Does fructan have a functional role in physiological traits? Investigation by quantitative trait locus mapping

* The role of fructan in growth and drought-stress responses of perennial ryegrass (Lolium perenne) was investigated in an F(2) mapping family that segregates for carbohydrate metabolism. * A quantitative trait locus approach was used to compare the genetic control of traits. * Growth and drought-stress traits were extremely variable within the family. Most traits had high broad-sense heritability. Quantitative trait loci (QTL) were identified for most traits; the maximum number of QTL per trait was four. Between 11% and 75% of total phenotypic variation was explained. Few growth-trait QTL coincided with previously identified fructan QTL. A cluster of drought-trait QTL was close to two previously identified regions of the genome with tiller base fructan QTL in repulsion. * The high sugar parent contributed few alleles that increased 'reserve-driven' growth or performance during drought-stress. Correlation of growth and drought-stress traits with fructan content was low and increasing fructan content per se would not appear to improve drought resistance. Complex patterns of carbohydrate partitioning and metabolism within the cell may explain contradictory relationships between carbohydrate content and growth/stress-resistance traits.     

直播水稻茎鞘非结构碳水化合物积累与转运的遗传剖析

为了揭示水稻(Oryza sativa)茎鞘非结构碳水化合物(nonstructural carbohydrate, NSC)积累与转运的遗传基础, 在大田直播条件下, 利用来源于Lemont/特青的重组自交系群体, 对5个相关性状进行了QTL定位。始穗期和成熟期共检测到3个茎鞘NSC含量QTL, 分别位于第1、9和12染色体上, 贡献率分别为13%、7%和7%, 增效等位基因均来自特青。检测到的2个NSC转运率QTL均位于第12染色体上, 贡献率分别为8%和14%。检测到的结实率和千粒重QTL分别为3个和4个, 3个结实率QTL的贡献率分别为9%、24%和6%, 4个千粒重QTL的贡献率分别为14%、11%、12%和13%。进一步的分析表明,来自Lemont的等位基因降低成熟期茎鞘NSC含量的同时却能提高NSC转运率、结实率和千粒重, 而来自特青的等位基因对NSC转运率和结实率均有增效作用, 这为性状间表型相关提供了重要的遗传解释。     

Characterization of QTL for oil content in maize kernel

Kernel oil content in maize is a complex quantitative trait. Phenotypic variation in kernel oil content can be dissected into its component traits such as oil metabolism and physical characteristics of the kernel, including embryo size and embryo-to-endosperm weight ratio (EEWR). To characterize quantitative trait loci (QTL) for kernel oil content, a recombinant inbred population derived from a cross between normal line B73 and high-oil line By804 was genotyped using 228 molecular markers and phenotyped for kernel oil content and its component traits [embryo oil content, embryo oil concentration, EEWR, embryo volume, embryo width, embryo length, and embryo width-to-length ratio (EWLR)]. A total of 58 QTL were identified for kernel oil content and its component traits in 26 genomic regions across all chromosomes. Eight main-effect QTL were identified for kernel oil content, embryo oil content, embryo oil concentration, EEWR, embryo weight, and EWLR, each accounting for over 10?% of the phenotypic variation in six genomic regions. Over 90?% of QTL identified for kernel oil content co-localized with QTL for component traits, validating their molecular contribution to kernel oil content. On chromosome 1, the QTL that had the largest effect on kernel oil content (qKO1-1) was associated with embryo width; on chromosome 9, the QTL for kernel oil content (qKO9) was related to EEWR (qEEWR9). Embryo oil concentration and embryo width were identified as the most important component traits controlling the second largest QTL for kernel oil content on chromosome 6 (qKO6) and a minor QTL for kernel oil content on chromosome 5 (qKO5-2), respectively. The dissection of kernel oil QTL will facilitate future cloning and/or functional validation of kernel oil content, and help to elucidate the genetic basis of kernel oil content in maize.     

