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Results for “Quantitative Trait Loci”

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PubMed2002

Quantitative trait loci for bone density in mice: the genes determining total skeletal density and femur density show little overlap in F2 mice.

Bone mineral density variation is a highly heritable trait and is the best predictor of skeletal fragility. Total skeletal density was determined by PIXIMUS, and femur density was determined by pQCT. The data were analyzed for quantitative trait loci (QTL) to determine if bone density at a specific skeletal site (femur) would identify new gene loci or the same gene loci as total body (PIXIMUS). In order to show concordance and differences in QTL for total body bone density versus femur bone density, we performed a genome-wide scan from 633 (MRL x SJL) F2 mice. The bone mineral density (BMD) data from pQCT were used to identify nine QTL on chromosomes 1, 3, 4, 9, 12, 17, and 18, while nine QTL on chromosomes 1, 2, 4, 9, 11, 14, and 15 were identified by PIXIMUSdata, accounting for 32.5% and 30.4% variation in F2 mice, respectively. QTL on chromosomes 1, 2, 3, 9, 11, 12, 14, 15, 17, and 18 are unique to our study, as they have never been described before. Chromosome 1 (D1Mit33 and D1Mit362) had similar QTL between pQCT and PIXIMUS. Several QTL were identified for both femur and total body BMD but only two QTL were common for both of these phenotypes. This suggests that genes regulating bone density differ depending on the skeletal site analyzed.

Animals↗

PubMed1995

The contribution of quantitative trait loci and neutral marker loci to the genetic variances and covariances among quantitative traits in random mating populations.

Using Cockerham's approach of orthogonal scales, we develop genetic models for the effect of an arbitrary number of multiallelic quantitative trait loci (QTLs) or neutral marker loci (NMLs) upon any number of quantitative traits. These models allow the unbiased estimation of the contributions of a set of marker loci to the additive and dominance variances and covariances among traits in a random mating population. The method has been applied to an analysis of allozyme and quantitative data from the European oyster. The contribution of a set marker loci may either be real, when the markers are actually QTLs, or apparent, when they are NMLs that are in linkage disequilibrium with hidden QTLs. Our results show that the additive and dominance variances contributed by a set of NMLs are always minimum estimates of the corresponding variances contributed by the associated QTLs. In contrast, the apparent contribution of the NMLs to the additive and dominance covariances between two traits may be larger than, equal to or lower than the actual contributions of the QTLs. We also derive an expression for the expected variance explained by the correlation between a quantitative trait and multilocus heterozygosity. This correlation explains only a part of the genetic variance contributed by the markers, i.e., in general, a combination of additive and dominance variances and, thus, provides only very limited information relative to the method supplied here.

Alleles↗

PubMed2004

A genome scan for quantitative trait loci and imprinted regions affecting reproduction in pigs.

Quantitative trait loci for reproductive traits in a three-generation resource population of a cross between low-indexing pigs from a control line and high-indexing pigs from a line selected 10 generations for increased index of ovulation rate and embryonic survival are reported. Phenotypic data were collected in F2 females for birth weight (BWT, n = 428), weaning weight (WWT, n = 405), age at puberty (AP, n = 295), ovulation rate (OR, n = 423), number of fully formed pigs (FF, n = 370), number of pigs born alive (NBA, n = 370), number of mummified pigs (MUM, n = 370), and number of stillborn pigs (NSB, n = 370). Grandparent, F1, and F2 animals were genotyped for 151 microsatellite markers. Sixteen putative QTL (P < 0.10) for reproductive traits were identified in previous analyses of these data with single QTL line-cross models. Data were reanalyzed with multiple QTL models, including imprinting effects. Data also were analyzed with half-sib models. Permutation was used to establish genome-wide significance levels ( = 0.01, 0.05, and 0.10). Thirty-one putative QTL for reproductive traits and two QTL for birth weight were identified (P < 0.10). One Mendelian QTL for FF (P < 0.05), one for NBA (P < 0.05), three for NSB (P < 0.05), three for NN (P < 0.05), seven for AP (P < 0.10), five for MUM (P < 0.10), and one for BWT (P < 0.10) were found. Partial imprinting of QTL affecting OR (P < 0.01), BWT (P < 0.05), and MUM (P < 0.05) was detected. There were four paternally expressed QTL for NN (P < 0.10) and one each for AP (P < 0.05) and MUM (P < 0.10). Maternally expressed QTL affecting NSB (P < 0.10), NN (P < 0.10), and MUM (P < 0.10) were detected. No QTL were detected with half-sib analyses. Multiple QTL models with imprinting effects are more appropriate for analyzing F2 data than single Mendelian QTL line-cross models.

