Identification of quantitative trait loci affecting reproduction in pigs

The objective of this research was to identify chromosomal regions harboring QTL affecting reproduction in pigs. A three-generation resource population was developed by crossing low-indexing pigs from a randomly selected control line (C) with high-indexing pigs of a line selected for increased index of ovulation rate and embryonic survival (I). Differences between Lines I and C at Generation 10 were 6.7 ova and 3.3 fetuses at 50 d of gestation and 3.1 fully formed and 1.6 live pigs at birth. Phenotypic data were collected on F2 females, born in three replicates, for ovulation rate (n = 423), age at puberty (n = 295), litter size (n = 370), and number of nipples (n = 428). Litter-size data included number of fully formed, live, stillborn, and mummified pigs. Grandparent, F1, and F2 animals were genotyped for 151 microsatellite markers distributed across all 18 autosomes and the X chromosome. Genotypic data were available on 423 F2 females. Average spacing between markers was 19.3 Kosambi centimorgans. Calculations of logarithms of odds (LOD) scores were by least squares, and fixed effects for sire-dam combination and replicate were included in the models. Genome-wide significance level thresholds of 5% and 10% were calculated using a permutation approach. There was evidence (P < 0.05) for QTL affecting ovulation rate on SSC9, age at puberty on SSC7 and SSC8, number of nipples on SSC8 and SSC11, number of stillborn pigs on SSC5 and SSC13, and number of fully formed pigs on SSC11. There was evidence (P < 0.10) for additional QTL affecting age at puberty on SSC7, SSC8, and SSC12, number born live on SSC11, and number of nipples on SSC1, SSC6, and SSC7. Litter size is lowly heritable and sex-limited. Therefore, accuracy of selection for litter size may be enhanced by marker-assisted selection. Ovulation rate and age at puberty are laborious to measure, and thus marker-assisted selection may provide a practical and efficient method of selection.     

猪繁殖性状QTL基因定位研究进展

哺乳动物的繁殖过程包括卵泡和精子的发育成熟、排卵、受精和受精卵在母体子宫内的发育等一系列过程.在此过程中.机体通过神经内分泌系统,特别是下丘脑-垂体-卵泡轴分泌各种激素进行精确的调控.其中任何影响某一步骤的体内或体外因素.都会使动物最终的性能表现发生改变.另外,猪繁殖性状的遗传力一般都较低,如窝产仔数的平均遗传力只有0.1 0(表1)[1]     

Detection of quantitative trait loci for fat androstenone levels in pigs

A QTL analysis of fat androstenone levels from a three-generation experimental cross between Large White and Meishan pig breeds was carried out. A total of 485 F2 males grouped in 24 full-sib families, their 29 parents and 12 grandparents were typed for 137 markers distributed over the entire porcine genome. The F2 male population was measured for fat androstenone levels at 100, 120, 140, and 160 d of age and at slaughter around 80 kg liveweight. Statistical analyses were performed using two interval mapping methods: a line-cross (LC) regression method, which assumes alternative alleles are fixed in founder lines, and a half- full-sib (HFS) maximum likelihood method, where allele substitution effects were estimated within each half- and full-sib family. Both methods revealed genomewide significant gene effects on chromosomes 3, 7, and 14. The QTL explained, respectively, 7 to 11%, 11 to 15%, and 6 to 8% of phenotypic variance. Three additional significant QTL explaining 4 to 7% of variance were detected on chromosomes 4 and 9 using LC method and on chromosome 6 using HFS method. Suggestive QTL were also obtained on chromosomes 2, 10, 11, 13, and 18. Meishan alleles were associated with higher androstenone levels, except on chromosomes 7, 10, and 13, although 10 and 13 additive effects were near zero. The QTL had essentially additive effects, except on chromosomes 4, 10, and 13. No evidence of linked QTL or imprinting effects on androstenone concentration could be found across the entire porcine genome. The steroid chromosome P450 21-hydroxylase (CYP21) and cytochrome P450 cholesterol side chain cleavage subfamily XIA (CYP11A) loci were investigated as possible candidate genes for the chromosome 7 QTL. No mutation of coding sequence has been found for CYP21. Involvement of a candidate regulatory mutation of CYP11A gene proposed by others can be excluded in our animals.     