Identification of quantitative trait loci influencing aerial morphogenesis in the model legume <Emphasis Type="Italic">Medicago truncatula</Emphasis>

In many legume crops, especially in forage legumes, aerial morphogenesis defined as growth and development of plant organs, is an essential trait as it determines plant and seed biomass as well as forage quality (protein concentration, dry matter digestibility). Medicago truncatula is a model species for legume crops. A set of 29 accessions of M. truncatula was evaluated for aerial morphogenetic traits. A recombinant inbred lines (RILs) mapping population was used for analysing quantitative variation in aerial morphogenetic traits and QTL detection. Genes described to be involved in aerial morphogenetic traits in other species were mapped to analyse co-location between QTLs and genes. A large variation was found for flowering date, morphology and dynamics of branch elongation among the 29 accessions and within the RILs population. Flowering date was negatively correlated to main stem and branch length. QTLs were detected for all traits, and each QTL explained from 5.2 to 59.2% of the phenotypic variation. A QTL explaining a large part of genetic variation for flowering date and branch growth was found on chromosome 7. The other chromosomes were also involved in the variation detected in several traits. Mapping of candidate genes indicates a co-location between a homologue of Constans gene or a flowering locus T (FT) gene and the QTL of flowering date on chromosome 7. Other candidate genes for several QTLs are described. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Identification and mapping of genetic loci affecting the free-threshing habit and spike compactness in wheat (<Emphasis Type="Italic">Triticum aestivum</Emphasis> L.)

Recombinant inbred lines of the International Triticeae Mapping Initiative (ITMI) mapping population were used to localize genetic loci that affect traits related to the free-threshing habit (percent threshability, glume tenacity, and spike fragility) and to spike morphology (spike length, spikelet number, and spike compactness) of wheat (Triticum aestivum L.). The ITMI population was planted in three environments during 1999 and 2000, and phenotypic and genotypic data were used for composite interval mapping. Two quantitative trait loci (QTL) that consistently affected threshability-associated traits were localized on chromosomes 2D and 5A. Coincident QTL on the short arm of 2D explained 44% of the variation in threshability, 17% of the variation in glume tenacity, and 42% of the variation in rachis fragility. QTL on chromosomes 2D probably represent the effect of Tg, a gene for tenacious glumes. Coincident QTL on the long arm of 5A explained 21% and 10% of the variation in glume tenacity and rachis fragility, respectively. QTL on 5A are believed to represent the effect of Q. Overall, free-threshing-related characteristics were predominantly affected by Tg and to a lesser extent by Q. Other QTL that were significantly associated with threshability-related traits in at least one environment were localized on chromosomes 2A, 2B, 6A, 6D, and 7B. Four QTL on chromosomes 1B, 4A, 6A, and 7A consistently affected spike characteristics. Coincident QTL on the short arm of chromosome 1B explained 18% and 7% of the variation in spike length and spike compactness, respectively. QTL on the long arm of 4A explained 11%, 14%, and 12% of the variation in spike length, spike compactness, and spikelet number, respectively. A QTL on the short arm of 6A explained 27% of the phenotypic variance for spike compactness, while a QTL on the long arm of 7A explained 18% of the variation in spikelet number. QTL on chromosomes 1B and 6A appear to affect spike dimensions by modulating rachis internode length, while QTL on chromosomes 4A and 7A do so by affecting the formation of spikelets. Other QTL that were significantly associated with spike morphology-related traits, in at least one environment, were localized on chromosomes 2B, 3A, 3D, 4D, and 5A.Communicated by J. Dvorak     

Identification of quantitative trait loci for shank length and growth at different development stages in chicken

