Line-cross Model Research Articles

Mapping genes for phosphorus utilization and correlated traits using a 4k SNP linkage map in Japanese quail (Coturnix japonica).

A large F2 cross with 920 Japanese quail was used to map QTL for phosphorus utilization, calcium utilization, feed per gain and body weight gain. In addition, four bone ash traits were included, because it is known that they are genetically correlated with the focal trait of phosphorus utilization. Trait recording was done at the juvenile stage of the birds. The individuals were genotyped genome-wide for about 4k SNPs and a linkage map constructed, which agreed well with the reference genome. QTL linkage mapping was performed using multimarker regression analysis in a line cross model. Single marker association mapping was done within the mapped QTL regions. The results revealed several genome-wide significant QTL. For the focal trait phosphorus utilization, a QTL on chromosome CJA3 could be detected by linkage mapping, which was substantiated by the results of the SNP association mapping. Four candidate genes were identified for this QTL, which should be investigated in future functional studies. Some overlap of QTL regions for different traits was detected, which is in agreement with the corresponding genetic correlations. It seems that all traits investigated are polygenic in nature with some significant QTL and probably many other small-effect QTL that were not detectable in this study.

Genetic analysis of an F2 intercross between two strains of Japanese quail provided evidence for quantitative trait loci affecting carcass composition and internal organs

The purpose of this study was to identify genomic regions, quantitative trait loci (QTL), affecting carcass traits on chromosome 1 in an F2 population of Japanese quail. For this purpose, two white and wild strains of Japanese quail (16 birds) were crossed reciprocally and F1 generation (34 birds) was created. The F2 generation was produced by intercrossing of the F1 birds. Phenotypic data including carcass weight, internal organs and carcass parts were collected on F2 animals (422 birds). The total mapping population (472 birds) was genotyped for 8 microsatellite markers on chromosome 1. QTL analysis was performed with interval mapping method applying the line-cross model. Significant QTL were identified for breast weight at 0 (P < 0.01), 172 (P < 0.05) and 206 (P < 0.01), carcass weight at 91 (P < 0.05), carcass fatness at 0 (P < 0.01), pre-stomach weight at 206 (P < 0.01) and uropygial weight gland at 197 (P < 0.01) cM on chromosome 1. There was also evidence for imprinted QTL affecting breast weight (P < 0.01) on chromosome 1. The proportion of the F2 phenotypic variation explained by the significant additive, dominance and imprinted QTL effects ranged from 1.0 to 7.3%, 1.2 to 3.3% and 1.4 to 2.2%, respectively.

Quantitative trait loci underlying hatching weight and growth traits in an F2 intercross between two strains of Japanese quail

A three-generation resource population was developed using two distinct Japanese quail strains, wild and white, to map quantitative trait loci underlying hatching weight and growth traits. Eight pairs of white and wild birds were crossed reciprocally and 34 F1 birds were produced. The F1 birds were intercrossed to generate 422 F2 offspring. All of the animals from three generations (472 birds) were genotyped for eight microsatellite markers on chromosome 1. Liveweight data from hatch to 5 weeks of age were collected on the F2 birds. Quantitative trait loci (QTL) analysis was conducted applying the line-cross model and the least-squares interval mapping approach. The results indicated QTL affecting hatching weight and several growth related traits on chromosome 1. The F2 phenotypic variance explained by the detected additive QTL effects ranged from 1.0 to 3.7 for different traits. Modelling both additive and dominance QTL effects revealed additional QTL with significant dominance mode of action affecting pre-slaughter weight. However, there was no evidence for imprinting (parent-of-origin) effects. The variance due to the reciprocal cross effect ranged between 3.0 and 19.1% for weight at 1 week of age and hatching weight, respectively.

