Genetic mapping of quantitative trait loci affecting carcass and meat quality traits in Beijing ducks (Anas platyrhynchos)

Quantitative trait loci (QTL) for carcass and meat quality traits were detected in a sample of 224 progeny from four males in line VI and 12 females in line V of Beijing ducks. These lines were selected for high body weight at 42 days of age (line VI) or high egg production at 360 days of age (line V). Traits were weights of the carcass, head, neck, shanks, wings, legs, thighs, breast, heart, liver, crop, gizzard, abdominal fat (AFW) and skin fat, as well as fat thickness in the tail, and pH value, shear force, drip loss (DL) (%) and cooking loss (CL) (%) of the breast. Using a half-sib analysis with a multiple QTL model, linkage between the carcass and meat quality traits and 95 microsatellite markers was investigated. Eight genome-wide significant QTL for weight of crop, skin fat, liver, neck, shanks, wings, DL were detected on linkage groups CAU4 and CAU6. One genome-wide suggestive QTL and one chromosome-wide significant QTL for weight of breast were found on CAU1 and CAU4 respectively. Fifteen chromosome-wide suggestive QTL influencing weight of AFW, breast, crop, heart, carcass, thighs, liver, shanks, gizzard, fat thickness in tail, DL (%) and CL (%) were mapped on CAU2, CAU4, CAU5, CAU6, CAU7, CAU10 and CAU13. In addition, two linked QTL for weight of liver and DL (%) were located on CAU2 and CAU7 respectively. The detection of QTL in ducks is a step towards identification of genes influencing these traits and their use for genetic improvement in this species.     

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.     

Mapping quantitative trait loci affecting some carcass and meat traits in duck (Anas platyrhynchos)

Contrary to chicken and livestock mammals, duck genome has not been explored much. Nowadays a relatively small number of reports on molecular variability and mapping of loci in Peking ducks has been published. Therefore, the objective of this study was to detect single loci affecting body weight, carcass and meat traits in Peking ducks (Anas platyrhynchos). The study was based on an F2 cross between two parental lines A-55 and GL-30. Phenotypes of 387 birds from generation F2 including carcass and meat quality traits were collected. Linkage map, of the linkage group CAU1, consisting of 29 microsatellite markers was constructed. One highly significant (p?p?相似文献   

Quantitative trait loci for bone traits segregating independently of those for growth in an F2 broiler x layer cross

An F2 broiler-layer cross was phenotyped for 18 skeletal traits at 6, 7 and 9 weeks of age and genotyped with 120 microsatellite markers. Interval mapping identified 61 suggestive and significant QTL on 16 of the 25 linkage groups for 16 traits. Thirty-six additional QTL were identified when the assumption that QTL were fixed in the grandparent lines was relaxed. QTL with large effects on the lengths of the tarsometatarsus, tibia and femur, and the weights of the tibia and femur were identified on GGA4 between 217 and 249 cM. Six QTL for skeletal traits were identified that did not co-locate with genome wide significant QTL for body weight and two body weight QTL did not coincide with skeletal trait QTL. Significant evidence of imprinting was found in ten of the QTL and QTL x sex interactions were identified for 22 traits. Six alleles from the broiler line for weight- and size-related skeletal QTL were positive. Negative alleles for bone quality traits such as tibial dyschondroplasia, leg bowing and tibia twisting generally originated from the layer line suggesting that the allele inherited from the broiler is more protective than the allele originating from the layer.     

Mapping quantitative trait loci affecting chicken body size traits via genome scanning

Body size traits reflect the condition of body development, are always mentioned when a breed is described, and are also targets in breeding programmes. In chicken, there are several reports focused on body size traits, such as shank length, tibia length or bone traits. However, no study was carried out on chest width (CW), chest depth (CD), body slope length (BL) and head width (HW) traits. In this study, genome scans were conducted on an F₂ resource population (238 F₂ individuals from 15 full‐sib families derived from an intercross of the White Plymouth Rock with the Silkies Fowl) to identify quantitative trait loci (QTL) associated with CW, CD, BL and HW from 7 to 12 weeks of age. In total, 21 significant or suggestive QTL were found that affected four body size traits. Four QTL reached 1% genome‐wide significance level: at 297 cM on GGA3 (associated with CW at 9 weeks of age), between 155 and 184 cM on GGA1 (affecting BL traits at 9 and 10 weeks of age), at 22 cM on GGA2 (related with BL traits at 12 weeks of age) and at 36 cM on GGA1 (for HW trait at 8 weeks of age).     