Shank length affects chicken leg health and longer shanks are a source of leg problems in heavy-bodied chickens. Identification of quantitative trait loci (QTL) affecting shank length traits may be of value to genetic improvement of these traits in chickens. A genome scan was conducted on 238 F₂ chickens from a reciprocal cross between the Silky Fowl and the White Plymouth Rock breeds using 125 microsatellite markers to detect static and developmental QTL affecting weekly shank length and growth (from 1 to 12 weeks) in chickens. Static QTL affected shank length from birth to time t , while developmental QTL affected shank growth from time t− 1 to time t . Seven static QTL on six chromosomes (GGA2, GGA3, GGA4, GGA7, GGA9 and GGA23) were detected at ages of 2, 3, 4, 5, 6, 7, 9 and 12 weeks, and six developmental QTL on five chromosomes (GGA1, GGA2, GGA4, GGA5 and GGA23) were detected for five shank growth periods, weeks 2–3, 4–5, 5–6, 10–11 and 11–12. A static QTL and a developmental QTL ( SQSL1 and DQSL2 ) were identified at GGA2 (between ADL0190 and ADL0152 ). SQSL1 explained 2.87–5.30% of the phenotypic variation in shank length from 3 to 7 weeks. DQSL2 explained 2.70% of the phenotypic variance of shank growth between 2 and 3 weeks. Two static and two developmental QTL were involved chromosome 4 and chromosome 23. Two chromosomes (GGA7 and GGA9) had static QTL but no developmental QTL and another two chromosomes (GGA1 and GGA5) had developmental QTL but no static QTL. The results of this study show that shank length and shank growth at different developmental stages involve different QTL.     

Quantitative trait loci variation for growth and obesity between and within lines of pigs (Sus scrofa)

The hypothesis that quantitative trait loci (QTL) that explain variation between divergent populations also account for genetic variation within populations was tested using pig populations. Two regions of the porcine genome that had previously been reported to harbor QTL with allelic effects that differed between the modern pig and its wild-type ancestor and between the modern pig and a more distantly related population of Asian pigs were studied. QTL for growth and obesity traits were mapped using selectively genotyped half-sib families from five domesticated modern populations. Strong support was found for at least one QTL segregating in each population. For all five populations there was evidence of a segregating QTL affecting fatness in a region on chromosome 7. These findings confirm that QTL can be detected in highly selected commercial populations and are consistent with the hypothesis that the same chromosome locations that account for variation between populations also explain genetic variation within populations.     

Molecular mapping of quantitative trait loci for drought tolerance in maize plants

Drought tolerance is one of the most important but complex traits of crops. We looked for quantitative trait loci (QTLs) that affect drought tolerance in maize. Two maize inbreds and their advanced lines were evaluated for drought-related traits. A genetic linkage map developed using RFLP markers was used to identify QTLs associated with drought-related traits. Twenty-two QTLs were detected, with a minimum of one and a maximum of nine for drought-related traits. A single-QTL was detected for sugar concentration accounting for about 52.2% of the phenotypic variation on chromosome 6. A single-QTL was also identified for each of the traits root density, root dry weight, total biomass, relative water content, and leaf abscisic acid content, on chromosomes 1 and 7, contributing to 24, 0.2, 0.4, 7, and 19% of the phenotypic variance, respectively. Three QTLs were identified for grain yield on chromosomes 1, 5, and 9, explaining 75% of the observed phenotypic variability, whereas four QTLs were detected for osmotic potential on chromosomes 1, 3, and 9, together accounting for 50% of the phenotypic variance. Nine QTLs were detected for leaf surface area on chromosomes 3 and 9, with various degrees of phenotypic variance, ranging from 25.8 to 42.2%. Four major clusters of QTLs were identified on chromosomes 1, 3, 7, and 9. A QTL for yield on chromosome 1 was found co-locating with the QTLs for root traits, total biomass, and osmotic potential in a region of about 15 cM. A cluster of QTLs for leaf surface area were coincident with a QTL for osmotic potential on chromosome 3. The QTLs for leaf area also clustered on chromosome 9, whereas QTLs for leaf abscisic acid content and relative water content coincided on chromosome 7, 10 cM apart. Co-location of QTLs for different traits indicates potential pleiotropism or tight linkage, which may be useful for indirect selection in maize improvement for drought tolerance.     