Characterization of QTL for Growth and Meat Quality in Combined Pig QTL Populations

This study was conducted to detect quantitative trait loci (QTL) for thirteen growth and meat quality traits in pigs by combing QTL experimental populations. Two F2 reference populations that were sired by Korea native pig (KNP) and dammed by Landrace (LN) or Yorkshire (YK) were generated to construct linkage maps using 123 genetic markers (mostly microsatellites) and to perform QTL analysis on porcine chromosomes (SSCs) 1, 2, 3, 6, 7, 8, 9, 11, 13, 14, and 15. A set of line-cross models was applied to detect QTL, and a series of lack-of-fit tests between the models was used to characterize inheritance mode of QTL. A total of 23, 11 and 19 QTL were detected at 5% chromosome-wise level for the data sets of KNP×LN, KNP×YK cross and joint sets of the two cross populations, respectively. With the joint data, two Mendelian expressed QTL for live weight and cooking loss were detected on SSC3 and SSC15 at 1% chromosome-wise level, respectively. Another Mendelian expressed QTL was detected for CIE a on SSC7 at 5% genome-wise level. Our results suggest that QTL analysis by combining data from two QTL populations increase power for QTL

QTL Scan for Meat Quality Traits Using High-density SNP Chip Analysis in Cross between Korean Native Pig and Yorkshire

We attempted to generate a linkage map using Illumina Porcine 60K SNP Beadchip genotypes of the F2 offspring from Korean native pig (KNP) crossed with Yorkshire (YS) pig, and to identify quantitative trait loci (QTL) using the line-cross model. Among the genotype information of the 62,136 SNPs obtained from the high-density SNP analysis, 45,308 SNPs were used to select informative markers with allelic frequencies >0.7 between the KNP (n = 16) and YS (n = 8) F0 animals. Of the selected SNP markers, a final set of 500 SNPs with polymorphic information contents (PIC) values of >0.300 in the F2 groups (n = 252) was used for detection of thirty meat quality-related QTL on chromosomes at the 5% significance level and 10 QTL at the 1% significance level. The QTL for crude protein were detected on SSC2, SSC3, SSC6, SSC9 and SSC12; for intramuscular fat and marbling on SSC2, SSC8, SSC12, SSC14 and SSC18; meat color measurements on SSC1, SSC3, SSC4, SSC5, SSC6, SSC10, SSC11, SSC12, SSC16 and SSC18; water content related measurements in pork were detected on SSC4, SSC6, SSC7, SSC10, SSC12 and SSC14. Additional QTL of pork quality traits such as texture, tenderness and pH were detected on SSC6, SSC12, SSC13 and SSC16. The most important chromosomal region of superior pork quality in KNP compared to YS was identified on SSC12. Our results demonstrated that a QTL linkage map of the F2 design in the pig breed can be generated with a selected data set of high density SNP genotypes. The QTL regions detected in this study

Quantitative trait loci analysis for leg weakness-related traits in a Duroc × Pietrain crossbred population

BackgroundLeg weakness issues are a great concern for the pig breeding industry, especially with regard to animal welfare. Traits associated with leg weakness are partly influenced by the genetic background of the animals but the genetic basis of these traits is not yet fully understood. The aim of this study was to identify quantitative trait loci (QTL) affecting leg weakness in pigs.MethodsThree hundred and ten F2 pigs from a Duroc × Pietrain resource population were genotyped using 82 genetic markers. Front and rear legs and feet scores were based on the standard scoring system. Osteochondrosis lesions were examined histologically at the head and the condylus medialis of the left femur and humerus. Bone mineral density, bone mineral content and bone mineral area were measured in the whole ulna and radius bones using dual energy X-ray absorptiometry. A line-cross model was applied to determine QTL regions associated with leg weakness using the QTL Express software.ResultsEleven QTL affecting leg weakness were identified on eight autosomes. All QTL reached the 5% chromosome-wide significance level. Three QTL were associated with osteochondrosis on the humerus end, two with the fore feet score and two with the rear leg score. QTL on SSC2 and SSC3 influencing bone mineral content and bone mineral density, respectively, reached the 5% genome-wide significance level.ConclusionsOur results confirm previous studies and provide information on new QTL associated with leg weakness in pigs. These results contribute towards a better understanding of the genetic background of leg weakness in pigs.