QTL analysis of body weight and conformation score in commercial broiler chickens using variance component and half-sib analyses

The aim of the study was to investigate quantitative trait loci (QTL) in previously identified regions of chicken chromosomes 1, 4 and 5 relating to 40-day body weights and conformation scores. Half-sib (HS) and variance component analyses were implemented and compared using QTL Express software. Data were from a two-generation design and consisted of 100 dam families nested in 46 sire families with trait values for 2,708 offspring. Chicken chromosome 4 showed nominal significance for QTL affecting body weight and conformation, and linkage was confirmed for both traits on chromosome 5. Results varied according to method of analysis and with common parent in the HS method.     

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.     

Genome-wide interval mapping using SNPs identifies new QTL for growth,body composition and several physiological variables in an F2 intercross between fat and lean chicken lines

Background

For decades, genetic improvement based on measuring growth and body composition traits has been successfully applied in the production of meat-type chickens. However, this conventional approach is hindered by antagonistic genetic correlations between some traits and the high cost of measuring body composition traits. Marker-assisted selection should overcome these problems by selecting loci that have effects on either one trait only or on more than one trait but with a favorable genetic correlation. In the present study, identification of such loci was done by genotyping an F₂ intercross between fat and lean lines divergently selected for abdominal fatness genotyped with a medium-density genetic map (120 microsatellites and 1302 single nucleotide polymorphisms). Genome scan linkage analyses were performed for growth (body weight at 1, 3, 5, and 7 weeks, and shank length and diameter at 9 weeks), body composition at 9 weeks (abdominal fat weight and percentage, breast muscle weight and percentage, and thigh weight and percentage), and for several physiological measurements at 7 weeks in the fasting state, i.e. body temperature and plasma levels of IGF-I, NEFA and glucose. Interval mapping analyses were performed with the QTLMap software, including single-trait analyses with single and multiple QTL on the same chromosome.

Results

Sixty-seven QTL were detected, most of which had never been described before. Of these 67 QTL, 47 were detected by single-QTL analyses and 20 by multiple-QTL analyses, which underlines the importance of using different statistical models. Close analysis of the genes located in the defined intervals identified several relevant functional candidates, such as ACACA for abdominal fatness, GHSR and GAS1 for breast muscle weight, DCRX and ASPSCR1 for plasma glucose content, and ChEBP for shank diameter.

Conclusions

The medium-density genetic map enabled us to genotype new regions of the chicken genome (including micro-chromosomes) that influenced the traits investigated. With this marker density, confidence intervals were sufficiently small (14 cM on average) to search for candidate genes. Altogether, this new information provides a valuable starting point for the identification of causative genes responsible for important QTL controlling growth, body composition and metabolic traits in the broiler chicken.     

Mapping QTL for growth and shank traits in chickens divergently selected for high or low body weight

An F₂ population (695 individuals) was established from broiler chickens divergently selected for either high (HG) or low (LG) growth, and used to localize QTL for developmental changes in body weight (BW), shank length (SL9) and shank diameter (SD9) at 9 weeks. QTL mapping revealed three genome‐wide QTL on chromosomes (GGA) 2, 4 and 26 and three suggestive QTL on GGA 1, 3 and 5. Most of the BW QTL individually explained 2–5% of the phenotypic variance. The BW QTL on GGA2 explained about 7% of BW from 3 to 7 weeks of age, while that on GGA4 explained 15% of BW from 5 to 9 weeks. The BW QTL on GGA2 and GGA4 could be associated with early and late growth respectively. The GGA4 QTL also had the largest effect on SL9 and SD9 and explained 7% and 10% of their phenotypic variances respectively. However, when SL9 and SD9 were corrected with BW9, a shank length percent QTL was identified on GGA2. We identified novel QTL and also confirmed previously identified loci in other chicken populations. As the foundation population was established from commercial broiler strains, it is possible that QTL identified in this study could still be segregating in commercial strains.     