水稻叶片叶绿素和过氧化氢含量的QTL检测及上位性分析

研究水稻叶片叶绿素和过氧化氢含量的遗传规律,对探讨光合代谢产物遗传规律和开展高产育种具有重要指导意义。利用由日本晴／Kasalath∥日本晴的杂交组合衍生的98个回交重组自交家系(BC1F9)所组成的BIL(backcross inbred lines)群体,在第1、2、3和10染色体上分别检测出5个与叶绿素含量相关的QTL和2个影响剑叶过氧化氢含量的QTL,其中位于第1染色体的RFLP标记C86和C813之间的q-Chll对叶绿素含量的影响最为显著,对表型变异的贡献率达22％,其增效基因来自粳稻品种日本晴;同时在该区间检测到1个与剑叶过氧化氢含量相关的QTL:q-H2O2I,对过氧化氢含量的减效基因来自日本晴品种。上位性分析结果显示影响叶绿素含量及过氧化氢含量的非等位QTL之间存在显著的上位性效应。具有上位性效应的QTL分布于第2、6、11和12染色体上,未检测到与q-Chll或q-H2O2I互作的位点。暗示日本晴品种的RFLP标记C86和C813之间存在1个能够提高叶绿素含量,同时又能降低过氧化氢含量的主效QTL,其加性效应显著而不存在上位性效应。     

Detection of quantitative trait loci for growth- and fatness-related traits in a large-scale White Duroc × Erhualian intercross pig population

Growth and fatness are economically important traits in pigs. In this study, a genome scan was performed to detect quantitative trait loci (QTL) for 14 growth and fatness traits related to body weight, backfat thickness and fat weight in a large-scale White Duroc × Erhualian F(2) intercross. A total of 76 genome-wide significant QTL were mapped to 16 chromosomes. The most significant QTL was found on pig chromosome (SSC) 7 for fatness with unexpectedly small confidence intervals of ～2 cM, providing an excellent starting point to identify causal variants. Common QTL for both fatness and growth traits were found on SSC4, 5, 7 and 8, and shared QTL for fat deposition were detected on SSC1, 2 and X. Time-series analysis of QTL for body weight at six growth stages revealed the continuously significant effects of the QTL on SSC4 at the fattening period and the temporal-specific expression of the QTL on SSC7 at the foetus and fattening stages. For fatness traits, Chinese Erhualian alleles were associated with increased fat deposition except that at the major QTL on SSC7. For growth traits, most of White Duroc alleles enhanced growth rates except for those at three significant QTL on SSC6, 7 and 9. The results confirmed many previously reported QTL and also detected novel QTL, revealing the complexity of the genetic basis of growth and fatness in pigs.     

A quantitative trait locus for oleic fatty acid content on Sus scrofa chromosome 7

A partial genome scan using microsatellite markers was conducted to detect quantitative trait loci (QTLs) for 10 fatty acid contents of backfat on 15 chromosomes in a porcine resource population. Two QTLs were discovered on Sus scrofa chromosome 4 (SSC4) and SSC7. The QTL on SSC4 was located between marker loci sw1336 and sw512, and this QTL was detected (P < 0.05) only for linoleic acid. Its position was in proximity of those mapped for linoleic acid content in previous studies. The QTL on SSC7 was mapped between markers swr1343 and sw2155, and it was significant (P < 0.05) only for oleic acid. A novelty of the QTL for oleic acid was suggested because the QTL was located far from any other QTLs previously mapped for fatness traits. The QTL on SSC7 explained 19% of phenotypic variation for oleic acid content. Further studies on fine mapping and positional comparative candidate gene analysis would be the next step toward better understanding of the genetic architecture of fatty acid contents.     