Identification of Carcass and Meat Quality QTL in an F2 Duroc × Pietrain Pig Resource Population Using Different Least-Squares Analysis Models

A three-generation resource population was constructed by crossing pigs from the Duroc and Pietrain breeds. In this study, 954 F2 animals were used to identify quantitative trait loci (QTL) affecting carcass and meat quality traits. Based on results of the first scan analyzed with a line-cross (LC) model using 124 microsatellite markers and 510 F2 animals, 9 chromosomes were selected for genotyping of additional markers. Twenty additional markers were genotyped for 954 F2 animals and 20 markers used in the first scan were genotyped for 444 additional F2 animals. Three different Mendelian models using least-squares for QTL analysis were applied for the second scan: a LC model, a half-sib (HS) model, and a combined LC and HS model. Significance thresholds were determined by false discovery rate (FDR). In total, 50 QTL using the LC model, 38 QTL using the HS model, and 3 additional QTL using the combined LC and HS model were identified (q < 0.05). The LC and HS models revealed strong evidence for QTL regions on SSC6 for carcass traits (e.g., 10th-rib backfat; q < 0.0001) and on SSC15 for meat quality traits (e.g., tenderness, color, pH; q < 0.01), respectively. QTL for pH (SSC3), dressing percent (SSC7), marbling score and moisture percent (SSC12), CIE a* (SSC16), and carcass length and spareribs weight (SSC18) were also significant (q < 0.01). Additional marker and animal genotypes increased the statistical power for QTL detection, and applying different analysis models allowed confirmation of QTL and detection of new QTL.

Progeny-testing of full-sibs IBD in a SSC2 QTL region highlights epistatic interactions for fatness traits in pigs

BackgroundMany QTL have been detected in pigs, but very few of them have been fine-mapped up to the causal mutation. On SSC2, the IGF2-intron3-G3072A mutation has been described as the causative polymorphism for a QTL underlying muscle mass and backfat deposition, but further studies have demonstrated that at least one additional QTL should segregate downstream of this mutation. A marker-assisted backcrossing design was set up in order to confirm the segregation of this second locus, reduce its confidence interval and better understand its mode of segregation.ResultsFive recombinant full-sibs, with genotype G/G at the IGF2 mutation, were progeny-tested. Only two of them displayed significant QTL for fatness traits although four inherited the same paternal and maternal chromosomes, thus exhibiting the same haplotypic contrast in the QTL region. The hypothesis of an interaction with another region in the genome was proposed to explain these discrepancies and after a genome scan, four different regions were retained as potential interacting regions with the SSC2 QTL. A candidate interacting region on SSC13 was confirmed by the analysis of an F2 pedigree, and in the backcross pedigree one haplotype in this region was found to mask the SSC2 QTL effect.ConclusionsAssuming the hypothesis of interactions with other chromosomal regions, the QTL could be unambiguously mapped to a 30 cM region delimited by recombination points. The marker-assisted backcrossing design was successfully used to confirm the segregation of a QTL on SSC2 and, because full-sibs that inherited the same alleles from their two parents were analysed, the detection of epistatic interactions could be performed between alleles and not between breeds as usually done with the traditional Line-Cross model. Additional analyses of other recombinant sires should provide more information to further improve the fine-mapping of this locus, and confirm or deny the interaction identified between chromosomes 2 and 13.

