Mapping of quantitative trait loci for flesh colour and growth traits in Atlantic salmon (Salmo salar)

Background

Flesh colour and growth related traits in salmonids are both commercially important and of great interest from a physiological and evolutionary perspective. The aim of this study was to identify quantitative trait loci (QTL) affecting flesh colour and growth related traits in an F2 population derived from an isolated, landlocked wild population in Norway (Byglands Bleke) and a commercial production population.

Methods

One hundred and twenty-eight informative microsatellite loci distributed across all 29 linkage groups in Atlantic salmon were genotyped in individuals from four F2 families that were selected from the ends of the flesh colour distribution. Genotyping of 23 additional loci and two additional families was performed on a number of linkage groups harbouring putative QTL. QTL analysis was performed using a line-cross model assuming fixation of alternate QTL alleles and a half-sib model with no assumptions about the number and frequency of QTL alleles in the founder populations.

Results

A moderate to strong phenotypic correlation was found between colour, length and weight traits. In total, 13 genome-wide significant QTL were detected for all traits using the line-cross model, including three genome-wide significant QTL for flesh colour (Chr 6, Chr 26 and Chr 4). In addition, 32 suggestive QTL were detected (chromosome-wide P < 0.05). Using the half-sib model, six genome-wide significant QTL were detected for all traits, including two for flesh colour (Chr 26 and Chr 4) and 41 suggestive QTL were detected (chromosome-wide P < 0.05). Based on the half-sib analysis, these two genome-wide significant QTL for flesh colour explained 24% of the phenotypic variance for this trait.

Conclusions

A large number of significant and suggestive QTL for flesh colour and growth traits were found in an F2 population of Atlantic salmon. Chr 26 and Chr 4 presented the strongest evidence for significant QTL affecting flesh colour, while Chr 10, Chr 5, and Chr 4 presented the strongest evidence for significant QTL affecting growth traits (length and weight). These QTL could be strong candidates for use in marker-assisted selection and provide a starting point for further characterisation of the genetic components underlying flesh colour and growth.     

Detection of quantitative trait loci for backfat thickness and intramuscular fat content in pigs (Sus scrofa).

In an experimental cross between Meishan and Dutch Large White and Landrace lines, 619 F(2) animals and their parents were typed for molecular markers covering the entire porcine genome. Associations were studied between these markers and two fatness traits: intramuscular fat content and backfat thickness. Association analyses were performed using interval mapping by regression under two genetic models: (1) an outbred line-cross model where the founder lines were assumed to be fixed for different QTL alleles; and (2) a half-sib model where a unique allele substitution effect was fitted within each of the 19 half-sib families. Both approaches revealed for backfat thickness a highly significant QTL on chromosome 7 and suggestive evidence for a QTL at chromosome 2. Furthermore, suggestive QTL affecting backfat thickness were detected on chromosomes 1 and 6 under the line-cross model. For intramuscular fat content the line-cross approach showed suggestive evidence for QTL on chromosomes 2, 4, and 6, whereas the half-sib analysis showed suggestive linkage for chromosomes 4 and 7. The nature of the QTL effects and assumptions underlying both models could explain discrepancies between the findings under the two models. It is concluded that both approaches can complement each other in the analysis of data from outbred line crosses.     

Results of a whole-genome quantitative trait locus scan for growth, carcass composition and meat quality in a porcine four-way cross

A whole-genome quantitative trait locus (QTL) scan for 31 phenotypes related to growth, carcass composition and meat quality was conducted using 1187 progeny of a commercial four-way cross. Animals were genotyped for 198 microsatellite markers that spanned the entire porcine genome. QTL analysis was conducted to extract information from paternal and maternal meioses separately using a rank-based nonparametric approach for half-sib designs. Nine QTL exceeded genome-wide significance: one QTL affecting growth (average daily gain on SSC1), two QTL influencing carcass composition (fatness on SSC3 and muscle mass on SSC15) and six QTL influencing meat quality (tenderness on SSC4 and SSC14; colour on SSC5, SSC6 and SSCX; and conductivity on SSC16). All but one of these coincided with previously reported QTL. In addition, we present evidence for 78 suggestive QTL with a combined false discovery rate of 40%.     