A whole-genome scan for quantitative trait loci affecting teat number in pigs

A whole-genome scan was conducted using 132 microsatellite markers to identify chromosomal regions that have an effect on teat number. For this purpose, an experimental cross between Chinese Meishan pigs and five commercial Dutch pig lines was used. Linkage analyses were performed using interval mapping by regression under line cross models including a test for imprinting effects. The whole-genome scan revealed highly significant evidence for three quantitative trait loci (QTL) affecting teat number, of which two were imprinted. Paternally expressed (i.e., maternally imprinted) QTL were found on chromosomes 2 and 12. A Mendelian expressed QTL was found on chromosome 10. The estimated additive effects showed that, for the QTL on chromosomes 10 and 12, the Meishan allele had a positive effect on teat number, but, for the QTL on chromosome 2, the Meishan allele had a negative effect on teat number. This study shows that imprinting may play an important role in the expression of teat number.     

Interval mapping of growth quantitative trait loci in Japanese Black beef cattle using microsatellite DNA markers and half-sib regression analysis

A confirmatory scan for the regions of bovine chromosome 1 segregating the quantitative trait loci (QTL) influencing birthweight, weaning weight, yearling weight, and preweaning and postweaning average daily gains was performed by genotyping half‐sib progeny of four Japanese Black sires using microsatellite DNA markers. Data were analyzed by generating an F‐statistic every 1 cM on a linkage map by the regression of phenotype on the probabilities of inheriting an allele from the sire after adjusting for the fixed effects of sire, sex, parity and season of birth as well as age as a covariate. Permutation tests at chromosome‐wide significance thresholds were carried out over 10 000 iterations. A significant QTL for birthweight at 114 cM was detected in the sire 2 family. This identification of a birthweight QTL in Japanese Black cattle may be useful for the implementation of marker‐assisted selection.     

Detection and characterization of quantitative trait loci for meat quality traits in pigs.

In an experimental cross between Meishan and Dutch Large White and Landrace lines, 785 F2 animals with carcass information and their parents were typed for molecular markers covering the entire porcine genome. Linkage was studied between these markers and eight meat quality traits. Quantitative trait locus analyses were performed using interval mapping by regression under two genetic models: 1) the line-cross approach, 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 38 half-sib families. The line-cross approach included tests for genomic imprinting and sex-specific QTL effects. In total, three genome-wide significant and 26 suggestive QTL were detected. The significant QTL on chromosomes 3, 4, and 13, affecting meat color, were only detected under the half-sib model. Failure of the line-cross approach to detect the meat color QTL suggests that the founder lines have similar allele frequencies for these QTL. This study provides information on new QTL affecting meat quality traits. It also shows the benefit of analyzing experimental data under different genetic and statistical models.     

A genome scan for quantitative trait loci and imprinted regions affecting reproduction in pigs

Quantitative trait loci for reproductive traits in a three-generation resource population of a cross between low-indexing pigs from a control line and high-indexing pigs from a line selected 10 generations for increased index of ovulation rate and embryonic survival are reported. Phenotypic data were collected in F2 females for birth weight (BWT, n = 428), weaning weight (WWT, n = 405), age at puberty (AP, n = 295), ovulation rate (OR, n = 423), number of fully formed pigs (FF, n = 370), number of pigs born alive (NBA, n = 370), number of mummified pigs (MUM, n = 370), and number of stillborn pigs (NSB, n = 370). Grandparent, F1, and F2 animals were genotyped for 151 microsatellite markers. Sixteen putative QTL (P < 0.10) for reproductive traits were identified in previous analyses of these data with single QTL line-cross models. Data were reanalyzed with multiple QTL models, including imprinting effects. Data also were analyzed with half-sib models. Permutation was used to establish genome-wide significance levels ( = 0.01, 0.05, and 0.10). Thirty-one putative QTL for reproductive traits and two QTL for birth weight were identified (P < 0.10). One Mendelian QTL for FF (P < 0.05), one for NBA (P < 0.05), three for NSB (P < 0.05), three for NN (P < 0.05), seven for AP (P < 0.10), five for MUM (P < 0.10), and one for BWT (P < 0.10) were found. Partial imprinting of QTL affecting OR (P < 0.01), BWT (P < 0.05), and MUM (P < 0.05) was detected. There were four paternally expressed QTL for NN (P < 0.10) and one each for AP (P < 0.05) and MUM (P < 0.10). Maternally expressed QTL affecting NSB (P < 0.10), NN (P < 0.10), and MUM (P < 0.10) were detected. No QTL were detected with half-sib analyses. Multiple QTL models with imprinting effects are more appropriate for analyzing F2 data than single Mendelian QTL line-cross models.     

