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.     

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.     

A genome scan for quantitative trait loci affecting male reproductive traits in a White Duroc x Chinese Erhualian resource population

Chinese Erhualian boars have dramatically smaller testes, greater concentrations of circulating androgens, and fewer Sertoli cells than Western commercial breeds. To identify QTL for boar reproductive traits, testicular weight, epididymal weight, seminiferous tubular diameter at 90 and 300 d, and serum testosterone concentration at 300 d were measured in 347 F(2) boars from a White Duroc x Chinese Erhualian cross. A whole genome scan was performed with 183 microsatellites covering 19 porcine chromosomes. A total of 16 QTL were identified on 9 chromosomes, including 1% genome-wide significant QTL for testicular weight at 90 and 300 d and seminiferous tubular diameter at 90 d on SSCX, and for epididymal weight and testosterone concentration at 300 d on SSC7. Two 5% genome-wide significant QTL were detected for testicular weight at 300 d on SSC1 and seminiferous tubular diameter at 300 d on SSC16. Nine suggestive QTL were found on SSC1, 2, 3, 5, 7, 13, and 14. Chinese Erhualian alleles were not systematically favorable for greater reproductive performance. This study confirmed the previous significant QTL for testicular weight on SSCX and for epididymal weight on SSC7, and reported QTL for seminiferous tubular diameter and testosterone concentration at the first time. The observed different QTL for the same trait at different ages reflect the involvement of distinct genes in the development of male reproductive traits.     

A primary screen of the bovine genome for quantitative trait loci affecting carcass and growth traits.

A primary genomic screen for quantitative trait loci (QTL) affecting carcass and growth traits was performed by genotyping 238 microsatellite markers on 185 out of 300 total progeny from a Bos indicus x Bos taurus sire mated to Bos taurus cows. The following traits were analyzed for QTL effects: birth weight (BWT), weaning weight (WW), yearling weight (YW), hot carcass weight (HCW), dressing percentage (DP), fat thickness (FT), marbling score (MAR), longissimus muscle area (LMA), rib bone (RibB), rib fat (RibF), and rib muscle (RibM), and the predicted whole carcass traits, retail product yield (RPYD), fat trim yield (FATYD), bone yield (BOYD), retail product weight (RPWT), fat weight (FATWT), and bone weight (BOWT). Data were analyzed by generating an F-statistic profile computed at 1-cM intervals for each chromosome by the regression of phenotype on the conditional probability of receiving the Brahman allele from the sire. There was compelling evidence for a QTL allele of Brahman origin affecting an increase in RibB and a decrease in DP on chromosome 5 (BTA5). Putative QTL at or just below the threshold for genome-wide significance were as follows: an increase in RPYD and component traits on BTA2 and BTA13, an increase in LMA on BTA14, and an increase in BWT on BTA1. Results provided represent a portion of our efforts to identify and characterize QTL affecting carcass and growth traits.     

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 quantitative trait locus genome scan for porcine muscle fiber traits reveals overdominance and epistasis

Muscle histochemical characteristics are decisive determinants of meat quality. The relative percentage and diameters of the different muscular fiber types influence crucial aspects of meat such as color, tenderness, and ultimate pH. Despite its relevance, however, the information on muscle fiber genetic architecture is scant, because histochemical muscle characterization is a laborious task. Here we report a complete QTL scan of muscle fiber traits in 160 animals from a F(2) cross between Iberian and Landrace pigs using 139 markers. We identified 20 genome regions distributed along 15 porcine chromosomes (SSC1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, and X) with direct and(or) epistatic effects. Epistasis was frequent and some interactions were highly significant. Chromosomes 10 and 11 seemed to behave as hubs; they harbored 2 individual QTL, but also 6 epistatic regions. Numerous individual QTL effects had cryptic alleles, with opposite effects to phenotypic pure breed differences. Many of the QTL identified here coincided with previous reports for these traits in the literature, and there was overlapping with potential candidate genes and previously reported meat quality QTL.     

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.     

A genome scan for quantitative trait loci affecting the length of small intestine in a White Duroc × Chinese Erhualian intercross resource population

The small intestine is a vital organ in animal gastrointestinal system, in which a large variety of nutrients are absorbed. To identify quantitative trait loci (QTL) for the length of porcine small intestine, phenotypic values were measured in 1034 individuals at 240 d from a White Duroc × Chinese Erhualian intercross F₂ population. The length of small intestine showed strong correlation with growth traits and carcass length in the F2 population. A whole‐genome scan was performed based on 183 microsatellites covering the pig genome in the F₂ population. A total of 10 QTL for this trait were identified on 8 pig chromosomes (SSC), including four 1% genome‐wide significant QTL on SSC2, 4, 7 and 8, one 5% genome‐wide significant QTL on SSC12, and five 5% chromosome‐wide significant QTL on SSC5, 7, 13 and 14. The Erhualian alleles were generally associated with shorter length of the small intestine except the alleles on SSC7 and 13. The QTL on SSC4 overlapped with the previously reported QTL for the length of small intestine. Several significant QTL on SSC2, 8, and 12 were consistent with previous reports. The significant QTL detected on SSC7 was reported for the first time. All QTL identified in this study corresponded to the known region significantly associated with growth traits, supporting the important role of the length of small intestine in pig growth.     