Animals↗

PubMed2005

Epistasis, not numbers, regulates functions of clustered Dahl rat quantitative trait loci applicable to human hypertension.

Quantitative trait loci (QTLs) for blood pressure (BP) were found on chromosome 10 of Dahl salt-sensitive rats and are potentially important to human essential hypertension. But their identities and how they influence BP together were not known. Presently, we first fine mapped existing QTLs, C10QTL1, C10QTL2, and C10QTL3, by constructing congenic strains. In the process, a new QTL, C10QTL4, was identified. Because the intervals harboring C10QTL1 and C10QTL4 contain a maximum of 16 and 10 possible genes, respectively, a limited number of specific gene targets has been identified to be QTLs residing in human homologous regions on chromosome 17. Moreover, because none of these candidates encodes a gene known to influence BP, the 2 QTLs will represent novel genes for BP regulations. Second, we used congenic strains with QTL combinations to analyze the interactions between the QTLs. Consequently, a double combination of C10QTL4 and C10QTL1 possessed the same BP as each of the 2 QTLs alone. BP of a triple combination of C10QTL4, C10QTL1, and C10QTL3 was not different from BP of the C10QTL4 and C10QTL1 double combination. These results demonstrate that C10QTL4, C10QTL1, and C10QTL3 are epistatic to one another in their BP effects. In contrast, when adding C10QTL2 into the triple formation of the 3 QTLs above to create a quadruple QTL combination, BP increased proportionately, indicating that C10QTL2 acts independently of C10QTL4, C10QTL1, and C10QTL3. The epistatic and additive interactions uncovered in the animal model will help elucidate similar interactions playing a role in human essential hypertension.

Animals↗

PubMed2001

Enhanced efficiency of quantitative trait loci mapping analysis based on multivariate complexes of quantitative traits.

An approach to increase the efficiency of mapping quantitative trait loci (QTL) was proposed earlier by the authors on the basis of bivariate analysis of correlated traits. The power of QTL detection using the log-likelihood ratio (LOD scores) grows proportionally to the broad sense heritability. We found that this relationship holds also for correlated traits, so that an increased bivariate heritability implicates a higher LOD score, higher detection power, and better mapping resolution. However, the increased number of parameters to be estimated complicates the application of this approach when a large number of traits are considered simultaneously. Here we present a multivariate generalization of our previous two-trait QTL analysis. The proposed multivariate analogue of QTL contribution to the broad-sense heritability based on interval-specific calculation of eigenvalues and eigenvectors of the residual covariance matrix allows prediction of the expected QTL detection power and mapping resolution for any subset of the initial multivariate trait complex. Permutation technique allows chromosome-wise testing of significance for the whole trait complex and the significance of the contribution of individual traits owing to: (a) their correlation with other traits, (b) dependence on the chromosome in question, and (c) both a and b. An example of application of the proposed method on a real data set of 11 traits from an experiment performed on an F(2)/F(3) mapping population of tetraploid wheat (Triticum durum x T. dicoccoides) is provided.

Chromosome Mapping↗

PubMed2005

Quantitative trait loci analysis of heat stress resistance of spermatocytes in the MRL/MpJ mouse.

The MRL/MpJ mouse has previously been reported to possess an interesting phenotype in which spermatocytes are resistant to the abdominal temperature heat shock. In this study genetic analysis for it was performed. The phenotypes of F2 progenies produced by mating MRL/MpJ and control strain C57BL/6 mice were not segregated into two types as parental phenotypes, suggesting that the phenotype is controlled by multiple genetic loci. Thus, quantitative trait loci (QTL) analysis was performed using 98 microsatellite markers. The weight ratio of the cryptorchid testis to the intact testis (testis weight ratio) and the Sertoli cell index were used for quantitative traits. QTL analysis revealed two significant QTLs located on Chrs 1 and 11 for testis weight ratio and one significant QTL located in the same region of Chr 1 for the Sertoli cell index. A microsatellite marker locus located in the peak of the QTL on Chr 1 did not recombine with the exonuclease 1 (Exo1) gene locus in 140 F2 progenies. Mutation of the Exo1 gene was previously reported to be responsible for metaphase-specific apoptosis (MSA) of spermatocytes in the MRL/MpJ mouse. These results raise the possibility that mutation of the Exo1 gene is responsible for both MSA and heat stress resistance of spermatocytes in the MRL/MpJ mouse.