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

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.     

Power of a genome scan to detect and locate quantitative trait loci in cattle using dense single nucleotide polymorphisms

There is increasing use of dense single nucleotide polymorphisms (SNPs) for whole‐genome association studies (WGAS) in livestock to map and identify quantitative trait loci (QTL). These studies rely on linkage disequilibrium (LD) to detect an association between SNP genotypes and phenotypes. The power and precision of these WGAS are unknown, and will depend on the extent of LD in the experimental population. One complication for WGAS in livestock populations is that they typically consist of many paternal half‐sib families, and in some cases full‐sib families; unless this subtle population stratification is accounted for, many spurious associations may be reported. Our aim was to investigate the power, precision and false discovery rates of WGAS for QTL discovery, with a commercial SNP array, given existing patterns of LD in cattle. We also tested the efficiency of selective genotyping animals. A total of 365 cattle were genotyped for 9232 SNPs. We simulated a QTL effect as well as polygenic and environmental effects for all animals. One QTL was simulated on a randomly chosen SNP and accounted for 5%, 10% or 18% of the total variance. The power to detect a moderate‐sized additive QTL (5% of the phenotypic variance) with 365 animals genotyped was 37% (p < 0.001). Most importantly, if pedigree structure was not accounted for, the number of false positives significantly increased above those expected by chance alone. Selective genotyping also resulted in a significant increase in false positives, even when pedigree structure was accounted for.     

Genetic linkage mapping of quantitative trait loci for behavioral and neuroendocrine stress response traits in pigs

A QTL analysis of behavioral and neuroendocrine responses to a "novel environment" stress was conducted in a three-generation experimental cross between Meishan and Large White pig breeds. A total of 186 F2 males and 182 F2 females were studied for their behavioral and neuroendocrine reactivity to a novel environment test at 6 wk of age. Locomotion, vocalization, and defecation rate, as well as exploration time, were measured for 10 min. Blood samples were taken immediately before and after the test to measure plasma levels of ACTH, cortisol, and glucose. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using two interval mapping methods: a line-cross regression method, where founder lines were assumed to be fixed for different QTL alleles, and a half-/full-sib maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Both methods revealed a highly significant gene effect for poststress cortisol level (P < 0.001) and a significant effect for basal cortisol level (P < 0.05) at the end of the q arm of chromosome 7, explaining, respectively, 20% and 7% of the phenotypic variance. Meishan alleles are associated with higher cortisol levels and are partially dominant (for poststress levels) over Large White alleles. Other significant gene effects on biological measures were detected on chromosomes 1 and 17 (ACTH response to stress), 3, 5, and 8 (glucose levels). The SSC 17 QTL explains 12% of the phenotypic variance of poststress ACTH levels, with a suggestive evidence of imprinting effects. Meishan alleles are associated with lower poststress ACTH levels. Gene effects of low amplitude only were found for behavioral reactivity traits. Considering the effects of stress neuroendocrine systems on energy fluxes and protein deposition, and the importance of stress reactivity for meat quality and animal welfare, these results open new perspectives for pig selection.     

Mapping quantitative trait loci for metabolic and cytological fatness traits of connected F2 crosses in pigs

In the present study 3 connected F(2) crosses were used to map QTL for classical fat traits as well as fat-related metabolic and cytological traits in pigs. The founder breeds were Chinese Meishan, European Wild Boar, and Pietrain with to some extent the same founder animals in the different crosses. The different selection history of the breeds for fatness traits as well as the connectedness of the crosses led to a high statistical power. The total number of F(2) animals varied between 694 and 966, depending on the trait. The animals were genotyped for around 250 genetic markers, mostly microsatellites. The statistical model was a multi-allele, multi-QTL model that accounted for imprinting. The model was previously introduced from plant breeding experiments. The traits investigated were backfat depth and fat area as well as relative number of fat cells with different sizes and 2 metabolic traits (i.e., soluble protein content as an indicator for the level of metabolic turnover and NADP-malate dehydrogenase as an indicator for enzyme activity). The results revealed in total 37 significant QTL on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 14, 17, and 18, with often an overlap of confidence intervals of several traits. These confidence intervals were in some cases remarkably small, which is due to the high statistical power of the design. In total, 18 QTL showed significant imprinting effects. The small and overlapping confidence intervals for the classical fatness traits as well as for the cytological and metabolic traits enabled positional and functional candidate gene identification for several mapped QTL.     