Combined line-cross and half-sib QTL analysis of crosses between outbred lines

Data from an F 2 cross between breeds of livestock are typically analysed by least squares line-cross or half-sib models to detect quantitative trait loci (QTL) that differ between or segregate within breeds. These models can also be combined to increase power to detect QTL, while maintaining the computational efficiency of least squares. Tests between models allow QTL to be characterized into those that are fixed (LC QTL), or segregating at similar (HS QTL) or different (CB QTL) frequencies in parental breeds. To evaluate power of the combined model, data wih various differences in QTL allele frequencies (FD) between parental breeds were simulated. Use of all models increased power to detect QTL. The line-cross model was the most powerful model to detect QTL for FD>0.6. The combined and half-sib models had similar power for FD<0.4. The proportion of detected QTL declared as LC QTL decreased with FD. The opposite was observed for HS QTL. The proportion of CB QTL decreased as FD deviated from 0.5. Accuracy of map position tended to be greatest for CB QTL. Models were applied to a cross of Berkshire and Yorkshire pig breeds and revealed 160 (40) QTL at the 5% chromosome (genome)-wise level for the 39 growth, carcass composition and quality traits, of which 72, 54, and 34 were declared as LC, HS and CB QTL. Fourteen CB QTL were detected only by the combined model. Thus, the combined model can increase power to detect QTL and mapping accuracy and enable characterization of QTL that segregate within breeds.     

Genome-wide QTL analysis of meat quality-related traits in a large F2 intercross between Landrace and Korean native pigs

Background

We conducted a genome-wide linkage analysis to identify quantitative trait loci (QTL) that influence meat quality-related traits in a large F₂ intercross between Landrace and Korean native pigs. Thirteen meat quality-related traits of the m. longissimus lumborum et thoracis were measured in more than 830 F₂ progeny. All these animals were genotyped with 173 microsatellite markers located throughout the pig genome, and the GridQTL program based on the least squares regression model was used to perform the QTL analysis.

Results

We identified 23 genome-wide significant QTL in eight chromosome regions (SSC1, 2, 6, 7, 9, 12, 13, and 16) (SSC for Sus Scrofa) and detected 51 suggestive QTL in the 17 chromosome regions. QTL that affect 10 meat quality traits were detected on SSC12 and were highly significant at the genome-wide level. In particular, the QTL with the largest effect affected crude fat percentage and explained 22.5% of the phenotypic variance (F-ratio = 278.0 under the additive model, nominal P = 5.5 × 10⁻⁵⁵). Interestingly, the QTL on SSC12 that influenced meat quality traits showed an obvious trend for co-localization.

Conclusions

Our results confirm several previously reported QTL. In addition, we identified novel QTL for meat quality traits, which together with the associated positional candidate genes improve the knowledge on the genetic structure that underlies genetic variation for meat quality traits in pigs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-014-0080-6) contains supplementary material, which is available to authorized users.     

Epistatic QTL pairs associated with meat quality and carcass composition traits in a porcine Duroc × Pietrain population

Background

Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.

Methods

Five hundred and eighty five F₂ pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F₂ animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.

Results

A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.

Conclusions

Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes.     

Quantitative trait loci associated with fatness in a broiler–layer cross

An F₂ population established by crossing a broiler male line and a layer line was used to map quantitative trait loci (QTL) affecting abdominal fat weight, abdominal fat percentage and serum cholesterol and triglyceride concentrations. Two genetic models, the line-cross and the half-sib, were applied in the QTL analysis, both using the regression interval method. Three significant QTL and four suggestive QTL were mapped in the line-cross analysis and four significant and four suggestive QTL were mapped in the half-sib analysis. A total of five QTL were mapped for abdominal fat weight, six for abdominal fat percentage and four for triglyceride concentration in both analyses. New QTL associated with serum triglyceride concentration were mapped on GGA5, GGA23 and GG27. QTL mapped between markers LEI0029 and ADL0371 on GGA3 for abdominal fat percentage and abdominal fat weight and a suggestive QTL on GGA12 for abdominal fat percentage showed significant parent-of-origin effects. Some QTL mapped here match QTL regions mapped in previous studies using different populations, suggesting good candidate regions for fine-mapping and candidate gene searches.     

A genome-wide association study of production traits in a commercial population of Large White pigs: evidence of haplotypes affecting meat quality

Background

Numerous quantitative trait loci (QTL) have been detected in pigs over the past 20 years using microsatellite markers. However, due to the low density of these markers, the accuracy of QTL location has generally been poor. Since 2009, the dense genome coverage provided by the Illumina PorcineSNP60 BeadChip has made it possible to more accurately map QTL using genome-wide association studies (GWAS). Our objective was to perform high-density GWAS in order to identify genomic regions and corresponding haplotypes associated with production traits in a French Large White population of pigs.