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.     

Multiple-trait QTL mapping for body and organ weights in a cross between NMRI8 and DBA/2 mice

Multiple-trait analyses have been shown to improve the detection of quantitative trait loci (QTLs) with multiple effects. Here we applied a multiple-trait approach on obesity- and growth-related traits that were surveyed in 275 F2 mice generated from an intercross between the high body weight selected line NMRI8 and DBA/2 as lean control. The parental lines differed 2.5-fold in body weight at the age of 6 weeks. Within the F2 population, the correlations between body weight and weights of abdominal fat weight, muscle, liver and kidney at the age of 6 weeks were about 0.8. A least squares multiple-trait QTL analysis was performed on these data to understand more precisely the cause of the genetic correlation between body weight, body composition traits and weights of inner organs. Regions on Chr 1, 2, 7 and 14 for body weights at different early ages and regions on Chr 1, 2, 4, 7, 14, 17 and 19 for organ weights at 6 weeks were found to have significant multiple effects at the genome-wide level.     

QTL analysis of body weight and carcass body length traits in an F2 intercross between Landrace and Korean native pigs

Growth traits, such as body weight and carcass body length, directly affect productivity and economic efficiency in the livestock industry. We performed a genome‐wide linkage analysis to detect the quantitative trait loci (QTL) that affect body weight, growth curve parameters and carcass body length in an F₂ intercross between Landrace and Korean native pigs. Eight phenotypes related to growth were measured in approximately 1000 F₂ progeny. All experimental animals were subjected to genotypic analysis using 173 microsatellite markers located throughout the pig genome. The least squares regression approach was used to conduct the QTL analysis. For body weight traits, we mapped 16 genome‐wide significant QTL on SSC1, 3, 5, 6, 8, 9 and 12 as well as 22 suggestive QTL on SSC2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 16 and 17. On SSC12, we identified a major QTL affecting body weight at 140 days of age that accounted for 4.3% of the phenotypic variance, which was the highest test statistic (F‐ratio = 45.6 under the additive model, nominal P = 2.4 × 10^?11) observed in this study. We also showed that there were significant QTL on SSC2, 5, 7, 8, 9 and 12 affecting carcass body length and growth curve parameters. Interestingly, the QTL on SSC2, 3, 5, 6, 8, 9, 10, 12 and 17 influencing the growth‐related traits showed an obvious trend for co‐localization. In conclusion, the identified QTL may play an important role in investigating the genetic structure underlying the phenotypic variation of growth in pigs.     

A genome scan reveals QTL for growth, fatness, leanness and meat quality in a Duroc-Pietrain resource population

We performed a genome-wide QTL scan for production traits in a line cross between Duroc and Pietrain breeds of pigs, which included 585 F(2) progeny produced from 31 full-sib families genotyped with 106 informative microsatellites. A linkage map covering all 18 autosomes and spanning 1987 Kosambi cM was constructed. Thirty-five phenotypic traits including body weight, growth, carcass composition and meat quality traits were analysed using least square regression interval mapping. Twenty-four QTL exceeded the genome-wide significance threshold, while 47 QTL reached the suggestive threshold. These QTL were located at 28 genomic regions on 16 autosomal chromosomes and QTL in 11 regions were significant at the genome-wide level. A QTL affecting pH value in loin was detected on SSC1 between marker-interval S0312-S0113 with strong statistical support (P < 3.0 x 10(-14)); this QTL was also associated with meat colour and conductivity. QTL for carcass composition and average daily gain was also found on SSC1, suggesting multiple QTL. Seventeen genomic segments had only a single QTL that reached at least suggestive significance. Forty QTL exhibited additive inheritance whereas 31 QTL showed (over-) dominance effects. Two QTL for trait backfat thickness were detected on SSC2; a significant paternal effect was found for a QTL in the IGF2 region while another QTL in the middle of SSC2 showed Mendelian expression.     