Identification of candidate markers on bovine chromosome 14 (BTA14) under milk production trait quantitative trait loci in Holstein

The objective of this study was to identify single-nucleotide polymorphisms using a bovine chromosome 14 high-density SNP panel after accounting for the effect of DGAT1. Linkage disequilibrium information and sire heterozygosity were used to select markers for linkage analysis on bovine chromosome 14 for milk production traits in 321 Holstein animals. Results show putative milk peaks at 42 and 61 cM, both at p<0.10, a fat yield peak at 42 and 63 cM, both at p<0.05; a protein yield peak at 42 (p<0.01) and 84 cM (p<0.05); fat per cent peaks at 3 (p<0.01) and 29 cM (p<0.05), and a protein per cent peak at 4 cM (p<0.05). Once quantitative trait loci positions were established, allele substitution effects for all markers were evaluated using the same statistical model. Overlaying information between quantitative trait loci (QTL) and allele effect analysis enabled the identification (p<0.01) of 20 SNPs under the milk yield QTL, 2 under both of the fat yield peaks, 8 and 9 under the protein yield peaks, 2 and 6 for the fat per cent peaks and 5 for the protein per cent peak. One SNP in particular, ss61514555:A>C, showed association with 3 of the 5 traits: milk (p=1.59E-04), fat (p=6.88E-05) and protein yields (p=5.76E-05). Overall, combining information from linkage disequilibrium, sire heterozygosity and genetic knowledge of traits enabled the characterization of additional markers with significant associations with milk production traits.     

Use of new immunoglobulin isotype-specific ELISA-systems to detect Salmonella infections in pigs

In Germany, the program for controlling salmonella infections in pigs is based on tests detecting salmonella-lipopolysaccharide (LPS) induced antibodies in meat-juice or blood. These conventional tests which are based on the technology of enzyme-linked immunosorbent assay (ELISA) detect exclusively or mainly immunoglobulin(lg)G antibodies. Meanwhile, novel ELISA systems (WCE-ELISA, 3-Isotype-Screening-ELISA) have been developed, which additionally detect the antibody classes IgM and IgA.This fact enables the registration of fresh salmonella infections (starting with day 5 p.i.) and thus, the distinction between early and older infections.The results show that animals with early salmonella infections appear significantly more often in herds with a high than with a low prevalence. With the newly developed tests this group of animals can be detected much more efficiently and precisely than with the tests used so far. Due to their clearly improved sensitivity the application of the WCE-ELISA and the 3-Isotype-Screening-ELISA in terms of the QS-Salmonella-Monitoring program can therefore significantly improve the selection of farms with potential salmonella excretors. Additionally, the WCE-ELISA can be applied very suitable for the examination of individual animals.     

Transmission disequilibrium test for quantitative trait loci detection in livestock populations

The performance of several transmission disequilibrium tests (TDT) for detection of quantitative trait loci (QTL) in data structures typical of outbred livestock populations were investigated. Factorial mating designs were simulated with 10 sires mated to either 50 or 200 dams, each family having five or eight full sibs. A single marker and QTL, both bi‐allelic, were simulated using a disequilibrium coefficient based on complete initial disequilibrium and 50 generations of recombination [i.e. D = D₀(1 ? θ)⁵⁰], where θ is the recombination fraction between marker and QTL. The QTL explained either 10% (small QTL) or 30% (large QTL) of the genetic variance for a trait with heritability of 0.3. Methods were: TDT for QTL (Q‐TDT; both parents known), 1‐TDT (only one parent known) and sibling‐based TDT (S‐TDT; neither parent known, but sibs available). All were found to be effective tests for association and linkage between the QTL and a tightly linked marker (θ < 0.02) in these designs. For a large QTL, θ = 0.01, and five full sibs per family, the empirical power for Q‐TDT, 1‐TDT and S‐TDT was 0.966, 0.602 and 0.974, respectively, in a large population, versus 0.700, 0.414 and 0.654, respectively, in a small population. For a small QTL effect, θ = 0.01, large population the empirical power of these tests were 0.709, 0.287 and 0.634. The power of Q‐TDT, 1‐TDT and S‐TDT was satisfactory for large populations, for QTL with large effects and for five full sibs per family. The 1‐TDT based on a linear model was more powerful than the normal 1‐TDT. The empirical power for Q‐TDT and 1‐TDT with a linear model was 0.978 and 0.995 respectively. TDT based on analogous linear models, incorporating the polygenic covariance structure, provided only small increases in power compared with the usual TDT for QTL.     