Methods

Animals (385 Large White pigs from 106 sires) were genotyped using the PorcineSNP60 BeadChip and evaluated for 19 traits related to feed intake, growth, carcass composition and meat quality. Of the 64 432 SNPs on the chip, 44 412 were used for GWAS with an animal mixed model that included a regression coefficient for the tested SNPs and a genomic kinship matrix. SNP haplotype effects in QTL regions were then tested for association with phenotypes following phase reconstruction based on the Sscrofa10.2 pig genome assembly.

Results

Twenty-three QTL regions were identified on autosomes and their effects ranged from 0.25 to 0.75 phenotypic standard deviation units for feed intake and feed efficiency (four QTL), carcass (12 QTL) and meat quality traits (seven QTL). The 10 most significant QTL regions had effects on carcass (chromosomes 7, 10, 16, 17 and 18) and meat quality traits (two regions on chromosome 1 and one region on chromosomes 8, 9 and 13). Thirteen of the 23 QTL regions had not been previously described. A haplotype block of 183 kb on chromosome 1 (six SNPs) was identified and displayed three distinct haplotypes with significant (0.0001 < P < 0.03) associations with all evaluated meat quality traits.

Conclusions

GWAS analyses with the PorcineSNP60 BeadChip enabled the detection of 23 QTL regions that affect feed consumption, carcass and meat quality traits in a LW population, of which 13 were novel QTL. The proportionally larger number of QTL found for meat quality traits suggests a specific opportunity for improving these traits in the pig by genomic selection.     

Genome-wide association analyses for meat quality traits in Chinese Erhualian pigs and a Western Duroc?×?(Landrace × Yorkshire) commercial population

Background

Understanding the genetic mechanisms that underlie meat quality traits is essential to improve pork quality. To date, most quantitative trait loci (QTL) analyses have been performed on F₂ crosses between outbred pig strains and have led to the identification of numerous QTL. However, because linkage disequilibrium is high in such crosses, QTL mapping precision is unsatisfactory and only a few QTL have been found to segregate within outbred strains, which limits their use to improve animal performance. To detect QTL in outbred pig populations of Chinese and Western origins, we performed genome-wide association studies (GWAS) for meat quality traits in Chinese purebred Erhualian pigs and a Western Duroc × (Landrace × Yorkshire) (DLY) commercial population.

Methods

Three hundred and thirty six Chinese Erhualian and 610 DLY pigs were genotyped using the Illumina PorcineSNP60K Beadchip and evaluated for 20 meat quality traits. After quality control, 35 985 and 56 216 single nucleotide polymorphisms (SNPs) were available for the Chinese Erhualian and DLY datasets, respectively, and were used to perform two separate GWAS. We also performed a meta-analysis that combined P-values and effects of 29 516 SNPs that were common to Erhualian, DLY, F₂ and Sutai pig populations.

Results

We detected 28 and nine suggestive SNPs that surpassed the significance level for meat quality in Erhualian and DLY pigs, respectively. Among these SNPs, ss131261254 on pig chromosome 4 (SSC4) was the most significant (P = 7.97E-09) and was associated with drip loss in Erhualian pigs. Our results suggested that at least two QTL on SSC12 and on SSC15 may have pleiotropic effects on several related traits. All the QTL that were detected by GWAS were population-specific, including 12 novel regions. However, the meta-analysis revealed seven novel QTL for meat characteristics, which suggests the existence of common underlying variants that may differ in frequency across populations. These QTL regions contain several relevant candidate genes.

Conclusions

These findings provide valuable insights into the molecular basis of convergent evolution of meat quality traits in Chinese and Western breeds that show divergent phenotypes. They may contribute to genetic improvement of purebreds for crossbred performance.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0120-x) contains supplementary material, which is available to authorized users.     