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.     

Use of microsatellite markers to detect quantitative trait loci in Yorkshire pigs

To identify genetic markers associated with economic traits in pigs, 157 microsatellite markers were examined in Yorkshire pigs. Thirty eight female Yorkshire pigs were initially examined and six of them were selected as progenitors; half were more than 1.5 standard deviations (SD) above the mean for average daily gain (ADG) and backfat thickness (BFT), and the remaining half were more than 1.5 SD below the mean. These pigs were then mated to male Duroc pigs, and 200 F2 pig offspring were examined for the association of specific alleles with ADG and BFT. To confirm the specific markers identified in the initial analysis, associations of significant markers with economic traits were further examined in 228 additional performance-tested purebred pigs. Twenty-five microsatellite markers were significantly associated with either ADG or BFT, and among these, 17 were associated with both traits. The markers with the highest association to ADG were also associated with BFT. Our study reveals that specific markers could be used to predict economic significance, and confirms several quantitative trait loci (QTL) identified in previous studies. However, further analysis with more closely-spaced microsatellite markers is required to refine predictive values for economic traits and positions of QTL that are reliable for actual phenotypic prediction.     

Genetic analyses and quantitative trait loci detection, using a partial genome scan, for intramuscular fatty acid composition in Scottish Blackface sheep

Genetic parameters for LM fatty acid composition were estimated in Scottish Blackface sheep, previously divergently selected for carcass lean content (LEAN and FAT lines). Furthermore, QTL were identified for the same fatty acids. Fatty acid phenotypic measurements were made on 350 male lambs, at approximately 8 mo of age, and 300 of these lambs were genotyped across candidate regions on chromosomes 1, 2, 3, 5, 14, 18, 20, and 21. Fatty acid composition measurements included in total 17 fatty acids of 3 categories: saturated, monounsaturated, and polyunsaturated. Total i.m. fat content was estimated as the sum of the fatty acids. The FAT line had a greater i.m. fat content and more oleic acid, but less linoleic acid (18:2 n-6) and docosapentaenoic acid (22:5 n-3) than did the LEAN line. Saturated fatty acids were moderately heritable, ranging from 0.19 to 0.29, and total SFA were highly heritable (0.90). Monounsaturated fatty acids were moderately to highly heritable, with cis-vaccenic acid (18:1 n-7) being the most heritable (0.67), and total MUFA were highly heritable (0.73). Polyunsaturated fatty acids were also moderately to highly heritable; arachidonic acid (20:4 n-6) and CLA were the most heritable, with values of 0.60 and 0.48, respectively. The total PUFA were moderately heritable (0.40). The QTL analyses were performed using regression interval mapping techniques. In total, 21 chromosome-wide QTL were detected in 6 out of 8 chromosomal regions. The chromosome-wide, significant QTL affected 3 SFA, 5 MUFA, and 13 PUFA. The most significant result was a QTL affecting linolenic acid (18:3 n-3) on chromosome 2. This QTL segregated in 2 of the 9 families and explained 37.6% of the phenotypic variance. Also, 10 significant QTL were identified on chromosome 21, where 8 out of 10 QTL were segregating in the same families and detected at the same position. The results of this study demonstrate that altering carcass fatness will simultaneously change i.m. fat content and oleic, linoleic, and docosapentaenoic acid content. The heritabilities of the fatty acids indicate opportunities for genetically altering most fatty acids. Moreover, this is the first report of detection of QTL directly affecting fatty acid composition in sheep.     

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.     

A proximal genomic region of mouse chromosome 10 contains quantitative trait loci affecting fatness

Body weight and fatness are quantitative traits of agricultural and medical importance. In previous genome‐wide quantitative trait locus (QTL) analyses, two QTLs for body weight and weight gain at an early postnatal growth period were discovered on mouse chromosome 10 from a gene pool of wild subspecies mice, Mus musculus castaneus. In this study, we developed a congenic strain with an approximately 63‐Mb wild‐derived genomic region on which the two growth QTLs could be located, by recurrent backcrossing to the common inbred strain C57BL/6J. We compared body weights at 1–10 weeks of age, body weight gains at 1–3, 3–6 and 6–10 weeks, internal organ weights and body lengths between the congenic strain developed and C57BL/6J. Unfortunately, no effects of the two growth QTLs on body weights and weight gains were confirmed. However, at least two new QTLs affecting fatness traits were discovered within the introgressed congenic region. The wild‐derived allele at one QTL increased body mass index, whereas at another one it decreased white fat pad weight and adiposity index. Thus, the congenic mouse strain developed here is a useful model animal for understanding the genetic and molecular basis of fat deposition in livestock as well as humans.     

