Whole-genome QTL scan for ultrasound and carcass merit traits in beef cattle using Bayesian shrinkage method

Fine mapping of quantitative trait loci (QTL) for 16 ultrasound measurements and carcass merit traits that were collected from 418 hybrid steers was conducted using 1207 SNP markers covering the entire genome. These SNP markers were evaluated using a Bayesian shrinkage estimation method and the empirical critical significant thresholds (α = 0.05 and α = 0.01) were determined by permutation based on 3500 permuted datasets for each trait to control the genome-wide type I error rates. The analyses identified a total of 105 QTLs (p < 0.05) for seven ultrasound measure traits including ultrasound backfat, ultrasound marbling and ultrasound ribeye area and 113 QTLs for seven carcass merit traits of carcass weight, grade fat, average backfat, ribeye area, lean meat yield, marbling and yield grade. Proportion of phenotypic variance accounted for by a single QTL ranged from 0.06% for mean ultrasound backfat to 4.83% for carcass marbling (CMAR) score, while proportion of the phenotypic variance accounted for by all significant (p < 0.05) QTL identified for a single trait ranged from 4.54% for carcass weight to 23.87% for CMAR.     

Genome-wide mapping and identification of new quantitative trait loci affecting meat production, meat quality, and carcass traits within a Duroc purebred population

Most QTL detection studies in pigs have been carried out in experimental F(2) populations. However, segregation of a QTL must be confirmed within a purebred population for successful implementation of marker-assisted selection. Previously, QTL for meat quality and carcass traits were detected on SSC 7 in a Duroc purebred population. The objectives of the present study were to carry out a whole-genome QTL analysis (except for SSC 7) for meat production, meat quality, and carcass traits and to confirm the presence of segregating QTL in a Duroc purebred population. One thousand and four Duroc pigs were studied from base to seventh generation; the pigs comprised 1 closed population of a complex multigenerational pedigree such that all individuals were related. The pigs were evaluated for 6 growth traits, 7 body size traits, 8 carcass traits, 2 physiological traits, and 11 meat quality traits, and the number of pigs with phenotypes ranged from 421 to 953. A total of 119 markers were genotyped and then used for QTL analysis. We utilized a pedigree-based, multipoint variance components approach to test for linkage between QTL and the phenotypic values using a maximum likelihood method; the logarithm of odds score and QTL genotypic heritability were estimated. A total of 42 QTL with suggestive linkages and 3 QTL with significant linkages for 26 traits were detected. These included selection traits such as daily BW gain, backfat thickness, loin eye muscle area, and intramuscular fat content as well as correlated traits such as body size and meat quality traits. The present study disclosed QTL affecting growth, body size, and carcass, physiological, and meat quality traits in a Duroc purebred population.     

Genome-wide linkage and QTL mapping in porcine F2 families generated from Pietrain, Meishan and Wild Boar crosses