Application of alternative models to identify QTL for growth traits in an F2 Duroc x Pietrain pig resource population

BackgroundA variety of analysis approaches have been applied to detect quantitative trait loci (QTL) in experimental populations. The initial genome scan of our Duroc x Pietrain F2 resource population included 510 F2 animals genotyped with 124 microsatellite markers and analyzed using a line-cross model. For the second scan, 20 additional markers on 9 chromosomes were genotyped for 954 F2 animals and 20 markers used in the first scan were genotyped for 444 additional F2 animals. Three least-squares Mendelian models for QTL analysis were applied for the second scan: a line-cross model, a half-sib model, and a combined line-cross and half-sib model.ResultsIn total, 26 QTL using the line-cross model, 12 QTL using the half-sib model and 3 additional QTL using the combined line-cross and half-sib model were detected for growth traits with a 5% false discovery rate (FDR) significance level. In the line-cross analysis, highly significant QTL for fat deposition at 10-, 13-, 16-, 19-, and 22-wk of age were detected on SSC6. In the half-sib analysis, a QTL for loin muscle area at 19-wk of age was detected on SSC7 and QTL for 10th-rib backfat at 19- and 22-wk of age were detected on SSC15.ConclusionsAdditional markers and animals contributed to reduce the confidence intervals and increase the test statistics for QTL detection. Different models allowed detection of new QTL which indicated differing frequencies for alternative alleles in parental breeds.

QTL for percentage of carcass and carcass parts in a broiler x layer cross

An F2 experimental population, developed from a broiler layer cross, was used in a genome scan of QTL for percentage of carcass, carcass parts, shank and head. Up to 649 F2 chickens from four paternal half-sib families were genotyped with 128 genetic markers covering 22 linkage groups. Total map length was 2630 cM, covering approximately 63% of the genome. QTL interval mapping using regression methods was applied to line-cross and half-sib models. Under the line-cross model, 12 genome-wide significant QTL and 17 suggestive linkages for percentages of carcass parts, shank and head were mapped to 13 linkage groups (GGA1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 14, 18 and 27). Under the paternal half-sib model, six genome-wide significant QTL and 18 suggestive linkages for percentages of carcass parts, shank and head were detected on nine chicken linkage groups (GGA1, 2, 3, 4, 5, 12, 14, 15 and 27), seven of which seemed to corroborate positions revealed by the previous model. Overall, three novel QTL of importance to the broiler industry were mapped (one significant for shank% on GGA3 and two suggestive for carcass and breast percentages on GGA14 and drums and thighs percentage on GGA15). One novel QTL for wings% was mapped to GGA3, six novel QTL (GGA1, 3, 7, 8, 9 and 27) and suggestive linkages (GGA2, 4, and 5) were mapped for head%, and suggestive linkages were identified for back% on GGA2, 11 and 12. In addition, many of the QTL mapped in this study confirmed QTL previously reported in other populations.

A quantitative trait locus for a primary antibody response to keyhole limpet hemocyanin on chicken chromosome 14—Confirmation and candidate gene approach

A QTL involved in the primary antibody response toward keyhole limpet hemocyanin (KLH) was detected on chicken chromosome 14 in the experimental population, which was created by crossing commercial White Leghorn and a Polish native chicken breed (green-legged partridgelike). The current QTL location is a validation of previous experiments pointing to the same genomic location for the QTL linked to a primary antibody response to KLH. An experimental population was typed with microsatellite markers distributed over the chicken chromosome 14. Titers of antibodies binding KLH were measured for all individuals by ELISA. Statistical models applied in the Grid QTL Web-based software were used to analyze the data: a half-sib model, a line-cross model, and combined analysis in a linkage disequilibrium and linkage analysis model. Candidate genes that have been proposed were genotyped with SNP located in genes exons. Statistical analyses of single SNP associations were performed pointing out 2 SNP of an axis inhibitor protein (AXIN1) gene as significantly associated with the trait of an interest.

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

BackgroundFlesh 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.MethodsOne 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.ResultsA 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.ConclusionsA 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.

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

An F(2) resource population, derived from a broiler x 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 F(2) 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.

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.

QTL for microstructural and biophysical muscle properties and body composition in pigs.