Primary genome scan to identify putative quantitative trait loci for feedlot growth rate, feed intake, and feed efficiency of beef cattle

Feed intake and feed efficiency of beef cattle are economically relevant traits. The study was conducted to identify QTL for feed intake and feed efficiency of beef cattle by using genotype information from 100 microsatellite markers and 355 SNP genotyped across 400 progeny of 20 Angus, Charolais, or Alberta Hybrid bulls. Traits analyzed include feedlot ADG, daily DMI, feed-to-gain ratio [F:G, which is the reciprocal of the efficiency of gain (G:F)], and residual feed intake (RFI). A mixed model with sire as random and QTL effects as fixed was used to generate an F-statistic profile across and within families for each trait along each chromosome, followed by empirical permutation tests to determine significance thresholds for QTL detection. Putative QTL for ADG (chromosome-wise P < 0.05) were detected across families on chromosomes 5 (130 cM), 6 (42 cM), 7 (84 cM), 11 (20 cM), 14 (74 cM), 16 (22 cM), 17 (9 cM), 18 (46 cM), 19 (53 cM), and 28 (23 cM). For DMI, putative QTL that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (93 cM), 3 (123 cM), 15 (31 cM), 17 (81 cM), 18 (49 cM), 20 (56 cM), and 26 (69 cM) in the across-family analyses. Putative across-family QTL influencing F:G that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 3 (62 cM), 5 (129 cM), 7 (27 cM), 11 (16 cM), 16 (30 cM), 17 (81 cM), 22 (72 cM), 24 (55 cM), and 28 (24 cM). Putative QTL influencing RFI that exceeded the chromosome-wise P < 0.05 threshold were detected on chromosomes 1 (90 cM), 5 (129 cM), 7 (22 cM), 8 (80 cM), 12 (89 cM), 16 (41 cM), 17 (19 cM), and 26 (48 cM) in the across-family analyses. In addition, a total of 4, 6, 1, and 8 chromosomes showed suggestive evidence (chromosome-wise, P < 0.10) for putative ADG, DMI, F:G, and RFI QTL, respectively. Most of the QTL detected across families were also detected within families, although the locations across families were not necessarily the locations within families, which is likely because of differences among families in marker informativeness for the different linkage groups. The locations and direction of some of the QTL effects reported in this study suggest potentially favorable pleiotropic effects for the underlying genes. Further studies will be required to confirm these QTL in other populations so that they can be fine-mapped for potential applications in marker-assisted selection and management of beef cattle.     

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.     

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.     

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.     

A directed search in the region of GDF8 for quantitative trait loci affecting carcass traits in Texel sheep

A directed search for QTL affecting carcass traits was carried out in the region of growth differentiation factor 8 (GDF8, also known as myostatin) on ovine chromosome 2 in seven Texel-sired half-sib families totaling 927 progeny. Weights were recorded at birth, weaning, ultrasound scanning, and slaughter. Ultrasonic measures of LM cross-sectional dimensions and s.c. fat above the LM were made, with the same measurements made on the LM after slaughter. Following slaughter, linear measurements of carcass length and width were made on all carcasses, and legs and loins from 540 lambs were dissected. Genotyping was carried out using eight microsatellite markers from FCB128 to RM356 on OAR 2 and analyzed using Haley-Knott regression. There was no evidence for QTL for growth rates or linear carcass traits. There was some evidence for QTL affecting LM dimensions segregating in some sire families, although it was not consistent between ultrasound and carcass measures of the same traits. There was strong and consistent evidence for a QTL affecting muscle and fat traits in the leg that mapped between markers BM81124 and BULGE20 for the four sires that were heterozygous in this region, but not for the three sires that were homozygous. The size of the effect varied across the four sires, ranging from 0.5 to 0.9 of an adjusted SD for weight-adjusted leg muscle traits, and ranging from 0.6 to 1.2 of an adjusted SD for weight-adjusted leg fat traits. The clearest effect shown was for multivariate analysis combining all leg muscle and fat traits analyzed across sires, where the -log(10) probability was 14. Animals carrying the favorable haplotype had 3.3% more muscle and 9.9% less fat in the leg relative to animals carrying other haplotypes. There was evidence for a second peak in the region of marker TEXAN2 for one sire group. It seems that a QTL affecting muscle and fat traits exists within the New Zealand Texel population, and it maps to the region of GDF8 on OAR2.     

Mapping of quantitative trait loci affecting organ weights and blood variables in a broiler layer cross

1. A genome scan was performed to locate genomic regions associated with traits that are known to vary in birds (most commonly broilers) suffering from heart, lung or muscular dysfunction and for weight of the dressed carcass and some internal organs. 2. The F2 population studied was derived from a cross between a broiler and a layer line and consisted of over 460 birds that were genotyped for 101 markers. 3. There was strong support for segregation of quantitative trait loci (QTL) for carcass and organ weights and blood variables. We identified 11 genome-wide significant QTL (most of them for dressed carcass weight) and several genome-wide suggestive QTL. 4. The results point to some genome regions that may be associated with health-related traits and merit further study, with the final aim of identifying linked genetic markers that could be used in commercial breeding programmes to decrease the incidence of muscular and metabolic disorders in broiler populations.