Identification of quantitative trait loci affecting shank length, body weight and carcass weight from the Japanese cockfighting chicken breed, Oh-Shamo (Japanese Large Game)

We performed a quantitative trait locus (QTL) analysis to map QTLs controlling shank length, body weight, and carcass weight in a resource family of 245 F(2) birds developed from a cross of the large-sized, native, Japanese cockfighting breed, Oh-Shamo (Japanese Large Game), and the White Leghorn breed of chickens. Interval mapping revealed three significant QTLs for shank length on chromosomes 1, 4 and 24 at the experiment-wise 5% level, and a suggestive shank length QTL on chromosome 27 at the experiment-wise 10% level. For body weight two QTLs, one significant and the other suggestive, were identified on chromosomes 4 and 24, respectively. As expected, QTLs for carcass weight, which was highly correlated with body weight (r = 0.95), were detected at the same chromosomal locations as the detected body weight QTLs. Interestingly, the chromosomal locations containing these body weight and carcass weight QTLs coincided with those of two of the four shank length QTLs detected. No QTL with an epistatic interaction effect was discovered for any trait. The total contribution of all detected QTLs to genetic variance was 98.4%, 27.0% and 25.9% for shank length, body weight and carcass weight, respectively, indicating that most shank length QTLs have been identified but many body weight and carcass weight QTLs have been overlooked by the present analysis because of a low coverage rate of the 88 microsatellite markers used here (approximately 46% of the whole genome).     

QTL for percentage of carcass and carcass parts in a broiler x layer cross

An F₂ experimental population, developed from a broiler layer cross, was used in a genome scan of QTL for percentage of carcass, carcass parts, shank and head. Up to 649 F₂ chickens from four paternal half‐sib families were genotyped with 128 genetic markers covering 22 linkage groups. Total map length was 2630 cM, covering approximately 63% of the genome. QTL interval mapping using regression methods was applied to line‐cross and half‐sib models. Under the line‐cross model, 12 genome‐wide significant QTL and 17 suggestive linkages for percentages of carcass parts, shank and head were mapped to 13 linkage groups (GGA1, 2, 3, 4, 5, 7, 8, 9, 11, 12, 14, 18 and 27). Under the paternal half‐sib model, six genome‐wide significant QTL and 18 suggestive linkages for percentages of carcass parts, shank and head were detected on nine chicken linkage groups (GGA1, 2, 3, 4, 5, 12, 14, 15 and 27), seven of which seemed to corroborate positions revealed by the previous model. Overall, three novel QTL of importance to the broiler industry were mapped (one significant for shank% on GGA3 and two suggestive for carcass and breast percentages on GGA14 and drums and thighs percentage on GGA15). One novel QTL for wings% was mapped to GGA3, six novel QTL (GGA1, 3, 7, 8, 9 and 27) and suggestive linkages (GGA2, 4, and 5) were mapped for head%, and suggestive linkages were identified for back% on GGA2, 11 and 12. In addition, many of the QTL mapped in this study confirmed QTL previously reported in other populations.     

Mapping quantitative trait loci regulating chicken body composition traits

Genome scans were conducted on an F₂ resource population derived from intercross of the White Plymouth Rock with the Silkies Fowl to detect QTL affecting chicken body composition traits. The population was genotyped with 129 microsatellite markers and phenotyped for 12 body composition traits on 238 F₂ individuals from 15 full-sib families. In total, 21 genome-wide QTL were found to be responsible for 11 traits, including two newly studied traits of proventriculus weight and shank girth. Three QTL were genome-wide significant: at 499 c m on GGA1 (explained 3.6% of phenotypic variance, P  < 0.01) and 51 c m on GGA5 (explained 3.3% of phenotypic variance, P  < 0.05) for the shank & claw weight and 502 c m on GGA1 (explained 1.4% of phenotypic variance, P  < 0.05) for wing weight. The QTL on GGA1 seemed to have pleiotropic effects, also affecting gizzard weight at 490 c m , shank girth at 489 c m and intestine length at 481 c m . It is suggested that further efforts be made to understand the possible pleiotropic effects of the QTL on GGA1 and that on GGA5 for two shank-related traits.     