BackgroundThe proportion of muscle fibre types and their size affect muscularity as well as functional properties of the musculature and meat quality. We aimed to identify QTL for microstructural muscle properties including muscle fibre size, their numbers and fibre type proportions as well as biophysical parameters of meat quality and traits related to body composition, i.e. pH, conductivity, area of M. longissimus dorsi and lean meat content. A QTL scan was conducted in a porcine experimental population that is based on Duroc and Berlin Miniature Pig.ResultsLeast square regression interval mapping revealed five significant and 42 suggestive QTL for traits related to muscle fibre composition under the line-cross model as well as eight significant and 40 suggestive QTL under the half-sib model. For traits related to body composition and biophysical parameters of meat quality five and twelve significant plus nine and 22 suggestive QTL were found under the line-cross and half-sib model, respectively. Regions with either significant QTL for muscle fibre traits or significant QTL for meat quality and muscularity or both were detected on SSC1, 2, 3, 4, 5, 13, 14, 15, and 16. QTL for microstructural properties explained a larger proportion of variance than did QTL for meat quality and body composition.ConclusionMicrostructural properties of pig muscle and meat quality are governed by genetic variation at many loci distributed throughout the genome. QTL analysis under both, the line-cross and half-sib model, allows detecting QTL in case of fixation or segregation of the QTL alleles among the founder populations and thus provide comprehensive insight into the genetic variation of the traits under investigation. Genomic regions affecting complex traits of muscularity and meat quality as well as microstructural properties might point to QTL that in first instance affect muscle fibre traits and by this in second instance meat quality. Disentangling complex traits in their constituent phenotypes might facilitate the identification of QTL and the elucidation of the pleiotropic nature of QTL effects.

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.

Joint analysis of two breed cross populations in pigs to improve detection and characterization of quantitative trait loci1

The purpose of this study was to develop and implement least squares interval-mapping models for joint analysis of breed cross QTL mapping populations and to evaluate the effect of joint analysis on QTL detected for economic traits in data from two breed crosses in pigs. Data on 26 growth, carcass composition, and meat quality traits from F2 crosses between commercially relevant pig breeds were used: a Berkshire x Yorkshire cross at Iowa State University (ISU) and a Berkshire x Duroc cross at the University of Illinois (UOI). All animals were genotyped for a total of 39 (ISU) and 32 (UOI) markers on chromosomes 2, 6, 13, and 18. Marker linkage maps derived from the individual and joint data were similar with regard to order and relative position, but some differences in absolute distances existed. Maps from the joint data were used in all analyses. The individual and joint data sets were analyzed using several least squares interval-mapping models: line-cross (LC) models with Mendelian and parent-of-origin effects; halfsib models (HS); and combined models (CB) that included LC and HS effects. Lack-of-fit tests between the models were used to characterize QTL for mode of expression and to identify segregation of QTL within parental breeds. A total of 26 (8), 47 (18), and 53 (16) QTL were detected at the 5% chromosome (genome)-wise level in the ISU, UOI, and joint data for the 26 analyzed traits. Of the 53 QTL detected in the joint data, only six were detected in both populations and for many, allele effects differed between the two crosses. Despite the lack of overlap between the two populations, joint analysis resulted in an increase in significance for many QTL, including detection of ten QTL that did not reach significance in either population. Confidence intervals for position also were smaller for several QTL. In contrast, 24 QTL, most of which were detected at chromosome-wise levels in the ISU or UOI population, were not detected in the joint data. Presence of paternally expressed QTL near the IGF2 region of SSC2 was confirmed, with major effects on backfat and loin muscle area, particularly in the UOI population, as well as one or more QTL for carcass composition in the distal arm of Chromosome 6. Results of this study suggest that joint analysis using a range of QTL models increases the power of QTL mapping and QTL characterization, which helps to identify genes for subsequent marker-assisted selection.

