTBR T⁺ tf/J (BTBR) strain, exhibiting fully penetrant AgCC, a diminished hippocampal commissure, and abnormal behaviors that may have face validity to autism, to study the genetic basis of these disorders.

Methods

We generated 410 progeny from an F2 intercross between the BTBR and C57BL/6J strains. The progeny were phenotyped for social behaviors (as juveniles and adults) and commisural morphology, and genotyped using 458 markers. Quantitative trait loci (QTL) were identified using genome scans; significant loci were fine-mapped, and the BTBR genome was sequenced and analyzed to identify candidate genes.

Results

Six QTL meeting genome-wide significance for three autism-relevant behaviors in BTBR were identified on chromosomes 1, 3, 9, 10, 12, and X. Four novel QTL for commissural morphology on chromosomes 4, 6, and 12 were also identified. We identified a highly significant QTL (LOD score = 20.2) for callosal morphology on the distal end of chromosome 4.

Conclusions

We identified several QTL and candidate genes for both autism-relevant traits and commissural morphology in the BTBR mouse. Twenty-nine candidate genes were associated with synaptic activity, axon guidance, and neural development. This is consistent with a role for these processes in modulating white matter tract development and aspects of autism-relevant behaviors in the BTBR mouse. Our findings reveal candidate genes in a mouse model that will inform future human and preclinical studies of autism and AgCC.     

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.     

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: I. egg production traits

A genome scan was performed to detect chromosomal regions that affect egg production traits in reciprocal crosses between two genetically and phenotypically extreme chicken lines: the partially inbred line New Hampshire (NHI) and the inbred line White Leghorn (WL77). The NHI line had been selected for high growth and WL77 for low egg weight before inbreeding. The result showed a highly significant region on chromosome 4 with multiple QTL for egg production traits between 19.2 and 82.1 Mb. This QTL region explained 4.3 and 16.1% of the phenotypic variance for number of eggs and egg weight in the F₂ population, respectively. The egg weight QTL effects are dependent on the direction of the cross. In addition, genome‐wide suggestive QTL for egg weight were found on chromosomes 1, 5, and 9, and for number of eggs on chromosomes 5 and 7. A genome‐wide significant QTL affecting age at first egg was mapped on chromosome 1. The difference between the parental lines and the highly significant QTL effects on chromosome 4 will further support fine mapping and candidate gene identification for egg production traits in chicken.     

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.