Animals↗

PubMed2000

Identification of four new quantitative trait loci regulating arthritis severity and one new quantitative trait locus regulating autoantibody production in rats with collagen-induced arthritis.

OBJECTIVE: Collagen-induced arthritis (CIA) is a polygenic model of experimentally induced autoimmunity and chronic joint inflammation. This study maps genetic loci that regulate CIA susceptibility in DA/Bkl (DA) and BN/SsNHsd (BN) rats. METHODS: Genome scans covering chromosomes 1-20 and interval mapping techniques using 159 simple sequence-length polymorphism markers were used to identify quantitative trait loci (QTLs) that regulate CIA in (DA x BN)F2 hybrids. Serum antibody titers to type II collagen were determined by enzyme-linked immunosorbent assay. RESULTS: DA rats were high responders to porcine type II collagen (PII) and developed severe CIA (100%). BN rats were low responders to PII and resistant to CIA (0%). BN genes strongly repressed PII-induced CIA. Only 12% of (DA x BN)F1 rats (7 of 60) and 31% of (DA x BN)F2 rats (307 of 1,004) developed CIA. Three new QTLs (Cia11, Cia12, and Cia13) with significant logarithm of odds (LOD) scores of 5.6, 4.6, and 4.5, respectively, plus a suggestive QTL (Cia14*, LOD 3.0) regulating arthritis severity were identified on chromosomes 3, 12, 4, and 19. A new QTL, Ciaa3, associating with anticollagen antibody titer (antibody to PII LOD 6.5; antibody to rat type II collagen LOD 5.2) mapped to chromosome 9. Of 10 CIA QTLs previously identified in (DA x F344) and (DA x ACI) rats, only Cia1 in the major histocompatibility complex and a region coincident to Cia5 on chromosome 10 (LOD >8.0) influenced CIA severity in (DA x BN)F2 rats. CONCLUSION: Since CIA exhibits many of the pathologic features of rheumatoid arthritis, the data indicate that the variety of genetic elements regulating human autoimmune and rheumatic diseases may be much larger and more varied than originally envisioned.

Animals↗

PubMed2006

Identification of diabetes susceptibility loci in db mice by combined quantitative trait loci analysis and haplotype mapping.

To identify the disease-susceptibility genes of type 2 diabetes, we performed quantitative trait loci (QTL) analysis in F(2) populations generated from a BKS.Cg-m+/+Lepr(db) and C3H/HeJ intercross, taking advantage of genetically determined obesity and diabetes traits associated with the db gene. A genome-wide scan in the F(2) populations divided by sex and db genotypes identified 14 QTLs in total and 3 major QTLs on chromosome (Chr) 3 (LOD 5.78) for fat pad weight, Chr 15 (LOD 6.64) for body weight, and Chr 16 (LOD 8.15) for blood glucose concentrations. A linear-model-based genome scan using interactive covariates allowed us to consider sex- or sex-by db-specific effects of each locus. For the most significant QTL on Chr 16, the high-resolution haplotype comparison between BKS and C3H strains reduced the critical QTL interval from 20 to 4.6 Mb by excluding shared haplotype regions and identified 11 nonsynonymous single-nucleotide polymorphisms in six candidate genes.

Animals↗

PubMed2001

Bayesian mapping of quantitative trait loci under complicated mating designs.

Quantitative trait loci (QTL) are easily studied in a biallelic system. Such a system requires the cross of two inbred lines presumably fixed for alternative alleles of the QTL. However, development of inbred lines can be time consuming and cost ineffective for species with long generation intervals and severe inbreeding depression. In addition, restriction of the investigation to a biallelic system can sometimes be misleading because many potentially important allelic interactions do not have a chance to express and thus fail to be detected. A complicated mating design involving multiple alleles mimics the actual breeding system. However, it is difficult to develop the statistical model and algorithm using the classical maximum-likelihood method. In this study, we investigate the application of a Bayesian method implemented via the Markov chain Monte Carlo (MCMC) algorithm to QTL mapping under arbitrarily complicated mating designs. We develop the method under a mixed-model framework where the genetic values of founder alleles are treated as random and the nongenetic effects are treated as fixed. With the MCMC algorithm, we first draw the gene flows from the founders to the descendants for each QTL and then draw samples of the genetic parameters. Finally, we are able to simultaneously infer the posterior distribution of the number, the additive and dominance variances, and the chromosomal locations of all identified QTL.