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.     

Quantitative trait loci segregating in crosses between New Hampshire and White Leghorn chicken lines: II. Muscle weight and carcass composition

In order to identify genetic factors influencing muscle weight and carcass composition in chicken, a linkage analysis was performed with 278 F₂ males of reciprocal crosses between the extremely different inbred lines New Hampshire (NHI) and White Leghorn (WL77). The NHI line had been selected for high meat yield and the WL77 for low egg weight before inbreeding. Highly significant quantitative trait loci (QTL) controlling body weight and the weights of carcass, breast muscle, drumsticks–thighs and wings were identified on GGA4 between 151.5 and 160.5 cM and on GGA27 between 4 and 52 cM. These genomic regions explained 13.7–40.2% and 5.3–13.8% of the phenotypic F₂ variances of the corresponding traits respectively. Additional genome‐wide highly significant QTL for the weight of drumsticks–thighs were mapped on GGA1, 5 and 7. Moreover, significant QTL controlling body weight were found on GGA2 and 11. The data obtained in this study can be used for increasing the mapping resolution and subsequent gene targeting on GGA4 and 27 by combining data with other crosses where the same QTL were found.     

Mapping quantitative trait Loci underlying fitness-related traits in a free-living sheep population

We searched for quantitative trait loci (QTL) underlying fitness-related traits in a free-living pedigree of 588 Soay sheep in which a genetic map using 251 markers with an average spacing of 15 cM had been established previously. Traits examined included birth date and weight, considered both as maternal and offspring traits, foreleg length, hindleg length, and body weight measured on animals in August and jaw length and metacarpal length measured on cleaned skeletal material. In some cases the data were split to consider different age classes separately, yielding a total of 15 traits studied. Genetic and environmental components of phenotypic variance were estimated for each trait and, for those traits showing nonzero heritability (N= 12), a QTL search was conducted by comparing a polygenic model with a model including a putative QTL. Support for a QTL at genome-wide significance was found on chromosome 11 for jaw length; suggestive QTL were found on chromosomes 2 and 5 (for birth date as a trait of the lamb), 8 (birth weight as a trait of the lamb), and 15 (adult hindleg length). We discuss the prospects for refining estimates of QTL position and effect size in the study population, and for QTL searches in free-living pedigrees in general.     

Quantitative Trait Loci for Light Sensitivity,Body Weight,Body Size,and Morphological Eye Parameters in the Bumblebee,Bombus terrestris

Bumblebees such as Bombus terrestris are essential pollinators in natural and managed ecosystems. In addition, this species is intensively used in agriculture for its pollination services, for instance in tomato and pepper greenhouses. Here we performed a quantitative trait loci (QTL) analysis on B. terrestris using 136 microsatellite DNA markers to identify genes linked with 20 traits including light sensitivity, body size and mass, and eye and hind leg measures. By composite interval mapping (IM), we found 83 and 34 suggestive QTLs for 19 of the 20 traits at the linkage group wide significance levels of p = 0.05 and 0.01, respectively. Furthermore, we also found five significant QTLs at the genome wide significant level of p = 0.05. Individual QTLs accounted for 7.5-53.3% of the phenotypic variation. For 15 traits, at least one QTL was confirmed with multiple QTL model mapping. Multivariate principal components analysis confirmed 11 univariate suggestive QTLs but revealed three suggestive QTLs not identified by the individual traits. We also identified several candidate genes linked with light sensitivity, in particular the Phosrestin-1-like gene is a primary candidate for its phototransduction function. In conclusion, we believe that the suggestive and significant QTLs, and markers identified here, can be of use in marker-assisted breeding to improve selection towards light sensitive bumblebees, and thus also the pollination service of bumblebees.