Three informative pig F₂ families based on European Wild Boar (W), Meishan (M) and Pietrain (P) crosses have been used for genome‐wide linkage and quantitative trait loci (QTL) analysis. Altogether 129 microsatellites, 56 type I loci and 46 trait definitions (specific to growth, fattening, fat deposition, muscling, meat quality, stress resistance and body conformation) were included in the study. In the linkage maps of M × P, W × P and W × M families, average spacing of markers were 18.4, 19.7 and 18.8 cM, the numbers of informative meioses were 582, 534 and 625, and the total lengths of autosomes measured were 27.3, 26.0 and 26.2 Morgan units, respectively. Maternal maps were on average 1.3 times longer than paternal maps. QTLs contributing more than 3% of F₂ phenotypic variance could be identified at p < 0.05 chromosome‐wide level. Differences in the numbers and positions of QTLs were observed between families. Genome‐wide significant QTL effects were mapped for growth and fattening traits on eight chromosomes (1, 2, 4, 13, 14, 17, 18 and X), for fat deposition traits on seven chromosomes (1, 2, 3, 4, 6, 7 and X), for muscling traits on 11 chromosomes (1, 2, 3, 4, 6, 7, 8, 12, 14, 15 and X), for meat quality and stress resistance traits on seven chromosomes (2, 3, 6, 13, 16, 18 and X), and QTLs for body‐conformation traits were detected on 14 chromosomes. Closely correlated traits showed similar QTL profiles within families. Major QTL effects for meat quality and stress resistance traits were found on SSC6 in the interval RYR1‐A1BG in the W × P and M × P families, and could be attributed to segregation of the RYR1 allele T derived from Pietrain, whereas no effect in the corresponding SSC6 interval was found in family W × M, where Wild Boar and Meishan both contributed the RYR1 allele C. QTL positions were mostly similar in two of the three families for body conformation traits and for growth, fattening, fat deposition and muscling traits, especially on SSC4 (interval SW1073‐NGFB). QTLs with large effects were also mapped on SSC7 in the major histocompatibility complex (MHC) (interval CYP21A2‐S0102) and affected body length, weight of head and many other traits. The identification of DNA variants in genes causative for the QTLs requires further fine mapping of QTL intervals and a positional cloning. However, for these subsequent steps, the genome‐wide QTL mapping in F₂ families represents an essential starting point and is therefore significant for animal breeding.     

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.     

Mapping QTL for porcine muscle fibre traits in a White Duroc × Erhualian F2 resource population

Muscle fibre traits are related with meat quality in meat animals. In this study, a whole‐genome scan with 183 microsatellite markers covering the pig genome was performed to identify quantitative trait loci (QTL) for cross‐sectional area, numerical percentage and relative area of type I, IIA and IIB myofibres, fibre number per square centimetre and total fibre number in the longissimus muscle by using 120 F₂ animals in a White Duroc × Erhualian intercross. In total, 20 QTL were mapped on pig chromosomes (SSC) 1, 2, 7, 8, 9, 11, 15, 16 and X, of which eight reached genome‐wide significance levels and explained large proportions (6.53–34.63%) of phenotypic variance. Five QTL detected in this study confirmed the previous QTL reports and the others were detected for the first time. Chinese Erhualian alleles are generally associated with muscle fibre traits favourable for meat quality.     

紫花苜蓿粗灰分与矿质元素含量QTL定位分析

为初步鉴定与紫花苜蓿(Medicago sativa)粗灰分、钾、钙、镁、磷含量调控相关的数量性状基因座(Quantitative trait loci，QTL)和分子标记，本研究用低产早熟苜蓿和高产晚熟苜蓿杂交，构建了由392个个体组成的F₁群体，对这些性状进行3年表型数据测定，且基于前期已构建的高密度遗传连锁图谱开展QTL定位。结果表明：共检测到63个与粗灰分和4种矿质元素含量相关的QTL，分布于22个染色体上，单个QTL的贡献率为2.50%~29.85%；其中重复定位的QTL共8个(qCa-3C-1和qCa-3C-2，qCa-6B-1和qCa-6B-2，qCa-6D-1和qCa-6D-2，qAsh-8B-1和qAsh-8B-2)，共定位的QTL有6个(qP-2C和qK-2C，qP-3A和qMg-3A，qP-6D-3和qMg-6D-2)；经进一步验证，与这些QTL紧密连锁的标记可用于分子标记辅助选择育种。本研究为选育矿质营养更丰富的苜蓿新品种奠定了基础。     

Search for quantitative trait loci affecting growth and carcass traits in a cross population of beef and dairy cattle