Identification of quantitative trait loci for osteoarthritis of hip joints in dogs

OBJECTIVE: To identify quantitative trait loci (QTL) associated with osteoarthritis (OA) of hip joints of dogs by use of a whole-genome microsatellite scan. ANIMALS: 116 founder, backcross, F1, and F2 dogs from a crossbred pedigree. PROCEDURES: Necropsy scores and an optimized set of 342 microsatellite markers were used for interval mapping by means of a combined backcross and F2 design module from an online statistical program. Breed and sex were included in the model as fixed effects. Age of dog at necropsy and body weight at 8 months of age were also included in the model as covariates. The chromosomal location at which the highest F score was obtained was considered the best estimate of a QTL position. Chromosome-wide significance thresholds were determined empirically from 10,000 permutations of marker genotypes. RESULTS: 4 chromosomes contained putative QTL for OA of hip joints in dogs at the 5% chromosome-wide significance threshold: chromosomes 5, 18, 23, and 31. CONCLUSIONS AND CLINICAL RELEVANCE: Osteoarthritis of canine hip joints is a complex disease to which many genes and environmental factors contribute. Identification of contributing QTL is a strategy to elucidate the genetic mechanisms that underlie this disease. Refinement of the putative QTL and subsequent candidate gene studies are needed to identify the genes involved in the disease process.     

Scaling to account for heterogeneous variances in a Bayesian analysis of broiler quantitative trait loci

A Bayesian method for QTL analysis that is capable of accounting for heterogeneity of variance between sexes, is introduced. The Bayesian method uses a parsimonious model that includes scaling parameters for polygenic and QTL allelic effects per sex. Furthermore, the method employs a reduced animal model to increase computational efficiency. Markov Chain Monte Carlo techniques were applied to obtain estimates of genetic parameters. In comparison with previous regression analyses, the Bayesian method 1) estimates dispersion parameters and polygenic effects, 2) uses individual observations instead of offspring averages, and 3) estimates fixed effect levels and covariates and heterogeneity of variance between sexes simultaneously with other parameters, taking uncertainties fully into account. Broiler data collected in a feed efficiency and a carcass experiment were used to illustrate QTL analysis based on the Bayesian method. The experiments were conducted in a population consisting of 10 full-sib families of a cross between two broiler lines. Microsatellite genotypes were determined on generation 1 and 2 animals and phenotypes were collected on third-generation offspring from mating members from different families. Chromosomal regions that seemed to contain a QTL in previous regression analyses and showed heterogeneity of variance were chosen. Traits analyzed in the feed efficiency experiment were BW at 48 d and growth, feed intake, and feed intake corrected for BW between 23 and 48 d. In the carcass experiment, carcass percentage was analyzed. The Bayesian method was successful in finding QTL in all regions previously detected.     

Microsatellite mapping of quantitative trait loci affecting female reproductive tract characteristics in Meishan x Large White F(2) pigs