Genome-wide identification of quantitative trait loci for carcass composition and meat quality in a large-scale White Duroc × Chinese Erhualian resource population

Carcass and meat quality traits are economically important in pigs. In this study, 17 carcass composition traits and 23 meat quality traits were recorded in 1028 F₂ animals from a White Duroc × Erhualian resource population. All pigs in this experimental population were genotyped for 194 informative markers covering the entire porcine genome. Seventy-seven genome-wide significant quantitative trait loci (QTL) for carcass traits and 68 for meat quality were mapped to 34 genomic regions. These results not only confirmed many previously reported QTL but also revealed novel regions associated with the measured traits. For carcass traits, the most prominent QTL was identified for carcass length and head weight at 57 cM on SSC7, which explained up to 50% of the phenotypic variance and had a 95% confidence interval of only 3 cM. Moreover, QTL for kidney and spleen weight and lengths of cervical vertebrae were reported for the first time in pigs. For meat quality traits, two significant QTL on SSC5 and X were identified for both intramuscular fat content and marbling score in the longissimus muscle, while three significant QTL on SSC1 and SSC9 were found exclusively for IMF. Both LM and the semimembranous muscle showed common QTL for colour score on SSC4, 5, 7, 8, 13 and X and discordant QTL on other chromosomes. White Duroc alleles at a majority of QTL detected were favourable for carcass composition, while favourable QTL alleles for meat quality originated from both White Duroc and Erhualian.     

Combined line-cross and half-sib QTL analysis in Duroc–Pietrain population

A Duroc–Pietrain resource population was built to detect quantitative trait loci (QTL) that affect growth, carcass composition, and pork quality. The data were analyzed by applying three least-squares Mendelian models: a line-cross (LC) model, a half-sib (HS) model, and a combined LC and HS model (CB), which enabled the detection of QTL that had fixed, equal, and different allele frequencies for alternate breed alleles, respectively. Permutation tests were performed to determine 5% chromosome-wide and 5% genome-wide threshold values. A total of 40 (137) QTL were detected at the 5% genome-wide (chromosome-wide) level for the 35 traits analyzed. Of the 137 QTL detected, 62 were classified as the LC type (LC-QTL), 47 as the HS type (HS-QTL), and 28 as the CB type (CB-QTL). The results indicate that implementation of a series of model-based framework is not only beneficial to detect QTL, but also provides us with a new and more robust interpretation from which further methodology could be developed. G. Liu and J. J. Kim contributed equally to this work.     

Selection in action: dissecting the molecular underpinnings of the increasing muscle mass of Belgian Blue Cattle

Background

Belgian Blue cattle are famous for their exceptional muscular development or “double-muscling”. This defining feature emerged following the fixation of a loss-of-function variant in the myostatin gene in the eighties. Since then, sustained selection has further increased muscle mass of Belgian Blue animals to a comparable extent. In the present paper, we study the genetic determinants of this second wave of muscle growth.

Results

A scan for selective sweeps did not reveal the recent fixation of another allele with major effect on muscularity. However, a genome-wide association study identified two genome-wide significant and three suggestive quantitative trait loci (QTL) affecting specific muscle groups and jointly explaining 8-21% of the heritability. The top two QTL are caused by presumably recent mutations on unique haplotypes that have rapidly risen in frequency in the population. While one appears on its way to fixation, the ascent of the other is compromised as the likely underlying MRC2 mutation causes crooked tail syndrome in homozygotes. Genomic prediction models indicate that the residual additive variance is largely polygenic.

Conclusions

Contrary to complex traits in humans which have a near-exclusive polygenic architecture, muscle mass in beef cattle (as other production traits under directional selection), appears to be controlled by (i) a handful of recent mutations with large effect that rapidly sweep through the population, and (ii) a large number of presumably older variants with very small effects that rise slowly in the population (polygenic adaptation).

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-796) contains supplementary material, which is available to authorized users.     

QTL for mohair traits in South African Angora goats

The aim of this study was to identify QTL associated with mohair production and quality traits in South African Angora goats. Limited research has been performed on QTL influencing the economically important mohair traits of Angora goats. Twelve half-sib Angora goat families with an average of 58 offspring per sire were genotyped for 88 microsatellites covering 22 autosomes. Phenotypic data was collected at second and third shearing for males and females respectively. A linkage analysis was performed under the half-sib model using the least squared regression approach of GridQTL. Three putative QTL were detected for fleece weight on CHI 2, 5 and 24, which corresponds with the locations of keratin and keratin-associated proteins. This study detected two putative QTL associated with mohair fibre diameter (on CHI 4 and 24, respectively), which is the most important price-determining trait. Four QTL were detected on CHI 8, 13, 18 and 20 which influence both comfort factor and spinning fineness. The variance explained by the QTL ranged between 6.9% for fibre diameter and 33.6% for standard deviation along the length of the staple. These results reveal segregation of QTL influencing mohair production and quality, and contribute to the understanding of the genetic variation of mohair traits.     

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.     

