The twofold difference in adult size between the red junglefowl and White Leghorn chickens is largely explained by a limited number of QTLs

A large intercross between the domestic White Leghorn chicken and the wild ancestor, the red junglefowl, has been used in a Quantitative Trait Loci (QTL) study of growth and egg production. The linkage map based on 105 marker loci was in good agreement with the chicken consensus map. The growth of the 851 F2 individuals was lower than both parental lines prior to 46 days of age and intermediate to the two parental lines thereafter. The QTL analysis of growth traits revealed 13 loci that showed genome-wide significance. The four major growth QTLs explained 50 and 80% of the difference in adult body weight between the founder populations for females and males, respectively. A major QTL for growth, located on chromosome 1 appears to have pleiotropic effects on feed consumption, egg production and behaviour. There was a strong positive correlation between adult body weight and average egg weight. However, three QTLs affecting average egg weight but not body weight were identified. An interesting observation was that the estimated effects for the four major growth QTLs all indicated a codominant inheritance.     

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.     

A genetic analysis of seed and berry weight in grapevine.

Fruit size and seedlessness are highly relevant traits in many fruit crop species, and both are primary targets of breeding programs for table grapes. In this work we performed a quantitative genetic analysis of size and seedlessness in an F1 segregating population derived from the cross between a classical seeded (Vitis vinifera L. 'Dominga') and a newly bred seedless ('Autumn Seedless') cultivar. Fruit size was scored as berry weight (BW), and for seedlessness we considered both seed fresh weight (SFW) and the number of seeds and seed traces (SN) per berry. Quantitative trait loci (QTL) analysis of BW detected 3 QTLs affecting this trait and accounting for up to 67% of the total phenotypic variance. QTL analysis for seedlessness detected 3 QTLs affecting SN (explaining up to 35% of total variance) and 6 affecting SFW (explaining up to 90% of total variance). Among them, a major effect QTL explained almost half of the phenotypic variation for SFW. Comparative analysis of QTLs for these traits reduced the number of grapevine genomic regions involved, one of them being a major effect QTL for seedlessness. Association analyses showed that microsatellite locus VMC7F2, closely linked to this QTL, is a useful marker for selection of seedlessnes.     

Mapping QTLs for root morphological traits inBrassica rapa L. based on AFLP and RAPD markers

Root growth and thickening plays a key role in the final productivity and even the quality of storage roots in root crops. This study was conducted to identify and map quantitative trait loci (QTLs) affecting root morphological traits in Brassica rapa by using molecular markers. An F2 population was developed from a cross between Chinese cabbage (Brassica rapa ssp. chinensis) and turnip (B. rapa ssp. rapifera), which differed greatly in root characters. A genetic map covering 1837.1 cM, with 192 marker loci and 11 linkage groups, was constructed by using this F2 population. The F3 families derived from F2 plants were grown in the field and evaluated for taproot traits (thickness, length, and weight). QTL analysis via simple interval mapping detected 18 QTLs for the 3 root traits, including 7 QTLs for taproot thickness, 5 QTLs for taproot length, and 6 QTLs for taproot weight. Individually, the QTLs accounted for 8.4-27.4% of the phenotypic variation. The 2 major QTLs, qTRT4b for taproot thickness and qTRW4 for taproot weight, explained 27.4% and 24.8% of the total phenotypic variance, respectively. The QTLs for root traits, firstly detected in Brassica crops, may provide a basis for marker-assisted selection to improve productivity in root-crop breeding.     

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.     

亚麻主要农艺与品质相关性状的QTL定位

为了全面了解亚麻产量和品质相关性状的遗传基础,为亚麻基因克隆和分子标记辅助育种提供理论依据,在已构建SNP连锁遗传图谱的基础上,以LH-89为父本,R43为母本构建F2:3家系QTL定位群体,用R/QTL软件采用复合区间作图法对13个农艺和品质性状进行QTL定位。结果表明:(1)该研究共检测出35个QTL位点,与粗脂肪及其组成成分相关的QTL有20个,与农艺性状相关的QTL有15个;其中:亚油酸和粗脂肪各5个,亚麻酸、千粒重各4个,棕榈酸、株高、工艺长度各3个,硬脂酸、分枝数各2个,单株果数、果粒数、单株粒重、油酸各1个。(2)共有18个QTL的表型贡献率超10%(主效基因),其中农艺性状定位8个主效基因,品质性状定位10个主效基因。     

Identification of Quantitative Trait Loci for Grain Appearance and Milling Quality Using a Doubled-Haploid Rice Population