A QTL analysis of female reproductive data from a 3-generation experimental cross between Meishan and Large White pig breeds is presented. Six F(1) boars and 23 F(1) sows, progeny of 6 Large White boars and 6 Meishan sows, produced 502 F(2) gilts whose reproductive tract was collected after slaughter at 30 d of gestation. Five traits [i.e., the total weight of the reproductive tract, of the empty uterine horns, of the ovaries (WOV), and of the embryos], as well as the length of uterine horns (LUH), were measured and analyzed with and without adjustment for litter size. Animals were genotyped for a total of 137 markers covering the entire porcine genome. Analyses were carried out based on interval mapping methods, using a line-cross regression and a half-full sib maximum likelihood test. A total of 18 genome-wide significant (P < 0.05) QTL were detected on 9 different chromosomes (i.e., SSC 1, 5, 6, 7, 9, 12, 13, 18, and X). Five genome-wide significant QTL were detected for LUH, 4 for weight of the empty uterine horns and WOV, 2 for total weight of the reproductive tract, and 1 for weight of the embryos. Twenty-two additional suggestive QTL were also detected. The largest effects were obtained for LUH and WOV on SSC13 (9.2 and 7.0% of trait phenotypic variance, respectively). Meishan alleles had both positive (e.g., on SSC7) and negative effects (e.g., on SSC13) on the traits investigated. Moreover, the QTL were generally not fixed in founder breeds, and opposite effects were in some cases obtained in different families. Although reproductive tract characteristics had only a moderate correlation with reproductive performances, most of the major QTL detected in this study were previously reported as affecting female reproduction, generally with reduced significance levels. This study thus shows that focusing on traits with high heritability might help to detect loci involved in low heritability major traits for breeding.     

Detection of quantitative trait loci affecting non-return rate in French dairy cattle

The purpose of this study was to map quantitative trait loci (QTL) influencing female fertility estimated by non-return rate (NRR) in the French dairy cattle breeds Prim'Holstein, Normande and Montbeliarde. The first step was a QTL detection study on NRR at 281 days after artificial insemination on 78 half-sib families including 4993 progeny tested bulls. In Prim'Holstein, three QTL were identified on Bos taurus chromosomes BTA01, BTA02 and BTA03 (p < 0.01), whereas one QTL was identified in Normande on BTA01 (p < 0.05). The second step aimed at confirming these three QTL and refining their location by selecting and genotyping additional microsatellite markers on a sub-sample of 41 families from the three breeds using NRR within 56, 90 and 281 days after AI. Only the three QTL initially detected in Prim'Holstein were confirmed. Moreover, the analysis of NRR within 56, 90 and 281 days after AI allowed us to distinguish two FF QTL on BTA02 in Prim'Holstein, one for NRR56 and one for NRR90. Estimated QTL variance was 18%, 14%, 11.5% and 14% of the total genetic variance, respectively, for QTL mapping to BTA01, BTA02 (NRR90 and NRR56) and BTA03.     

Detection of quantitative trait loci for growth and carcass composition in cattle

The objective of the present study was to detect quantitative trait loci for economically important traits in a family from a Bos indicus x Bos taurus sire. A Brahman x Hereford sire was used to develop a half-sib family (n = 547). The sire was mated to Bos taurus cows. Traits analyzed were birth (kg) and weaning weights (kg); hot carcass weight (kg); marbling score; longissimus area (cm2); USDA yield grade; estimated kidney, pelvic, and heart fat (%); fat thickness (cm); fat yield (%); and retail product yield (%). Meat tenderness was measured as Warner-Bratzler shear force (kg) at 3 and 14 d postmortem. Two hundred and thirty-eight markers were genotyped in 185 offspring. One hundred and thirty markers were used to genotype the remaining 362 offspring. A total of 312 markers were used in the final analysis. Seventy-four markers were common to both groups. Significant QTL (expected number of false-positives < 0.05) were observed for birth weight and longissimus area on chromosome 5, for longissimus area on chromosome 6, for retail product yield on chromosome 9, for birth weight on chromosome 21, and for marbling score on chromosome 23. Evidence suggesting (expected number of false-positives < 1) the presence of QTL was detected for several traits. Putative QTL for birth weight were detected on chromosomes 1, 2, and 3, and for weaning weight on chromosome 29. For hot carcass weight, QTL were detected on chromosomes 10, 18, and 29. Four QTL for yield grade were identified on chromosomes 2, 11, 14, and 19. Three QTL for fat thickness were detected on chromosomes 2, 3, 7, and 14. For marbling score, QTL were identified on chromosomes 3, 10, 14, and 27. Four QTL were identified for retail product yield on chromosomes 12, 18, 19, and 29. A QTL for estimated kidney, pelvic, and heart fat was detected on chromosome 15, and a QTL for meat tenderness measured as Warner-Bratzler shear force at 3 d postmortem was identified on chromosome 20. Two QTL were detected for meat tenderness measured as Warner-Bratzler shear force at 14 d postmortem on chromosomes 20 and 29. These results present a complete scan in all available progeny in this family. Regions underlying QTL need to be assessed in other populations.