Analysis of Variance↗

PubMed2004

On the integration of alcohol-related quantitative trait loci and gene expression analyses.

BACKGROUND: Quantitative trait loci (QTLs) have been detected for a wide variety of ethanol-related phenotypes, including acute and chronic ethanol withdrawal, acute locomotor activation, and ethanol preference. This study was undertaken to determine whether the process of moving from QTL to quantitative trait gene (QTG) could be accelerated by the integration of functional genomics (gene expression) into the analysis strategy. METHODS: Six ethanol-related QTLs, all detected in C57BL/6J and DBA/2J intercrosses were entered into the analysis. Each of the QTLs had been confirmed in independent genetic models at least once; the cumulative probabilities for QTL existence ranged from 10 to 10. Brain gene expression data for the C57BL/6 and DBA/2 strains (n = 6 per strain) and an F2 intercross sample (n = 56) derived from these strains were obtained by using the Affymetrix U74Av2 and 430A arrays; additional data with the U74Av2 array were available for the extended amygdala, dorsomedial striatum, and hippocampus. Low-level analysis was performed by using multiple methods to determine the likelihood that a transcript was truly differentially expressed. For the 430A array data, the F2 sample was used to determine which of the differentially expressed transcripts within the QTL intervals were cis-regulated and, thus, strong candidates for QTGs. RESULTS: Within the 6 QTL intervals, 39 transcripts (430A array) were identified as being highly likely to be differentially expressed between the C57BL/6 and DBA/2 strains at a false discovery rate of 0.01 or better. Twenty-eight of these transcripts showed significant (logarithm of odds > or =3.6) to highly significant (logarithm of odds >7) cis-regulation. The process correctly detected Mpdz (chromosome 4) as a candidate QTG for acute withdrawal. CONCLUSIONS: Although improvements are needed in the expression databases, the integration of QTL and gene expression analyses seems to have potential as a high-throughput strategy for moving from QTL to QTG.

Alcohol Drinking↗

PubMed2005

Survival analysis of life span quantitative trait loci in Drosophila melanogaster.

We used quantitative trait loci (QTL) mapping to evaluate the age specificity of naturally segregating alleles affecting life span. Estimates of age-specific mortality rates were obtained from observing 51,778 mated males and females from a panel of 144 recombinant inbred lines (RILs). Twenty-five QTL were found, having 80 significant effects on life span and weekly mortality rates. Generation of RILs from heterozygous parents enabled us to contrast effects of QTL alleles with the means of RIL populations. Most of the low-frequency alleles increased mortality, especially at younger ages. Two QTL had negatively correlated effects on mortality at different ages, while the remainder were positively correlated. Chromosomal positions of QTL were roughly concordant with estimates from other mapping populations. Our findings are broadly consistent with a mix of transient deleterious mutations and a few polymorphisms maintained by balancing selection, which together contribute to standing genetic variation in life span.

Alleles↗

PubMed2006

Identification of two novel quantitative trait loci for pre-eclampsia susceptibility on chromosomes 5q and 13q using a variance components-based linkage approach.

Pre-eclampsia/eclampsia (PE/E) is a common and serious disorder of human pregnancy that is associated with substantial maternal and perinatal morbidity and mortality. The suspected aetiology of PE/E is complex, with susceptibility being attributable to multiple environmental factors and a large genetic component. By assuming that the underlying liability towards PE/E susceptibility is inherently quantitative, any PE/E susceptibility gene would represent a quantitative trait locus (QTL). This assumption enables a more refined and powerful variance components procedure using a threshold model for our PE/E statistical analysis. Using this more efficient linkage approach, we have now re-analysed our previously completed Australian/New Zealand genome scan data to identify two novel PE/E susceptibility QTLs on chromosomes 5q and 13q. We have obtained strong evidence of linkage on 5q with a peak logarithm-of-odds (LOD) score of 3.12 between D5S644 and D5S433 [at approximately 121 centimorgan (cM)] and strong evidence of linkage on 13q with a peak LOD score of 3.10 between D13S1265 and D13S173 (at approximately 123 cM). Objective identification and prioritization of positional candidate genes using the quantitative bioinformatics program GeneSniffer revealed highly plausible PE/E candidate genes encoding aminopeptidase enzymes and a placental peptide hormone on the 5q QTL and two type IV collagens on the 13q QTL regions, respectively.