QTL affecting stress response to crowding in a rainbow trout broodstock population

Background

Genomic analyses have the potential to impact selective breeding programs by identifying markers that serve as proxies for traits which are expensive or difficult to measure. Also, identifying genes affecting traits of interest enhances our understanding of their underlying biochemical pathways. To this end we conducted genome scans of seven rainbow trout families from a single broodstock population to identify quantitative trait loci (QTL) having an effect on stress response to crowding as measured by plasma cortisol concentration. Our goal was to estimate the number of major genes having large effects on this trait in our broodstock population through the identification of QTL.

Results

A genome scan including 380 microsatellite markers representing 29 chromosomes resulted in the de novo construction of genetic maps which were in good agreement with the NCCCWA genetic map. Unique sets of QTL were detected for two traits which were defined after observing a low correlation between repeated measurements of plasma cortisol concentration in response to stress. A highly significant QTL was detected in three independent analyses on Omy16, many additional suggestive and significant QTL were also identified. With linkage-based methods of QTL analysis such as half-sib regression interval mapping and a variance component method, we determined that the significant and suggestive QTL explain about 40-43% and 13-27% of the phenotypic trait variation, respectively.

Conclusions

The cortisol response to crowding stress is a complex trait controlled in a sub-sample of our broodstock population by multiple QTL on at least 8 chromosomes. These QTL are largely different from others previously identified for a similar trait, documenting that population specific genetic variants independently affect cortisol response in ways that may result in different impacts on growth. Also, mapping QTL for multiple traits associated with stress response detected trait specific QTL which indicate the significance of the first plasma cortisol measurement in defining the trait. Fine mapping these QTL can lead towards the identification of genes affecting stress response and may influence approaches to selection for this economically important stress response trait.

     

Genetic mapping of quantitative trait loci affecting carcass and meat quality traits in Beijing ducks (Anas platyrhynchos)

Quantitative trait loci (QTL) for carcass and meat quality traits were detected in a sample of 224 progeny from four males in line VI and 12 females in line V of Beijing ducks. These lines were selected for high body weight at 42 days of age (line VI) or high egg production at 360 days of age (line V). Traits were weights of the carcass, head, neck, shanks, wings, legs, thighs, breast, heart, liver, crop, gizzard, abdominal fat (AFW) and skin fat, as well as fat thickness in the tail, and pH value, shear force, drip loss (DL) (%) and cooking loss (CL) (%) of the breast. Using a half-sib analysis with a multiple QTL model, linkage between the carcass and meat quality traits and 95 microsatellite markers was investigated. Eight genome-wide significant QTL for weight of crop, skin fat, liver, neck, shanks, wings, DL were detected on linkage groups CAU4 and CAU6. One genome-wide suggestive QTL and one chromosome-wide significant QTL for weight of breast were found on CAU1 and CAU4 respectively. Fifteen chromosome-wide suggestive QTL influencing weight of AFW, breast, crop, heart, carcass, thighs, liver, shanks, gizzard, fat thickness in tail, DL (%) and CL (%) were mapped on CAU2, CAU4, CAU5, CAU6, CAU7, CAU10 and CAU13. In addition, two linked QTL for weight of liver and DL (%) were located on CAU2 and CAU7 respectively. The detection of QTL in ducks is a step towards identification of genes influencing these traits and their use for genetic improvement in this species.     

Genetic variances, heritabilities and maternal effects on body weight, breast meat yield, meat quality traits and the shape of the growth curve in turkey birds

Background

Turkey is an important agricultural species and is largely used as a meat bird. In 2004, turkey represented 6.5% of the world poultry meat production. The world-wide turkey population has rapidly grown due to increased commercial farming. Due to the high demand for turkey meat from both consumers and industry global turkey stocks increased from 100 million in 1970 to over 276 million in 2004. This rapidly increasing importance of turkeys was a reason to design this study for the estimation of genetic parameters that control body weight, body composition, meat quality traits and parameters that shape the growth curve in turkey birds.

Results

The average heritability estimate for body weight traits was 0.38, except for early weights that were strongly affected by maternal effects. This study showed that body weight traits, upper asymptote (a growth curve trait), percent breast meat and redness of meat had high heritability whereas heritabilities of breast length, breast width, percent drip loss, ultimate pH, lightness and yellowness of meat were medium to low. We found high positive genetic and phenotypic correlations between body weight, upper asymptote, most breast meat yield traits and percent drip loss but percent drip loss was found strongly negatively correlated with ultimate pH. Percent breast meat, however, showed genetic correlations close to zero with body weight traits and upper asymptote.