A genome scan to detect QTL influencing growth and carcass-related traits was conducted in a Charolais x Holstein crossbred cattle population. Phenotypic measurements related to growth and carcass traits were made on the 235 second-generation crossbred males of this herd (F2 and reciprocal backcrosses), which were born in 4 consecutive annual cohorts. Traits measured in vivo were related to birth dimensions, growth rates, and ultrasound measurements of fat and muscle depth. The animals were slaughtered near a target BW of 550 kg, and a wide range of postmortem traits were measured: visual assessment of carcass conformation and carcass fatness, estimated subcutaneous fat percentage, weights of kidney knob and channel fat, and weights of carcass components after commercial and full-tissue dissections. The whole population, including grandparents, parents, and the crossbred bulls, was genotyped initially for 139 genome-wide microsatellite markers. Twenty-six additional markers were subsequently analyzed to increase marker density on some of the chromosomes where QTL had been initially identified. The linear regression analyses based on the 165 markers revealed a total of 51 significant QTL at the suggestive level, 21 of which were highly significant (F-value >or=9; based on the genome-wide thresholds obtained in the initial scan). A large proportion of the highly significant associations were found on chromosomes 5 and 6. The most highly significant QTL was localized between markers DIK1054 and DIK082 on chromosome 6 and explained about 20% of the phenotypic variance for the total bone proportion estimated after the commercial dissection. In the adjacent marker interval on this chromosome, 2 other highly significant QTL were found that explain about 30% of the phenotypic variance for birth dimension traits (BW and body length at birth). On chromosome 5, the most significant association influenced the lean:bone ratio at the forerib joint and was flanked by markers DIK4782 and BR2936. Other highly significant associations were detected on chromosomes 10 (estimated subcutaneous fat percentage), 11 (total saleable meat proportion), 16 (prehousing growth rate), and 22 (bone proportion at the leg joint). These results provide a useful starting point for the identification of the genes associated with traits of direct interest to the beef industry, using fine mapping or positional candidate gene approaches.     

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 and fine mapping of quantitative trait loci for bone traits on chicken chromosome one

In broiler chickens, bone problems are an important welfare issue that has been linked to genetic selection for rapid growth. The objectives of this study were to identify and fine map quantitative trait loci (QTL) associated with bone traits. The Northeast Agricultural University resource population (NEAURP) being an F(2) population was used in this study, and a total of 17 bone traits were measured. In primary genome scan, the linkage map was constructed with 23 microsatellite markers across the entire chicken chromosome 1. Seventeen QTLs for bone traits were identified and 12 of these were found between LEI0079 and ROS0025 (50.8 cM apart). To fine map the QTLs located between LEI0079 and ROS0025, more markers and more individuals were used and a new partial linkage map was constructed. The confidence intervals for QTLs were sharply narrowed down from 24.5～52.6 to 2.7～17.0 Mb. This study identified chromosome regions harbouring significant QTLs affecting bone traits and showed that the use of more markers and individuals could decrease the confidence interval of QTL effectively. The results provide a useful reference for further candidate gene research and MAS for bone traits.     

A whole genome scan to map QTL for milk production traits and somatic cell score in Canadian Holstein bulls

The detection and mapping of genetic markers linked to quantitative trait loci (QTL) can be utilized to enhance genetic improvement of livestock populations. With the completion of the bovine genome sequence assembly, single nucleotide polymorphisms (SNP) assays spanning the whole bovine genome and research work on large scale identification, validation and analysis of genotypic variation in cattle has become possible. The objective of the present study was to perform a whole genome scan to identify and map QTL affecting milk production traits and somatic cell scores using linkage disequilibrium (LD) regression and 1536 SNP markers. Three and 18 SNP were found to be associated with only milk yield (MY) at a genome and chromosome wise significance (p < 0.05) level respectively. Among the 21 significant SNP, 16 were in a region reported to have QTL for MY in other dairy cattle populations and while the rest five were new QTL finding. Four SNP out of 21 are significant for the milk production traits (MY, fat yield, protein yield (PY), and milk contents) in the present study. Six and nine SNP were associated with PY at a genome and chromosome wise significant (p < 0.05) level respectively. Three and 17 SNP were found to be associated with FY at a genome and chromosome wise significant (p < 0.05) level. Five and seven SNP were mapped with somatic cell score at a genome and chromosome wise significant (p < 0.05) level respectively. The results of this study have revealed QTL for MY, PY, protein percentage, FY, fat percentage, somatic cell score and persistency of milk in the Canadian dairy cattle population. The chromosome regions identified in this study should be further investigated to potentially identify the causative mutations underlying the QTL.     