Analysis of Variance↗

PubMed2000

Quantitative trait loci affecting growth and carcass composition of cattle segregating alternate forms of myostatin.

The effects of the bovine myostatin gene on chromosome 2 on birth and carcass traits have been previously assessed. The objective of this study was to identify additional quantitative trait loci (QTL) for economically important traits in two families segregating an inactive copy of myostatin. Two half-sib families were developed from Belgian Blue x MARC III (n = 246) and Piedmontese x Angus (n = 209) sires. Traits analyzed were birth (kg) and yearling weight (kg); hot carcass weight (kg); fat depth (cm); marbling score; longissimus muscle area (cm2); estimated kidney, pelvic, and heart fat (%); USDA yield grade; retail product yield (%); fat yield (%); and wholesale rib-fat yield (%). Meat tenderness was measured as Warner-Bratzler shear force at 3 and 14 d postmortem. The effect of myostatin on these traits was removed by using phase information obtained from the previous study with six microsatellite markers flanking the locus. Selective genotyping was done on 92 animals from both families to identify genomic regions potentially associated with retail product yield and fat depth, using a total of 150 informative markers in each family. Regions in which selective genotyping indicated the presence of QTL were evaluated further by genotyping the entire population and additional markers. For the family with Belgian Blue inheritance (n = 246), a significant QTL for birth and yearling weight was identified on chromosome 6. Suggestive QTL were identified for longissimus muscle area and hot carcass weight on chromosome 6 and for marbling on chromosomes 17 and 27. For the family with Piedmontese inheritance (n = 209), suggestive QTL on chromosome 5 were identified for fat depth, retail product yield, and USDA yield grade and on chromosome 29 for Warner-Bratzler shear force at 3 and 14 d postmortem. Interactions suggesting the presence of QTL were observed between myostatin and chromosome 5 for Warner-Bratzler shear force at 14 d postmortem and between myostatin and chromosome 14 for fat depth. Thus, in families segregating an inactive copy of myostatin in cattle, other loci influencing quantitative traits can be detected. These results are the initial effort to identify and characterize QTL affecting carcass and growth traits in families segregating myostatin.

Alleles↗

PubMed2006

Identification of quantitative trait loci for ABA sensitivity at seed germination and seedling stages in rice.

Abscisic acid (ABA) is one of the important plant hormones, which plays a critical role in seed development and adaptation to abiotic stresses. The sensitivity of rice (Oryza sativa L.) to exogenous ABA at seed germination and seedling stages was investigated in the recombinant inbred line (RIL) population derived from a cross between irrigated rice Zhenshan 97 and upland rice IRAT109, using relative germination vigor (RGV), relative germination rate (RGR) and leaf rolling scores of spraying (LRS) or culturing (LRC) with ABA as sensitivity indexes. The phenotypic correlation analysis revealed that only RGV at germination stage was positively correlated to ABA sensitivity at seedling stage. QTL detection using composite interval mapping (CIM) and mixed linear model was conducted to dissect the genetic basis of ABA sensitivity, and the single-locus QTLs detected by both methods are in good agreement with each other. Five single QTLs and six pairs of epistatic QTLs were detected for ABA sensitivity at germination stage. Eight single QTLs and five pairs of epistatic QTLs were detected for ABA sensitivity at seedling stage. Two QTLs were common between LRS and LRC; and one common QTL was detected for RGV, LRS and LRC simultaneously. These results indicated that both single and epistatic loci were involved in the ABA sensitivity in rice, and the genetic basis of ABA sensitivity at seed germination and seedling stage was largely different.

Abscisic Acid↗

PubMed1997

A two-stage half-sib design for mapping quantitative trait loci in food animals.