Quantitative Trait Loci for Body Weight in Layers Differ from Quantitative Trait Loci Specific for Antibody Responses to Sheep Red Blood Cells

Quantitative trait loci for BW at 4, 6, 8, 12, and 18 wk of age were detected in an experimental F2 cross of layers divergently selected for primary antibody response to SRBC. A negative phenotypic correlation between levels of antibody titers and BW, was reported earlier within founder lines. The entire experimental population was genotyped with 174 microsatellite markers equally distributed over the genome. Two genetic models were applied in the QTL analysis: a half-sib model and a line-cross model, both using the regression interval method. In the half-sib model, 3 QTL for BW at 4 wk of age on chromosomes GGA2, GGA3, and GGA9 were detected. For BW at 6 wk of age, 3 QTL were detected on GGA2, GGA3, and GGA6. For BW at 8 wk of age, a QTL was detected on GGA7, and for BW at 12 and 18 wk of age, a QTL was detected on GGAZ. With the line-cross analysis model, one QTL on GGA7 for BW at 4 wk of age was detected. Two QTL were detected on GGA3 and GGA7 for BW at 6 wk of age, and one on GGA3 was detected for BW for 8 and 12 wk of age. For BW at 18 wk of age, there were no QTL under the line-cross analysis model. The present data suggest that 1) a different set of genes affects the early and the late growth, and 2) genes selected to humoral immune responsiveness are different from genes underlying growth.

Identification of QTLs involved in open-field behavior in young and adult laying hens.

Line differences for open-field behavior in chickens have been observed, and it has been shown that this behavior has a genetic component. The aim of this study was to detect quantitative trait loci (QTL) involved in open-field behavior. For this purpose, open-field behavior was studied at 5 and 29 weeks of age in F(2) hens coming from an intercross between two commercial White Leghorn laying lines selected for egg production traits. Latencies, durations, and frequencies of general activity (sitting, standing, walking, and stepping), defecation, and vocalizations were recorded individually for each bird, and a factor score was calculated. All animals (F(0), F(1), and F(2)) were screened with 180 microsatellite markers. Regression interval mapping was applied using both a paternal half-sib analysis and a line-cross analysis method. For general activity at 5 weeks of age, a significant QTL was detected on GGA4 and a suggestive QTL on GGA2 under the line-cross model. For general activity at 29 weeks of age, a significant QTL was detected on GGA4 and two suggestive QTLs were detected on GGA1 and on GGA10, respectively, also using the line-cross analysis. The QTL on GGA4 at 5 weeks of age did not overlap with the QTL on GGA4 at 29 weeks of age. The current study indicated that open-field behavior in young chickens was regulated by QTL that differ from the QTL for open-field behavior in adult chickens.

Mapping of Quantitative Trait Loci on Porcine Chromosome 7 Using Combined Data Analysis

To further investigate the regions on porcine chromosome 7 that are responsible for economically important traits, phenotypic data from a total of 287 F2 individuals were collected and analyzed from 1998 to 2000. All animals were genotyped for eight microsatellite loci spanning the length of chromosome 7. QTL analysis was performed using interval mapping under the line-cross model. A permutation test was used to establish significance levels associated with QTL effects. Observed QTL effects were (chromosomewide significance, position of maximum significance in centimorgans): Birth weight (<0.01, 3); Carcass length (<0.05, 80); Longissimus muscle area (<0.01, 69); Skin percentage (<0.01, 69); Bone percentage (<0.01, 74); Fat depths at shoulder (<0.05, 54); Mean fat depth (<0.05, 81); Moisture in m. Longissimus Dorsi (<0.05, 88). Additional evidence was also found which suggested QTL for dressing percentage and fat depths at buttock. This study offers confirmation of several QTL affecting growth and carcass traits on SSC7 and provides an important step in the search for the actual major genes involved in the traits of economic interest. (Asian-Aust. J. Anim. Sci. 2004. Vol 17, No. 10 : 1350-1354)