利用白色杜洛克×二花脸资源家系定位影响猪肉硬实度的QTL

为定位影响猪背最长肌和半膜肌硬实度的数量性状基因座(QTL),本研究测定了白色杜洛克×二花脸资源家系中490头F_2代猪的背最长肌和半膜肌硬实度,检测了3代个体在19条染色体上194个微卫星的基因型,并据此进行了QTL定位分析.共检测到9个QTLs,包括影响背最长肌硬实度的4个QTLs,分别位于SSC1、SSC2、SSC7和SSC10,其中SSC1和SSC7的QTLs达到1%基因组显著水平;影响半膜肌硬实度的5个QTLs分别位于SSC1、SSC7、SSC10、SSC12和SSC14,其中SSC7和SSC14的QTLs分别达到5%和1%基因组显著水平.     

Detection of QTL for greasy fleece weight in sheep using a 50 K single nucleotide polymorphism chip

Genome-wide association studies (GWAS) have introduced an influential tool in the search for quantitative trait loci (QTL) influencing economically important traits in sheep. To identify QTL associated with greasy fleece weight, a GWAS with 50 K single nucleotide polymorphisms (SNPs) was performed in a Baluchi sheep population. Association with greasy fleece weights was tested using the software Plink. The results of our GWAS provided three novel SNP markers and candidate genes associated with greasy fleece weight. A total of three chromosome-wide significant associations were detected for SNP on chromosomes 17 and 20 affecting greasy fleece weight across the four shearing. One of the significant SNP markers was located within ovine known genes namely FAM101A. Further investigation of these identified regions in validation studies will facilitate the identification of strong candidate genes for wool production in sheep.     

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.     

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.     

芒属植物分蘖数性状的QTL定位

芒属植物是一种多年生C₄高大禾草,是一种重要的生物能源作物。分蘖是芒属植物重要的农艺性状之一,在调控其产量方面具有极其重要的作用。以五节芒和荻的种间杂交群体为材料,利用前期已构建的五节芒和荻的种间基因组遗传连锁图谱,结合2014年泰安、2015年泰安和东平3次重复调查的分蘖数表型数据,进行该重要性状的QTL遗传定位研究。结果表明:分蘖数频率分布呈现正态连续分布,符合数量性状遗传的特征;采用MQM复合区间作图法共定位到16个与分蘖数性状相关的QTL,单个QTL可解释的表型变异范围为11.4%~21.5%,LOD值为3.06~6.09。其中,3个QTL在3次定位分析中可重复检测到,qmfTI-2可分别解释12.7%、12.0%和15.5%的表型变异,qmsTI-1可分别解释12.0%、12.1%和19.8%的表型变异,qmsTI-2可分别解释21.5%、20.2%和13.4%的表型变异;3个QTL在2次定位分析中可重复检测到,qmfTI-1、qmfTI-3和qmsTI-4分别解释12.4%和11.4%、13.8%和13.2%、12.1%和14.3%的表型变异。通过对芒属植物分蘖数性状QTL分析,为芒属植物种质资源改良、分子标记辅助选择以及遗传学研究奠定基础。     

Single- and joint-population analyses of two experimental pig crosses to confirm quantitative trait loci on Sus scrofa chromosome 6 and leptin receptor effects on fatness and growth traits