Daughter and granddaughter half-sib designs for mapping quantitative trait loci were modified to increase experimental power. This new design includes a two-stage procedure, in contrast to conventional one-step half-sib designs. In stage 1, a few progeny of each sire are genotyped for marker loci. Based on the analyses of stage 1 data, some sires are chosen to continue genotyping more progeny for stage 2. When multiple chromosomes are under investigation, chromosomes and sires for stage 2 are selected based on the analysis of stage 1 data. Sire selection results in increased frequency of heterozygous genotypes of interest in stage 2 if the markers are linked to those genes. Chromosome selection can increase the proportion of chromosomes with segregating quantitative trait loci in stage 2 if not all of the chromosomes evaluated in stage 1 have segregating quantitative trait loci. Numerical results indicated that two-stage half-sib designs are generally more powerful than conventional designs when 1) the noncentrality parameter is moderate or larger, 2) larger quantitative trait loci are mapped using tightly linked markers in larger families, and 3) variation is large in numbers and sizes of segregating quantitative trait loci among the chromosomes evaluated in stage 1.

Animals↗

PubMed1999

Multiple-trait quantitative trait loci analysis using a large mouse sibship.

Quantitative trait loci influencing several phenotypes were assessed using a genetically heterogeneous mouse population. The 145 individuals were produced by a cross between (BALB/cJ x C57BL/6J)F1 females and (C3H/HeJ x DBA/2J)F1 males. The population is genetically equivalent to full siblings derived from heterozygous parents, with known linkage phase. Each individual in the population represents a unique combination of alleles from the inbred grandparents. Quantitative phenotypes for eight T cell measures were obtained at 8 and 18 mo of age. Single-marker locus, repeated measures analysis of variance identified nine marker-phenotype associations with an experimentwise significance level of P < 0.05. Six of the eight quantitative phenotypes could be associated with at least one locus having experiment-wide significance. Composite interval, repeated measures analysis of variance identified 13 chromosomal regions with comparisonwise (nominal) significance associations of P < 0.001. The heterozygous-parent cross provides a reproducible, general method for identification of loci associated with quantitative trait phenotypes or repeated phenotypic measures.

Animals↗

PubMed2001

Concordance of murine quantitative trait loci for salt-induced hypertension with rat and human loci.

To investigate the genetic control of salt-induced hypertension, we performed a quantitative trait locus analysis on male mice from a reciprocal backcross between the salt-sensitive C57BL/6J and the normotensive A/J inbred mouse strains after they were provided with water containing 1% salt for 2 weeks. Genome-wide scans performed on these mice and analyzed with a combination of conventional marker-based regressions and a novel simultaneous search for pairs revealed six significant quantitative trait loci associated with salt-induced blood pressure, two of which were interacting loci. These six loci, named Bpq1-6 for blood pressure quantitative trait loci, mapped to D1Mit334, D1Mit14, D4Mit164, D5Mit31, D6Mit15, and D15Mit13. Furthermore, five of these six loci were concordant with hypertension loci in rats, and four were concordant with hypertension loci in humans, suggesting that quantitative trait loci mapping in model organisms can be used to guide the search for human blood pressure genes.

Analysis of Variance↗

PubMedDate not supplied

Quantitative trait loci influencing honeybee alarm pheromone levels.

Quantitative trait loci (QTL) mapping procedures were used to identify loci that influence the levels of alarm pheromones found in the stinging apparatus of worker honeybees. An F1 queen was produced from a cross between a queen of European origin and a drone descended from an African subspecies. Haploid drones from the hybrid queen were individually backcrossed to European queens to produce 172 colonies. Samples of stings were taken from backcross workers of these colonies. Alarm pheromone levels were determined by gas chromatography. RAPD markers were scored from the haploid drone fathers of these colonies. The multiple-QTL model (MQM) of MapQTL was used to identify QTLs that influence the levels of four alarm pheromone components. Seven independent, potential QTLs were identified with LOD scores greater than two, and one at LOD 1.88. We identified one QTL for n-decyl acetate, three for n-octanol, four for isopentyl acetate, and one for hexyl acetate. One region of linkage group XI shows a strong influence on body size and the levels of three alarm pheromone components. This locus explained 40% of the variance for the amount of n-decyl acetate (LOD 6.57). In general, the QTLs influencing alarm pheromone levels were independent of previously identified loci that influenced the stinging behavior of these colonies. The only exception was a potential locus influencing levels of n-octanol, which was inversely correlated with stinging behavior.

1-Octanol↗