Improving grain quality, which is composed primarily of the appearance of the grain and its cooking and milling attributes, is a major objective of many rice-producing areas in China. In the present study, we conducted a marker-based genetic analysis of the appearance and milling quality of rice （Oryza sativa L.） grains using a doubled-haploid population derived from a cross between the indica inbred Zhenshan 97 strain and the japonica inbred Wuyujing 2 strain. Quantitative trait locus （QTL） analysis using a mixed linear model approach revealed that the traits investigated were affected by one to seven QTLs that individually explained 4.0%-30.7% of the phenotypic variation. Cumulatively, the QTL for each trait explained from 12.9% to 61.4% of the phenotypic variation. Some QTLs tended to have a pleiotropic or location-linked association as a cause of the observed phenotypic correlations between different traits. Improvement of the characteristics of grain appearance and grain weight, as well as an improvement in the milling quality of rice grains, would be expected by a recombination of different QTLs using marker-assisted selection.     

A genome scan for quantitative trait loci associated with body weight at different developmental stages in chickens

A genome scan to detect quantitative trait loci (QTL) affecting body weight in chickens was conducted on 238 F(2) chickens from a reciprocal cross of Silky Fowl and White Plymouth Rock using 125 microsatellite markers covering 23 autosomes and the Z chromosome. Two types of QTL were considered: static QTL (SQ) and developmental QTL (DQ). Static QTL affected the body weight from hatch to time t, and DQ affected the body weight from time t-1 to time t. Six SQ and nine DQ were detected. Of these QTL, four reached a genome-wide significance of 5% or better, with SQ1 and DQ1 being the most significant QTL. Static QTL1 was on chromosome 1 between GCT0006 and MCW0106 and explained 4.05-9.80% of the phenotypic variation in body weights from 3 to 12 weeks of age. At 9, 10 and 11 weeks, the genome-wide significance thresholds of SQ1 were <1%. Developmental QTL1 was located on chromosome 1 between MCW0168 and GCT0006, and explained 2.75% of the phenotypic variation for body weight from week 7 to 8 with a genome-wide significance level <1%. The results suggest that body weight from hatch to time t and developmental growth from time t-1 to time t may involve two different sets of genes or gene actions.     

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.     

Mapping and analysis of quantitative trait loci for grain oil content and agronomic traits using AFLP and SSR in sunflower ( Helianthus annuus L.)

Crosses were made between two inbred lines of sunflower. Parents and 118 F(3) families were planted in the field in a randomized complete block design in two replications. Genetic control for some agronomical traits: grain weight by plant (GWP), 1,000-grain weight (TGW), percentage of oil in grain (POG) and sowing to flowering date (STF) was investigated in F(3) families and their parents. Genetic variability was observed among the 118 F(3) families for all the traits studied. Genetic gain was obtained when the best F(3) family, or the mean of 10% of the selected families was compared with the best parent for GWP, TWG and POG. Heritability was 0.23 for GWP, 0.55 for TGW, 0.57 for POG and 0.32 for STF. A set of 244 F(3) families from the same cross, including the above 118 mentioned families and their two parents, were screened with 276 AFLP and microsatellite markers and a linkage map was constructed based on 170 markers. Two putative QTLs for the GWP trait ( gmp), one QTL for TGW ( tgw), six QTLs for POG ( pog) and two for STF ( stf) were detected. The percentage of phenotypic variance explained by each QTL ranged from 2.6% to 70.9%. The percentage of total phenotypic variance explained was 50.7% for GWP, 5.4% for TGW, 90.4% for POG and 89.3% for STF. Although these regions need to be more-precisely mapped, the information obtained should help in marker-assisted selection.     

Bayesian analyses of multiple epistatic QTL models for body weight and body composition in mice

To comprehensively investigate the genetic architecture of growth and obesity, we performed Bayesian analyses of multiple epistatic quantitative trait locus (QTL) models for body weights at five ages (12 days, 3, 6, 9 and 12 weeks) and body composition traits (weights of two fat pads and five organs) in mice produced from a cross of the F1 between M16i (selected for rapid growth rate) and CAST/Ei (wild-derived strain of small and lean mice) back to M16i. Bayesian model selection revealed a temporally regulated network of multiple QTL for body weight, involving both strong main effects and epistatic effects. No QTL had strong support for both early and late growth, although overlapping combinations of main and epistatic effects were observed at adjacent ages. Most main effects and epistatic interactions had an opposite effect on early and late growth. The contribution of epistasis was more pronounced for body weights at older ages. Body composition traits were also influenced by an interacting network of multiple QTLs. Several main and epistatic effects were shared by the body composition and body weight traits, suggesting that pleiotropy plays an important role in growth and obesity.     