Conclusion

The results of this analysis and the growth curve from the studied population of turkey birds suggest that the turkey birds could be selected for breeding between 60 and 80 days of age in order to improve overall production and the production of desirable cuts of meat. The continuous selection of birds within this age range could promote high growth rates but specific attention to meat quality would be needed to avoid a negative impact on the quality of meat.     

A genome scan reveals QTL for growth, fatness, leanness and meat quality in a Duroc-Pietrain resource population

We performed a genome-wide QTL scan for production traits in a line cross between Duroc and Pietrain breeds of pigs, which included 585 F(2) progeny produced from 31 full-sib families genotyped with 106 informative microsatellites. A linkage map covering all 18 autosomes and spanning 1987 Kosambi cM was constructed. Thirty-five phenotypic traits including body weight, growth, carcass composition and meat quality traits were analysed using least square regression interval mapping. Twenty-four QTL exceeded the genome-wide significance threshold, while 47 QTL reached the suggestive threshold. These QTL were located at 28 genomic regions on 16 autosomal chromosomes and QTL in 11 regions were significant at the genome-wide level. A QTL affecting pH value in loin was detected on SSC1 between marker-interval S0312-S0113 with strong statistical support (P < 3.0 x 10(-14)); this QTL was also associated with meat colour and conductivity. QTL for carcass composition and average daily gain was also found on SSC1, suggesting multiple QTL. Seventeen genomic segments had only a single QTL that reached at least suggestive significance. Forty QTL exhibited additive inheritance whereas 31 QTL showed (over-) dominance effects. Two QTL for trait backfat thickness were detected on SSC2; a significant paternal effect was found for a QTL in the IGF2 region while another QTL in the middle of SSC2 showed Mendelian expression.     

Fine mapping and imprinting analysis for fatness trait QTLs in pigs

Quantitative trait loci (QTL) for fatness traits were reported recently in an experimental Meishan × Large White and Landrace F₂ cross. To further investigate the regions on pig Chr 2 (SSC2), SSC4, and SSC7, 25 additional markers from these regions were typed on 800 animals (619 F₂ animals, their F₁ parents, and F₀ grandfathers). Compared with the published maps, a modified order of markers was observed for SSC4 and SSC7. QTL analyses were performed both within the half-sib families as well as across families (line cross). Furthermore, a QTL model accounting for imprinting effects was tested. Information content could be increased considerably on all three chromosomes. Evidence for the backfat thickness QTL on SSC7 was increased, and the location could be reduced to a 33-cM confidence interval. The QTL for intramuscular fat on SSC4 could not be detected in this half-sib analysis, whereas under the line cross model a suggestive QTL on a different position on SSC4 was detected. For SSC2, in the half-sib analysis, a suggestive QTL for backfat thickness was detected with the best position at 26 cM. Imprinting analysis, however, revealed a genome-wise, significant, paternally expressed QTL on SSC2 with the best position at 63 cM. Our results suggest that this QTL is different from the previously reported paternally expressed QTL for muscle mass and fat deposition on the distal tip of SSC2p. Received: 15 October 1999 / Accepted: 21 February 2000     

Quantitative trait loci for performance traits in a broiler × layer cross

An F₂ resource population, derived from a broiler × layer cross, was used to map quantitative trait loci (QTL) for body weights at days 1, 35 and 41, weight gain, feed intake, feed efficiency from 35 to 41 days and intestinal length. Up to 577 F₂ chickens were genotyped with 103 genetic markers covering 21 linkage groups. A preliminary QTL mapping report using this same population focused exclusively on GGA1. Regression methods were applied to line-cross and half-sib models for QTL interval mapping. Under the line-cross model, eight QTL were detected for body weight at 35 days (GGA2, 3 and 4), body weight at 41 days (GGA2, 3, 4 and 10) and intestine length (GGA4). Under the half-sib model, using sire as common parent, five QTL were detected for body weight at day 1 (GGA3 and 18), body weight at 35 days (GGA2 and 3) and body weight at 41 days (GGA3). When dam was used as common parent, seven QTL were mapped for body weight at day 1 (GGA2), body weight at day 35 (GGA2, 3 and 4) and body weight at day 41 (GGA2, 3 and 4). Growth differences in chicken lines appear to be controlled by a chronological change in a limited number of chromosomal regions.