Dissecting the regulation of fructan metabolism in perennial ryegrass (Lolium perenne) with quantitative trait locus mapping

Quantitative trait locus (QTL) mapping, which can be a useful tool for dissecting complex traits, has been used here to study the regulation of fructan metabolism in temperate forage grasses. An F2 mapping family, derived from a high water-soluble carbohydrate (WSC) x low WSC cross, was used to map fructans and the other components of WSC (sucrose, glucose and fructose) in leaves and tiller bases of perennial ryegrass (Lolium perenne) in spring and autumn. To characterize regions of the genome that control basic carbohydrate metabolism, a strategy to minimize the impact of genotype (G) x environment (E), and E-effects on the characterization of G-effects, was adopted. Most traits were highly variable within the family. There was also considerable year-to-year environmental variation. However, significant genetic effects were detected, and several traits had high broad-sense heritability. QTL were identified on chromosomes 1, 2, 5 and 6. Leaf and tiller base QTL did not coincide. Individual QTL explained between 8 and 59% of the total phenotypic variation in the traits. Fructan turnover, metabolism and their genetic control, and the effect of environment, are discussed in the context of the results.     

Construction of Chromosome Segment Substitution Lines in Peanut (Arachis hypogaea L.) Using a Wild Synthetic and QTL Mapping for Plant Morphology

Chromosome segment substitution lines (CSSLs) are powerful QTL mapping populations that have been used to elucidate the molecular basis of interesting traits of wild species. Cultivated peanut is an allotetraploid with limited genetic diversity. Capturing the genetic diversity from peanut wild relatives is an important objective in many peanut breeding programs. In this study, we used a marker-assisted backcrossing strategy to produce a population of 122 CSSLs from the cross between the wild synthetic allotetraploid (A. ipaënsis×A. duranensis)^4x and the cultivated Fleur11 variety. The 122 CSSLs offered a broad coverage of the peanut genome, with target wild chromosome segments averaging 39.2 cM in length. As a demonstration of the utility of these lines, four traits were evaluated in a subset of 80 CSSLs. A total of 28 lines showed significant differences from Fleur11. The line×trait significant associations were assigned to 42 QTLs: 14 for plant growth habit, 15 for height of the main stem, 12 for plant spread and one for flower color. Among the 42 QTLs, 37 were assigned to genomic regions and three QTL positions were considered putative. One important finding arising from this QTL analysis is that peanut growth habit is a complex trait that is governed by several QTLs with different effects. The CSSL population developed in this study has proved efficient for deciphering the molecular basis of trait variations and will be useful to the peanut scientific community for future QTL mapping studies.     

Several QTLs involved in osmotic-adjustment trait variation in barley (Hordeum vulgare L.)

 Osmotic adjustment (OA) was previously demonstrated to be an important adaptive mechanism of drought tolerance in cereals. In order to determine which genomic regions are involved in OA variation, 187 barley (Hordeum vulgare L.) recombinant inbred lines (RILs) derived from a cross between Tadmor (drought tolerant) and Er/Apm (susceptible) were studied in a growth chamber for their OA capacity (through correlated traits and by calculation), at an early growth stage and under two water treatments (soil moisture of 14% and 100% of field capacity). The continuous distribution of the traits and their broad-sense line heritabilities, ranging from 0.04 to 0.44, indicated that OA and related traits should have a polygenic nature. A subset of 167 RILs were also genotyped using 78 RFLP, 32 RAPD and three morphological markers and a linkage map was constructed. Despite strong environmental effects acting on the traits, interval mapping and single-marker ANOVA allowed the detection of three QTLs for relative water content (RWC), four QTLs for osmotic potential (ψ_π), two QTLs of osmotic potential at full turgor (ψ_π100) and one QTL for osmotic adjustment at a soil moisture of 14% field capacity. For the irrigated treatment, only two QTLs were detected: one for RWC and one for ψ_π100. Two chromosomal regions were involved in several OA-related trait variations and could be considered as regions controlling OA; these were present on chromosome 1 (7H) and chromosome 6 (6H), whereas other regions were specific for one trait. No major QTL was found. However, the genomic region involved in OA-related traits on chromosome 1 (7H) in barley seemed to be conserved for OA variation among cereals. Epistatic effects, with or without additive effects, acted on the traits. Received: 15 July 1997 / Accepted: 29 October 1997     