Architecture of energy balance traits in emerging lines of the Collaborative Cross

The potential utility of the Collaborative Cross (CC) mouse resource was evaluated to better understand complex traits related to energy balance. A primary focus was to examine if genetic diversity in emerging CC lines (pre-CC) would translate into equivalent phenotypic diversity. Second, we mapped quantitative trait loci (QTL) for 15 metabolism- and exercise-related phenotypes in this population. We evaluated metabolic and voluntary exercise traits in 176 pre-CC lines, revealing phenotypic variation often exceeding that seen across the eight founder strains from which the pre-CC was derived. Many phenotypic correlations existing within the founder strains were no longer significant in the pre-CC population, potentially representing reduced linkage disequilibrium (LD) of regions harboring multiple genes with effects on energy balance or disruption of genetic structure of extant inbred strains with substantial shared ancestry. QTL mapping revealed five significant and eight suggestive QTL for body weight (Chr 4, 7.54 Mb; CI 3.32-10.34 Mb; Bwq14), body composition, wheel running (Chr 16, 33.2 Mb; CI 32.5-38.3 Mb), body weight change in response to exercise (1: Chr 6, 77.7Mb; CI 72.2-83.4 Mb and 2: Chr 6, 42.8 Mb; CI 39.4-48.1 Mb), and food intake during exercise (Chr 12, 85.1 Mb; CI 82.9-89.0 Mb). Some QTL overlapped with previously mapped QTL for similar traits, whereas other QTL appear to represent novel loci. These results suggest that the CC will be a powerful, high-precision tool for examining the genetic architecture of complex traits such as those involved in regulation of energy balance.     

Quantitative trait loci for body weight in the intercross between SM/J and A/J mice.

We performed a genome-wide quantitative trait locus (QTL) analysis of body weight at 10 weeks of age in a population of 321 intercross offspring from SM/J and A/J mice, progenitor strains of SMXA recombinant inbred strains. Interval mapping revealed two significant QTLs, Bwq3 (body weight QTL3) and Bwq4, on Chromosomes (Chrs) 8 and 18 respectively, and five suggestive QTLs on Chrs 2, 6, 7, 15 and 19. Bwq3 and Bwq4 explained 6% of the phenotypic variance. The SM/J alleles at both QTLs increased body weight, though the SM/J mouse was smaller than the A/J mouse. On the other hand, four of the five suggestive QTLs detected had male-specific effects on body weight and the remainder was female-specific. These suggestive QTLs explained 5-6% of the phenotypic variance and all the SM/J alleles decreased body weight.     

Improvement of Rice Biomass Yield through QTL-Based Selection

Biomass yield of rice (Oryza sativa L.) is an important breeding target, yet it is not easy to improve because the trait is complex and phenotyping is laborious. Using progeny derived from a cross between two high-yielding Japanese cultivars, we evaluated whether quantitative trait locus (QTL)-based selection can improve biomass yield. As a measure of biomass yield, we used plant weight (aboveground parts only), which included grain weight and stem and leaf weight. We measured these and related traits in recombinant inbred lines. Phenotypic values for these traits showed a continuous distribution with transgressive segregation, suggesting that selection can affect plant weight in the progeny. Four significant QTLs were mapped for plant weight, three for grain weight, and five for stem and leaf weight (at α = 0.05); some of them overlapped. Multiple regression analysis showed that about 43% of the phenotypic variance of plant weight was significantly explained (P < 0.0001) by six of the QTLs. From F₂ plants derived from the same parental cross as the recombinant inbred lines, we divergently selected lines that carried alleles with positive or negative additive effects at these QTLs, and performed successive selfing. In the resulting F₆ lines and parents, plant weight significantly differed among the genotypes (at α = 0.05). These results demonstrate that QTL-based selection is effective in improving rice biomass yield.     