The primary goal of this study was to detect and confirm QTL on SSC6 for growth and fatness traits in 2 experimental F(2) intercrosses: Iberian x Landrace (IB x LR) and Iberian x Meishan (IB x MS), which were used in this study for the first time in a QTL analysis related to productive traits. For this purpose, single- and joint-population analyses with single and bivariate trait models of both populations were performed. The presence of the SSC6 QTL for backfat thickness previously identified in the IB x LR cross was detected in this population with additional molecular information, but also was confirmed in the IB x MS cross. In addition, a QTL affecting BW was detected in both crosses in a similar position to the QTL detected for backfat thickness. This is the first study in which a QTL affecting BW is detected on SSC6 in the IB x LR cross, as well as in the IB x MS resource population. Furthermore, we analyzed a previously described nonsynonymous leptin receptor (LEPR) SNP located in exon 14 (c.2002C > T) for causality with respect to this QTL within both F(2) populations. Our results supported the previously reported association between LEPR alleles and backfat thickness in the IB x LR cross, and this association was also confirmed within the IB x MS cross. An association not reported before between LEPR alleles and BW was identified in both populations.     

Identification of quantitative trait loci for carcass composition and pork quality traits in a commercial finishing cross

A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Piétrain/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4 traits), carcass composition (11 traits), and meat quality (15 traits). Offspring of 8 sires (n = 715) were used for linkage analysis and genotyped for 73 microsatellite markers covering 14 chromosomal regions representing approximately 50% of the pig genome. The regions examined were selected based on previous studies suggesting the presence of QTL affecting carcass composition or meat quality traits. Thirty-two QTL exceeding the 5% chromosome-wise significance level were identified. Among these, 5 QTL affecting 5 different traits were significant at the 1% chromosome-wise level. The greatest significance levels were found for a QTL affecting loin weight on SSC11 and a QTL with an effect on the Japanese color scale score of the loin on SSC4. About one-third of the identified QTL were in agreement with QTL previously reported. Results showed that QTL affecting carcass composition and meat quality traits segregated within commercial lines. Use of these results for marker-assisted selection offers opportunities for improving pork quality by within-line selection.     

Mapping of quantitative trait loci for lactation persistency traits in German Holstein dairy cattle

A whole genome scan to map quantitative trait loci (QTL) for persistency of milk yield (PMY), persistency of fat yield (PFY), persistency of protein yield (PPY) and persistency of milk energy yield (PEY) was performed in a granddaughter design in the German Holstein dairy cattle population. The analysis included 16 paternal half‐sib families with a total of 872 bulls. The analysis was carried out for the first lactation and for the first three lactations combined using univariate weighted multimarker regression. Controlling the false discovery rate across traits and data sets at a level of 0.15 and treating the four persistency traits as different traits revealed 27 significant QTL. A total of 12 chromosomes showed significant QTL effects on a chromosomewise basis. The DGAT1 effect was highly significant for PPY and protein yield. A haplotype analysis using results of previous studies of the same design revealed a co‐segregation of various persistency QTL and QTL affecting health traits like dystocia and stillbirth and functional traits like non‐return rate 90 and somatic cell score.     

Bayesian analysis of quantitative trait loci for boar taint in a Landrace outbred population

The genetic basis of the main components of boar taint was investigated in intact male pigs in a commercial population. We analyzed fat androsten-one and skatole concentrations from 217 males of an outbred Landrace population. Records were normalized using a logarithm transformation and tested for normality using a Wilk-Shapiro test. Bayesian analysis was then used to map QTL in 10 candidate regions previously selected on chromosomes 1, 2, 3, 4, 6, 7, 8, 9, 10, and 13. The criterion for QTL detection was the Bayes factor (BF) between polygenic models with and without QTL effects. Both traits had considerable genetic determination, with posterior means of total heritabilities ranging from 0.59 to 0.73 for androstenone and from 0.74 to 0.89 for skatole. Positive evidence for a fat skatole QTL was detected on SSC6 (BF = 5.16); however, no QTL for androstenone were found in any of the 10 chromosomal regions analyzed. With the detection of a QTL for the fat skatole concentration segregating in this population, marker-assisted selection or even gene-assisted selection could be used once the causal mutation of the QTL was identified.     

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.