The genetic architecture of Drosophila sensory bristle number

We have mapped quantitative trait loci (QTL) for Drosophila mechanosensory bristle number in six recombinant isogenic line (RIL) mapping populations, each of which was derived from an isogenic chromosome extracted from a line selected for high or low, sternopleural or abdominal bristle number and an isogenic wild-type chromosome. All RILs were evaluated as male and female F(1) progeny of crosses to both the selected and the wild-type parental chromosomes at three developmental temperatures (18 degrees, 25 degrees, and 28 degrees ). QTL for bristle number were mapped separately for each chromosome, trait, and environment by linkage to roo transposable element marker loci, using composite interval mapping. A total of 53 QTL were detected, of which 33 affected sternopleural bristle number, 31 affected abdominal bristle number, and 11 affected both traits. The effects of most QTL were conditional on sex (27%), temperature (14%), or both sex and temperature (30%). Epistatic interactions between QTL were also common. While many QTL mapped to the same location as candidate bristle development loci, several QTL regions did not encompass obvious candidate genes. These features are germane to evolutionary models for the maintenance of genetic variation for quantitative traits, but complicate efforts to understand the molecular genetic basis of variation for complex traits.     

大白菜部分形态性状的QTL定位与分析

应用352个标记位点的大白菜AFLP和RAPD图谱和一套栽培品种间杂交获得的重组自交系群体,采用复合区间作图的方法对大白菜9个形态性状进行QTL定位及遗传效应研究。在14个连锁群上检测到50个QTL:其中控制株型的QTL有5个;控制株高的QTL有6个;控制开展度的QTL有5个;控制最大叶长的QTL有7个;控制最大叶宽的QTL有4个;控制叶形指数的QTL有6个;控制中肋长的QTL有7个;控制中肋宽的QTL有4个;控制抽苔的QTL有6个。另外,估算了单个QTL的遗传贡献率和加性效应。这将为大白菜品种改良中形态性状的分子标记辅助选择提供理论依据。     

Detection of multiple quantitative trait loci and their pleiotropic effects in outbred pig populations

Background

Simultaneous detection of multiple QTLs (quantitative trait loci) may allow more accurate estimation of genetic effects. We have analyzed outbred commercial pig populations with different single and multiple models to clarify their genetic properties and in addition, we have investigated pleiotropy among growth and obesity traits based on allelic correlation within a gamete.

Methods

Three closed populations, (A) 427 individuals from a Yorkshire and Large White synthetic breed, (B) 547 Large White individuals and (C) 531 Large White individuals, were analyzed using a variance component method with one-QTL and two-QTL models. Six markers on chromosome 4 and five to seven markers on chromosome 7 were used.

Results

Population A displayed a high test statistic for the fat trait when applying the two-QTL model with two positions on two chromosomes. The estimated heritabilities for polygenic effects and for the first and second QTL were 19%, 17% and 21%, respectively. The high correlation of the estimated allelic effect on the same gamete and QTL test statistics suggested that the two separate QTL which were detected on different chromosomes both have pleiotropic effects on the two fat traits. Analysis of population B using the one-QTL model for three fat traits found a similar peak position on chromosome 7. Allelic effects of three fat traits from the same gamete were highly correlated suggesting the presence of a pleiotropic QTL. In population C, three growth traits also displayed similar peak positions on chromosome 7 and allelic effects from the same gamete were correlated.

Conclusion

Detection of the second QTL in a model reduced the polygenic heritability and should improve accuracy of estimated heritabilities for both QTLs.     