Novel pleiotropic loci controlling panicle architecture across environments in japonica rice （Oryza sativa L.）

To identify quantitative trait loci (QTLs) controlling panicle architecture in japonica rice, a genetic map was constructed based on simple sequence repeat (SSR) markers and 254 recombinant inbred lines (RILs) derived from a cross between cultivars Xiushui 79 and C Bao. Seven panicle traits were investigated under three environments. Single marker analysis indicated that a total of 27 SSR markers were highly associated with panicle traits in all the three environments. Percentage of phenotypic variation explained by single locus varied from 2% to 35%. Based on the mixed linear model, a total of 40 additive QTLs for seven panicle traits were detected by composite interval mapping, explaining 1.2%-35% of phenotypic variation. Among the 9 QTLs with more than 10% of explained phenotypic variation, two QTLs were for the number of primary branches per panicle (NPB), two for panicle length (PL), two for spikelet density (SD), one for the number of secondary branches per panicle (NSB), one for secondary branch distribution density (SBD), and one for the number of spikelets per panicle (NS), respectively. qPLSD-9-1 and qPLSD-9-2 were novel pleiotropic loci, showing effects on PL and SD simultaneously. qPLSD-9-1 explained 34.7% of the phenotypic variation for PL and 25.4% of the phenotypic variation for SD, respec- tively. qPLSD-9-2 explained 34.9% and 24.4% of the phenotypic variation for PL and SD, respectively. The C Bao alleles at the both QTLs showed positive effects on PL, and the Xiushui 79 alleles at the both QTLs showed positive effects on SD. Genetic variation of panicle traits are mainly attributed to additive effects. QTL × environment interactions were not significant for additive QTLs and additive × additive QTL pairs.     

Mapping quantitative trait loci for a common bean (Phaseolus vulgaris L.) ideotype.

Breeding a model plant that encompasses individual traits thought to enhance yield potential, known as ideotype breeding, has traditionally focused on phenotypic selection of plants with desirable morphological traits. Broadening this breeding method to the molecular level through the use of molecular markers would avoid the environmental interactions associated with phenotypic selection. A population of 110 F5 recombinant inbred lines (RILs), derived from the cross between WO3391 and 'OAC Speedvale', was used to develop a genetic linkage map consisting of 105 random amplified polymorphic DNA (RAPD), simple sequence repeat (SSR), and sequence-tagged site (STS) markers. The map has a total length of 641 cM distributed across 8 linkage groups (LGs). Five of them were aligned on the core linkage map of bean. Twenty-one quantitative trait loci (QTLs) were identified over three environments for eight agronomic and architectural traits previously defined for a bean (Phaseolus vulgaris L.) ideotype. The QTLs were mapped to seven LGs with several regions containing QTLs for multiple traits. At least one QTL was located for each trait and a maximum of four were associated with lodging. Total explained phenotypic variance ranged from 10.6% for hypocotyl diameter to 45.4% for maturity. Some of the QTLs identified will be useful for early generation selection of tall, upright, high-yielding lines in a breeding program.     

小麦株高性状的QTL分析

自20世纪60年代农林10号矮秆基因被用于小麦育种以来,矮化育种成为世界范围内势不可挡的趋势,矮秆基因研究被越来越多的育种专家重视,先后鉴定出20余个矮秆基因,并应用其中6,7个基因,培育了大批丰产潜力大的半矮秆品种,应用矮秆冬小麦吕系DN3338（♀）和F390（♂）杂交得到的F2：3群体,研究小麦株高的遗传基础,以控制株高的数量性状基因座进行定位,利用240个F2：3家系,构建了含215个微卫星标记,覆盖3600cM,由21个连锁群组成的遗传 连锁图谱,并对该群体进行了4个环境（2年：2000年和2001年,2点：北京和石家庄）3重复的田间种植;采用区间作图法,对该群体的株高性状进行了QTL分析。结果表明：7个影响株高的QTL分别位于染色体1B,4B(2个）,6A（2个）,6D和7A上,每个QTL能解释5．2％－50．1％的表型变异,每个环境条件下检测出的所有QTL能解释64．8％－75％,的表型变异,除了7A上的QTL外,其他6个降低株高的QTL均来自ND3338,其效应介于0．94cm-9.33cm之间,且其中的4个在所有的环境下都能被检测出来,具有较高的稳定性,在4BS的Xgwm113标记附近有一主效QTL,其在不同的环境下能降低株高7．91cm-9.33cm,解释27．8％－36．2％,的表型变异,有着同农林10号中Rht-Blb相近的效应;同时在4BS上还发现一个和地点互作的QTL,该QTL在石家庄的两年试验中均被检测到,且有较大的效应值（80cm和7.6cm),因此,认为大部分的QTL能在所有的环境中检测到,这些QTO可以被用于品种改良和分子标记辅助选择育种。     

Quantitative trait locus analysis of growth-related traits in a new Arabidopsis recombinant inbred population