QTL analysis of plant development and fruit traits in pepper and performance of selective phenotyping

A QTL analysis was performed to determine the genetic basis of 13 horticultural traits conditioning yield in pepper (Capsicum annuum). The mapping population was a large population of 297 recombinant inbred lines (RIL) originating from a cross between the large-fruited bell pepper cultivar ‘Yolo Wonder’ and the small-fruited chilli pepper ‘Criollo de Morelos 334’. A total of 76 QTLs were detected for 13 fruit and plant traits, grouped in 28 chromosome regions. These QTLs explained together between 7% (internode growth time) and 91% (fruit diameter) of the phenotypic variation. The QTL analysis was also performed on two subsets of 141 and 93 RILs sampled using the MapPop software. The smaller populations allowed for the detection of a reduced set of QTLs and reduced the overall percentage of trait variation explained by QTLs. The frequency of false positives as well as the individual effect of QTLs increased in reduced population sets as a result of reduced sampling. The results from the QTL analysis permitted an overall glance over the genetic architecture of traits considered by breeders for selection. Colinearities between clusters of QTLs controlling fruit traits and/or plant development in distinct pepper species and in related solanaceous crop species (tomato and eggplant) suggests that shared mechanisms control the shape and growth of different organs throughout these species.     

Detection of quantitative trait loci for meat quality traits in cattle

A whole-genome scan was carried out to detect quantitative trait loci (QTL) affecting sensory, organoleptic, physical and chemical properties of meat. The study used phenotypic data from 235 second-generation cross-bred bull calves of a Charolais × Holstein experimental population. Loin muscle samples were evaluated for yield force, intramuscular fat and nitrogen contents, myofibrillar fragmentation index, haem pigment concentration, moisture content and pH at 24 h postmortem. A sensory assessment was performed on grilled loin and roasted silverside joints by trained panellists. A linear regression analysis based on 165 markers revealed 35 QTL at the 5% chromosome-wide significance level (20 for sensory traits and 15 for physical and chemical traits), five of which were highly significant ( F -value: ≥9). The most significant QTL was located on chromosome 6 (with the best likely position at 39 cM) and affected haem pigment concentration. The Holstein allele for this QTL was associated with an increase of 0.53 SD in the haem scores. A QTL for pH_24h was identified on chromosome 14 (at 40 cM) and a QTL for moisture content was identified on chromosome 22 (at 21 cM). Two highly significant QTL were identified for sensory panel-assessed traits: beef odour intensity (grilled sample) on chromosome 10 (at 119 cM), and juiciness (roast sample) on chromosome 16 (at 70 cM). The proportion of phenotypic variance explained by the significant QTL ranged from 3.6% (for nitrogen content on chromosome 10) to 9.5% (for juiciness, roast sample on chromosome 16).     

QTL detection and allelic effects for growth and fat traits in outbred pig populations

Quantitative trait loci (QTL) for growth and fatness traits have previously been identified on chromosomes 4 and 7 in several experimental pig populations. The segregation of these QTL in commercial pigs was studied in a sample of 2713 animals from five different populations. Variance component analysis (VCA) using a marker-based identity by descent (IBD) matrix was applied. The IBD coefficient was estimated with simple deterministic (SMD) and Markov chain Monte Carlo (MCMC) methods. Data for two growth traits, average daily gain on test and whole life daily gain, and back fat thickness were analysed. With both methods, seven out of 26 combinations of population, chromosome and trait, were significant. Additionally, QTL genotypic and allelic effects were estimated when the QTL effect was significant. The range of QTL genotypic effects in a population varied from 4.8% to 10.9% of the phenotypic mean for growth traits and 7.9% to 19.5% for back fat trait. Heritabilities of the QTL genotypic values ranged from 8.6% to 18.2% for growth traits, and 14.5% to 19.2% for back fat. Very similar results were obtained with both SMD and MCMC. However, the MCMC method required a large number of iterations, and hence computation time, especially when the QTL test position was close to the marker.