Arabidopsis natural variation was used to analyze the genetics of plant growth rate. Screening of 22 accessions revealed a large variation for seed weight, plant dry weight and relative growth rate but not for water content. A positive correlation was observed between seed weight and plant area 10 d after planting, suggesting that seed weight affects plant growth during early phases of development. During later stages of plant growth this correlation was not significant, indicating that other factors determine growth rate during this phase. Quantitative trait locus (QTL) analysis, using 114 (F9 generation) recombinant inbred lines derived from the cross between Landsberg erecta (Ler, from Poland) and Shakdara (Sha, from Tadjikistan), revealed QTLs for seed weight, plant area, dry weight, relative growth rate, chlorophyll fluorescence, flowering time, and flowering-related traits. Growth traits (plant area, dry weight, and relative growth rate) colocated at five genomic regions. At the bottom of chromosome 5, colocation was found of QTLs for leaf area, leaf initiation speed, specific leaf area, and chlorophyll fluorescence but not for dry weight, indicating that this locus might be involved in leaf development. No consistent relation between growth traits and flowering time was observed despite some colocations. Some of the QTLs detected for flowering time overlapped with loci detected in other recombinant inbred line populations, but also new loci were identified. This study shows that Arabidopsis can successfully be used to study the genetic basis of complex traits like plant growth rate.     

Conservation genomics of Atlantic salmon: SNPs associated with QTLs for adaptive traits in parr from four trans-Atlantic backcrosses

European Atlantic salmon (Salmo salar) differ in skin pigmentation and shape from the North American lineage of Atlantic salmon but the genetic basis of these differences are poorly understood. We created four large (N=300) backcross families by crossing F1 hybrid male siblings to two females from the European and two from the North American aquacultural strains. We recorded 15 morphological landmarks and two skin pigmentation, three growth and three condition traits on parr. The backcross families were genotyped for at least 129 SNPs (single nucleotide polymorphisms) within expressed sequence tags (ESTs) spaced throughout the Atlantic salmon linkage map. The high polymorphism and low rates of crossover in our hybrid sires provided enough statistical power to detect 79 significant associations between SNP markers and quantitative traits after experiment-wide permutation analysis for all families within traits. Linkage group AS22 contained a quantitative trait loci (QTL) for parr mark number; its homolog AS24 contained a large QTL, which explained 26% of the phenotypic variance in parr mark contrast. We found 25 highly significant QTLs for body shape and fin position on seven different linkage groups, and 16 for growth and condition on six different linkage groups. QTL(s) for pectoral fin position, caudal peduncle position, late parr growth and condition index were associated with an SNP on linkage group AS1, which was linked to the sex-determining locus. Our work adds to the evidence that much of the variation in growth rate, shape and skin pigmentation observed among Atlantic salmon parr from different natal streams is genetic.     

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

Background

Flesh colour and growth related traits in salmonids are both commercially important and of great interest from a physiological and evolutionary perspective. The aim of this study was to identify quantitative trait loci (QTL) affecting flesh colour and growth related traits in an F2 population derived from an isolated, landlocked wild population in Norway (Byglands Bleke) and a commercial production population.

Methods

One hundred and twenty-eight informative microsatellite loci distributed across all 29 linkage groups in Atlantic salmon were genotyped in individuals from four F2 families that were selected from the ends of the flesh colour distribution. Genotyping of 23 additional loci and two additional families was performed on a number of linkage groups harbouring putative QTL. QTL analysis was performed using a line-cross model assuming fixation of alternate QTL alleles and a half-sib model with no assumptions about the number and frequency of QTL alleles in the founder populations.

Results

A moderate to strong phenotypic correlation was found between colour, length and weight traits. In total, 13 genome-wide significant QTL were detected for all traits using the line-cross model, including three genome-wide significant QTL for flesh colour (Chr 6, Chr 26 and Chr 4). In addition, 32 suggestive QTL were detected (chromosome-wide P < 0.05). Using the half-sib model, six genome-wide significant QTL were detected for all traits, including two for flesh colour (Chr 26 and Chr 4) and 41 suggestive QTL were detected (chromosome-wide P < 0.05). Based on the half-sib analysis, these two genome-wide significant QTL for flesh colour explained 24% of the phenotypic variance for this trait.

Conclusions

A large number of significant and suggestive QTL for flesh colour and growth traits were found in an F2 population of Atlantic salmon. Chr 26 and Chr 4 presented the strongest evidence for significant QTL affecting flesh colour, while Chr 10, Chr 5, and Chr 4 presented the strongest evidence for significant QTL affecting growth traits (length and weight). These QTL could be strong candidates for use in marker-assisted selection and provide a starting point for further characterisation of the genetic components underlying flesh colour and growth.